Acoustic Event Classification (AEC) poses difficult technical challenges as a result of the complexity in capturing and processing sound data. Of the various applicable approaches, Support Vector Machine (SVM) with Gaussian Mixture Model (GMM) supervectors has been proven to obtain better solutions for such problems. In this paper, based on the multiple kernel selection model, we introduce two non-linear kernels, which are derived from the linear kernels of GMM Kullback-Leibler divergence (GMM KL) and GMM-UBM mean interval (GUMI). The proposed method improved the AEC model's accuracy from 85.58% to 90.94% within the domain of home AEC.

We present the concept of an on-line electric vehicle (OLEV) and its wireless power transfer mechanism and analyze the electromagnetic compatibility characteristics. As magnetic fields transfer 100kW of power to the vehicle, reduction of electromagnetic field (EMF) noise is a critical issue for protection of the human body. Also, with respect to electromagnetic interference (EMI) noise, a proper measurement method has not yet been established for this low frequency high power system. In this paper, low frequency magnetic field shielding methods and application of the shields to the OLEV system are presented. Furthermore, a standard low frequency magnetic field measurement is suggested as an EMI test.

An augmented PAKE (Password-Authenticated Key Exchange) protocol provides password-only authentication in the presence of an attacker, establishment of session keys between the involving parties, and extra protection for server compromise (i.e., exposure of password verification data). Among many augmented PAKE protocols, AMP variants (AMP2 [16] and AMP+ [15]) have been standardized in IEEE 1363.2 [9] and ISO/IEC 11770-4 [10]. In this paper, we thoroughly investigate APKAS-AMP (based on AMP2 [16]) and KAM3 (based on AMP+ [15]) which require several validity checks on the values, received and computed by the parties, when using a secure prime. After showing some attacks on APKAS-AMP and KAM3, we suggest new sanity checks that are clear and sufficient to prevent an attacker from doing these attacks.

The equivalent circuit of aperture-coupled cavities filled with a lossy dielectric is considered by means of an eigenmode expansion technique founded on the segmentation concept. It is different from a series LCR resonant circuit, and the resistor which symbolizes the dielectric loss is connected to the capacitor in parallel. If the cavities are formed by a short-circuited oversize waveguide, then the input admittance can be represented by the product of a coupling factor to the connected waveguide port and the equivalent admittance of the short-circuited waveguide. The transmission line model is effective even if lossy wall effect and dielectric partially-loading effect are considered. As a result, three-dimensional eigenmode parameters, such as the resonant frequency and the Q-factor, become dispensable and the computational complexity for the cavity simulation in the field of microwave heating is dramatically reduced.

In this paper, we present new important privacy goals for on-line matchmaking protocols, which are resistance to off-line dictionary attacks and forward privacy of users' identities and matching wishes. We enhance traditional privacy requirements (e.g., user anonymity, matching-wish authenticity) with our new privacy goals and define the notion of privacy-enhanced matchmaking. We show that previous solutions for on-line matchmaking do not satisfy the new privacy goals and argue that privacy-enhanced matchmaking cannot be provided by solutions to seemingly related problems such as secret handshakes, set intersection, and trust negotiation. We define an adversary model, which captures the key security properties of privacy-enhanced matchmaking, and show that a simple, practical protocol derived by a two-step transformation of a password-based authenticated key exchange counters adversary attacks in a provable manner (in the standard model of cryptographic security).

This paper presents a non-blind watermarking technique that is robust to non-linear geometric distortion attacks. This is one of the most challenging problems for copyright protection of digital content because it is difficult to estimate the distortion parameters for the embedded blocks. In our proposed scheme, the location of the blocks are recorded by the translation parameters from multiple Scale Invariant Feature Transform (SIFT) feature points. This method is based on two assumptions: SIFT features are robust to non-linear geometric distortion and even such non-linear distortion can be regarded as “linear” distortion in local regions. We conducted experiments using 149,800 images (7 standard images and 100 images downloaded from Flickr, 10 different messages, 10 different embedding block patterns, and 14 attacks). The results show that the watermark detection performance is drastically improved, while the baseline method can achieve only chance level accuracy.

In this paper, we propose a modified Tomlinson Harashima precoding (THP) method with less increase of computational complexity for the multi-user MIMO downlink system. The proposed THP scheme minimizes the influence of noise enhancement at the receivers by placing the diagonal weighted filters at both transmitter side and receiver side with square root. Compared to previously proposed non-linear precoding methods including vector perturbation (VP), the proposed THP achieves high BER performance. Furthermore, we show that the proposed THP method is implemented with lower computational complexity than that of existing modified THP and VP in literature.

Recursive least squares-based online nonnegative matrix factorization (RLS-ONMF), an NMF algorithm based on the RLS method, was developed to solve the NMF problem online. However, this method suffers from a partial-data problem. In this study, the partial-data problem is resolved by developing an improved online NMF algorithm using RLS and a sparsity constraint. The proposed method, RLS-based online sparse NMF (RLS-OSNMF), consists of two steps; an estimation step that optimizes the Euclidean NMF cost function, and a shaping step that satisfies the sparsity constraint. The proposed algorithm was evaluated with recorded speech and music data and with the RWC music database. The results show that the proposed algorithm performs better than conventional RLS-ONMF, especially during the adaptation process.

Developing a complex network accelerator like an IPsec processor is a great challenge. To this end, we propose a Network Virtual Platform ( NetVP ) that consists of one or more virtual host (vHOST) modules and virtual local area network (vLAN) modules to support electronic system level (ESL) top-down design flow as well as provide the on-line verification throughout the entire development process. The on-line verification capability of NetVP enables the designed target to communicate with a real network for system validation. For ESL top-down design flow, we also propose untimed and timed interfaces to support hardware/software co-simulation. In addition, the NetVP can be used in conjunction with any ESL development platform through the untimed/timed interface. System development that uses this NetVP is efficient and flexible since it allows the designer to explore design spaces such as the network bandwidth and system architecture easily. The NetVP can also be applied to the development of other kinds of network accelerators.

The paper describes how a robust and compact on-line handwritten Japanese text recognizer was developed by compressing each component of an integrated text recognition system including a SVM classifier to evaluate segmentation points, an on-line and off-line combined character recognizer, a linguistic context processor, and a geometric context evaluation module to deploy it on hand-held devices. Selecting an elastic-matching based on-line recognizer and compressing MQDF2 via a combination of LDA, vector quantization and data type transformation, have contributed to building a remarkably small yet robust recognizer. The compact text recognizer covering 7,097 character classes just requires about 15 MB memory to keep 93.11% accuracy on horizontal text lines extracted from the TUAT Kondate database. Compared with the original full-scale Japanese text recognizer, the memory size is reduced from 64.1 MB to 14.9 MB while the accuracy loss is only 0.5% from 93.6% to 93.11%. The method is scalable so even systems of less than 11 MB or less than 6 MB still remain 92.80% or 90.02% accuracy, respectively.

Precoding is an excellent choice for complementing the MIMO systems. Linear precoding techniques offer better performance at low signal-to-noise ratios (SNRs) while non-linear techniques perform better at higher SNRs. In addition, the non-linear techniques can achieve near optimal capacity at the expense of reasonable levels of complexity. However, precoding depends on the knowledge of the wireless channel. Recent work on MIMO systems have shown that channel-knowledge at the transmitter, in either full or partial forms, can increase the channel capacity and system performance considerably. Therefore, hybrid techniques should be deployed in order to obtain a better trade-off in terms of complexity and performance. In this paper, we present a hybrid precoding technique which deals with the condition of partial channel-knowledge while offering robustness against the effects of correlation and poorly scattered channels while at the same time keeping low levels of complexity and high performance.

In this paper, a new bandwidth allocation scheme is proposed based on the Mechanism Design (MD); MD is a branch of game theory that stimulates rational users to behave cooperatively for a global goal. The proposed scheme consists of bandwidth adaptation, call admission control and pricing computation algorithms to improve network performance. These algorithms are designed based on the adaptive online approach and work together to maximize bandwidth efficiency economically. A simulation shows that the proposed scheme can satisfy contradictory requirements and so provide well-balanced network performance.

3 dB bandwidth enhancement of single mode semiconductor lasers is confirmed numerically and experimentally when they are operated by intensity modulated signal light injection. 3 dB bandwidth is enlarged to 2.5 times of resonant frequency. The numerical analysis of rate equations predicts that the bandwidth enhancement is accomplished by the modal gain control of semiconductor lasers with injected intensity modulated signal light through non-linear gain coefficient term.

To achieve more accurate measurements of the mobile station (MS) location, it is possible to integrate many kinds of measurements. In this paper we proposed several simpler methods that utilized time of arrival (TOA) at three base stations (BSs) and the angle of arrival (AOA) information at the serving BS to give location estimation of the MS in non-line-of-sight (NLOS) environments. From the viewpoint of geometric approach, for each a TOA value measured at any BS, one can generate a circle. Rather than applying the nonlinear circular lines of position (LOP), the proposed methods are much easier by using linear LOP to determine the MS. Numerical results demonstrate that the calculation time of using linear LOP is much less than employing circular LOP. Although the location precision of using linear LOP is only reduced slightly. However, the proposed efficient methods by using linear LOP can still provide precise solution of MS location and reduce the computational effort greatly. In addition, the proposed methods with less effort can mitigate the NLOS effect, simply by applying the weighted sum of the intersections between different linear LOP and the AOA line, without requiring priori knowledge of NLOS error statistics. Simulation results show that the proposed methods can always yield superior performance in comparison with Taylor series algorithm (TSA) and the hybrid lines of position algorithm (HLOP).

This article presents an algorithm that solves an on-line version of the longest common subsequence (LCS) problem for two strings over a constant alphabet in O(d+n) time and O(m+d) space, where m is the length of the shorter string, the whole of which is given to the algorithm in advance, n is the length of the longer string, which is given as a data stream, and d is the number of dominant matches between the two strings. A new upper bound, O(p(m-q)), of d is also presented, where p is the length of the LCS of the two strings, and q is the length of the LCS of the shorter string and the m-length prefix of the longer string.

Intelligent transportation system (ITS) makes use of vehicle position to decrease the heavy traffic and improve service reliability of public transportation system. Many existing systems, such as global positioning system (GPS) and cellular communication systems, can be used to estimate vehicle location. The objective of wireless location is to determine the mobile station (MS) location in a wireless cellular communications system. The non-line-of-sight (NLOS) problem is the most crucial factor that it causes large measured error. In this paper, we present a novel positioning algorithm based on genetic algorithm (GA) to locate MS when three BSs are available for location purpose. Recently, GA are widely used as many various optimization problems. The proposed algorithm utilizes the intersections of three time of arrival (TOA) circles based on GA to estimate the MS location. The simulation results show that the proposed algorithms can really improve the location accuracy, even under severe NLOS conditions.

This paper proposes an adaptive algorithm for adaptive arrays that minimizes the bit error rate (BER) of the array output signals in radio communication systems with the use of multilevel modulation signals. In particular, amplitude phase shift keying (APSK) is used as one type of multilevel modulations in this paper. Simultaneous non-linear equations that are satisfied by the optimum weight vector of the proposed algorithm are derived and used for theoretical analyze of the performance of the adaptive array based on the proposed algorithm. As a result of the theoretical analysis, it can be shown that the proposed adaptive array improves the carrier to interference ratio of the array output signal without taking advantage of the nulls. Furthermore, it is confirmed that the result of the theoretical analysis agrees with that of computer simulation. When the number of the received antenna is less than that of the received signals, the adaptive array based on the proposed algorithm is verified to achieve much better performance then that based on the least mean square (LMS) algorithm.

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.

We consider a model composed of nonlinear perceptrons and analytically investigate its generalization performance using correlated examples in the framework of on-line learning by a statistical mechanical method. In Hebbian and AdaTron learning, the larger the number of examples used in an update, the slower the learning. In contrast, Perceptron learning does not exhibit such behaviors, and the learning becomes fast in some time region.

Weight perturbation learning was proposed as a learning rule in which perturbation is added to the variable parameters of learning machines. The generalization performance of weight perturbation learning was analyzed by statistical mechanical methods and was found to have the same asymptotic generalization property as perceptron learning. In this paper we consider the difference between perceptron learning and AdaTron learning, both of which are well-known learning rules. By applying this difference to weight perturbation learning, we propose adaptive weight perturbation learning. The generalization performance of the proposed rule is analyzed by statistical mechanical methods, and it is shown that the proposed learning rule has an outstanding asymptotic property equivalent to that of AdaTron learning.