Masqueraders who impersonate other users pose serious threat to computer security. Unfortunately, firewalls or misuse-based intrusion detection systems are generally ineffective in detecting masqueraders. Anomaly detection techniques have been proposed as a complementary approach to overcome such limitations. However, they are not accurate enough in detection, and the rate of false alarm is too high for the technique to be applied in practice. For example, recent empirical studies on masquerade detection using UNIX commands found the accuracy to be below 70%. In this research, we performed a comparative study to investigate the effectiveness of SVM (Support Vector Machine) technique using the same data set and configuration reported in the previous experiments. In order to improve accuracy of masquerade detection, we used command frequencies in sliding windows as feature sets. In addition, we chose to ignore commands commonly used by all the users and introduce the concept of voting engine. Though still imperfect, we were able to improve the accuracy of masquerade detection to 80.1% and 94.8%, whereas previous studies reported accuracy of 69.3% and 62.8% in the same configurations. This study convincingly demonstrates that SVM is useful as an anomaly detection technique and that there are several advantages SVM offers as a tool to detect masqueraders.

This paper is concerned with the signal processing aspects of the recently proposed interleave-division multiple-access (IDMA) scheme. We propose several low-cost detection algorithms to solve the problems of multiple-access, cross-antenna and intersymbol interference (ISI). The complexities (per user) of these algorithms are very low and increase either linearly or quadratically with the number of paths. It is shown that an IDMA system with a rate- 16-state convolutional code and a length-8 spreading sequence can support more than 100 users in a multipath fading channel with two receive antennas. This clearly indicates the great potential of IDMA systems.

The effect of feedback delay and channel estimation error on closed-loop transmit diversity (CTD) systems is investigated in time-selective Rayleigh fading channels. Based on a minimum mean square error (MMSE) channel estimator, the variance of the estimation error is formulated in terms of fading index and the number of transmit antennas. A bit error rate (BER) expression for the CTD system is analytically derived as a function of channel estimation error, feedback delay, and fading index. It is shown that the BER performance of the CTD system improves as the length of training symbols increases and/or the frame length decreases. In the CTD system, more accurate channel estimation scheme is required to achieve its full gain as the number of employed transmit antennas increases. It is also found that the CTD system is applicable to the slowly moving channel environments, such as pedestrians, but not for fast moving vehicles.

We have developed a quick battery checker the Li-ion battery packs used in mobile phones. It checks for capacity deterioration by using an impedance-measuring method. Our previous measurements of the capacity and impedance at 1 kHz for various battery packs proved conclusively that there is a strong correlation between degraded capacity and impedance. The battery checker's design took into account the results we obtained from measuring impedances. We showed that the battery checker is highly accurate and fast.

The MPEG-2 Test Model 5 (TM5) algorithm describes a rate control method which consists of three steps: bit allocation, rate control and modulation. In TM5, however, buffer overflow and picture quality degradation may occur at the end of the GOP because the target bits and the actual coding bits for each picture do not match well. This paper presents a new bit rate control algorithm for matching the target and the actual coding bits based on accurate bit allocation. The key idea of the proposed algorithm is to determine quantization parameters which enable us to generate the actual coding bits close to the target bits for each picture, while improving the picture quality. The proposed algorithm exploits the relationship between the number of the actual coding bits and the number of the estimated bits of the previous macroblock within a picture.

In this paper, we consider a blind channel estimation and equalization for single input multiple output (SIMO) channels. It is based on the one-step forward multichannel linear prediction error method. The derivation of the existing method is based on the noiseless assumption, however, we analyze the effects of additive noise at the output of the one-step forward multichannel linear prediction error filters. Moreover, we derive analytical results for the error in the blind channel estimation and equalization using linear prediction.

A high accuracy numerical technique based on the Finite Difference Time Domain (FDTD) method for a long dipole antenna analysis is presented. An improvement of the accuracy can be achieved without reducing the cell size by incorporating a quasi-static field behavior into the FDTD update equations. A closed form of the quasi-static field is obtained from a low frequency limit of a sinusoidal current distribution. The validity of the proposed algorithm is confirmed even when the length of dipole antenna is longer than half wavelength by comparing the results with the Method of Moment.

Fairness is one of the most important features of a rate allocation strategy. Proportional fairness criterion has been recently proposed by F. P. Kelly and his colleagues. In this paper, we have proposed a two-level hierarchical technique which allocates proportionally-fair rates to the network elastic users. Part of the network links which are used commonly by the end-users and are congestion prone, constitute the higher (first) level of the hierarchy. In this level, the users with common path in the network are grouped as virtual users. End-users and remaining network links constitute the lower (second) level of hierarchy. To improve the convergence rate of the algorithm, a combination of Jacobi method and fuzzy techniques is deployed in the higher level of hierarchy. Implementing such fast algorithms in the higher level (which is topologically simpler than the whole network), reduces the computational complexity with respect to the use of such algorithms in the whole network. Additionally, the lower level penalty function computation is done once in each N iterations, which reduces the computational complexity furthermore. The simulation results show that the proposed algorithm outperforms that of Kelly in the convergence speed.

In this paper, an adaptive bound reduced-form genetic algorithm (ABRGA) to tune the control points of B-spline neural networks is proposed. It is developed not only to search for the optimal control points but also to adaptively tune the bounds of the control points of the B-spline neural networks by enlarging the search space of the control points. To improve the searching speed of the reduced-form genetic algorithm (RGA), the ABRGA is derived, in which better bounds of control points of B-spline neural networks are determined and paralleled with the optimal control points searched. It is shown that better efficiency is obtained if the bounds of control points are adjusted properly for the RGA-based B-spline neural networks.

In this paper, we propose a fast fractal image coding based on LMSE (least mean square error) analysis and subblock feature. The proposed method focuses on efficient search of contrast scaling, position of its matched domain block, and isometric transform for a range block. The contrast scaling and the domain block position are searched using a cost function that comes from the LMSE analysis of the range block and its fractal-approximated block. The isometric transform is searched using 2 2 blocks formed with the averages of subblocks of range block and domain block. Experimental results show that the encoding time of a conventional fractal image coding with our search method is 25.6-39.7 times faster than that with full search method at the same bit rate while giving PSNR decrement of 0.2-0.7 dB with negligible deterioration in subjective quality. It is also shown that the encoding time of a conventional fractal image coding with our search method is 3.4-4.2 times faster than Jacquin's fractal image coding and is superior by maximum 0.8 dB in PSNR. It also yields reconstructed images of better quality.

A huge amount of information is being accumulated on the Internet as the Internet usage spreads and numbers of Web pages increase. However, it is also becoming very difficult to find required information, even when the information exists. The actual value of the Web is thus much lower than its potential value. In order to solve this problem, technologies which allow machines to handle Web content in an efficient, accurate, and flexible way by using machine-readable metadata are being developed. This paper is a survey of knowledge representation on the Web, and the utilization of metadata and ontology for data integration and information sharing, with a focus on the Semantic Web concept.

Application of multipled block codes (MBCs) for realizing new flexible and efficient transmission systems that feature in hunting-free reframing and asynchronous multiplexing is investigated. First, the principles of MBC are overviewed to show the capacities of filterless clock recovery. Then it is shown that modification of simple frame structure of MBC line code can be used for attaining hunting-free reframing for multiplexing systems. Two types of MBCs are developed to this end. While the one uses header blocks for hunting-free reframing, the other uses distributed frame patterns. Header design of multipled block codes (MBC) for hunting-free reframing (HFR) is investigated for frame patterns with and without violation compensation. The feasibility of hunting-free reframing is tested in an experimental system. Application of hunting-free reframing to asynchronous multiplexing is also investigated and tested in an experimental system. Finally, advantages of hunting-free multiplexing systems are discussed.

We develop an algorithm for a controller design method for Max-Plus Linear (MPL) systems with selective parameters. Since the conventional algorithm we proposed requires high computational load when the prediction horizon is large, two methods for reducing the calculation time are proposed. One is based upon the branch-and-bound method, and the other is to reuse the optimal solution. The effectiveness of these two methods is confirmed through numerical simulation.

Next generation wireless networks are expected to support multimedia applications (audio phone, video on demand, video conference, file transfer, etc.). Multimedia applications make a great demand for bandwidth and impose stringent quality of service (QoS) requirements on the wireless networks. In order to provide mobile hosts with high QoS, efficient and better bandwidth reservation is necessary in multimedia wireless networks. This paper presents a novel hybrid dynamic-grouping bandwidth reservation scheme to support QoS guarantees in the next generation wireless networks. The proposed scheme is based on probabilistic resource estimation to provide QoS guarantees for multimedia traffic in cellular networks. We establish several reservation time-sections, called groups, according to the mobility information of mobile hosts (MHs) of each base station (BS). The amount of reserved bandwidth for each BS is dynamically adjusted for each reservation group. We use the hybrid dynamic-grouping bandwidth reservation scheme to decrease the connection-dropping probability (CDP) and connection-blocking probability (CBP), while increasing the bandwidth utilization. The simulation results show that the hybrid dynamic-grouping bandwidth reservation scheme provides less CDP and less CBP, and achieves high bandwidth utilization.

This paper presents a model-based study of SET (Single-Electron-Transistor) logic gate family for synthesizing binary, MV (Multiple-Valued) and mixed-mode logic circuits. The use of SETs combined with MOS transistors allows compact realization of basic logic functions that exhibit periodic transfer characteristics. The operation of basic SET logic gates is successfully confirmed through SPICE circuit simulation based on the physical device model of SETs. The proposed SET logic gates are useful for implementing binary logic circuits, MV logic circuits and binary-MV mixed-mode logic circuits in a highly flexible manner. As an example, this paper describes design of various parallel counters for carry-propagation-free arithmetic, where MV signals are effectively used to achieve higher functionality with lower hardware complexity.

Nonminimum phase systems are difficult to be controlled with a conventional PID-type controller because of their inherent characteristics of undershooting. A neuro-controller combined with a PID-type controller has been shown to improve the control performance of the nonminimum phase systems while maintaining stability. In this paper, we apply a multiobjective evolutionary optimization method for training the neuro-controller to reduce the undershooting of the nonminimum phase system. The computer simulation shows that the proposed multiobjective approach is very effective and suitable because it can minimize the control error as well as reduce undershooting and chattering. This method can be applied to many industrial nonminimum phase problems with ease.

Feedforward neural networks have been successfully developed and applied in many areas because of their universal approximation capability. However, there still remains the problem of determining a suitable network structure for the given task. In this paper, we propose a novel self-organizing neural network which automatically adjusts its structure according to the task. Utilizing both the constructive and the pruning procedures, the proposed algorithm finds a near-optimal network which is compact and shows good generalization performance. One of its important features is reliability, which means the randomness of neural networks is effectively reduced. The resultant networks can have suitable numbers of hidden neurons and hidden layers according to the complexity of the given task. The simulation results for the well-known function regression problems show that our method successfully organizes near-optimal networks.

This paper is concerned with improving noise-robustness of a multi-SNR multi-band speaker identification system by introducing automatic adjustment of subband likelihood recombination weights. The adjustment is performed on the basis of subband power calculated from the noise observed just before the speech starts in the input signal. To evaluate the noise-robustness of this system, text-independent speaker identification experiments were conducted on speech data corrupted with noises recorded in five environments: "bus," "car," "office," "lobby," and "restaurant". It was found that the present method reduces the identification error by 15.9% compared with the multi-SNR multi-band method with equal recombination weights at 0 dB SNR. The performance of the present method was compared with a clean fullband method in which a speaker model training is performed on clean speech data, and spectral subtraction is applied to the input signal in the speaker identification stage. When the clean fullband method without spectral subtraction is taken as a baseline, the multi-SNR multi-band method with automatic adjustment of recombination weights attained 56.8% error reduction on average, while the average error reduction rate of the clean fullband method with spectral subtraction was 11.4% at 0 dB SNR.

This paper presents a multi-resolution optical flow estimation method that is robust against large variation in the estimation parameter. For each level solution of the multi-grid estimation, a nonlinear iteration is proposed differently from the existing method, where the incremental displacement from the coarser level optical flow is calculated by linear iteration. The experimental results show that the proposed scheme has better error-performance in a much wider range of regularization parameters.

Recently, a new light-weight version of the secure electronic transaction protocol was proposed. The protocol can achieve two goals. One goal is that the security level is the same as the SET protocol. The other goal is to reduce the computational time in message generation and verification, and reduce the communication overhead. However, the protocol has a weakness, which is that non-repudiation is acquired, but confidentiality is lost. In this paper, we point out the weakness of the protocol. We also propose an improvement to the protocol to overcome this weakness.