Search results for: multi-agent reasoning

Authors: Apkar Salatian

Abstract:

To relieve the burden of reasoning on a point to point basis, in many domains there is a need to reduce large and noisy data sets into trends for qualitative reasoning. In this paper we propose and describe a new architectural design pattern called REDUCER for reducing large and noisy data sets that can be tailored for particular situations. REDUCER consists of 2 consecutive processes: Filter which takes the original data and removes outliers, inconsistencies or noise; and Compression which takes the filtered data and derives trends in the data. In this seminal article we also show how REDUCER has successfully been applied to 3 different case studies.

Keywords: Design Pattern, filtering, compression.

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Authors: Chung-Seong Hong, Hyung-Sun Kim, Joonmyun Cho, Hyun Kyu Cho, Hyun-Chan Lee

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To realize the vision of ubiquitous computing, it is important to develop a context-aware infrastructure which can help ubiquitous agents, services, and devices become aware of their contexts because such computational entities need to adapt themselves to changing situations. A context-aware infrastructure manages the context model representing contextual information and provides appropriate information. In this paper, we introduce Context-Aware Middleware for URC System (hereafter CAMUS) as a context-aware infrastructure for a network-based intelligent robot system and discuss the ontology-based context modeling and reasoning approach which is used in that infrastructure.

Keywords: CAMUS, Context-Aware, Context Model, Ontology.

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Authors: Zbigniew Les, Magdalena Les

Abstract:

Intelligence tests are series of tasks designed to measure the capacity to make abstractions, to learn, and to deal with novel situations. Testing of the visual abilities of the shape understanding system (SUS) is performed based on the visual intelligence tests. In this paper the progressive matrices tests are formulated as tasks given to SUS. These tests require good visual problem solving abilities of the human subject. SUS solves these tests by performing complex visual reasoning transforming the visual forms (tests) into the string forms. The experiment proved that the proposed method, which is part of the SUS visual understanding abilities, can solve a test that is very difficult for human subject.

Keywords: Shape understanding, intelligence test, visual concept, visual reasoning.

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Authors: M. Rodionov, Z. Dedovets

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This article discusses plausible reasoning use for solution to practical problems. Such reasoning is the major driver of motivation and implementation of mathematical, scientific and educational research activity. A general, practical problem solving algorithm is presented which includes an analysis of specific problem content to build, solve and interpret the underlying mathematical model. The author explores the role of practical problems such as the stimulation of students' interest, the development of their world outlook and their orientation in the modern world at the different stages of learning mathematics in secondary school. Particular attention is paid to the characteristics of those problems which were systematized and presented in the conclusions.

Keywords: Mathematics, motivation, secondary school, student, practical problem.

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Authors: O. Matarazzo, L. Abbamonte, G. Nigro

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This study aimed at assessing whether and to what extent moral judgment and behaviour were: 1. situation-dependent; 2. selectively dependent on cognitive and affective components; 3. influenced by gender and age; 4. reciprocally congruent. In order to achieve these aims, four different types of moral dilemmas were construed and five types of thinking were presented for each of them – representing five possible ways to evaluate the situation. The judgment criteria included selfishness, altruism, sense of justice, and the conflict between selfishness and the two moral issues. The participants were 250 unpaid volunteers (50% male; 50% female) belonging to two age-groups: young people and adults. The study entailed a 2 (gender) x 2 (age-group) x 5 (type of thinking) x 4 (situation) mixed design: the first two variables were betweensubjects, the others were within-subjects. Results have shown that: 1. moral judgment and behaviour are at least partially affected by the type of situations and by interpersonal variables such as gender and age; 2. moral reasoning depends in a similar manner on cognitive and affective factors; 3. there is not a gender polarity between the ethic of justice and the ethic of cure/ altruism; 4. moral reasoning and behavior are perceived as reciprocally congruent even though their congruence decreases with a more objective assessment. Such results were discussed in the light of contrasting theories on morality.

Keywords: Contextual-pragmatic approach to morality, ethic ofcare, ethic of justice, Kohlbergian approach, moral behaviour, moralreasoning.

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Authors: J.L. Castro, K. Benghazi, M.V. Hurtado, M. Navarro, J.M. Zurita

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Nowadays, quick technological changes force companies to develop innovative products in an increasingly competitive environment. Therefore, how to enhance the time of new product development is very important. This design problem often lacks the exact formula for getting it, and highly depends upon human designers- past experiences. For these reasons, in this work, a Casebased reasoning (CBR) system to assist in new product development is proposed. When a case is recovered from the case base, the system will take into account not only the attribute-s specific value and how important it is. It will also take into account if the attribute has a positive influence over the product development. Hence the manufacturing time will be improved. This information will be introduced as a new concept called “adaptability". An application to this method for hearing instrument new design illustrates the proposed approach.

Keywords: Case based reasoning, Fuzzy logic, New product development, Retrieval stage, Similarity.

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Authors: Sagir M. Yusuf, Chris Baber

Abstract:

In this paper, we describe how Bayesian inferential reasoning will contributes in obtaining a well-satisfied prediction for Distributed Constraint Optimization Problems (DCOPs) with uncertainties. We also demonstrate how DCOPs could be merged to multi-agent knowledge understand and prediction (i.e. Situation Awareness). The DCOPs functions were merged with Bayesian Belief Network (BBN) in the form of situation, awareness, and utility nodes. We describe how the uncertainties can be represented to the BBN and make an effective prediction using the expectation-maximization algorithm or conjugate gradient descent algorithm. The idea of variable prediction using Bayesian inference may reduce the number of variables in agents’ sampling domain and also allow missing variables estimations. Experiment results proved that the BBN perform compelling predictions with samples containing uncertainties than the perfect samples. That is, Bayesian inference can help in handling uncertainties and dynamism of DCOPs, which is the current issue in the DCOPs community. We show how Bayesian inference could be formalized with Distributed Situation Awareness (DSA) using uncertain and missing agents’ data. The whole framework was tested on multi-UAV mission for forest fire searching. Future work focuses on augmenting existing architecture to deal with dynamic DCOPs algorithms and multi-agent information merging.

Keywords: DCOP, multi-agent reasoning, Bayesian reasoning, swarm intelligence.

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Authors: Sagir M. Yusuf, Chris Baber

Abstract:

In this paper, we describe how to achieve knowledge understanding and prediction (Situation Awareness (SA)) for multiple-agents conducting searching activity using Bayesian inferential reasoning and learning. Bayesian Belief Network was used to monitor agents' knowledge about their environment, and cases are recorded for the network training using expectation-maximisation or gradient descent algorithm. The well trained network will be used for decision making and environmental situation prediction. Forest fire searching by multiple UAVs was the use case. UAVs are tasked to explore a forest and find a fire for urgent actions by the fire wardens. The paper focused on two problems: (i) effective agents’ path planning strategy and (ii) knowledge understanding and prediction (SA). The path planning problem by inspiring animal mode of foraging using Lévy distribution augmented with Bayesian reasoning was fully described in this paper. Results proof that the Lévy flight strategy performs better than the previous fixed-pattern (e.g., parallel sweeps) approaches in terms of energy and time utilisation. We also introduced a waypoint assessment strategy called k-previous waypoints assessment. It improves the performance of the ordinary levy flight by saving agent’s resources and mission time through redundant search avoidance. The agents (UAVs) are to report their mission knowledge at the central server for interpretation and prediction purposes. Bayesian reasoning and learning were used for the SA and results proof effectiveness in different environments scenario in terms of prediction and effective knowledge representation. The prediction accuracy was measured using learning error rate, logarithm loss, and Brier score and the result proves that little agents mission that can be used for prediction within the same or different environment. Finally, we described a situation-based knowledge visualization and prediction technique for heterogeneous multi-UAV mission. While this paper proves linkage of Bayesian reasoning and learning with SA and effective searching strategy, future works is focusing on simplifying the architecture.

Keywords: Lèvy flight, situation awareness, multi-agent system, multi-robot coordination, autonomous system, swarm intelligence.

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Authors: Tamanna Siddiqui, M. Afshar Alam

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Censored Production Rule is an extension of standard production rule, which is concerned with problems of reasoning with incomplete information, subject to resource constraints and problem of reasoning efficiently with exceptions. A CPR has a form: IF A (Condition) THEN B (Action) UNLESS C (Censor), Where C is the exception condition. Fuzzy CPR are obtained by augmenting ordinary fuzzy production rule “If X is A then Y is B with an exception condition and are written in the form “If X is A then Y is B Unless Z is C. Such rules are employed in situation in which the fuzzy conditional statement “If X is A then Y is B" holds frequently and the exception condition “Z is C" holds rarely. Thus “If X is A then Y is B" part of the fuzzy CPR express important information while the unless part acts only as a switch that changes the polarity of “Y is B" to “Y is not B" when the assertion “Z is C" holds. The proposed approach is an attempt to discover fuzzy censored production rules from set of discovered fuzzy if then rules in the form: A(X) ÔçÆ B(Y) || C(Z).

Keywords: Uncertainty Quantification, Fuzzy if then rules, Fuzzy Censored Production Rules, Learning algorithm.

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Authors: Berardina De Carolis, Giovanni Cozzolongo

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In this paper, we present C@sa, a multiagent system aiming at modeling, controlling and simulating the behavior of an intelligent house. The developed system aims at providing to architects, designers and psychologists a simulation and control tool for understanding which is the impact of embedded and pervasive technology on people daily life. In this vision, the house is seen as an environment made up of independent and distributed devices, controlled by agents, interacting to support user's goals and tasks.

Keywords: Ambient intelligence, agent-based systems, influence diagrams.

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Authors: Denis Trcek

Abstract:

Trust is essential for further and wider acceptance of contemporary e-services. It was first addressed almost thirty years ago in Trusted Computer System Evaluation Criteria standard by the US DoD. But this and other proposed approaches of that period were actually solving security. Roughly some ten years ago, methodologies followed that addressed trust phenomenon at its core, and they were based on Bayesian statistics and its derivatives, while some approaches were based on game theory. However, trust is a manifestation of judgment and reasoning processes. It has to be dealt with in accordance with this fact and adequately supported in cyber environment. On the basis of the results in the field of psychology and our own findings, a methodology called qualitative algebra has been developed, which deals with so far overlooked elements of trust phenomenon. It complements existing methodologies and provides a basis for a practical technical solution that supports management of trust in contemporary computing environments. Such solution is also presented at the end of this paper.

Keywords: internet security, trust management, multi-agent systems, reasoning and judgment, modeling and simulation, qualitativealgebra

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Authors: Liming Chen, Baoxin Xiu, Zhaoyun Ding, Bin Liu, Xianqiang Zhu

Abstract:

In the era of big data, public investors are faced with more complicated information related to investment decisions than ever before. To survive in the fierce competition, it has become increasingly urgent for investors to combine multi-source knowledge and evaluate the companies’ true value efficiently. For this, a rule-based ontology reasoning method is proposed to support steel companies’ value assessment. Considering the delay in financial disclosure and based on cost-benefit analysis, this paper introduces the supply chain enterprises financial analysis and constructs the ontology model used to value the value of steel company. In addition, domain knowledge is formally expressed with the help of Web Ontology Language (OWL) language and SWRL (Semantic Web Rule Language) rules. Finally, a case study on a steel company in China proved the effectiveness of the method we proposed.

Keywords: Financial ontology, steel company, supply chain, ontology reasoning.

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Authors: Souad Demigha

Abstract:

The paper aims to specify and build a system, a learning support in radiology-senology (breast radiology) dedicated to help assist junior radiologists-senologists in their radiologysenology- related activity based on experience of expert radiologistssenologists. This system is named SAFRS (i.e. system supporting the training of radiologists-senologists). It is based on the exploitation of radiologic-senologic images (primarily mammograms but also echographic images or MRI) and their related clinical files. The aim of such a system is to help breast cancer screening in education. In order to acquire this expert radiologist-senologist knowledge, we have used the CBR (case-based reasoning) approach. The SAFRS system will promote the evolution of teaching in radiology-senology by offering the “junior radiologist" trainees an advanced pedagogical product. It will permit a strengthening of knowledge together with a very elaborate presentation of results. At last, the know-how will derive from all these factors.

Keywords: Learning support, radiology-senology, training, education, CBR, accumulated experience.

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Authors: Ong Sing Goh, C. Ardil, Wilson Wong, Chun Che Fung

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The evaluation of conversational agents or chatterbots question answering systems is a major research area that needs much attention. Before the rise of domain-oriented conversational agents based on natural language understanding and reasoning, evaluation is never a problem as information retrieval-based metrics are readily available for use. However, when chatterbots began to become more domain specific, evaluation becomes a real issue. This is especially true when understanding and reasoning is required to cater for a wider variety of questions and at the same time to achieve high quality responses. This paper discusses the inappropriateness of the existing measures for response quality evaluation and the call for new standard measures and related considerations are brought forward. As a short-term solution for evaluating response quality of conversational agents, and to demonstrate the challenges in evaluating systems of different nature, this research proposes a blackbox approach using observation, classification scheme and a scoring mechanism to assess and rank three example systems, AnswerBus, START and AINI.

Keywords: Evaluation, conversational agents, Response Quality, chatterbots

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Authors: Junjie Gao, Guishi Deng

Abstract:

In order to integrate knowledge in heterogeneous case-based reasoning (CBR) systems, ontology-based CBR system has become a hot topic. To solve the facing problems of ontology-based CBR system, for example, its architecture is nonstandard, reusing knowledge in legacy CBR is deficient, ontology construction is difficult, etc, we propose a novel approach for semi-automatically construct ontology-based CBR system whose architecture is based on two-layer ontology. Domain knowledge implied in legacy case bases can be mapped from relational database schema and knowledge items to relevant OWL local ontology automatically by a mapping algorithm with low time-complexity. By concept clustering based on formal concept analysis, computing concept equation measure and concept inclusion measure, some suggestions about enriching or amending concept hierarchy of OWL local ontologies are made automatically that can aid designers to achieve semi-automatic construction of OWL domain ontology. Validation of the approach is done by an application example.

Keywords: OWL ontology, Case-based Reasoning, FormalConcept Analysis, Knowledge Integration

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Authors: Anant Oonsivilai, Kenedy A. Greyson

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The demand of the energy management systems (EMS) set forth by modern power systems requires fast energy management systems. Contingency analysis is among the functions in EMS which is time consuming. In order to handle this limitation, this paper introduces agent based technology in the contingency analysis. The main function of agents is to speed up the performance. Negotiations process in decision making is explained and the issue set forth is the minimization of the operating costs. The IEEE 14 bus system and its line outage have been used in the research and simulation results are presented.

Keywords: Agents, model, negotiation, optimal dispatch, powersystems.

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Authors: Rohana Mahmud, Hairul Aysa Abdul Halim Sithiq, Haryuna Mohd Taharim

Abstract:

In this paper, the authors present architecture of a multi agent consultation system for obesity related problems, which hybrid the technology of an expert system (ES) and an intelligent agent (IA). The strength of the ES which is capable of pulling the expert knowledge is consulted and presented to the end user via the autonomous and friendly pushing environment of the intelligent agent.

Keywords: Expert System, Hybrid Technology, Intelligent Agent, Medical Informatics, Multi Agent Consultation System.

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Authors: Goh Ong Sing, C. Ardil, Wilson Wong, Shahrin Sahib

Abstract:

The evaluation of the question answering system is a major research area that needs much attention. Before the rise of domain-oriented question answering systems based on natural language understanding and reasoning, evaluation is never a problem as information retrieval-based metrics are readily available for use. However, when question answering systems began to be more domains specific, evaluation becomes a real issue. This is especially true when understanding and reasoning is required to cater for a wider variety of questions and at the same time achieve higher quality responses The research in this paper discusses the inappropriateness of the existing measure for response quality evaluation and in a later part, the call for new standard measures and the related considerations are brought forward. As a short-term solution for evaluating response quality of heterogeneous systems, and to demonstrate the challenges in evaluating systems of different nature, this research presents a black-box approach using observation, classification scheme and a scoring mechanism to assess and rank three example systems (i.e. AnswerBus, START and NaLURI).

Keywords: Evaluation, question answering, response quality.

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Authors: G. Balakayeva, A. Aktymbayeva

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In this paper, we consider components of discrete event imitating model, implementing a simulation model by using JAVA and performing an input analysis of the data and an output analysis of the simulation results. Was lead development of imitating model of mass service system with n (n≥1) devices of service. On the basis of the developed process of a multithreading simulated the distributed processes with presence of synchronization. Was developed the algorithm of event-oriented simulation, was received results of system functioning with n devices of service.

Keywords: Imitating modeling, Mass service system, Multi agentsystem.

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Authors: Marc Sango, Olimpia Hoinaru, Christophe Gransart, Laurence Duchien

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Ontologies offer a means for representing and sharing information in many domains, particularly in complex domains. For example, it can be used for representing and sharing information of System Requirement Specification (SRS) of complex systems like the SRS of ERTMS/ETCS written in natural language. Since this system is a real-time and critical system, generic ontologies, such as OWL and generic ERTMS ontologies provide minimal support for modeling temporal information omnipresent in these SRS documents. To support the modeling of temporal information, one of the challenges is to enable representation of dynamic features evolving in time within a generic ontology with a minimal redesign of it. The separation of temporal information from other information can help to predict system runtime operation and to properly design and implement them. In addition, it is helpful to provide a reasoning and querying techniques to reason and query temporal information represented in the ontology in order to detect potential temporal inconsistencies. To address this challenge, we propose a lightweight 3-layer temporal Quality of Service (QoS) ontology for representing, reasoning and querying over temporal and non-temporal information in a complex domain ontology. Representing QoS entities in separated layers can clarify the distinction between the non QoS entities and the QoS entities in an ontology. The upper generic layer of the proposed ontology provides an intuitive knowledge of domain components, specially ERTMS/ETCS components. The separation of the intermediate QoS layer from the lower QoS layer allows us to focus on specific QoS Characteristics, such as temporal or integrity characteristics. In this paper, we focus on temporal information that can be used to predict system runtime operation. To evaluate our approach, an example of the proposed domain ontology for handover operation, as well as a reasoning rule over temporal relations in this domain-specific ontology, are presented.

Keywords: System Requirement Specification, ERTMS/ETCS, Temporal Ontologies, Domain Ontologies.

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Authors: O. P. Rishi, Rekha Govil, Madhavi Sinha

Abstract:

Online learning with Intelligent Tutoring System (ITS) is becoming very popular where the system models the student-s learning behavior and presents to the student the learning material (content, questions-answers, assignments) accordingly. In today-s distributed computing environment, the tutoring system can take advantage of networking to utilize the model for a student for students from other similar groups. In the present paper we present a methodology where using Case Based Reasoning (CBR), ITS provides student modeling for online learning in a distributed environment with the help of agents. The paper describes the approach, the architecture, and the agent characteristics for such system. This concept can be deployed to develop ITS where the tutor can author and the students can learn locally whereas the ITS can model the students- learning globally in a distributed environment. The advantage of such an approach is that both the learning material (domain knowledge) and student model can be globally distributed thus enhancing the efficiency of ITS with reducing the bandwidth requirement and complexity of the system.

Keywords: CBR, ITS, student modeling, distributed system, intelligent agent.

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Authors: A. R. Seifi

Abstract:

This work presents a new algorithm based on a combination of fuzzy (FUZ), Dynamic Programming (DP), and Genetic Algorithm (GA) approach for capacitor allocation in distribution feeders. The problem formulation considers two distinct objectives related to total cost of power loss and total cost of capacitors including the purchase and installation costs. The novel formulation is a multi-objective and non-differentiable optimization problem. The proposed method of this article uses fuzzy reasoning for sitting of capacitors in radial distribution feeders, DP for sizing and finally GA for finding the optimum shape of membership functions which are used in fuzzy reasoning stage. The proposed method has been implemented in a software package and its effectiveness has been verified through a 9-bus radial distribution feeder for the sake of conclusions supports. A comparison has been done among the proposed method of this paper and similar methods in other research works that shows the effectiveness of the proposed method of this paper for solving optimum capacitor planning problem.

Keywords: Capacitor planning, Fuzzy logic method, Genetic Algorithm, Dynamic programming, Radial Distribution feeder

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Authors: Maithem Al-Saadi, Min An

Abstract:

During airport planning and design stages, the major issues of capacity and safety in construction and operation of an airport need to be taken into consideration. The airside of an airport is a major and critical infrastructure that usually consists of runway(s), taxiway system, and apron(s) etc., which have to be designed according to the international standards and recommendations, and local limitations to accommodate the forecasted demands. However, in many cases, airport airsides are suffering from unexpected risks that occurred during airport operations. Therefore, safety risk assessment should be applied in the planning and design of airsides to cope with the probability of risks and their consequences, and to make decisions to reduce the risks to as low as reasonably practicable (ALARP) based on safety risk assessment. This paper presents a combination approach of Failure Modes, Effect, and Criticality Analysis (FMECA), Fuzzy Reasoning Approach (FRA), and Fuzzy Analytic Hierarchy Process (FAHP) to develop a risk analysis model for safety risk assessment. An illustrated example is used to the demonstrate risk assessment process on how the design of an airside in an airport can be analysed by using the proposed safety design risk assessment model.

Keywords: Airport airside planning and design, design for safety, fuzzy reasoning approach, fuzzy AHP, risk assessment.

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Authors: Meltem Serhatli, Ferda N. Alpaslan

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Processing the data by computers and performing reasoning tasks is an important aim in Computer Science. Semantic Web is one step towards it. The use of ontologies to enhance the information by semantically is the current trend. Huge amount of domain specific, unstructured on-line data needs to be expressed in machine understandable and semantically searchable format. Currently users are often forced to search manually in the results returned by the keyword-based search services. They also want to use their native languages to express what they search. In this paper, an ontology-based automated question answering system on software test documents domain is presented. The system allows users to enter a question about the domain by means of natural language and returns exact answer of the questions. Conversion of the natural language question into the ontology based query is the challenging part of the system. To be able to achieve this, a new algorithm regarding free text to ontology based search engine query conversion is proposed. The algorithm is based on investigation of suitable question type and parsing the words of the question sentence.

Keywords: Description Logics, ontology, question answering, reasoning.

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Authors: Chang, Chun-Lang, Liu, Chun-Kai

Abstract:

This study, for its research subjects, uses patients who had undergone total knee replacement surgery from the database of the National Health Insurance Administration. Through the review of literatures and the interviews with physicians, important factors are selected after careful screening. Then using Cross Entropy Method, Genetic Algorithm Logistic Regression, and Particle Swarm Optimization, the weight of each factor is calculated and obtained. In the meantime, Excel VBA and Case Based Reasoning are combined and adopted to evaluate the system. Results show no significant difference found through Genetic Algorithm Logistic Regression and Particle Swarm Optimization with over 97% accuracy in both methods. Both ROC areas are above 0.87. This study can provide critical reference to medical personnel as clinical assessment to effectively enhance medical care quality and efficiency, prevent unnecessary waste, and provide practical advantages to resource allocation to medical institutes.

Keywords: Total knee replacement, Case Based Reasoning, Cross Entropy Method, Genetic Algorithm Logistic Regression, Particle Swarm Optimization.

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Authors: Mohammad J. Heydari, Farnaz Derakhshan

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In this paper, we focus on the problem of driving and herding a collection of autonomous actors to a given area. Then, a new method based on multi-agent coordination is proposed for solving the problem. In our proposed method, we assume that the environment is covered by sensors. When an event is occurred, sensors forward information to a sink node. Based on received information, the sink node will estimate the direction and the speed of movement of actors and announce the obtained value to the actors. The actors coordinate to reach the target location.

Keywords: Coordination, Environmental Inspection, Multiagent systems, Wireless Sensor and Actor Networks (WSANs)

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Authors: S. Behnam Malekzadeh, I. Kerr, T. Kaempffer, T. Harper, A Watson

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The Site C Hydroelectric dam is currently being constructed in north-eastern British Columbia on sub-horizontal sedimentary strata that dip approximately 15 meters from one bank of the Peace River to the other. More than 615 pressure sensors (Vibrating Wire Piezometers) have been installed on bedding planes (BPs) since construction began, with over 80 more planned before project completion. These pressure measurements are essential to monitor the stability of the rock foundation during and after construction and for dam safety purposes. BPs are identified by their clay gouge infilling, which varies in thickness from less than 1 to 20 mm and can be challenging to identify as the core drilling process often disturbs or washes away the gouge material. Without the use of depth predictions from nearby boreholes, stratigraphic markers, and downhole geophysical data, it is difficult to confidently identify BP targets for the sensors. In this paper, a Case-Based Reasoning (CBR) method was used to develop an empirical model called the Bedding Plane Elevation Prediction (BPEP) to help geologists and geotechnical engineers to predict geological features and BPs at new locations in a fast and accurate manner. To develop CBR, a database was developed based on 64 pressure sensors already installed on key bedding planes BP25, BP28, and BP31 on the Right Bank, including BP elevations and coordinates. 13 (20%) of the most recent cases were selected to validate and evaluate the accuracy of the developed model, while the similarity was defined as the distance between previous cases and recent cases to predict the depth of significant BPs. The average difference between actual BP elevations and predicted elevations for above BPs was ± 55 cm, while the actual results showed that 69% of predicted elevations were within ± 79 cm of actual BP elevations while 100% of predicted elevations for new cases were within ± 99 cm range. Eventually, the actual results will be used to develop the database and improve BPEP to perform as a learning machine to predict more accurate BP elevations for future sensor installations.

Keywords: Case-Based Reasoning, CBR, geological feature, geology, piezometer, pressure sensor, core logging, dam construction.

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Authors: José Neves, M. Rosário Martins, Fátima Candeias, Diana Ferreira, Sílvia Arantes, Júlio Cruz-Morais, Guida Gomes, Joaquim Macedo, António Abelha, Henrique Vicente

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Some plants of genus Schinus have been used in the folk medicine as topical antiseptic, digestive, purgative, diuretic, analgesic or antidepressant, and also for respiratory and urinary infections. Chemical composition of essential oils of S. molle and S. terebinthifolius had been evaluated and presented high variability according with the part of the plant studied and with the geographic and climatic regions. The pharmacological properties, namely antimicrobial, anti-tumoural and anti-inflammatory activities are conditioned by chemical composition of essential oils. Taking into account the difficulty to infer the pharmacological properties of Schinus essential oils without hard experimental approach, this work will focus on the development of a decision support system, in terms of its knowledge representation and reasoning procedures, under a formal framework based on Logic Programming, complemented with an approach to computing centered on Artificial Neural Networks and the respective Degree-of-Confidence that one has on such an occurrence.

Keywords: Artificial neuronal networks, essential oils, knowledge representation and reasoning, logic programming, Schinus molle L, Schinus terebinthifolius raddi.

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Authors: Olimpia Matarazzo, Ivana Baldassarre

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The main aim of this study was to examine whether people understand indicative conditionals on the basis of syntactic factors or on the basis of subjective conditional probability. The second aim was to investigate whether the conditional probability of q given p depends on the antecedent and consequent sizes or derives from inductive processes leading to establish a link of plausible cooccurrence between events semantically or experientially associated. These competing hypotheses have been tested through a 3 x 2 x 2 x 2 mixed design involving the manipulation of four variables: type of instructions (“Consider the following statement to be true", “Read the following statement" and condition with no conditional statement); antecedent size (high/low); consequent size (high/low); statement probability (high/low). The first variable was between-subjects, the others were within-subjects. The inferences investigated were Modus Ponens and Modus Tollens. Ninety undergraduates of the Second University of Naples, without any prior knowledge of logic or conditional reasoning, participated in this study. Results suggest that people understand conditionals in a syntactic way rather than in a probabilistic way, even though the perception of the conditional probability of q given p is at least partially involved in the conditionals- comprehension. They also showed that, in presence of a conditional syllogism, inferences are not affected by the antecedent or consequent sizes. From a theoretical point of view these findings suggest that it would be inappropriate to abandon the idea that conditionals are naturally understood in a syntactic way for the idea that they are understood in a probabilistic way.

Keywords: Conditionals, conditional probability, conditional syllogism, inferential task.

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Authors: K. Idir, H. Merouani, Y. Tlili.

Abstract:

An effective method for the early detection of breast cancer is the mammographic screening. One of the most important signs of early breast cancer is the presence of microcalcifications. For the detection of microcalcification in a mammography image, we propose to conceive a multiagent system based on a dual irregular pyramid. An initial segmentation is obtained by an incremental approach; the result represents level zero of the pyramid. The edge information obtained by application of the Canny filter is taken into account to affine the segmentation. The edge-agents and region-agents cooper level by level of the pyramid by exploiting its various characteristics to provide the segmentation process convergence.

Keywords: Dual Pyramid, Image Segmentation, Multi-agent System, Region/Edge Cooperation.

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