ALBERT

Description: With the convening of the annual global climate conference, the issue of global climate change has gradually become the focus of attention of the international community. As the largest carbon emitter in the world, China is facing a serious situation of carbon emission reduction. This paper uses the IPCC (The Intergovernmental Panel on Climate Change) method to calculate the carbon emissions of energy consumption in China from 1996 to 2016, and uses it as a dependent variable to analyze the influencing factors. In this paper, five factors, total population, per capita GDP (Gross Domestic Product), urbanization level, primary energy consumption structure, technology level, and industrial structure are selected as the influencing factors of carbon emissions. Based on the expanded STIRPAT (Stochastic Impacts by Regression on Population, Affluence, and Technology) model, the influencing degree of different factors on carbon emissions of energy consumption is analyzed. The results show that the order of impact on carbon emissions from high to low is total population, per capita GDP, technology level, industrial structure, primary energy consumption structure, and urbanization level. On the basis of the above research, the carbon emissions of China′s energy consumption in the future are predicted under eight different scenarios. The results show that, when the population and economy keep a low growth rate, while improving the technology level can effectively control carbon emissions from energy consumption, China′s carbon emissions from energy consumption will reach 302.82 million tons in 2020.

Description: To solve the self-alignment problem of the Strapdown Inertial Navigation System (SINS), a novel adaptive filter based on Complementary Ensemble Empirical Mode Decomposition (CEEMD) is proposed. The Gravitational Apparent Motion (GAM) is used in the coarse alignment, and the problem of obtaining the attitude matrix between the body frame and the navigation frame is attributed to obtaining the matrix between the initial body frame and the current navigation frame using two gravitational apparent motion vectors at different moments. However, the accuracy and time of this alignment method always suffer from the measurement noise of sensors. Thus, a novel adaptive filter based on CEEMD using an l 2 -norm to calculate the similarity measure between the Probability Density Function (PDF) of each Intrinsic Mode Function (IMF) and the original signal is proposed to denoise the measurements of the accelerometer. Furthermore, the advantage of this filter is verified by comparing with other conventional denoising methods, such as PDF-based EMD (EMD-PDF) and the Finite Impulse Response (FIR) digital low-pass filter method. The results of the simulation and experiments indicate that the proposed method performs better than the conventional methods in both alignment time and alignment accuracy.

Description: The motivation of this work is to help outpatients find their corresponding departments or clinics, thus, it needs to provide indoor positioning services with a room-level accuracy. Unlike wireless outdoor localization that is dominated by the global positioning system (GPS), wireless indoor localization is still an open issue. Many different schemes are being developed to meet the increasing demand for indoor localization services. In this paper, we investigated the AoA-based wireless indoor localization for outpatients’ wayfinding in a hospital, where Wi-Fi access points (APs) are deployed, in line, on the ceiling. The target position can be determined by a mobile device, like a smartphone, through an efficient geometric calculation with two known APs coordinates and the angles of the incident radios. All possible positions in which the target may appear have been comprehensively investigated, and the corresponding solutions were proven to be the same. Experimental results show that localization error was less than 2.5 m, about 80% of the time, which can satisfy the outpatients’ requirements for wayfinding.

Description: Model-free reinforcement learning is a powerful and efficient machine-learning paradigm which has been generally used in the robotic control domain. In the reinforcement learning setting, the value function method learns policies by maximizing the state-action value (Q value), but it suffers from inaccurate Q estimation and results in poor performance in a stochastic environment. To mitigate this issue, we present an approach based on the actor-critic framework, and in the critic branch we modify the manner of estimating Q-value by introducing the advantage function, such as dueling network, which can estimate the action-advantage value. The action-advantage value is independent of state and environment noise, we use it as a fine-tuning factor to the estimated Q value. We refer to this approach as the actor-dueling-critic (ADC) network since the frame is inspired by the dueling network. Furthermore, we redesign the dueling network part in the critic branch to make it adapt to the continuous action space. The method was tested on gym classic control environments and an obstacle avoidance environment, and we design a noise environment to test the training stability. The results indicate the ADC approach is more stable and converges faster than the DDPG method in noise environments.

Description: In sensor-based systems, the data of an object is often provided by multiple sources. Since the data quality of these sources might be different, when querying the observations, it is necessary to carefully select the sources to make sure that high quality data is accessed. A solution is to perform a quality evaluation in the cloud and select a set of high-quality, low-cost data sources (i.e., sensors or small sensor networks) that can answer queries. This paper studies the problem of min-cost quality-aware query which aims to find high quality results from multi-sources with the minimized cost. The measurement of the query results is provided, and two methods for answering min-cost quality-aware query are proposed. How to get a reasonable parameter setting is also discussed. Experiments on real-life data verify that the proposed techniques are efficient and effective.

Description: The social investment, natural resource consumption, and pollutant emissions involved in steel production can be evaluated comprehensively using the emergy analysis. We explored the sustainability of the steel production system from four aspects: input index, output index, input–output index, and sustainability index. The results showed that the maximum inputs were the intermediate product/recyclable materials produced within the production line; energy sources were mainly non-renewable and the emergy value of pollutants discharged was rather low. The environmental load rate of the pelletizing and sintering processes were the highest and the proportion of recycled materials for puddling and steel-making were the highest. The emergy investment rate of rolling was the highest; the emergy value of the pollutants discharged in each process was very small, and the emergy yield ratio was highest in the rolling process. Pelletizing, sintering, and steel-making were input consuming processes, but the sustainability index of puddling and rolling processes was sound. The whole process line can be sustainable, considering the useful intermediate and recyclable products.

Description: High strength steel has attracted a lot of attention due to its excellent advantage of weight reduction. A thin Al-Si coating covered on the surface of hot-press-forming (HPF) steel offers functions of antioxidation and decarburization under high temperature processing conditions. In this study, the microstructure characteristic, phase, microhardness, and tensile strength of laser welded Al-Si coated HPF steel joints were investigated at different laser powers. Experimental results show that the welding process becomes unstable because of metallic vapor generated by ablation of the coating. Some of the white bright rippled Fe-Al phase was observed to be distributed in the fusion zone randomly. It is found that microhardness, tensile strength, and cupping test qualification rate decreases with the increase of the laser power. For the 1.1 kW laser power, the sound weld performs the best mechanical properties: Microhardness of 466.53 HV and tensile strength of 1349.9 MPa.

Description: In this research a DNA aptamer, which was selected through SELEX (systematic evolution of ligands by exponential enrichment) to be specific against the H5N1 subtype of the avian influenza virus (AIV), was used as an alternative reagent to monoclonal antibodies in an impedance biosensor utilizing a microfluidics flow cell and an interdigitated microelectrode for the specific detection of H5N1 AIV. The gold surface of the interdigitated microelectrode embedded in a microfluidics flow cell was modified using streptavidin. The biotinylated aptamer against H5N1 was then immobilized on the electrode surface using biotin–streptavidin binding. The target virus was captured on the microelectrode surface, causing an increase in impedance magnitude. The aptasensor had a detection time of 30 min with a detection limit of 0.0128 hemagglutinin units (HAU). Scanning electron microscopy confirmed the binding of the target virus onto the electrode surface. The DNA aptamer was specific to H5N1 and had no cross-reaction to other subtypes of AIV (e.g., H1N1, H2N2, H7N2). The newly developed aptasensor offers a portable, rapid, low-cost alternative to current methods with the same sensitivity and specificity.

Description: This paper takes advantage of the complementary characteristics of Global Positioning System (GPS) and Light Detection and Ranging (LiDAR) to provide periodic corrections to Inertial Navigation System (INS) alternatively in different environmental conditions. In open sky, where GPS signals are available and LiDAR measurements are sparse, GPS is integrated with INS. Meanwhile, in confined outdoor environments and indoors, where GPS is unreliable or unavailable and LiDAR measurements are rich, LiDAR replaces GPS to integrate with INS. This paper also proposes an innovative hybrid scan matching algorithm that combines the feature-based scan matching method and Iterative Closest Point (ICP) based scan matching method. The algorithm can work and transit between two modes depending on the number of matched line features over two scans, thus achieving efficiency and robustness concurrently. Two integration schemes of INS and LiDAR with hybrid scan matching algorithm are implemented and compared. Real experiments are performed on an Unmanned Ground Vehicle (UGV) for both outdoor and indoor environments. Experimental results show that the multi-sensor integrated system can remain sub-meter navigation accuracy during the whole trajectory.

Description: The occurrence of fluoroquinolone antibiotics in wastewater has drawn great attention. Adsorption of widely used fluoroquinolone antibiotics (enrofloxacin and ofloxacin) in wastewater using bamboo biochar was investigated. More than 99% of fluoroquinolone antibiotics were removed from the synthetic wastewater through adsorption. Adsorption capacities of bamboo biochar slightly changed when pH increased from 3.0 to 10.0. The adsorption capacity of bamboo biochar increased sharply when the initial concentration of enrofloxacin or ofloxacin increased from 1 to 200 mg L−1 and then began to plateau with further increases in initial concentration. The maximum adsorption capacity (45.88 ± 0.90 mg·g−1) was observed when the ratio of bamboo biochar to fluoroquinolone antibiotics was 10. The enrofloxacin adsorption capacity of bamboo biochar decreased from 19.91 ± 0.21 mg·g−1 to 14.30 ± 0.51 mg·g−1 while that of ofloxacin decreased from 19.82 ± 0.22 mg·g−1 to 13.31 ± 0.56 mg·g−1 when the NaCl concentrations increased from 0 to 30 g·L−1. The adsorptions of fluoroquinolone on bamboo biochar have isotherms that obeyed the Freundlich model (r2 values were in the range of 0.990–0.991).