High efficiency video coding (HEVC) is a video compression standard that outperforms the predecessor H.264/AVC by doubling the compression efficiency. To enhance the coding accuracy, HEVC adopts sample adaptive offset (SAO), which reduces the distortion of reconstructed pixels using classification based non-linear filtering. In the traditional coding tree unit (CTU) grain based VLSI encoder implementation, during the pixel classification stage, SAO cannot use the raw samples in the boundary of the current CTU because these pixels have not been processed by deblocking filter (DF). This paper proposes a hardware-oriented category determination algorithm based on estimating the deblocking strengths on CTU boundaries and selectively adopting the promising samples in these areas during SAO classification. Compared with HEVC test mode (HM11.0), experimental results indicate that the proposed method achieves an average 0.13%, 0.14%, and 0.12% BD-bitrate reduction (equivalent to 0.0055dB, 0.0058dB, and 0.0097dB increases in PSNR) in CTU sizes of 64 × 64, 32 × 32, and 16 × 16, respectively.

Some networks, such as wireless sensor networks, vehicle networks, etc., are often disconnected and thus fail to provide an end-to-end route for transmission. As a result, a new kind self-organized wireless network, i.e., Delay Tolerant Network (DTN) is proposed to transmit messages using a store-carry-forward method. To efficiently process aggregation queries, this paper proposes a subscription aggregation query processing method that combines query processing and transfer protocols. The basic idea is reducing the number of redundant copy transmissions, increasing the message delivery rate and reducing the transmission delay by matrix summation. Theoretical and experimental results show that the method can attain a good performance in the delay tolerant networks.

A novel activation method for a B dopant implanted in a Si substrate using a soft X-ray undulator was examined. As the photon energy of the irradiated soft X-ray approached the energy of the core level of Si 2p, the activation ratio increased. The effect of soft X-ray irradiation on B activation was remarkable at temperatures lower than 400°C. The activation energy of B activation by soft X-ray irradiation (0.06 eV) was lower than that of B activation by furnace annealing (0.18 eV). The activation of the B dopant by soft X-ray irradiation occurs at low temperature, although the activation ratio shows small values of 6.2×10-3 at 110°C. The activation by soft X-ray is caused not only by thermal effects, but also electron excitation and atomic movement.

The growing trends in Internet usage for data and knowledge sharing calls for dynamic classification of web contents, particularly at the edges of the Internet. Rather than considering Linked Data as an integral part of Big Data, we propose Autonomous Decentralized Semantic-based Content Classifier (ADSCC) for dynamic classification of unstructured web contents, using Linked Data and web metadata in Content Delivery Network (CDN). The proposed framework ensures efficient categorization of URLs (even overlapping categories) by dynamically mapping the changing user-defined categories to ontologies' category/classes. This dynamic classification is performed by the proposed system that mainly involves three main algorithms/modules: Dynamic Mapping algorithm, Autonomous coordination-based Inference algorithm, and Context-based disambiguation. Evaluation results show that the proposed system achieves (on average), the precision, recall and F-measure within the 93-97% range.

This paper proposes a moving source localization method that combines TDOA, FDOA and doppler rate measurements. First, the observation equations are linearized by introducing nuisance variables and an initial solution of all the variables is acquired using the weighted least squares method. Then, the Taylor expression and gradient method is applied to eliminate the correlation between the elements in the initial solution and obtain the final estimation of the source position and velocity. The proposed method achieves CRLB derived using TDOA, FDOA and doppler rate and is much more accurate than the conventional TDOA/FDOA based method. In addition, it can avoid the rank-deficiency problem and is more robust than the conventional method. Simulations are conducted to examine the algorithm's performance and compare it with conventional TDOA/FDOA based method.

In this study, we propose a simple, yet general and powerful framework of integrating multiple global and local features by Product Sparse Coding (PSC) for image retrieval. In our framework, multiple global and local features are extracted from images and then are transformed to Trimmed-Root (TR)-features. After that, the features are encoded into compact codes by PSC. Finally, a two-stage ranking strategy is proposed for indexing in retrieval. We make three major contributions in this study. First, we propose TR representation of multiple image features and show that the TR representation offers better performance than the original features. Second, the integrated features by PSC is very compact and effective with lower complexity than by the standard sparse coding. Finally, the two-stage ranking strategy can balance the efficiency and memory usage in storage. Experiments demonstrate that our compact image representation is superior to the state-of-the-art alternatives for large-scale image retrieval.

Quantum efficiency (QE) evolution by several negative electron affinity (NEA) activation process for p-doped GaAs(100) specimen has been studied. We have carried out the surface pretreatment at 580°C or 480°C and the successive NEA activation process at room temperature (R.T.). When the NEA surface was degraded, the surface was refreshed by above pretreatment and activation process, and approximately 0.10 of QE was repeatedly obtained. It was found that the higher QE of 0.13 was achieved with the reduced pretreatment temperature at 480°C with the specific experimental conditions. This is probably caused by the residual Cs-related compounds playing an important role of the electron emission. In addition, after the multiple pretreatment and activation sequence, surface morphology of GaAs remarkably changed.

Low-temperature bonding methods of optoelectronic chips, such as laser diodes (LD) and photodiode (PD) chips, have been the focus of much interest to develop highly functional and compact optoelectronic devices, such as microsensors and communication modules. In this paper, room-temperature bonding of the optoelectronic chips with Au thin film to coined Au stud bumps with smooth surfaces (Ra: 1.3nm) using argon and hydrogen gas mixture atmospheric-pressure plasma was demonstrated in ambient air. The die-shear strength was high enough to exceed the strength requirement of MIL-STD-883F, method 2019 (×2). The measured results of the light-current-voltage characteristics of the LD chips and the dark current-voltage characteristics of the PD chips indicated no degradation after bonding.

Wheeze is a general sign for obstructive airway diseases whose clinical diagnosis mainly depends on auscultating or X-ray imaging with subjectivity or harm. Therefore, this paper introduces an automatic, noninvasive method to detect wheeze which consists of STFT decomposition, preprocessing of the spectrogram, correlation-coefficients calculating and duration determining. In particular, duration determining takes the Haas effect into account, which facilitates us to achieve a better determination. Simulation result shows that the sensibility (SE), the specificity (SP) and the accuracy (AC) are 88.57%, 97.78% and 93.75%, respectively, which indicates that this method could be an efficient way to detect wheeze.

Negative electron affinity (NEA) surfaces can be formed by alternating supply of alkali metals (e.g. Cs, Rb, K) and oxygen on semiconductor surfaces. We have studied adsorption structures of Cs on an As-terminated (2×4) (001) GaAs surface using scanning tunneling microscopy (STM). We found that the initial adsorption of Cs atoms occurs around the step sites in the form of Cs clusters and that the size of clusters is reduced by successive exposure to O2, indicating that As-terminated (2×4) surfaces are relatively stable compared to Ga-terminated surfaces and are not broken by the Cs clusters adsorption.

Research into closed-form Gaussian sum smoother has provided an attractive approach for tracking in clutter, joint detection and tracking (in clutter), and multiple target tracking (in clutter) via the probability hypothesis density (PHD). However, Gaussian sum smoother with nonlinear target model has particular nonlinear expressions in the backward smoothed density that are different from the other filters and smoothers. In order to extend the closed-form solution of linear Gaussian sum smoother to nonlinear model, two closed-form approximations for nonlinear Gaussian sum smoother are proposed, which use Gaussian particle approximation and unscented transformation approximation, separately. Since the estimated target number of PHD smoother is not stable, a heuristic approximation method is added. At last, the Bernoulli smoother and PHD smoother are simulated using Gaussian particle approximation and unscented transformation approximation, and simulation results show that the two proposed algorithms can obtain smoothed tracks with nonlinear models, and have better performance than filter.

Efficient detection schemes for an overloaded multiple-input multiple-output (MIMO) system have been investigated recently. The literature shows that trellis coded modulation (TCM) is able to enhance a system's capability to separate signal streams in the detection process of MIMO systems. However, the computational complexity remains high as a maximum likelihood detection (MLD) algorithm is used in the scheme. Thus, a sphere decoding (SD) algorithm with a pseudo distance (PD) is proposed in this paper. The PD maintains the coding gain advantage of the TCM by keeping some potential paths connected unlike conventional SD which truncates them. It is shown that the proposed scheme can reduce the number of distance calculations by about 98% for the transmission of 3 signal streams. In addition, the proposed scheme improves the performance by about 2dB at the bit error rate of 10-2.

Ultra-wideband (UWB) communications is used for medical information communication technology (MICT) as a dependable and safe communication technology in recent years. On the other hand, there are existing various UWB systems that are not used for MICT. Generally, these UWB systems use almost the same frequency band. Therefore, they interfere to each other in general transmission channel environment. In our previous work, a novel UWB pulse shape modulation using modified Hermite pulse is proposed as a multiple user access scheme. In this paper, we propose a mitigation method for inter-user interference and inter-system interference using combination of orthogonal pulse shape modulation and orthogonal matched filter (OMF) detector. The purposes of our system are to detect all signals of users in the same UWB system and to reduce the unknown interference from other UWB systems at the same time. This paper provides performance evaluation results based on both of analytical and numerical evaluation. Simulation results show that the proposed system can detect the signals that were transmitted from the same UWB system using orthogonal pulse set, while the proposed system can reduce the interference from unknown UWB systems at the same time. The theoretical analysis is expected that noise tolerance of our proposal will be deteriorated in the additive Gaussian noise channel in comparison with the conventional matched filter. It is confirmed that the numerical evaluation illustrates such noise tolerance equivalent to the theoretical analysis result.

In this paper, we consider the problem of generating uniformly random mosaic floorplans. We propose a polynomial-time algorithm that generates such floorplans with f faces. Two modified algorithms are created to meet additional criteria.

In distributed storage systems, codes with lower repair locality are much more desirable due to their superiority in reducing the disk I/O complexity of each repair process. Motivated partially by both codes with information (r,δ1)c locality and codes with cooperative (r,l) locality, we propose the concept of codes with information (r,l,δ) locality in this paper. For a linear code C with information (r,l,δ) locality, values at arbitrary l information coordinates of an information set I can be recovered by connecting any of δ existing pairwise disjoint local repair sets with size no more than r, where a local repair set of l coordinates is defined as the set of some other coordinates by which one can recover the values at these l coordinates. We derive a lower bound on the codeword length n for [n,k,d] linear codes with information (r,l,δ) locality. Furthermore, we indicate its tightness for some special cases. Particularly, some existing results can be deduced from our bound by restriction on parameters.

Glial cells include several types of cells such as astrocytes, and oligodendrocytes apart from the neurons in the brain. In particular, astrocytes are known to be important in higher brain function and are therefore sometimes simply called glial cells. An astrocyte can transmit signals to other astrocytes and neurons using ion concentrations. Thus, we expect that the functions of an astrocyte can be applied to an artificial neural network. In this study, we propose a multi-layer perceptron (MLP) with a pulse glial chain. The proposed MLP contains glia (astrocytes) in a hidden layer. The glia are connected to neurons and are excited by the outputs of the neurons. The excited glia generate pulses that affect the excitation thresholds of the neurons and their neighboring glia. The glial network provides a type of positional relationship between the neurons in the hidden layer, which can enhance the performance of MLP learning. We confirm through computer simulations that the proposed MLP has better learning performance than a conventional MLP.

Software architecture recovery techniques are often adopted to derive a module view of software from its source code in case software architecture documents are unavailable or outdated. The module view is one of the most important perspectives of software architecture. In this paper, we propose a novel approach to derive a module view by adaptively integrating structural dependency and textual similarity. Our approach utilizes Newman modularity and Shannon information entropy to determine the appropriate weights of the dependencies during the integration. We apply our approach to various open-source projects and show the experimental results validating the effectiveness of the approach.

Web Service Business Process Execution Language (BPEL) has become the de facto standard for developing instant service-oriented workflow applications in open environment. The correctness and reliability of BPEL processes have gained increasing concerns. However, the unique features (e.g., dead path elimination (DPE) semantics, parallelism, etc.) of BPEL language have raised enormous problems to it, especially in path feasibility analysis of BPEL processes. Path feasibility analysis of BPEL processes is the basis of BPEL testing, for it relates to the test case generation. Since BPEL processes support both parallelism and DPE semantics, existing techniques can't be directly applied to its path feasibility analysis. To address this problem, we present a novel technique to analyze the path feasibility for BPEL processes. First, to tackle unique features mentioned above, we transform a BPEL process into an intermediary model — BPEL control flow graph, which is proposed to abstract the execution flow of BPEL processes. Second, based on this abstraction, we symbolically encode every path of BPEL processes as some Satisfiability formulas. Finally, we solve these formulas with the help of Satisfiability Modulo Theory (SMT) solvers and the feasible paths of BPEL processes are obtained. We illustrate the applicability and feasibility of our technique through a case study.

In the obnoxious facility game with a set of agents in a space, we wish to design a mechanism, a decision-making procedure that determines a location of an undesirable facility based on locations reported by the agents, where we do not know whether the location reported by an agent is where exactly the agent exists in the space. For a location of the facility, the benefit of each agent is defined to be the distance from the location of the facility to where the agent exists. Given a mechanism, all agents are informed of how the mechanism utilizes locations reported by the agents to determine a location of the facility before they report their locations. Some agent may try to manipulate the decision of the facility location by strategically misreporting her location. As a fair decision-making, mechanisms should be designed so that no particular group of agents can get a larger benefit by misreporting their locations. A mechanism is called group strategy-proof if no subset of agents can form a group such that every member of the group can increase her benefit by misreporting her location jointly with the rest of the group. For a given mechanism, a point in the space is called a candidate if it can be output as the location of the facility by the mechanism for some set of locations reported by agents. In this paper, we consider the case where a given space is a tree metric, and characterize the group strategy-proof mechanisms in terms of distribution of all candidates in the tree metric. We prove that there exists a group strategy-proof mechanism in the tree metric if and only if the tree has a point to which every candidate has the same distance.

In this study, our recent research activities on nanophotonic devices with semiconductor quantum nanostructures are reviewed. We have developed a technique for nanofabricating of high-quality and high-density semiconductor quantum dots (QDs). On the basis of this core technology, we have studied next-generation nanophotonic devices fabricated using high-quality QDs, including (1) a high-performance QD laser for long-wavelength optical communications, (2) high-efficiency compound-type solar cell structures, and (3) single-QD devices for future applications related to quantum information. These devices are expected to be used in high-speed optical communication systems, high-performance renewable energy systems, and future high-security quantum computation and communication systems.