Knowledge-Based Expert Systems

This paper presents a conceptual framework on user acceptance of biometrics application, namely fingerprint-based smart kiosk, which is adopted by Malaysia’s Employees Provident Fund (EPF). In order to expedite the process and waiting time of EPF’s customers, fingerprint-based smart kiosk was introduced enabling customers to (i) acquire activation code in order to create a personalize myEPF website and (ii) print the latest account statement of the fund. This study extends the Unified Theory of Acceptance and Use of Technology (UTAUT) to determine the factors that influence the usage of fingerprint-based smart kiosk. Based on conventional UTAUT, an additional independent variable was added i.e., personal concerns. Qualitative and quantitative approaches will be used for data collection from a sample of 1200 participants. Consequently, descriptive and inferential analysis will be applied to summarize and interpret the relationship between the variables. It is expected that the resear...

Academic advising has become a critical factor of students' success as universities offer a variety of programs and courses in their curriculum. It is a student-centered initiative that fosters a student's involvement with the institution by supporting students in their academic progression and career goals. Managing the knowledge involved in the advising process is crucial to ensure that the knowledge is available to those who need it and that it is used effectively to make good advising decisions that impact student persistence and success. The use of AI-based tools strengthens the advising process by reducing the workload of advisors and providing better decision support tools to improve the advising practice. This study explores the challenges associated with the current advising system from a knowledge management perspective and proposes an integrated AI-based framework to tackle the main advising tasks.

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Models of consensus are used in the validation process to develop a basis for system performance. This paper develops two analytic models of consensus that can be useful in the validation process. The first model employs the binomial model to study the probability that the consensus judgment is correct or incorrect. This problem is critical for the validation of expert systems, since the model leads us to conclude that in some cases consensus judgment is not appropriate. That basic model is extended to account for both different levels of expertise and unequal prior odds. The second model is a Bayesian model of the use of consensus judgment and the validation process. There are two applications of the Bayesian model The first application ofthe Bayesian model finds that, in some cases, consensus judgment is not appropriate and to generate a hypothesis as to the conditions for the use of the consensus judgment. The second application compares an expert systems performance to the consensus judgment. It can be used to assist in deriving stopping criteria for the: validation process.

Third-generation robotic systems are intelligent in the sense that they can perform a large repertory of complex tasks under conditions not known a priori. They are usually sensor-coupled using multisensory (vision, force, tactiie, etc.) information about their initial state and environment, have decision-making capabilities, can monitor and modify their plans learning from past experience. They have the properties of flexibility and artificial intelligence. The aim of the book was to provide wide coverage of these concepts based on the latest developments of well-known experts working in academic and research institutions. The book is addressed to scientists, engineers, postgraduate students and professionals working or having interest in intelligent robotics and control. The book is divided in 5 parts containing 18 chapters. Part I is devoted to introductory issues and it consists of Chapter 1: Introduction to Intelligent Robotic Systems written by Tzafestas (National Technical University of Athens,. Greece). The general architecture of intelligent robotic control (consisting of organization, coordination and execution levels), the basic problems of robot modeling and motion control, and the classification of sensors including vision are introduced. Three examples of intelligen t robotic systems are selected from the field of sensor-based (Espirit 278 and Pardue system) and mobile (KAMRO) robots. Part II deals with the structure and programming of intelligent robotic systems. Chapter 2: Theory and Design of Intelligent Robotic Systems by Valavanis (Northeastern University, Boston, Massachusetts), presents a general theory of intelligent machines and robotic systems based on a heuristic probabilistic model and entropy functions to describe the system performance of structures composed of organization, coordination and execution levels. Chapter 3: Hierarchy oj Intelligent On-Line Execution by Kelley (Rensselaer Polytechnic Institute, Troy, New York) deals with a robotic assembly system that allows both automatic programming and execution despite uncertainties in the task environment. The principle ofleast commitment is followed, and the system is partitioned into off-line (planners, specialists) and on-line (supervisor, specialists, interfaces) modules. Some details are given for the design of the supervisor and its implementation with 4 specialists on VAX running under Unix. Chapter 4: Skill-Based Expert Systems in Robotics by Tomovic (University of Belgrade, Yugoslavia), deals with the skill level (functional motion of human extremities) of a hierarchical control structure using both numerical and non numerical models. It concentrates on multifinger robot hands and describes the hand mechanics, sensors and local controllers of the Belgrade-USC Hand, and the multilevel manipulator control using computer vision and expert system (for preshaping, grasping mode, etc.

Expert systems (ES) are systems that emanate from the new area of computing known as Artificial Intelligence (AI). An expert system is an application program that makes decisions to solve problems in a particular field, such as finance or medicine, by using knowledge and analytical rules defined by the expert of the field. It uses two components, a knowledge base and an inference engine to form conclusions. Additional tools include a user interface and explanation facilities, which enable the system to justify or explain its conclusions as well as allow developers to run check the operating system.

Academic advising has become a critical factor of students' success as universities offer a variety of programs and courses in their curriculum. It is a student-centered initiative that fosters a student's involvement with the institution by supporting students in their academic progression and career goals. Managing the knowledge involved in the advising process is crucial to ensure that the knowledge is available to those who need it and that it is used effectively to make good advising decisions that impact student persistence and success. The use of AI-based tools strengthens the advising process by reducing the workload of advisors and providing better decision support tools to improve the advising practice. This study explores the challenges associated with the current advising system from a knowledge management perspective and proposes an integrated AI-based framework to tackle the main advising tasks.

Security is becoming an increasingly important issue for business, and with it comes the need for appropriate authentication; consequently, it is becoming gradually more important to develop secure e-commerce systems. Fraud via the web, identity theft, and phishing are raising concerns for users and financial organisations. In addition, current authentication methods, like passwords, have many problems (e.g. some users write them down, they forget them, or they make them easy to hack). We can overcome these drawbacks by using biometric authentication systems. Biometric systems are being used for personal authentication in response to the rising issue of authentication and security. Biometrics provide much promise, in terms of preserving our identities without the inconvenience of carrying ID cards and/or remembering passwords. This research is important because the securing of e-commerce transactions is becoming increasingly important. Identity theft, hacking and viruses are growing...

This paper proposes a knowledge-based system to help parents diagnose some of their children's diseases at an early stage and to give them insight into whether they should see a doctor. It covers the most common diseases encountered by pediatric specialists, such as intestinal obstruction, dehydration, anemia, etc. An overview of these diseases is provided, the etiology of the disease is outlined, and treatment suggestions for the most common diseases are given when possible. CLIPS was used to develop the proposed expert system.

This paper proposes a knowledge-based system to help parents diagnose some of their children's diseases at an early stage and to give them insight into whether they should see a doctor. It covers the most common diseases encountered by pediatric specialists, such as intestinal obstruction, dehydration, anemia, etc. An overview of these diseases is provided, the etiology of the disease is outlined, and treatment suggestions for the most common diseases are given when possible. CLIPS was used to develop the proposed expert system.

Policy design requires the investigation of various data in several design steps for making the right decisions, validating, or monitoring the political environment. The increasing amount of data is challenging for the stakeholders in this domain. One promising way to access the "big data" is by abstracted visual patterns and pictures, as proposed by information visualization. This chapter introduces the main idea of information visualization in policy modeling. First abstracted steps of policy design are introduced that enable the identification of information visualization in the entire policy life-cycle. Thereafter, the foundations of information visualization are introduced based on an established reference model. The authors aim to amplify the incorporation of information visualization in the entire policy design process. Therefore, the aspects of data and human interaction are introduced, too. The foundation leads to description of a conceptual design for social data visualization, and the aspect of semantics plays an important role.

Background There are approximately five Zhengs reported in psoriatic patients. Systematic data collection and proper analysis for the classification of psoriasis have been lacking. This study aims to cluster the Zhengs in psoriatic patients based on the application of a checklist of traditional Chinese medicine (TCM) symptoms and signs followed by latent class analysis (LCA). Methods A cross-sectional study of 507 psoriatic patients aged above 10 years was performed in Yunnan Provincial Hospital of TCM and the First Affiliated Hospital of Kunming Medicine University from October 2010 to September 2011 using a TCM symptoms and signs checklist obtained from 16 TCM experts by the Delphi technique. LCA was applied to obtain the best fitted model for clustering of symptoms and signs that can be interpreted as underlying Zhengs of psoriasis. Results The LCA identified three Zhengs: dampness-heat Zheng (35.1%); blood heat Zheng (34.7%); and yin deficiency and blood dryness Zheng (30.2%). T...

Most of the data mining projects generate information (summarized in the form of graphs and charts) for business executives and decision makers; however it leaves to the choice of decision makers either to use it or disregard it. The manual use of the extracted knowledge limits the effectiveness of data mining technology considerably. This chapter proposes an architecture, in which data mining module is utilized to provide continuous supply of knowledge to a rule based expert system. Proposed approach solves the knowledge acquisition problem of rule based systems and also enhances effective utilization of data mining techniques (i.e. by supplying extracted knowledge to rule based system for automated use). The chapter describes the details of a data mining driven rule based expert system applied in medical billing domain. Main modules of the system along with the final analysis of performance of the system have also been presented.

This paper presents a conceptual framework on user acceptance of biometrics application, namely fingerprint-based smart kiosk, which is adopted by Malaysia’s Employees Provident Fund (EPF). In order to expedite the process and waiting time of EPF’s customers, fingerprint-based smart kiosk was introduced enabling customers to (i) acquire activation code in order to create a personalize myEPF website and (ii) print the latest account statement of the fund. This study extends the Unified Theory of Acceptance and Use of Technology (UTAUT) to determine the factors that influence the usage of fingerprint-based smart kiosk. Based on conventional UTAUT, an additional independent variable was added i.e., personal concerns. Qualitative and quantitative approaches will be used for data collection from a sample of 1200 participants. Consequently, descriptive and inferential analysis will be applied to summarize and interpret the relationship between the variables. It is expected that the resear...

In this paper we propose a multi-agent intelligent tutoring system building tool that integrates different formalisms in order to facilitate the teacher task of developing the contents of a tutorial system and at the same time to provide adaptiveness and flexibility in the presentation. The adopted formalisms are ground logic terms for the student model, data-bases for the domain model and object Petri nets for the pedagogical model. The interaction between the student and each agent of the system is controlled by an object Petri net, automatically translated into a rule-based expert system. The object Petri net tokens are composed by data objects that contain pointers to the student model and to the domain knowledge, stored into a data-base of texts, examples and exercises. The object Petri net transitions are controlled by logical conditions that refer to the student model and the firing of these transitions produce actions that update this student model.

The simple production rule representation is generalized by adding programs to a management system that manipulate rules in a rule-based system. By adapting this methodology, a single generalized rule can represent a group of simple ones. Then programs are employed to satisfy the general rule in a partial way while recursively reducing a decision problem into smaller ones of the same nature until a decision is made. It is shown that the reduction method is more efficient than the simple rule approach and that it minimizes the number of rules used to express a problem. The concept of using a management program to manipulate a set of rules is emphasized through solving a problem in a differential diagnosis expert system. A comparison between the number of rules employed to express a problem is made to show advantages of the reduction methodology over the simple rule representation.

DIVA is an expert system for turbine generator diagnosis. Its aim is to help a plant operator interpret vibration evolution to diagnose developing faults. Interpretation of vibration evolution is primarily a recognition process which is achieved by a particular model of heuristic classification. DIVA tries to recognize the observed situation among a hierarchy of typical situations. The purpose of this paper is to present the model we used for heuristic classification, based on prototypes. Prototypes represent typical problem situations and may also be seen as experts with special knowledge of what to do in such situations. We argue that this model presents significant advantages to deal with complex problems such as vibration surveillance.

An Expert System is an intelligent computer program that employs knowledge and inference procedures to solve problems that are considered difficult enough to require significant human expertise for their solutions [12]. Since the implementation of the first expert systems (the DENDRAL, MYCIN, Dipmeter Advisor, XCON,to mention but a few.) in the early 1970s, and the successes that followed, coupled with the advantages that humankind benefited from these early expert systems and their successors; one would expect that four decades later, there would have been a boom in the use of expert systems to perform more specialized tasks in different specific domains and application areas. The reasons for this could stem, asides other non-intrinsically-technical factors (such as financial implication, cultural and religious beliefs and restrictions surrounding the implementation of Expert Systems especially in third-world African Countries), either from a lack of adequate knowledge of the exist...

The simple production rule representation is generalized by adding programs to a management system that manipulate rules in a rule-based system. By adapting this methodology, a single generalized rule can represent a group of simple ones. Then programs are employed to satisfy the general rule in a partial way while recursively reducing a decision problem into smaller ones of the same nature until a decision is made. It is shown that the reduction method is more efficient than the simple rule approach and that it minimizes the number of rules used to express a problem. The concept of using a management program to manipulate a set of rules is emphasized through solving a problem in a differential diagnosis expert system. A comparison between the number of rules employed to express a problem is made to show advantages of the reduction methodology over the simple rule representation.

The study has utilized heuristic reasoning and the concept of Fuzzy Decision Variables in order to undertake the risk analysis of a proposed construction project in a selected domain The objectives included determining the sources of risks, obtaining the Fuzzy Decision Variables by deductive reasoning, identifying the types of risks prevailing in the project and the utilization of fuzzy set analysis in order to estimate the possible magnitudes of the risks. Five completed projects were analysed. For each project , a breakdown of the final contract sum into variations, remeasurement of provisional quantities, nominated subcontractors' accounts, nominated suppliers' accounts, loss and expense caused by disturbances of regular progress of the works, fluctuation in rates of labour and prices of materials was undertaken in order to derive the sources of risks, the Fuzzy Decision Variables and the subsequent risks. Fuzzy set analysis was used to calculate the possible magnitudes of the risks. Heuristic reasoning and fuzzy set analysis could be used in a composite framework to undertake the risk analysis of a proposed project in a selected domain.

The model of RISK ANALYZER was implemented as Knowledge-based System for the purpose of undertaking risk analysis for proposed construction projects in a selected domain. The Fuzzy Decision Variables (FDVs) that cause differences between initial and final contract sums of building projects were identified, the likelihood of the occurrence of the risks were determined and a Knowledge-Based System that would rank the risks was constructed using JAVA programming language and Graphic User Interface. The Knowledge-Based System is composed a Knowledge Base for storing data, an Inference Engine for controlling and directing the use of knowledge for problem-solution, and a User Interface that assists the user retrieve, use and alter data in the Knowledge Base. The developed Knowledge-Based System was compiled, implemented and validated with data of previously completed projects. The client could utilize the Knowledge-Based System to undertake proposed building projects

In this paper we propose a multi-agent intelligent tutoring system building tool that integrates different formalisms in order to facilitate the teacher task of developing the contents of a tutorial system and at the same time to provide adaptiveness and flexibility in the presentation. The adopted formalisms are ground logic terms for the student model, databases for the domain model and object Petri nets for the pedagogical model. The interaction between the student and each agent of the system is controlled by an object Petri net, automatically translated into a rule-based expert system. The object Petri net tokens are composed by data objects that contain pointers to the student model and to the domain knowledge, stored into a database of texts, examples and exercises. The object Petri net transitions are controlled by logical conditions that refer to the student model and the firing of these transitions produce actions that update this student model.

The model of RISK ANALYZER was implemented as Knowledge-based System for the purpose of undertaking risk analysis for proposed construction projects in a selected domain. The Fuzzy Decision Variables (FDVs) that cause differences between initial and final contract sums of building projects were identified, the likelihood of the occurrence of the risks were determined and a Knowledge-Based System that would rank the risks was constructed using JAVA programming language and Graphic User Interface. The Knowledge-Based System is composed a Knowledge Base for storing data, an Inference Engine for controlling and directing the use of knowledge for problem-solution, and a User Interface that assists the user retrieve, use and alter data in the Knowledge Base. The developed Knowledge-Based System was compiled, implemented and validated with data of previously completed projects. The client could utilize the Knowledge-Based System to undertake proposed building projects

According to traditional Chinese medicine (TCM), anger is closely related to the liver. This review was conducted to understand the liver-associated patterns that manifest as anger syndromes in TCM. Methods: Data regarding preclinical and clinical studies extracted from the China National Knowledge Infrastructure were reviewed to investigate whether it is justifiable and possible to define liver-associated patterns as anger syndrome. TCM patterns from two standard data sources-the World Health Organization standardization of terminologies in TCM and the pattern diagnosis standards of TCM-were analyzed for liverassociated patterns with the anger symptom. The direction, duration, and severity of anger symptoms of the extracted patterns were classified according to the TCM theory concepts such as yin and yang and excess and deficient by two independent authors. Results: Among 18 liver-associated patterns involving anger symptoms from the two data sources, 12 were associated with outward-focused anger (tendency to express anger verbally and/or behaviorally), four with inward-focused anger (tendency to suppress anger), and two with both outward-focused and inward-focused anger (a problem of anger control). All studies retrieved from the database were examined for the relationship between the liver and anger, with few or no studies examining the relationship between the other four viscera and anger. Conclusions: This review suggests that using liver-associated patterns in TCM may be a useful strategy for understanding and managing anger syndromes. However, because this study presents only a theoretical framework and preliminary review, further studies linking liver-associated patterns with various anger states are warranted.

Imperfections in healthcare revenue cycle management systems cause discrepancies between submitted claims and received payments. This paper presents a method for deriving attributional rules that can be used to support the preparation and screening of claims prior to their submission to payers. The method starts with unsupervised analysis of past payments to determine normal levels of payments for services. Then, supervised machine learning is used to derive sets of attributional rules for predicting potential discrepancies in claims. New claims can be then classified using the created models. The method was tested on a subset of Obstetrics claims for payment submitted by one hospital to Medicaid. One year of data was used to create models, which were tested using the following year's data. Results indicate that rule-based models are able to detect abnormal claims prior to their submission.

An Expert System is an intelligent computer program that employs knowledge and inference procedures to solve problems that are considered difficult enough to require significant human expertise for their solutions [12]. Since the implementation of the first expert systems (the DENDRAL, MYCIN, Dipmeter Advisor, XCON,to mention but a few.) in the early 1970s, and the successes that followed, coupled with the advantages that humankind benefited from these early expert systems and their successors; one would expect that four decades later, there would have been a boom in the use of expert systems to perform more specialized tasks in different specific domains and application areas. The reasons for this could stem, asides other non-intrinsically-technical factors (such as financial implication, cultural and religious beliefs and restrictions surrounding the implementation of Expert Systems especially in third-world African Countries), either from a lack of adequate knowledge of the exist...

The model of RISK ANALYZER was implemented as Knowledge-based System for the purpose of undertaking risk analysis for proposed construction projects in a selected domain. The Fuzzy Decision Variables (FDVs) that cause differences between initial and final contract sums of building projects were identified, the likelihood of the occurrence of the risks were determined and a Knowledge-Based System that would rank the risks was constructed using JAVA programming language and Graphic User Interface. The Knowledge-Based System is composed a Knowledge Base for storing data, an Inference Engine for controlling and directing the use of knowledge for problem-solution, and a User Interface that assists the user retrieve, use and alter data in the Knowledge Base. The developed Knowledge-Based System was compiled, implemented and validated with data of previously completed projects. The client could utilize the Knowledge-Based System to undertake proposed building projects

Most of the data mining projects generate information (summarized in the form of graphs and charts) for business executives and decision makers; however it leaves to the choice of decision makers either to use it or disregard it. The manual use of the extracted knowledge limits the effectiveness of data mining technology considerably. This chapter proposes an architecture, in which data mining module is utilized to provide continuous supply of knowledge to a rule based expert system. Proposed approach solves the knowledge acquisition problem of rule based systems and also enhances effective utilization of data mining techniques (i.e. by supplying extracted knowledge to rule based system for automated use). The chapter describes the details of a data mining driven rule based expert system applied in medical billing domain. Main modules of the system along with the final analysis of performance of the system have also been presented.

The model of RISK ANALYZER was implemented as Knowledge-based System for the purpose of undertaking risk analysis for proposed construction projects in a selected domain. The Fuzzy Decision Variables (FDVs) that cause differences between initial and final contract sums of building projects were identified, the likelihood of the occurrence of the risks were determined and a Knowledge-Based System that would rank the risks was constructed using JAVA programming language and Graphic User Interface. The Knowledge-Based System is composed a Knowledge Base for storing data, an Inference Engine for controlling and directing the use of knowledge for problem-solution, and a User Interface that assists the user retrieve, use and alter data in the Knowledge Base. The developed Knowledge-Based System was compiled, implemented and validated with data of previously completed projects. The client could utilize the Knowledge-Based System to undertake proposed building projects

This study seeks to develop a comprehensive model of consumer acceptance in the context of Smart Mobile Device (SMDs). This paper proposes an adaptation of the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT2) model that can be employed to explain and predict the acceptance of SMDs. Also included in the model are a number of external and new moderating variables that can be used to explain user intentions and subsequent usage behaviour. The model holds that Activity-based Usage and Device Characteristics are posited to moderate the impact of the constructs empirically validated in the UTAUT2 model. Through an important cluster of antecedents the proposed model aims to enhance our understanding of consumer motivations for using SMDs and aid efforts to promote the adoption and diffusion of these devices.

Models ofconsensus are used in the validation process to develop a basis for system performance. This paper develops two analytic models ofconsensus that can be useful in the validation process. The first model employs the binomial model to study the probability that the consensus judgment is correct or incorrect. This problem is critical for the validation of expert systems, since the model leads us to conclude that in some cases consensus judgment is not appropriate. That basic model is extended to account for both different levels of expertise and unequal prior odds. The second model is a Bayesian model of the use of consensus judgment and the validation process. There are two applications of the Bayesian model The first application ofthe Bayesian model finds that, in some cases, consensus judgment is not appropriate and to generate a hypothesis as to the conditions for the use of the consensus judgment. The second application compares an expert systems performance to the consens...

The automated verification tool is developed to help users in bui]ding or modifying a rulcbascd expert system. The design of this tool differs from that of other verification tools in two major components. First, this tool provides a front-end to existing expert system shells. [Jsers interact with their expert system through a user-friend] y interface. Al 1 rules are entered in simple “if-then” statements rather than an expert system shell language. Verification is performed in mcta-lanuagc before the rules arc translated to any specific expert system lanuagc. In addition, the tool provides a visual representation of the state of a knowledge base. The inference relationship among rules of a knowledge base is illustrated by a directed graph. ‘J’he tool automatica]l y performs verification and syntax checking. lJscrs are notified of errors and conflicts through popup message windows and by highlighting nodes in the graphical analyzer. l’hcsis Supervisor: Kenneth Haase Title: MIT’ Medi...

Dr. Dym is a Fellow of the Acoustical Society of America, the American Society of Mechanical Engineers, and the American Society of Civil Engineers. He was also the recipient of the Walter L. Huber Research Prize of the ASCE in 1980 and the Western Electric Fund Award of the New England Section of the ASEE in 1983. He was on the Editorial Board of the Journal of Sound and Vibration and has been an Associate Editor of the Journal of the Acoustical Society of America. Dr. Dym is also the founding Editor of the journal, Artificial Intelligence for Engineering Design, Analysis and Manufacturing (AI EDAM). He has published more than 55 archival journal articles and eight books.

This study seeks to develop a comprehensive model of consumer acceptance in the context of Smart Mobile Device (SMDs). This paper proposes an adaptation of the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT2) model that can be employed to explain and predict the acceptance of SMDs. Also included in the model are a number of external and new moderating variables that can be used to explain user intentions and subsequent usage behaviour. The model holds that Activity-based Usage and Device Characteristics are posited to moderate the impact of the constructs empirically validated in the UTAUT2 model. Through an important cluster of antecedents the proposed model aims to enhance our understanding of consumer motivations for using SMDs and aid efforts to promote the adoption and diffusion of these devices.

The problem of automatically reprogramming an expert system either to adjust for solving different types of computational problems or to improve run-time performance is addressed. A computeraided software engineering (CASE) method using artificial intelligence techniques to instantiate a concrete program from a given abstract expert system architecture is proposed. Our method, called expert system reification, is suitable for use in a large range of problem-solving behaviors. Reification combines meta-level programming with partial evaluation of the program. Expert system reification extends the above blend with a knowledge-based translation module, thus obtaining an efficient and portable expert system version. We demonstrate the method by applying it to STAREX, an electronic circuit pack troubleshooting expert system developed in PROLOG to derive automatically the corresponding C code, which is currently installed at one of the AT&T manufacturing facilities.

Healthcare sector contains large volumes of data. A large volume of health related data is in the form of graphics, images and text. Clinical decision support system is an old area of research but current Electronic Medical Records (EMR) has no decision support system that could create a proper relationship between relevant treatments against their respective diagnoses. This research has a unique idea to incorporate decision support system in EMR. Paper based environment has already been replaced with EMR but still medical providers are facing problems by choosing less relevant procedures, which may not produce the optimal result. Due to this reason claims rejection rate are high and payments are low in numbers. Focus of this research work is to provide a decision support system and to deliver focused knowledge in the form of relationship between diagnoses and their procedures. The system follows three steps to make a decision. Firstly, it checks the past claims for diagnosis and tr...

n the previous article, the concept of the ‘separation of Yin and Yang’ was described in its varied forms. While this term has historically been employed to describe the ultimate separation of Yin and Yang that occurs at death, it is also possible to perceive the subtler manifestations of this process even in incipient stages. It is important to note these are long-term problems. As we shall see, having an understanding of the aetiology of the condition is vitally important.

n the previous article, the concept of the ‘separation of Yin and Yang’ was described in its varied forms. While this term has historically been employed to describe the ultimate separation of Yin and Yang that occurs at death, it is also possible to perceive the subtler manifestations of this process even in incipient stages. It is important to note these are long-term problems. As we shall see, having an understanding of the aetiology of the condition is vitally important.

To simplify the TCM pattern of the zang-fu organs. Methods: A database of zang-fu syndromes was established. The relationship between the zang-fu syndromes was analyzed by means of frequency analysis, association rule, and-coefficient correlation. Results: The six zang-fu organs of the heart, liver, spleen, lung, kidney, and stomach prove to be the main components of the zang-fu pattern. The large intestine, small intestine, gallbladder, bladder, triple energizer, and pericardium have strong association and positive correlation with the above-mentioned six zang-fu organs, and their clinical symptoms can all be included into the symptoms of these six zang-fu organs. Conclusion: The traditional TCM pattern of six-zang and six-fu can be simplified into five-zang and one-fu.

The traditional approaches used for the development of expert systems are mainly based on the interaction between the knowledge engineer and domain expert .However, the role of user in development process has been undetermined. This paper represents the problem of the users which are not familiar with compiler, at the time of execution of source code. The source code have specific piece of information code written in a programming language L for which there is an interpreter, compiler, linker and editor .After execution of source code define in any language will provide standard error messages that can not be easily understandable by every users. The actual knowledge based software maintenance system carries out essentially error diagnosis and messages that are not user friendly, so the designed expert system will provide a user friendly help messages for beginners. Domain is specified as error messages of C compiler.

Argument for Hybridization This article describes our initial experience with building applications programs in a hybrid AI tool environment. Traditional AI systems developments have emphasized a single methodology, such as frames, rules, or logic programming, as a methodology that is natural, efficient, and uniform The applications we have developed suggest that naturalness, efficiency and flexibility are all increased by trading uniformity for the power that is provided by a small set of appropriate programming and representation tools The tools we use are based on five major AI methodologies: frame-based knowledge representation with inheritance, rule-based reasoning, LISP, interactive graphics, and active values Object-oriented computing provides a principle for unifying these different methodologies within a single system.

Most research in the area of rule mining tends to focus mining of either ‘classification rules’ or ‘association rules’, while ignoring ‘production rules’. Production rules are building blocks of rule based expert systems. This paper presents an algorithm for production rule mining. Algorithm matches two states of an object; current state and previous state - collectively termed as ‘record-couple’. The algorithm tries to find differences within a record-couple, and generates production rules from these differences. The proposed algorithm has been tested on synthetic data and then applied on actual data. The Algorithm is being used for supplying production rules to a rule based expert system which is applied in medical billing domain. The system is being used for finding knowledge oriented data inconsistencies in medical claims. Implementation of the algorithm is a demonstration of how data mining technology can be used for providing continuous supply of knowledge to rule-based expert...

Most research in the area of rule mining tends to focus mining of either 'classification rules' or 'association rules', while ignoring 'production rules'. Production rules are building blocks of rule based expert systems. This paper presents an algorithm for production rule mining. Algorithm matches two states of an object; current state and previous statecollectively termed as 'record-couple'. The algorithm tries to find differences within a record-couple, and generates production rules from these differences. The proposed algorithm has been tested on synthetic data and then applied on actual data. The Algorithm is being used for supplying production rules to a rule based expert system which is applied in medical billing domain. The system is being used for finding knowledge oriented data inconsistencies in medical claims. Implementation of the algorithm is a demonstration of how data mining technology can be used for providing continuous supply of knowledge to rule-based expert systems.

Artifical intelligence is a discipline engaged in the development and application of methods, tools and techniques for solving logically complex problems. These tools and techniques are now becoming accepted in computer applications in general and their use is proliferating rapidly in areas other than computer science. This paper reviews part of the existing artificial intelligence technology with a special view toward potential applications in manufacturing systems. The review includes automatic planning, learning, programming by examples, qualitative modelling and AI programming languages.

The study has utilized heuristic reasoning and the concept of Fuzzy Decision Variables in order to undertake the risk analysis of a proposed construction project in a selected domain The objectives included determining the sources of risks, obtaining the Fuzzy Decision Variables by deductive reasoning, identifying the types of risks prevailing in the project and the utilization of fuzzy set analysis in order to estimate the possible magnitudes of the risks. Five completed projects were analysed. For each project , a breakdown of the final contract sum into variations, remeasurement of provisional quantities, nominated subcontractors' accounts, nominated suppliers' accounts, loss and expense caused by disturbances of regular progress of the works, fluctuation in rates of labour and prices of materials was undertaken in order to derive the sources of risks, the Fuzzy Decision Variables and the subsequent risks. Fuzzy set analysis was used to calculate the possible magnitudes of the risks. Heuristic reasoning and fuzzy set analysis could be used in a composite framework to undertake the risk analysis of a proposed project in a selected domain.

Big data and traditional Chinese medicine (TCM) is a new interdisciplinary field quietly emerging in Chinese society. Internet of Things (IoT) sensor system technology is currently being developed to gather large volumes of personal data so that TCM, specifically herbal pharmaceutics, can be applied to treat acute and chronic diseases alike utilizing low cost, safe, and effective treatment protocols that have been prescribed in clinical practice for thousands of years. Through a survey of existing literature, this paper investigates what a future state of medicine may look like with the deployment of a big data TCM system as a means to enhance humankind's health and quality of life.

A Knowledge-Based System for the risk analysis of proposed building projects was developed for a selected client. The Fuzzy Decision Variables (FDVs) that cause differences between initial and final contract sums of building projects were identified, the likelihood of the occurrence of the risks were determined and a Knowledge-Based System that would rank the risks was constructed using JAVA programming language and Graphic User Interface. The Knowledge-Based System is composed a Knowledge Base for storing data, an Inference Engine for controlling and directing the use of knowledge for problem-solution, and a User Interface that assists the user retrieve, use and alter data in the Knowledge Base. The developed Knowledge-Based System was compiled, implemented and validated with data of previously completed projects. The client could utilize the Knowledge-Based System to undertake proposed building projects

Recognizing and detecting system problems by any human intelligent is a complicated process which demands high technical-know-how just as simple problem could take hours or even days to solve. Expert systems use human knowledge often stored as rules within the computer to solve problems that generally would entail human intelligence. This paper proposes a stored-knowledge based troubleshooting and diagnosing system that mimic human intelligence in solving system problems. The system is composed of a user interface, a knowledge-base, an inference engine, and a stored-knowledge based system interface including an intelligent agent that assists in the knowledge acquisition process. The stored-knowledge based system is meant to automate troubleshooting and diagnosis of system problems that ordinarily would have been carried out manually by human intelligence, which is laborious, costly, and time consuming. The developed system used backward chaining approach to infer the rules while the forward chaining approach is left as future work.