Ranking fuzzy numbers is one of very important research topics in fuzzy set theory because it is a base of decision-making in applications. However, fuzzy numbers may not be easily ordered into one sequence according to their magnitudes because they represent uncertain values. When two fuzzy numbers overlap with each other, a fuzzy number may not be considered absolutely larger than the other. That is, even when a fuzzy number may be considered larger than the other, it may also be considered smaller than the other. It means that for a given set of fuzzy numbers, several ranking sequences possibly exist. However, most of the existing ranking methods produce only one ranking sequence. They ignore other possible sequences due to the overlap between fuzzy numbers. We propose a ranking method which generates possible ranking sequences of given fuzzy numbers. Our method takes a viewpoint from users, and uses it for evaluation of fuzzy numbers. Fuzzy numbers will be ranked based on the evaluations and a fuzzy set of sequences of fuzzy numbers will be produced as a ranking results. Numeric examples and comparisons with other methods are also presented.

Automatic image inspector inspects the quality of printed circuit boards using image-processing technology. In this study, we change an automatic inspection problem into a problem for detecting the signal singularities. Based on the wavelet theory that the wavelet transform can focus on localized signal structures with a zooming procedure, a novel singularity detection and measurement algorithm is proposed. Singularity positions are detected with the local wavelet transform modulus maximum (WTMM) line, and the Lipschitz exponent is estimated at each singularity from the decay of the wavelet transform amplitude along the WTMM line. According to the theoretical analysis and computer simulation results, the proposed algorithm is shown to be successful for solving the automatic inspection problem and calculating the Lipschitz exponents of signals. These Lipschitz exponents successfully characterize singular behavior of signals at singularities.

It is shown that bounded impulse action can be combined with usual bang-bang control input to minimize the performance index. Especially for unstable oscillators, the size of controllable region can be increased. We present results on how to minimize the performance index using both ordinary bang-bang control and impulse actions with a recharge constraint on impulse firing. Following the maximum principle and necessary conditions induced from usual perturbation arguments, the mixed control input (bang-bang and impulse actions) is represented in adjoint state and then state variable feedback form. Simulation results show how the switch curves can be used to determine the optimal control value.

The objective of this study was to explore suitable spatial filters for inverse estimation of cortical potentials from the scalp electroencephalogram. The effect of incorporating noise covariance into inverse procedures was examined by computer simulations. The parametric projection filter, which allows inverse estimation with the presence of information on the noise covariance, was applied to an inhomogeneous three-concentric-sphere model under various noise conditions in order to estimate the cortical potentials from the scalp potentials. The present simulation results suggest that incorporation of information on the noise covariance allows better estimation of cortical potentials, than inverse solutions without knowledge about the noise covariance, when the correlation between the signal and noise is low. The method for determining the optimum regularization parameter, which can be applied for parametric inverse techniques, is also discussed.

In this letter, we present groupwise successive interference cancellation (GSIC) receiver with adaptive minimum mean squared error (MMSE) detection and extended GSIC (EGSIC) receiver with adaptive MMSE detection for dual-rate DS-CDMA system. The receivers are GSIC receiver and EGSIC receiver combined with adaptive MMSE detection which is introduced to make initial bit detection more reliable. Furthermore, a multi-user detection scheme is introduced to mitigate the effect of multiple access interference (MAI) between users in a group which is usually ignored in conventional GSIC receiver and EGSIC receiver. Specifically, parallel interference cancellation (PIC) is adopted as a multi-user detection scheme within a group. It is shown that performance of the GSIC receiver and EGSIC receiver is significantly improved by employing adaptive MMSE detection. It is also shown that the performance of the receivers can be improved further by using PIC within a group.

Analog Hopfield neural networks (HNNs) have so far been used to solve many kinds of optimization problems, in particular, combinatorial problems such as the TSP, which can be described by an objective function and some equality constraints. When we solve a minimization problem with equality constraints by using HNNs, however, the constraints are satisfied only approximately. In this paper we propose a circuit which rigorously realizes the equality constraints and whose energy function corresponds to the prescribed objective function. We use the SPICE program to solve circuit equations corresponding to the above circuits. The proposed method is applied to several kinds of optimization problems and the results are very satisfactory.

In this paper, we evaluate the performance of pilot channel-aided channel estimation for multicarrier direct-sequence (DS) code division multiple access (CDMA) communication system as proposed by Kondo and Milstein . We consider a multicarrier DS-CDMA system with different number of pilot and data channels. We investigate the optimum number of pilot channels for various coherence bandwidths and different number of subchannels. Keeping the total transmit bandwidth fixed, an optimum number of total subchannels and pilot channels exists under specific channel environment and transmitted energy. As the number of pilot channels increases, more accurate channel estimation is possible but the number of data channels decreases resulting a smaller diversity gain. We show that there is a tradeoff between the number of pilot channels and data subchannels, thereby requiring differing numbers of optimum pilot channels according to channel conditions.

Described here is an automatic text summarization system for Japanese newspaper articles on sassho-jiken (murders and bodily harms). We extract the pieces of information from a text, inter-connect them to represent the scenes and participants involved in the sassho-jiken, and finally produce a summary by generating sentences from the information extracted. An experiment and its evaluation show that, while a limitation being imposed on the domain, our method works well in depicting important information from the newspaper articles and the summaries produced are better in adequacy and readability than those obtained by extracting sentences.

The present paper deals with the frequency-dependent finite difference time domain ((FD)2TD) method analysis of the light-beam diffraction from a land/groove recording phase-change (PC) disk model with a metal (Al or Au) reflective layer in order to improve the conventional analysis for PC optical disk models with a perfectly conducting reflective layer. The diffracted fields are numerically calculated for both recorded and non-recorded states of the recording layer, and the comparison of the detected signal characteristics between two states is discussed. The crosstalk between the recording marks on lands and grooves are evaluated and the optimum groove depth is examined for Al,Au and perfectly conducting layer models.

In this paper, we propose a machine learning-based method of multi-document summarization integrating sentence extraction with bunsetsu elimination. We employ Support Vector Machines for both of the modules used. To evaluate the effect of bunsetsu elimination, we participated in the multi-document summarization task at TSC-2 by the following two approaches: (1) sentence extraction only, and (2) sentence extraction + bunsetsu elimination. The results of subjective evaluation at TSC-2 show that both approaches are superior to the Lead-based method from the viewpoint of information coverage. In addition, we made extracts from given abstracts to quantitatively examine the effectiveness of bunsetsu elimination. The experimental results showed that our bunsetsu elimination makes summaries more informative. Moreover, we found that extraction based on SVMs trained by short extracts are better than the Lead-based method, but that SVMs trained by long extracts are not.

This paper presents a Japanese Question Answering (QA) system based on a "Question Answering as Abduction" perspective. This perspective regards QA as the process of abductively explaining why a question is true based on logical contents of appropriately described textual information. This perspective is strongly inspired by Jerry Hobbs et al.'s "Interpretation as Abduction". It is also a simple conceptualization of Harabagiu et al.'s logic based QA system. We reify this concept in our QA system called SAIQA-Is. This system was designed to output only most likely answer candidates to a question. This system was participated in NTCIR QAC1. SAIQA-Is provided very good results in Task 2 and Task 3 of the QAC experiments. This results demonstrated strong feasibility and high potential of our Question Answering as Abduction approach.

In this paper, we give an algorithm for the node-to-set disjoint paths problem in pancake graphs with its evaluation results. The algorithm is of polynomial order of n for an n-pancake graph. It is based on recursion and divided into two cases according to the distribution of destination nodes in classes into which all the nodes in a pancake graph are categorized. The sum of lengths of paths obtained and the time complexity of the algorithm are estimated and the average performance is evaluated based on computer simulation.

Although there has been a great deal of research on automatic summarization, most methods rely on statistical methods, disregarding relationships between extracted textual segments. We propose a novel method to extract a set of comprehensible sentences which centers on several key points to ensure sentence connectivity. It features a similarity network from documents with a lexical dictionary, and spreading activation to rank sentences. We show evaluation results of a multi-document summarization system based on the method participating in a competition of summarization, TSC (Text Summarization Challenge) task, organized by the third NTCIR project.

This paper describes a practical Japanese natural language Question Answering system adopting effective selection of dynamic passages, Lexico-Semantic Patterns (LSP), and Predictive Answer Indexing. By analyzing the previous TREC QA data, we defined a dynamic passage unit and developed a passage selection method suitable for Question Answering. Using LSP, we identify the answer type of a question and detect answer candidates without any deep linguistic analyses of the texts. To guarantee a short response time, Predictive Answer Indexing is combined into our overall system architecture. As a result of the three engineering techniques, our system showed excellent performance when evaluated by mean reciprocal rank (MRR) in NTCIR-3 QAC-1.

A unified linear multiuser receiver that minimizes a weighted sum of the multiple access interference (MAI) and the background noise is introduced. The proposed receiver includes the three popular linear receivers, namely the matched-filter, the decorrelating and the minimum mean-square-error receivers as special cases. Furthermore, by tuning a single weighting factor, it is possible to improve the performance of the proposed receiver over that of any of the above mentioned linear receivers.

NK-Landscapes are stochastically generated fitness functions on bit strings, parameterized with N bits and K epistatic interactions between bits. The term epistasis describes nonlinearities in fitness functions due to changes in the values of interacting bits. Empirical studies have shown that the overall performance of random bit climbers on NK-Landscapes is superior to the performance of some simple and enhanced genetic algorithms (GAs). Analytical studies have also lead to suggest that NK-Landscapes may not be appropriate for testing the performance of GAs. In this work we study the effect of selection, drift, mutation, and recombination on NK-Landscapes for N = 96. We take a model of generational parallel varying mutation GA (GA-SRM) and switch on and off its major components to emphasize each of the four processes mentioned above. We observe that using an appropriate selection pressure and postponing drift make GAs quite robust on NK-Landscapes; different to previous studies, even simple GAs with these two features perform better than a random bit climber (RBC+) for a broad range of classes of problems (K 4). We also observe that the interaction of parallel varying mutation with crossover improves further the reliability of the GA, especially for 12 < K < 32. Contrary to intuition, we find that for small K a mutation only evolutionary algorithm (EA) is very effective and crossover may be omitted; but the relative importance of crossover interacting with varying mutation increases with K performing better than mutation alone (K > 12). This work indicates that NK-Landscapes are useful for testing each one of the major processes involved in a GA and for assessing the overall behavior of a GA on complex non-linear problems. This study also gives valuable guidance to practitioners applying GAs to real world problems of how to configure the GA to achieve better results as the non-linearity and complexity of the problem increases.

We present a new approach to the loop scheduling problem, which excels previous solutions in two important aspects: The resource constraints are formulated using flow graphs, and the initiation interval λ is treated as a rational variable. The approach supports heterogeneous processor architectures and pipelined functional units, and the Integer Linear Programming implementation produces an optimum loop schedule, whereby a minimum λ is achieved. Our flow graph model facilitates the cyclic binding of loop operations to functional units. Compared to previous research results, the solution can provide faster loop schedules and a significant reduction of the problem complexity and solution time.

In this paper our recently introduced method called output distributional influence function (ODIF) is used for the evaluation of the robustness properties of the nonlinear filter class of morphological filters. Several examples of the ODIFs for the dilation, closing and clos-opening are given and explained carefully. For each of these morphological filters the effect of filter length is examined by using the ODIFs for the expectation and variance. The robustness properties of the filters are also compared to each other and the effect of the distribution of the contamination is investigated for the closing as an example of realistic filtering conditions.

The array-enhanced coherence resonance (AECR) in the diffusively coupled active rotators is investigated and its analysis with the nonlinear Fokker-Planck equation is presented. By considering the nonlinear Fokker-Planck equation of the rotators, it is found that the time-periodic solution exists in some parameter range. By solving the equation of a rotator and the Fokker-Planck equation simultaneously, the behavior of a rotator in the system with infinite number of rotators is considered, and it is found that AECR also takes place in this infinite system. Thus it is concluded that AECR is caused by the time-periodic solution of the probability density induced by noise.

Probabilistic encryption becomes more and more important since its ability to against chosen-ciphertext attack. Applications like online voting schemes and one-show credentials are based on probabilistic encryption. Research on good probabilistic encryptions are on going, while many good deterministic encryption schemes are already well implemented and available in many systems. To convert any deterministic encryption scheme into a probabilistic encryption scheme, a randomized media is needed to apply on the message and carry the message over as an randomized input. In this paper, nonlinear codes obtained by certain mapping from linear error-correcting codes are considered to serve as such carrying media. Binary nonlinear codes obtained by Gray mapping from 4-linear codes are discussed as example for a such scheme.