Ultra-wideband (UWB) beamforming is now attracting significant research attention for attaining spatial gain from array antennas. It is commonly believed that directional antenna based communication could improve the system performance. In order to further make clear the relationship between system performance and the antenna array beamforming, UWB indoor channels are extracted from practical measurements and circular horn antenna is used to characterize the channel properties and to evaluate the system performance. Using a single beam directional antenna with a certain half power beamwidth (HPBW), the channel capacity and the bit-error-rate (BER) performance of a UWB RAKE receiver are evaluated. In the line-of-sight (LOS) environments, the channel capacity and BER performance are improved with the beamwidth becoming smaller. However in the non-line-of-sight (NLOS) environments, the capacity and BER performance are not always better with directional antennas. And the variation trend between the system performance and the antenna beamwidth disappears. This is mainly because that there exist no dominant strong path components like those seen in LOS environments. Then beam combining is introduced to further improve the system performance. Simulation results show that the channel capacity and BER performance cloud be greatly improved by multiple beam combining, especially for the NLOS environments. This reminds us that when antenna beamforming is used to obtain array gain, the beamwidth should be carefully designed and beam combining is necessary to obtain optimal performance, especially in NLOS environments.

Facial paralysis is a popular clinical condition occurring in 30 to 40 patients per 100,000 people per year. A quantitative tool to support medical diagnostics is necessary. This paper proposes a simple, visual and robust method that can objectively measure the degree of the facial paralysis by the use of spatiotemporal features. The main contribution of this paper is the proposal of an effective spatiotemporal feature extraction method based on a tracking of landmarks. Our method overcomes the drawbacks of the other techniques such as the influence of irrelevant regions, noise, illumination change and time-consuming process. In addition, the method is simple and visual. The simplification helps to reduce the time-consuming process. Also, the movements of landmarks, which relate to muscle movement ability, are visual. Therefore, the visualization helps reveal regions of serious facial paralysis. For recognition rate, experimental results show that our proposed method outperformed the other techniques tested on a dynamic facial expression image database.

A broadband mode transition between grounded coplanar waveguide (GCPW) and post-wall waveguide (PWW) is proposed. The transition is composed of GCPW, microstrip line (MSL) and PWW, where the GCPW and PWW are connected via the MSL. The transition is fabricated on liquid crystal polymer (LCP) substrate because of its low dielectric loss and cost effectiveness based on a roll-to-roll fabrication process. Center strip of the GCPW is sandwiched by two ground pads in each of which two through-holes and a rectangular slit are structured. Broadband impedance matching is achieved by this structure thanks to an addition of lumped inductance and capacitance to the transition. A part of the MSL is tapered for the broadband operation. A 25% impedance bandwidth for |S11| less than -15dB is achieved in measurement of a fabricated transition. Loss of the GCPW ground-signal-ground (GSG) pad of 0.12dB and that of the MSL-PWW transition of 0.29dB at 60GHz are evaluated from the measurement. Fabrication error and the caused tolerance on performance are also evaluated and small variation in production is confirmed. The mode transition can be used for low loss antenna-in-package in millimeter-wave applications.

This paper presents a pattern reconfigurable Yagi-Uda antenna on an FR-4 printed circuit board (PCB) for 2.435-2.465GHz-frequency short-range radiocommunication devices. To realize the antenna, pin diodes are attached onto the antenna's driven elements and parasitic elements. The direction of the beam is shifted by alternating the pin diodes status between ON and OFF to induce a quad-directional operation so that E-plane maximum beams are formed in the directions of 135°, 45°, 310° and 225° (i.e. regions 1, 2, 3, 4), respectively. A series of simulations are performed on four parameters: microstrip-to-CPS (coplanar stripline), inter-parasitic spacing, parasitic length, and modes of parasitic elements (i.e. director/reflector) to determine the optimal antenna design. A prototype is fabricated based on the optimal simulation results. The experiments showed very good agreement between the simulation and measured results with regard to the reflection coefficients, radiation patterns and gains for all four beams.

Even though the IEEE 802.15.4 standard defines processes for handling the loss of beacon frames in beacon-enabled low-rate wireless personal area networks (LR-WPANs), they are not efficient nor detailed. This letter proposes an enhanced process to improve the throughput performance of LR-WPANs under the losses of beacon frames. The key idea of our proposed enhancement is to make devices that have not received a beacon frame, due to packet loss, to transmit their data in the contention period and even in the inactive period instead of holding pending frames during the whole superframe period. The proposed protocol is evaluated using mathematical analysis as well as simulations, and the throughput improvement of LR-WPANs is proved.

In this paper, we propose SimCS (similarity based on contribution scores) to compute the similarity of scientific papers. For similarity computation, we exploit a notion of a contribution score that indicates how much a paper contributes to another paper citing it. Also, we consider the author dominance of papers in computing contribution scores. We perform extensive experiments with a real-world dataset to show the superiority of SimCS. In comparison with SimCC, the-state-of-the-art method, SimCS not only requires no extra parameter tuning but also shows higher accuracy in similarity computation.

The two-dimensional (2D) interference is one of the major impairments in bit-patterned media recording (BPMR) systems due to small bit and track pitches, especially at high recording densities. To alleviate this problem, we introduced a rate-4/5 constructive inter-track interference (CITI) coding scheme to prevent the destructive data patterns to be written onto a magnetic medium for an uncoded BPMR system, i.e., without error-correction codes. Because the CITI code produces only the hard decision, it cannot be employed in a coded BPMR system that uses a low-density parity-check (LDPC) code. To utilize it in an iterative decoding scheme, we propose a soft CITI coding scheme based on the log-likelihood ratio algebra implementation in Boolean logic mappings in order that the soft CITI coding scheme together with a modified 2D soft-output Viterbi algorithm (SOVA) detector and a LDPC decoder will jointly perform iterative decoding. Simulation results show that the proposed scheme provides a significant performance improvement, in particular when an areal density (AD) is high and/or the position jitter is large. Specifically, at a bit-error rate of 10-4 and no position jitter, the proposed system can provide approximately 1.8 and 3.5 dB gain over the conventional coded system without using the CITI code at the ADs of 2.5 and 3.0 Tera-bit per square inch (Tb/in2), respectively.

The challenges of providing a divide-and-conquer strategy for tackling large geospatial raster data input/output (I/O) are longstanding. Solutions need to change with advances in the technology and hardware. After analyzing the reason for the problems of traditional parallel raster I/O mode, a parallel I/O strategy using file view is proposed to solve these problems. Message Passing Interface I/O (MPI-IO) is used to implement this strategy. Experimental results show how a file view approach can be effectively married to General Parallel File System (GPFS). A suitable file view setting provides an efficient solution to parallel geospatial raster data I/O.

Postcopy live migration is a promising alternative of virtual machine (VM) migration, which transfers memory pages after switching the execution host of a VM. It allows a shorter and more deterministic migration time than precopy migration. There is, however, a possibility that postcopy migration would degrade VM performance just after switching the execution host. In this paper, we propose a performance improvement technique of postcopy migration, extending the para-virtualized page fault mechanism of a virtual machine monitor. When the guest operating system accesses a not-yet-transferred memory page, our proposed mechanism allows the guest kernel to defer the execution of the current process until the page data is transferred. In parallel with the page transfer, the guest kernel can yield VCPU to other active processes. We implemented the proposed technique in our postcopy migration mechanism for Qemu/KVM. Through experiments, we confirmed that our technique successfully alleviated performance degradation of postcopy migration for web server and database benchmarks.

In this letter, we propose a novel supervised pre-training technique for deep neural network (DNN)-hidden Markov model systems to achieve robust speech recognition in adverse environments. In the proposed approach, our aim is to initialize the DNN parameters such that they yield abstract features robust to acoustic environment variations. In order to achieve this, we first derive the abstract features from an early fine-tuned DNN model which is trained based on a clean speech database. By using the derived abstract features as the target values, the standard error back-propagation algorithm with the stochastic gradient descent method is performed to estimate the initial parameters of the DNN. The performance of the proposed algorithm was evaluated on Aurora-4 DB, and better results were observed compared to a number of conventional pre-training methods.

Determining an effective way to reduce computation complexity is an essential task for adaptive echo cancellation applications. Recently, a family of partial update (PU) adaptive algorithms has been proposed to effectively reduce computational complexity. However, because a PU algorithm updates only a portion of the weights of the adaptive filters, the rate of convergence is reduced. To address this issue, this paper proposes an enhanced switching-based variable step-size (ES-VSS) approach to the M-max PU least mean square (LMS) algorithm. The step-size is determined by the correlation between the error signals and their noise-free versions. Noise-free error signals are approximated according to the level of convergence achieved during the adaptation process. The approximation of the noise-free error signals switches among four modes, such that the resulting step-size is as close to its optimal value as possible. Simulation results show that when only a half of all taps are updated in a single iteration, the proposed method significantly enhances the convergence rate of the M-max PU LMS algorithm.

This paper proposes a novel matching pursuit generalized approximate message passing (MPGAMP) algorithm which explores the support of sparse representation coefficients step by step, and estimates the mean and variance of non-zero elements at each step based on a generalized-approximate-message-passing-like scheme. In contrast to the classic message passing based algorithms and matching pursuit based algorithms, our proposed algorithm saves a lot of intermediate process memory, and does not calculate the inverse matrix. Numerical experiments show that MPGAMP algorithm can recover a sparse signal from compressed sensing measurements very well, and maintain good performance even for non-zero mean projection matrix and strong correlated projection matrix.

In the literature, many cryptosystems have been proposed to be secure under the Strong Diffie-Hellman (SDH) and related problems. For example, there is a cryptosystem that is based on the SDH/related problem or allows the Diffie-Hellman oracle. If the cryptosystem employs general domain parameters, this leads to a significant security loss caused by Cheon's algorithm [14], [15]. However, all elliptic curve domain parameters explicitly recommended in the standards (e.g., ANSI X9.62/63 [1], [2], FIPS PUB 186-4 [43], SEC 2 [50], [51]) are susceptible to Cheon's algorithm [14], [15]. In this paper, we first prove that (q-1)(q+1) is always divisible by 24 for any prime order q>3. Based on this result and depending on small divisors d1,d2≤(log q)2, we classify primes q>3, such that both (q-1)/d1 and (q+1)/d2 are primes, into Perfect, Semiperfect, SEC1v2 and Acceptable. Then, we describe algorithmic procedures and show their simulation results of secure elliptic curve domain parameters over prime/character 2 finite fields resistant to Cheon's algorithm [14], [15]. Also, several examples of the secure elliptic curve domain parameters (including Perfect or Semiperfect prime q) are followed.

Conventional localization techniques such as triangulation and multilateration are not reliable in non-line-of-sight (NLOS) environments such as dense urban areas. Although fingerprint-based localization techniques have been proposed to solve this problem, we may face difficulties because we do not know the parameters of the illegal radio when creating the fingerprint database. This paper proposes a novel technique to localize illegal radios in an urban environment by interpolating the channel impulse responses stored as fingerprints in a database. The proposed interpolation technique consists of interpolation in the bandwidth (delay), frequency and spatial domains. A localization algorithm that minimizes the squared error criterion is employed in this paper, and the proposed technique is evaluated through Monte Carlo simulations using location fingerprints obtained from ray-tracing simulations. Results show that utilizing an interpolated fingerprint database is advantageous in such scenarios.

In this paper, we propose a low-power circuit-shared static flip-flop (CS2FF) for extremely low power digital VLSIs. The CS2FF consists of five static NORs and two inverters (INVs). The CS2FF utilizes a positive edge of a buffered clock signal, which is generated from a root clock, to take data into a master latch and a negative edge of the root clock to hold the data in a slave latch. The total number of transistors is only 24, which is the same as the conventional transmission-gate flip flop (TGFF) used in the most standard cell libraries. SPICE simulations in 0.18-µm standard CMOS process demonstrated that our proposed CS2FF achieved clock-to-Q delay of 18.3ns, setup time of 10.0ns, hold time of 5.5ns, and power dissipation of 9.7nW at 1-MHz clock frequency and 0.5-V power supply. The physical design area increased by 16% and power dissipation was reduced by 13% compared with those of conventional TGFF. Measurement results demonstrated that our proposed CS2FF can operate at 0.352V with extremely low energy of 5.93fJ.

The RO (Ring-Oscillator)-based sensor is one of easily-implementable variation sensors, but for decomposing the observed variability into multiple unique device-parameter variations, a large number of ROs with different structures and sensitivities to device-parameters is required. This paper proposes an area efficient device parameter estimation method with sensitivity-configurable ring oscillator (RO). This sensitivity-configurable RO has a number of configurations and the proposed method exploits this property for reducing sensor area and/or improving estimation accuracy. The proposed method selects multiple sets of sensitivity configurations, obtains multiple estimates and computes the average of them for accuracy improvement exploiting an averaging effect. Experimental results with a 32-nm predictive technology model show that the proposed averaging with multiple estimates can reduce the estimation error by 49% or reduce the sensor area by 75% while keeping the accuracy. Compared to previous work with iterative estimation, 23% accuracy improvement is achieved.

Cassuto and Blaum presented a new coding framework for channels whose outputs are overlapping pairs of symbols in storage applications. Such channels are called symbol-pair read channels. Pair distance and pair error are used in symbol-pair read channels. Yaakobi et al. proved a lower bound on the minimum pair distance of cyclic codes. Furthermore, they provided a decoding algorithm for correcting pair errors using a decoder for cyclic codes, and showed the number of pair errors that can be corrected by their algorithm. However, their algorithm cannot correct all pair error vectors within half of the minimum pair distance. In this paper, we propose an efficient decoding algorithm for cyclic codes over symbol-pair read channels. It is based on the relationship between pair errors and syndromes. In addition, we show that the proposed algorithm can correct more pair errors than Yaakobi's algorithm.

The role of an optical low-pass filter (OLPF) in a digital still camera is to remove the high spatial frequencies that cause aliasing, thereby enhancing the image quality. However, this also causes some loss of detail. Yet, when an image is captured without the OLPF, moiré generally appears in the high spatial frequency region of the image. Accordingly, this paper presents a moiré reduction method that allows omission of the OLPF. Since most digital still cameras use a CCD or a CMOS with a Bayer pattern, moiré patterns and color artifacts are simultaneously induced by aliasing at high spatial frequencies. Therefore, in this study, moiré reduction is performed in both the luminance channel to remove the moiré patterns and the color channel to reduce color smearing. To detect the moiré patterns, the spatial frequency response (SFR) of the camera is first analyzed. The moiré regions are identified using patterns related to the SFR of the camera and then analyzed in the frequency domain. The moiré patterns are reduced by removing their frequency components, represented by the inflection point between the high-frequency and DC components in the moiré region. To reduce the color smearing, color changing regions are detected using the color variation ratios for the RGB channels and then corrected by multiplying with the average surrounding colors. Experiments confirm that the proposed method is able to reduce the moiré in both the luminance and color channels, while also preserving the detail.

In this paper, we propose a patch-wise learning based approach to deal with the multiple-shot people re-identification task. In the proposed approach, re-identification is formulated as a patch-wise set-to-set matching problem, with each patch set being matched using a specifically learned Mahalanobis distance metric. The proposed approach has two advantages: (1) a patch-wise representation that moderates the ambiguousness of a non-rigid matching problem (of human body) to an approximate rigid one (of body parts); (2) a patch-wise learning algorithm that enables more constraints to be included in the learning process and results in distance metrics of high quality. We evaluate the proposed approach on popular benchmark datasets and confirm its competitive performance compared to the state-of-the-art methods.

This paper presents a 20GHz Class-C VCO using a noise sensitivity mitigation technique. A radio frequency Class-C VCO suffers from the AM-PM conversion, caused by the non-linear capacitance of cross coupled pair. In this paper, the phase noise degradation mechanism is discussed, and a desensitization technique of AM-PM noise is proposed. In the proposed technique, AM-PM sensitivity is canceled by tuning the tail impedance, which consists of 4-bit resistor switches. A 65-nm CMOS prototype of the proposed VCO demonstrates the oscillation frequency from 19.27 to 22.4GHz, and the phase noise of -105.7dBc/Hz at 1-MHz offset with the power dissipation of 6.84mW, which is equivalent to a Figure-of-Merit of -183.73dBc/Hz.