As the number of surveillance cameras keeps increasing, the demand for automated traffic-monitoring systems is growing. In this paper, we propose a practical vehicle detection method for such systems. In the last decade, vehicle detection mainly has been performed by employing an image scan strategy based on sliding windows whereby a pre-trained appearance model is applied to all image areas. In this approach, because the appearance models are built from vehicle sample images, the normalization of the scales and aspect ratios of samples can significantly influence the performance of vehicle detection. Thus, to successfully apply sliding window schemes to detection, it is crucial to select the normalization sizes very carefully in a wise manner. To address this, we present a novel vehicle detection technique. In contrast to conventional methods that determine the normalization sizes without considering given scene conditions, our technique first learns local region-specific size models based on scene-contextual clues, and then utilizes the obtained size models to normalize samples to construct more elaborate appearance models, namely local size-specific classifiers (LSCs). LSCs can provide advantages in terms of both accuracy and operational speed because they ignore unnecessary information on vehicles that are observable in faraway areas from each sliding window position. We conduct experiments on real highway traffic videos, and demonstrate that the proposed method achieves a 16% increased detection accuracy with at least 3 times faster operational speed compared with the state-of-the-art technique.

Self-luminous light sources in the real world often have nonnegligible sizes and radiate light inhomogeneously. Acquiring the model of such a light source is highly important for accurate image synthesis and understanding. In this paper, we propose an approach to measuring 4D light fields of self-luminous extended light sources by using a liquid crystal (LC) panel, i.e. a programmable optical filter and a diffuse-reflection board. The proposed approach recovers the 4D light field from the images of the board illuminated by the light radiated from a light source and passing through the LC panel. We make use of the feature that the transmittance of the LC panel can be controlled both spatially and temporally. The approach enables multiplexed sensing and adaptive sensing, and therefore is able to acquire 4D light fields more efficiently and densely than the straightforward method. We implemented the prototype setup, and confirmed through a number of experiments that our approach is effective for modeling self-luminous extended light sources in the real world.

Finding software vulnerabilities in source code before the program gets deployed is crucial to ensure the software quality. Existing source code auditing tools for vulnerability detection generate too many false positives, and only limited types of vulnerability can be detected automatically. In this paper, we propose an extendable mechanism to reveal vulnerabilities in source code with low false positives by specifying security requirements and detecting requirement violations of the potential vulnerable sinks. The experimental results show that the proposed mechanism can detect vulnerabilities with zero false positives and indicate the extendability of the mechanism to cover more types of vulnerabilities.

For phase stabilization of two-tone coherent millimeter-wave/microwave carrier generation, two types of phase detection schemes were devised based on lightwave interferometric technique, the Mach-Zehnder interferometric method and the pseudo Mach-Zehnder interferometric method. The former system showed clear eye patterns at both OOK and PSK modulations of 1 Gbit/s on the 12.5-GHz carrier. The latter system demonstrated the error-free transmission at OOK modulation of 11 Gbit/s on the 100-GHz carrier.

Light field data, which is composed of multi-view images, have various 3D applications. However, the cost of acquiring many images from slightly different viewpoints sometimes makes the use of light fields impractical. Here, compressive sensing is a new way to obtain the entire light field data from only a few camera shots instead of taking all the images individually. In paticular, the coded aperture/mask technique enables us to capture light field data in a compressive way through a single camera. A pixel value recorded by such a camera is a sum of the light rays that pass though different positions on the coded aperture/mask. The target light field can be reconstructed from the recorded pixel values by using prior information on the light field signal. As prior information, the current state of the art uses a dictionary (light field atoms) learned from training datasets. Meanwhile, it was reported that general bases such as those of the discrete cosine transform (DCT) are not suitable for efficiently representing prior information. In this study, however, we demonstrate that a 4D-DCT basis works surprisingly well when it is combined with a weighting scheme that considers the amplitude differences between DCT coefficients. Simulations using 18 light field datasets show the superiority of the weighted 4D-DCT basis to the learned dictionary. Furthermore, we analyzed a disparity-dependent property of the reconstructed data that is unique to light fields.

In this paper, we consider a two-hop relay network with a decode-and-forward (DF) relaying protocol where a multi-input/multi-output (MIMO) relay station (RS) is deployed in a cell edge to extend cell coverage of a base station (BS). We propose two MIMO relaying schemes to improve the quality of the BS-RS link, which is a key to improve data rates in the DF relaying: 1) spatial multiplexed MIMO antenna relaying (SM-MAR) with a uniform channel decomposition (UCD) precoder, and 2) MIMO relaying with section diversity (SD-MAR). In the SM-MAR, we greatly simplify user allocation by the UCD precoder and propose a sophisticated rate maximization technique to resolve the non-convexity of rate maximization problems. Through simulations, we show that the proposed UCD based power allocation exhibits up to two times higher achievable throughput than other techniques. In addition, the proposed SD-MAR supports the BS with a single transmit antenna and increases the signal quality of the BS-RS link with the selection diversity at the RS, which is much simpler to be implemented. For the SD-MAR, we derive a closed form expression for the achievable throughput and show that the selection diversity plays more important role on the achievable throughput than the multiuser diversity.

Outside wireless signals often obstruct GNSS receivers from acquiring satellite signals. Traditional anti-jamming algorithms are used to suppress interference using a convex optimization method based on minimizing output power. These algorithms can reduce interference. However, these models suppress satellite signals as well as jamming interference. Under the high-dynamic condition, the output signal-to-interference-and-noise ratio (SINR) deteriorates seriously and the success rate in acquiring satellite signals falls accordingly. This paper introduces a novel, broadened model with a no-main-lobe-and-multi-virtual-null-constraints (NMLCB) method based on maximizing output power and constraining interference sources. With the new method, GNSS receivers can receive satellite signals more easily than using the power inversion (PI) and power minimization with derivative constraints null (NB) methods under the high-dynamic condition.

In this research, we investigated the reliability of a 1-out-of-2 system with two-stage repair comprising hardware restoration and data reconstruction modes. Hardware restoration is normally independently executed by two modules. In contrast, we assumed that one of the modules could omit data reconstruction by replicating the data from the module during normal operation. In this 1-out-of-2 system, the two modules mutually cooperated in the recovery mode. As a first step, an evaluation model using Markov chains was constructed to derive a reliability measure: “unavailability in steady state.” Numerical examples confirmed that the reliability of the system was improved by the use of two cooperating modules. As the data reconstruction time increased, the gains in terms of system reliability also increased.

The copy-move or region duplication forgery technique is a very common type of image manipulation, where a region of the image is copied and then pasted in the same image in order to hide some details. In this paper, a keypoint-based method for copy-move forgery detection is proposed. Firstly, the feature points are detected from the image by using the Förstner Operator. Secondly, the algorithm extracts the features by using MROGH feature descriptor, and then matching the features. Finally, the affine transformation parameters can be estimated using the RANSAC algorithm. Experimental results are presented to confirm that the proposed method is effective to locate the altered region with geometric transformation (rotation and scaling).

In this paper, we consider filter-and-forward relay beamforming using orthogonal frequency-division multiplexing (OFDM) in the presence of inter-block interference (IBI). We propose a filter design method based on a constrained max-min problem, which aims to suppress IBI and also avoid deep nulls in the frequency domain. It is shown that IBI can be suppressed completely owing to the employment of beamforming with multiple relays or multiple receive antennas at each relay when perfect channel state information (CSI) is available. In addition, we modify the proposed method to cover the case where only the partial CSI for relay-receiver channels is available. Numerical simulation results show that the proposed method significantly improves the performance as the number of relays and antennas increases due to spatial diversity, and the modified method can make use of the channel correlation to improve the performance.

With the appearance of large OLED panels, the OLED TV industry has experienced significant growth. However, this technology is still in the early stages of commercialization, and some technical challenges remain to be overcome. During the development phase of a product, power consumption is one of the most important considerations. To reduce power consumption in OLED displays, we propose a method based on just-noticeable difference (JND). JND refers to the minimum visibility threshold when visual content is altered and results from physiological and psychophysical phenomena in the human visual system (HVS). A JND model suitable for OLED displays is derived from numerous experiments with OLED displays. With the use of JND, it is possible to reduce power consumption while minimizing perceptual image quality degradation.

Circuit performance of SiC-MOSFET-based bidirectional isolated DC/DC converters is investigated based on circuit simulation with the physically accurate compact device model HiSIM_HV. It is demonstrated that the combined optimization of the MOSFETs Ron and of the inductances in the transformer can enable a conversion efficiency of more than 97%. The simulation study also verifies that the possible efficiency improvements are diminished due to the MOSFET-performance degradation, namely the carrier-mobility reduction, which results in a limitation of the possible Ron reduction. It is further demonstrated that an optimization of the MOSFET-operation conditions is important to utilize the resulting higher MOSFET performance for achieving additional converter efficiency improvements.

To achieve overall business goals, GQM+Strategies is one approach that aligns business goals at each level of an organization to strategies and assesses the achievement of goals. Strategies are based on rationales (contexts and assumptions). Because extracting all rationales is an important process in the GQM+Strategies approach, we propose the Context-Assumption-Matrix (CAM), which refines the GQM+Strategies model by extracting rationales based on analyzing the relationships between stakeholders, and the process of using GQM+Strategies with CAM effectively. To demonstrate the effectiveness of the CAM and the defined process, we conducted three experiments involving students majoring in information sciences at two different Japanese universities. Moreover, we applied the GQM+Strategies approach with CAM to the Recruit Sumai Company in Japan. The results reveal that compared to GQM+Strategies alone, GQM+Strategies with CAM can extract rationales of the same quality more efficiently and exhaustively.

A compact multiple-input multiple-output (MIMO) dielectric resonator antenna (DRA) was proposed and studied. The DRA consists of three antenna ports. The antennas operate at 2.4GHz, where one of the antenna ports was placed at the center and resonates in the monopole mode, and the two other ports were located at the sides and resonate in the TEy111 mode. Both simulation and measurements were carried out, and reasonably good agreement was obtained. In addition, a study for miniaturization with different permittivities for the DRA and a comparison of the throughput with the reference antennas of a commercial wireless LAN router were performed. Our proposed MIMO DRA gave similar performance as that of the reference antennas but was more compact in size.

In recent data centers, large-scale storage systems storing big data comprise thousands of large-capacity drives. Our goal is to establish a method for building highly reliable storage systems using more than a thousand low-cost large-capacity drives. Some large-scale storage systems protect data by erasure coding to prevent data loss. As the redundancy level of erasure coding is increased, the probability of data loss will decrease, but the increase in normal data write operation and additional storage for coding will be incurred. We therefore need to achieve high reliability at the lowest possible redundancy level. There are two concerns regarding reliability in large-scale storage systems: (i) as the number of drives increases, systems are more subject to multiple drive failures and (ii) distributing stripes among many drives can speed up the rebuild time but increase the risk of data loss due to multiple drive failures. If data loss occurs by multiple drive failure, it affects many users using a storage system. These concerns were not addressed in prior quantitative reliability studies based on realistic settings. In this work, we analyze the reliability of large-scale storage systems with distributed stripes, focusing on an effective rebuild method which we call Dynamic Refuging. Dynamic Refuging rebuilds failed blocks from those with the lowest redundancy and strategically selects blocks to read for repairing lost data. We modeled the dynamic change of amount of storage at each redundancy level caused by multiple drive failures, and performed reliability analysis with Monte Carlo simulation using realistic drive failure characteristics. We showed a failure impact model and a method for localizing the failure. When stripes with redundancy level 3 were sufficiently distributed and rebuilt by Dynamic Refuging, the proposed technique turned out to scale well, and the probability of data loss decreased by two orders of magnitude for systems with a thousand drives compared to normal RAID. The appropriate setting of a stripe distribution level could localize the failure.

In Android OS, we discover that a notification service called inotify is a new side-channel allowing malware to identify file accesses associated with the display of a security-relevant UI screen. This paper proposes a phishing attack that detects victim UI screens by their file accesses in applications and steals private information.

This paper presents non-iterative cooperative/parallel Kalman filtering algorithms for decentralized network navigation, in which mobile nodes cooperate in both spatial and temporal domains to infer their positions. We begin by presenting an augmented minimum-mean-square error (MMSE) estimator for centralized navigation network, and then decouple it into a set of local sub-ones each corresponding to a mobile node; all these sub-estimators work in parallel and cooperatively — with the state estimates exchanging between neighbors — to provide results similar to those obtained by the augmented one. After that, we employ the approximation methods that adopted in the conventional nonlinear Kalman filters to calculate the second-order terms involved in these sub-estimators, and propose a decentralized cooperative/parallel Kalman filtering based network navigation framework. Finally, upon the framework, we present two cooperative/parallel Kalman filtering algorithms corresponding to the extended and unscented Kalman filters respectively, and compare them with conventional decentralized methods by simulations to show the superiority.

Various DC power supply systems such as photovoltaic power generation, fuel cell and others have been gradually spreading, so that DC power distribution systems are expected as one of energy-saving technologies at houses and business-related buildings as well as data centers and factories. Under such circumstances switches for electric appliances are requested to interrupt DC current safely in DC power systems (DC 300-400V). It is well-known that DC current is much more difficult to be interrupted than AC current with current-zero. In this paper a model switch is developed and fundamental characteristics of DC current interruption in a resistive circuit is experimentally and theoretically examined. Consequently arc duration is found to be approximately a function of interrupted power rather than source voltage and circuit current. In addition arc length at its extinction is obtained by the observation of a high-speed camera. Then the arc length is found to be decided only by interrupted power like the gap length, independent of separation velocity. From these results it can be made clear that the arc form becomes arc-shaped at its extinction when the interrupted power is larger than about 500W. In addition the effect of magnetic blow-out on arc extinction is examined.