A Topology Control Approach Reducing Construction Cost for Lossy Wireless Sensor Networks

In lossy wireless sensor networks, many links suffer from significant quality variation with time and environments. Topology control approaches need to consider such stochastic nature to yield different topologies for different application requirements. However, the metric of links must be timely obtained to speed up the topology construction. In fact, the existing approaches address it by passive monitoring, which is not timely adaptive to link quality variation. Also, timely access to the metric of all links at all power levels causes a large burden on topology control operation. We do not insist on getting the link metrics of all power levels at a time. Most urgently needed link metrics are firstly obtained by an active probing mode in this paper. If these link metrics do not meet the topology performance requirements, sub-urgently needed link metrics will be obtained on demand. At the same time, each node performs a topology control process based on the information in a smaller range (e.g., 1-hop neighborhood). Therefore, our approach has the low construct cast, which is proved in this paper. The simulation results also show that our approach outperforms the existing typical works in terms of average transmission power level, though it is slightly less efficient in terms of average delivery rate, average end-to-end delay and total energy consumption. In addition, our approach has advantage in terms of standard deviation of remaining energy under the relatively smaller required path quality bound or lower node density.     

Comparison of Performance of Packet Scheduling Algorithms in LTE-A HetNets

The concept of usage of heterogeneous networks (HetNets) is about improving the LTE system performance by increasing the capacity and coverage of the Macro cell. In this paper, a performance comparison of various packet scheduling algorithms such as Proportional Fair, Maximum Largest Weighted Delay First and Exponential/Proportional Fair is studied in detail in the HetNets environment. The key performance indicators such as throughput, packet loss ratio, delay and fairness are considered to judge the performance of the scheduling algorithms. Various strategies such as increasing the number of Pico cells in the cell edge were used in the simulation for the performance evaluation study. The results achieved through various simulations show that adding Pico cells to the existing Macros enhances the overall system performance in addition to the various scheduling algorithms implemented in Macros. For reader’s convenience, various types of graphs have been used to represent the simulation results to better understand the performance metrics of various scheduling algorithms. Simulation results shows that overall system gain has increased because of adding Picos and thereby providing better coverage in the cell edge areas and thereby increasing the capacity of the network to provide better quality of service.     

The PPG Physiological Signal for Heart Rate Variability Analysis

The photoplethysmography (PPG) sensor can be applied to measure the situation and function of human blood circulation. The PPG sensor is not only existed the characteristics of simple, convenient and low price but also easy non-invasive to measure physiological signal. The advantage of PPG signal is easy to measure from various sensing location. The physiological information of the clinical detection method is broadly implemented for such type. In this paper, we utilize “the green LED reflective” PPG sensor to capture physiological signals operated in static and exercise modes. Therefore, we adopted the short-term measurement in 5 min. Those captured signals are divided into five segments and 1 min for each segment. We calculated heart beats per minute and heart rate variability (HRV) operated in time domain analysis criteria. The related theory of short-time Fourier transform (STFT) combined with power spectral density (PSD) is implemented for finding HRV in frequency domain analysis. Then, we derived random process theory and the autocorrelation function which are verified the PPG measurement is stationary process or not. In the future experiment, we can compare the 24 h data with the previous results. Consequently, we apply the physical health status monitoring of long-term and short-term modes to observe subject varies of HRV and ANS after listening music concurrently.     

A Simple Method for the Growth of Very Smooth and Ultra-Thin GaSb Films on GaAs (111) Substrate by MOCVD

We present a simple thermal treatment with the antimony source for the metal–organic chemical vapor deposition of thin GaSb films on GaAs (111) substrates for the first time. The properties of the as-grown GaSb films are systematically analyzed by scanning electron microscopy, atomic force microscopy, x-ray diffraction, photo-luminescence (PL) and Hall measurement. It is found that the as-grown GaSb films by the proposed method can be as thin as 35 nm and have a very smooth surface with the root mean square roughness as small as 0.777 nm. Meanwhile, the grown GaSb films also have high crystalline quality, of which the full width at half maximum of the rocking-curve is as small as 218 arcsec. Moreover, the good optical quality of the GaSb films has been demonstrated by the low-temperature PL. This work provides a simple and feasible buffer-free strategy for the growth of high-quality GaSb films directly on GaAs substrates and the strategy may also be applicable to the growth on other substrates and the hetero-growth of other materials.     

Stochastic convergence analysis of recursive successive over-relaxation algorithm in adaptive filtering

A stochastic convergence analysis of the parameter vector estimation obtained by the recursive successive over-relaxation (RSOR) algorithm is performed in mean sense and mean-square sense. Also, excess of mean-square error and misadjustment analysis of the RSOR algorithm is presented. These results are verified by ensemble-averaged computer simulations. Furthermore, the performance of the RSOR algorithm is examined using a system identification example and compared with other widely used adaptive algorithms. Computer simulations show that the RSOR algorithm has better convergence rate than the widely used gradient-based algorithms and gives comparable results obtained by the recursive least-squares RLS algorithm.     

Sharpening filter for false color imaging of dual-energy X-ray scans

Dual-energy X-ray imaging has a vast range of application in security. Luggage inspection is an essential process for an airplane or court house security as well as securing mass events. An image of a content of some package may help to figure out if there is any dangerous object inside and avoid possibly threatening situation. As the raw X-ray images are not always easy to analyze and interpret, some image processing methods like an object detection, a frequency resolution increase or a pseudocoloring are being used. Since color can be a powerful tool to improve the usefulness of an information display, we propose pseudocoloring improvement by modifying material-based approach with edge detection to fill and sharpen color layers over the image making it easier to read and analyze. We demonstrate the effectiveness of the methods using real data, acquired from a professional dual-energy X-ray scanner.     

Analysis of fractal inter frame video coding using parallel approach

Digital video has many applications varying from telecommunications to broadcasting and so on. Video compression techniques have evolved over the past two decades with prominent technique being developed using fractal. However, this technique was not so popular because of its computationally intensive nature. This paper proposes an inter frame video compression technique, which consists of a combination of a block matching using fractal compression. The proposed algorithm is implemented on CUDA-enabled GPU which significantly reduces the encoding time of the video and provides a very high compression ratio with reasonable quality of the decoded video. Extensive simulations were carried out to analyze the performance of the proposed algorithm.     

A fast method for moving object detection in video surveillance image

Moving object detection and extraction are widely used in video surveillance and image processing. In this paper, we present a fast method for moving object detection. We use weights of the Gaussian distribution as decision factors, update parameters of the Gaussian mixture model if its values are smaller than that of those not belonging to the background; otherwise, no updates are done. It improves the existing methods by updating the Gaussian mixture model selectively. Experimental results on various scenes of video surveillance show that computation time of the proposed method is reduced.     

DSTBC experimental research on UV communication system

Diversity gain can be obtained by applying the space–time block code (STBC) technology to ultraviolet (UV) communication. However, some STBCs, for example, the Alamouti code, quite depend on the acquisition of UV channel state information (CSI) because the accuracy of the obtained CSI influences the quality of the received signal and finally influences the system performance. Yet it is not easy to precisely obtain CSI, and this will affect the validity of some STBC decoding. To solve this problem, this paper tends to study the application of differential space–time block code (DSTBC) technology in the UV communication system. The validity with the exact diversity gain is verified with simulation and experimental results. The processes of the transmitters and receivers in \(2\times 2\) DSTBC are analyzed, and the different UV system performances in different communication situations are acquired. The algorithm complexity of DSTBC is compared with that of Alamouti code. The conclusion then is that the advantage of the DSTBC scheme with no requirement of obtaining real-time CSI is found in the fast time-varying and quick decaying UV channel.