In 2009, Wang et al. proposed an efficient and secure dynamic ID-based remote user authentication scheme based on the one-way secure hash function. This letter demonstrates that Wang et al.'s scheme is still vulnerable to impersonation attacks.

400 V DC power distribution systems for data centers require a fast response DC circuit breaker is required. The semiconductor DC circuit breaker is an important key technology in DC power distribution systems. This paper considers the malfunction of Silicon Carbide- Static Induction Transistor (SiC-SIT) based DC circuit breakers in 400 V DC power distribution systems for data centers. The malfunction mechanism is explained, and a solution is proposed. Investigations are achieved by MATLAB/Simulink and experimental verification.

Joint transmit and receive antenna selection (JTRAS) is proposed for the multiple-input multiple-output (MIMO) two-way relaying channel. A simple and closed-form lower bound on the outage probability of JTRAS is derived. Furthermore, asymptotic analysis reveals that JTRAS can attain the maximum achievable diversity order of the MIMO dual-hop relaying channel.

The Direct Sampling Mixer (DSM) with a complex coefficient transfer function is demonstrated. The operation theory and the detail design methodology are discussed for the high order complex DSM, which can achieve large image rejection ratio by introducing the attenuation pole at the image frequency band. The proposed architecture was fabricated in a 65 nm CMOS process. The measured results agree well with the theoretical calculation, which proves the validity of the proposed architecture and the design methodology. By using the proposed design method, it will be possible for circuit designers to design the DSM with large image rejection ratio without repeated lengthy simulations.

This paper proposes a method of accurately detecting the boundary of narrow stripes, such as lane markings, by employing gradient cues of edge points. Using gradient direction cues, the edge points at the two sides of the boundary of stripes are classified into two groups before the Hough transform is applied to extract the boundary lines. The experiments show that the proposed method improves significantly the performance in terms of the accuracy of boundary detection of narrow stripes over the conventional approaches without edge point grouping.

To improve the observability during the post-silicon validation, it is the key to select the limited trace signals effectively for the data acquisition. This paper proposes an automated trace signal selection algorithm, which uses the pruning-based strategy to reduce the exploration space. First, the restoration range is covered for each candidate signals. Second, the constraints are generated based on the conjunctive normal form (CNF) to avoid the conflict. Finally the candidates are selected through pruning-based enumeration. The experimental results indicate that the proposed algorithm can bring higher restoration ratios and is more effective compared to existing methods.

The market growths of smart-phones and thin clients have been significantly increasing communication traffic in mobile networks. To handle the increased traffic, network operators should consider how to leverage distributed wireless resources such as distributed spots of wireless local access networks. In this paper, we consider the system where multiple moving users share distributed wireless access points on their traveling routes between their start and goal points and formulate as an optimization problem. Then, we come up with three algorithms as a solution for the problem. The key idea here is 'longcut route instruction', in which users are instructed to choose a traveling route where less congested access points are available; even if the moving distance increases, the throughput for users in the system would improve. In this paper, we define the gain function. Moreover, we analyze the basic characteristics of the system using as a simple model as possible.

We present a new framework of the data-reusing (DR) adaptive algorithms by incorporating a constraint on noise, referred to as a noise constraint. The motivation behind this work is that the use of the statistical knowledge of the channel noise can contribute toward improving the convergence performance of an adaptive filter in identifying a noisy linear finite impulse response (FIR) channel. By incorporating the noise constraint into the cost function of the DR adaptive algorithms, the noise constrained DR (NC-DR) adaptive algorithms are derived. Experimental results clearly indicate their superior performance over the conventional DR ones.

A 315 MHz power-gated ultra low power transceiver for wireless sensor network is developed in 40 nm CMOS. The developed transceiver features an injection-locked frequency multiplier for carrier generation and a power-gated low noise amplifier with current second-reuse technique for receiver front-end. The injection-locked frequency multiplier implements frequency multiplication by edge-combining and thereby achieves 11 µW power consumption at 315 MHz. The proposed low noise amplifier achieves the lowest power consumption of 8.4 µW with 7.9 dB noise figure and 20.5 dB gain in state-of-the-art designs.

With the consideration of real-time stream processing technology, it's important to develop high availability mechanism to guarantee stream-based application not interfered by faults caused by potential anomalies. In this paper, we present a novel online prediction technique for predicting some anomalies which may occur in the near future. Concretely, we first present a value prediction which combines the Hidden Markov Model and the Mixture of Expert Model to predict the values of feature metrics in the near future. Then we employ the Support Vector Machine to do anomaly identification, which is a procedure to identify the kind of anomaly that we are about to alarm. The purpose of our approach is to achieve a tradeoff between fault penalty and resource cost. The experiment results show that our approach is of high accuracy for common anomaly prediction and low runtime overhead.

We propose an optimal access-point (AP) selection algorithm for maximizing the aggregated throughput of each AP (system throughput) while preserving newly arrived-user throughput in multi rate WLAN system. In our algorithm, newly arrived users cooperate with a wireless local area network (WLAN) system they are trying to use, i.e., they are willing to move toward an appropriate AP before the newly arrived user connects to AP. To select the AP by using our AP selection algorithm, the newly arriving users request two novel parameter values, “the minimum acceptable throughput” with which newly arrived users can be satisfied and “the minimum movable distance” in which a user can move to an appropriate AP. While preserving these conditions, we maximize system throughput. When users cannot obtain a throughput greater than “the minimum acceptable throughput” with our proposed AP selection algorithm, they are rejected. Because, if users use streaming applications, which have strict bandwidth demands, with a very low bit-rate connection, they will not be satisfied. Thus, the newly arrived users having low bit-rate connection may be allowed to be rejected before the newly arrived user connects. In this paper, we show the optimal AP by using theoretical proof. We discuss the effectiveness of our proposed AP selection algorithm by using numerical analysis. We also clarify and analyze the characteristics of system throughput. Moreover, we show that a newly arrived user can select the movable distance and acceptable throughput by using examples from graphs depicting every position of newly arrived users. By using the graphs, we also show the relationship between the two parameters (the movable distance and the acceptable throughput) and the optimal AP, and the relationship between the two parameters and optimal system throughput when the movable distance and acceptable throughput are variable.

This paper proposes applying our inter-cell interference (ICI) cancellation method to fractional frequency reuse (FFR) and evaluates the resulting spectral efficiency improvement. With our ICI cancellation method based on base station cooperation, the control station generates ICI replica signals by simple linear processing. Moreover, FFR effectively utilizes frequency resources by both allowing users in the cell-center region to access all available sub-channels and increasing the transmission power to users in the cell-edge region. FFR provides the conditions under which the ICI cancellation method works effectively. Computer simulations show that the average spectral efficiency of the proposed method is comparable to that of cooperative MU-MIMO, which can completely remove ICI.

This paper deals with an integral method analyzing the diffraction of a transverse electric (TE) wave by a perfectly conductive periodic surface. The conventional integral method fails to work for a critical angle of incidence. To overcome such a drawback, this paper applies the method of image Green's function. We newly obtain an image integral equation for the basic surface current in the TE case. The integral equation is solved numerically for a very rough sinusoidal surface. Then, it is found that a reliable solution can be obtained for any real angle of incidence including a critical angle.

We present a fast voting scheme for localizing circular objects among clutter and occlusion. Typical solutions for the problem are based on Hough transform that evaluates an instance of circle by counting the number of edge points along its boundary. The evaluated value is proportional to radius, making the normalization with respect to the factor necessary for detecting circles with different radii. By representing circle with a number of sampled points, we get rid of the step. To evaluate an instance then involves obtaining the same number of edge points, each close to a sampled point in both spatial position and orientation. The closeness is measured by compatibility function, where a truncating operation is used to suppress noise and deal with occlusion. To evaluate all instances of circle is fulfilled by letting edge point vote in a maximizing way such that any instance possesses a set of maximally compatible edge points. The voting process is further separated into the radius-independent and -dependent parts. The time-consuming independent part can be shared by different radii and outputs the sparse matrices. The radius-dependent part shifts these sparse matrices according to the radius. We present precision-recall curves showing that the proposed approach outperforms the solutions based on Hough transform, at the same time, achieves the comparable time complexity as algorithm of Hough transform using 2D accumulator array.

Effects of conductive defects on unipolar resistive random access memory (RRAM) are investigated in order to reduce the operation current for high density and low power RRAM applications. It is clarified that forming voltage decreases with increasing charged conductive defects which are a source of conductive filament (CF) path and with decreasing cell thickness. Random circuit breaker (RCB) network simulation model which is a dynamic percolation simulation model is used to elucidate these effects. From this simulation results, the optimal cell thickness with sufficient conductive defect shows improved resistive switching characteristics such as low forming voltage, small set voltage distribution and low reset current. From the deep understanding of relationship between conductive defect in various cell thickness and other resistive switching parameters, RRAM with low forming voltage and reset current can be obtained and it will be one of the most promising next generation nonvolatile memories.

In this letter, we propose a novel resource allocation scheme to enhance downlink system performance for orthogonal frequency division multiple access (OFDMA) and time division duplex (TDD) based femtocell networks. In the proposed scheme, the macro base station (mBS) and femto base stations (fBSs) service macro user equipments (mUEs) and femto user equipments (fUEs) in inner and outer zones in different periods to reduce interference substantially. Simulations show the proposed scheme outperforms femtocell networks with fractional frequency reuse (FFR) systems in terms of the system capacity and outage probability for mUEs and fUEs.

This paper proposes a video-quality estimation method based on a reduced-reference model for realtime quality monitoring in video streaming services. The proposed method chooses representative-luminance values for individual original-video frames at a server side and transmits those values, along with the pixel-position information of the representative-luminance values in each frame. On the basis of this information, peak signal-to-noise ratio (PSNR) values at client sides can be estimated. This enables realtime monitoring of video-quality degradation by transmission errors. Experimental results show that accurate PSNR estimation can be achieved with additional information at a low bit rate. For SDTV video sequences which are encoded at 1 to 5 Mbps, accurate PSNR estimation (correlation coefficient of 0.92 to 0.95) is achieved with small amount of additional information of 10 to 50 kbps. This enables accurate realtime quality monitoring in video streaming services without average video-quality degradation.

We recently determined the values of intrinsic spin-orbit (SO) parameters for In0.52Al0.48As/In0.53Ga0.47As(10 nm)/In0.52Al0.48As (InGaAs/InAlAs) quantum wells (QW), lattice-matched to (001) InP, from the weak localization/antilocalization analysis of the low-temperature magneto-conductivity measurements [1]. We have then studied the subband energy spectra for the InGaAs/InAlAs double QW system from beatings in the Shubnikov de Haas (SdH) oscillations. The basic properties obtained here for the double QW system provides useful information for realizing nonmagnetic spin-filter devices based on the spin-orbit interaction [2].

Decoding of Reed-Solomon (RS) codes requires many arithmetic operations in the Galois field. While the software decoding of RS codes has the advantage of its flexibility to support RS codes of variable parameters, the speed of the software decoding is slower than dedicated hardware RS decoders because arithmetic operations in the Galois field on an ordinary processor require many instruction steps. To achieve fast software decoding of RS codes, it is effective to accelerate Galois operations by both dedicated circuitry and parallel processing. In this paper, an accelerator is proposed which is attached to the base processor to speed up the software decoding of RS codes by parallel execution of Galois operations.

This paper presents fundamental concepts, overall process and recent research issues of Mining Software Repositories. The data sources such as source control systems, bug tracking systems or archived communications, data types and techniques used for general MSR problems are also presented. Finally, evaluation approaches, opportunities and challenge issues are given.