In this paper, we propose a face representation approach using multi-orientation Log-Gabor local binary pattern (MOLGLBP) for realizing face recognition under facial expressions, illuminations and partial occlusions. Log-Gabor filters with different scales (frequencies) and orientations are applied on Y, I, and Q channel image in the YIQ color space respectively. Then Log-Gabor images of different orientations at the same scale are combined to form a multi-orientation Log-Gabor image (MOLGI) and two LBP operators are applied to it. For face recognition, histogram intersection metric is utilized to measure the similarity of faces. The proposed approach is evaluated on the CurtinFaces database and experiments demonstrate that the proposed approach is effectiveness against two simultaneous variations: expression & illumination, and illumination & occlusion.

Feature Selection (FS) is widely used to resolve the problem of selecting a subset of information-rich features; Fuzzy-Rough QuickReduct (FRQR) is one of the most successful FS methods. This paper presents two variants of the FRQR algorithm in order to improve its performance: 1) Combining Fuzzy-Rough Dependency Degree with Correlation-based FS merit to deal with a dilemma situation in feature subset selection and 2) Hybridizing the newly proposed method with the threshold based FRQR. The effectiveness of the proposed approaches are proven over sixteen UCI datasets; smaller subsets of features and higher classification accuracies are achieved.

This paper seeks to improve power-performance efficiency of embedded systems by the use of dynamic reconfiguration. Programmable logic devices (PLDs) have the competence to optimize the power consumption by the use of partial and/or dynamic reconfiguration. It is a non-exclusive approach, which can use other power-reduction techniques simultaneous, and thus it is applicable to a myriad of systems. The power-performance improvement by dynamic reconfiguration was evaluated through an augmented reality system that translates Japanese into English. It is a wearable and mobile system with a head-mounted display (HMD). In the system, the computing core detects a Japanese word from an input video frame and the translated term will be output to the HMD. It includes various image processing approaches such as pattern recognition and object tracking, and these functions run sequentially. The system does not need to prepare all functions simultaneously, which provides a function by reconfiguration only when it is needed. In other words, by dynamic reconfiguration, the spatiotemporal module-based pipeline can introduce the reduction of its circuit amount and power consumption compared to the naive approach. The approach achieved marked improvements; the computational speed was the same but the power consumption was reduced to around $rac{1}{6}$.

This paper describes a simple-yet-effective control method for a DC-DC buck converter with voltage mode control (VMC), with a triangular wave generator (TWG) which regulates the slope of triangular wave based on the input and output voltages of the converter. Using the proposed TWG, both the load and line transient responses are improved. Since the TWG provides a line feed-forward control for the line transient response, it increases the open-loop bandwidth, and then better dynamic performance is obtained. Additional required circuit components are only a voltage controlled linear resistor (VCR) and a voltage controlled current source (VCCS). Compared with the conventional voltage control, the proposed method significantly improves the line and load transient responses. Furthermore this triangular wave slope regulation scheme is simple compared to digital feed-forward control scheme that requires non-linear calculation. Simulation results shows the effectiveness of the proposed method.

Presently, many identity-based proxy signature (IBPS) schemes have been proposed, but most of them require high computational costs and the proposed security model for IBPS is not enough complete. To overcome this weakness, Gu et al. recently proposed a framework and a detailed security model for IBPS. They also proposed an efficient IBPS scheme and proved the unforgeability of their scheme in the standard model. However, in this letter, we demonstrate that Gu et al.'s scheme fails to satisfy the property of unforgeability because it can not resist the following attacks: after getting a private key, an adversary behaving as a malicious signer can forge a private key on any identity without the help of the private key generator (PKG); after getting a delegation, an adversary behaving as a malicious proxy signer can forge a proxy signing key on any delegation without the agreement of the original signer; after getting a signature, an adversary behaving as a malicious user can forge a signature on any identity without the private key or forge a proxy signature on any warrant without the proxy signing key.

While emphasizing the intensity or saturation component for getting high-quality color images, keeping the hue component unchanged is important; thus, perceptual color models such as HSI and HSV have been used. Hue-Saturation-Intensity (HSI) is a public color model, and many color applications are commonly based on this model. However, the transformation from the HSI color space to the RGB color space after processing intensity/saturation in the HSI color space usually generates the gamut problem. In this study, we clear the relationship between the RGB gamut and the HSI gamut completely. According to the result, we can check whether the processing result is located inside or outside of the RGB gamut without transforming to the RGB color space. If the processing result is judged outside of the RGB gamut, we apply the effective way of hue preserving correction algorithm which is proposed in this study to the saturation component. Experimental results demonstrate that the proposed algorithm can correct the color distortion caused by the enhancement without reducing the visual effect and it is especially useful for images with rich colors and local high component values.

Since it is difficult to understand or predict research trends, we proposed methodologies for understanding and predicting research trends in the sciences, focusing on the structures of grants in the Japan Society for the Promotion of Science (JSPS), a Japanese funding agency. Grant applications are suitable for predicting research trends because these are research plans for the future, different from papers, which report research outcomes in the past. We investigated research trends in science focusing on research histories identified in grant application data of JSPS. Then we proposed a model for predicting research trends, assuming that breakthrough research encourages researchers to change from their current research field to an entirely new research field. Using breakthrough research, we aim to obtain higher precision in the prediction results. In our experimental results, we found that research fields in Informatics correlate well with actual scientific research trends. We also demonstrated that our prediction models are effective in actively interacting research areas, which include Informatics and Social Sciences.

The concept of sparse representation is gaining momentum in image processing applications, especially in image compression, from last one decade. Sparse coding algorithms represent signals as a sparse linear combination of atoms of an overcomplete dictionary. Earlier works shows that sparse coding of images using learned dictionaries outperforms the JPEG standard for image compression. The conventional method of image compression based on sparse coding, though successful, does not adapting the compression rate based on the image local block characteristics. Here, we have proposed a new framework in which the image is classified into three classes by measuring the block activities followed by sparse coding each of the classes using dictionaries learned specific to each class. K-SVD algorithm has been used for dictionary learning. The sparse coefficients for each class are Huffman encoded and combined to form a single bit stream. The model imparts some rate-distortion attributes to compression as there is provision for setting a different constraint for each class depending on its characteristics. We analyse and compare this model with the conventional model. The outcomes are encouraging and the model makes way for an efficient sparse representation based image compression.

This paper presents 2-(hydroxyl) quinoline lithium (Liq) used as an n-type dopant to improve white hybrid organic light-emitting diode (WHOLEDs) performance. The Liq doped tris(8-hydroxyquinolinato) aluminum (Alq$_{3})$ layer possessed enhanced electron injection, efficient hole and electron balance in the emitting layer, as one of the most essential issues for device applications. This work investigates the optimum recipe (Liq concentration and thickness) of Alq$_{3}$:Liq n-type doped electron injection layer (EIL) for WHOLED devices by comparing the current density and efficiency results with conventional Alq$_{3}$/LiF technique. A blocking layer or interlayer is inserted between emitting layer and EIL to avoid excitons quenched. In this work suitable material and optimum thickness for blocking layer are studied, a white small-molecular organic light-emitting diode (SM-OLEDs) based on a 1,3,5-tris (N-phenylbenzimidazol-2-yl) benzene (TPBi) stamping transfer process is investigated. The proposed stamping transfer process can avoid the complexity of the vacuum deposition process.

Concurrency bugs do significantly affect system reliability. Although many efforts have been made to address this problem, there are still many bugs that cannot be detected because of the complexity of concurrent programs. Compared with atomicity violations, order violations are always neglected. Efficient and effective approaches to detecting order violations are therefore in urgent need. This paper presents a bidirectional predictive trace analysis approach, BIPED, which can detect order violations in parallel based on a recorded program execution. BIPED collects an expected-order execution trace into a layered bidirectional prediction model, which intensively represents two types of expected-order data flows in the bottom layer and combines the lock sets and the bidirectionally order constraints in the upper layer. BIPED then recognizes two types of candidate violation intervals driven by the bottom-layer model and then checks these recognized intervals bidirectionally based on the upper-layer constraint model. Consequently, concrete schedules can be generated to expose order violation bugs. Our experimental results show that BIPED can effectively detect real order violation bugs and the analysis speed is 2.3x-10.9x and 1.24x-1.8x relative to the state-of-the-art predictive dynamic analysis approaches and hybrid model based static prediction analysis approaches in terms of order violation bugs.

Novel deterministic digital calibration of pipelined ADC has been proposed and analyzed theoretically. Each MDAC is dithered exploiting its inherent redundancy during the calibration. The dither enables fast accurate convergence of calibration without requiring any accurate reference signal and hence with minimum area and power overhead. The proposed calibration can be applied to both the 1.5-bit/stage MDAC and the multi-bit/stage MDAC. Due to its simple structure and algorithm, it can be modified to the background calibration easily. The effectiveness of the proposed calibration has been confirmed by both the extensive simulations and the measurement of the prototype 0.13-µm-CMOS 50-MS/s pipelined ADC using the op-amps with only 37-dB gain. As expected, SNDR and SFDR have improved from 35.5dB to 58.1dB and from 37.4dB to 70.4dB, respectively by the proposed calibration.

A quartz-crystal-microbalance (QCM) and surface-plasmon-resonance (SPR) hybrid sensor was prepared, and the depositions of polymer electrolytes layer-by-layer (LbL) films were observed in situ. The estimated thicknesses obtained from the QCM method were different from those obtained from the SPR method. This was estimated to be caused by film swelling and water contained in the film.

The authors have focused on wideband, including ultra-wideband (UWB, 3.1 to 10.6GHz) radio propagation in various environments, such as a small space-craft and a passenger car, moreover on-body radio propagation measurements have been conducted. Many studies have been reported about indoor propagation for narrowband and wideband. However previous study has not been examined characteristics between 10-MHz and 1-GHz frequencies. In our previous study, UWB and narrowband propagation were measured in a UWB frequency band within closed/semi-closed spaces (e.g. a spacecraft, a passenger car, and a metal desk equipped with a metal partition). While narrowband propagation resulted in considerable spatial variations in propagation gain due to interferences caused by multipath environments, UWB yielded none. This implies that the UWB systems have an advantage over narrowband from a viewpoint of reducing fading margins. Thus, a use of UWB technology within spacecrafts has been proposed with a view to partially replacing wired interface buses with wireless connections. Adoption of wireless technologies within the spacecrafts could contribute to reduction in cable weight (and launching cost as a result), reduction in the cost of manufacture, more flexibility in layout of spacecraft subsystems, and reliable connections at rotary, moving, and sliding joints. Path gains and throughputs were also measured for various antenna settings and polarizations in the small spacecraft. Polarization configurations were found to produce almost no effect on average power delay profiles and substantially small effects on the throughputs. Furthermore, statistical channel models were proposed. Also UWB technologies have been considered for use in wireless body area networks (WBAN) because of their possible low power consumption and anti-multipath capabilities. A series of propagation measurements were carried out between on-body antennas in five different rooms. A new path loss and statistical models considering room volume had been proposed. In this paper, we evaluated propagation characteristics in heavy multipath environments, especially examined the channels at 10-MHz to 1-GHz frequencies.

We propose that the current distribution along a dipole can be divided into a component proportional to the port current, a component proportional to the port voltage, and an antisymmetrical component. In this paper, we perform numerical computations to verify that the component proportional to the port voltage always lags the port voltage by 90°, and the ratio of its amplitude to that of the port voltage is not significantly affected by the arrangement of other dipoles located nearby or by circuits connected to the ports of the dipoles if the dipoles have lengths not exceeding one wavelength.

This paper derives the optimal learning time for the learning-assisted rendezvous channel. One problem with the dynamic spectrum access system of cognitive radio is access channel mismatch between two wireless terminals. In the learning-assisted rendezvous channel, before exchanging packets for link connection, the rate of channel occupancy by the other system is estimated within the learning time; it is referred to as the channel occupancy rate (COR). High speed packet exchange is made possible by selecting a low COR channel. However, the optimal learning time and the impact of COR estimation errors have not been clarified yet. This paper analyzes the time to rendezvous channel (TTR), where TTR is the time needed to complete the rendezvous with a certain probability. The results indicate that the learning time and TTR have a concave relationship which means that the optimal learning time can be determined.

Autonomous ad hoc networks are networks with nodes belonging to different authorities, and cooperative behavior of nodes is not guaranteed in such networks. In this paper, defense mechanisms are introduced to protect nodes against injecting traffic attacks in an autonomous ad hoc network, and to stimulate nodes to forward packets for each other. We have a cross-layer approach in the design of our mechanisms, and nodes use information from medium access control (MAC) layer for selecting a good route. In addition, nodes attempt to drop packets of those nodes that violate MAC layer backoff mechanism. Analytical and simulation results demonstrate the effectiveness of our proposed mechanisms in the presence of injecting traffic attacks and MAC layer misbehaviors in an ad hoc network that consists of selfish nodes.

This paper proposes a novel image classification scheme for cloth pattern recognition. The rotation and scale invariant delta-HOG (DHOG)-based descriptor and the entire recognition process using random ferns with this descriptor are proposed independent from pose and scale changes. These methods consider maximun orientation and various radii of a circular patch window for fast and efficient classification even when cloth patches are rotated and the scale is changed. It exhibits good performance in cloth pattern recognition experiments. It found a greater number of similar cloth patches than dense-SIFT in 20 tests out of a total of 36 query tests. In addition, the proposed method is much faster than dense-SIFT in both training and testing; its time consumption is decreased by 57.7% in training and 41.4% in testing. The proposed method, therefore, is expected to contribute to real-time cloth searching service applications that update vast numbers of cloth images posted on the Internet.

In the scattering problem of dielectric gratings in conical mounting, we have considered and formulated scattering fields using transverse electric (TE) and transverse magnetic (TM) waves. This paper formulates scattering fields by superpositions of right-circularly (RC) and left-circularly (LC) polarized waves through the matrix eigenvalue method.

A cloud system is defined as a large scale computer system that contains running high performance computers and responds to a large number of incoming tasks over the Internet. In this paper, we consider the problem to schedule computational jobs efficiently regarding system resource constraint and introduce a cuckoo search (CS) algorithm. Experimental results show that CS outperforms the genetic algorithm in terms of fitness value.