A power analysis attack is a well-known side-channel attack but the efficiency of the attack is frequently degraded by the existence of power components, irrelative to the encryption included in signals used for the attack. To enhance the performance of the power analysis attack, we propose a preprocessing method based on extracting encryption-related parts from the measured power signals. Experimental results show that the attacks with the preprocessed signals detect correct keys with much fewer signals, compared to the conventional power analysis attacks.

This paper proposes a method for recognizing hand-shapes by using multi-viewpoint image sets. The recognition of a hand-shape is a difficult problem, as appearance of the hand changes largely depending on viewpoint, illumination conditions and individual characteristics. To overcome this problem, we apply the Kernel Orthogonal Mutual Subspace Method (KOMSM) to shift-invariance features obtained from multi-viewpoint images of a hand. When applying KOMSM to hand recognition with a lot of learning images from each class, it is necessary to consider how to run the KOMSM with heavy computational cost due to the kernel trick technique. We propose a new method that can drastically reduce the computational cost of KOMSM by adopting centroids and the number of images belonging to the centroids, which are obtained by using k-means clustering. The validity of the proposed method is demonstrated through evaluation experiments using multi-viewpoint image sets of 30 classes of hand-shapes.

Shape is one of the primary low-level image features in content-based image retrieval. In this paper we propose a new shape description method that consists of a rotationally invariant angular radial transform descriptor (IARTD). The IARTD is a feature vector that combines the magnitude and aligned phases of the angular radial transform (ART) coefficients. A phase correction scheme is employed to produce the aligned phase so that the IARTD is invariant to rotation. The distance between two IARTDs is defined by combining differences in the magnitudes and aligned phases. In an experiment using the MPEG-7 shape dataset, the proposed method outperforms existing methods; the average BEP of the proposed method is 57.69%, while the average BEPs of the invariant Zernike moments descriptor and the traditional ART are 41.64% and 36.51%, respectively.

A 4th-order programmable continuous-time filter (CTF) for hard-disk-drive (HDD) read channels was developed with 65-nm CMOS process technology. The CTF cutoff frequency and boost are programmable by switching units of the operational trans-conductance amplifier (OTA) banks and the capacitor banks. The switches are operated by lifted local-supply voltage to reduce on-resistance of the transistors. The CTF characteristics were robust against process technology variations and supply voltage and temperature ranges due to the introduction of a digitally assisted compensation scheme with analog auto-tuning circuits and digital calibration sequences. The digital calibration sequences, which fit into the operation sequence of the HDD read channel, compensate for the tuning circuits of the process technology variations, and the tuning circuits compensate for the CTF characteristics over the supply voltage and temperature ranges. As a result, the CTF had a programmability of 100–1000-MHz cutoff frequency and 0–12-dB boost.

In this letter, we describe a low power current to time converter for wireless sensor networks. The proposed circuit has some advantages of high linearity and wide measurement range. From the evaluation using HSPICE with 0.18 µm CMOS device parameters, the output differential error for the input current variation is approximately 0.1 µs/nA under the condition that the current is varied from 100 nA to 500 nA. The idle power consumption is approximately zero.

We have proposed a novel geometric model of the eye in order to avoid the problems faced while using the conventional spherical model of the cornea for three dimensional (3D) model-based gaze estimation. The proposed model models the eye, including the boundary region of the cornea, as a general surface of revolution about the optical axis of the eye. Furthermore, a method for calculating the point of gaze (POG) on the basis of our model has been proposed. A prototype system for estimating the POG was developed using this method. The average root mean square errors (RMSEs) of the proposed method were experimentally found to be smaller than those of the gaze estimation method that is based on a spherical model of the cornea.

Non-homogeneous Poisson processes (NHPPs) have gained much popularity in actual software testing phases to estimate the software reliability, the number of remaining faults in software and the software release timing. In this paper, we propose a new modeling approach for the NHPP-based software reliability models (SRMs) to describe the stochastic behavior of software fault-detection processes. The fundamental idea is to apply the equilibrium distribution to the fault-detection time distribution in NHPP-based modeling. We also develop efficient parameter estimation procedures for the proposed NHPP-based SRMs. Through numerical experiments, it can be concluded that the proposed NHPP-based SRMs outperform the existing ones in many data sets from the perspective of goodness-of-fit and prediction performance.

As an add-on device option for the ultra-low power CMOS technology, the double-gated vertical-channel Tunnel Field-Effect Transistors (TFETs) of different source configurations are comparatively studied from the perspectives of fabrication and current drivability. While the top-source design where the source of the device is placed on the top of the fin makes the fabrication and source engineering much easier, it is more susceptible to parasitic resistance issue. The bottom-source design is difficult to engineer the tunneling barrier and may require a special replacement technique. Examples of the schemes to engineer the tunneling barrier for the bottom-source TFET are suggested. A TCAD simulation study on the bottom-source devices shows that both the parasitic resistance of source region and the current enhancement mechanism by field coupling need be carefully considered in designing the source.

Multi-valued Model Checking extends classical, two-valued model checking to multi-valued logic such as Quasi-Boolean logic. The added expressivity is useful in dealing with such concepts as incompleteness and uncertainty in target systems, while it comes with the cost of time and space. Chechik and others proposed an efficient reduction from multi-valued model checking problems to two-valued ones, but to the authors' knowledge, no study was done for multi-valued bounded model checking. In this paper, we propose a novel, efficient algorithm for multi-valued bounded model checking. A notable feature of our algorithm is that it is not based on reduction of multi-values into two-values; instead, it generates a single formula which represents multi-valuedness by a suitable encoding, and asks a standard SAT solver to check its satisfiability. Our experimental results show a significant improvement in the number of variables and clauses and also in execution time compared with the reduction-based one.

The fringe field effects of nano-electromechanical (NEM) nonvolatile memory cells have been investigated analytically for the accurate evaluation of NEM memory cells. As the beam width is scaled down, fringe field effect becomes more severe. It has been observed that pull-in, release and hysteresis voltage decrease more than our prediction. Also, the fringe field on cell characteristics has been discussed.

Switch-and-stay combining (SSC) is a simple diversity technique where a single radio frequency (RF) chain is connected to one of several antenna branches and stays there if the channel quality is satisfied or otherwise switches to a new branch. Compared with Selection Combining (SC), SSC requires less overhead in channel estimation and antenna selection feedback. In this paper, we analyze the performance of SSC in a time-correlated flat fading channel and with causal channel state information. We derive the general expressions for the distribution of the output signal-to-noise ratio (SNR), outage rate and average bit error rate (ABER) and then the analytical results are compared with the simulation results under the Jakes Rayleigh fading channel. Our results show that (1) For slowly varying channels, L branch SSC can achieve the full diversity order and the same outage rate as SC; (2) Increasing the number of antenna branches can improve the performance of SSC, however, the gain from adding antennas diminishes quickly as the channel variation speed increases. Moreover, to avoid the complexity in optimizing the fixed threshold, we also propose a simple adaptive SSC scheme which has almost the same ABER as the SSC with optimized fixed threshold.

With more digital home appliances and network devices having OSGi as the software management platform, the power-saving capability of the OSGi platform has become a critical issue. This paper is aimed at improving the power-efficiency of the OSGi platform, i.e. reducing the energy consumption with minimum performance degradation. The key to this study is an efficient power-saving technique which exploits the runtime information already available in a Java virtual machine (JVM), the base software of the OSGi platform, to best determine the timing of performing DVFS (Dynamic Voltage and Frequency Scaling). This, technically, involves a phase detection scheme that identifies the memory phase of the OSGi-enabled device/server in a correct and almost effortless way. The overhead of the power-saving procedure is thus minimized, and the system performance is well maintained. We have implemented and evaluated the proposed power-saving approach on an OSGi server, where the Apache Felix OSGi implementation and the DaCapo benchmarks were applied. The results show that this approach can achieve real power-efficiency for the OSGi platform, in which the power consumption is significantly reduced and the performance remains highly competitive, compared with the other power-saving techniques.

This paper describes the application of two attractive categories of topic modeling techniques to the problem of spoken document retrieval (SDR), viz. document topic model (DTM) and word topic model (WTM). Apart from using the conventional unsupervised training strategy, we explore a supervised training strategy for estimating these topic models, imagining a scenario that user query logs along with click-through information of relevant documents can be utilized to build an SDR system. This attempt has the potential to associate relevant documents with queries even if they do not share any of the query words, thereby improving on retrieval quality over the baseline system. Likewise, we also study a novel use of pseudo-supervised training to associate relevant documents with queries through a pseudo-feedback procedure. Moreover, in order to lessen SDR performance degradation caused by imperfect speech recognition, we investigate leveraging different levels of index features for topic modeling, including words, syllable-level units, and their combination. We provide a series of experiments conducted on the TDT (TDT-2 and TDT-3) Chinese SDR collections. The empirical results show that the methods deduced from our proposed modeling framework are very effective when compared with a few existing retrieval approaches.

The proposed scheduling scheme minimizes the mean power consumption of real-time tasks with probabilistic computation amounts while meeting their deadlines. Our study formally solves the minimization problem under finitely discrete clock frequencies with irregular power consumptions, whereas state-of-the-arts studies did under infinitely continuous clock frequencies with regular power consumptions.

Kudekar et al. proved an interesting result in low-density parity-check (LDPC) convolutional codes: The belief-propagation (BP) threshold is boosted to the maximum-a-posteriori (MAP) threshold by spatial coupling. Furthermore, the authors showed that the BP threshold for code-division multiple-access (CDMA) systems is improved up to the optimal one via spatial coupling. In this letter, a phenomenological model for elucidating the essence of these phenomenon, called threshold improvement, is proposed. The main result implies that threshold improvement occurs for spatially-coupled general graphical models.

In the framework of decentralized supervisory control of timed discrete event systems (TDESs), each local supervisor decides the set of events to be enabled to occur and the set of events to be forced to occur under its own local observation in order for a given specification to be satisfied. In this paper, we focus on fusion rules for the enforcement decisions and adopt the combined fusion rule using the AND rule and the OR rule. We first derive necessary and sufficient conditions for the existence of a decentralized supervisor under the combined fusion rule for a given partition of the set of forcible events. We next study how to find a suitable partition.

This paper proposes a wide-band noise reduction method using a zero phase (ZP) signal which is defined as the IDFT of a spectral amplitude. When a speech signal has periodicity in a short observation, the corresponding ZP signal becomes also periodic. On the other hand, when a noise spectral amplitude is approximately flat, its ZP signal takes nonzero values only around the origin. Hence, when a periodic speech signal is embedded in a flat spectral noise in an analysis frame, its ZP signal becomes a periodic signal except around the origin. In the proposed noise reduction method, we replace the ZP signal around the origin with the ZP signal in the second or latter period. Then, we get an estimated speech ZP signal. The major advantages of this method are that it can reduce not only stationary wide-band noises but also non-stationary wide-band noises and does not require a prior estimation of the noise spectral amplitude. Simulation results show that the proposed noise reduction method improves the SNR more than 5 dB for a tunnel noise and 13 dB for a clap noise in a low SNR environment.

As RFID technology is being more widely adopted, it is fairly common to read mobile tags using RFID systems, such as packages on conveyer belt and unit loads on pallet jack or forklift truck. In RFID systems, multiple tags use a shared medium for communicating with a reader. It is quite possible that tags will exit the reading area without being read, which results in tag leaking. In this letter, a reliable tag anti-collision algorithm for mobile tags is proposed. It reliably estimates the expectation of the number of tags arriving during a time slot when new tags continually enter the reader's reading area and no tag leaves without being read. In addition, it gives priority to tags that arrived early among read cycles and applies the expectation of the number of tags arriving during a time slot to the determination of the number of slots in the initial inventory round of the next read cycle. Simulation results show that the reliability of the proposed algorithm is close to that of DFSA algorithm when the expectation of the number of tags entering the reading area during a time slot is a given, and is better than that of DFSA algorithm when the number of time slots in the initial inventory round of next read cycle is set to 1 assuming that the number of tags arriving during a time slot follows Poisson distribution.

Thin-film 2-arm Archimedean spiral antenna coupled with a bismuth (Bi) microbolometer was fabricated on a fused quartz substrate backed by cupper (Cu) plate reflector. Antenna patterns of the device agreed with the theoretical patterns derived from the imaging force model at 100 GHz band. The detected voltages of the antenna exhibited a periodic variation with changing the thickness of the substrate. The maximum and minimum detected voltages were obtained when the substrate thickness was odd and even integer multiples of a quarter of the wavelength in the substrate, respectively. Furthermore, the detected voltages were almost constant within the change of 3 dB ranging from 76.9 to 106.8 GHz. The wide band characteristic of the antenna was obtained.

In this paper, we analyze current-voltage characteristics of InSb/AlInSb triple-barrier resonant tunneling diodes (TBRTDs) with spin-splitting under zero magnetic fields. The InSb has very small effective mass, thus we can obtain large spin-splitting by Rashba spin-orbit interaction due to asymmetric InSb/AlInSb quantum wells. In our model, broadening of each resonant tunneling level and spin-splitting energy can be considered to calculate spin-polarized resonant tunneling current.