Recently, radar resource management of multifunction radar is a challenging issue in electronically scanned array radar technology. This paper deals with radar beam scheduling, which is a core issue of radar resource management. This paper proposed stochastic scheduler algorithm using Simulated Annealing (SA) and Hybrid scheduler algorithm which automatically selects two different types of schedulers according to the radar load: Rule based scheduler using modified Butler algorithm for underload situations and SA based scheduler for overload situations. The proposed algorithms are evaluated in terms of scheduling latency, the number of scheduled tasks, and time complexity. The simulation results show that the performance of rule based scheduler is seriously degraded in overload situation. However, SA based scheduler and Hybrid scheduler have graceful performance degradation in overload situation. Compared with rule based scheduler, SA based scheduler and Hybrid scheduler can schedule many more tasks on time for the same operation duration in the overload situation. Even though their time complex is relatively high, it can be applied to real applications if the parameters are properly controlled. Especially, Hybrid scheduler has an advantage of low time complexity with good performance.

This letter introduces a new reference frame to improve the performance of motion estimation and compensation in video coding, based on a video stabilization technique. The proposed method synthesizes the new reference frame from the previous frame in a way that the new reference and current frames have the same camera orientations. The overhead data for each frame to transmit from an encoder to a decoder is only three rotational angles along the x, y, and z axes. Since the new reference and current frames have the same camera orientations, the proposed method significantly improves the performance of motion estimation and compensation for video sequences having dynamic camera motion by up to 0.98 dB with negligible overhead data.

Local descriptors, Local Binary Pattern (LBP) and Scale Invariant Feature Transform (SIFT) are widely used in various computer applications. They emphasize different aspects of image contents. In this letter, we propose to combine them in sparse coding for categorizing scene images. First, we regularly extract LBP and SIFT features from training images. Then, corresponding to each feature, a visual word codebook is constructed. The obtained LBP and SIFT codebooks are used to create a two-dimensional table, in which each entry corresponds to an LBP visual word and a SIFT visual word. Given an input image, LBP and SIFT features extracted from the same positions of this image are encoded together based on sparse coding. After that, spatial max pooling is adopted to determine the image representation. Obtained image representations are converted into one-dimensional features and classified by utilizing SVM classifiers. Finally, we conduct extensive experiments on datasets of Scene Categories 8 and MIT 67 Indoor Scene to evaluate the proposed method. Obtained results demonstrate that combining features in the proposed manner is effective for scene categorization.

In this paper, we introduced a novel Kernel-Reliability-based K-Means (KRKM) clustering algorithm for categorizing an unknown dataset under noisy condition. Compared with the conventional clustering algorithms, the proposed KRKM algorithm will measure both the reliability and the similarity for classifying data into its neighbor clusters by the dynamic kernel functions, where the noisy data will be rejected by being given low reliability. The reliability for classifying data is measured by a dynamic kernel function whose window size will be determined by the triangular relationship from this data to its two nearest clusters. The similarity from a data item to its neighbor clusters is measured by another adaptive kernel function which takes into account not only the similarity from data to clusters but also that between its two nearest clusters. The main contribution of this work lies in introducing the dynamic kernel functions to evaluate both the reliability and similarity for clustering, which makes the proposed algorithm more efficient in dealing with very strong noisy data. Through various experiments, the efficiency and effectiveness of proposed algorithm have been confirmed.

For break arcs occurring between Ag and Ag/SnO$_2$ 12,wt% electrical contact pairs, the electrical conductivity, viscosity and specific heat at constant pressure are calculated as thermodynamic and transport properties. Mixture rates of contact material vapor are 0%, 1%, 10% and 100%. Influence of the contact material on the properties is investigated. Temperature for the calculation ranges from 2000,K to 20000,K. Following results are shown. When the mixture rate is changed, the electrical conductivity varies at lower temperature (< 10000,K), and the viscosity and specific heat vary widely at all temperature range. The electrical conductivity is independent of the mixture rate when the temperature is exceeding 10000,K. The thermodynamic and transport properties are independent of the kind of the contact materials.

We discuss the division of radio resources in the time and frequency domains for wireless local area network (WLAN) devices powered with microwave energy. In general, there are two ways to avoid microwave power transmission (MPT) from influencing data communications: adjacent channel operation of continuous MPT and WLAN data transmission and co-channel operation of intermittent MPT and WLAN data transmission. Experimental results reveal that, even when we implement these methods, several problems arise because WLAN devices have been developed without supposing the existence of MPT. One problem clarified in our experiment is that adjacent channel operation at 2.4GHz does not necessarily perform well owing to the interference from MPT. This interference occurs regardless of the frequency separation at 2.4GHz. The other problem is that intermittent MPT could result in throughput degradation owing to the data rate control algorithm and the association scheme of the WLAN. In addition, the experimental results imply that a microwave energy source and a WLAN device should share information on the timings of intermittent MPT and data transmission to avoid buffer overflow.

This paper presents a graph-based approach to designing arithmetic circuits over Galois fields (GFs) using normal basis representations. The proposed method is based on a graph-based circuit description called Galois-field Arithmetic Circuit Graph (GF-ACG). First, we extend GF-ACG representation to describe GFs defined by normal basis in addition to polynomial basis. We then apply the extended design method to Massey-Omura parallel multipliers which are well known as typical multipliers based on normal basis. We present the formal description of the multipliers in a hierarchical manner and show that the verification time can be greatly reduced in comparison with those of the conventional techniques. In addition, we design GF exponentiation circuits consisting of the Massey-Omura parallel multipliers and an inversion circuit over composite field GF(((22)2)2) in order to demonstrate the advantages of normal-basis circuits over polynomial-basis ones.

Feedback data loss can severely degrade overall system performance. In addition, it can affect the control and computation of the Cyber-physical Systems (CPS). CPS hold enormous potential for a wide range of emerging applications that include different data traffic patterns. These data traffic patterns have wide varieties of diversities. To recover various traffic patterns we need to know the nature of their underlying property. In this paper, we propose a data recovery framework for different traffic patterns of CPS, which comprises data pre-processing step. In the proposed framework, we designed a Data Pattern Analyzer to classify the different patterns and built a model based on the pattern as a data pre-processing step. Inside the framework, we propose a data recovery scheme, called Efficient Temporal and Spatial Data Recovery (ETSDR) algorithm to recover the incomplete feedback for CPS to maintain real time control. In this algorithm, we utilize the temporal model based on the traffic pattern and consider the spatial correlation of the nearest neighbor sensors. Numerical results reveal that the proposed ETSDR outperforms both the weighted prediction (WP) and the exponentially weighted moving average (EWMA) algorithms regardless of the increment percentage of missing data in terms of the root mean square error, the mean absolute error, and the integral of absolute error.

Optical interfaces have been recently standardized as the main physical layer interfaces for most short length optical communication systems, such as IEEE802.3ae, OIF-VSR, and the Fiber Channel. As interface speed increases, the requirements for forecasting the optical characteristics of direct modulated laser diodes (LDs) also increase because those standards define the specifications for physical layers with optical domains. In this paper, a vertical-cavity surface-emitting laser (VCSEL) equivalent electronic circuit model is described with which designers can simulate the $I-L-V$, S-parameter, and transient characteristics of LDs on a circuit simulator by improving convergence. We show that the proposed VCSEL model can model an 850-nm bandwidth VCSEL with 10-Gbps operation.

At present, vast numbers of information resources are available on the Internet. However, one emerging issue is how to search and exploit these information resources in an efficient and flexible manner with high scalability. In this study, we focused our attention on the design of a distributed hash table (DHT)-based search system that supports efficient scalable multi-attribute queries of information resources in a distributed manner. Our proposed system, named D-AVTree, is built on top of a ring-based DHT, which partitions a one-dimensional key space across nodes in the system. It utilizes a descriptive naming scheme, which names each resource using an attribute-value (AV) tree, and the resource names are mapped to d-bit keys in order to distribute the resource information to responsible nodes based on a DHT routing algorithm. Our mapping scheme maps each AV branch of a resource name to a d-bit key where AV branches that share a subsequence of AV pairs are mapped to a continuous portion of the key space. Therefore, our mapping scheme ensures that the number of resources distributed to a node is small and it facilitates efficient multi-attribute queries by querying only a small number of nodes. Further, the scheme has good compatibility with key-based load balancing algorithms for DHT-based networks. Our system can achieve both efficiency and a good degree of load balancing even when the distribution of AV pairs in the resource names is skewed. Our simulation results demonstrated the efficiency of our solution in terms of the distribution cost, query hit ratio, and the degree of load balancing compared with conventional approaches.

We proposed a method for estimating sound source positions in 3D space by integrating sound directions estimated by multiple microphone arrays and taking advantage of reflection information. Two types of sources with different directivity properties (human speech and loudspeaker speech) were evaluated for different positions and orientations. Experimental results showed the effectiveness of using reflection information, depending on the position and orientation of the sound sources relative to the array, walls, and the source type. The use of reflection information increased the source position detection rates by 10% on average and up to 60% for the best case.

Binaural reproduction is one of the promising approaches to present a highly realistic virtual auditory space to a listener. Generally, binaural signals are reproduced using a set of headphones that leads to a simple implementation of such a system. In contrast, binaural signals can be presented to a listener using a technique called “transaural reproduction” which employs a few loudspeakers with crosstalk cancellation for compensating acoustic transmissions from the loudspeakers to both ears of the listener. The major advantage of transaural reproduction is that a listener is able to experience binaural reproduction without wearing any device. This leads to a more natural listening environment. However, in transaural reproduction, the listener is required to be still within a very narrow sweet spot because the crosstalk canceller is very sensitive to the listener's head position and orientation. To solve this problem, dynamic transaural systems have been developed by utilizing contact type head tracking. This paper introduces the development of a dynamic transaural system with non-contact head tracking which releases the listener from any attachment, thereby preserving the advantage of transaural reproduction. Experimental results revealed that sound images presented in the horizontal and median planes were localized more accurately when the system tracked the listener's head rotation than when the listeners did not rotate their heads or when the system did not track the listener's head rotation. These results demonstrate that the system works effectively and correctly with the listener's head rotation.

In this manuscript we present a methodology for reducing the impact of the hosting room reflections in sound field rendering applications based on loudspeaker arrays. The problem is formulated in a least-squares sense. Since matrices involved in the problem are ill-conditioned, it is important to devise a suitable technique for the regularisation of the pseudo-inverse. In this work we adopt a truncated SVD method. The truncation, in particular, aims at reducing the impact of numerical errors and also errors on the knowledge of the sound speed. We include a wide set of experimental results, which validate the proposed technique.

In the traditional microphone array signal processing, the performance degrades rapidly when the array aperture decreases, which has been a barrier restricting its implementation in the small-scale acoustic system such as digital hearing aids. In this work a new compressed sampling method of miniature microphone array is proposed, which compresses information in the internal of ADC by means of mixture system of hardware circuit and software program in order to remove the redundancy of the different array element signals. The architecture of the method is developed using the Verilog language and has already been tested in the FPGA chip. Experiments of compressed sampling and reconstruction show the successful sparseness and reconstruction for speech sources. Owing to having avoided singularity problem of the correlation matrix of the miniature microphone array, when used in the direction of arrival (DOA) estimation in digital hearing aids, the proposed method has the advantage of higher resolution compared with the traditional GCC and MUSIC algorithms.

Recently the word-based stream ciphers have been the subject of a considerable amount of research. The theory of such stream ciphers requires the study of the complexity of a multisequence. Let S1, S2, . . . , Sm be m N-ary sequences of period T, i.e., a multisequence. The relationship between the joint N-adic complexity and the number of the nonzero columns of the generalized Fourier transform for the N-ary multisequence is determined which generalizes the well-known result about the joint linear complexity and the generalized Fourier transform for a multisequence to the case of the joint N-adic complexity.

We analyze the outage probability of the multiuser two-way relay network (TWRN) where the N-th best mobile user (MU) out of M MUs and the base station (BS) exchange messages with the aid of an amplify-and-forward relay. In the analysis, we focus on the practical unbalanced Nakagami-m fading between the MUs-relay link and the relay-BS link. We also consider both perfect and outdated channel state information (CSI) between the MUs and the relay. We first derive tight closed-form lower bounds on the outage probability. We then derive compact expressions for the asymptotic outage probability to explicitly characterize the network performance in the high signal-to-noise ratio regime. Based on our asymptotic results, we demonstrate that the diversity order is determined by both Nakagami-m fading parameters, M, and N when perfect CSI is available. When outdated CSI is available, the diversity order is determined by Nakagami-m fading parameters only. In addition, we quantify the contributions of M, N, and the outdated CSI to the outage probability via the array gain.

In this paper, we study the feasibility of a batteryless wireless sensor supplied with energy by using microwave power transmission (MPT). If we perform co-channel operation of MPT and wireless local area networks (WLANs) for the sake of spectral efficiency, a time division method for MPT and WLAN communications is required to avoid serious interference from MPT to WLAN data transmissions. In addition, to reduce the power consumption of a sensor, the use of power-save operation of the sensor is desirable. We proposed a scheduling scheme that allocates time for MPT and WLAN communications. Specifically, in the proposed scheduling system, an energy source transmits microwave power to a sensor station except when the sensor station transmits data frames or receives beacon frames. In addition, in the proposed scheduling system, we force the remaining energy of the sensor station to converge to a maximum value by adjusting the time interval of data transmission from the sensor station such that the power consumption of the sensor station is reduced. On the basis of the proposition, we implemented a scheduling system and then confirmed that it performed successfully in the conducted experiments. Finally, we discussed the feasibility of the proposed scheduling scheme by evaluating the coverage and then showed that the scheduling scheme can be applied to closed space or room.

In mobile wireless sensor networks, coverage and energy are two significant factors determining network performance. When taking both factors into account, the challenges include how to select and migrate nodes to keep coverage quality, how to forecast and prevent potential coverage holes and how to use energy control in mobile networks. In this paper, we propose a new Coverage Maintenance and Energy Control (CMEC) algorithm to achieve and keep high coverage quality and energy efficiency. For CMEC, we provide a new cost metric for selecting migration nodes. Our simulation results confirm that our algorithm improves coverage performance and lifetime of network.

With the phenomenal explosion in online services, social networks are becoming an emerging ubiquitous platform for numerous services where service consumers require the selection of trustworthy service providers before invoking services with the help of other intermediate participants. Under this circumstance, evaluation of the trustworthiness of the service provider along the social trust paths from the service consumer to the service provider is required and to this end, selection of the optimal social trust path (OSTP) that can yield the most trustworthy evaluation result is a pre-requisite. OSTP selection with multiple quality of trust (QoT) constraints has been proven to be NP-Complete. Heuristic algorithms with polynomial and pseudo-polynomial-time complexities are often used to deal with this problem. However, existing solutions cannot guarantee the search efficiency, that is, they have difficulty in avoiding suboptimal solutions during the search process. Quantum annealing uses delocalization and tunneling to avoid local minima without sacrificing execution time. Several recent studies have proven that it is a promising way to tackle many optimization problems. In this paper, we propose a novel quantum annealing based OSTP selection algorithm (QA_OSTP) for large-scale complex social networks. Experiments show that QA_OSTP has better performance than its heuristic counterparts.