This paper proposes performance improvement schemes for non-coherent multiple-input multiple-output (MIMO) communication systems employing per transmit antenna differential mapping (PADM). PADM is one form of differential space-time coding (DSTC), which generates an independent differentially encoded sequence for each of the multiple transmit antennas by means of space-time coding and mapping. The features of the proposed schemes are as follows: 1) it employs an asymmetric space-time mapping instead of the conventional symmetric space-time mapping in order to lower the required signal to noise power ratio (SNR) for maintaining the bit error rate (BER) performance; 2) it employs an analytically derived branch metric criterion based on channel prediction for per-survivor processing (PSP) in order to track fast time-varying channels. Finally, computer simulation results confirm that the proposed schemes improve the required SNR by around 1dB and can track at the maximum Doppler frequency normalized by symbol rate of 5%.

Transfer boosting, a branch of instance-based transfer learning, is a commonly adopted transfer learning method. However, currently popular transfer boosting methods focus on binary classification problems even though there are many multi-classification tasks in practice. In this paper, we developed a new algorithm called MultiTransferBoost on the basis of TransferBoost for multi-classification. MultiTransferBoost firstly separated the multi-classification problem into several orthogonal binary classification problems. During each iteration, MultiTransferBoost boosted weighted instances from different source domains while each instance's weight was assigned and updated by evaluating the difficulty of the instance being correctly classified and the “transferability” of the instance's corresponding source domain to the target. The updating process repeated until it reached the predefined training error or iteration number. The weight update factors, which were analyzed and adjusted to minimize the Hamming loss of the output coding, strengthened the connections among the sub binary problems during each iteration. Experimental results demonstrated that MultiTransferBoost had better classification performance and less computational burden than existing instance-based algorithms using the One-Against-One (OAO) strategy.

Sorting is an extremely important computation kernel that has been accelerated in a lot of fields such as databases, image processing, and genome analysis. Given that advent of Internet of Things (IoT) era due to mobile technology progressions, the future needs a sorting method that is available on any environment, such as not only high performance systems like servers but also low computational performance machines like embedded systems. In this paper, we present an FPGA-based sorting accelerator combining Sorting Network and Merge Sorter Tree, which is customizable by means of tuning design parameters. The proposed FPGA accelerator sorts data sent from a host PC via the PCIe bus, and sends back the fully sorted data sequence to it. We also present a detailed analytical model that accurately estimates the sorting performance. Due to these characteristics, designers can know how fast a developed sorting hardware is in advance and can implement the best one to fulfill the cost and performance constraints. Our experiments show that the proposed hardware achieves up to 19.5x sorting performance, compared with Intel Core i7-3770K operating at 3.50GHz, when sorting 256M 32-bits integer elements. However, this result is limited because of insufficient memory bandwidth. To overcome this problem, we propose a data compression mechanism and the experimental result shows that the sorting hardware with it achieves almost 90% of the estimated performance, while the hardware without it does about 60%. In order to allow every designer to easily and freely use this accelerator, the RTL source code is released as open-source hardware.

The Seebeck coefficient of Si wire co-doped with P and Ga atoms is investigated for applying thermoelectric devices. The observed Seebeck coefficient is closed to the theoretical values of electronic part of Seebeck coefficient due to the electronic transport. From the estimation of phonon scattering processes, it is found that the phonon-drag contribution to the Seebeck coefficient in co-doped Si wire is mainly governed by the phonon-boundary scattering.

This paper focuses on differences in comment densities among individual programmers, and proposes to adjust the conventional code complexity metric (the cyclomatic complexity) by using the abnormality of the comment density. An empirical study with nine popular open source Java products (including 103,246 methods) shows that the proposed metric performs better than the conventional one in predicting change-prone methods; the proposed metric improves the area under the ROC curve (AUC) by about 3.4% on average.

Device-to-device (D2D) communication enables two local users to communicate with each other directly instead of relaying through a third party, e.g., base station. In this paper, we study a subchannel sharing strategy underlaying multichannel cellular network for D2D pairs and existing cellular users (CUs). In the investigated scenario, we try to improve the spectrum efficiency of D2D pairs, but inevitably brings cross interference between two user groups. To combat interference, we attempt to assign each D2D pair with appropriate subchannels, which may belong to different CUs, and manipulate transmission power of all users so as to maximize the sum rate of all D2D pairs, while assuring each CU with a minimum data rate on its subchannel set. The formulated problem is a nonconvex problem and thus, obtaining its optimal solution is a tough task. However, we can find optimal power and subchannel assignment for a special case by setting an independent data rate constraint on each subchannel. Then we find an efficient method to calculate a gradient for our original problem. Finally, we propose a gradient-based search method to address the problem with coupled minimum data rate constraint. The performance of our proposed subchannel sharing strategy is illustrated via extensive simulation results.

High Efficiency Video Coding is a new video coding standard after H.264/AVC. By introducing a flexible coding unit, which can be recursively divided from 64×64 to 8×8 blocks in a Quadtree-Structure, HEVC achieves significantly higher coding efficiency than the previous standards. With the flexible CU structure, HEVC can effectively adapt to highly varying contents with a smaller CU or to flat contents with a larger CU, making it suitable for applications from mobile video to super high definition television. On the other hand, CU division does incur high computational cost for HEVC. In this paper, we propose a simple and fast CU division algorithm by using only a subset of pixels to determine when CU division happens. Experiment results show that our algorithm can achieve prediction quality close to HEVC Test Model with much lower computational cost.

In this paper, a nanopower supply-insensitive complementary metal-oxide-semiconductor (CMOS) unit threshold voltage (Vth) extractor circuit is proposed. It meets the contemporary industry demand for portable devices that operate with very low power consumption and small output sensitivity. An α times Vth (αVth) extractor is also described, in which α varies continuously. Both incremental and decremental αVth voltages are obtained. A post-layout simulation results using HSPICE with CMOS 0.18um process show that the proposed unit Vth extractor consumes 265nW of power given a 1.6V power supply. Sensitivity to temperature is 0.022%/°C ranging from 0°C to 100°C. Sensitivity to supply voltage is 0.027%/V.

We have studied the formation of Ti-nanodots (NDs) by remote H2 plasma (H2-RP) exposure and investigated how the embedding of Ti-NDs affects the resistive switching properties of Si-rich oxides (SiOx) because it is expected that NDs will trigger the formation of the conductive filament path in SiOx. Ti-NDs with an areal density as high as 1011 cm-2 were fabricated by exposing a Ge/Ti stacked layer to the H2-RP without external heating, and changes in the chemical structure of Ge/Ti stacked layer with the Ti-NDs formation were evaluated by using hard x-ray photoemission spectroscopy (HAXPES) and x-ray photoelectron spectroscopy (XPS). Resistive switching behaviors of SiOx with Ti-NDs were measured from current-voltage curves and compared to the results obtained from samples of SiOx with a Ti thin layer.

In this paper, we consider optimal sensing scheduling for sequential cooperative spectrum sensing (SCSS) technique in cognitive radio networks (CRNs). Activities of primary users (PU) on a primary channel are captured by using a two states discrete time Markov chain process and a soft combination is considered at the FC. Based on the theory of optimal stopping, we propose an algorithm to optimize the cooperative sensing process in which the FC sequentially asks each CU to report its sensing result until the stopping condition that provides the maximum expected throughput for the CRN is satisfied. Simulation result shows that the performance of the proposed scheme can be improved by further shortening the reporting overhead and reducing the probability of false alarm in comparison to other schemes in literature. In addition, the collision ratio on the primary channel is also investigated.

High Efficiency Video Coding (HEVC) is the latest coding standard. Compared with Advanced Video coding (H.264/AVC), HEVC offers about a 50% bitrate reduction at the same reconstructed video quality. However, this new coding standard leads to enormous computational complexity, which makes it difficult to encode video in real time. Therefore, in this paper, aiming at the high complexity of intra coding in HEVC, a new fast coding unit (CU) splitting algorithm is proposed based on the decision tree. Decision tree, as a method of machine learning, can be designed to determine the size of CUs adaptively. Here, two significant features, Just Noticeable Difference (JND) values and coding bits of each CU can be extracted to train the decision tree, according to their relationships with the CUs' partitions. The experimental results have revealed that the proposed algorithm can save about 34% of time, on average, with only a small increase of BD-rate under the “All_Intra” setting, compared with the HEVC reference software.

In this paper, the virtual antenna technique is applied to a single input multiple output (SIMO) radar system to enhance the performance of the conventional beamforming direction of arrival (DOA) estimation method. Combining the virtual array generated by the interpolated array technique and the real array, the angular resolution of the DOA estimation algorithm is improved owing to the extended number of antennas and aperture size. Based on the proposed interpolation technique, we transform the position of the antenna elements in a uniform linear array (ULA) to the arbitrary positions to suppress the grating lobe and side lobe levels. In simulations, the pseudo spectrum of the Bartlett algorithm and the root mean square error (RMSE) of the DOA estimation with the signal-to-noise ratio (SNR) are analyzed for the real array and the proposed virtually extended array. Simulation results show that the angular resolution of the proposed array is better than that of the real array using the same aperture size of array and the number of antennas. The proposed technique is verified with the practical data from commercialized radar system.

The phonon-drag contribution to the Seebeck coefficient (Sph) for p-type Si, Ge and Si1-xGex is investigated for thermoelectric applications. The Sph in Si and Ge is found to mainly determined by the phonon velocity, phonon mean free path and carrier mobility associated with acoustic deformation potential scattering. Moreover, the Sph in Si1-xGex is predictable by the above-mentioned material parameters interpolated with those in Si and Ge.

This paper proposes the statistical analysis of phase-only correlation functions between two real signals with phase-spectrum differences. For real signals, their phase-spectrum differences have odd-symmetry with respect to frequency indices. We assume phase-spectrum differences between two signals to be random variables. We next derive the expectation and variance of the POC functions considering the odd-symmetry of the phase-spectrum differences. As a result, the expectation and variance of the POC functions can be expressed by characteristic functions or trigonometric moments of the phase-spectrum differences. Furthermore, it is shown that the peak value of the POC function monotonically decreases and the sidelobe values monotonically increase as the variance of the phase-spectrum differences increases.

Wi-Fi Direct is a promising and available technology for device-to-device (D2D) proximity communications. To improve the performances of Wi-Fi Direct communication, optimized radio resource allocations are important. This paper proposes network assisted Wi-Fi Direct (NAWD), which operates based on the media independent services framework of IEEE 802.21 standard, for optimizing radio resource allocations. The NAWD is enhanced Wi-Fi Direct with the assistance of infrastructure networks (e.g., cellular network) and allocates radio resources (e.g., frequency channels and transmit power) to reduce radio interferences among Wi-Fi Direct devices (e.g., smart phones and set-top boxes). The NAWD includes mechanisms for gathering configuration information (e.g., location information and network connection information) of Wi-Fi Direct devices and allocating optimized radio resources (e.g., frequency channels and transmit power) to reduce radio interferences among Wi-Fi Direct devices. Simulation results show that the proposed NAWD increases significantly SINR, power efficiency, and areal capacity compared to legacy Wi-Fi Direct, where areal capacity is total traffic throughput per unit area.

Significant challenges in ball tracking of sports analysis by computer vision technology are: 1) accuracy of estimated 3D ball trajectory under difficult conditions; 2) external forces added by players lead to irregular motions of the ball; 3) unpredictable situations in the real game, i.e. the ball occluded by players and other objects, complex background and changing lighting condition. With the goal of multi-view 3D ball tracking, this paper proposes an abrupt motion adaptive system model, an anti-occlusion observation model, and a spatial density-based automatic recovery based on particle filter. The system model combines two different system noises that cover the motion of the ball both in general situation and situation subject to abrupt motion caused by external force. Combination ratio of these two noises and number of particles are adaptive to the estimated motion by weight distribution of particles. The anti-occlusion observation model evaluates image feature of each camera and eliminates influence of the camera with less confidence. The spatial density, which is calculated based on 3D ball candidates filtered out by spatial homographic relationship between cameras, is proposed for generating new set of particles to recover the tracking when tracking failure is detected. Experimental results based on HDTV video sequences (2014 Inter High School Men's Volleyball Games, Japan), which were captured by four cameras located at each corner of the court, show that the success rate achieved by the proposals of 3D ball tracking is 99.42%.

In this paper, Epitaxial (Epi) Junction Termination Extension (JTE) technique for silicon carbide (SiC) power device is presented. Unlike conventional JTE, the Epi-JTE doesn't require high temperature (about 500°C) implantation process. Thus, it doesn't require high temperature (about 1700°C) process for implanted dose activation and surface defect curing. Therefore, the manufacturing cost will be decreased. Also, the fabrication process is very simple because the dose of the JTE is controlled by epitaxy growth. The blocking characteristic is analyzed through 2D-simulation for the proposed Epi-JTE. In addition, the effect was validated by experiment of fabricated SiC device with the Single-Zone-Epi-JTE. As a result, it has blocking capability of 79.4% compared to ideal parallel-plane junction breakdown.

This paper proposes an effective continuous super-resolution (CSR) algorithm for the multipath channel estimation. By designing a preamble including up-chirp and down-chirp symbols, the Doppler shift and multipath delay are estimated jointly by using convex programming. Simulation results show that the proposed CSR can achieve better detection probability of the number of multipaths than the eigenvalue based methods. Moreover, compared with conventional super-resolution techniques, such as MUSIC and ESPRIT methods, the proposed CSR algorithm demonstrates its advantage in root mean square error of the Doppler shift and multipath delay, especially for the closely located paths within low SNR.

Image interpolation is one of the image upsampling technologies from a single input image. This technology obtains high resolution images by fitting functions or models. Although image interpolation methods are faster than other upsampling technologies, they tend to cause jaggies and blurs in edge and texture regions. Multi-surface Fitting is one of the image upsampling techniques from multiple input images. This algorithm utilizes multiple local functions and the weighted means of the estimations in each local function. Multi-surface Fitting obtains high quality upsampled images. However, its quality depends on the number of input images. Therefore, this method is used in only limited situations. In this paper, we propose an image interpolation method with both high quality and a low computational cost which can be used in many situations. We adapt the idea of Multi-surface Fitting for the image upsampling problems from a single input image. We also utilize local functions to reduce blurs. To improve the reliability of each local function, we introduce new weights in the estimation of the local functions. Besides, we improve the weights for weighted means to estimate a target pixel. Moreover, we utilize convolutions with small filters instead of the calculation of each local function in order to reduce the computational cost. Experimental results show our method obtains high quality output images without jaggies and blurs in short computational time.

The paper presents a small reversible language R-CORE, a structured imperative programming language with symbolic tree-structured data (S-expressions). The language is reduced to the core of a reversible language, with a single command for reversibly updating the store, a single reversible control-flow operator, a limited number of variables, and data with a single atom and a single constructor. Despite its extreme simplicity, the language is reversibly universal, which means that it is as powerful as any reversible language can be, while it is linear-time self-interpretable, and it allows reversible programming with dynamic data structures. The four-line program inverter for R-CORE is among the shortest existing program inverters, which demonstrates the conciseness of the language. The translator to R-CORE, which is used to show the formal properties of the language, is clean and modular, and it may serve as a model for related reversible translation problems. The goal is to provide a language that is sufficiently concise for theoretical investigations. Owing to its simplicity, the language may also be used for educational purposes.