In this paper, we propose a novel texture analysis method capable of estimating multiple primitives, which are elements repetitively arranged to compose a texture, in multi-structured textures. The approach is based on a texture description model that uses mathematical morphology, called the “Primitive, Grain, and Point Configuration (PGPC)” texture model. The estimation of primitives based on the PGPC texture model involves searching the optimal structuring element for primitives according to a size distribution function and a magnification. The proposed method achieves the following two improvements: (1) the simultaneous estimation of a multiple number of primitives in multi-structured textures with a ranking of primitives on the basis of their significance. and (2) the introduction of flexibility in the process of magnification to obtain a higher degree of fitness of large grains. With a computational combination of different primitives, the method provides an ordered priority to denote the significance of elements. The promising performance of the proposed method is experimentally shown by a comparison with conventional methods.

WiMAX wireless communication has been rapidly developed for broadband mobile communication. Mobile WiMAX communication system uses microwave carrier of 2.5 GHz frequency band and modulation is OFDM mainly. By using OFDM technique, WiMAX provide high speed and reliable communication against multi pass interferences due to the presence of obstacles in communication channels. To design excellent high performance mobile communication systems, accurate evaluation of communication system is indispensable. By using parallel FDTD, we studied fundamental characteristics of microwave propagation and scattering in urban area. We also studied wave propagation and scattering by forest and trees using FDTD method. The effects of multiple scattering and attenuation of microwave by forest are severe factors of high speed wireless communications. In this paper, signal propagation and receiving characteristics of OFDM modulated wave are studied by parallel FDTD method. Propagation, reflection, scattering, interference and delay of digital code signals in received code signals are evaluated to show the environmental characteristics. Parallel FDTD methods are applied for signal and noise analysis about several different complex models and inhomogeneous materials such as forests in long distance communication channels.

The mode-matching applications to scattering from circular and annular apertures in a thick perfectly conducting plane are reviewed. The Hankel and Weber transforms are utilized to solve the boundary-value problems of circular and annular apertures. Simple electrostatic problems are presented to illustrate the mode-matching method in terms of the Hankel and Weber transforms. Various types of Weber transform are discussed with boundary-value problems. Electromagnetic radiation and scattering from circular and annular aperture geometries are summarized. The utility of the mode-matching method in circular and annular aperture scattering is emphasized.

Nowadays, there are a great deal of e-documents being accessed on the Internet. It would be helpful if those documents and significant extract contents could be automatically analyzed. Similarity analysis and topic extraction are widely used as document relation analysis techniques. Most of the methods being proposed need some processes such as stemming, stop words removal, and etc. In those methods, natural language processing (NLP) technology is necessary and hence they are dependent on the language feature and the dataset. In this study, we propose novel document relation analysis and topic extraction methods based on text compression. Our proposed approaches do not require NLP, and can also automatically evaluate documents. We challenge our proposal with model documents, URCS and Reuters-21578 dataset, for relation analysis and topic extraction. The effectiveness of the proposed methods is shown by the simulations.

In this letter we propose a practical sensing-based opportunistic spectrum sharing scheme for cognitive radio (CR) downlink MIMO systems. Multi-antennas are exploited at the secondary transmitter to opportunistically access the primary spectrum and effectively achieve a balance between secondary throughput maximization and mitigation of interference probably caused to primary radio link. We first introduce a brief secondary frame structure, in which a sensing phase is exploited to estimate the effective interference channel. According to the sensing result and taking the interference caused by the primary link into account, we propose an enhanced signal-to-leakage-and-noise ratio (SLNR)-based precoding scheme for the secondary transmitter. Compared to conventional schemes where perfect knowledge of the channels over which the CR transmitter interferes with the primary receiver (PR) is assumed, our proposed scheme shows its superiority and simulation results validate this.

This paper proposes a low-phase-noise ring-VCO-based frequency multiplier with a new subharmonic direct injection locking technique that only uses a time-delay cell and four MOS transistors. Since the proposed technique behaves as an exclusive OR and can double the reference signal frequency, it increases phase correction points and achieves low phase noise characteristic across the wide output frequency range. The frequency multiplier was fabricated by using 65 nm Si CMOS process. Measured 1-MHz-offset phase noise at 6.34 GHz with reference signals of 528 MHz was -119 dBc/Hz.

We have previously proposed an indoor monitoring and security system with an array sensor. The array sensor has some advantages, such as low privacy concern, easy installation with low cost, and wide detection range. Our study is different from the previously proposed classification method for array sensor, which uses a threshold to classify only two states for intrusion detection: nothing and something happening. This paper describes a novel state classification method based on array signal processing with a machine learning algorithm. The proposed method uses eigenvector and eigenvalue spanning the signal subspace as features, obtained from the array sensor, and assisted by multiclass support vector machines (SVMs) to classify various states of a human being or an object. The experimental results show that our proposed method can provide high classification accuracy and robustness, which is very useful for monitoring and surveillance applications.

It is becoming more and more important to make use of personal or classified information while keeping it confidential. A promising tool for meeting this challenge is secure multi-party computation (MPC). It enables multiple parties, each given a snippet of a secret s, to compute a function f(s) by communicating with each other without revealing s. However, one of the biggest problems with MPC is that it requires a vast amount of communication. Much research has gone into making each protocol (equality testing, interval testing, etc.) more efficient. In this work, we make a set of multiple protocols more efficient by transforming them into their equivalent batch processing form and propose two protocols: “Batch Logical OR” and “Batch Logical AND.” Using proposed protocols recursively, we also propose “Batch Logical OR-AND” and “Batch Logical AND-OR,” and show arbitrary formula consisting of Boolean protocols, OR gates, and AND gates can be batched. Existing logical OR and logical AND protocols consisting of t equality testing invocations have a communication complexity of O(t), where is the bit length of the secrets. Our batched versions of these protocols reduce it to O( + t). For t interval testing invocations, they reduce both communication and round complexity. Thus they can make the queries on a secret shared database more efficient. For example, the use of the proposed protocols reduces the communication complexity for a query consisting of equality testing and interval testing by approximately 70% compared to the use of the corresponding existing protocols. The concept of the proposed protocols is versatile and can be applied to logical formulae consisting of protocols other than equality testing and interval testing, thereby making them more efficient as well.

In this letter, we adopt a new factor analysis of neighborhood-preserving embedding (NPE) for speaker verification. NPE aims at preserving the local neighborhood structure on the data and defines a low-dimensional speaker space called neighborhood-preserving embedding space. We compare the proposed method with the state-of-the-art total variability approach on the telephone-telephone core condition of the NIST 2008 Speaker Recognition Evaluation (SRE) dataset. The experimental results indicate that the proposed NPE method outperforms the total variability approach, providing up to 24% relative improvement.

This paper presents a self-clustering algorithm to detect symmetry in images. We combine correlations of orientations, scales and descriptors as a triple feature vector to evaluate each feature pair while low confidence pairs are regarded as outliers and removed. Additionally, all confident pairs are preserved to extract potential symmetries since one feature point may be shared by different pairs. Further, each feature pair forms one cluster and is merged and split iteratively based on the continuity in the Cartesian and concentration in the polar coordinates. Pseudo symmetric axes and outlier midpoints are eliminated during the process. Experiments demonstrate the robustness and accuracy of our algorithm visually and quantitatively.

In this paper, we propose a hardware solution for overcoming the problem of high computational demands in a nearest neighbor (NN) based multi-prototype learning system. The multiple prototypes are obtained by a high-speed K-means clustering algorithm utilizing a concept of software-hardware cooperation that takes advantage of the flexibility of the software and the efficiency of the hardware. The one nearest neighbor (1-NN) classifier is used to recognize an object by searching for the nearest Euclidean distance among the prototypes. The major deficiency in conventional implementations for both K-means and 1-NN is the high computational demand of the nearest neighbor searching. This deficiency is resolved by an FPGA-implemented coprocessor that is a VLSI circuit for searching the nearest Euclidean distance. The coprocessor requires 12.9% logic elements and 58% block memory bits of an Altera Stratix III E110 FPGA device. The hardware communicates with the software by a PCI Express (4) local-bus-compatible interface. We benchmark our learning system against the popular case of handwritten digit recognition in which abundant previous works for comparison are available. In the case of the MNIST database, we could attain the most efficient accuracy rate of 97.91% with 930 prototypes, the learning speed of 1.310-4 s/sample and the classification speed of 3.9410-8 s/character.

Decision tree-based clustering and parameter estimation are essential steps in the training part of an HMM-based speech synthesis system. These two steps are usually performed based on the maximum likelihood (ML) criterion. However, one of the drawbacks of the ML criterion is that it is sensitive to outliers which usually result in quality degradation of the synthesized speech. In this letter, we propose an approach to detect and remove outliers for HMM-based speech synthesis. Experimental results show that the proposed approach can improve the synthetic speech, particularly when the available training speech database is insufficient.

Recently, Luo et al. proposed an efficient hierarchical identity based encryption (HIBE) scheme with constant size of ciphertexts, and proved its full security under standard assumptions. To construct the scheme, they used the dual system encryption technique of Waters, and devised a method that compresses the tag values of dual system encryption. In this paper, we show that the security proof of Luo et al. is wrong since there exists an algorithm that distinguishes whether it is a simulation or not.

In most software development environments, time, computing and human resources needed to perform the testing of a component is strictly limited. In order to deal with such situations, this paper proposes a method of creating the best possible test suite (covering the maximum number of 3-tuples) within a fixed number of test cases.

The wireless sensor network (WSN) is a technology that senses environmental information and provides appropriate services to users. There are diverse application areas for WSNs such as disaster prevention, military, and facility management. Despite the many prospective applications, WSN s are vulnerable to various malicious attacks. In false report attacks, a malicious attacker steals a few sensor nodes and obtains security materials such as authentication keys from the nodes. The attacker then injects false event reports to the network through the captured nodes. The injected false reports confuse users or deplete the limited energy of the nodes in the network. Many filtering schemes have been proposed to detect and remove false reports. In the statistical en route filtering (SEF) scheme, each node shares authentication keys selected from a global key pool. Due to the limited memory, each node is able to store only a small portion of the global key pool. Therefore, the routing paths of the event reports significantly affect the filtering (i.e., detecting) probability of false reports. In this paper, we propose a method to determine the routing paths of event reports both hop by hop and on demand at each node. In this method, each node chooses the next node on the path from the event source to the sink node based on the key indexes of its neighbor nodes. Experiments show that the proposed method is far more energy efficient than the SEF when the false traffic ratio (FTR) is ≥ 50% in the network.

Electromagnetic wave scattering in two open-ended coaxial cables with flanges is presented for adiabatic transmission line applications. Field distributions in the cables are obtained by employing the mode-matching method. A set of simultaneous equations is solved to investigate the transmission and reflection coefficients.

The location-based routing protocol has proven to be scalable and efficient in large wireless sensor networks with mobile sinks. A great challenge in location-based routing protocols is the design of scalable distributed location service that tracks the current locations of mobile sinks. Although various location services have been proposed in the literature, hierarchical-based location services have the significant advantage of high scalability. However, most of them depend on a global hierarchy of grids. A major disadvantage of this design is that high control overhead occurs when mobile sinks cross the boundaries of the top level grids. In this paper, we introduce Hierarchical Ring Location Service (HRLS) protocol, a practical distributed location service that provides sink location information in a scalable and distributed manner. In contrast to existing hierarchical-based location services, each sink in HRLS constructs its own hierarchy of grid rings distributively. To reduce the communication overhead of location update, sinks utilize the lazy update mechanism with their indirect location. Once a sensor node detects a target, it queries the location of a sink by sending request packets in eight directions. HRLS is evaluated through mathematical analysis and simulations. Compared with a well-known hierarchical-based location service, our results show that HRLS provides a more scalable and efficient distributed location service in scenarios with various network size, sink mobility and increasing number of source nodes.

In this paper, a new skin detection method using pixel color and image regional information, intended for objectionable image filtering is proposed. The method consists of three stages: skin detection, feature extraction and image classification. Skin detection is implemented in two steps. First, a Sinc function, fitted to skin color distribution in the Cb-Cr chrominance plane is used for detecting pixels with skin color properties. Next, to benefit regional information, based on the theory of color image reproduction, it's shown that the scattering of skin pixels in the RGB color space can be approximated by an exponential function. This function is incorporated to extract the final accurate skin map of the image. As objectionable image features, new shape and direction features, along with area feature are extracted. Finally, a Multi-Layer Perceptron trained with the best set of input features is used for filtering images. Experimental results on a dataset of 1600 images illustrate that the regional method improves the pixel-based skin detection rate by 10%. The final classification result with 94.12% accuracy showed better results when compared to other methods.

This paper customizes Goal/Question/Metric (GQM) project monitoring models for various projects and organizations to take advantage of the data from the software tool EPM and to allow the tailoring of the interpretation models based upon the context and success criteria for each project and organization. The basic idea is to build less concrete models that do not include explicit baseline values to interpret metrics values. Instead, we add hypothesis and interpretation layers to the models to help people of different projects make decisions in their own context. We applied the models to two industrial projects, and found that our less concrete models could successfully identify typical problems in software projects.

The authors have been investigating degradation process of Au plated slip ring and Ag-Pd-Cu brush system. In almost all cases the lifetime of the sliding system ends, when Au plating layer is worn out, the ring surface is oxidized to be black in color and contact resistance becomes very high. Further, the lifetime is very short without lubricant. So, the lubricant is very effective to make the lifetime longer. However, even with lubricant the lifetime is varied from about 1000 hours to almost 7000 hours in the past experiments. It is an important issue how the lubricant works on the lifetime of the system. In this paper the effect of lubricant on the degradation process of contact resistance is focused on. In the past tests the lubricant is supplied only once before the test. In this test the lubricant is regularly supplied almost every 900 operation hours. Consequently, the operation more than 8000 hours is realized, which is the longest among tests so far. In addition the contact voltage drop increase gradually until 2600 hours and after that it stays almost constant around 70 mV. According to the Element Analysis after the test the Ni base plating layer is totally exposed in many tracks. It means that the Au plating layer is gradually worn out probably at the stage of increasing voltage drop. In the previous tests the lifetime ended even when the Ni plating layer remained. So, the reason of long operation in this test is guessed to be that the lubricant not only decreases wear of ring and brush, but also suppresses oxidation of the Ni layer.