This paper is to investigate the application of fuzzy c-means clustering to the direct identification of coherent synchronous generators in power systems. Because of the conceptual appropriateness and computational simplicity, this approach is essentially a fast and flexible method. At first, the coherency measures are derived from the time-domain responses of generators in order to reveal the relations between any pair of generators. And then they are used as initial element values of the membership matrix in the clustering procedures. An application of the proposed method to the Taiwan power (Taipower) system is demonstrated in an attempt to show the effectiveness of this clustering approach. The effects of short circuit fault locations, operating conditions, data sampling interval, and power system stabilizers are also investigated, as well. The results are compared with those obtained from the similarity relation method. And thus it is found that the presented approach needs less computation time and can directly initialize a clustering process for any number of clusters.

Many researchers have attempted to solve the combinatorial optimization problems, that are NP-hard or NP-complete problems, by using neural networks. Though the method used in a neural network has some advantages, the local minimum problem is not solved yet. It has been shown that the Inverse Function Delayed (ID) model, which is a neuron model with a negative resistance on its dynamics and can destabilize an intended region, can be used as the powerful tool to avoid the local minima. In our previous paper, we have shown that the ID network can separate local minimum states from global minimum states in case that the energy function of the embed problem is zero. It can achieve 100% success rate in the N-Queen problem with the certain parameter region. However, for a wider parameter region, the ID network cannot reach a global minimum state while all of local minimum states are unstable. In this paper, we show that the ID network falls into a particular permanent oscillating state in this situation. Several neurons in the network keep spiking in the particular permanent oscillating state, and hence the state transition never proceed for global minima. However, we can also clarify that the oscillating state is controlled by the parameter α which affects the negative resistance region and the hysteresis property of the ID model. In consequence, there is a parameter region where combinatorial optimization problems are solved at the 100% success rate.

The present paper introduces an integrated construction of binary sequences having a zero-correlation zone. The cross-correlation function and the side-lobe of the auto-correlation function of the proposed sequence set is zero for the phase shifts within the zero-correlation zone. The proposed method enables more flexible design of the binary zero-correlation zone sequence set with respect to its member size, length, and width of zero-correlation zone. Several previously reported sequence construction methods of binary zero-correlation zone sequence sets can be explained as special cases of the proposed method.

This paper presents a method to automatically acquire a given noun's telic and agentive roles from corpus data. These relations form part of the qualia structure assumed in the generative lexicon, where the telic role represents a typical purpose of the entity and the agentive role represents the origin of the entity. Our proposed method employs a supervised machine-learning technique which makes use of template-based contextual features derived from token instances of each noun. The output of our method is a ranked list of verbs for each noun, across the different qualia roles. We also propose a variant of Spearman's rank correlation to evaluate the correlation of two top-N ranked lists. Using this correlation method, we represent the ability of the proposed method to identify qualia structure relative to a conventional template-based method.

In a time-invariant wireless channel, the multipath that exceeds the cyclic prefix (CP) or the guard interval (GI) causes orthogonal frequency division multiplexing (OFDM) systems to hardly achieve high data rate transmission due to the inter-symbol interference (ISI) and the inter-carrier interference (ICI). In this paper the new canceller scheme, named as Double Window Cancellation and Combining (DWCC) is proposed. It includes the entire symbol interval, delayed by multipath as a signal processing window and intends to improve the performance by combining the double windows that can be formed by the pre- and post-ISI cancellation and reconstruction to the received OFDM symbol interfered by the multipath exceeding the guard interval. The proposed scheme has two algorithm structures of the DWCC-I and -II which are distinguished by the operational sequence (Symbol-wise or Group-wise) to the OFDM symbols of the received packet and by the selection of the processing window in the iterative decision feedback processing. Since the performance of the canceller is dependant on the equalization, particularly on the initial equalization, the proposed schemes operate with the time and frequency domain equalizer in the initial and the iterative symbol detection, respectively. For the verification of the proposed schemes, each scheme is evaluated in the turbo coded OFDM for low (QPSK) and high level modulation systems (16QAM, 64QAM), and compared with the conventional canceller with respect to the performance and computational complexity. As a result, the proposed schemes do not have an error floor even for 64QAM in a severe frequency selective channel.

This paper describes the distortion properties created by self-phase modulation in super wideband FM converted 40 AM/30 64-QAM CATV and super-high-frequency RF converted 8 BS/12 CS TV signal transmission based on the optical SSB modulation scheme.

Visual inpainting is an interpolation problem that restores an image or a frame with missing or damaged parts. Over the past decades, a number of computable models of visual inpainting have been developed, but most of these models are based on the pixel domain. Little theoretical and computational work of visual inpainting is based on the compressed domain. In this paper, a visual inpainting model in the discrete cosine transform (DCT) domain is proposed. DCT coefficients of the non-inpainting blocks are utilized to get block features, and those block features are propagated to the inpainting region iteratively. The experimental results with I frames of MPEG4 are presented to demonstrate the efficiency and accuracy of the proposed algorithm.

This paper reviews and discusses devices, circuits, and signal processing techniques for CMOS imaging SoC's based on column-parallel processing architecture. The pinned photodiode technology improves the noise characteristics at the device level to be comparable to CCD image sensors and as a result, low-noise design in CMOS image sensors has been shifted to the reduction of noise at the circuit level. Techniques for reducing the circuit noise are discussed. The performance of the imaging SoC's greatly depends on that of the analog-to-digital converter (ADC) used at the column. Three possible architectures of the column-parallel ADC are reviewed and their advantage and disadvantage are discussed. Finally, a few applications of the device and circuit techniques and the column-parallel processing architecture are described.

It has been shown that the output information produced by the soft output Viterbi algorithm (SOVA) is too optimistic. To compensate for this, the output information should be normalized. This letter proposes a simple normalization technique that extends the existing sign difference ratio (SDR) criterion. The new normalization technique counts the sign differences between the a-priori information and the extrinsic information, and then adaptively determines the corresponding normalization factor for each data block. Simulations comparing the new technique with other well-known normalization techniques show that the proposed normalization technique can achieve about 0.2 dB coding gain improvement on average while reducing up to about 1/2 iteration for decoding.

A 128128 pixel functional image sensor was implemented. The sensor was able to capture images at 1,000 frame/s and extract the sizes and positions of 10 objects/frame when clocked at 8 MHz. The size of each pixel was 18 µm18 µm and the fill factor was 28%. The chip, 3.24 mm3.48 mm in size, was implemented with a 0.35 µm CMOS sensor process; the power consumption was 29.7 mW at 8 MHz.

For the closed loop multiple-input-multiple-output (MIMO) systems, Fisher's adaptive bit loading algorithm gives the best error performance by jointly optimizing the transmit powers, rates, and number of streams. However, its good performance comes at the cost of high and variable computational complexity for the joint optimization. In this letter, we propose an efficient multi-mode precoding algorithm using a simplified mode table. Numerical results show that the proposed algorithm provides almost the same performance as Fischer's with much less computational complexity.

A Verilog-AMS model of a fractional-N frequency synthesizer is presented that is capable of predicting spurious tones as well as noise and jitter performance. The model is based on a voltage-domain behavioral simulation. Simulation efficiency is improved by merging the voltage controlled oscillator (VCO) and the frequency divider. Due to the benefits of Verilog-AMS, the ΔΣ modulator which is incorporated in the synthesizer is modeled in a fully digital way. This makes it accurate enough to evaluate how the performance of the frequency synthesizer is affected by cyclic behavior in the ΔΣ modulator. The spur-minimizing effect of an odd initial condition on the first accumulator of the ΔΣ modulator is verified. Sequence length control and its effect on the fractional-N frequency synthesizer are also discussed. The simulated results are in agreement with prior published data on fractional-N synthesizers and with new measurement results.

A new scheme for reducing optical beat interference noise in a reflective semiconductor optical amplifier based wavelength division multiplexed/subcarrier multiplexing -- passive optical network is proposed. This method uses an Fabry Perot laser locked by modulated lights from optical network units in a central office. As an experimental verification, it is reported that carrier to noise ratio is enhanced by 10 dB and power penalty is improved by 16 dB.

Inter-Vehicle Communication (IVC) is one of the most important technologies to realize advanced Intelligent Transport Systems (ITS). We extensively apply the IVC technology to the communications between pedestrians and vehicles. We call this kind of communications VPEC (Vehicle-PEdestrian Communications). The objective of this paper is to present an effective control scheme for VPEC and to evaluate the performance of proposed scheme by experiments. We deal with direct communications between pedestrians and vehicles. Due to the battery shortage of pedestrians' terminals (p-node), we have presented a reflect-transmission scheme. In this paper, we propose a new access protocol for reflect-transmission scheme, and show its validity by various experiments with several vehicles.

The major application of digital data hiding techniques is to deliver confidential data secretly via public but unreliable computer networks. Most of the existing data hiding schemes, however, exploit the raw data of cover images to perform secret communications. In this paper, a novel data hiding scheme was presented with the manipulation of images based on the compression of side-match vector quantization (SMVQ). This proposed scheme provided adaptive alternatives for modulating the quantized indices in the compressed domain so that a considerable quantity of secret data could be artfully embedded. As the experimental results demonstrated, the proposed scheme indeed provided a larger payload capacity without making noticeable distortions in comparison with schemes proposed in earlier works. Furthermore, this scheme also presented a satisfactory compression performance.

In this paper, we propose a novel analysis method for large-scale networks with consideration of the behavior of the congestion control mechanism of TCP. In the analysis, we model the behavior of TCP at end-host and network link as independent systems, and combine them into a single system in order to analyze the entire network. Using this analysis, we can analyze a large-scale network, i.e. with over 100/1,000/10,000 routers/hosts/links and 100,000 TCP connections very rapidly. Especially, a calculation time of our analysis, it is different from that of ns-2, is independent of a network bandwidth and/or propagation delay. Specifically, we can derive the utilization of the network links, the packet loss ratio of the link buffer, the round-trip time (RTT) and the throughput of TCP connections, and the location and degree of the network congestion. We validate our approximate analysis by comparing analytic results with simulation ones. We also show that our analysis method treats the behavior of TCP connection in a large-scale network appropriately.

Note taking is a fundamental activity for learning, and many software tools which enable students to take digitized notes have been proposed. Digitized notes are advantageous because they can be easily edited, rearranged, and shared. Although many note-taking tools have been proposed, there has been little research to examine the effect of note annotation and rearrangement with a digitized tool in terms of knowledge acquisition. Therefore, we have investigated the effect of note annotation and rearrangement on how well lecture content is remembered by learners. By annotation, we mean adding both handwritten and typed text, and rearrangement includes moving and deleting handwritten notes. We developed a simple note-taking application specialized for explanation, and evaluated it through a laboratory experiment with eight participants. The results show that note annotation and rearrangement significantly improved how well the participants remembered lecture content. Thus, the effect of annotation and rearrangement on remembrance was confirmed with respect to digitized notes.

Correctness of Java programs is important because they are executed in distributed computing environments. The object initialization scheme in the Java programming language is complicated, and this complexity may lead to undesirable semantic bugs. Various tools have been developed for detecting program patterns that might cause errors during program execution. However, current tools cannot identify code patterns in which an uninitialized field is accessed when an object is initialized. We refer to such erroneous patterns as uninitialized field references. In this paper, we propose a static pattern detection algorithm for identifying uninitialized field references. We design a sound analysis for this problem and implement an analyzer using the Soot framework. In addition, we apply our algorithm to some real Java applications. From the experiments, we identify 12 suspicious field references in the applications, and among those we find two suspected errors by manual inspection.

We designed subthreshold analog MOS circuits implementing an inhibitory network model that performs noise-shaping pulse-density modulation (PDM) with noisy neural elements, with the aim of developing a possible ultralow-power one-bit analog-to-digital converter. The static and dynamic noises given to the proposed circuits were obtained from device mismatches of current sources (transistors) and externally applied random spike currents, respectively. Through circuit simulations we confirmed that the circuit exhibited noise-shaping properties, and signal-to-noise ratio (SNR) of the network was improved by 7.9 dB compared with that of the uncoupled network as a result of noise shaping.

Petri nets are known as a modeling language for concurrent and distributed systems. In recent years, various object-oriented Petri nets were proposed, and we are proposing a kind of object-oriented Petri nets, called multi agent nets (MANs). In this letter, we consider the reachability analysis of MANs. We propose an algorithm for generating an abstract state space of a multi agent net, and report results of computational experiments.