In this paper, a non-isolated bidirectional DC-DC converter with zero voltage switching and constant switching frequency is proposed. Unlike the active clamp bidirectional converters, to create soft switching condition in both direction, only one auxiliary switch is used, which reduces conduction losses and the complexity of the circuit. The proposed converter is controlled by pulse width modulation and the switches are gated complementary, thus the implementation of the control circuit is simple. Low switching losses, high efficiency, high power density, are the advantages of this converter. The simulation and experimental results of the converter verify theoretical analysis. Based on an implemented prototype of the proposed converter at 80 watts, the measured efficiency is 96.5%.

To identify problems in a software development process, we have been developing an automated measurement tool called TaskPit, which monitors software development tasks such as programming, testing and documentation based on the execution history of software applications. This paper introduces the system requirements, design and implementation of TaskPit; then, presents two real-world case studies applying TaskPit to actual software development. In the first case study, we applied TaskPit to 12 software developers in a certain software development division. As a result, several concerns (to be improved) have been revealed such as (a) a project leader spent too much time on development tasks while he was supposed to be a manager rather than a developer, (b) several developers rarely used e-mails despite the company's instruction to use e-mail as much as possible to leave communication records during development, and (c) several developers wrote too long e-mails to their customers. In the second case study, we have recorded the planned, actual, and self reported time of development tasks. As a result, we found that (d) there were unplanned tasks in more than half of days, and (e) the declared time became closer day by day to the actual time measured by TaskPit. These findings suggest that TaskPit is useful not only for a project manager who is responsible for process monitoring and improvement but also for a developer who wants to improve by him/herself.

An improved multivariate wavelet denoising algorithm combined with subspace and principal component analysis is presented in this paper. The key element is deriving an optimal orthogonal matrix that can project the multivariate observation signal to a signal subspace from observation space. Univariate wavelet shrinkage operator is then applied to the projected signals channel-wise resulting in the improvement of the output SNR. Finally, principal component analysis is performed on the denoised signal in the observation space to further improve the denoising performance. Experimental results based on synthesized and real world ECG data verify the effectiveness of the proposed algorithm.

In this paper, a hamburger architecture with a 3D stacked reconfigurable memory is proposed for a 4K motion estimation (ME) processor. By positioning the memory dies on both the top and bottom sides of the processor die, the proposed hamburger architecture can reduce the usage of the signal through-silicon via (TSV), and balance the power delivery network and the clock tree of the entire system. It results in 1/3 reduction of the usage of signal TSVs. Moreover, a stacked reconfigurable memory architecture is proposed to reduce the fabrication complexity and further reduce the number of signal TSVs by more than 1/2. The reduction of signal TSVs in the entire design is 71.24%. Finally, we address unique issues that occur in electronic design automation (EDA) tools during 3D large-scale integration (LSI) designs. As a result, a 4K ME processor with 7-die stacking 3D system-on-chip design is implemented. The proposed design can support real time 3840 × 2160 @ 120 fps encoding at 130 MHz with less than 540 mW.

Feature extractor plays an important role in visual tracking, but most state-of-the-art methods employ the same feature representation in all scenes. Taking into account the diverseness, a tracker should choose different features according to the videos. In this work, we propose a novel feature adaptive correlation tracker, which decomposes the tracking task into translation and scale estimation. According to the luminance of the target, our approach automatically selects either hierarchical convolutional features or histogram of oriented gradient features in translation for varied scenarios. Furthermore, we employ a discriminative correlation filter to handle scale variations. Extensive experiments are performed on a large-scale benchmark challenging dataset. And the results show that the proposed algorithm outperforms state-of-the-art trackers in accuracy and robustness.

In this paper we propose a method for estimating time-to-contact in scattering media. Images taken in scattering media are often unclear and blurry, making it difficult to detect appropriate geometric information from these images for computing the 3 dimensional properties of the scene. Therefore, instead of searching for geometric information, we attempt to use photometric information instead. In our approach, we use the observed image intensity. The method proposed in this paper is able to utilize the effect of scattering media on the resultant image and estimate the time-to-contact toward objects without any prior knowledge of the scene, cameras, and the scattering media. This method is then evaluated using simulated and real images.

The compressive sensing (CS) theory has been widely used in synthetic aperture radar (SAR) imaging for its ability to reconstruct image from an extremely small set of measurements than what is generally considered necessary. Because block-based CS approaches in SAR imaging always cause block boundaries between two adjacent blocks, resulting in namely the block artefacts. In this paper, we propose a weighted overlapped block-based compressive sensing (WOBCS) method to reduce the block artefacts and accomplish SAR imaging. It has two main characteristics: 1) the strategy of sensing small and recovering big and 2) adaptive weighting technique among overlapped blocks. This proposed method is implemented by the well-known CS recovery schemes like orthogonal matching pursuit (OMP) and BCS-SPL. Promising results are demonstrated through several experiments.

In this work, we study efficient scheduling with network coding in a scalable video coding (SVC) multicast system. Transmission consists of two stages. The original SVC packets are multicasted by the server in the first stage and the lost packets are retransmitted in the second stage. With deadline constraint, the consumer can be only satisfied when the requested packets are received before expiration. Further, the hierarchical encoding architecture of SVC introduces extra decoding delay which poses a challenge for providing acceptable reconstructed video quality. To solve these problems, instantly decodable network coding is applied for reducing the decoding delay, and a novel packet weighted policy is designed to better describe the contribution a packet can make in upgrading the recovered video quality. Finally, an online packet scheduling algorithm based on the maximal weighted clique is proposed to improve the delay, deadline miss ratio and users' experience. Multiple characteristics of SVC packets, such as the packet utility, the slack time and the number of undelivered/wanted packets, are jointly considered. Simulation results prove that the proposed algorithm requires fewer retransmissions and achieves lower deadline miss ratio. Moreover, the algorithm enjoys fine recovery video quality and provides high user satisfaction.

Zero correlation zone (ZCZ) aperiodic complementary sequence (ZACS) sets have potential applications in multi-carriers (MC) CDMA communication systems, which can support more users than traditional complementary sequence sets. In this letter, methods for constructing ZACS sets based on orthogonal matrices are proposed. The new constructions may propose ZACS sets with optimal parameters. The new ZACS sets can be applied in approximately synchronized MC-CDMA to remove interferences.

The quality assessment of screen content images (SCIs) has been attractive recently. Different from natural images, SCI is usually a mixture of picture and text. Traditional quality metrics are mainly designed for natural images, which do not fit well into the SCIs. Motivated by this, this letter presents a simple and effective method to naturalize SCIs, so that the traditional quality models can be applied for SCI quality prediction. Specifically, bicubic interpolation-based up-sampling is proposed to achieve this goal. Extensive experiments and comparisons demonstrate the effectiveness of the proposed method.

The Android pattern unlock is a widely adopted graphical password system that requires a user to draw a secret pattern connecting points arranged in a grid. The theoretical security of pattern unlock can be defined by the number of possible patterns. However, only upper bounds of the number of patterns have been known except for 3×3 and 4×4 grids for which the exact number of patterns was found by brute-force enumeration. In this letter, we present the first lower bound by computing the minimum number of visible points from each point in various subgrids.

This paper presents a hybrid push/pull streaming scheme to take advantage of both the interval caching-based push method and the mesh-based pull method. When a new peer joins, a mesh-based pull method is adopted to avoid the overhead to reorganize the structure only if all of its potential preceding peers are likely to leave before the end of its playback. Otherwise, an interval caching-based push method is adopted so that the better performance of the push method can be maintained until it completes the playback. We demonstrate that our proposed scheme outperforms compared with when either the interval caching-based push method or mesh-based pull method is employed alone.

A text-dependent i-vector extraction scheme and a lexicon-based binary vector (L-vector) representation are proposed to improve the performance of text-dependent speaker verification. I-vector and L-vector are used to represent the utterances for enrollment and test. An improved cosine distance kernel is constructed by combining i-vector and L-vector together and is used to distinguish both speaker identity and lexical (or text) diversity with back-end support vector machine (SVM). Experiments are conducted on RSR 2015 Corpus part 1 and part 2, the results indicate that at most 30% improvement can be obtained compared with traditional i-vector baseline.

A comprehensive model is presented for estimating the bit error rate (BER) of write disturbance in a resistive memory composed of a cross-point array. While writing a datum into the selected address, the non-selected addresses are biased by word-line (WL) and bit-line (BL). The stored datum in the non-selected addresses will be disturbed if the bias is large enough. It is necessary for the current flowing through the non-selected address to be calculated in order to estimate the BER of the write disturbance. Since it takes a long time to calculate the current flowing in a large-scale cross-point array, several simplified circuits have been utilized to decrease the calculating time. However, these simplified circuits are available to the selected address, not to the non-selected one. In this paper, new simplified circuits are proposed for calculating the current flowing through the non-selected address. The proposed and the conventional simplified circuits are used, and on that basis the trade-off between the write disturbance and the write error is discussed. Furthermore, the error correcting code (ECC) is introduced to improve the trade-off and to provide the low-cost memory chip matching current production lines.

Wireless sensor networks are being used in many disaster-related applications. Certain types of disasters are studied and modeled with different and dynamic risk estimations in different areas, hence requiring different levels of monitoring. Such nonuniform and dynamic coverage requirements pose a challenge to a sensor coverage problem. This work proposes the Mobile sensor Relocation using Delaunay triangulation And Shifting on Hill climbing (MR-DASH) approach, which calculates an appropriate location for each mobile sensor as an attempt to maximize coverage ratio. Based on a probabilistic sensing model, it constructs a Delaunay triangulation from static sensors' locations and vertices of interesting regions. The resulting triangles are then prioritized based on their sizes and corresponding levels of requirement so that mobile sensors can be relocated accordingly. The proposed method was both compared with an existing previous work and demonstrated with real-world disaster scenarios by simulation. The result showed that MR-DASH gives appropriate target locations that significantly improve the coverage ratio with relatively low total sensors' moving distance, while properly adapting to variations in coverage requirements.

When debugging bugs, programmers often prepare test cases to reproduce buggy behaviours. However, for concurrent programs, test cases alone are typically insufficient to reproduce buggy behaviours, due to the nondeterminism of multi-threaded executions. In literature, various approaches have been proposed to reproduce buggy behaviours for concurrency bugs deterministically, but to the best of our knowledge, they are still limited. In particular, we have recognized three debugging scenarios from programming practice, but existing approaches can handle only one of the scenarios. In this paper, we propose a novel approach, called SPDebugger, that provides finer-grained thread controlling over test cases, programs under test, and even third party library code, to reproduce the predesigned thread execution schedule. The evaluation shows that SPDebugger handles more debugging scenarios than the state-of-the-art tool, called IMUnit, with similar human effort.

3GPP (3rd Generation Partnership Project) has started to discuss D2D (Device-to-Device)-aided OTDOA (Observed Time Difference Of Arrival) as one of the mobile positioning enhancement techniques for LTE (Long Term Evolution) systems. It is a kind of multi-node based OTDOA which directly receives D2D signals from adjacent multiple UEs (User Equipment) to measure RSTD (Reference Signal's Time Difference). D2D signals provide valuable advantages in terms of OTDOA positioning because it can guarantee more reference nodes and high SNR (Signal-to-Noise Ratio) of PRS (Positioning Reference Signal). Two typical methods for multi-node based OTDOA can be applied to D2D-aided OTDOA. Multiple OTDOA positioning is one of the multi-node based methods that averages multiple results from OTDOA; however, it cannot always guarantee high accuracy due to the non-uniform geometry of UEs. OTDOA positioning based on TSE (Taylor Series Expansion) algorithm may be one of the solutions; however, it has the initial value problem and high computational complexity due to its iterative procedure. Therefore, in this paper, we propose a novel D2D-aided OTDOA positioning method which utilizes UEs not as reference node of OTDOA but as assisting node for RSTD error reduction. The proposed method can reduce RSTD error of eNB based hyperbola by using multiple hyperbola bands. The hyperbola band indicates the possible range in which a hyperbola can occur due to RSTD error. Then, by using principal axes of hyperbolas, we estimate a modified hyperbola from the overlap area of hyperbola bands, which has less RSTD error. We verify that the proposed method can effectively reduce RSTD error and improve positioning performance with lower computational complexity.

In this review, we present recent advances relating to superconducting nanowire single-photon detectors (SSPDs or SNSPDs) and their broad range of applications. During a period exceeding ten years, the system performance of SSPDs has been drastically improved, and lately excellent detection efficiencies have been realized in practical systems for a wide range of target photon wavelengths. Owing to their advantages such as high system detection efficiency, low dark count rate, and excellent timing jitter, SSPDs have found application in various research fields such as quantum information, quantum optics, optical communication, and also in the life sciences. We summarize the photon detection principle and the current performance status of practical SSPD systems. In addition, we introduce application examples in which SSPDs have been applied.

Antenna-coupled kinetic inductance detectors (KIDs) have recently shown great promise as microwave detection systems with a large number of channels. However, this technique, still has difficulties in eliminating the radiation loss of the resonator signals. To solve this problem, we propose a design in which the absorption area connected to an antenna is located on the ground-side of a coplanar waveguide. Thereby, radiation loss due to leakage from the resonator to the antenna can be considerably reduced. This simple design also enables the use of a contact aligner for fabrication. We have developed KIDs with this design, named as the ground-side absorption (GSA)-KIDs and demonstrated that they have higher quality factors than those of the existing KIDs, while maintaining a good total sensitivity.