An anonymous password-authenticated key exchange (PAKE) protocol is designed to provide both password-only authentication and client anonymity against a semi-honest server, who honestly follows the protocol. In INDOCRYPT2008, Yang and Zhang [26] proposed a new anonymous PAKE (NAPAKE) protocol and its threshold (D-NAPAKE) which they claimed to be secure against insider attacks. In this paper, we first show that the D-NAPAKE protocol [26] is completely insecure against insider attacks unlike their claim. Specifically, only one legitimate client can freely impersonate any subgroup of clients (the threshold t > 1) to the server. After giving a security model that captures insider attacks, we propose a threshold anonymous PAKE (called, TAP+) protocol which provides security against insider attacks. Moreover, we prove that the TAP+ protocol has semantic security of session keys against active attacks as well as insider attacks under the computational Diffie-Hellman problem, and provides client anonymity against a semi-honest server, who honestly follows the protocol. Finally, several discussions are followed: 1) We also show another threshold anonymous PAKE protocol by applying our RATIONALE to the non-threshold anonymous PAKE (VEAP) protocol [23]; and 2) We give the efficiency comparison, security consideration and implementation issue of the TAP+ protocol.

This study formulates and solves the wire planning problem with electro-migration and interference using an effective integer linear programming (ILP)-based approach. For circuits without obstacles, the proposed approach obtains a wire planning with the minimum wiring area. An effective approach for estimating the length of feasible routing wire is proposed to handle circuits with obstacles. In addition, the space reservation technique, which allocates the ring of the free silicon space around obstacles, is presented to improve interference among routing wires and on-obstacle wires. For circuits with obstacles, the proposed method minimizes total wiring area and reduces interference. Experimental results show that the integer linear-programming-based approach effectively and efficiently minimizes wiring area of routing wires.

Kudekar et al. recently proved that for transmission over the binary erasure channel (BEC), spatial coupling of LDPC codes increases the BP threshold of the coupled ensemble to the MAP threshold of the underlying LDPC codes. One major drawback of the capacity-achieving spatially-coupled LDPC codes is that one needs to increase the column and row weight of parity-check matrices of the underlying LDPC codes. It is proved, that Hsu-Anastasopoulos (HA) codes and MacKay-Neal (MN) codes achieve the capacity of memoryless binary-input symmetric-output channels under MAP decoding with bounded column and row weight of the parity-check matrices. The HA codes and the MN codes are dual codes each other. The aim of this paper is to present an empirical evidence that spatially-coupled MN (resp. HA) codes with bounded column and row weight achieve the capacity of the BEC. To this end, we introduce a spatial coupling scheme of MN (resp. HA) codes. By density evolution analysis, we will show that the resulting spatially-coupled MN (resp. HA) codes have the BP threshold close to the Shannon limit.

In this paper, we present a construction method of non-binary low-density parity-check (LDPC) convolutional codes. Our construction method is an extension of Felstrom and Zigangirov construction [1] for non-binary LDPC convolutional codes. The rate-compatibility of the non-binary convolutional code is also discussed. The proposed rate-compatible code is designed from one single mother (2,4)-regular non-binary LDPC convolutional code of rate 1/2. Higher-rate codes are produced by puncturing the mother code and lower-rate codes are produced by multiplicatively repeating the mother code. Simulation results show that non-binary LDPC convolutional codes of rate 1/2 outperform state-of-the-art binary LDPC convolutional codes with comparable constraint bit length. Also the derived low-rate and high-rate non-binary LDPC convolutional codes exhibit good decoding performance without loss of large gap to the Shannon limits.

Nowadays, pedestrian recognition for automotive and security applications that require accurate recognition in images taken from distant observation points is a recent challenging problem in the field of computer vision. To achieve accurate recognition, both detection and tracking must be precise. For detection, some excellent schemes suitable for pedestrian recognition from distant observation points are proposed, however, no tracking schemes can achieve sufficient performance. To construct an accurate tracking scheme suitable for pedestrian recognition from distant observation points, we propose a novel pedestrian tracking scheme using multiple cues: HSV histograms and HOG features. Experimental results show that the proposed scheme can properly track a target pedestrian where tracking schemes using only a single cue fails. Moreover, we implement the proposed scheme on NVIDIA® TeslaTM C1060 processor, one of the latest GPU, to achieve real-time processing of the proposed scheme. Experimental results show that computation time required for tracking of a frame by our implementation is reduced to 8.80 ms even though Intel® CoreTM i7 CPU 975 @ 3.33 GHz spends 111 ms.

In processing stream data, time is one of the most significant facts not only because the size of data is dramatically increased but because the characteristics of data is varying over time. To learn stream data evolving over time effectively, it is required to detect the drift of concept. We present a window adaptation function on domain value (WAV) to determine the size of windowed batch for learning algorithms of stream data and a method to detect the change of data characteristics with a criterion function utilizing correlation. When applying our adaptation function to a clustering task on a multi-stream data model, the result of learning synopsis of windowed batch determined by it shows its effectiveness. Our criterion function with correlation information of value distribution over time can be the reasonable threshold to detect the change between windowed batches.

This paper introduces a new dynamic 3D mesh representation that provides 3D animation support of progressive display and drastically reduces the amount of storage space required for 3D animation. The primary purpose of progressive display is to allow viewers to get animation as quickly as possible, rather than having to wait until all data has been downloaded. In other words, this method allows for the simultaneous transmission and playing of 3D animation. Experiments show that coarser 3D animation could be reconstructed with as little as 150 KB of data transferred. Using the sustained transmission of refined operators, viewers feel that resolution approaches that of the original animation. The methods used in this study are based on a compression technique commonly used in 3D animation - clustered principle component analysis, using the linearly independent rules of principle components, so that animation can be stored using smaller amounts of data. This method can be coupled with streaming technology to reconstruct animation through iterative updating. Each principle component is a portion of the streaming data to be stored and transmitted after compression, as well as a refined operator during the animation update process. This paper considers errors and rate-distortion optimization, and introduces weighted progressive transmitting (WPT), using refined sequences from optimized principle components, so that each refinement yields an increase in quality. In other words, with identical data size, this method allows each principle component to reduce allowable error and provide the highest quality 3D animation.

In this paper, a geometric source separation system using nonnegative matrix factorization (NMF) is proposed. The adaptive beamformer is the best method for geometric source separation, but it suffers from a “target signal cancellation” problem in multi-path situations. We modified the HALS-NMF algorithm for decomposition into bases, and developed an interference suppression module in order to cancel the interference bases. A performance comparison between the proposed and subband GSC-RLS algorithm using a MATLAB® simulation was executed; the results show that the proposed system is robust in multi-path situations.

Whether a patent is registered or not is usually based on the subjective judgment of the patent examiners. However, the patent examiners may determine whether the patent is registered or not according to their personal knowledge, backgrounds etc. In this paper, we propose a novel patent registration method based on patent data. The method estimates whether a patent is registered or not by utilizing the objective past history of patent data instead of existing methods of subjective judgments. The proposed method constructs an estimation model by applying multivariate statistics algorithm. In the prediction model, the application date, activity index, IPC code and similarity of registration refusal are set to the input values, and patent registration and rejection are set to the output values. We believe that our method will contribute to improved reliability of patent registration in that it achieves highly reliable estimation results through the past history of patent data, contrary to most previous methods of subjective judgments by patent agents.

In MANET (Mobile Ad-hoc NETworks), there are two kinds of routing methods: proactive and reactive. Each has different characteristics and advantages. The latter generally employs the flooding technique to finding a routing path to the destination. However, flooding has big overheads caused by broadcasting RREQ packets to the entire network. Therefore, reducing this overhead is really needed to enable several network efficiencies. Previous studies introduced many approaches which are mainly concerned with the restriction of flooding. However, they usually configure the detailed routing path in the forward flooding procedure and ignore the factors causing the flooding overheads. In this paper, we propose the FSRS (First Search and Reverse Setting) routing protocol which is a new approach in flooding techniques and a new paradigm shift. FSRS is based on cluster topology and is composed of two main mechanisms: inter-cluster and intra-cluster flooding. Inter-cluster routing floods RREQ packets between cluster units and sets a cluster path. When the destination node receives the RREQ packet, it floods RREP packets to an intra-cluster destination which is a gateway to relay the RREP packet to a previous cluster. This is called intra-cluster routing. So to speak, a specific routing path configuration progresses in the RREP process through the reverse cluster path. Consequently, FSRS is a new kind of hybrid protocol well adapted to wireless ad-hoc networks. This suggests a basic wireless networking architecture to make a dynamic cluster topology in future work. In the simulation using NS-2, we compare it to several other protocols and verify that FSRS is a powerful protocol. In the result of the simulation, FSRS conserves energy by a maximum of 12% compared to HCR.

With the rapid development and proliferation of the Internet, cyber attacks are increasingly and continually emerging and evolving nowadays. Malware – a generic term for computer viruses, worms, trojan horses, spywares, adwares, and bots – is a particularly lethal security threat. To cope with this security threat appropriately, we need to identify the malwares' tendency/characteristic and analyze the malwares' behaviors including their classification. In the previous works of classification technologies, the malwares have been classified by using data from dynamic analysis or code analysis. However, the works have not been succeeded to obtain efficient classification with high accuracy. In this paper, we propose a new classification method to cluster malware more effectively and more accurately. We firstly perform dynamic analysis to automatically obtain the execution traces of malwares. Then, we classify malwares into some clusters using their characteristics of the behavior that are derived from Windows API calls in parallel threads. We evaluated our classification method using 2,312 malware samples with different hash values. The samples classified into 1,221 groups by the result of three types of antivirus softwares were classified into 93 clusters. 90% of the samples used in the experiment were classified into 20 clusters at most. Moreover, it ensured that 39 malware samples had characteristics different from other samples, suggesting that these may be new types of malware. The kinds of Windows API calls confirmed the samples classified into the same cluster had the same characteristics. We made clear that antivirus softwares named different name to malwares that have same behavior.

In non-cooperative scenarios, the estimation of direct sequence spread spectrum (DS-SS) signals has to be done in a blind manner. In this letter, we consider the spreading sequence estimation problem for DS-SS signals. First, the maximum likelihood estimate (MLE) of spreading sequence is derived, then a semidefinite relaxation (SDR) approach is proposed to cope with the exponential complexity of performing MLE. Simulation results demonstrate that the proposed approach provides significant performance improvements compared to existing methods, especially in the case of low numbers of data samples and low signal-to-noise ratio (SNR) situations.

This letter considers a sum-rate maximization problem with user scheduling wherein each user has a minimum-rate requirement in multiple-input-multiple-output broadcast channel. The multiuser strategy used in the user scheduling is a joint transceiver scheme with block diagonal geometric mean decomposition. Since optimum solution to the user scheduling problem generally requires exhaustive search, we propose a suboptimum user scheduling algorithm with each user's minimum-rate requirement as the main constraint. In order to satisfy maximum sum-rate and minimum-rate constraints simultaneously, we additionally consider power allocation for scheduled users. Simulation results show that the proposed user scheduling algorithm, together with the user power allocation, achieves sum-rate close to the exhaustive search, while also guarantees minimum-rate requirement of each user.

In this paper, we evaluate the downlink performance of Transparent mode (T-mode) and Non-Transparent mode (NT-mode) in a two-hop cellular system based on IEEE 802.16j. In particular, we evaluate the performance in terms of the system capacity, optimal resource allocation, and outage probability using Monte Carlo simulation with various system parameters such as different Frequency Reuse Factors (FRFs) and the distance between Base Station (BS) and Relay Station (RS). To analyze the Signal to Interference and Noise Ratio (SINR) of the access and relay links, an SINR model is introduced for cellular multihop systems considering intra- and inter-cell interferences. Then, we present a method of optimal resource allocation for the Access Zone (AZ) and Relay Zone (RZ) to maximize the system capacity. Consequently, the simulation results provide an insight into choosing the appropriate RS position and optimal resource allocation. Through numerical examples, it is found that the FRFs of two and three are good choices to achieve the highest capacity with low outage in T- and NT-modes, respectively.

We determine the autocorrelations of the quaternary sequence over F4 and its modified version introduced by Du et al. [X.N. Du et al., Linear complexity of quaternary sequences generated using generalized cyclotomic classes modulo 2p, IEICE Trans. Fundamentals, vol.E94-A, no.5, pp.1214–1217, 2011]. Furthermore, we reveal a drawback in the paper aforementioned and remark that the proof in the paper by Kim et al. can be simplified.

In this paper, an active control scheme is designed for the hybrid direct methanol fuel cell (DMFC) system to achieve the following three objectives simultaneously: (i) maximize the power produced by the DMFC stack in the stable operation as high loading (for avoiding the operation of DMFC in diffusion region), (ii) keep the power produced by the DMFC stack with the high efficiency as low loading, (iii) prevent the problem of methanol crossover at a very low load. Considering the characteristics of DMFC stack during actual operation, the states VP (t) and P (t) are utilized as the linguistic variables. Also considering the fuel efficiency of DMFC stack ηfuel as the linguistic variable, the active control scheme is designed to achieve the above multiple objectives. To clarify the reliability and stability of the proposed control scheme, an experiment is performed. Its results show that the proposed control scheme can achieve above multiple objectives efficiently.

We have previously proposed a howling canceller which cancels howling by using a cascade notch filter designed from a distance between a loudspeaker and a microphone. This method utilizes a pilot signal to estimate the distance. In this paper, we introduce two methods into the distance-based howling canceller to improve speech quality. The first one is an adaptive cascade notch filter which adaptively adjusts the nulls to eliminate howling and to keep speech components. The second one is a silent pilot signal whose frequencies exist in the ultrasonic band, and it is inaudible while on transmission. We implement the proposed howling canceller on a DSP to evaluate its capability. The experimental results show that the proposed howling canceller improves speech quality in comparison to the conventional one.

Adaptive interference suppression strategies based on the transform domain approach are proposed for a satellite on-board filter bank under tone-type interferences. In the proposed methods, the three kinds of algorithms to compute the threshold level are jointly employed with the notch filter or the clipper. Simulation results show that the proposed schemes significantly improve performance under interfering environments, compared to the no suppression case.

This paper deals with the configuration of a wireless network with the aim of minimizing the overall cost of both operation and network installation. The trade-off between the operation cost and the installation cost is the key consideration when designing cellular telecommunication networks, and can save costs and improve the performance of the network. In this paper, we propose an integrated framework for selecting Mobile Switching Center (MSC) among the candidate MSCs and assigning Base Stations (BSs) to the selected MSCs with the objective function of minimizing the cost of MSC setup, BS to MSC cabling, as well as the cost of handover. Capacity constraint for the selected MSC is also considered in the problem. The problem is expressed in an integer programming model and the Lagrangian relaxation method is proposed to solve the problem by dualizing some constraints. The Lagrangian relaxed problem is decomposed into subproblems that can be resolved optimally. The Lagrangian heuristic algorithm is suggested to find feasible solutions to the original problem. Computational experiments are performed to test the effectiveness and efficiency of the proposed heuristic algorithm. In the experiments, Lagrangian bounds on the optimal solution are used to show the effectiveness of the algorithm. The results of the proposed algorithm are also compared with those of some conventional meta-heuristics, Tabu search (TS) and Genetic algorithm (GA). The computational experiments show that the performance of the proposed heuristics is satisfactory in both the speed and the quality of the solution generated.

A novel grouping approach to segment text lines from handwritten documents is presented. In this text line segmentation algorithm, for each text line, a text string that connects the center points of the characters in this text line is built. The text lines are then segmented using the resulting text strings. Since the characters of the same text line are situated close together and aligned on a smooth curve, 2D tensor voting is used to reduce the conflicts when building these text strings. First, the text lines are represented by separate connected components. The center points of these connected components are then encoded by second order tensors. Finally, a voting process is applied to extract the curve saliency values and normal vectors, which are used to remove outliers and build the text strings. The experimental results obtained from the test dataset of the ICDAR 2009 Handwriting Segmentation Contest show that the proposed method generates high detection rate and recognition accuracy.