Inference Engine

We created an inference engine and query language for expressing temporal patterns in data. The patterns are represented by using temporally-ordered sets of data objects. Patterns are elaborated by reference to new objects inferred from original data, and by interlocking temporal and other relationships among sets of these objects. We found the tools well-suited to define scenarios of events that are evidence of inappropriate use of prescription drugs, using Medicaid administrative data that describe medical events. The tools' usefulness in research might be considerably more general.

This paper tries to discuss some findings in mathematical decision-making modeling models with applications in business processes. We start by presenting some technological implications and implementations of decision-making models. After this we discuss some implementations realized by us and that consists in a neural network, a JAVA implementation of the decision-making model, an expert systems-shell implementation and an implementation with ontology and inference engine. The paper ends with usefull conclusions drawn for decision-making modeling activities.

An embedded real-time fault detection, isolation and reconfiguration (FDIR) solution has the potential to reduce the likelihood of loss of life, aircraft or mission, by promptly isolating sudden failures and reconfiguring the system to avoid disasters. However, existing embedded ...

In this paper, a delayed treatment to handwritten numerals with fuzzy logic has been provided. The patterns which used in this system consisted 100 patterns of 10 numerals (0 to 9). They were taken from 10 different subjects and converted by the scanner to computer into 30×20 binary patterns. We used off-line system in take the patterns. The recognition rate is 94%.

An embedded real-time fault detection, isolation and reconfiguration (FDIR) solution has the potential to reduce the likelihood of loss of life, aircraft or mission, by promptly isolating sudden failures and reconfiguring the system to avoid disasters. However, existing embedded ...

The knowledge-based organization for the West Virginia University face decision support system is given, along with the initial development of the associated inference engine. The knowledge base contains generic knowledge about underground coal mines that utilize specifically continuous miners. A typical knowledge entry is given. The inference engine methodology is then explained. The engine utilizes this knowledge with data from monitoring systems and from interaction with the section foreman, to assist in making section management decisions and plans.

Despite the widely acknowledged potential of intelligent transport systems and services (ITS), the deployment of ITS has generally been scattered and slow. One of the main reasons for this is that people deciding on investments in the road and public transport sector often lack knowledge of the feasibility, cost-effectiveness, impacts and user acceptance of ITS solutions to their own transport related problems. One solution is to build up an intelligent ITS toolkit, which would propose to the decision maker the most viable ITS solutions in relation to his problems in his context. The study describes how such a toolkit has been designed and developed, including the knowledge base and inference engine providing the intelligence to that toolkit. The study is focusing on how to infer the most likely impacts and benefit/cost matching the user input on the basis of existing ITS evaluations studies and the available assessment expertise in the specific user contexts.

The purpose of this paper is to provide an introduction to the OWL Web ontology language, a survey focused on the current state of the art in OWL inferencing capabilities, and a historical perspective on procedural attachments. The perspective is aligned with current OWL research. Several limitations of the OWL language and proposed extensions to overcome these limitations are discussed. A framework that provides empirical testing support for evaluating the effects of procedural attachments to the OWL inferencing capabilities is outlined. The examples presented suggest that it is possible to provide rule-based extensibility support for OWL that does not limit the ability of an OWL reasoner to perform consistency checking. Specifically, the framework is used to demonstrate with an example experiment the ability to provide support for the compound sub-property axiom.

Presently, computers are changing from isolated devices into entry points to a worldwide network of information exchange and business transactions called the World Wide Web (WWW). However, the success of the WWW has made it increasingly difficult to find, access, present and maintain the information required by a wide variety of users. In response to this problem, many new research initiatives and commercial enterprises have been set up to enrich the available information with machine-processable semantics. This Semantic Web will provide intelligent access to distributed information, enabling software products (agents) to mediate between user needs and the information sources available. As a response to the challenge of providing high quality healthcare services with reasonable costs while the elderly population and the associated chronic disease increase, this paper provides a conceptual model (Semantic health model) of using the Semantic Web to locate required information regardin...

This paper describes a framework for implementing intrusion detection systems using fuzzy logic. A fuzzy data-mining algorithm is used to extract fuzzy rules for the inference engine. The modular architecture is implemented using the Java expert system shell (Jess) and the FuzzyJess toolkit developed by Sandia National Laboratories and the National Research Council of Canada respectively. Experimental results for a

ABSTRACT The paper presents an EDA system, which is supported by the experimental speech recognition system menu with the dialog module. The main idea of the system is presented. Some aspects concerning the proposed speech recognition methodology are described. Problems specific to the Polish language are emphasized. The idea of dialog system menus is discussed. The inference engine based on AI techniques supporting Polish (natural) language processing is proposed. The entire expert system architecture is introduced. Implementation and examples are discussed.

A machine-printed character recognition system that relies on prior knowledge of character shapes is presented. Because the classification performance is strongly dependent on the input feature set, the focus is on the creation of features based on curvature estimation. A set of `clean' characters from multiple fonts was used to emphasize the authors' belief that a clean set of characters can be used to build an inference engine to recognize noisy characters. Clustering of a clean character set from multiple fonts led to 263 unique character contours

Abstract—This research paper describes the design and implementation of an autonomous room air cooler using fuzzy rule based control system. The rule base receives two crisp input values from temperature and humidity sensors, divides the universe of discourse into ...

Fluid and electrolyte balancing in the human body is an important issue, especially for patients in the Intensive Care Unit or under long surgical operation. Fluid excess would evoke heart failure while fluid deficit would cause dehydration. Currently there is no precise analytical relationship for fluid administration. The development of a decision support system (DSS) assisting the anaesthetist to accurately estimate the patient's body fluid during a major surgery is studied. Fuzzy logic control (FLC) is the main method employed in the inference ...

A method that employs grammars to direct the inference process of a vision system that does interpretation of dynamic scenes is described. The system uses a set of qualitative image descriptors to drive the interpretation. The result is a 'natural language' description of scene activities. In addition the inference engine generates a set of predictions that can be used to control the interpretation strategy so as to make the processing of new images more efficient. The system has been implemented in an expert system shell to demonstrate the viability of the approach. Results on real images are reported. Frame 0 Frame 1 Frame 3 Frame 5 Frame 7 Frame 9 Frame 11 Frame 13

HAZOP (Hazard and Operability) is a preliminary and systematic approach for identifying hazards and suggesting hazard mitigation measures in a process facility. A knowledge-based expert system, ExpHAZOP+, has been developed to automate the manual HAZOP ...

Adaptive Intelligent Web Based Education System, (AIWBES) is an education technology which has been used worldwide. An Intelligent and adaptive AIWBES is materialized from the combination of Users' Model, Knowledge Based and Inference Engine. The development of adaptation or personalization in AIWBES will provide an Intelligence system for the users to obtain knowledge and information. This paper will focus on the user model to enhance AIWBES personalization based on its users' modality learning style. The objective of this paper is to compare the precision between Production-Fuzzy Rule and Naives Bayes for classifying modality learning styles in the user model. A prototype namely K-Stailo, is developed. These two different techniques were applied in K-Stailo. A test was carried out by the researcher to evaluate the precision between these two techniques. The results show that Production-Fuzzy Rule is the better technique when compared to Naives Bayes in user's modality learning style prediction.

INES (INtelligent Educational System) is a functional prototype of an online learning platform, which combines three essential capabilities related to e-learning activities. These capabilities are those concerning to a LMS (Learning Management System), a LCMS (Learning Content Management System), and an ITS (Intelligent Tutoring System). To carry out all this functionalities, our system, as a whole, comprises a set of different tools and technologies, as follows: semantic managing users (administrators, teachers, students…) and contents tools, an intelligent chatterbot able to communicate with students in natural language, an intelligent agent based on BDI (Believes, Desires, Intentions) technology that acts as the brain of the system, an inference engine based on JESS (a rule engine for the Java platform) and ontologies (to modelate the user, his/her activities, and the learning contents) that contribute with the semantics of the system, etc. At the present paper we will focus on the chatterbot, CHARLIE (CHAtteR Learning Interface Entity), developed and used in the platform, which is an AIMLbased (Artificial Intelligence Markup Language) bot. We will specifically address its performance and its contribution to INES.

Presently, computers are changing from isolated devices into entry points to a worldwide network of information exchange and business transactions called the World Wide Web (WWW). However, the success of the WWW has made it increasingly difficult to find, access, present and maintain the information required by a wide variety of users. In response to this problem, many new research initiatives and commercial enterprises have been set up to enrich the available information with machine-processable semantics. This Semantic Web will provide intelligent access to distributed information, enabling software products (agents) to mediate between user needs and the information sources available. As a response to the challenge of providing high quality healthcare services with reasonable costs while the elderly population and the associated chronic disease increase, this paper provides a conceptual model (Semantic health model) of using the Semantic Web to locate required information regarding health matters, thereby facilitating healthcare delivery in rural areas. The Semantic health model will consist of four (4) layers: Database, Data transfer mechanism (DTM), Medical Inference Engine (MIE) and User interface.

Adaptive Intelligent Web Based Education System, (AIWBES) is an education technology which has been used worldwide. An Intelligent and adaptive AIWBES is materialized from the combination of Users' Model, Knowledge Based and Inference Engine. The development of adaptation or personalization in AIWBES will provide an Intelligence system for the users to obtain knowledge and information. This paper will focus on the user model to enhance AIWBES personalization based on its users' modality learning style. The objective of this paper is to compare the precision between Production-Fuzzy Rule and Naives Bayes for classifying modality learning styles in the user model. A prototype namely K-Stailo, is developed. These two different techniques were applied in K-Stailo. A test was carried out by the researcher to evaluate the precision between these two techniques. The results show that Production-Fuzzy Rule is the better technique when compared to Naives Bayes in user's modality learning style prediction.

With the increase in VLSI circuit complexity and density, the problem of testing them has become a major challenge. Design for testability (DFT) has been accepted as the primary approach to the solution of the problem. However, the variety and richness of the DFT techniques require expert assistance for their appropriate utilization. Variety in circuit design style (PLA, random logic, ROM, etc.) and various other design constraints (fault coverage, logic area overhead, etc.) also call for different DFT Techniques. In this paper we present two knowledge based expert systems (KBES) for the selection of test methodologies for PLAs and random logic circuits. Designer requirements are taken as the motion vector which gives the strength of his/her motivation for maximizing or minimizing the various DFT parameters (fault coverage, logic area overhead, test time, etc.), which act as the design constraints. Production rules form the basic knowledge representation scheme and a tool has been developed to implement each of these KBES. Results for both PLA and random logic circuits are also presented.

HAZOP (Hazard and Operability) is a preliminary and systematic approach for identifying hazards and suggesting hazard mitigation measures in a process facility. A knowledge-based expert system, ExpHAZOP+, has been developed to automate the manual HAZOP ...

We present a novel architecture to map the twodimensional Internet space in virtual worlds according to predefined or inferred metaphors. Web elements and metaphor elements are both conceptualized as semanticnetworks and are compared through an inference engine in order to detect similarities. Once all the web elements have been mapped within a virtual world metaphor, a VR-Builder generates VRML sources according to the virtual representation.