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Cognitive Informatics & Cognitive Computing (ICCI*CC), 2012 IEEE 11th International Conference on

Date 22-24 Aug. 2012

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Displaying Results 1 - 25 of 88
  • The Ersatz Brain Project: A brain-like computer architecture for cognition

    Page(s): 1
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (142 KB) |  | HTML iconHTML  

    The Ersatz Brain Project is an attempt to develop programming techniques and software applications for a brain-like computing system. Its brain-like hardware architecture design is based on a select set of ideas taken from the anatomy of mammalian neo-cortex. In common with other such attempts it is based on a massively parallel, two-dimensional array of CPUs and their associated memory. The design used in this project (1) uses an approximation to cortical computation called the network of networks which holds that the basic computing unit in the cortex is not a single neuron but groups of neurons working together in attractor networks; (2) assumes connections and data representations in cortex are sparse; (3) makes extensive use of local lateral connections and topographic data representations, and (4) scales in a natural way from small groups of neurons to the involvement of entire cortical regions. View full abstract»

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  • Textual affect sensing and affective communication

    Page(s): 2 - 3
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (66 KB) |  | HTML iconHTML  

    In addition to semantic content, affect conveyed by text plays an important role for rich and friendly communication. This is particularly true in human communication. In recent days, the percentage of human-computer and computer-mediated communications is increasing in our life. In this situation, a computer is expected to understand the affects or emotions included in text. We have been working on this problem, i.e., textual affect sensing, for some years. As a related topic, textual sentiment analysis has been studied, where positive and negative sentences are typically extracted for Web opinion mining with respect to a specific issue or product. While the distinction between affect sensing and sentiment analysis is not necessarily clear in this field, I call here sentiment analysis when a sentence is classified into positive, negative or neutral one. Unlike this sort of sentiment analysis, our textual affect sensing detects more detailed affective or emotional states appearing in text, such as happy, sad, anger, fear, disgust, surprise and much more. We basically have developed the following two such models or systems so far: (A) The first one detects nine emotions using a set of rules implemented on the basis of a compositionality principle proposed for textual affect interpretation. This process includes symbolic cue processing, detection and transformation of abbreviations, sentence parsing, and word/phrase/sentence-level analyses. (B) The second one challenged to recognize 22 emotion types defined in the OCC (Ortony, Clore & Collins) emotion model, which is the most comprehensive emotion model and employs several cognitive variables including one relating to valenced reactions of events or agents. In this research, we have shown how these cognitive variables of the emotion model can be computed from linguistic components in text. View full abstract»

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  • Augmenting conversational environment

    Page(s): 4
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (69 KB)  

    People are very proficient in collaboratively forming and maintaining gatherings thereby shaping and cultivating collective thoughts through fluent interactions. A big challenge is to develop a technology for augmenting the conversational environment so that people can conduct even better conversational interactions for collective intelligence and creation. Conversational informatics is a field of research that focuses on investigating conversational interactions and designing artifacts that can interact with people in a conversational fashion. The field draws on a foundation provided by artificial intelligence, natural language processing, speech and image processing, cognitive science, and conversation analysis. In this article, I will discuss the opportunity and challenges in an engineering approach to conversational informatics. I will focus on an immersive interaction environment that not only serves as an augmented environment for conversation but also allows us to synthesize conversational artifacts. I also discuss issues for making agents empathic so that they can induce sustained and constructive engagement with people. View full abstract»

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  • On abstract intelligence and brain informatics: Mapping the cognitive functions onto the neural architectures

    Page(s): 5 - 6
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (103 KB) |  | HTML iconHTML  

    Summary form only given. A fundamental challenge for almost all scientific disciplines is to explain how natural intelligence is generated by physiological organs and what the logical model of the brain is beyond its neural architectures. According to cognitive informatics and abstract intelligence, the exploration of the brain is a complicated recursive problem where contemporary denotational mathematics is needed to efficiently deal with it. Cognitive psychology and medical science are used to explain that the brain works in a certain way based on empirical observations of corresponding activities in usually overlapped brain areas. However, the lack of precise models and rigorous causality in brain studies has dissatisfied the formal expectations of researchers in computational science and mathematics, because a computer, the logical counterpart of the brain, might not be explained in such a vigor and empirical approach without the support of a formal model and a rigorous means. In order to formally explain the architectures and functions of the brain, as well as their intricate relations and interactions, systematic models of the brain are sought for revealing the principles and mechanisms of the brain at the neural, physiological, cognitive, and logical (abstract) levels. Cognitive and brain informatics investigate into the brain via not only inductive syntheses through these four cognitive levels from the bottom up in order to form theories based on empirical observations, but also deductive analyses from the top down in order to explain various functional and behavioral instances according to the abstract intelligence theory. This keynote lecture presents systematic models of the brain from the facets of cognitive informatics, abstract intelligence, brain Informatics, neuroinformatics and cognitive psychology. A logical model of the brain is introduced that maps the cognitive functions of the brain onto its neural and physiological architectures. This work le- ds to a coherent abstract intelligence theory based on both denotational mathematical models and cognitive psychology observations, which rigorously explains the underpinning principles and mechanisms of the brain. On the basis of the abstract intelligence theories and the logical models of the brain, a comprehensive set of cognitive behaviors as identified in the Layered Reference Model of the Brain (LRMB) such as perception, inference and learning can be rigorously explained and simulated.The logical model of the brain and the abstract intelligence theory of the natural intelligence will enable the development of cognitive computers that perceive, think and learn. The functional and theoretical difference between cognitive computers and classic computers are that the latter are data processors based on Boolean algebra and its logical counterparts; while the former are knowledge processors based on contemporary denotational mathematics. A wide range of applications of the cognitive computers have been developing in ICIC and my laboratory such as , inter alia, cognitive robots, cognitive learning engines, cognitive Internet, cognitive agents, cognitive search engines, cognitive translators, cognitive control systems, and cognitive automobiles. View full abstract»

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  • On formal models for cognitive linguistics

    Page(s): 7 - 17
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (257 KB) |  | HTML iconHTML  

    Cognitive linguistics is an emerging discipline that studies the cognitive properties of natural languages and the cognitive models of languages in computational linguistics, cognitive computing, and computational intelligence. This paper presents the theoretical framework of cognitive linguistics in order to systematically formalize the syntaxes and grammars of natural languages. An abstract language model of cognitive linguistics is created at the top level. Based on it, the cognitive structures of languages at the levels of lexis, phrase, clauses, sentence, paragraph, and essay are formally modeled from the bottom up. Using contemporary denotational mathematics, the deductive grammar of English is formally modeled and rigorously analyzed. The basic research provides support for a wide range of applications in computational linguistics, cognitive informatics, online text processing, web search engines, machine language comprehension, autonomous machine learning, smart cell phones, semantic computing, and computing with words. View full abstract»

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  • BRINK: Initial theory on bounded rationality and inconsistent knowledge

    Page(s): 18 - 26
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (381 KB) |  | HTML iconHTML  

    The theory of bounded rationality takes into consideration the cognitive limitations of decision makers in accomplishing their goals and emphasizes on satisficing behaviors when searching for solutions. One of the hallmarks of rational behaviors in decision-making process is embodied in how to cope with inconsistency. Building cognitive computing systems for real world applications amounts to developing systems that possess bounded rationality. In this paper, we examine how bounded rationality is exhibited in the human cognitive capabilities in handling inconsistency and propose an initial theory on how to incorporate those capabilities into cognitive computing systems. In particular, we focus our attention on two important phenomena: rational-but-inconsistent circumstances, and irrational-but-consistent circumstances. The main contribution of the work lies in the fact that we shed some new light on the interplay between bounded rationality and inconsistency. View full abstract»

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  • Denotatum-based models of knowledge creation for monitoring and evaluating R&D program implementation

    Page(s): 27 - 34
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (267 KB) |  | HTML iconHTML  

    The paper presents two semiotic models for a description of development stages of indicators, including generation microprocesses of expert knowledge about developed indicators. For the description of stages of these microprocesses, a new notion of “Frege's space” is introduced. A related example is an application of two semiotic models to knowledge acquisition for an expert knowledge base named the proactive dictionary, which is a component of an evaluation system. This dictionary enables experts to fix stages of indicators development, to present the results of developing different variants of indicators in graphic form, to compare and evaluate these variants. View full abstract»

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  • A proposed model for visual memory identification

    Page(s): 35 - 42
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (422 KB) |  | HTML iconHTML  

    Memory is an important process of human behaviour. In particular visual memory the brain to encode, store, and retrieve acquired knowledge about the environment. The visual memory system involves different kinds of processes, such as sensory input and short-term visual memory. The model presents a first approach for visual memory recognition that supports the three stages mentioned above. The model design is based on neuroscience results. This document presents only the memory system specifications that support a cognitive architecture for visual object identification. We validated the model with two case studies: known and unknown stimulus. View full abstract»

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  • Multimodal Cancelable Biometrics

    Page(s): 43 - 49
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (513 KB) |  | HTML iconHTML  

    Multimodal biometric systems have emerged as highly successful new approach to combat problems of unimodal biometric system such as intraclass variability, interclass similarity, data quality, non-universality, and sensitivity to noise. However, one major issue pertinent to unimodal system remains. It has to do with actual biometric characteristics of users being permanent, and their number being limited. Thus, if user's biometric is compromised, it might be impossible or highly difficult to replace it in a particular system. Cancellable biometric for individual biometric has been a significantly understudied problem. The concept of cancelable biometric or cancelability is to transform a biometric data or feature into a new one so that users can change their single biometric template in a biometric security system. However, cancelability in multimodal biometric has been barely addressed at all. In this paper, we tackle the problem and present a novel solution for cancelable biometrics in multimodal system. We develop a new cancelable biometric template generation algorithm using random projection and transformation-based feature extraction and selection. Performance of the proposed algorithm is validated on multi-modal face and ear database. View full abstract»

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  • A collaborative pointing experiment for analyzing bodily communication in a virtual immersive environment

    Page(s): 50 - 57
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (185 KB) |  | HTML iconHTML  

    Virtual environments are a medium in which humans can effectively interact with each other, however up until recently research on body expression in these worlds has been sparse. This has changed with the recent development of markerless motion capture. This paper is a first step towards using these technologies as part of an investigation into a collaborative task in the virtual world. In this task, participants used a pointing gesture as a means to both complete the task and communicate with their partner. The results gained from the experiment were inconclusive, but did show that the effectiveness of the experiment depends largely on the algorithm used to detect gesture and thereby influence the virtual world. It is intended that this research be used to show the potential of examining body expression in collaborative virtual environments. View full abstract»

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  • Forecasting river runoff through Support Vector Machines

    Page(s): 58 - 64
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (265 KB) |  | HTML iconHTML  

    How “wet” or “dry” a year is predicted to be has many impacts. Public utilities need to determine what percentage of their electric energy generation will be hydro power. Good water years enable the utilities to use more hydro power and, consequently, save oil. Conversely, in a dry year, the utilities must depend more on steam generation and therefore use more oil, coal, and atomic fuel. Agricultural interests use the information to determine crop planting patterns, ground water pumping needs, and irrigation schedules. Operators of flood control projects determine how much water can safely be stored in a reservoir while reserving space for predicted inflows. Municipalities use the information to evaluate their water supply and determine whether (in a dry year) water rationing may be needed. Currently a combination of linear regression equations and human judgment is used for producing these forecasts. In this paper, we describe a Support Vector Machine based method for river runoff forecasting. Our method uses Smola/Scholkopf's Sequential Minimal Optimization algorithm for training a Support Vector Machine with a RBF kernel. The experimental results on predicting the full natural flow of the American River at the Folsom Dam measurement station in California indicates that our method outperforms the current forecasting practices. View full abstract»

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  • A scheduling method in semiconductor manufacturing lines based on ant colony optimization

    Page(s): 65 - 69
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (205 KB) |  | HTML iconHTML  

    As is well known, the semiconductor manufacturing is one of the most complicated manufacturing processes. It can be considered as a Job shop Scheduling Problem(JSP), which is classified NP-complete problem. In this kind of problem, the combination of goals and resources can exponential increase the complexity, because a much larger searching space and more constrains exist among tasks. Ant colony optimization, as an effective meat-heuristic technique, can be adopted to find a optimized solution. In this paper, the scheduling problem of semiconductor manufacturing lines is solved by adopting ant colony optimization. The result shows that ACO performs better than some other well known algorithms and the problem can be well solved by ACO. View full abstract»

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  • Wireless brain signal acquisition circuits for body sensor network

    Page(s): 70 - 77
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (611 KB) |  | HTML iconHTML  

    The paper presents the proposed wireless brain signal acquisition circuits for body sensor network. Considering the power-efficient communication in the body sensor network, the required low-power analog integrated circuits (ICs) are developed for a wireless brain signal acquisition system. To acquire the electroencephalogram (EEG) signal, this paper proposes an analog front-end (AFE) circuit, including only one low-noise amplifier with chopping techniques and one high-pass sigma-delta modulator (HPSDM), which can be applied as a sensing circuit for EEG signal acquisition systems. To transmit the EEG signal through wireless communication, a quadrature CMOS voltage-controlled oscillator and a 2.4 GHz direct-conversion transmitter with a power amplifier and up-conversion mixer are also developed. In the receiver, a 2.4 GHz fully integrated CMOS radio-frequency front-end is also implemented. The circuits have been implemented to fit the specifications of the IEEE 802.15.4 2.4 GHz standard. The low-power ICs of the wireless EEG acquisition systems have been fabricated using a 0.18 μm TSMC CMOS standard process. The measured results reveal that the proposed low-power analog front-end ICs can be used for the wireless brain signal acquisition. View full abstract»

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  • Security testing of a modular cryptosystem based on continuous cellular automata

    Page(s): 78 - 85
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (494 KB) |  | HTML iconHTML  

    This paper presents specially designed tests performed in a cryptosystem based on chaotic continuous cellular automata (CCA). The degree of the cryptosystem security is evaluated by taking two approaches: (i) stationarity and (ii) spectral fractal dimension. These tools are verified with known signals before applying them to test the cryptosystem. This paper provides groundbreaking research about a robust method to determine the minimum stationary window in a given time series. This new ideas is relevant because the stationarity of a signal can be rapidly determined. This idea has never been done in the past, at least in the reported literature, outside this research group. View full abstract»

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  • Comparing similarity of concepts identified by temporal patterns of terms in biomedical research documents

    Page(s): 86 - 93
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    In this paper, we present an analysis of a relationship between temporal trends of automatically extracted terms in medical research document and their similarities on a structured vocabulary. In order to obtain the temporal trends, we used our temporal pattern extraction method that combines an automatic term extraction, an importance index of the terms, and clustering for the values in each period. By using a set of medical research documents that were published every year, we extracted temporal patterns of the automatically extracted terms. Then, we calculated their similarities on the medical taxonomy by defining a distance on the tree structure. For analyzing the relationship between the terms included in the patterns and the similarity of the terms on the taxonomy, the differences of the averaged similarities of the terms in each pattern are compared between the two trends of the temporal patterns. View full abstract»

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  • A formal measurement of the cognitive complexity of texts in cognitive linguistics

    Page(s): 94 - 102
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    The cognitive complexity of texts in natural languages is a fundamental measure of the properties of syntax and semantics in textual comprehension, processing, and search. This paper presents a formal metrics of text comprehension complexity in cognitive linguistics. Both objective and subjective aspects of text comprehension and their complexity are formally modeled. A formal language model is established that characterizes the discourse of natural languages. The mathematical models of cognitive complexity of texts and their comprehension are rigorously described. On the basis of the cognitive and mathematical models of cognitive linguistics, the measurement of cognitive complexity of texts is quantitatively established and tested by a set of case studies. A wide range of applications of the measurement of textual complexity are identified in cognitive linguistics and contemporary web technologies such as search engines, online document retrieval, natural language processing, cognitive linguistics, cognitive computing, cognitive machine learning, and computing with words. View full abstract»

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  • A kind of web service recommendation method based on improved hybrid collaborative filtering

    Page(s): 103 - 108
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (221 KB) |  | HTML iconHTML  

    Similar to product recommendation used in e-commerce sites and other fields, the recommendation of web service often take advantage of the history invocation information of users and services (denotes as QoS, Quality of service) to predict the unknown QoS value and then recommend web services to the active user with the best QoS. In order to adapt to the complex and changeful prediction occasions of QoS value of web service, this paper presents a hybrid collaborative filtering approach for the recommendation of web service by combining user-based collaborative filtering algorithm (UBCF) and item-based collaborative filtering algorithm(IBCF). This hybrid method consider the personalization of invocation information of users and services in the net while using Pearson Correlation Coefficient (PCC) to measure the similarity of two users or two services and adaptively balance the weigh of UBCF and IBCF while recommending services to the active user. Finally, though the experimental data provided by [12], we conduct a set of experiments and the results show that our proposed improved hybrid collaborative filtering algorithm had improved the accuracy of recommendation. View full abstract»

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  • Towards modeling question popularity in community question answering

    Page(s): 109 - 114
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    Community question answering (QA) has become increasingly popular and received a great variety of questions every day. Among them, some questions are very attractive and popular to many users, while some other questions are very tedious and unattractive. In this paper, we aim to identify popular questions in the community QA through modeling question popularity. Three popularity-related features of questions are defined to build the popularity model: (a) potential hits, which reflect how many users are attracted by a question at their first glance; (b) popular terms, from which users find a question attractive; and (c) tedious unpopular terms. The notable characteristic of the proposed framework is extensibility and more features can be incorporated. A large-scale question dataset from a practical community QA website was used to train and test the model. Meanwhile, two well-known classifiers, k-nearest neighbors and support vector machines, were implemented for comparison. Our approach is well validated by the experimental results with much higher prediction accuracy than the baseline methods. View full abstract»

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  • An intelligent digital colour image watermarking approach based on wavelets and general regression neural networks

    Page(s): 115 - 123
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (742 KB) |  | HTML iconHTML  

    In this paper, we propose a new intelligent, robust and adaptive digital watermarking technique for colour images based on the combination of discrete wavelet transform (DWT), human visual system (HVS) model and general regression neural network (GRNN). First, the RGB image is converted to YCrCb image, and then the luminance component Y is decomposed by DWT. Wavelet coefficients are then analyzed by a HVS model to select suitable coefficients for embedding the watermark. The watermark bits are embedded into the selected coefficients by training a GRNN. At the decoder, the trained GRNN is used to recover the watermark from the watermarked image. The experimental results show that our proposed approach achieves robustness and imperceptibility in watermarking. View full abstract»

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  • A rule based approach for Japanese-Uighur machine translation system

    Page(s): 124 - 129
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    Japanese Uighur machine translation system has been designed and developed using recent rule based approach. However, translate result shows that as a matter of course, the fact that Japanese and Uighur are different languages does not allow us to apply the word-for-word translation in a straightforward way. Even though Japanese and Uighur language has many similarities, but there are also some linguistic differences cause serious problems to the word for word translation. In fact, as straightforward word-for-word Japanese-Uighur translation sometimes yields unnatural Uighur sentences. To raise the translation accuracy, we propose a word-for-word translation system using subject verb agreement in Uighur. After a brief introduction to the comparative study of Japanese-Uyghur grammars, morphology and syntax, we explain our developing of a word to word rule base system. The coverage of this rule base system and the rules for translation are explained. Some practical suffix translation methods solving problems in Uighur language are also proposed. View full abstract»

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  • An empirical study on pertinent aspects of sketch maps for navigation

    Page(s): 130 - 139
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (394 KB) |  | HTML iconHTML  

    Navigation systems which employ sequence-based directions have been found not effective in facilitating the spatial awareness of an environment. Traditional maps are found easily conveying the configuration of spatial objects but having difficulty to facilitate the correspondence to spatial objects in the real world. Sketch maps as schematic map-like representations, have been suggested being a possible way of achieving goals of facilitating both navigation and spatial awareness. Moreover, sketch maps as externalizations of cognitive maps have been proved as reliable representations for human spatial thinking. In this study, we investigate the characteristics of directions given in two different forms: sketch maps and turn-by-turn instructions (verbal descriptions). The investigation addresses three aspects of spatial relations which are orientation, street topology and sequential order and their representations using qualitative reasoning calculi. The results of this study demonstrate sketch maps as a better direction-giving method and provide insights of applying sketch-map-like components for navigation. View full abstract»

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  • Path planning for unmanned aerial vehicle based on genetic algorithm

    Page(s): 140 - 144
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (284 KB) |  | HTML iconHTML  

    Path planning has always been a crucial issue for UAV. The UAVs path planning in multiple missions involves the solution of an optimization problem. Genetic algorithms (GAs) are well applied to solve such problems as a stochastic search method. In this paper, a new method based on genetic algorithm is presented to generate path for UAV in the existence of unknown obstacle environments. The path planning model is based on 2D digital map, and an adaptive evolutionary planner is adopted based on a set of criteria to generate path online to avoid being detected by ground surveillance radar sites. Simulation studies are carried out to verify the effectiveness of the proposed algorithm. We believe the GA algorithm may be of help in the future reseach direction of UAV path planning problem. View full abstract»

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  • Exploratory temporal data mining process in hospital information systems

    Page(s): 145 - 152
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (240 KB) |  | HTML iconHTML  

    This paper proposes an exploratory temporal data mining process which aims at capturing behavior of medical staff. The process consists of the following four process. First, datasets will be extracted from hospital information systems through double-step datawarehousing. Second, similarities between temporal sequences are calculated from datasets. Third, data mining methods such as clustering, multidimensional scaling are applied for obtaining the class labels. Finally, other data mining methods, such as decision tree and correspondence analysis are applied to original data sets with the class labels. View full abstract»

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  • Comparing people's preference on culture-dependent queuing behaviors in a simulated crowd

    Page(s): 153 - 162
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (400 KB) |  | HTML iconHTML  

    Difficulties in living in a different culture are caused by different patterns of thinking, feeling and potential actions. People who enter into a new culture or unfamiliar social situation don't know how to behave toward other people. Queuing is a good example behavior of intercultural interaction in a human crowd. This research aims to develop a system that can help users learn a different culture of nonverbal interaction using a simulated crowd. Users can learn how to engage in interaction or imitate queuing behavior in different styles from a simulated human crowd. The human recognition and body interaction section describe the hypothesis of participants' acceptance and feedback. The video and interactive-game environment are discussed and the setting example scenario are shown. The comparative discussion shows the interactive-game is cover the participants' acceptant and feedback. The queuing behavior coding is designed from the posture scoring system. An immersive environment is used for 360 degrees viewing. Learners can observe the agents' behavior in the scenario via immersive display and can interact with the agents by using their body. The FAtiMA emotion agent architecture is applied in the agent's behavioral interaction planning. Preliminary work is shown. The result is a variety of styles of the formation of queuing behavior of people from different cultures. View full abstract»

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  • Investigation of potency-magnitude relations of eWOM messages with a focus on intensified comparative expressions

    Page(s): 163 - 173
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (334 KB) |  | HTML iconHTML  

    Electronic word-of-mouth (eWOM) is an important information source that influences consumer product evaluations. The author previously developed a computational model that predicts the potency-magnitude relations of eWOM messages involving subjective rank expressions, which refer to the linguistic representations related to the attitude-levels of the benefits of product attributes. This paper extends the typology of eWOM messages and investigates mathematically potency-magnitude relations with a focus on intensified comparative expressions, which involve the “degree” of the differences between two or more objects. The investigations include the developments of a Q-magnitude Relation Map (Q-Map) and a Priority Message-Class Map (P-Map), which illustrate how the relations change based on the values of two evaluation parameters: evaluation target size and evaluation scale size. The effects of the messages involving intensified comparative expressions are discussed from the viewpoint of eWOM message filtering agents that promote consumer product evaluations. The investigations were performed first under the premise of a strict assumption called an interval assumption and the results were then verified and discussed under the premise of a conservative assumption called a surjection assumption. View full abstract»

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