ALBERT

Description: Gold nanorods (GNRs) with surface plasmon resonance peak at 1063.8 nm were fabricated and experimentally exploited as the single and combined saturable absorber (SA) in a $Q$ -switched Nd:YAG laser for the first time. In the situation using GNRs as a single SA, the maximum pulse energy of 19 $muhbox{J} $ was achieved at a pulse repetition rate of 20 kHz. However, due to the small effective modulation depth of the GNRs, microsecond pulses were generated in such a GNRs-based passively $Q$ -switched laser. A novel configuration using GNRs as a combined SA in an acoustooptic $Q$ -switched Nd:YAG laser was proposed. The small nonlinear loss modulation induced by the GNRs played a distinctive role in flexibly manipulating the nanosecond pulse waveforms. Our study demonstrated the feasibility of generating high-energy pulses by singly using GNRs-based SA in all solid-state lasers. Meanwhile, a new application mode incorporating GNRs as a combined SA was studied, providing an alternative method to take advantage of the nanomaterial-based SA with a relatively small modulation depth.

Description: Commercial, industrial, and military aerospace designs are increasingly deploying MEMS micro inertial measurement unit (MIMU) for motion control, automation, and positioning applications, such as the unmanned aerial vehicle (UAV), robot, and smart phone. On the one hand, MIMU has the merit of low cost, small size, low-power consumption, and high shock resistance, but on the other hand, low-cost MIMU is affected by systematic error caused by the instability of the drift, scaling factors, and axes misalignment, which may lead to large errors in the position and attitude’s determination from time to time. That means calibration before use is an effective way to improve the practical precision of MIMU. However, many customers have no precise turntable to calibrate the MIMU before they use it. To address these problems, this paper presents an easy self-calibration method to implement calibration of the MIMU on a common table only with an inclined surface, no precise turntable is needed. The calibration method is based on the following principles. First, the module of the output vector of the orthogonal configured three-axis accelerometers is equal to unit gravity. Second, when IMU rotates to a known gesture with a stable axis, the angles can be calculated through integration. Third, when the accelerometers’ parameters are calculated, it can act as a level datum. Furthermore, the accelerometers on the inclined surface are used to determine the rotating heading datum. Finally, after a series static positions test and rotating test, the parameters can be extracted and estimated. To demonstrate the success and the convenience of the proposed method, comparison experiments with the precision turntable have been made on an ADI’s MIMU. The calibration results show that the accuracy and precision of this method is quite equivalent with the turntable-based calibration, and the scale factors error with an order of magnitude always equal or less than $10^{-5}$ . The observed static and dynamic yaw maximum angular error in a certain period is <0.8°, the pitch maximum angular error is <0.5°, and the roll maximum angular error is <0.3°.

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: 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: Recharging sensor networks using Unmanned Aerial Vehicles (UAVs) provides a possible method for increasing network lifetime. In this paper, we evaluate that approach, determining how much of a benefit it provides and under what conditions. We base our simulations and field experiments on data collected from charging with our UAV-based wireless power transfer system, which has similar transfer ranges and efficiencies as other such systems. We determine that a UAV can increase the network lifetime up to 290% compared to no recharging, that the UAV should recharge 30% of the sensor node battery capacity at one time for the maximum benefit, and that the UAV should recharge the lowest powered node until the network reaches a size of approximately 306 nodes at which point it should recharge the sink. We also examine how the sensor network can aid this through sink selection. The policy varies as network size increases, with a static approach working well until 200 nodes, and then either a perimeter or heuristic approach works best. These results inform future use of UAVs in recharging and working with sensor networks.

Description: The aim of this study is to construct an intelligent wireless sensing and control system to address health issues. We combine three technologies including (1) wireless sensing technology to develop an extendable system for monitoring environmental indicators such as temperature, humidity and CO2 concentration, (2) ARIMA (autoregressive integrated moving average) to predict air quality trends and take action before air quality worsens, and (3) fuzzy theory which is applied to build an energy-saving mechanism for feedback control. Experimental results show the following. (1) A longer historical data collected time interval will reduce the effects of abnormal surges on prediction results. We find the ARIMA prediction model accuracy improving from 3.19 ± 3.47% for a time interval of 10 minutes to 1.71 ± 1.45% for a time interval of 50 minutes. (2) The stability experiment shows that the error rate of prediction model is also less than 7.5%. (3) In the energy-saving experiment, fuzzy logic-based decision model can reduce the 55% energy while maintaining adequate air quality.

Description: The pattern synthesis and activated element selection for conformal array is investigated based on hybrid particle swarm optimization-gravitational search algorithm (PSOGSA) in this paper. With the introduction of PSOGSA algorithm which is a novel hybrid optimization technique, the element excitations are optimized to obtain the desired pattern for conformal array in the case of considering uncoupled and coupled element pattern. Numerical simulation and full-wave electromagnetic calculation verify the advantage and efficiency of our method. Then, a novel strategy of activated element selection based on PSOGSA algorithm is proposed for saving the energy consumption in conformal array.

Description: Low-energy technologies in the Internet of Things (IoTs) era are still unable to provide the reliability needed by the industrial world, particularly in terms of the wireless operation that pervasive deployments demand. While the industrial wireless performance has achieved an acceptable degree in communications, it is no easy task to determine an efficient energy-dimensioning of the device in order to meet the application requirements. This is especially true in the face of the uncertainty inherent in energy harvesting. Thus, it is of utmost importance to model and dimension the energy consumption of the IoT applications at the pre-deployment or pre-production stages, especially when considering critical factors, such as reduced cost, life-time, and available energy. This paper presents a comprehensive model for the power consumption of wireless sensor nodes. The model takes a system-level perspective to account for all energy expenditures: communications, acquisition and processing. Furthermore, it is based only on parameters that can empirically be quantified once the platform (i.e., technology) and the application (i.e., operating conditions) are defined. This results in a new framework for studying and analyzing the energy life-cycles in applications, and it is suitable for determining in advance the specific weight of application parameters, as well as for understanding the tolerance margins and tradeoffs in the system.

Description: With the development of Internet of Things (IoT), a large amount of machine-to-machine (M2M) devices produce the data from a huge number of M2M communications. A massive access congestion control scheme in M2M communication is important in a wireless M2M network, where a wireless M2M network is constituted by a large number of wireless M2M devices. In this paper, we developed a spiderweb-based massive access management protocol for M2M wireless networks. The wireless M2M network topology considered, in this paper, is a spiderweb-based topology, which belongs to a regular topology. The spiderweb-based topology is split into a number of sub-spiderweb, while each sub-spiderweb can be seen as a small reservoir. The main function of the small reservoir is to temporarily store the massive access if the congestion problem is occurred due to the massive assess has been suddenly happened from the M2M devices. When the congestion problem is alleviated gradually, the temporarily-stored massive assess can be digested from these small reservoirs. The contribution of the proposed scheme is to reduce the packet loss rate and prolong the wireless M2M network lifetime. In addition, a dynamically adjustment of the different sub-spiderweb size is developed based on the amount of different data traffics. Simulation result finally illustrates that the proposed mechanism significantly reduces the packet loss rate and keeps the maximum network lifetime.

Description: The paper presents the methodology including the deployment of a structure comprising of C-clamp magnetic stripes and a self-calibration scheme using a four-coil design to resolve the issues of the interference and misplacement problems existing in the flexible nonintrusive current sensor tag for the current detection of household two-wire power lines. Experimental results show that the stripe structure can effectively screen out the magnetic flux originating from the nearby power line for the reduction of sensing error caused by the electromagnetic field interference and the calibration scheme containing the correction of horizontal misplacement and the analysis of power cable thickness via the four-coil design can provide the information of sensor location for accurate current sensing. Less than 4% of sensing error indicates that the proposed methodology can indeed facilitate the flexible current sensor tag for practical use.

Description: Rapidly emerging batteryless sensors are creating tremendous opportunities for truly wearable sensors for activity recognition. However, data streams from such sensors are characterized by sparsity and noise, which make activity recognition a challenging task. In this paper, we study the feasibility of passive computational RFID sensors for ambulatory monitoring. In particular, we focus on recognizing transfers out of beds or chairs and walking. Ideally, all these activities need to be monitored by movement sensor alarm systems to alert caregivers to provide supervision during the ambulation of older people in hospitals and nursing homes to prevent a fall. Our novel approach to partition continuous sensor data on natural activity boundaries and to identify transfers out of beds or chairs and walking as transitions between sequences of movements overcomes issues posed by the sparsity and the noise. We demonstrate through in-depth experiments the high performance (F-score > 93%) and the responsiveness of our approach.

Description: A common-mode (CM) active filter was designed in a compact package to suppress CM conducted emissions at a switching mode power supply (SMPS). Based on the analytical expressions considering both stability and performance, the design and optimization rules for the proposed active filter have been presented. After verifying its performance by measurements using vector network analysis, the proposed filter was installed in a 200-W SMPS board with 64 and 110 kHz switching frequencies, demonstrating its usefulness by experiments. The performance degradation due to the magnetic saturation and the AEF grounding impedance was also analyzed and investigated.

Description: This paper proposes an approach to design multiple-input multiple-output radar waveforms that are orthogonal on both the transmitter and receiver. The proposed method jointly utilizes the direct sequence spread spectrum coding and orthogonal frequency division multiplexing (OFDM) chirp signaling techniques. We name it spread spectrum-coded OFDM chirp waveform diversity design. The performance of the designed waveforms is analyzed by examining the ambiguity function and correlation function. The influences of the spread spectrum code choice and the OFDM chirp parameters are also investigated. It is verified that the proposed design scheme can ensure these waveforms stay orthogonal on the receiver and have large time-bandwidth product which is beneficial to separate closely spaced targets.

Description: Studies have presented that the driver vigilance level has serious implication in the causation of road accidents. This paper focuses on integrating both the vehicle-based control behavior and physiological state to predict the driver vigilance index which is evaluated by using a smartwatch. The vehicle control behavior can be observed from the steering wheel movement. Our study utilized the smartwatch motion sensors to study the steering wheel behavior. Meanwhile, physiological state of driver reflects the driver capability of safety alert driving which is estimated by photoplethysmogram (PPG) and respiration signals in this paper. The PPG sensor is integrated in a sport wristband with a Bluetooth low energy module, transmitted the PPG signals to smartwatch in real time. The steering angle is derived by the reading from smartwatch built-in accelerometer and gyroscope sensors. On the other hand, the respiration is derived using the PPG peak baseline method. In order to utterly investigate the sleepiness-induced factors, the time, spectral, and phase space domain features are calculated. Considering the smartwatch processing capability, mutual-information technique is applied to designate the ten most descriptive features. Then, the extracted descriptive features are serve as parameters to a classifier to determine the driver aptitude status. The features are analyzed for their correlation with the subjective Koralinska sleepiness scale and through recorded video observations. The experimental results reveal that our system is capable of estimating driver hypervigilance at average of 96.5% accuracy rate by evaluating on both driving behavior and driver physiological state, provided a novel and low-cost implementation.

Description: A cavitating two-phase flow of water in a pipe with area shrinkage was experimentally investigated, acquiring at high sampling rate pressure signals and images of the cavitating flow field. The time series of the pressure fluctuations was analyzed in terms of power spectral density and related to the cavitation regimes. Furthermore, the fluctuations of the pressure measurements were also decomposed using the wavelet transform to analyze the frequency distribution of the signals energy with respect to the flow behavior. The energy content at each frequency band of the acquire signals is well related to cavitation flow-field behavior. Moreover, the artificial neural network and the least squares support vector machine (LS-SVM) were implemented to identify the cavitation regime, using, as inputs, the power spectral density distributions of the pressure fluctuations, and some features of the decomposed signals, as the wavelet energy for each decomposition level and wavelet entropy. Results indicate the most accurate model to be used in the cavitation regime identification, underlining the enhanced capability of LS-SVM trained with the input data set based on the wavelet decomposition features.

Description: In this paper, we present a novel silicon-on-insulator (SOI) complementary metal–oxide–semiconductor (CMOS) microelectromechanical-system thermal wall shear stress sensor based on a tungsten hot-wire and a single thermopile. Devices were fabricated using a commercial 1- $mu text{m}$ SOI-CMOS process followed by a deep reactive ion etching back-etch step to release a silicon dioxide membrane, which mechanically supports and thermally isolates heating and sensing elements. The sensors show an electrothermal transduction efficiency of $50~mu text{W}$ /°C, and a very small zero flow offset. Calibration for wall shear stress measurement in air in the range of 0–0.48 Pa was performed using a suction type, 2-D flow wind tunnel. The sensors were found to be extremely sensitive, up to 4 V/Pa for low wall shear stress values. Furthermore, we demonstrate the superior signal-to-noise ratio (up to five times higher) of a single thermopile readout configuration compared with a double thermopile readout configuration (embedded for comparison purposes within the same device). Finally, we verify that the output of the sensor is proportional to the cube root of the wall shear stress and we propose an accurate semiempirical formula for its modeling.

Description: A kind of low-cost electric and magnetic field simulators, which are used to produce simulative lightning electromagnetic pulse (LEMP) with adjustable waveforms and intensity output, are presented. The lightning electric field can be produced within the GTEM cell by feed-in of impulse voltage output by a Marx generator. The lightning magnetic field can be produced within the coil by feed-in of surge current from the lightning surge generator. The simulated magnetic field is measured by a “B-dot” coil. The measured results show that the lightning electric field simulator and magnetic field simulator could provide relatively homogeneous LEMP environment within certain area in the GTEM cell and the coil within 3 dB deviation. The effects of the simulated lightning electric fields on some electronic devices and the influence of the turns and size of the coil on the homogeneity of the simulated magnetic fields are also investigated.

Description: This paper presents a detailed model of devices utilizing many nanotubes and the coupling between them based on the electromagnetic model of a device using one nanotube. Empirical equations are proposed to link the device conductance with the number of nanotubes per device. Then, a circuit model is developed to predict the effect of the number of nanotubes per device on the overall conductance, capacitance, and the frequency response of the device. A prototype structure is fabricated. Its performance is tested and compared with the proposed model, and it shows promising agreements. The model is flexible and can be integrated with quantum transport models.

Description: A full-wave analysis of the fundamental quasi-TEM modes supported by multiple graphene nanoribbons above a ground plane is presented, aimed at characterizing crosstalk in graphene multiconductor lines. A method-of-moments discretization of the relevant electric-field integral equation is performed. Assuming first a local scalar conductivity, an efficient spatial-domain approach with subsectional basis functions is assuming first a local scalar conductivity, a spatial-domain approach with subsectional basis functions is developed. This allows for the efficient treatment of nanoribbons with wide transverse separations, and can be expanded to include in the simulation model spatial nonuniformity of the graphene conductivity. This spatial-domain formulation is then extended to treat the case of weakly nonlocal conductivity, via an original integro-differential approach derived by approximating a recent full spectral graphene conductivity model in the limit of low wavenumbers. Numerical results are provided for propagation constants and characteristic impedances of two identical coupled graphene nanoribbons; on this basis, a crosstalk analysis is performed by means of the modal decomposition method.

Description: We propose an optical fiber hydrostatic pressure sensor based on micro-cavities generated by the fiber fuse effect. The presented sensor is manufactured through the recycling of optical fiber destroyed by the fiber fuse effect, being, therefore, a cost-effective solution, when compared with other similar micro-cavity-based solutions. The developed sensor was characterized for pressures up to 20 kPa, showing a linear sensitivity coefficient of $0.47pm 0.03~{rm nm}cdot {rm kPa}^{-1}$ , for pressure values below 8 kPa. Furthermore, we propose a new theoretical model to describe the behavior of the microcavities embedded in optical fibers. This allows us to solve the discrepancies, already identified by other authors, between the experimental results and the ones attained with the flat mirrors Fabry-Perot model. By this way, we were able to describe the sensor response, within the full dynamic range.

Description: The monitoring and control of crops in precision agriculture sometimes requires a high collection frequency of information (e.g., temperature, humidity, and salinity) due to the variability in crops. Data acquisition and transmission are generally achieved thanks to wireless sensor networks. However, sensor nodes have limited resources. Thus, it is necessary to adapt the increase in sampling frequency for different crops, under application constraints (reliability, packet delay, and lifetime duration). In this paper, we propose to properly tune IEEE 802.15.4 MAC parameters ( macMinBE and macMaxCSMABackoffs ) and the sampling frequency of deployed sensor nodes. An analytical model of network performance is derived and used to perform the tuning of these tradeoff parameters. Simulation analysis shows that our scheme provides an efficient increase of sampling frequency of sensor nodes while satisfying application requirements.

Description: Sensors based on the magnetoelectric (ME) effect have the potential to be genuine alternatives for measuring bio-magnetic signals. Unfortunately, the sensor structure usually inhibits the problem that several non-magnetic types of noise couple mechanically into the sensor: in this contribution, we will focus on undesired acoustic coupling. Therefore, an adaptive cancellation approach based on a computationally efficient gradient estimation algorithm with a pseudo-optimally control scheme is proposed. The approach is using a microphone as a noise reference sensor and is implemented in real time. An evaluation in terms of measurements is performed inside a magnetically shielded chamber. For a particular scenario, which is characterized by double excitation, an algorithm with binary control-scheme improves the signal-to-noise ratio (SNR) only by around 4dB. If the proposed control scheme is used instead, an improvement of the SNR of around 13dB is achieved.

Description: Target detection is an important issue in the unattended ground sensors. In this paper, inspired by the idea of subspace-based direction of arrival estimation algorithms, a new target detection algorithm called subspace-based target detection (SBTD) is proposed to detect moving targets. The SBTD employs the SNR of the acoustic signals to decide whether moving targets are exiting or not. Although the SBTD has good detection performance, its cost maybe a little high for unattended sensors with low-cost hardware and long-term monitoring. To relieve the cost, we propose the hierarchical detection scheme and develop a two-stage detection method based on the SBTD for target detection in the wild, in which the first stage detection algorithm is chosen from current detection algorithms, while the second stage detection algorithm employs the SBTD. Experiments are conducted to verify the proposed detection method through acoustic signals gathered by the micro-electro-mechanical systems (MEMS) microphone array in the wild. Results show that the detector constructed by our two-stage detection method cannot only estimate the SNR of the acoustic signals but also can reduce the false alarm rate significantly with the detection rate almost unchanged in comparison with the detector chosen by its first-stage detection algorithm. The results indicate that a better detection performance is achieved in terms of the receiver operator characteristic curves.

Description: Crosstalk within cable bundles can degrade system performance. In aircraft systems that use shielded twisted pairs, the crosstalk occurs primarily in the connector where individual signal wires are not shielded or twisted. In many cases, the parameters which determine crosstalk within the connector are unknown because the connector is closed and wires cannot be easily accessed. Expanding on prior research [14] , a methodology for measuring coupling parameters and modeling crosstalk within aircraft cable connectors at low frequencies (〈400 MHz) was developed. The values of mutual inductance and capacitance were extracted from measurements made with a vector network analyzer (VNA). The characteristics of the individual wires were extracted from VNA-measured TDR response. The accuracy of the model was evaluated through comparison of simulated and measured results. Additionally, a closed-form solution was developed to estimate the worst-case envelope of the differential crosstalk. The calculated results match the measured peak values well. This worst-case crosstalk estimate allows effective evaluation of the impact of crosstalk within different connectors. The developed method can be effective for analyzing complex aircraft cable assemblies and connectors without requiring extensive knowledge of the assembly procedure.

Description: Surface roughness topography of printed circuit boards (PCBs) needs to be included in signal integrity simulations in order to accurately predict the insertion loss of the structure and its delay time. An effective roughness dielectric (ERD) model can be used to substitute an inhomogeneous interface between copper foil and laminate dielectric in a PCB. Herein, this approach is tested for verification using 3-D full-wave numerical simulations. These ERD layers with the appropriate complex permittivity are included in the modeling of stripline examples. The parameters of an ambient laminate dielectric refined from conductor roughness in the stripline are determined using differential extrapolation roughness measurement technique. The agreement of the results of 3-D full-wave modeling simulations and measurements on multiple test structures justifies the proposed approach. Based on the extracted ERD parameters “design curves” can be built and used in numerical simulations of PCB high-speed designs.

Description: Biometric systems provide a valuable service in helping to identify individuals from their stored personal details. Unfortunately, with the rapidly increasing use of such systems [1], there is a growing concern about the possible misuse of that information. To counteract the threat, the European Union (EU) has introduced comprehensive legislation [2] that seeks to regulate data collection and help strengthen an individual?s right to privacy. This article looks at the implications of the legislation for biometric system deployment. After an initial consideration of current privacy concerns, the definition of ?personal data? and its protection is examined in legislative terms. Also covered are the issues surrounding the storage of biometric data, including its accuracy, its security, and justification for what is collected. Finally, the privacy issues are illustrated through three biometric use cases: border security, online bank access control, and customer profiling in stores.

Description: The articles in this special section were conceived to champion recent developments in the rapidly evolving field of biometrics and also to encourage research in new signal processing solutions to security and privacy protection. Biometrics is the science of recognizing individuals based on their behavioral and biological characteristics such as face, fingerprints, iris, voice, gait, and signature. The past decade has witnessed a rapid increase in biometrics research in addition to the deployment of large-scale biometrics solutions in both civilian and law enforcement applications. Example applications that incorporate biometric recognition include: logical and physical access systems; surveillance operations to fight against fraud and organized crime; immigration control and border security systems; national identity programs; identity management systems; and the determination of friend or foe in military installations.

Description: A small amount of jitter can quickly eat up timing budgets and create timing issues. Precise characterization of deterministic and crosstalk-induced jitter can help isolate and solve issues within high-speed links. Characterizing deterministic and crosstalk-induced jitter is challenging, however, because many types of jitter work together to create the overall jitter profile. Methods are presented in this paper to characterize the deterministic and crosstalk-induced jitter from measurements of total jitter. An improved tail-fit deconvolution method is proposed for characterizing the impact of deterministic jitter in the presence of random jitter. The contribution of random jitter to total jitter is found first, and then that contribution is accounted for to find deterministic jitter. A Wiener filter deconvolution method is also presented for extracting the characteristics of crosstalk-induced jitter from measurements of total jitter made when the crosstalk sources were and were not present. The Wiener filter allows for accurate deconvolution of the measured histograms for total jitter even in the presence of the measurement noise. The proposed techniques are shown to work well both in simulations and in measurements of a high-speed link.

Description: This paper proposes a new control structure for tasks where explicit disturbance compensation is not only critical for overcoming poor feedback performance but is also challenging due to the complexity and nonrepetitive nature of the interaction between the plant and the environment. The approach proposed uses a particular form of iterative learning control (ILC) to estimate the previous disturbances, which are used as a preview of the disturbance in the next iteration. A disturbance observer is used to compensate for the difference between the ILC prediction and the true disturbance. The controller is evaluated and compared with a proportional controller, with ILC, and with an observer-based controller in extensive field trials using an automated excavator.

Description: This paper explored the possibility of building channel emulators by utilizing fused deposition modeling (FDM) three-dimensional (3-D) printing technology. The FDM 3-D printing provides a rapid and economic method to produce parts with different shapes. An optimizing algorithm was developed for obtaining the printing pattern and loss profile. Parts with different dielectric constants and loss tangents can be printed. Those parts will be placed or directly printed on a low-loss transmission line to modify its transmission or reflection. As a result, different channel emulators can be built to emulate the S -parameter and eye diagrams of a target channel with the advantage of avoiding complicated electronic components and only being limited in the frequency range by the transmission line and attached connectors.

Description: In this paper, we present general considerations for the application of the multiconductor transmission-line theory for simulating shielded spacecraft harness cable assemblies. Some of the practical issues that occur in the modeling process of various components of cable assemblies in spacecraft applications, namely connectors, pigtails, and backshells are discussed. The overall transfer impedance of the assembly measured through a current injection with a pseudomicrostrip line is used as a figure of merit to evaluate the total shielding provided by the harness. Some of the parameters of the model were available from the manufacturers’ datasheets, while others were determined either experimentally or empirically. The position of the cables along the cross section was randomly assigned by the simulation tool. In general, the obtained simulation results are found to be in reasonable agreement with the experimental data. It is found that the generally overlooked contact impedances between the cable shields and connectors play a significant role, especially at low frequencies. The presented simulation results also emphasize the importance of the inductance and resistance of the connector backshell interconnection to the spacecraft chassis.

Description: Encryptions are used in almost all standards to ensure the confidentiality of the data. Encryptions can be and indeed are implemented in the different layers of a network protocol stack. Conventional encryption performs the bitwise XOR operation between one message bit and one key stream bit to generate one ciphertext bit. Huo et al. have recently proposed to provide confidentialities on the user data by performing the phase encryption on the time domain OFDM samples in LTE system. Phase encryption is performed on the modulated symbols, different from the bit level of XOR encryption, i.e., stream cipher encryption. In this paper, we extend their study. We first generalize the phase encryption to general communication systems independent of the underlying modulation scheme. Then, we formulate the mathematical models for XOR and phase encryptions. Based on our model, we compare these two encryption methods in terms of their security and encryption efficiency. We also show phase encryption can resist traffic analysis attack when implemented in the physical layer. Finally, we conduct simulations to compare the performance of these two methods in terms of their decoding symbol error rate.

Description: In this paper, an adaptive hierarchical sparse grid collocation (ASGC) method combined with the discontinuous Galerkin time-domain method is leveraged to quantify the impacts of random parameters on the electromagnetics systems. The ASGC method approximates the stochastic observables of interest using interpolation functions over a set of collocation points determined by the Smolyak's algorithm integrated with an adaptive strategy. Instead of resorting to a full-tensor product sense, the Smolyak's algorithm constructs the collocation points in a hierarchical scheme with the interpolation level. Enhanced by an adaptive strategy, the Smolyak's algorithm will sample more points along important dimensions with sharp variations or discontinuities, resulting in a nonuniform sampling scheme. To flexibly handle different stochastic systems, either piecewise linear or Lagrange polynomial basis functions are applied. With these strategies, the number of collocation points is significantly reduced. The statistical knowledge of stochastic observables including the expected value, variance, probability density function, and cumulative distribution function are presented. The accuracy and robustness of the algorithm are demonstrated by various examples.

Description: Signal integrity (SI) analysis based on state-of-the-art measurements can be difficult to perform especially when the structures of interest are on inner layers of multilayer boards or are enclosed by IC packages. To enable an SI analysis in such cases the authors have recently developed a method that is based on the extraction of accurate simulation models from computed tomography (CT) scans. These models can be used in electromagnetic (EM) field simulators for computer-aided SI analyses. Such CT-based models include geometry variations or defects due to the manufacturing process so that computed EM field simulation results have a good correlation with common measurements. In order to identify the potential of the method an analysis of the required voxel resolution for the extraction of single-ended and differential striplines is presented. The analysis is based on the measurement uncertainty of length measurements in CT scans and an analysis of the propagation of uncertainty for the characteristic impedances of single-ended and differential striplines. This analysis shows that the voxel resolution of industrial CT scans is well suited for the extraction of accurate simulation models which can be used for an SI analysis.

Description: In the millimeter wave (mmW) frequency range, the root mean square height of the through silicon via (TSV) sidewall roughness is comparable to the skin depth, and hence, becomes a critical factor for TSV modeling and analysis. In this paper, the impact of the TSV sidewall roughness on electrical performance, such as the loss and impedance alteration in the mmW frequency range, is examined and analyzed. The second-order small analytical perturbation method is applied to obtain a simple closed-form expression for the power absorption enhancement factor of the TSV. In this study, we propose an electrical model of the TSV, which considers the TSV sidewall roughness effect, the skin effect, and the metal oxide semiconductor effect. The parameters of the proposed circuit model can be determined analytically; the accuracy of the model is validated through a comparison of circuit model behavior for full wave electromagnetic field simulations up to 100 GHz.

Description: Histopathological grading of cancer not only offers an insight to the patients’ prognosis but also helps in making individual treatment plans. Mitosis counts in histopathological slides play a crucial role for invasive breast cancer grading using the Nottingham grading system. Pathologists perform this grading by manual examinations of a few thousand images for each patient. Hence, finding the mitotic figures from these images is a tedious job and also prone to observer variability due to variations in the appearances of the mitotic cells. We propose a fast and accurate approach for automatic mitosis detection from histopathological images. We employ area morphological scale space for cell segmentation. The scale space is constructed in a novel manner by restricting the scales with the maximization of relative-entropy between the cells and the background. This results in precise cell segmentation. The segmented cells are classified in mitotic and non-mitotic category using the random forest classifier. Experiments show at least 12% improvement in $F_{1}$ score on more than 450 histopathological images at $40times $ magnification.

Description: This paper proposes a fast multi-band image fusion algorithm, which combines a high-spatial low-spectral resolution image and a low-spatial high-spectral resolution image. The well admitted forward model is explored to form the likelihoods of the observations. Maximizing the likelihoods leads to solving a Sylvester equation. By exploiting the properties of the circulant and downsampling matrices associated with the fusion problem, a closed-form solution for the corresponding Sylvester equation is obtained explicitly, getting rid of any iterative update step. Coupled with the alternating direction method of multipliers and the block coordinate descent method, the proposed algorithm can be easily generalized to incorporate prior information for the fusion problem, allowing a Bayesian estimator. Simulation results show that the proposed algorithm achieves the same performance as the existing algorithms with the advantage of significantly decreasing the computational complexity of these algorithms.

Description: In recent years, baggage screening at airports has included the use of dual-energy X-ray computed tomography (DECT), an advanced technology for nondestructive evaluation. The main challenge remains to reliably find and identify threat objects in the bag from DECT data. This task is particularly hard due to the wide variety of objects, the high clutter, and the presence of metal, which causes streaks and shading in the scanner images. Image noise and artifacts are generally much more severe than in medical CT and can lead to splitting of objects and inaccurate object labeling. The conventional approach performs object segmentation and material identification in two decoupled processes. Dual-energy information is typically not used for the segmentation, and object localization is not explicitly used to stabilize the material parameter estimates. We propose a novel learning-based framework for joint segmentation and identification of objects directly from volumetric DECT images, which is robust to streaks, noise and variability due to clutter. We focus on segmenting and identifying a small set of objects of interest with characteristics that are learned from training images, and consider everything else as background. We include data weighting to mitigate metal artifacts and incorporate an object boundary field to reduce object splitting. The overall formulation is posed as a multilabel discrete optimization problem and solved using an efficient graph-cut algorithm. We test the method on real data and show its potential for producing accurate labels of the objects of interest without splits in the presence of metal and clutter.

Description: Feature point matching is a fundamental and challenging problem in many computer vision applications. In this paper, a robust feature point matching algorithm named spatial order constraints bilateral-neighbor vote (SOCBV) is proposed to remove outliers for a set of matches (including outliers) between two images. A directed ${k}$ nearest neighbor ( knn ) graph of match sets is generated, and the problem of feature point matching is formulated as a binary discrimination problem. In the discrimination process, the class labeled matrix is built via the spatial order constraints defined on the edges that connect a point to its knn . Then, the posterior inlier class probability of each match is estimated with the knn density estimation and spatial order constraints. The vote of each match is determined by averaging all posterior class probabilities that originate from its associative inliers set and is used for removing outliers. The algorithm iteratively removes outliers from the directed graph and recomputes the votes until the stopping condition is satisfied. Compared with other popular algorithms, such as RANSAC, RSOC, GTM, SOC and WGTM, experiments under various testing data sets demonstrate strong robustness for the proposed algorithm.

Description: Acoustic localization is an essential technique in speech capturing, speech enhancement, video conferencing, and human–robot interaction. However, in practical situations, localization has to be performed in abominable environments, where the presence of reverberation and noise degrades the performance of available position estimates. Besides, the designed systems should be adaptive to locomotion of targets with low computational complexity. In the context, this paper introduces a robust hierarchical acoustic localization method via time-delay compensation (TDC) and interaural matching filter (IMF). Firstly, interaural time-delay (ITD) and interaural level difference (ILD), which are cues involved in first two layers, respectively, are yielded by TDC all at once. Then, a novel feature named IMF, which can eliminate the difference between binaural signals, is proposed in the third layer. The final decision making is based on a Bayesian rule. The relationships among the three layers are that the former layer provides candidate directions for later ones such that the searching space becomes gradually smaller to reduce matching time. Experiments using both a public database and a real scenario verify that TDC and IMF are robust for acoustic localization, and hierarchical system has less consumption time.

Description: Canonical correlation analysis (CCA) is a widely used data analysis tool that allows to assess the correlation between two distinct sets of signals. It computes optimal linear combinations of the signals in both sets such that the resulting signals are maximally correlated. The weight vectors defining these optimal linear combinations are referred to as “principal CCA directions”. In addition to this particular type of data analysis, CCA is also often used as a blind source separation (BSS) technique, i.e., under certain assumptions, the principal CCA directions have certain demixing properties. In this paper, we propose a distributed CCA (DCCA) algorithm that can operate in wireless sensor networks (WSNs) with a fully connected or a tree topology. The algorithm estimates the $Q$ principal CCA directions from the sensor signal observations collected by the different nodes in the WSN and extracts the corresponding sources. These network-wide principal CCA directions are estimated in a time-recursive fashion without explicitly constructing the corresponding network-wide correlation matrices, i.e., without the need for data centralization. Instead, each node locally computes smaller CCA problems and only transmits compressed sensor signal observations (of dimension $Q$ ), which significantly reduces the bit rate over the wireless links of the WSN. We prove convergence and optimality of the DCCA algorithm, and we demonstrate its performance by means of numerical simulations in a blind source separation scenario.

Description: The vision of the Internet of Things (IoT) includes large and dense deployment of interconnected smart sensing and monitoring devices. This vast deployment necessitates collection and processing of large volume of measurement data. However, collecting all the measured data from individual devices on such a scale may be impractical and time-consuming. Moreover, processing these measurements requires complex algorithms to extract useful information. Thus, it becomes imperative to devise distributed information processing mechanisms that identify application-specific features in a timely manner and with low overhead. In this paper, we present a feature extraction mechanism for dense networks that takes advantage of dominance-based medium access control (MAC) protocols to (i) efficiently obtain global extrema of the sensed quantities, (ii) extract local extrema, and (iii) detect the boundaries of events, by using simple transforms that nodes employ on their local data. We extend our results for a large dense network with multiple broadcast domains (MBD). We discuss and compare two approaches for addressing the challenges with MBD and we show through extensive evaluations that our proposed distributed MBD approach is fast and efficient at retrieving the most valuable measurements, independent of the number sensor nodes in the network.

Description: Self-localization is one of the key technologies in the wireless sensor networks (WSN). Some traditional self-localization algorithms can provide a reasonable positioning accuracy only in a uniform and dense network, while for a nonuniform network the performance is not acceptable. In this paper, we presented a novel grid-based linear least squares (LLS) self-localization algorithm. The proposed algorithm uses the grid method to screen the anchors based on the distribution characteristic of a nonuniform network. Furthermore, by taking into consideration the quasi-uniform distribution of anchors in the area, we select suitable anchors to assist the localization. Simulation results demonstrate that the proposed algorithm can greatly enhance the localization accuracy of the anonymous nodes and impose less computation burden compared to traditional Trilateration and Multilateration.

Description: Localization is emerging as a fundamental component in wireless sensor network and is widely used in the field of environmental monitoring, national and military defense, transportation monitoring, and so on. Current localization methods, however, focus on how to improve accuracy without considering the robustness. Thus, the error will increase rapidly when nodes density and SNR (signal to noise ratio) have changed dramatically. This paper introduces CTLL, Cell-Based Transfer Learning Method for Localization in WSNs, a new way for localization which is robust to the variances of nodes density and SNR. The method combines samples transfer learning and SVR (Support Vector Regression) regression model to get a better performance of localization. Unlike past work, which considers that the nodes density and SNR are invariable, our design applies regional division and transfer learning to adapt to the variances of nodes density and SNR. We evaluate the performance of our method both on simulation and realistic deployment. The results show that our method increases accuracy and provides high robustness under a low cost.

Description: Broadcast has critical significance for wide application of wireless sensor networks (WSNs). Minimum-latency broadcast (MLB) studies how to devise a broadcast schedule, which can achieve minimum broadcast latency with no signal interference. In multichannel duty-cycled WSNs, nodes can exploit multiple channels to communicate and periodically fall asleep after working for some time. Nevertheless, most solutions to the MLB problem either focus on nonsleeping scenarios or only exploit one single channel. Therefore, we investigate the MLB problem in multichannel duty-cycled WSNs in this paper and call this problem as MLBCD problem. We prove that MLBCD problem is NP-hard. We propose a new concept of active interference graph (AIG). Based on AIG, we present one novel approximation broadcast algorithm called NAB to solve the MLBCD problem. We prove that our proposed NAB algorithm achieves provable performance guarantee. The results of our extensive evaluations show that NAB algorithm can significantly improve the broadcast latency.

Description: A distributed parallel clustering method MCR-ACA is proposed by integrating the ant colony algorithm with the computing framework Map-Combine-Reduce for mining groups with the same or similar features from big data on vehicle trajectories stored in Wide Area Network. The heaviest computing burden of clustering is conducted in parallel at local nodes, of which the results are merged to small size intermediates. The intermediates are sent to the central node and clusters are generated adaptively. The great overhead of transferring big volume data is avoided by MCR-ACA, which improves the computing efficiency and guarantees the correctness of clustering. MCR-ACA is compared with an existing parallel clustering algorithm on practical big data collected by the traffic monitoring system of Jiangsu province in China. Experimental results demonstrate that the proposed method is effective for group mining by clustering.

Description: This paper investigates the indoor position tracking problem under the variation of received signal strength (RSS) characteristic from the changes of device statuses and environmental factors. A novel indoor position tracking algorithm is introduced to provide reliable position estimates by integrating motion sensor-based positioning (i.e., dead-reckoning) and RSS-based fingerprinting positioning with Kalman filter. In the presence of the RSS variation, RSS-based fingerprinting positioning provides unreliable results due to different characteristics of RSS measurements in the offline and online phases, and the tracking performance is degraded. To mitigate the effect of the RSS variation, a recursive least square estimation-based self-calibration algorithm is proposed that estimates the RSS variation parameters and provides the mapping between the offline and online RSS measurements. By combining the Kalman filter-based tracking algorithm with the self-calibration, the proposed algorithm can achieve higher tracking accuracy even in severe RSS variation conditions. Through extensive computer simulations, we have shown that the proposed algorithm outperforms other position tracking algorithms without self-calibration.

Description: With the development of wireless communication and sensor techniques, source localization based on sensor network is getting more attention. However, fewer works investigate the multiple source localization for binary sensor network. In this paper, a self-adaptive particle swarm optimization based multiple source localization method is proposed. A detection model based on Neyman-Pearson criterion is introduced. Then the maximum likelihood estimator is employed to establish the objective function which is used to estimate the location of sources. Therefore, the multiple-source localization problem is transformed into optimization problem. In order to improve the ability of global search of particle swarm optimization, the self-adaptive particle swarm optimization is used to solve this problem. Various simulations have been conducted, and the results show that the proposed method owns higher localization accuracy in comparison with other methods.

Description: Based on multiobjective particle swarm optimization, a localization algorithm named multiobjective particle swarm optimization localization algorithm (MOPSOLA) is proposed to solve the multiobjective optimization localization issues in wireless sensor networks. The multiobjective functions consist of the space distance constraint and the geometric topology constraint. The optimal solution is found by multiobjective particle swarm optimization algorithm. Dynamic method is adopted to maintain the archive in order to limit the size of archive, and the global optimum is obtained according to the proportion of selection. The simulation results show considerable improvements in terms of localization accuracy and convergence rate while keeping a limited archive size by a method using the global optimal selection operator and dynamically maintaining the archive.

Description: Anomaly detection in wireless sensor networks (WSNs) is critical to ensure the quality of senor data, secure monitoring, and reliable detection of interesting and critical events. The main challenge of anomaly detection algorithm in WSNs is identifying anomalies with high accuracy while consuming minimal resource of the network. In this paper two lightweight anomaly detection algorithms LADS and LADQA are proposed for WSNs. Both algorithms utilize the one-class quarter-sphere support vector machine (QSSVM) and convert the linear optimization problem of QSSVM to a sort problem for the reduced computational complexity. Experimental results show that the proposed algorithms can keep the lower computational complexity without reducing the accuracy for anomaly detection, compared to QSSVM.

Description: In VANETs, frequent beacon broadcasting can lead to high bandwidth consumption and channel congestion. In this paper, a position prediction based beacon approach is proposed to reduce beacon frequency and decrease bandwidth consumption. Vehicles track their neighbors using the predicted position instead of using periodic beacon broadcasting. Only when the prediction error is higher than a predefined tolerance will a beacon broadcasting be triggered. For improving the prediction accuracy, we classify the motion of vehicles into two typical patterns: a constant speed pattern and a maneuvering pattern. A maneuver detection module is responsible for recognizing current motion patterns, and a variable dimension filter that can switch dynamically between the two patterns is employed to generate high accurate position prediction. The simulation results show the proposed scheme can reduce significantly the number of beacons than three existing beacon approaches.

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 demand for higher throughput and more reliable quality of service (QoS) explosive increases the number of base stations in future wireless networks, which causes severe energy waste problems in wireless networks, especially when base stations are in low traffic load status. This paper has two main contributions: first of all, we propose a semistatic energy efficient method to find out the optimal on-off pattern considering the interference from adjacent base stations using integer convex optimization, from which the optimal on-off proportion of base stations could be obtained; then we propose a novel energy efficient cooperative heuristic algorithm in dynamic scenario, by separating the waiting time into two independent Markov processes using the new method; the total power consumption could be reduced significantly by adopting the novel method. Compared with reference method, simulation results indicate that in semistatic scenario, the total system power consumption could be reduced up to 26%, and, in dynamic scenario, the system power consumption could be reduced up to 40%.

Description: Network lifetime plays an important role in the design of wireless sensor networks. This paper studies the problem of prolonging the wireless sensor network’s lifetime, through introducing additional sensors at proper locations to achieve the goal of minimizing the length of the longest edge in the network. The problem is in fact the bottleneck Steiner tree problem, trying to find a Steiner tree minimizing the length of the longest edges for the given terminals in the Euclidean plane by introducing at most Steiner points. A restricted bottleneck Steiner tree problem is studied in this paper, which requires that only degree 3 Steiner points are not allowed to be adjacent in the optimal solution. We show that the restricted problem is MAX-SNP hard and cannot be approximated within performance ratio in polynomial time unless = NP; we first propose a polynomial time -approximation algorithm and then improve the ratio to for any given , by presenting a polynomial time randomized approximation algorithm, which is almost optimal to the restricted problem.

Description: A wireless sensor network (WSN) consists of many resource constraint sensor nodes, which are always deployed in unattended environment. Therefore, the sensor nodes are vulnerable to failure and malicious attacks. The failed nodes have a heavily negative impact on WSNs’ real-time services. Therefore, we propose a task allocation algorithm based on score incentive mechanism (TASIM) for WSNs. In TASIM, the score is proposed to reward or punish sensor nodes’ task execution in cluster-based WSNs, where cluster heads are responsible for task allocation and scores’ calculation. Based on the task scores, cluster members can collaborate with each other to complete complex tasks. In addition, the uncompleted tasks on failed nodes can be timely migrated to other cluster members for further execution. Furthermore, the uncompleted tasks on death nodes can be reallocated by cluster heads. Simulation results demonstrate that TASIM is quite suitable for real-time task allocation. In addition, the performance of the TASIM is clearly better than that of conventional task allocation algorithms in terms of both network load balance and energy consumption.

Description: This paper proposes the improved design of an ultraviolet (UV)- and-blue-light-inhibited white light-emitting diode for use as a safe and practical light source. Covered with a glass substrate coated with a photocatalyst resin on one side and a reflectance film on the other side, wavelengths below 400 nm are reflected back to re-excite the red–green–blue phosphors and, consequently, enhance luminous efficiency. The absorption spectrum of bismuth oxide photocatalysts is below 521 nm, and the leaked UV and blue light can be absorbed, thereby exciting electron–hole pairs and producing the photocatalytic effect. Thus, blue light and UV leakage can be suppressed appreciably, and the luminous efficiency can be increased markedly. Experimental results showed a UV suppression ratio of 88.43% and a visible light increasing ratio of 21.66%. The Commission International de L'Eclairage chromaticity coordinates $(x,y)$ were (0.343, 0.404), the correlated color temperature and the deviation from de Blackbody locus were (5201 K, 0.0250), and the color rendering index was 93.16. In addition, the photocatalyst coating layer can act as a diffuser to provide a comfortable visual experience and facilitate environmental purification.

Description: Metamaterial-based perfect absorbers have attracted considerable attention due to their potential for practical applications. The existing absorbers, however, are mostly polarization insensitive or only sensitive to one direction, which is inapplicable in some areas. Polarization tunable or high absorption in two orthogonal directions is very useful and necessary. Herein, we present a polarization tunable absorber formed by an asymmetric patch and a dielectric layer on top of a metallic board. With this structure, the frequency of the absorber can be tuned by merely changing the polarization of the incident. The tunable mechanism originates from the different length of the patch along the two orthogonal directions. The concept is rather general and applicable to various absorbers, as long as the asymmetric design is valid. The absorber can find practical applications in manipulation of the polarization of the light and detecting waves with specific polarization.

Description: The major activity during speech production is glottal activity and is earlier detected using strength of excitation (SoE). This work uses the normalized autocorrelation peak strength (NAPS) and higher order statistics (HOS) as additional features for detecting glottal activity. The three features, namely, SoE, NAPS, and HOS, are, respectively indicators of different attributes of glottal activity, namely, energy, periodicity, and asymmetrical nature of the resulting source signal. The effectiveness of these features is analyzed using the differential electroglottograph signal, zero-frequency filtered signal, and integrated linear prediction residual, as representatives of source signal. The combination of glottal activity information from the three features outperforms any single of them, demonstrating different information represented by each of these features.

Description: This letter addresses the texture classification problem through a pixel-based local binary pattern (LBP) statistics aggregation mechanism. Real-world texture images often present challenges for classification algorithms in terms of intra-class variability due, among others, to variable illumination. The LBP operator, a state-of-the-art texture descriptor, possesses key properties for tackling real-world texture images: discriminative power and invariance against monotonic gray level changes. We propose a novel texture classification approach that increases the robustness of LBP-based methods with respect to any type of intra-class variations. The method locally characterizes each pixel with an LBP code histogram and globally computes the label of a textured image by aggregating pixel labels through a voting process. Our approach can be in principle applied to any LBP version, as it focuses on how statistics are computed from LBP codes. We show that the proposed pixel-based approach improves upon traditional LBP block-based approaches in terms of classification accuracy by up to 5.1 p.p. on the public Outex database for the classic LBP with various neighborhoods as well as for various LBP extensions.

Description: We present a new trigonometric basis function that is capable of perfectly reproducing circles, spheres and ellipsoids while at the same time being interpolatory. Such basis functions have the advantage that they allow to construct shapes through a sequence of control points that lie on their contour (2-D) or surface (3-D) which facilitates user-interaction, especially in 3-D. Our piecewise exponential basis function has finite support, which enables local control for shape modification. We derive and prove all the necessary properties of the kernel to represent shapes that can be smoothly deformed and show how idealized shapes such as ellipses and spheres can be constructed.

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: Network coding is known to be effective in overcoming packet losses and packet reordering in multihop wireless networks. Despite the benefits, network coding is hard to deploy without being compatible with TCP. To address this problem, a seminal paper proposed a network coding scheme that adopts an ACK-based sliding-widow network coding approach. In this paper we show that the previous scheme may not suffice to mitigate the effects of packets received out of order in multipath wireless networks where severe packet reordering persists. We propose a modified network coding layer where the receiver acknowledges every degree of freedom by using the sequence number of a newly seen packet instead of using that of the oldest unseen packet so that the network coding layer can be compatible with a TCP variant for severe packet reordering. To reduce the decoding matrix size and the coding buffer size, our scheme allows retransmission at the network coding layer. Simulation results show that our scheme outperforms the exiting scheme in multipath wireless networks particularly when severe packet reordering persists.

Description: A practical antenna design combined with a universal serial bus (USB) connector in close vicinity is proposed. In the proposed arrangement, the antenna unit consisted of two planar inverted F antennas (PIFAs) placed on the two sides of the USB connector. The antenna is located at the bottom of the mobile phone to avoid the crowded space on the top side of the phone where various mobile phone accessories are usually assigned. A diplexer is incorporated in the unit to alleviate the adverse effect of the metal USB connector on the radiating efficiency of the antenna. A prototype antenna was fabricated and tested and showed good coverage for GSM850/900/1800/1900, UMTS2100, and LTE700/2500 multibands operation. The overall performances demonstrated the good design of the proposed unit for mobile phone application.

Description: While indoor localization has become a highly growing application domain in the last few years, it is hardly investigated in industrial environments. Interferences of magnetic fields, shadowing, and multipath propagation discourage positioning system vendors from porting their techniques to these harsh environments. However, the actual influence of these interferences on the positioning accuracy and the differences between an industrial and a nonindustrial environment have never been evaluated. This paper analyzes the actual differences for a positioning technique that is based on Wi-Fi fingerprinting, map matching, dead reckoning, filtering, and a plausibility determination. An investigation of the Wi-Fi signal strengths and compass sensor values in an industrial and a nonindustrial environment thereby showed that the differences between them are significant. In fact, it shows that more interferences and shadowing in the industrial environment resulted in even more accurate positioning.

Description: This paper presents design and testing of a shell-encapsulated solar collector which can be used in north area of China for wall-amounting installation. The designed solar collector is based on the combination of a novel compound curved surface concentrator and an aluminum concentric solar receiver, which is contained in a glass evacuated-tube. As there is no perforative joint between the double-skin glass evacuated-tube and the aluminum concentric solar receiver, the difficulty of vacuum keeping for a glass-metal joint is avoided. The cavity shell provides an additional thermal insulation to reduce heat loss of the designed solar collector. The working principle of the compound curved surface concentrator is described. The ray-tracing results are given to show the effect of deviation angle of the concentrator on its optical efficiency, hence determining its maximum acceptance angle. A prototype of the designed solar collector has been constructed and tested under the sunny winter weather condition. The experimental results indicate that the hot water temperature higher than 80°C with a daily average efficiency of about 45~50% has been achieved at the average ambient temperature below 0°C, so the designed solar collector can produce hot water at a useful temperature in winter.

Description: The aim of this work is the development of a network of wireless devices to determine, along with a time-stamp, postural changes of users that are to be used in personalized learning environments. For this purpose, we have designed a basic low-cost pressure sensor that can be built from components easily available. Several of these basic sensors (of sizes and shapes chosen specifically for the task) are integrated into a posture sensor cushion, which is electronically controlled by an Arduino microcontroller board. This accounts for experiments involving either a single cushion to be used by an individual end-user setting approach or classroom approaches where several of these cushions make up a sensor network via ZigBee wireless connections. The system thus formed is an excellent alternative to other more expensive commercial systems and provides a low-cost, easy-to-use, portable, scalable, autonomous, flexible solution with free hardware and software, which can be integrated with other sensing devices into a larger affect detection system, customizable to cope with postural changes at required time intervals and support single and collective oriented experimentation approaches.

Description: This paper proposes a new design technique for internal antenna development. The proposed method is based on the framework of topology optimization incorporated with three effective mechanisms favoring the building blocks of associated optimization problems. Conventionally, the topology optimization of antenna structures discretizes a design space into uniform and rectangular pixels. However, the defining length of the resultant building blocks is so large that the problem difficulty arises; furthermore, the order of the building blocks becomes extremely high, so genetic algorithms (GAs) and binary particle swarm optimization (BPSO) are not more efficient than the random search algorithm. In order to form tight linkage groups of building blocks, this paper proposes a novel approach to handle the design details. In particular, a nonuniform discretization is adopted to discretize the design space, and the initialization of GAs is assigned as orthogonal arrays (OAs) instead of a randomized population; moreover, the control map of GAs is constructed by ensuring the schema growth based on the generalized schema theorem. By using the proposed method, two internal antennas are thus successfully developed. The simulated and measured results show that the proposed technique significantly outperforms the conventional topology optimization.

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: A novel all-glass evacuated tube collector manifold header with an inserted tube is proposed in this paper which makes water in all-glass evacuated solar collector tube be forced circulated to improve the performance of solar collector. And a dynamic numerical model was presented for the novel all-glass evacuated tube collector manifold header water heater system. Also, a test rig was built for model validation and comparison with traditional all-glass evacuated tube collector. The experiment results show that the efficiency of solar water heater with a novel collector manifold header is higher than traditional all-glass evacuated tube collector by about 5% and the heat transfer model of water heater system is valid. Based on the model, the relationship between the average temperature of water tank and inserted tube diameter (water mass flow) has been studied. The results show that the optimized diameter of inserted tube is 32 mm for the inner glass with the diameter of 47 mm and the water flow mass should be less than 1.6 Kg/s.

Description: The performance of a dual-function solar collector (DFSC) that can work as either water heater or air heater depending on seasonal requirement is investigated via both experimental and numerical approaches in this paper. The numerical results are well consistent with the experimental results. Daily efficiency of the thermosiphon system with DFSC is more than 55% in water heating mode and the instantaneous air heating efficiency of the collector reaches 60%. The effects of inner parameters on the thermal efficiency of the collector are analyzed by numerical simulations of the operation of DFSC in two working modes. It is found that the depths of the two air channels in DFSC have an optimal range suitable for both working modes. The thickness of back insulation should be no less than 0.06 m to prevent heat loss via backboard, and the diameter and number of copper tubes show notable effect on the efficiency of DFSC in water heating mode but slight effect in air heating mode.

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: Nuclear power plants are highly complex systems and the issues related to their safety are of primary importance. Probabilistic safety assessment is regarded as the most widespread methodology for studying the safety of nuclear power plants. As maintenance is one of the most important factors for affecting the reliability and safety, an enhanced preventive maintenance optimization model based on a three-stage failure process is proposed. Preventive maintenance is still a dominant maintenance policy due to its easy implementation. In order to correspond to the three-color scheme commonly used in practice, the lifetime of system before failure is divided into three stages, namely, normal, minor defective, and severe defective stages. When the minor defective stage is identified, two measures are considered for comparison: one is that halving the inspection interval only when the minor defective stage is identified at the first time; the other one is that if only identifying the minor defective stage, the subsequent inspection interval is halved. Maintenance is implemented immediately once the severe defective stage is identified. Minimizing the expected cost per unit time is our objective function to optimize the inspection interval. Finally, a numerical example is presented to illustrate the effectiveness of the proposed models.

Description: An integrated deterministic and probabilistic safety analysis (IDPSA) was carried out to assess the performances of the firefighting means to be applied in a nuclear power plant. The tools used in the analysis are the code FDS (Fire Dynamics Simulator) for fire simulation and the tool MCDET (Monte Carlo Dynamic Event Tree) for handling epistemic and aleatory uncertainties. The combination of both tools allowed for an improved modelling of a fire interacting with firefighting means while epistemic uncertainties because lack of knowledge and aleatory uncertainties due to the stochastic aspects of the performances of the firefighting means are simultaneously taken into account. The MCDET-FDS simulations provided a huge spectrum of fire sequences each associated with a conditional occurrence probability at each point in time. These results were used to derive probabilities of damage states based on failure criteria considering high temperatures of safety related targets and critical exposure times. The influence of epistemic uncertainties on the resulting probabilities was quantified. The paper describes the steps of the IDPSA and presents a selection of results. Focus is laid on the consideration of epistemic and aleatory uncertainties. Insights and lessons learned from the analysis are discussed.

Description: In this paper we evaluate the impact of a power uprate on a pressurized water reactor (PWR) for a tsunami-induced flooding test case. This analysis is performed using the RISMC toolkit: the RELAP-7 and RAVEN codes. RELAP-7 is the new generation of system analysis codes that is responsible for simulating the thermal-hydraulic dynamics of PWR and boiling water reactor systems. RAVEN has two capabilities: to act as a controller of the RELAP-7 simulation (e.g., component/system activation) and to perform statistical analyses. In our case, the simulation of the flooding is performed by using an advanced smooth particle hydrodynamics code called NEUTRINO. The obtained results allow the user to investigate and quantify the impact of timing and sequencing of events on system safety. In addition, the impact of power uprate is determined in terms of both core damage probability and safety margins.

Description: In case of some nuclear power plants constructed at the soft soil sites, liquefaction should be analysed as beyond design basis hazard. The aim of the analysis is to define the postevent condition of the plant, definition of plant vulnerabilities, and identification of the necessary measures for accident management. In the paper, the methodology of the analysis of liquefaction effects for nuclear power plants is outlined. The procedure includes identification of the scope of the safety analysis and the acceptable limit cases for plant structures having different role from accident management point of view. Considerations are made for identification of dominating effects of liquefaction. The possibility of the decoupling of the analysis of liquefaction effects from the analysis of vibratory ground motion is discussed. It is shown in the paper that the practicable empirical methods for definition of liquefaction susceptibility provide rather controversial results. Selection of method for assessment of soil behaviour that affects the integrity of structures requires specific considerations. The case of nuclear power plant at Paks, Hungary, is used as an example for demonstration of practical importance of the presented results and considerations.

Description: The loss of off-site power (LOOP) event occurs when all electrical power to the nuclear power plant from the power grid is lost. Complete failure of both off-site and on-site alternating current (AC) power sources is referred to as a station blackout (SBO). Combined LOOP and SBO events are analyzed in this paper. The analysis is done for different time delays between the LOOP and SBO events. Deterministic safety analysis is utilized for the assessment of the plant parameters for different time delays of the SBO event. Obtained plant parameters are used for the assessment of the probabilities of the functional events in the SBO event tree. The results show that the time delay of the SBO after the LOOP leads to a decrease of the core damage frequency (CDF) from the SBO event tree. The reduction of the CDF depends on the time delay of the SBO after the LOOP event. The results show the importance of the safety systems to operate after the plant shutdown when the decay heat is large. Small changes of the basic events importance measures are identified with the introduction of the delay of the SBO event.

Description: We demonstrate low-voltage waveguide-coupled germanium avalanche photodetectors (APDs) with a (wafer-scale mean) gain $times$ bandwidth product of 140 GHz at $-$ 5 V by utilizing a 185-nm-thick Ge layer. An optical receiver based on such an APD operating up to 25 Gb/s is demonstrated.

Description: The realization of high-efficiency organic small molecule: Fullerene solar cells are challenging but become more and more feasible due to the rapid development in donor materials and device fabrication techniques. In the past several years, the optimization in the processing techniques, such as, solvent vapor annealing (SVA), the use of solvent additives had led to superior improvement in the device performance of organic solar cells from different donor systems, but at an expense of reduction in the open-circuit voltage ( $V_{{rm OC}}$ ). In this paper, we report that the overall device performance of the organic small molecule solar cells (SMSCs) can be significantly enhanced through a two-step process consisting of SVA and thermal annealing (TA) (short for SVA+TA), especially the reduction in $V_{{rm OC}}$ can be effectively avoided in case of exclusive use of SVA. The carrier dynamics is determined by transient photovoltage and transient photocurrent measurements, which can provide information on the origin of enhanced device performance upon the two-step annealing. The observed $V_{{rm OC}}$ recovery is attributed to the preferable change in charge dynamic, thus, leading to a superior overall device performance. Furthermore, the SVA and the consequential TA are complementary to each other; thus, the two-step annealing method represents a feasible route to simultaneously improve the $V_{{rm OC}}$ , $J_{{rm SC}}$ , FF, and PCE of SMSCs.