ALBERT

Description: Time–frequency packing (TFP) transmission provides the highest achievable spectral efficiency with a constrained symbol alphabet and detector complexity. In this paper, the application of the TFP technique to fiber-optic systems is investigated and experimentally demonstrated. The main theoretical aspects, design guidelines, and implementation issues are discussed, focusing on those aspects which are peculiar to TFP systems. In particular, adaptive compensation of propagation impairments, matched filtering, and maximum a posteriori probability detection are obtained by a combination of a two-dimensional equalizer and four eight-state parallel Bahl–Cocke–Jelinek–Raviv (BCJR) detectors. A novel algorithm that ensures adaptive equalization, channel estimation, and a proper distribution of tasks between the equalizer and BCJR detectors is proposed. A set of irregular low-density parity-check codes with different rates is designed to operate at low error rates and approach the spectral efficiency limit achievable by TFP at different signal-to-noise ratios. An experimental demonstration of the designed system is finally provided with five dual-polarization QPSK-modulated optical carriers, densely packed in a 100-GHz bandwidth, employing a recirculating loop to test the performance of the system at different transmission distances.

Description: We investigated nonlinear optical characteristics of Tungsten disulfide (WS 2 ) films and experimentally demonstrated their high potential for application as nonlinear saturable absorbers in passively mode-locked fiber lasers. Side polished fiber (SPF) was fabricated and WS 2 film was overlaid to provide an efficient evanescent field interaction. The WS 2 film was prepared using two methods: liquid phase exfoliation to form few-layer nano-sheets, and chemical vapor deposition (CVD) to grow uniform multilayer WS 2 on a SiO 2 substrate. Two SPF saturable absorbers were prepared by either spin coating WS 2 solution or lifting off the multilayer CVD WS 2 on SPF. An all-fiber ring cavity was built and the WS 2 film overlaid on SPF was employed as a mode locker along with Er-doped fiber as a gain medium. Using the spin-coated WS 2 SPF, stable soliton-like pulses were generated with a spectral width of 5.6 nm and 467 fs pulse duration. The fiber laser cavity containing CVD WS2 SPF generated a transform-limited soliton pulse train with a spectral width of 8.23 nm and a pulse duration of 332 fs. Our study confirmed a high potential of WS 2 film as a novel 2-D nonlinear optical material for laser applications.

Description: We propose and experimentally demonstrate an on-chip all-optical differential-equation solver capable of solving second-order ordinary differential equations (ODEs) characterizing continuous-time linear time-invariant systems. The photonic device is implemented by a self-coupled microresonator on a silicon-on-insulator platform with mutual coupling between the cavity modes. Owing to the mutual mode coupling within the same resonant cavity, the resonance wavelengths induced by different cavity modes are self-aligned, thus avoiding precise wavelength alignment and unequal thermal wavelength drifts as in the case of cascaded resonators. By changing the mutual mode coupling strength, the proposed device can be used to solve second-order ODEs with tunable coefficients. System demonstration using the fabricated device is carried out for 10-Gb/s optical Gaussian and super-Gaussian input pulses. The experimental results are in good agreement with theoretical predictions of the solutions, which verify the feasibility of the fabricated device as a tunable second-order photonic ODE solver.

Description: We demonstrate a 100 Gb/s short reach system using a multicarrier transmitter based on a gain switched monolithically integrated laser. An optical comb source with 12.5-GHz free spectral range is achieved by gain-switching an integrated passive feedback laser. The 100 Gb/s wavelength division multiplexed, single sideband, direct detection, orthogonal frequency division multiplexed (WDM-SSB-DD-OFDM) system operates over 25 km standard single mode fiber exhibiting a spectral efficiency of 1.8 b/s/Hz. Receiver sensitivity of –14.2 dBm is achieved after 25 km transmission. Performance optimization with phase and amplitude precompensation is employed to improve the SSB OFDM modulation thereby reducing the interchannel interference and overcoming the power fading induced by the optical filter. We also present a theoretical analysis of the SSB-OFDM modulation.

Description: In this paper, narrow-band emission lines are generated by means of two random distributed feedback fiber laser schemes. Spectral line-widths as narrow as 3.2 pm have been measured, which significantly improves previous reported results. The laser is analyzed with the aim of obtaining a spectral line-width as narrow as possible. Additionally a variation of this setup for multi-wavelength operation is also validated. Both schemes present a simple topology that use a combination of phase-shifted fiber Bragg gratings and regular fiber Bragg gratings as filtering elements.

Description: We report on the fabrication and characterization of 19-cell hypocycloid-shape Kagome fibers with core size larger than 100 μm. These inhibited coupling fibers present low propagation loss (100 dB/km) over broad transmission range with low chromatic dispersion combined with ultra-low power overlap with silica surround, making them an efficient solution for ultra-high power laser handling, ultra-fast laser delivery, and plasma photonics applications.

Description: The iterative demodulation and decoding algorithm introduced in 2005 by Colavolpe, Barbieri, and Caire to cope with channels affected by phase noise needs pilot symbols to bootstrap. However, pilot symbols reduce the spectral efficiency of the system and, consequently, system's throughput. The aim of this paper is to show that trellis-based demodulation can be used to bootstrap the iterative process without the need of pilot symbols. Also, the complexity issue of trellis-based demodulation is addressed in this paper. The result is that the performance of iterative demodulation and decoding after the iterations is virtually unaffected by complexity reduction, provided that the reduced-complexity demodulator guarantees cycle-slip-free operation. From the numerical results presented in this paper, we show that cycle-slip-free operation can be achieved with substantial complexity reduction also for phase noise associated with linewidths of practical interest.

Description: The optical pulse evolution in a highly nonlinear normal dispersion-increasing fiber has been considered, both experimentally and theoretically. It was found that large spectral broadening in tapered waveguides could occur without temporal instabilities and impose the linear frequency modulation, i.e., chirp, required for high-quality pulse compression. The pedestal-free pulses have been demonstrated after dechirping in a standard single-mode fiber.

Description: This work proposes a novel localized surface plasmon resonance (LSPR) biochemical sensor featuring high sensitivity and a high resolution. The sensor was divided into two subcomponents according to their distinct functions; namely, single-mode fiber and metal array. Single-mode fibers located on the left and right sides of the sensors function as the input and output for optical fiber signals. A metal array comprising an arrangement of cylindrical nanometal particles served as the detection area of the sensor. To effectively reduce the memory capacity and calculation time, two innovative techniques (i.e., object meshing and boundary meshing) were integrated with the finite element method. With the area of the triangular elements used as a basis, the object boundary, small object, medium object, and large objects were meshed at a ratio of 1:8:160:1600. The improved numerical simulation methods and six design procedures were adopted to develop and analyze the proposed LSPR biochemical sensor. The results show that the novel LSPR biochemical sensor outperformed two current high-performance biochemical sensors and provided additional advantages such as short length (approximately 430 μm), high resolution (approximately –120 dB), and high sensitivity (approximately 127 604 nm/RIU).

Description: We propose an ultra-broadband super light absorber by integrating different-sized tapered hyperbolic metamaterial (HMM) waveguides, each of which has a different and wide absorption band due to broadband slow-light response, into a unit cell. We numerically demonstrate that such an absorber is superior to a single-sized HMM absorber in terms of absorption bandwidth, while maintaining a comparable absorption efficiency. A three different-sized HMM absorber presents the capability of working with an ultra-wide frequency band ranging from 1 to 30 THz, which is much larger than previously proposed absorbers working in the same spectral region. Such a design shows great promise for a broad range of applications such as thermal emitters, photovoltaics, optical-chemical energy harvesting, and stealth technology, where ultra-wideband absorption is in very high demand.

Description: This paper proposes a ring-based integrated wireless optical network architecture and an associated protocol that involves Ethernet passive optical network (EPON) and long term evolution (LTE) wireless network. The architecture along with the proposed protocol is instrumental toward the reduction of handover delay. The proposed ring-based EPON architecture facilitates the implementation of the X2 interface for LTE network by enabling the optical network units of the EPON backhaul to directly communicate with each other. The work further discusses about an open access network architecture where a single EPON can be used by multiple mobile service providers without compromising information security. Extensive simulations have been carried out to evaluate the performance of the proposed network. An analytical model has been introduced to calculate the queuing delay experienced by the X2 interface. The model has been validated with the simulations results.

Description: High spectrum efficiency and fast restoration speed are highly desired for survivable elastic optical networks (EONs). In this paper, we take the advantages of failure-independent path-protecting preconfigured cycles (FIPP p -cycles) and investigate how to realize spectrum efficient resilience design with them. We first study the problem of offline service provisioning with FIPP p -cycles. We formulate an integer linear programming model and prove that the problem is $mathcal{NP}$ hard. Then, several time-efficient heuristics are designed for FIPP p -cycle formulation and related routing, modulation format, and spectrum assignment. Extensive simulations on offline provisioning verify that the heuristics can obtain near-optimal solutions. Next, we consider online service provisioning with FIPP p -cycles in dynamic EONs. In order to overcome the decrease of protection efficiency during dynamic network operation, we propose a p -cycle reconfiguration scheme to reoptimize protection structures on-the-fly. Simulation results demonstrate that the proposed algorithms can improve spectrum efficiency and reduce bandwidth blocking probability simultaneously.

Description: Photo-thermo-refractive (PTR) glasses are the class of polyfunctional materials that combine the properties of several monofunctional materials such as photo-refractive, laser, luminescent, and plasmonic ones. Based on PTR glasses, various diffractive holographic elements and photonic devices were developed in both the volume and fiber versions. In this paper, the fabrication of optical planar waveguides on PTR glass by low-temperature ion exchange is reported for the first time. Planar waveguides were fabricated through substituting the sodium ions in glass by silver, potassium, rubidium, and cesium ones from the nitrate melts. The silver waveguides were shown to have the largest depth (27 μm) and reveal no birefringence. For the silver waveguides, an increase in the refractive index is caused by differences in the polarizabilities of cations exchanged. The maximum increment of the refractive index was observed in the cesium waveguides (0.0512). An increase in the refractive index and also appearing the birefringence in potassium, rubidium, and cesium waveguides are found to be due to the compressive mechanical stresses and their relaxation. The potentialities of the ion exchange technology for fabricating, in PTR glasses, planar gradient waveguides with low losses (0.5 dB/cm) are demonstrated, the potentialities extending the application field of PTR glasses in photonics.

Description: A navigation algorithm is proposed to increase the inertial navigation performance of a ground vehicle using magnetic measurements and dynamic constraints. The navigation solutions are estimated based on inertial measurements such as acceleration and angular velocity measurements. To improve the inertial navigation performance, a three-axis magnetometer is used to provide the heading angle, and nonholonomic constraints (NHCs) are introduced to increase the correlation between the velocity and the attitude equation. The NHCs provide a velocity feedback to the attitude, which makes the navigation solution more robust. Additionally, an acceleration-based roll and pitch estimation is applied to decrease the drift when the acceleration is within certain boundaries. The magnetometer and NHCs are combined with an extended Kalman filter. An experimental test was conducted to verify the proposed method, and a comprehensive analysis of the performance in terms of the position, velocity, and attitude showed that the navigation performance could be improved by using the magnetometer and NHCs. Moreover, the proposed method could improve the estimation performance for the position, velocity, and attitude without any additional hardware except an inertial sensor and magnetometer. Therefore, this method would be effective for ground vehicles, indoor navigation, mobile robots, vehicle navigation in urban canyons, or navigation in any global navigation satellite system-denied environment.

Description: An ultrasonic technique, invariant to temperature changes, for a density measurement of different liquids under in situ extreme conditions is presented. The influence of geometry and material parameters of the measurement system (transducer, waveguide, matching layer) on measurement accuracy and reliability is analyzed theoretically along with experimental results. The proposed method is based on measurement of the amplitude of the ultrasonic wave, reflected from the interface of the solid/liquid medium under investigation. In order to enhance sensitivity, the use of a quarter wavelength acoustic matching layer is proposed. Therefore, the sensitivity of the measurement system increases significantly. Density measurements quite often must be performed in extreme conditions at high temperature (up to 220 °C) and high pressure. In this case, metal waveguides between piezoelectric transducer and the measured liquid are used in order to protect the conventional transducer from the influence of high temperature and to avoid depolarization. The presented ultrasonic density measurement technique is suitable for density measurement in different materials, including liquids and polymer melts in extreme conditions. A new calibration algorithm was proposed. The metrological evaluation of the measurement method was performed. The expanded measurement uncertainty Uρ = 7.4 × 10−3 g/cm3 (1%).

Description: A multi-sensor addressing method for fiber Bragg grating aided fiber loop ringdown (FBG-FLRD) sensor array is proposed. It is capable of simultaneous measurement of temperature and force. Light from a wavelength-swept fiber laser (WSFL) is modulated into pulsed light to illuminate FBG-FLRD sensor array. Based on the time sequence of pulsed lights reflected by fiber Bragg grating array, each FBG-FLRD sensor can be distinguished. The time interval between the trigger signal of the WSFL and the pulsed light reflected by FBG offers temperature variation information. By measuring the ringdown time of each FBG-FLRD, the loss of fiber ring induced by temperature and force can be obtained. And then simultaneous measurement can be implemented in real time. To prove the validity of the proposed system, a six elements array is experimentally validated with interrogation frequency of 27.5 Hz.

Description: In recent years, IoT (Internet of Things) technologies have seen great advances, particularly, the IPv6 Routing Protocol for Low-power and Lossy Networks (RPL), which provides a powerful and flexible routing framework that can be applied in a variety of application scenarios. In this context, as an important role of IoT, Wireless Sensor Networks (WSNs) can utilize RPL to design efficient routing protocols for a specific application to increase the ubiquity of networks with resource-constrained WSN nodes that are low-cost and easy to deploy. In this article, our work starts with the description of Agricultural Low-power and Lossy Networks (A-LLNs) complying with the LLN framework, and to clarify the requirements of this application-oriented routing solution. After a brief review of existing optimization techniques for RPL, our contribution is dedicated to a Scalable Context-Aware Objective Function (SCAOF) that can adapt RPL to the environmental monitoring of A-LLNs, through combining energy-aware, reliability-aware, robustness-aware and resource-aware contexts according to the composite routing metrics approach. The correct behavior of this enhanced RPL version (RPAL) was verified by performance evaluations on both simulation and field tests. The obtained experimental results confirm that SCAOF can deliver the desired advantages on network lifetime extension, and high reliability and efficiency in different simulation scenarios and hardware testbeds.

Description: The aim of this randomized clinical trial was to evaluate whether a recently described multi-sensor approach called BIONOTE® is accurate enough to verify the efficacy of treatment of patients with halitosis. A treatment with Lactobacillus brevis (CD2)–containing lozenges, compared with placebo was tested. The BIONOTE® was compared with traditional techniques used to detect halitosis: OralChroma™ and two calibrated odor judges enrolled for the organoleptic assessments. Twenty patients (10 treated and 10 placebo), suffering from active phase halitosis were included in the study. Treatment consisted of Lactobacillus brevis (CD2)—containing lozenges or placebo, 4 tablets/day for 14 days. t0 was before the beginning of the study; t1 was day 7 and t2 was day 14. The effectiveness of treatment was assessed through: (1) Rosenberg score; (2) Winkel tongue coating index (WTCI) anterior and posterior; (2) OralChroma™; (3) the new developed multi-sensor approach, called BIONOTE® (test technique). Only the WTCI anterior revealed statistically significant changes between t0 and t2 data (p = 0.014) in the treated group. Except for the WTCI anterior, all diagnostic methods revealed the lack of effectiveness for halitosis of a 14-days treatment with Lactobacillus brevis (CD2)–containing lozenges. The BIONOTE® multisensor system seems accurate in addition to OralChroma™ to assess the initial condition of halitosis and its mitigation during treatment.

Description: This paper presents a multipurpose and low cost sensor for the simultaneous monitoring of temperature and ullage of wine in barrels in two of the most important stages of winemaking, that being fermentation and maturation. The distributed sensor subsystem is imbedded within the bung of the barrel and runs on battery for a period of at least 12 months and costs around $27 AUD for all parts. In addition, software was designed which allows for the remote transmission and easy visual interpretation of the data for the winemaker. Early warning signals can be sent when the temperature or ullage deviates from a winemakers expectations so remedial action can be taken, such as when topping is required or the movement of the barrels to a cooler cellar location. Such knowledge of a wine’s properties or storage conditions allows for a more precise control of the final wine quality.

Description: Diffuse Correlation Spectroscopy (DCS) is a well-established optical technique that has been used for non-invasive measurement of blood flow in tissues. Instrumentation for DCS includes a correlation device that computes the temporal intensity autocorrelation of a coherent laser source after it has undergone diffuse scattering through a turbid medium. Typically, the signal acquisition and its autocorrelation are performed by a correlation board. These boards have dedicated hardware to acquire and compute intensity autocorrelations of rapidly varying input signal and usually are quite expensive. Here we show that a Raspberry Pi minicomputer can acquire and store a rapidly varying time-signal with high fidelity. We show that this signal collected by a Raspberry Pi device can be processed numerically to yield intensity autocorrelations well suited for DCS applications. DCS measurements made using the Raspberry Pi device were compared to those acquired using a commercial hardware autocorrelation board to investigate the stability, performance, and accuracy of the data acquired in controlled experiments. This paper represents a first step toward lowering the instrumentation cost of a DCS system and may offer the potential to make DCS become more widely used in biomedical applications.

Description: Wind tunnels are a key experimental tool for the analysis of airflow parameters in many fields of application. Despite their great potential impact on agricultural research, few contributions have dealt with the development of automatic control systems for wind tunnels in the field of greenhouse technology. The objective of this paper is to present an automatic control system that provides precision and speed of measurement, as well as efficient data processing in low-speed wind tunnel experiments for greenhouse engineering applications. The system is based on an algorithm that identifies the system model and calculates the optimum PI controller. The validation of the system was performed on a cellulose evaporative cooling pad and on insect-proof screens to assess its response to perturbations. The control system provided an accuracy of 〈0.06 m·s‾1 for airflow speed and 〈0.50 Pa for pressure drop, thus permitting the reproducibility and standardization of the tests. The proposed control system also incorporates a fully-integrated software unit that manages the tests in terms of airflow speed and pressure drop set points.

Description: A new application of utilizing ultra-wideband (UWB) technology to sense wind turbine blade deflections is introduced in this paper for wind energy cost reduction. The lower UWB band of 3.1–5.3 GHz is applied. On each blade, there will be one UWB blade deflection sensing system, which consists of two UWB antennas at the blade root and one UWB antenna at the blade tip. The detailed topology and challenges of this deflection sensing system are addressed. Due to the complexity of the problem, this paper will first realize the on-blade UWB radio link in the simplest case, where the tip antenna is situated outside (and on the surface of) a blade tip. To investigate this case, full-blade time-domain measurements are designed and conducted under different deflections. The detailed measurement setups and results are provided. If the root and tip antenna locations are properly selected, the first pulse is always of sufficient quality for accurate estimations under different deflections. The measured results reveal that the blade tip-root distance and blade deflection can be accurately estimated in the complicated and lossy wireless channels around a wind turbine blade. Some future research topics on this application are listed finally.

Description: A method for measuring shaft diameters is presented using structured light vision measurement. After calibrating a model of the structured light measurement, a virtual plane is established perpendicular to the measured shaft axis and the image of the light stripe on the shaft is projected to the virtual plane. On the virtual plane, the center of the measured shaft is determined by fitting the projected image under the geometrical constraints of the light stripe, and the shaft diameter is measured by the determined center and the projected image. Experiments evaluated the measuring accuracy of the method and the effects of some factors on the measurement are analyzed.

Description: Reliable data transmission over lossy communication link is expensive due to overheads for error protection. For signals that have inherent sparse structures, compressive sensing (CS) is applied to facilitate efficient sparse signal transmissions over lossy communication links without data compression or error protection. The natural packet loss in the lossy link is modeled as a random sampling process of the transmitted data, and the original signal will be reconstructed from the lossy transmission results using the CS-based reconstruction method at the receiving end. The impacts of packet lengths on transmission efficiency under different channel conditions have been discussed, and interleaving is incorporated to mitigate the impact of burst data loss. Extensive simulations and experiments have been conducted and compared to the traditional automatic repeat request (ARQ) interpolation technique, and very favorable results have been observed in terms of both accuracy of the reconstructed signals and the transmission energy consumption. Furthermore, the packet length effect provides useful insights for using compressed sensing for efficient sparse signal transmission via lossy links.

Description: In recent years, wireless sensor network (WSN) applications have tended to transmit data hop by hop, from sensor nodes through cluster nodes to the base station. As a result, users must collect data from the base station. This study considers two different applications: hop by hop transmission of data from cluster nodes to the base station and the direct access to cluster nodes data by mobile users via mobile devices. Due to the hardware limitations of WSNs, some low-cost operations such as symmetric cryptographic algorithms and hash functions are used to implement a dynamic key management. The session key can be updated to prevent threats of attack from each communication. With these methods, the data gathered in wireless sensor networks can be more securely communicated. Moreover, the proposed scheme is analyzed and compared with related schemes. In addition, an NS2 simulation is developed in which the experimental results show that the designed communication protocol is workable.

Description: The Mecanum automated guided vehicle (AGV), which can move in any direction by using a special wheel structure with a LIM-wheel and a diagonally positioned roller, holds considerable promise for the field of industrial electronics. A conventional method for Mecanum AGV localization has certain limitations, such as slip phenomena, because there are variations in the surface of the road and ground friction. Therefore, precise localization is a very important issue for the inevitable slip phenomenon situation. So a sensor fusion technique is developed to cope with this drawback by using the Kalman filter. ENCODER and StarGazer were used for sensor fusion. StarGazer is a position sensor for an image recognition device and always generates some errors due to the limitations of the image recognition device. ENCODER has also errors accumulating over time. On the other hand, there are no moving errors. In this study, we developed a Mecanum AGV prototype system and showed by simulation that we can eliminate the disadvantages of each sensor. We obtained the precise localization of the Mecanum AGV in a slip phenomenon situation via sensor fusion using a Kalman filter.

Description: Wireless sensor networks are vulnerable to sensor worm attacks in which the attacker compromises a few nodes and makes these compromised nodes initiate worm spread over the network, targeting the worm infection of the whole nodes in the network. Several defense mechanisms have been proposed to prevent worm propagation in wireless sensor networks. Although these proposed schemes use software diversity technique for worm propagation prevention under the belief that different software versions do not have common vulnerability, they have fundamental drawback in which it is difficult to realize the aforementioned belief in sensor motes. To resolve this problem, we propose on-demand software-attestation based scheme to defend against worm propagation in sensor network. The main idea of our proposed scheme is to perform software attestations against sensor nodes in on-demand manner and detect the infected nodes by worm, resulting in worm propagation block in the network. Through analysis, we show that our proposed scheme defends against worm propagation in efficient and robust manner. Through simulation, we demonstrate that our proposed scheme stops worm propagation at the reasonable overhead while preventing a majority of sensor nodes from being infected by worm.

Description: The sensor is quite easily attacked or invaded during the process of the node coverage optimization. It is a great challenge to make sure that the wireless sensor network could still carry out a secure communication and reliable coverage under the condition of being attacked. Therefore, this paper proposes a network coverage method for intrusion tolerance based on trust value of nodes by combining the trust value model with the reliable coverage optimization. It first estimates trust value of nodes through which to regulate the perception radius and decision-making radius. Furthermore, this algorithm also combines the classical methods of wireless network coverage, such as GSO and PSO, to realize the networks coverage of invasive tolerant sensor. After comparing with the conventional single cover mechanism, it can improve the security and coverage rate of network under the condition of invasion. The simulation results verify the effectiveness of the algorithm.

Description: We propose using multiple observed features of network traffic to identify new high-distributed low-rate quality of services (QoS) violation so that detection accuracy may be further improved. For the multiple observed features, we choose F feature in TCP packet header as a microscopic feature and, P feature and D feature of network traffic as macroscopic features. Based on these features, we establish multistream fused hidden Markov model (MF-HMM) to detect stealthy low-rate denial of service (LDoS) attacks hidden in legitimate network background traffic. In addition, the threshold value is dynamically adjusted by using Kaufman algorithm. Our experiments show that the additive effect of combining multiple features effectively reduces the false-positive rate. The average detection rate of MF-HMM results in a significant 23.39% and 44.64% improvement over typical power spectrum density (PSD) algorithm and nonparametric cumulative sum (CUSUM) algorithm.

Description: Wireless sensor network (WSN) is a kind of distributed and self-organizing networks, in which the sensor nodes have limited communication bandwidth, memory, and limited energy. The topology construction of this network is usually vulnerable when attacked by malicious nodes. Besides, excessive energy consumption is a problem that can not be ignored. Therefore, this paper proposes a secure topology protocol of WSN which is trust-aware and of low energy consumption, called TLES. The TLES considers the trust value as an important factor affecting the behavior of node. In detail, the TLES would take trust value, residual energy of the nodes, and node density into consideration when selecting cluster head nodes. Then, TLES constructs these cluster head nodes by choosing the next hop node according to distance to base station (BS), nodes’ degrees, and residual energy, so as to establish a safe, reliable, and energy saving network. Experimental results show that the algorithm can effectively isolate the malicious node in the network and reduce the consumption of energy of the whole network.

Description: In wireless sensor network (WSN), the sensors are deployed and placed uniformly to transmit the sensed data to a centralized station periodically. So, the major threat of the WSN network layer is sinkhole attack and it is still being a challenging issue on the sensor networks, where the malicious node attracts the packets from the other normal sensor nodes and drops the packets. Thus, this paper proposes an Intrusion Detection System (IDS) mechanism to detect the intruder in the network which uses Low Energy Adaptive Clustering Hierarchy (LEACH) protocol for its routing operation. In the proposed algorithm, the detection metrics, such as number of packets transmitted and received, are used to compute the intrusion ratio (IR) by the IDS agent. The computed numeric or nonnumeric value represents the normal or malicious activity. As and when the sinkhole attack is captured, the IDS agent alerts the network to stop the data transmission. Thus, it can be a resilient to the vulnerable attack of sinkhole. Above all, the simulation result is shown for the proposed algorithm which is proven to be efficient compared with the existing work, namely, MS-LEACH, in terms of minimum computational complexity and low energy consumption. Moreover, the algorithm was numerically analyzed using TETCOS NETSIM.

Description: The Internet of Things (IoT) emphasizes on connecting every object around us by leveraging a variety of wireless communication technologies. Heterogeneous data fusion is widely considered to be a promising and urgent challenge in the data processing of the IoT. In this study, we first discuss the development of the concept of the IoT and give a detailed description of the architecture of the IoT. And then we design a middleware platform based on service-oriented architecture (SOA) for integration of multisource heterogeneous information. New research angle regarding flexible heterogeneous information fusion architecture for the IoT is the theme of this paper. Experiments using environmental monitoring sensor data derived from indoor environment are performed for system validation. Through the theoretical analysis and experimental verification, the data processing middleware architecture represents better adaptation to multisensor and multistream application scenarios in the IoT, which improves heterogeneous data utilization value. The data processing middleware based on SOA for the IoT establishes a solid foundation of integration and interaction for diverse networks data among heterogeneous systems in the future, which simplifies the complexity of integration process and improves reusability of components in the system.

Description: This paper proposes a resonant electric cradle design with infant cries recognition, employing an Arduino UNO as the core processor. For most commercially available electric cradles, the drive motor is closely combined with the bearing on the top, resulting in a lot of energy consumption. In this proposal, a ball bearing design was adopted and the driving force is under the cradle to increase the distance from the object to fulcrum and torque. The sensors are designed to detect the oscillation state, and then the force is driven at the critical time to achieve the maximum output response while saving energy according to the principle of resonance. As for the driving forces, the winding power and motors are carefully placed under the cradle. The sensors, including the three-axis accelerometer and infrared sensor, are tested and applied under swinging amplitude control. In addition, infant cry recognition technology was incorporated in the design to further develop its functionality, which is a rare feature in this kind of hardware. The proposed nonlinear operator of fundamental frequency ( ) analysis is able to identify different types of infant cries. In conclusion, this paper proposes an energy-saving electric cradle with infant cries recognition and the experimental results demonstrate the effectiveness of this approach.

Description: Many people find that their sleep is restricted or disturbed by social obligations, including work. Sleep phase delays can affect an individual’s circadian rhythms on the following day and cause daytime sleepiness and/or poor performance. In this study, to examine weekly variations in sleep patterns, we analyzed sleep data for seven-day periods (from Sunday to Saturday) that had been collected from 2914 subjects (aged 20–79 years) over a total of 24,899 subject-weeks using contactless biomotion sensors. On the weekend, the subjects’ mean sleep midpoint, bedtime, and wake-up time were delayed by 40, 26 and 53 min, respectively, compared with those seen on weekdays. In addition, on weekdays, the mean difference between the maximum and median sleep midpoint ranged from 35 to 47 min among the subjects in their 20 s–70 s. The weekend delay and weekday variation in the subjects’ sleep patterns tended to decrease with age. This study detected sleep pattern disturbances on both weekdays and weekends. The serial changes in weekday bedtimes detected in this study suggest that sleep habits are influenced by changes in the temporal patterns of social activities/duties. We need further study the advantages of getting extra sleep and the disadvantages of sleep pattern disturbances in daily lifestyle.

Description: An appropriate network model and some suitable performance evaluation criterions including handoff delay and mobility management cost were proposed in this paper. And in this base the performance of Mobile IP protocol and various micromobility protocols was comprehensively compared and investigated. The research results show that the performance is mainly influenced by two factors which are route update methods of mobility support protocols and mobile network parameters. The route update time and mobility management cost of micromobility protocol are obviously shorter than that of Mobile IP. In all researched micromobility protocols, the route update method of Mobile IP Regional Registration protocol has the optimal performance.

Description: Atomic force microscope with applicable types of operation in a liquid environment is widely used to scan the contours of biological specimens. The contact mode of operation allows a tip to touch a specimen directly but sometimes it damages the specimen; thus, a tapping mode of operation may replace the contact mode. The tapping mode triggers the cantilever of the microscope approximately at resonance frequencies, and so the tip periodically knocks the specimen. It is well known that the cantilever induces extra liquid pressure that leads to drift in the resonance frequency. Studies have noted that the heights of protein surfaces measured via the tapping mode of an atomic force microscope are ~25% smaller than those measured by other methods. This discrepancy may be attributable to the induced superficial hydrodynamic pressure, which is worth investigating. In this paper, we introduce a semi-analytical method to analyze the pressure distribution of various tip geometries. According to our analysis, the maximum hydrodynamic pressure on the specimen caused by a cone-shaped tip is ~0.5 Pa, which can, for example, pre-deform a cell by several nanometers in compression before the tip taps it. Moreover, the pressure calculated on the surface of the specimen is 20 times larger than the pressure without considering the tip effect; these results have not been motioned in other papers. Dominating factors, such as surface heights of protein surface, mechanical stiffness of protein increasing with loading velocity, and radius of tip affecting the local pressure of specimen, are also addressed in this study.

Description: This study explores the potential of Synthetic Aperture Radar (SAR) to aid Unmanned Aerial Vehicle (UAV) navigation when Inertial Navigation System (INS) measurements are not accurate enough to eliminate drifts from a planned trajectory. This problem can affect medium-altitude long-endurance (MALE) UAV class, which permits heavy and wide payloads (as required by SAR) and flights for thousands of kilometres accumulating large drifts. The basic idea is to infer position and attitude of an aerial platform by inspecting both amplitude and phase of SAR images acquired onboard. For the amplitude-based approach, the system navigation corrections are obtained by matching the actual coordinates of ground landmarks with those automatically extracted from the SAR image. When the use of SAR amplitude is unfeasible, the phase content can be exploited through SAR interferometry by using a reference Digital Terrain Model (DTM). A feasibility analysis was carried out to derive system requirements by exploring both radiometric and geometric parameters of the acquisition setting. We showed that MALE UAV, specific commercial navigation sensors and SAR systems, typical landmark position accuracy and classes, and available DTMs lead to estimated UAV coordinates with errors bounded within ±12 m, thus making feasible the proposed SAR-based backup system.

Description: This paper demonstrates an automated computer vision system for outdoor tree crop enumeration in a seedling nursery. The complete system incorporates both hardware components (including an embedded microcontroller, an odometry encoder, and an uncalibrated digital color camera) and software algorithms (including microcontroller algorithms and the proposed algorithm for tree crop enumeration) required to obtain robust performance in a natural outdoor environment. The enumeration system uses a three-step image analysis process based upon: (1) an orthographic plant projection method integrating a perspective transform with automatic parameter estimation; (2) a plant counting method based on projection histograms; and (3) a double-counting avoidance method based on a homography transform. Experimental results demonstrate the ability to count large numbers of plants automatically with no human effort. Results show that, for tree seedlings having a height up to 40 cm and a within-row tree spacing of approximately 10 cm, the algorithms successfully estimated the number of plants with an average accuracy of 95.2% for trees within a single image and 98% for counting of the whole plant population in a large sequence of images.

Description: The combination of optical trapping with Raman spectroscopy provides a powerful method for the study, characterization, and identification of biological micro-particles. In essence, optical trapping helps to overcome the limitation imposed by the relative inefficiency of the Raman scattering process. This allows Raman spectroscopy to be applied to individual biological particles in air and in liquid, providing the potential for particle identification with high specificity, longitudinal studies of changes in particle composition, and characterization of the heterogeneity of individual particles in a population. In this review, we introduce the techniques used to integrate Raman spectroscopy with optical trapping in order to study individual biological particles in liquid and air. We then provide an overview of some of the most promising applications of this technique, highlighting the unique types of measurements enabled by the combination of Raman spectroscopy with optical trapping. Finally, we present a brief discussion of future research directions in the field.

Description: In this paper, we propose a novel extrinsic calibration method for camera networks using a sphere as the calibration object. First of all, we propose an easy and accurate method to estimate the 3D positions of the sphere center w.r.t. the local camera coordinate system. Then, we propose to use orthogonal procrustes analysis to pairwise estimate the initial camera relative extrinsic parameters based on the aforementioned estimation of 3D positions. Finally, an optimization routine is applied to jointly refine the extrinsic parameters for all cameras. Compared to existing sphere-based 3D position estimators which need to trace and analyse the outline of the sphere projection in the image, the proposed method requires only very simple image processing: estimating the area and the center of mass of the sphere projection. Our results demonstrate that we can get a more accurate estimate of the extrinsic parameters compared to other sphere-based methods. While existing state-of-the-art calibration methods use point like features and epipolar geometry, the proposed method uses the sphere-based 3D position estimate. This results in simpler computations and a more flexible and accurate calibration method. Experimental results show that the proposed approach is accurate, robust, flexible and easy to use.

Description: This paper presents preliminary polarization measurements and systematic-error characterization of the Thirty Gigahertz Instrument receiver developed for the QUIJOTE experiment. The instrument has been designed to measure the polarization of Cosmic Microwave Background radiation from the sky, obtaining the Q, U, and I Stokes parameters of the incoming signal simultaneously. Two kinds of linearly polarized input signals have been used as excitations in the polarimeter measurement tests in the laboratory; these show consistent results in terms of the Stokes parameters obtained. A measurement-based systematic-error characterization technique has been used in order to determine the possible sources of instrumental errors and to assist in the polarimeter calibration process.

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Description: Provides a listing of the editors, board members, and current staff for this issue of the publication.

Description: In this paper, we propose a distributed data-gathering scheme using an autonomous underwater vehicle (AUV) working as a mobile sink to gather data from a randomly distributed underwater sensor network where sensor nodes are clustered around several cluster headers. Unlike conventional data-gathering schemes where the AUV visits either every node or every cluster header, the proposed scheme allows the AUV to visit some selected nodes named path-nodes in a way that reduces the overall transmission power of the sensor nodes. Monte Carlo simulations are performed to investigate the performance of the proposed scheme compared with several preexisting techniques employing the AUV in terms of total amount of energy consumption, standard deviation of each node’s energy consumption, latency to gather data at a sink, and controlling overhead. Simulation results show that the proposed scheme not only reduces the total energy consumption but also distributes the energy consumption more uniformly over the network, thereby increasing the lifetime of the network.

Description: Capacitive-type transduction is now widely used in MEMS microphones. However, its sensitivity decreases with reducing size, due to decreasing air gap capacitance. In the present study, we proposed and developed the Electret Gate of Field Effect Transistor (ElGoFET) transduction based on an electret and FET (field-effect-transistor) as a novel mechanism of MEMS microphone transduction. The ElGoFET transduction has the advantage that the sensitivity is dependent on the ratio of capacitance components in the transduction structure. Hence, ElGoFET transduction has high sensitivity even with a smaller air gap capacitance, due to a miniaturization of the transducer. A FET with a floating-gate electrode embedded on a membrane was designed and fabricated and an electret was fabricated by ion implantation with Ga+ ions. During the assembly process between the FET and the electret, the operating point of the FET was characterized using the static response of the FET induced by the electric field due to the trapped positive charge at the electret. Additionally, we evaluated the microphone performance of the ElGoFET by measuring the acoustic response in air using a semi-anechoic room. The results confirmed that the proposed transduction mechanism has potential for microphone applications.

Description: Context aware applications, which can adapt their behaviors to changing environments, are attracting more and more attention. To simplify the complexity of developing applications, context aware middleware, which introduces context awareness into the traditional middleware, is highlighted to provide a homogeneous interface involving generic context management solutions. This paper provides a survey of state-of-the-art context aware middleware architectures proposed during the period from 2009 through 2015. First, a preliminary background, such as the principles of context, context awareness, context modelling, and context reasoning, is provided for a comprehensive understanding of context aware middleware. On this basis, an overview of eleven carefully selected middleware architectures is presented and their main features explained. Then, thorough comparisons and analysis of the presented middleware architectures are performed based on technical parameters including architectural style, context abstraction, context reasoning, scalability, fault tolerance, interoperability, service discovery, storage, security & privacy, context awareness level, and cloud-based big data analytics. The analysis shows that there is actually no context aware middleware architecture that complies with all requirements. Finally, challenges are pointed out as open issues for future work.

Description: Few techniques for guaranteeing a network lifetime have been proposed despite its great impact on network management. Moreover, since the existing schemes are mostly dependent on the combination of disparate parameters, they do not provide additional services, such as real-time communications and balanced energy consumption among sensor nodes; thus, the adaptability problems remain unresolved among nodes in wireless sensor networks (WSNs). To solve these problems, we propose a novel fuzzy logic model to provide real-time communication in a guaranteed WSN lifetime. The proposed fuzzy logic controller accepts the input descriptors energy, time and velocity to determine each node’s role for the next duration and the next hop relay node for real-time packets. Through the simulation results, we verified that both the guaranteed network’s lifetime and real-time delivery are efficiently ensured by the new fuzzy logic model. In more detail, the above-mentioned two performance metrics are improved up to 8%, as compared to our previous work, and 14% compared to existing schemes, respectively.

Description: We propose an autonomous self-aware and adaptive fault-tolerant routing technique (ASAART) for wireless sensor networks. We address the limitations of self-healing routing (SHR) and self-selective routing (SSR) techniques for routing sensor data. We also examine the integration of autonomic self-aware and adaptive fault detection and resiliency techniques for route formation and route repair to provide resilience to errors and failures. We achieved this by using a combined continuous and slotted prioritized transmission back-off delay to obtain local and global network state information, as well as multiple random functions for attaining faster routing convergence and reliable route repair despite transient and permanent node failure rates and efficient adaptation to instantaneous network topology changes. The results of simulations based on a comparison of the ASAART with the SHR and SSR protocols for five different simulated scenarios in the presence of transient and permanent node failure rates exhibit a greater resiliency to errors and failure and better routing performance in terms of the number of successfully delivered network packets, end-to-end delay, delivered MAC layer packets, packet error rate, as well as efficient energy conservation in a highly congested, faulty, and scalable sensor network.

Description: The development of public transit systems that are accessible and safe for everyone, including people with special needs, is an objective that is justified from the civic and economic points of view. Unfortunately, public transit services are conceived for people who do not have reduced physical or cognitive abilities. In this paper, we present an intelligent public transit system by highway with the goal of facilitating access and improving the safety of public transit for persons with special needs. The system is deployed using components that are commonly available in transport infrastructure, e.g., sensors, mobile communications systems, and positioning systems. In addition, the system can operate in non-urban transport contexts, e.g., isolated rural areas, where the availability of basic infrastructure, such as electricity and communications infrastructures, is not always guaranteed. To construct the system, the principles and techniques of Ubiquitous Computing and Ambient Intelligence have been employed. To illustrate the utility of the system, two cases of services rendered by the system are described: the first case involves a surveillance system to guarantee accessibility at bus stops; the second case involves a route assistant for blind people.

Description: An accurate performance analysis on the MDL criterion for source enumeration in array processing is presented in this paper. The enumeration results of MDL can be predicted precisely by the proposed procedure via the statistical analysis of the sample eigenvalues, whose distributive properties are investigated with the consideration of their interactions. A novel approach is also developed for the performance evaluation when the source number is underestimated by a number greater than one, which is denoted as “multiple-missed detection”, and the probability of a specific underestimated source number can be estimated by ratio distribution analysis. Simulation results are included to demonstrate the superiority of the presented method over available results and confirm the ability of the proposed approach to perform multiple-missed detection analysis.

Description: As society has developed, the number of vehicles has increased and road conditions have become complicated, increasing the risk of crashes. Therefore, a service that provides safe vehicle control and various types of information to the driver is urgently needed. In this study, we designed and implemented a real-time traffic information system and a smart camera device for smart driver assistance systems. We selected a commercial device for the smart driver assistance systems, and applied a computer vision algorithm to perform image recognition. For application to the dynamic region of interest, dynamic frame skip methods were implemented to perform parallel processing in order to enable real-time operation. In addition, we designed and implemented a model to estimate congestion by analyzing traffic information. The performance of the proposed method was evaluated using images of a real road environment. We found that the processing time improved by 15.4 times when all the proposed methods were applied in the application. Further, we found experimentally that there was little or no change in the recognition accuracy when the proposed method was applied. Using the traffic congestion estimation model, we also found that the average error rate of the proposed model was 5.3%.

Description: Foot pathologies can negatively influence foot function, consequently impairing gait during daily activity, and severely impacting an individual’s quality of life. These pathologies are often painful and correspond with high or abnormal plantar pressure, which can result in asymmetry in the pressure distribution between the two feet. There is currently no general consensus on the presence of asymmetry in able-bodied gait, and plantar pressure analysis during gait is in dire need of a standardized method to quantify asymmetry. This paper investigates the use of plantar pressure asymmetry for pathological gait diagnosis. The results of this study involving plantar pressure analysis in fifty one participants (31 healthy and 20 with foot pathologies) support the presence of plantar pressure asymmetry in normal gait. A higher level of asymmetry was detected at the majority of the regions in the feet of the pathological population, including statistically significant differences in the plantar pressure asymmetry in two regions of the foot, metatarsophalangeal joint 3 (MPJ3) and the lateral heel. Quantification of plantar pressure asymmetry may prove to be useful for the identification and diagnosis of various foot pathologies.

Description: In this paper, we present the development of an infrastructure-less indoor location system (ILS), which relies on the use of a microphone, a magnetometer and a light sensor of a smartphone, all three of which are essentially passive sensors, relying on signals available practically in any building in the world, no matter how developed the region is. In our work, we merge the information from those sensors to estimate the user’s location in an indoor environment. A multivariate model is applied to find the user’s location, and we evaluate the quality of the resulting model in terms of sensitivity and specificity. Our experiments were carried out in an office environment during summer and winter, to take into account changes in light patterns, as well as changes in the Earth’s magnetic field irregularities. The experimental results clearly show the benefits of using the information fusion of multiple sensors when contrasted with the use of a single source of information.

Description: The realization of the Internet of Things greatly depends on the information communication among physical terminal devices and informationalized platforms, such as smart sensors, embedded systems and intelligent networks. Playing an important role in information acquisition, sensors for stereo capture have gained extensive attention in various fields. In this paper, we concentrate on promoting such sensors in an intelligent system with self-assessment capability to deal with the distortion and impairment in long-distance shooting applications. The core design is the establishment of the objective evaluation criteria that can reliably predict shooting quality with different camera configurations. Two types of stereo capture systems—toed-in camera configuration and parallel camera configuration—are taken into consideration respectively. The experimental results show that the proposed evaluation criteria can effectively predict the visual perception of stereo capture quality for long-distance shooting.

Description: Autonomous vehicles require highly reliable navigation capabilities. For example, a lane-following method cannot be applied in an intersection without lanes, and since typical lane detection is performed using a straight-line model, errors can occur when the lateral distance is estimated in curved sections due to a model mismatch. Therefore, this paper proposes a localization method that uses GPS/DR error estimation based on a lane detection method with curved lane models, stop line detection, and curve matching in order to improve the performance during waypoint following procedures. The advantage of using the proposed method is that position information can be provided for autonomous driving through intersections, in sections with sharp curves, and in curved sections following a straight section. The proposed method was applied in autonomous vehicles at an experimental site to evaluate its performance, and the results indicate that the positioning achieved accuracy at the sub-meter level.

Description: A novel sensing device for fire detection in domestic environments is presented. The fire detector uses a combination of several sensors that not only detect smoke, but discriminate between different types of smoke. This feature avoids false alarms and warns of different situations. Power consumption is optimized both in terms of hardware and software, providing a high degree of autonomy of almost five years. Data gathered from the device are transmitted through a wireless communication to a base station. The low cost and compact design provides wide application prospects.

Description: Lipid multilayer gratings are recently invented nanomechanical sensor elements that are capable of transducing molecular binding to fluid lipid multilayers into optical signals in a label free manner due to shape changes in the lipid nanostructures. Here, we show that nanointaglio is suitable for the integration of chemically different lipid multilayer gratings into a sensor array capable of distinguishing vapors by means of an optical nose. Sensor arrays composed of six different lipid formulations are integrated onto a surface and their optical response to three different vapors (water, ethanol and acetone) in air as well as pH under water is monitored as a function of time. Principal component analysis of the array response results in distinct clustering indicating the suitability of the arrays for distinguishing these analytes. Importantly, the nanointaglio process used here is capable of producing lipid gratings out of different materials with sufficiently uniform heights for the fabrication of an optical nose.

Description: Broadband Power Line Communications (PLC) have taken advantage of the research advances in multi-carrier modulations to mitigate frequency selective fading, and their adoption opens up a myriad of applications in the field of sensory and automation systems, multimedia connectivity or smart spaces. Nonetheless, the use of these multi-carrier modulations, such as Wavelet-OFDM, requires a highly accurate symbol timing estimation for reliably recovering of transmitted data. Furthermore, the PLC channel presents some particularities that prevent the direct use of previous synchronization algorithms proposed in wireless communication systems. Therefore more research effort should be involved in the design and implementation of novel and robust synchronization algorithms for PLC, thus enabling real-time synchronization. This paper proposes a symbol timing estimator for broadband PLC based on cross-correlation with multilevel complementary sequences or Zadoff-Chu sequences and its efficient implementation in a FPGA; the obtained results show a 90% of success rate in symbol timing estimation for a certain PLC channel model and a reduced resource consumption for its implementation in a Xilinx Kyntex FPGA.

Description: In the smart grid, measurement devices may be compromised by adversaries, and their operations could be disrupted by attacks. A number of schemes to efficiently and accurately detect these compromised devices remotely have been proposed. Nonetheless, most of the existing schemes detecting compromised devices depend on the incremental response time in the attestation process, which are sensitive to data transmission delay and lead to high computation and network overhead. To address the issue, in this paper, we propose a low-cost remote memory attestation scheme (LRMA), which can efficiently and accurately detect compromised smart meters considering real-time network delay and achieve low computation and network overhead. In LRMA, the impact of real-time network delay on detecting compromised nodes can be eliminated via investigating the time differences reported from relay nodes. Furthermore, the attestation frequency in LRMA is dynamically adjusted with the compromised probability of each node, and then, the total number of attestations could be reduced while low computation and network overhead can be achieved. Through a combination of extensive theoretical analysis and evaluations, our data demonstrate that our proposed scheme can achieve better detection capacity and lower computation and network overhead in comparison to existing schemes.

Description: It is known that cardiac and respiratory rhythms in electrocardiograms (ECGs) are highly nonlinear and non-stationary. As a result, most traditional time-domain algorithms are inadequate for characterizing the complex dynamics of the ECG. This paper proposes a new ECG sensor card and a statistical-based ECG algorithm, with the aid of a reduced binary pattern (RBP), with the aim of achieving faster ECG human identity recognition with high accuracy. The proposed algorithm has one advantage that previous ECG algorithms lack—the waveform complex information and de-noising preprocessing can be bypassed; therefore, it is more suitable for non-stationary ECG signals. Experimental results tested on two public ECG databases (MIT-BIH) from MIT University confirm that the proposed scheme is feasible with excellent accuracy, low complexity, and speedy processing. To be more specific, the advanced RBP algorithm achieves high accuracy in human identity recognition and is executed at least nine times faster than previous algorithms. Moreover, based on the test results from a long-term ECG database, the evolving RBP algorithm also demonstrates superior capability in handling long-term and non-stationary ECG signals.

Description: Wireless sensor networks (WSNs) have been widely used to monitor the environment, and sensors in WSNs are usually power constrained. Because inner-node communication consumes most of the power, efficient data compression schemes are needed to reduce the data transmission to prolong the lifetime of WSNs. In this paper, we propose an efficient data compression model to aggregate data, which is based on spatial clustering and principal component analysis (PCA). First, sensors with a strong temporal-spatial correlation are grouped into one cluster for further processing with a novel similarity measure metric. Next, sensor data in one cluster are aggregated in the cluster head sensor node, and an efficient adaptive strategy is proposed for the selection of the cluster head to conserve energy. Finally, the proposed model applies principal component analysis with an error bound guarantee to compress the data and retain the definite variance at the same time. Computer simulations show that the proposed model can greatly reduce communication and obtain a lower mean square error than other PCA-based algorithms.

Description: Monitoring ocean waves plays a crucial role in, for example, coastal environmental and protection studies. Traditional methods for measuring ocean waves are based on ultrasonic sensors and accelerometers. However, the Global Positioning System (GPS) has been introduced recently and has the advantage of being smaller, less expensive, and not requiring calibration in comparison with the traditional methods. Therefore, for accurately measuring ocean waves using GPS, further research on the separation of the wave signals from the vertical GPS-mounted carrier displacements is still necessary. In order to contribute to this topic, we present a novel method that combines complementary ensemble empirical mode decomposition (CEEMD) with a wavelet threshold denoising model (i.e., CEEMD-Wavelet). This method seeks to extract wave signals with less residual noise and without losing useful information. Compared with the wave parameters derived from the moving average skill, high pass filter and wave gauge, the results show that the accuracy of the wave parameters for the proposed method was improved with errors of about 2 cm and 0.2 s for mean wave height and mean period, respectively, verifying the validity of the proposed method.

Description: Here, we provide an overview of the content of the Special Issue on “Human-computer interaction in smart environments”. The aim of this Special Issue is to highlight technologies and solutions encompassing the use of mass-market sensors in current and emerging applications for interacting with Smart Environments. Selected papers address this topic by analyzing different interaction modalities, including hand/body gestures, face recognition, gaze/eye tracking, biosignal analysis, speech and activity recognition, and related issues.

Description: The adsorption of the proteins CD13, mucin and bovine serum albumin on VLGXE-Au and YNGRT-Au interfaces was monitored by electrochemical impedance spectroscopy in the presence of [Fe(CN)6]3−/4−. The hydrophobicity of the Au surface was tailored using specific peptides, blocking agents and diluents. The combination of blocking agents (ethanolamine or n-butylamine) and diluents (hexanethiol or 2-mercaptoethanol) was used to prepare various peptide-modified Au surfaces. Protein adsorption onto the peptide-Au surfaces modified with the combination of n-butylamine and hexanethiol produced a dramatic decrease in the charge transfer resistance, Rct, for all three proteins. In contrast, polar peptide-surfaces induced a minimal change in Rct for all three proteins. Furthermore, an increase in Rct was observed with CD13 (an aminopeptidase overexpressed in certain cancers) in comparison to the other proteins when the VLGXE-Au surface was modified with n-butylamine as a blocking agent. The electrochemical data indicated that protein adsorption may be modulated by tailoring the peptide sequence on Au surfaces and that blocking agents and diluents play a key role in promoting or preventing protein adsorption. The peptide-Au platform may also be used for targeting cancer biomarkers with designer peptides.

Description: We report the results of a study of an optical sensor based on a channel-drop technique with two cascaded cavities in photonic-crystal slabs. Quality factors and intensities of the resonant modes of the sensor were analyzed with three-dimensional simulations. With the introduction of a reflector in the bus-channel and by control of the coupling between the two cavities and the drop-channel, the drop efficiency can be remarkably increased. In addition to the simulation, the two cavity sensor is fabricated and tested for optical response to water and oil infiltration. Both direct visual imaging and quantitative analysis were applied in experiment. A difference of refractive index $Delta n = 0.12$ between water and oil samples results in a wavelength shift of 18.3 nm, which greatly matches the simulation result of 20 nm and indicates a sensitivity of 153 nm RIU −1 . Both resonant peaks for water and oil infiltration have good selectivity in their transmission spectrum. The contrast between the broadband output of the bus-channel and the highly wavelength-selective outputs of the drop-channel opens opportunities for the two cascaded-cavity system as a fundamental building block for a multiplex drop-channel array for all-optical sensing, which can be widely used for bio/chemical detection and environmental monitoring.

Description: Nonlinearity-induced phase noise has become a major obstacle in long-haul coherent fiber-optic communication systems. Such phase noise has been shown to be signal dependent, and correlated over time. We propose a code-aided expectation-maximization algorithm to mitigate such nonlinear phase noise, iteratively utilizing both the time correlation of the nonlinearity-induced impairments and a soft-decision error-control code. Simulation and experimental results show that on a dual-polarization wavelength-division-multiplexed 16 QAM system, launch-power tolerance can be increased by ${1.5}$ dB, and the optical signal-to-noise ratio requirement can be relaxed by ${0.3}$ dB to achieve the same ${Q^2}$ -factor.

Description: Microring resonators have been the fundamental building blocks of integrated photonic networks. They play key roles in a number of on-chip photonic elements, such as filters, modulators, switches, and sensors. However, the applications of microring resonators in these components are hindered by the evanescent coupling, which requires very precise position control and is hard to be realized in standard photolithography. Here, we demonstrate a novel, general, and robust mechanism to achieve microdisk-based end-fire injection and collection devices. Instead of coupling light via evanescent waves, here the light is injected into the cavity by connecting a waveguide and a deformed microdisk directly. The light on resonance can be reflected back and detected at the same waveguide, making the devices to be “easy come easy go.” The reflectance is as high as 95% and can be periodically obtained from the long-lived resonances with free spectral range around 18 nm. The proposed mechanism is found to be robust to cavity shape, refractive index, and waveguide width and all the parameters can be larger than 500 nm, making the designed devices to be easier realized by standard photolithography. We believe this research will boost the development of low-cost silicon photonic devices.

Description: We proposed theoretically analyzed and experimentally demonstrated novel 1 × 4 channel flatband optical multiplexer/demultiplexer (MUX/DeMUX) that is based on Si-nanowire microring-assisted multiple delaylines. The proposed optical MUX/DeMUX scheme, which includes all-pass microring-type phase controllers and a Banyan-type 4 × 4 coupler, exhibits superior spectral flatness to any Si-nanowire optical DeMUXs that have previously been experimentally demonstrated.

Description: Analysis of the experimental data on microscopic, absorptive, fluorescent, and Raman-scattering properties of Bismuth (Bi)-doped yttria-alumino-silicate glass (Y-Al-SiO 2 :Bi)-based nanoengineered optical fibers, exhibiting broadband near-infrared fluorescence, is presented. Among the other well-established characteristics, inherent to Bi-doped silica fibers codoped with Aluminum (Al), a trend of spatial distributions of Bi atoms and Bi-related fluorescence-active centers is determined, being their concentrating in ring-like areas around the core's center, at approximately a half-distance to core/cladding interface. At the same time, the formation in this region of nanosized Bi clusters, supposedly weakly or nonfluorescing, is revealed for the fibers. These phenomena are argued to underlie worsening of the pump-to-signal overlap factor, which deteriorates efficiency of lasers and amplifiers based on such or similar Bi-doped alumino-silicate fibers.

Description: The paper develops a statistical model for the signals received in phase-sensitive optical time domain reflectometry (OTDR) probed by highly coherent sources. The backscattering process is modelled by a set of discrete scatterers with properly chosen parameters. Explicit equations for calculating the amplitude and the phase of the backscattered signal are obtained. The developed model predicts spectral and autocorrelation characteristics of the amplitude signals that are validated by experimental results. Characteristics of the phase signals, practicable for studying the sensing applications of the OTDR system, are presented and studied as well, demonstrating good correspondence with experiment. A more detailed modelling of distributed vibration sensing systems and their response to disturbances along an optical fiber will be possible as an extension of the developed formalism.

Description: A five channel step index plastic optical fiber proposal for a multiplexer/demultiplexer having insertion losses ( IL ) of 2.9–4 dB, pass bandwidths at −3 dB > 30 nm, crosstalk attenuation >30 dB and size of ∼65 mm × 55 mm, is demonstrated. It is based on a reflective diffraction grating with blazed profile and an aspheric lens. The theoretical analysis presented is used to further reduce the system size to ∼37 mm × 30 mm and to increase the number of channels to 8 keeping ILs 〈 4.5 dB. Experimental results have good agreement with theoretical expectations.

Description: Securing communications in wireless sensor networks is increasingly important as the diversity of applications increases. However, even today, it is equally important for the measures employed to be energy efficient. For this reason, this publication analyzes the suitability of various cryptographic primitives for use in WSNs according to various criteria and, finally, describes a modular, PKI-based framework for confidential, authenticated, secure communications in which most suitable primitives can be employed. Due to the limited capabilities of common WSN motes, criteria for the selection of primitives are security, power efficiency and memory requirements. The implementation of the framework and the singular components have been tested and benchmarked in our testbed of IRISmotes.

Description: Recently, the cross-layer design for the wireless sensor network communication protocol has become more and more important and popular. Considering the disadvantages of the traditional cross-layer routing algorithms, in this paper we propose a new fuzzy logic-based routing algorithm, named the Balanced Cross-layer Fuzzy Logic (BCFL) routing algorithm. In BCFL, we use the cross-layer parameters’ dispersion as the fuzzy logic inference system inputs. Moreover, we give each cross-layer parameter a dynamic weight according the value of the dispersion. For getting a balanced solution, the parameter whose dispersion is large will have small weight, and vice versa. In order to compare it with the traditional cross-layer routing algorithms, BCFL is evaluated through extensive simulations. The simulation results show that the new routing algorithm can handle the multiple constraints without increasing the complexity of the algorithm and can achieve the most balanced performance on selecting the next hop relay node. Moreover, the Balanced Cross-layer Fuzzy Logic routing algorithm can adapt to the dynamic changing of the network conditions and topology effectively.

Description: To solve the problem of coverage performance assessment, this study proposes an evaluation method based on the trajectory of the target, which is applicable to universal sensor networks, including both heterogeneous and homogeneous sensor networks. Different from the traditional Voronoi algorithm, the proposed Improved Coverage Force Division (ICFD) plans a coverage force division map whichscales the qualitative coverage performancebasedon both covering intensities andlocations of the nodes. Furthermore, the Trajectory-based Evaluating Schedule (TES) is responsible for solving the quantitative coverage evaluationproblem by measuringthe resulting trajectories’ Balance Values (BVs). A model of weak-point ranking conjoined in consideration of coverage force and distance can guide future deployment to compensate coverage. Comparative trials using the greedy algorithm, Voronoi algorithm, and the proposed TES verify that TES achieves the approximate results for two-stage and multistage heterogeneous sensor networks with acceptable difference and lower complexity, and it is superior to the Voronoi algorithm in homogeneous sensor networks interms of breaking the four-point circle block.

Description: Pyroelectric harvesters convert time-dependent temperature variations into electric current. The appropriate geometry of the pyroelectric cells, coupled with the optimal period of temperature fluctuations, is key to driving the optimal load resistance, which enhances the performance of pyroelectric harvesters. The induced charge increases when the thickness of the pyroelectric cells decreases. Moreover, the induced charge is extremely reduced for the thinner pyroelectric cell when not used for the optimal period. The maximum harvested power is achieved when a 100 μm-thick PZT (Lead zirconate titanate) cell is used to drive the optimal load resistance of about 40 MΩ. Moreover, the harvested power is greatly reduced when the working resistance diverges even slightly from the optimal load resistance. The stored voltage generated from the 75 μm-thick PZT cell is less than that from the 400 μm-thick PZT cell for a period longer than 64 s. Although the thinner PZT cell is advantageous in that it enhances the efficiency of the pyroelectric harvester, the much thinner 75 μm-thick PZT cell and the divergence from the optimal period further diminish the performance of the pyroelectric cell. Therefore, the designers of pyroelectric harvesters need to consider the coupling effect between the geometry of the pyroelectric cells and the optimal period of temperature fluctuations to drive the optimal load resistance.

Description: Continuous respiratory monitoring is an important tool for clinical monitoring. Associated with the development of biomedical technology, it has become more and more important, especially in the measuring of gas flow and CO2 concentration, which can reflect the status of the patient. In this paper, a new type of biomedical device is presented, which uses low-power sensors with a piezoresistive silicon differential pressure sensor to measure gas flow and with a pyroelectric sensor to measure CO2 concentration simultaneously. For the portability of the biomedical device, the sensors and low-power measurement circuits are integrated together, and the airway tube also needs to be miniaturized. Circuits are designed to ensure the stability of the power source and to filter out the existing noise. Modulation technology is used to eliminate the fluctuations at the trough of the waveform of the CO2 concentration signal. Statistical analysis with the coefficient of variation was performed to find out the optimal driving voltage of the pressure transducer. Through targeted experiments, the biomedical device showed a high accuracy, with a measuring precision of 0.23 mmHg, and it worked continuously and stably, thus realizing the real-time monitoring of the status of patients.

Description: In this work, we report a new design for an electrostatically actuated microgripper with a post-assembly self-locking mechanism. The microgripper arms are driven by rotary comb actuators, enabling the microgripper to grip objects of any size from 0 to 100 μm. The post-assembly mechanism is driven by elastic deformation energy and static electricity to produce self-locking and releasing actions. The mechanism enables the microgripper arms to grip for long periods without continuously applying the external driving signal, which significantly reduces the effects and damage to the gripped objects caused by these external driving signals. The microgripper was fabricated using a Silicon-On-Insulator (SOI) wafer with a 30 μm structural layer. Test results show that this gripper achieves a displacement of 100 μm with a driving voltage of 33 V, and a metal wire with a diameter of about 1.6 mil is successfully gripped to demonstrate the feasibility of this post-assembly self-locking mechanism.

Description: Ag-modified In2O3/ZnO bundles with micro/nano porous structures have been designed and synthesized with by hydrothermal method continuing with dehydration process. Each bundle consists of nanoparticles, where nanogaps of 10–30 nm are present between the nanoparticles, leading to a porous structure. This porous structure brings high surface area and fast gas diffusion, enhancing the gas sensitivity. Consequently, the HCHO gas-sensing performance of the Ag-modified In2O3/ZnO bundles have been tested, with the formaldehyde-detection limit of 100 ppb (parts per billion) and the response and recover times as short as 6 s and 3 s, respectively, at 300 °C and the detection limit of 100 ppb, response time of 12 s and recover times of 6 s at 100 °C. The HCHO sensing detect limitation matches the health standard limitation on the concentration of formaldehyde for indoor air. Moreover, the strategy to synthesize the nanobundles is just two-step heating and easy to scale up. Therefore, the Ag-modified In2O3/ZnO bundles are ready for industrialization and practical applications.

Description: Control of oxygen over cell cultures in vitro is a topic of considerable interest, as chronic and cyclic hypoxia can alter cell behaviour. Both static and transient hypoxic levels have been found to affect tumour cell behaviour; it is potentially valuable to include these effects in early, in vitro stages of drug screening. A barrier to their inclusion is that rates of transient hypoxia can be a few cycles/hour, which is difficult to reproduce in traditional in vitro cell culture environments due to long diffusion distances from control gases to the cells. We use a gas-permeable three-layer microfluidic device to achieve spatial and temporal oxygen control with biologically-relevant switching times. We measure the oxygen profiles with integrated, ratiometric optical oxygen sensors, demonstrate sensor and system stability over multi-day experiments, and characterize a pre-bleaching process to improve sensor stability. We show, with both finite-element modelling and experimental data, excellent control over the oxygen levels by the device, independent of fluid flow rate and oxygenation for the operating flow regime. We measure equilibration times of approximately 10 min, generate complex, time-varying oxygen profiles, and study the effects of oxygenated media flow rates on the measured oxygen levels. This device could form a useful tool for future long-term studies of cell behaviour under hypoxia.

Description: With the increasing climatic extremes, the frequency and severity of urban flood events have intensified worldwide. In this study, image-based automated monitoring of flood formation and analyses of water level fluctuation were proposed as value-added intelligent sensing applications to turn a passive monitoring camera into a visual sensor. Combined with the proposed visual sensing method, traditional hydrological monitoring cameras have the ability to sense and analyze the local situation of flood events. This can solve the current problem that image-based flood monitoring heavily relies on continuous manned monitoring. Conventional sensing networks can only offer one-dimensional physical parameters measured by gauge sensors, whereas visual sensors can acquire dynamic image information of monitored sites and provide disaster prevention agencies with actual field information for decision-making to relieve flood hazards. The visual sensing method established in this study provides spatiotemporal information that can be used for automated remote analysis for monitoring urban floods. This paper focuses on the determination of flood formation based on image-processing techniques. The experimental results suggest that the visual sensing approach may be a reliable way for determining the water fluctuation and measuring its elevation and flood intrusion with respect to real-world coordinates. The performance of the proposed method has been confirmed; it has the capability to monitor and analyze the flood status, and therefore, it can serve as an active flood warning system.

Description: Internet of Things (IoT) is driving innovation in an ever-growing set of application domains such as intelligent processing for autonomous robots. For an autonomous robot, one grand challenge is how to sense its surrounding environment effectively. The Simultaneous Localization and Mapping with RGB-D Kinect camera sensor on robot, called RGB-D SLAM, has been developed for this purpose but some technical challenges must be addressed. Firstly, the efficiency of the algorithm cannot satisfy real-time requirements; secondly, the accuracy of the algorithm is unacceptable. In order to address these challenges, this paper proposes a set of novel improvement methods as follows. Firstly, the ORiented Brief (ORB) method is used in feature detection and descriptor extraction. Secondly, a bidirectional Fast Library for Approximate Nearest Neighbors (FLANN) k-Nearest Neighbor (KNN) algorithm is applied to feature match. Then, the improved RANdom SAmple Consensus (RANSAC) estimation method is adopted in the motion transformation. In the meantime, high precision General Iterative Closest Points (GICP) is utilized to register a point cloud in the motion transformation optimization. To improve the accuracy of SLAM, the reduced dynamic covariance scaling (DCS) algorithm is formulated as a global optimization problem under the G2O framework. The effectiveness of the improved algorithm has been verified by testing on standard data and comparing with the ground truth obtained on Freiburg University’s datasets. The Dr Robot X80 equipped with a Kinect camera is also applied in a building corridor to verify the correctness of the improved RGB-D SLAM algorithm. With the above experiments, it can be seen that the proposed algorithm achieves higher processing speed and better accuracy.

Description: Standard upper-limb motor function impairment assessments, such as the Fugl-Meyer Assessment (FMA), are a critical aspect of rehabilitation after neurological disorders. These assessments typically take a long time (about 30 min for the FMA) for a clinician to perform on a patient, which is a severe burden in a clinical environment. In this paper, we propose a framework for automating upper-limb motor assessments that uses low-cost sensors to collect movement data. The sensor data is then processed through a machine learning algorithm to determine a score for a patient’s upper-limb functionality. To demonstrate the feasibility of the proposed approach, we implemented a system based on the proposed framework that can automate most of the FMA. Our experiment shows that the system provides similar FMA scores to clinician scores, and reduces the time spent evaluating each patient by 82%. Moreover, the proposed framework can be used to implement customized tests or tests specified in other existing standard assessment methods.

Description: Cupric oxide (CuO) thin films are promising materials in gas sensor applications. The CuO-based gas sensors behaved as p-type semiconductors and can be used as part of an e-nose or smart sensor array for breath analysis. The authors present the investigation results on M-doped CuO-based (M = Ag, Au, Cr, Pd, Pt, Sb, Si) sensors working at various temperatures upon exposure to a low concentration of C3H8, which can be found in exhaled human breath, and it can be considered as a one of the biomarkers of several diseases. The films have been deposited in magnetron sputtering technology on low temperature cofired ceramics substrates. The results of the gas sensors’ response are also presented and discussed. The Cr:CuO-based structure, annealed at 400 °C for 4 h in air, showed the highest sensor response, of the order of 2.7 at an operation temperature of 250 °C. The response and recovery time(s) were 10 s and 24 s, respectively. The results show that the addition of M-dopants in the cupric oxide films effectively act as catalysts in propane sensors and improve the gas sensing properties. The films’ phase composition, microstructure and surface topography have been assessed by the X-ray diffraction (XRD), scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDX) methods.

Description: We present a short review of recent progress in the field of optical gas sensors based on porous silicon (PSi) and PSi composites, which are separate from PSi optochemical and biological sensors for a liquid medium. Different periodical and nonperiodical PSi photonic structures (bares, modified by functional groups or infiltrated with sensory polymers) are described for gas sensing with an emphasis on the device specificity, sensitivity and stability to the environment. Special attention is paid to multiparametric sensing and sensor array platforms as effective trends for the improvement of analyte classification and quantification. Mechanisms of gas physical and chemical sorption inside PSi mesopores and pores of PSi functional composites are discussed.

Description: The damage detection of a wind turbine blade enables better operation of the turbines, and provides an early alert to the destroyed events of the blade in order to avoid catastrophic losses. A new non-baseline damage detection method based on the Fiber Bragg grating (FBG) in a wind turbine blade is developed in this paper. Firstly, the Chi-square distribution is proven to be an effective damage-sensitive feature which is adopted as the individual information source for the local decision. In order to obtain the global and optimal decision for the damage detection, the feature information fusion (FIF) method is proposed to fuse and optimize information in above individual information sources, and the damage is detected accurately through of the global decision. Then a 13.2 m wind turbine blade with the distributed strain sensor system is adopted to describe the feasibility of the proposed method, and the strain energy method (SEM) is used to describe the advantage of the proposed method. Finally results show that the proposed method can deliver encouraging results of the damage detection in the wind turbine blade.

Description: To improve the control effectiveness and make the prosthetic hand not only controllable but also perceivable, an EMG prosthetic hand control strategy was proposed in this paper. The control strategy consists of EMG self-learning motion recognition, backstepping controller with stiffness fuzzy observation, and force tactile representation. EMG self-learning motion recognition is used to reduce the influence on EMG signals caused by the uncertainty of the contacting position of the EMG sensors. Backstepping controller with stiffness fuzzy observation is used to realize the position control and grasp force control. Velocity proportional control in free space and grasp force tracking control in restricted space can be realized by the same controller. The force tactile representation helps the user perceive the states of the prosthetic hand. Several experiments were implemented to verify the effect of the proposed control strategy. The results indicate that the proposed strategy has effectiveness. During the experiments, the comments of the participants show that the proposed strategy is a better choice for amputees because of the improved controllability and perceptibility.

Description: A person tracking algorithm by fusing multicues based on patches is proposed to solve the problem of distinguishing person, occlusion, and illumination variations. Kinect is mounted on the robot for providing color images and depth maps. A detector representing a person by using the fusion of multicues based on patches is proposed. The detector divides the person into many patches and then represents each patch by using depth-color histograms and depth-texture histograms. The appearance representation, considering depth, color, and texture information, has powerful discrimination ability to handle the problems of occlusion, illumination changes, and pose variations. Considering the motion of the robot and person, a tracker called motion extended Kalman filter (MEKF) is presented to predict the person’s position. The result of the tracker is treated as a candidate sample of the detector, and then the result of the detector is the previous knowledge of the tracker. The detector and tracker supplement each other and improve the tracking performance. To drive the robot towards the given person precisely, a fuzzy based intelligent gear control strategy (FZ-IGS) is implemented. Experiments demonstrate that the proposed approach can track a person in a complex environment and have an optimum performance.

Description: We consider the sensor networks hierarchical optimization problem in high-speed railway transport hub (HRTH). The sensor networks are optimized from three hierarchies which are key area sensors optimization, passenger line sensors optimization, and whole area sensors optimization. Case study on a specific HRTH in China showed that the hierarchical optimization method is effective to optimize the sensor networks for security monitoring in HRTH.

Description: Because of their low cost and adaptability, wireless sensor networks are widely used in civil, military, and commercial fields and other fields. However, since the sensor node in the calculation of the capacity, battery capacity, and storage capacity are restricted by the limitations and inherent characteristics of the sensor networks, compared to traditional networks, which makes wireless sensor networks face more security threats. This paper summarized research progress of sensor network security issues as three aspects, key management, authentication, and secure routing, analyzed and commented on these results advantages and disadvantages and pointed out the future direction of the hot research field.

Description: The interaction of distributed robotics and wireless sensor networks has led to the creation of mobile sensor networks. There has been an increasing interest in building mobile sensor networks and they are the favored class of WSNs in which mobility plays a key role in the execution of an application. More and more researches focus on development of mobile wireless sensor networks (MWSNs) due to its favorable advantages and applications. In WSNs robotics can play a crucial role, and integrating static nodes with mobile robots enhances the capabilities of both types of devices and enables new applications. In this paper we present an overview on mobile sensor networks in robotics and vice versa and robotic sensor network applications.

Description: Background: Normative values are lacking for daily quantity of infant leg movements. This is critical for understanding the relationship between the quantity of leg movements and onset of independent walking, and will begin to inform early therapy intervention for infants at risk for developmental delay. Methods: We used wearable inertial movement sensors to record full-day leg movement activity from 12 infants with typical development, ages 1–12 months. Each infant was tested three times across 5 months, and followed until the onset of independent walking. We developed and validated an algorithm to identify infant-produced leg movements. Results: Infants moved their legs tens of thousands of times per day. There was a significant effect of leg movement quantity on walking onset. Infants who moved their legs more walked later than infants who moved their legs less, even when adjusting for age, developmental level or percentile length. We will need a much larger sample to adequately capture and describe the effect of movement experience on developmental rate. Our algorithm defines a leg movement in a specific way (each pause or change in direction is counted as a new movement), and further assessment of movement characteristics are necessary before we can fully understand and interpret our finding that infants who moved their legs more walked later than infants who moved their legs less. Conclusions: We have shown that typically-developing infants produce thousands of leg movements in a typical day, and that this can be accurately captured in the home environment using wearable sensors. In our small sample we can identify there is an effect of leg movement quantity on walking onset, however we cannot fully explain it.

Description: Heavy occlusions in cluttered scenes impose significant challenges to many computer vision applications. Recent light field imaging systems provide new see-through capabilities through synthetic aperture imaging (SAI) to overcome the occlusion problem. Existing synthetic aperture imaging methods, however, emulate focusing at a specific depth layer, but are incapable of producing an all-in-focus see-through image. Alternative in-painting algorithms can generate visually-plausible results, but cannot guarantee the correctness of the results. In this paper, we present a novel depth-free all-in-focus SAI technique based on light field visibility analysis. Specifically, we partition the scene into multiple visibility layers to directly deal with layer-wise occlusion and apply an optimization framework to propagate the visibility information between multiple layers. On each layer, visibility and optimal focus depth estimation is formulated as a multiple-label energy minimization problem. The layer-wise energy integrates all of the visibility masks from its previous layers, multi-view intensity consistency and depth smoothness constraint together. We compare our method with state-of-the-art solutions, and extensive experimental results demonstrate the effectiveness and superiority of our approach.

Description: Link scheduling is important for reliable data communication in wireless sensor networks. Previous works mainly focus on how to find the minimum scheduling length but ignore the impact of energy consumption. In this paper, we integrate them together and solve them by multiobjective genetic algorithms. As a contribution, by jointly modeling the route selection and interference-free link scheduling problem, we give a systematical analysis on the relationship between link scheduling and energy consumption. Considering the specific many-to-one communication nature of WSNs, we propose a novel link scheduling scheme based on NSGA-II (Non-dominated Sorting Genetic Algorithm II). Our approach aims to search the optimal routing tree which satisfies the minimum scheduling length and energy consumption for wireless sensor networks. To achieve this goal, the solution representation based on the routing tree, the genetic operations including tree based recombination and mutation, and the fitness evaluation based on heuristic link scheduling algorithm are well designed. Extensive simulations demonstrate that our algorithm can quickly converge to the Pareto optimal solution between the two performance metrics.

Description: The original sequential pattern mining model only considers occurrence frequencies of sequential patterns, disregarding their occurrence periodicity. We propose an asynchronous periodic sequential pattern mining model to discover the sequential patterns that not only occur frequently but also appear periodically. For this mining model, we propose a pattern-growth mining algorithm to mine asynchronous periodic sequential patterns with multiple minimum item supports. This algorithm employs a divide-and-conquer strategy to mine asynchronous periodic sequential patterns in a depth-first manner recursively. We describe the process of algorithm realization and demonstrate the efficiency and stability of the algorithm through experimental results.

Description: The design of wireless sensor networks (WSNs) in the Internet of Things (IoT) faces many new challenges that must be addressed through an optimization of multiple design objectives. Therefore, multiobjective optimization is an important research topic in this field. In this paper, we develop a new efficient multiobjective optimization algorithm based on the chaotic ant swarm (CAS). Unlike the ant colony optimization (ACO) algorithm, CAS takes advantage of both the chaotic behavior of a single ant and the self-organization behavior of the ant colony. We first describe the CAS and its nonlinear dynamic model and then extend it to a multiobjective optimizer. Specifically, we first adopt the concepts of “nondominated sorting” and “crowding distance” to allow the algorithm to obtain the true or near optimum. Next, we redefine the rule of “neighbor” selection for each individual (ant) to enable the algorithm to converge and to distribute the solutions evenly. Also, we collect the current best individuals within each generation and employ the “archive-based” approach to expedite the convergence of the algorithm. The numerical experiments show that the proposed algorithm outperforms two leading algorithms on most well-known test instances in terms of Generational Distance, Error Ratio, and Spacing.

Description: Mobility management in wireless sensor network is the most important factor to be considered for applications such as healthcare system. Recently, Identifier (ID)/Locator (LOC) separation based mobility management scheme has been proposed for wireless sensor network. However, it does not perform well in group-based mobility management in wireless body area network, and thus it tends to induce large registration, packet delivery, and handover delays. To overcome these limitations, we propose a group-based mobility management scheme based on ID/LOC separation concept for ID-based communications with location-based routing to reduce the number of control messages. In the proposed scheme, each sensor device has a globally unique device identifier (GDID) which contains the information of its home network domain. For handover support, each access gateway maintains its home GDID register (HGR) and visiting GDID register (VGR) which are used to keep the GDID-locator (LOC) mappings for primary mobile devices in the distributed manner. Besides, in the proposed scheme, only the coordinator will send Router Solicitation and Router Advertisement messages to reduce the control messages further. By numerical analysis, we show that the proposed scheme can significantly reduce the registration, packet delivery, and handover delays, compared to the existing schemes.

Description: Biological schemes provide useful resources for designing adaptive routing protocols for wireless sensor networks (WSNs). The key idea behind using bioinspired routing is to find the optimal path to the destination. Similarly, the idea of opportunistic routing (OR) is to find the least number of hops to deliver the data to the destination. Numerous routing schemes have been proposed in WSNs while targeting various performance goals, such as throughput, delay, and link quality. Recently, OR schemes have come onto the scene in comparison with the traditional routing algorithms. The performance of OR schemes, however, highly depends on the selection of forwarder nodes. In this paper, we consider a chain network topology, where nodes are separated by an equal distance. The throughput of the chain network is analyzed mathematically, and based on the analysis results, a heuristic algorithm is proposed to choose the forwarder nodes. We evaluate the performance of the proposed Heuristic Approach to Select Opportunistic Routing Forwarders (HASORF) by using the ns-2 simulator and compare it with previous schemes, such as random routing, Extremely Opportunistic Routing (ExOR), and Simple Opportunistic Adaptive Routing (SOAR). The empirical results show that our proposed scheme achieves the best performance among them.

Description: Orientation estimation using low cost sensors is an important task for Micro Aerial Vehicles (MAVs) in order to obtain a good feedback for the attitude controller. The challenges come from the low accuracy and noisy data of the MicroElectroMechanical System (MEMS) technology, which is the basis of modern, miniaturized inertial sensors. In this article, we describe a novel approach to obtain an estimation of the orientation in quaternion form from the observations of gravity and magnetic field. Our approach provides a quaternion estimation as the algebraic solution of a system from inertial/magnetic observations. We separate the problems of finding the “tilt” quaternion and the heading quaternion in two sub-parts of our system. This procedure is the key for avoiding the impact of the magnetic disturbances on the roll and pitch components of the orientation when the sensor is surrounded by unwanted magnetic flux. We demonstrate the validity of our method first analytically and then empirically using simulated data. We propose a novel complementary filter for MAVs that fuses together gyroscope data with accelerometer and magnetic field readings. The correction part of the filter is based on the method described above and works for both IMU (Inertial Measurement Unit) and MARG (Magnetic, Angular Rate, and Gravity) sensors. We evaluate the effectiveness of the filter and show that it significantly outperforms other common methods, using publicly available datasets with ground-truth data recorded during a real flight experiment of a micro quadrotor helicopter.