A fine-grain reconfigurable VLSI for various applications including arithmetic operations is developed. In the fine-grain architecture, it is important to define a cell function which leads to high utilization of a logic block and reduction of a switch block. From the point of view, a universal-literal-based multiple-valued cell suitable for bit-serial reconfigurable computation is proposed. A series-gating differential-pair circuit is effectively employed for implementing a full-adder circuit of Sum and a universal literal circuit. Therefore, a simple logic block can be constructed using the circuit technology. Moreover, interconnection complexity can be reduced by utilizing multiple-valued signaling, where superposition of serial data bits and a start signal which indicates heading of one-word is introduced. Differential-pair circuits are also effectively employed for current-output replication, which leads to high-speed signaling to adjacent cells The evaluation is done based on 90 nm CMOS design rule, and it is made clear that the area of the proposed cell can be reduced to 78% in comparison with that of the CMOS implementatiuon. Moreover, its area-time product becomes 92% while the delay time is increased by 18%.

In this letter, we propose an adaptive transmission method for an OFDMA system supporting both band-AMC and diversity modes in a frame, simultaneously. In the proposed method, users are classified into the two groups preferring the band-AMC mode or the diversity mode based on their channel parameters. Then the BS performs resource allocation to maximize the throughput. It is observed that the proposed adaptive transmission method can reduce the feedback overhead with negligible performance loss.

Source-drain follower has been designed and implemented for monolithically integrated biosensor array. The circuit acts as a voltage follower, in which a sensing transistor is operated at fixed gate-source and gate-drain voltages. It operates at 10 nW power dissipation. The wide-swing cascode configurations are investigated in constant and non-constant biasing methods. The constant biased cascode source-drain follower has the merit of small cell size. The chip was fabricated using 1.2 µm standard CMOS technology, and a wide range of operation between 1 nW and 100 µW was demonstrated. The accuracy of the voltage follower was 30 mV using minimum sized transistors, due to the variation of threshold voltage. The error in the output except for the threshold voltage mismatch was less than 10 mV. The temperature dependence of the output was 0.11 mV/. To improve the input voltage range and accuracy, non-constant biased cascode source-drain follower is examined. The sensor cell is designed for 10 mV accuracy and the cell size is 105.3µm 81.4 µm in 1.2 µm CMOS design rules. The sensor cell was fabricated and showed that the error in the output except for the threshold voltage mismatch was less than 2 mV in a range of total current between 3 nA and 10 µA and in a temperature range between 30 and 100.

Wireless technology has become widely popular and an important means of communication. A key issue in delivering wireless services is the problem of congestion which has an adverse impact on the Quality of Service (QoS), especially timeliness. Although a lot of work has been done in the context of RRM (Radio Resource Management), the deliverance of quality service to the end user still remains a challenge. Therefore there is need for a system that provides real-time services to the users through high assurance. We propose an intelligent agent-based approach to guarantee a predefined Service Level Agreement (SLA) with heterogeneous user requirements for appropriate bandwidth allocation in QoS sensitive cellular networks. The proposed system architecture exploits Case Based Reasoning (CBR) technique to handle RRM process of congestion management. The system accomplishes predefined SLA through the use of Retrieval and Adaptation Algorithm based on CBR case library. The proposed intelligent agent architecture gives autonomy to Radio Network Controller (RNC) or Base Station (BS) in accepting, rejecting or buffering a connection request to manage system bandwidth. Instead of simply blocking the connection request as congestion hits the system, different buffering durations are allocated to diverse classes of users based on their SLA. This increases the opportunity of connection establishment and reduces the call blocking rate extensively in changing environment. We carry out simulation of the proposed system that verifies efficient performance for congestion handling. The results also show built-in dynamism of our system to cater for variety of SLA requirements.

This letter presents a 0.5 V low-voltage op-amp in a standard 0.18 µm CMOS process for switched-capacitor circuits. Unlike other two-stage 0.5 V op-amp architectures, this op-amp consists of CMOS inverters that utilize floating voltage sources and forward body bias for obtaining high-speed operation. And two improved common-mode rejection circuits are well combined to achieve low power and chip area reduction. Simulation results indicate that the op-amp has an open-loop gain of 62 dB, and a high unity gain bandwidth of 56 MHz. The power consumption is only 350 µW.

This paper clarifies the adequacy of the linear channel coding approach for the source coding with partial side information at the decoder. A sufficient condition for an ensemble of linear codes which achieves the Wyner's bound is given. Our result reveals that, by combining a good lossy code, an LDPC code ensemble gives a good code for source coding with partial side information at the decoder.

In this paper, a robust sound source localization approach is proposed. The approach retains good performance even when model errors exist. Compared with previous work in this field, the contributions of this paper are as follows. First, an improved broad-band and near-field array model is proposed. It takes array gain, phase perturbations into account and is based on the actual positions of the elements. It can be used in arbitrary planar geometry arrays. Second, a subspace model errors estimation algorithm and a Weighted 2-Dimension Multiple Signal Classification (W2D-MUSIC) algorithm are proposed. The subspace model errors estimation algorithm estimates unknown parameters of the array model, i.e., gain, phase perturbations, and positions of the elements, with high accuracy. The performance of this algorithm is improved with the increasing of SNR or number of snapshots. The W2D-MUSIC algorithm based on the improved array model is implemented to locate sound sources. These two algorithms compose the robust sound source approach. The more accurate steering vectors can be provided for further processing such as adaptive beamforming algorithm. Numerical examples confirm effectiveness of this proposed approach.

In this letter, we propose a new energy efficient online routing algorithm for QoS-sensitive sensor networks. An important design principle underlying our algorithm is online decision making based on real time network estimation. This on-line approach gives adaptability and flexibility to solve a wide range of control tasks for efficient network performance. In addition, our distributed control paradigm is practical for real sensor network management. Simulation results indicate the superior performance of our algorithm between energy efficiency and QoS provisioning.

Wyner and Ziv characterized the rate distortion function for lossy source coding with side information at the decoder. It is well known that for the quadratic Gaussian case, the Wyner-Ziv rate-distortion function coincides with the conditional rate-distortion function. In this paper, we extend the problem to the coding of multivariate Gaussian source with multiple Gaussian side information at the decoder. The achievable region is obtained, and it is easily extended to the case that the difference between the source and the side information is multivariate Gaussian, no matter what distributions the source and the side information are. We apply this theoretical model to Distributed Video Coding (DVC) by considering the difference of the Distributed frame (D frame) and the Side-information frame (S frame) to be multivariate Gaussian distributed. This introduces rate allocation problem into DVC, which can be solved by a reverse water-filling method. Simulation results show that around 1.5-2 dB coding gain benefits from the multivariate Gaussian Wyner-Ziv coding model.

In this paper, we propose a two-microphone noise reduction method to deal with non-stationary interfering noises in multiple-noise-source environments in which the traditional two-microphone algorithms cannot function well. In the proposed algorithm, multiple interfering noise sources are regarded as one virtually integrated noise source in each subband, and the spectrum of the integrated noise is then estimated using its virtual direction of arrival. To do this, we suggest a direction finder for the integrated noise using only two microphones that performs well even in speech active periods. The noise spectrum estimate is further improved by integrating a single-channel noise estimation approach and then subtracted from that of the noisy signal, finally enhancing the desired target signal. The performance of the proposed algorithm is evaluated and compared with the traditional algorithms in various conditions. Experimental results demonstrate that the proposed algorithm outperforms the traditional algorithms in various conditions in terms of objective and subjective speech quality measures.

This paper illustrates a feasible health informatics domain knowledge management process which helps gather useful technology information and reduce many knowledge misunderstandings among engineers who have participated in the IBM mainframe rightsizing project at National Taiwan University (NTU) Hospital. We design an asynchronously sharing mechanism to facilitate the knowledge transfer and our health informatics domain knowledge management process can be used to publish and retrieve documents dynamically. It effectively creates an acceptable discussion environment and even lessens the traditional meeting burden among development engineers. An overall description on the current software development status is presented. Then, the knowledge management implementation of health information systems is proposed.

Research into applying LDPC code theory, which is used for channel coding, to source coding has received a lot of attention in several research fields such as distributed source coding. In this paper, a source coding problem with a fidelity criterion is considered. Matsunaga et al. and Martinian et al. constructed a lossy code under the conditions of a binary alphabet, a uniform distribution, and a Hamming measure of fidelity criterion. We extend their results and construct a lossy code under the extended conditions of a binary alphabet, a distribution that is not necessarily uniform, and a fidelity measure that is bounded and additive and show that the code can achieve the optimal rate, rate-distortion function. By applying a formula for the random walk on lattice to the analysis of LDPC matrices on Zq, where q is a prime number, we show that results similar to those for the binary alphabet condition hold for Zq, the multiple alphabet condition.

We propose a new algorithm for the blind source separation (BSS) approach in which independent component analysis (ICA) and frequency subband beamforming interpolation are combined. The slow convergence of the optimization of the separation filters is a problem in ICA. Our approach to resolving this problem is based on the relationship between ICA and null beamforming (NBF). The proposed method consists of the following three parts: (I) a frequency subband selector part for learning ICA, (II) a frequency domain ICA part with direction-of-arrivals (DOA) estimation of sound sources, and (III) an interpolation part in which null beamforming constructed with the estimated DOA is used. The results of the signal separation experiments under a reverberant condition reveal that the convergence speed is superior to that of the conventional ICA-based BSS methods.

There are many protocols proposed for protecting Radio Frequency Identification (RFID) system privacy and security. A number of these protocols are designed for protecting long-term security of RFID system using symmetric key or public key cryptosystem. Others are designed for protecting user anonymity and privacy. In practice, the use of RFID technology often has a short lifespan, such as commodity check out, supply chain management and so on. Furthermore, we know that designing a long-term security architecture to protect the security and privacy of RFID tags information requires a thorough consideration from many different aspects. However, any security enhancement on RFID technology will jack up its cost which may be detrimental to its widespread deployment. Due to the severe constraints of RFID tag resources (e.g., power source, computing power, communication bandwidth) and open air communication nature of RFID usage, it is a great challenge to secure a typical RFID system. For example, computational heavy public key and symmetric key cryptography algorithms (e.g., RSA and AES) may not be suitable or over-killed to protect RFID security or privacy. These factors motivate us to research an efficient and cost effective solution for RFID security and privacy protection. In this paper, we propose a new effective generic binary tree based key agreement protocol (called BKAP) and its variations, and show how it can be applied to secure the low cost and resource constraint RFID system. This BKAP is not a general purpose key agreement protocol rather it is a special purpose protocol to protect privacy, un-traceability and anonymity in a single RFID closed system domain.

This paper describes the IKEv2 protocol and presents how an open-source IKEv2 implementation, in particular OpenIKEv2 has been designed and implemented. All the issues found during this process and how they were solved are also described. Finally, a comparison between existing open-source implementations is presented.

To develop usable software, it is necessary to develop Graphical User Interfaces (GUIs) in iterative steps, such as evaluating the usability of GUIs and improving GUIs. In improving GUIs, developers are often required to modify both the GUI and the logic code of the software. In our research, to facilitate GUI improvement, we propose a method of automatically searching for code to be modified and suggesting how to modify them. To search for appropriate code to be modified, we define the roles of widgets according to their purpose and the patterns for how to change GUIs. In our method, how to change GUIs is specified, and then the parts of source programs that are required to be modified are searched for. Also, we classify methods for each widget according to their functions. Using this classification, a method of modifying the code that is searched for is suggested.

This paper investigates migration effects of parallel genetic algorithms (GAs) on the line topology of heterogeneous computing resources. Evolution process of parallel GAs is evaluated experimentally on two types of arrangements of heterogeneous computing resources: the ascending and descending order arrangements. Migration effects are evaluated from the viewpoints of scalability, chromosome diversity, migration frequency and solution quality. The results reveal that the performance of parallel GAs strongly depends on the design of the chromosome migration in which we need to consider the arrangement of heterogeneous computing resources, the migration frequency and so on. The results contribute to provide referential scheme of implementation of parallel GAs on heterogeneous computing resources.

Fetal electrocardiogram (FECG) extraction is of vital importance in biomedical signal processing. A promising approach is blind source extraction (BSE) emerging from the neural network fields, which is generally implemented in a semi-blind way. In this paper, we propose a robust extraction algorithm that can extract the clear FECG as the first extracted signal. The algorithm exploits the fact that the FECG signal's kurtosis value lies in a specific range, while the kurtosis values of other unwanted signals do not belong to this range. Moreover, the algorithm is very robust to outliers and its robustness is theoretically analyzed and is confirmed by simulation. In addition, the algorithm can work well in some adverse situations when the kurtosis values of some source signals are very close to each other. The above reasons mean that the algorithm is an appealing method which obtains an accurate and reliable FECG.

This paper investigates the fixed-slope lossy coding of individual sequences and nonstationary sources. We clarify that, for a given individual sequence, the optimal cost attainable by the blockwise lossy encoders is equal to the optimal average cost with respect to the empirical distribution of the given sequence. Moreover, we show that, for a given nonstationary source, the optimal cost attainable by the blockwise encoders is equal to the supremum of the optimal average cost over all the stationary sources in the stationary hull of the given source. In addition, we show that the universal lossy coding algorithm based on Lempel-Ziv 78 code attains the optimal cost for any individual sequence and any nonstationary source.

We present a TCP flow level performance evaluation on error rate aware scheduling algorithms in Evolved UTRA and UTRAN networks. With the introduction of the error rate, which is the probability of transmission failure under a given wireless condition and the instantaneous transmission rate, the transmission efficiency can be improved without sacrificing the balance between system performance and user fairness. The performance comparison with and without error rate awareness is carried out dependant on various TCP traffic models, user channel conditions, schedulers with different fairness constraints, and automatic repeat request (ARQ) types. The results indicate that error rate awareness can make the resource allocation more reasonable and effectively improve the system and individual performance, especially for poor channel condition users.