In a Cognitive Radio system, it is essential to recognize and avoid sources of interference signals. This paper describes a study on a location sensing scheme for interference signals, which utilizes multi-beam phased array antenna for cognitive wireless networks. This paper also elucidates its estimation accuracy of the interference location for the radio communication link using an OFDM signal such as WiMAX. Furthermore, we use the frequency spectrum of the received OFDM interference signal, to create a method that can estimate the propagation status. This spectrum can be monitored by using a software defined radio receiver.

Reliable detection of other radio systems is crucial for systems that share the same frequency band. In wireless communication channels, there is uncertainty in the received signal level due to multipath fading and shadowing. Cooperative sensing techniques in which radio stations share their sensing information can improve the detection probability of other systems. In this paper, a new cooperative sensing scheme that reduces the false detection probability while maintaining the outage probability of other systems is investigated. In the proposed system, sensing information is collected using multi-hop transmission from all sensing stations that detect other systems, and transmission decisions are based on the received sensing information. The proposed system also controls the transmit power based on the received CINRs from the sensing stations. Simulation results reveal that the proposed system can reduce the outage probability of other systems, or improve its link success probability.

The present paper proposes two novel and practical schemes for distributed and asynchronous power control in wireless ad hoc networks, in which users dynamically share several frequency bands as in "cognitive radio" networks. These schemes iteratively adjust transmit powers of individual network transmitters with respect to mutually caused interference in the shared bands. Their most attractive feature is that they find network-wide acceptable trade-offs to diverse signal-to-noise and interference (SINR) requirements and efficiently use techniques of stochastic approximation and time-averaging to guarantee a robust performance in random channels. Advantageously, both proposed algorithms do not assume any particular modulation, coding, QoS measure definition or network architecture, which assures their high applicability in the industry and research. Moreover, the broad definition and non-linear nature of these schemes mathematically generalize and thus encompass as a special case many widely deployed power control schemes such as e.g. those for achieving fixed SINR targets or using game-theoretic utility maximization. Simulations are provided to illustrate our approach and its better performance compared to standard algorithms.

RF system and circuit approaches for cognitive radios, based on software defined radio technology, are discussed. The increasing use of digital techniques, combined with wideband data converters and tunable front-end technologies, will enable these systems to become cost effective in the coming years.

"Cognitive radio" and "software-defined radio" (SDR) are today an important consideration in major spectrum debates in the United States. The U.S. drafted its first SDR rules in 2001, and since has continued efforts to resolve potential regulatory concerns and facilitate the benefits of the technology. At the same time, Japan has had a very rich experience in the lab with SDR, with significant achievements on many engineering topics. However, the regulatory state of SDR in Japan has not kept pace with the United States. Likewise cognitive radio, while a topic of inquiry, betrays a different focus. The paper explores why the paths for these technologies have diverged in the U.S. and Japan.

One of the challenging issues in affective computing is to give a machine the ability to recognize the affective states with intensity of a person. Few studies are directed toward this goal by categorizing affective behavior of the person into a set of discrete categories. But still two problems exist: gesture is not yet a concern as a channel of affective communication in interactive technology, and existing systems only model discrete categories but not affective dimensions, e.g., intensity. Modeling the intensity of emotion has been well addressed in synthetic autonomous agent and virtual environment literature, but there is an evident lack of attention in other important research areas such as affective computing, machine vision, and robotic. In this work, we propose an affective gesture recognition system that can recognize the emotion of a child and the intensity of the emotion states in a scenario of game playing. We used levels of cognitive and non-cognitive appraisal factors to estimate intensity of emotion. System has an intelligent agent (called Mix) that takes these factors into consideration and adapt the game state to create a more positive interactive environment for the child.

The RF environment in the future will consist of many mobile devices operating across a wide range of applications. Most radio developments assume a static operating environment. The physical layer, MAC layer, and network protocols are optimized for that specific environment. However, this new RF environment consisting of many mobile devices will be very dynamic. Radios will need the capacity to sense and adapt to changing environmental conditions. That characteristic is generally associated with cognitive radio. This paper will provide an introduction to new strategies for designing systems for this new, dynamic environment using cognitive radio technology.

The development of information/communication technology has made it possible to access substantial amounts of data and retrieve information. However, it is often difficult to locate the desired information, and it becomes necessary to spend considerable time determining how to access specific available data. This paper describes a method to quantitatively evaluate the usability of large-scale information-oriented websites and the effects of improvements made to the site design. This is achieved by utilizing the Cognitive Walkthrough for the Web and website modeling using Markov chains. We further demonstrate that we can greatly improve usability through simple modification of the link structure by applying our approach to an actual informational database website with over 40,000 records.

Aging is progressing in our country. Cerebral disease poses a serious problem. Viewing this problem objectively, we can say that support of aging and cerebral disease patients is a useful research theme. To the present, we have done rank evaluation of cerebral disease using synthetic face picture images. This study assesses cognitive ability and expression control ability for intoxication, which is known to impair thinking, cognition, and memory ability. We also examine correspondence of intoxication to cerebral disease. Measurement of cognitive ability corresponds to observation of an internal condition; the measurement of expression control ability corresponds to observation of an external condition. In measurement of cognitive ability, we simulated early stage symptoms of vascular dementia in the second stage of BAC. Also, decreased cognitive ability occurs from the first stage of BAC on face recognition to figure and language. Moreover, face test results show significant difference between decrease in the first stage of BAC and one in the second stage of BAC. These results indicate the possibility of rank evaluation and early stage detection of vascular dementia using a face picture image. From measurement of expression control ability, we obtained the result that we can judge whether a subject has reached second stage of BAC by observing an expression's strength of smile. The second stage of BAC shows symptoms similar to those of vascular dementia. We found the possibility that smile is valid as one externally-observable index for detection of cerebral disease.

We discuss human collaborative discovery processes using a production system model as a cognitive simulator. We have developed an interactive production system architecture to construct the simulator. Two production systems interactively find targets in which the only experimental results are shared; each does not know the hypothesis the other system has. Through this kind of interaction, we verify whether or not the performance of two systems interactively finding targets exceeds that of two systems independently finding targets. If we confirm the superiority of collaborative discovery, we approve of emergence by the interaction. The results are: (1) generally speaking collaboration does not produces the emergence defined above, and (2) as the different degree of hypothesis testing strategies that the two system use gets larger, the benefits of interaction gradually increases.

A requirement specification acquisition method combined with hypothesis-based reasoning and model reasoning is proposed for obtaining service specifications from the ambiguous and/or incomplete requirement specifications of communications services. Errors at an early stage of software development cost more to debug than those at a later stage. Specification acquisition is the most upstream development process. Nevertheless, the system support for specification acquisition is delayed compared with other development phases.' Users do not always have precise requirements. It is therefore inevitable that user requirements contain ambiguities, insufficiencies and even contradictions. Considering this, it is indispensable to support a specification completion method that derives service specifications from such problem requirements. This paper proposes a combined method to obtain consistent and complete specifications from such problem requirements. Communications service specifications can be described by specifying terminal behaviors which can be recognized from outside the communications system(s). Such specifications are described by a rule-based language. Requirement specifications usually have components that are ambiguous, incomplete, or even contradictory. They appear as rule description and/or missing rules. From such requirements, service specifications are obtained by using hypothesis-based reasoning on input requirements and existing service specifications. When existing specifications cannot be used to obtain complementary specifications, a communications service model is used to propose new rules. The proposed methods are implemented as a part of a communications software development system. The system enables non-experts in communications systems to define their own service specifications.

A system based on application of Fuzzy Cognitive Map (FCM) to perform on-line fault diagnosis is presented. The diagnostic part of the system is composed of two diagnostic schemes. The first one (basic diagnostic algorithm) can be considered as a simple transition of Shiozaki's signed directed graph approach to FCM framework. The second one is an extended version of the basic diagnostic algorithm where an important concept, the temporal associative memories (TAM) recall of FCM, is adopted. In on-line application, self-generated fault FCM model generates predicted pattern sequence through the TAM recall process, which is compared with observed pattern sequence to declare the origin of fault. As the resultant diagnosis scheme takes short computation time, it can be used for on-line fault diagnosis of large and complex processes, and even for incipient fault diagnosis. In practical case, since real observed pattern sequence may be different from predicted one through the TAM recall owing to propagation delay between process variables, the time indexed fault FCM model incorporating delay time is proposed. The utility of the proposed system is illustrated in fault diagnosis of a tank-pipe system.

Information systems to support cooperative work among people should be first designed to help humam communication. However, there are few systems based on the analysis of human communication. Standing on this situation, we propose a meeting support system for the participants' understandings by indicating the suitable information about the topic of the scene". Our system provides only useful information by monitoring each statement without complex methods. To show something useful multi-media information for members, we propose the following structure of the meeting on the basis of the analysis of communication. Each statement is classified into two levels, either; a statement about the progress" of the meeting (context-level utterances) or, a statement about objects" (content-level utterances). Further, content-level utterances are classified into two types, position utterances and argument utterances. Using this classification of statements, the proceeding of the meeting is represented as the tree model which is called a context-tree". If the structure of meetings is fixed, it is possible to select only useful information from all shared information for members by analyzing each content-level utterance. The system introduced in this paper shows appropriate multi-media information about the topic of the scene" by using the above model. We have implemented a prototype system based on the above ideas. Moreover, we have mode some experiments to show the effectiveness of this system. Those results show that our method is effective to improve the productivity" of meetings.

This letter presents a new method to efficiently extract closed loops as primitive symbols in line drawings. Our method uses a graph search technique for efficiency and exhaustibility, and also incorporates feasibility criteria of symbols. Experiments clearly demonstrated the method's effectiveness.

Graph unification is doubtlessly the most expensive process in unification-based grammar parsing since it takes the vast majority of the total parsing time of natural language sentences. A parsing time overload in unification consists in that, in general, no less than 60% of the graph unifications performed actually fail. Thus one way to achieve unification time speed-up is focusing on an efficient, fast way to deal with such unification failures. In this paper, a process, prior to unification itself, capable of filtering or stopping a considerably high percentage of graphs that would fail unification is proposed. This unification-filtering process consists of comparison of signatures that correspond to each one of the graphs to be unified. Unification-filter (hereafter UF) is capable of stopping around 87% of the non-unifiable graphs before unification itself takes place. UF takes significantly less time to detect graphs that do not unify and discard them than it would take to unification to fail the attempt to unify the same graphs. As a result of using UF, unification is performed in an around 71% of the time for the fastest known unification algorithm.

This paper gives a model to explain one phenomenon found in the process of creative concept formation, i.e. the phenomenon that people often get trapped in some state where the mental world remains nebulous and sometimes suddenly make a jump to a new concept. This phenomenon has been qualitatively explained mainly by the philosophers but there have not been models for explaining it quantitatively. Such model is necessary in a new research field to study the systems for aiding human creative activities. So far, the work on creation aid has not had theoretical background and the systems have been built based only on trial and error. The model given in this paper explains some aspects of the phenomena found in creative activities and give some suggestions for the future systems for aiding creative concept formation.

This paper describes a new algorithm for finding the contours of a moving object in an image sequence. A distinctive feature of this algorithm is its complete bottom-up strategy from image data to a consistent contour description. In our algorithm, an input image sequence is immediately converted to a complete set of quasi logical spatio-temporal measures on each pixel, which provide constraints on varying brightness. Then, candidate regions in which to localize the contour are bounded based on consistent grouping among neighboring measures. This reduces drastically the ambiguity of contour location. Finally, Some mid-level constraints on spatial and temporal smoothness of moving boundaries are invoked, and they are combined with these low-level measures in the candidate regions. This is performed efficiently by the regularization over the restricted trajectory of the moving boundary in the candidate regions. Since any quantity is dimensionless, the results are not affected by varying conditions of camera and objects. We examine the efficiency of this algorithm through several experiments on real NTSC motion pictures with dynamic background and natulal textures.

In the PICASSO, a system for the facial caricature generation, as the basic mechanisms to extract the individuality features of faces and to deform the features have been already introduced, it is expected to realize an autonomous mechanism to evaluate facial caricatures. The evaluation should be based on the framework of human visual cognition. In the PICASSO, some visual illusions such as the Wundt-Fick illusion and the Ponzo illusion for example, are applied to evaluate the shapes of the facial parts such as eyebrows, nose, mouth and face contour, in the deformation process. In many cases, as well-deformed caricatures are evaluated to be successful, it is confirmed that the utilization of the visual illusion is effective to evaluate the results of caricatures. In this paper, some experimental results are presented together with the definition of the evaluation measures and the further subjects.

In the approximate learning model introduced by Valiant, it has been shown by Blumer et al. that an Occam algorithm is immediately a PAC-learning algorithm. An Occam algorithm is a polynomial time algorithm that produces, for any sequence of examples, a simple hypothesis consistent with the examples. So an Occam algorithm is thought of as a procedure that compresses information in the examples. Weakening the compressing ability of Occam algorithms, a notion of weak Occam algorithms is introduced and the relationship between weak Occam algorithms and PAC-learning algorithms is investigated. It is shown that although a weak Occam algorithm is immediately a (probably) consistent PAC-learning algorithm, the converse does not hold. On the other hand, we show how to construct a weak Occam algorithm from a PAC-learning algorithm under some natural conditions. This result implies the equivalence between the existence of a weak Occam algorithm and that of a PAC-learning algorithm. Since the weak Occam algorithms constructed from PAC-learning algorithms are deterministic, our result improves a result of Board and Pitt's that the existence of a PAC-learning algorithm is equivalent to that of a randomized Occam algorithm.

The meaning of analogical reasoning in locally stratified logic programs are described by generalized stable model (GSM) semantics. Although studies on the theoretical aspects of analogical reasoning have recently been on the increase, there have been few attempts to give declarative semantics for analogical reasoning. This paper takes notice of the fact that GSM semantics gives meaning to the effect that the negated predicates represent exceptional cases. We define predicates that denote unusual cases regarding analogical reasoning; for example, ab(x)p(x)g(x), where p(s), q(s), p(t) are given. We also add rules with negated occurrences of such predicates into the original program. In this way, analogical models for original programs are given in the form of GSMs of extended programs. A proof procedure for this semantics is presented. The main objective of this paper is not to construct a practical analogical reasoning system, but rather to present a framework for analyzing characteristics of analogical reasoning.