Generation Expert Systems Research Articles

A Proprietary Language-Based Automatic Code Generation Expert System with Wider Business Applications

A Proprietary Language-Based Automatic Code Generation Expert System with Wider Business Applications

Elaboration of an Expert System for Sizing, Designing and Verifying Flexible Pavements

The use of expert systems in the world of civil engineering, and in particular for roads, has become a necessity for the reason of the particularity, complexity, and diversity of the influencing parameters at the level of the design calculation, the latter of which represents the major source of subsequent degradation. This system consists of proposing a tool for helping the user firstly to size the body of the roadway, with several analytical methods and models (Pre-project, Boussinesq, Westgaard, and Burmister), and secondly, to offer different design possibilities (thickness and type of the material) that make up the layers. Lastly, it is to calculate the stresses and strains in order to compare them with admissible limits. The management of a knowledge base of complex natures (words, sentences, numbers, symbols, tables, calculation methods, equations, conditions, etc.) requires an adequate methodology which goes beyond the simple use of the technology but enables you to imagine the process of regrouping this mass of complex data and classifying the data, which can then be integrated into a database or spreadsheets and external programs designed with code compatible with the expert system generator. Our contribution relates initially to the formulation, organization, and preparation of the algorithms, and then the starting of the programs in order to conceive fully executable programs, the latter of which we can call the expert system. The validation of such a system was made as the work progressed, changes were made in the formulation of the rules, and the order and orientation of the data in the knowledge that the advantage of this type of system is the possibility of permanently reinforcing the database with human expertise in the field, or in books, especially so that we can avoid data loss due to illnesses, retirement, etc.

A Conceptual Model of Mobile Expert System for Integrated Pest and Disease Control: The Case of MyCorn

The study of plant disease detection systems development has become very popular especially after the introduction of precision agriculture and the widespread use of mobile computing in almost all area including agriculture. While there exist an abundance of frameworks or models, however, given the unique nature of pest and disease management influenced by the different types of cultivation setting such as location, history, soil and the threat’s, research in this area is still needed. In addition, crop disease and pest detection is a complex task requiring accumulated knowledge and expertise as well as collecting detailed information very often manually. Therefore, on the basis of generic expert system model, this research aims to develop a conceptual model of mobile expert system for pest and disease management. Drawing from the case study of MyCorn development project, this study specifically offers a conceptual model of mobile application which offers a collaborative platform for integrated corn crop disease and pest diagnosis, treatment, and protection. The findings also offer useful practical insights for those who are seeking to build similar expert system for agriculture crops other than corn.

Analysıs of Stages of Development, Current State and Prospects of the Expert Systems

The objects of the study are stages of development and modern state. In general terms, expert systems are knowledge-based systems. This paper focuses on the components and principles of expert systems. Expert systems are also described. The components of expert systems include knowledge base, logical impact mechanism, user interface and decision-making. In addition, this article describes the capabilities of expert systems. One challenge is to identify the future prospects of expert systems. The research examined the expert system and its significance. It also focuses on generations of expert systems. The first generation of expert systems includes systems created before 1990. This article discusses SAINT, DENDRAL and HEARSAY-1. The features of this expert systems are also discussed here. First-generation expert systems are research prototypes. As a result, the foundations of artificial intelligence were developed. Mostly first-generation expert systems were used as a passive assistant expert. The second generation of expert systems refers to systems created since 1990. Features of second-generation expert systems include dynamism, interactivity, and processing of disparate knowledge. Unlike first-generation expert systems, these systems are able to test the completeness of the knowledge base, to process fuzzy knowledge. Their main difference is the ability to integrate second-generation expert systems with existing systems. At the moment, statistical and dynamic expert systems are distinguished. This article describes the current status of both types. Here are also discussed the tools of statistical and dynamic expert systems. At the end, possible prospects of expert systems are received.

A Framework for Evaluating the Standards for the Production of Airborne and Ground Traffic Management Software

The development of Airborne and Ground systems is framed by specific regulations, usually expressed as standards. A disadvantage of those standards is the inherent complexity for its application and the verification of compliance given the high number of requirements to be checked in many different situations of the application and which are highly dependent on the applicable level of criticality. When the development of this type of system requires the incorporation of new personnel without enough knowledge about the standards, risks of mistakes in their application grow exponentially. The objective of this work is to develop an Expert System (ES) that helps to evaluate the application of the standards DO-178C and DO-278A throughout the project life cycle, at the same time it serves to facilitate both its use and the learning of its application to a wide group of professionals. The proposed underlying method for the ES will allow evaluating the set of development processes to check coverage of the standards DO-178C and DO-278A without depending on a specific life cycle model. The method involves a model of the set of processes, so they can be evaluated by the ES. Additionally, the ES will require a minimum configuration to evaluate the development of systems based on these two standards. The main result is a new generic Expert System based on rules capable of being adapted to different environment of evaluation, whichh minor configuration operations thus allowing that a Generic ES can act as a Specific ES for each situation. This configurable ES has been customized to evaluate the software life cycle based on the standards under study.

G3MD: Mining frequent opcode sub-graphs for metamorphic malware detection of existing families

Attackers leverage various obfuscation techniques to create a metamorphic malware that can evade from detection by anti-malwares. To defeat, we propose Graph Mining for Metamorphic Malware Detection (G3MD), an intelligent system for static detection of metamorphic malwares. G3MD demonstrates one of the many aspects of what the current generation of machine-learning techniques and expert systems can do. It extends what is known about practical application of machine-learning techniques in the field of information security. It is intended to alleviate the burden of human experts and underlying costs. The novelty of G3MD is to apply graph mining on the opcode graphs of a metamorphic family of malwares to extract the frequent sub-graphs, so called micro-signatures. Based on these sub-graphs, a classifier is trained to distinguish between a benign file and a metamorphic malware. We conducted experiments on four families of metamorphic malwares common in previous studies, namely Next Generation Virus Generation Kit (NGVCK), Second Generation Virus Generator (G2), and Mass Produced Code Generation Kit (MPCGEN) viruses and Metamorphic Worm (MWOR) worms. The precision (over 99% in most cases) of metamorphic malware detection by the proposed approach corroborates its effectiveness over other existing approaches.

Surveillance scene representation and trajectory abnormality detection using aggregation of multiple concepts

Use of CCTV is growing rapidly in surveillance applications. Rapid advancement in machine learning and camera hardware has opened-up adequate scopes to build next generation of expert systems aiming at understanding surveillance environments automatically by detection of trajectory abnormality through analyzing object behavior. Such intelligent surveillance systems should be able to learn and combine multiple concepts of abnormality in real-life scenario and classify the events of interest as normal or abnormal. Primary challenges of such systems are to represent and learn patterns in surveillance scenes and combine multiple concepts of abnormalities to activate the alarm system.This paper presents a graph-based representation of a given surveillance scene and learning of relevant features including origin, destination, path, speed, size, etc. These features are combined and correlated with target behaviors to detect abnormalities in moving object trajectories. We also propose an aggregation method that reduces the number of missed alarms during aggregation. Several cases using publicly available surveillance video datasets have been presented and the results indicate that the proposed method can be useful to design intelligent and expert surveillance systems.

Identification of wavelengths from the visible spectrum by means of Arduino for the generation of a knowledge base managed by PROLOG

PROLOG is a programming language widely used in the generation of expert and intelligent systems, generally limited to data that is entered directly by a user in the form of software, having little or no interaction with data that is captured directly from a physical environment. This paper presents an implementation of an interface that detects the wavelengths of the visible spectrum, that is, identifies colors, colors that are stored in a knowledge base and then managed by PROLOG. This interface consists of two parts, software and hardware. The hardware is designed by means of the Arduino UNO development board, where a TCS3200 sensor is used. For the development of the software, two tools have been used, on the one hand, the standard programming of the Arduino IDE terminal has been used to manage the inputs and outputs of the Arduino board, and on the other hand, a data management system has been generated, in which PROLOG manages all the data obtained from hardware. This scheme seeks to generate color classifications in a dynamic and intelligent way in the future. The proposed system has the advantage that it is highly economical, easy to perform, uses the logical paradigm of programming, and opens the way to the design of intelligent systems managed by PROLOG from a monitoring of physical variables.

The Development of AudEx: An Audit Data Assessment System

ABSTRACTTools to assist auditors in making sound, complete, and consistent judgements have become increasingly important due to regulation, litigation, and the desire to increase audit effectiveness. Historically, expert systems have been problem specific and created from scratch. Such systems were challenging to update and had limited adaptability when applied to additional problem spaces. If an adaptable system is possible, then costs and time may be reduced related to production, testing, and implementation of quality audit tools. Increased availability of such tools could be a tremendous benefit to auditors. Using a design science research method, this paper describes the process used to create a fraud risk assessment audit tool by embedding audit rules into a generic expert system shell that is widely used in the medical field. The resulting decision and training aid can assist auditors in making fraud risk assessments. While prior research has addressed many components of the issue, the current system was created to address the current risk environment, and a variety of contexts of interest, as the risk environment changes. The system was evaluated by practicing auditors while completing a series of cases. Evaluation results support the benefits of the artifact when used to assist in fraud risk assessments.

The Development and Research of the Automatic Generation of Expert System of Garment Cad Pattern

The development and research of the automatic generation of expert system of Garment Cad Pattern will change the traditional garment pattern design concept and design tools to enable advanced CAD technology and expertise in China's garment industry work together, which will greatly improve the level of the software sustainable development and intellectualization. It will be proved through constant practice to help improve the professional level of the garment pattern CAD software, create new ways of professional popularization and application which are suitable for China's national conditions.

The Development and Research of the Automatic Generation of Expert System of Garment Cad Pattern

The development and research of the automatic generation of expert system of Garment Cad Pattern will change the traditional garment pattern design concept and design tools to enable advanced CAD technology and expertise in China's garment industry work together, which will greatly improve the level of the software sustainable development and intellectualization. It will be proved through constant practice to help improve the professional level of the garment pattern CAD software, create new ways of professional popularization and application which are suitable for China's national conditions.

New construction for expert system based on innovative knowledge discovery technology

Knowledge acquisition is the bottleneck of expert system. To solve this problem, KD (DK KDK*—the new process model based on double-basis fusion mechanism are introduced, respectively. The overall framework of ESKD is proposed. Some sub-systems and dynamic knowledge base system are discussed. Finally, the effectiveness and advantages of ESKD are tested in a real-world agriculture database. We hope that ESKD may be useful for the new generation of expert systems.

THE DEVELOPMENT DESIGN MODEL IN THE COMPETITIVENESS OF INTELLIGENT BUSINESS ORGANISATIONS

Croatian hotel and tourism companies are failing to keep abreast of modern tourism trends in the globalised marketplace of the twenty-first century. The imperative is to innovate the development design model based on a new value system. A precondition to success is transforming sluggish, inert companies that live according to the mindset of the past century into high-growth intelligent organisations capable of actively creating the future.The intelligent business organisation, founded on a new generation of managers, employee empowerment, software solutions and expert systems, needs to manage data and information to generate new development trends. The aim is to valorise intellectual capital and information in making innovations and creating new solutions in order to be able to stand up to rivals and more fully meet the needs of clients.

Expert Systems

The paper gives an overview of expert systems discussing all aspects concerned with them. Starting with the definition and evolution of expert systems the paper tells how, from the traditional mainstream of Artificial intelligence the growth of expert systems took place. Then the architecture and working of expert system is analyzed, giving details about the working of each component and its functions. Expert system shells and blackboards which have become an integral part of expert systems are also analyzed. Inference mechanisms used in expert systems and the design considerations while creating an expert system are also considered. Lastly the paper concludes with a case study of MYCIN (a famous expert system) and the challenges before the current expert systems to reach the next generation of expert systems.

A Modular Approach to the ECVAM Principles on Test Validity

The European Centre for the Validation of Alternative Methods (ECVAM) proposes to make the validation process more flexible, while maintaining its high standards. The various aspects of validation are broken down into independent modules, and the information necessary to complete each module is defined. The data required to assess test validity in an independent peer review, not the process, are thus emphasised. Once the information to satisfy all the modules is complete, the test can enter the peer-review process. In this way, the between-laboratory variability and predictive capacity of a test can be assessed independently. Thinking in terms of validity principles will broaden the applicability of the validation process to a variety of tests and procedures, including the generation of new tests, new technologies (for example, genomics, proteomics), computer-based models (for example, quantitative structure-activity relationship models), and expert systems. This proposal also aims to take into account existing information, defining this as retrospective validation, in contrast to a prospective validation study, which has been the predominant approach to date. This will permit the assessment of test validity by completing the missing information via the relevant validation procedure: prospective validation, retrospective validation, catch-up validation, or a combination of these procedures.

Metabonomics: Its Potential as a Tool in Toxicology for Safety Assessment and Data Integration

The functional genomic techniques of transcriptomics and proteomics promise unparalleled global information during the drug development process. However, if these technologies are used in isolation the large multivariate data sets produced are often difficult to interpret, and have the potential of missing key metabolic events (e.g. as a result of experimental noise in the system). To better understand the significance of these megavariate data the temporal changes in phenotype must be described. High resolution 1H NMR spectroscopy used in conjunction with pattern recognition provides one such tool for defining the dynamic phenotype of a cell, organ or organism in terms of a metabolic phenotype. In this review the benefits of this metabonomics/metabolomics approach to problems in toxicology will be discussed. One of the major benefits of this approach is its high throughput nature and cost effectiveness on a per sample basis. Using such a method the consortium for metabonomic toxicology (COMET) are currently investigating approximately 150 model liver and kidney toxins. This investigation will allow the generation of expert systems where liver and kidney toxicity can be predicted for model drug compounds, providing a new research tool in the field of drug metabolism. The review will also include how metabonomics may be used to investigate co-responses with transcripts and proteins involved in metabolism and stress responses, such as during drug induced fatty liver disease. By using data integration to combine metabolite analysis and gene expression profiling key perturbed metabolic pathways can be identified and used as a tool to investigate drug function.

Adding decision support to workflow systems by reusable standard software components

Industrial information systems like Enterprise Resource Planning (ERP) systems are increasingly comprehensive and integrated. Nevertheless, satisfying all the user requirements regarding information processing or decision support within a unique tool seems still to be unrealistic. As a consequence, being able to quickly provide the users with additional pieces of software for supporting specific decisions remains more than ever a topic of interest. Specific developments take time, are costly, have usually low reliability and are often poorly integrated with the main information system. In order to address these drawbacks, we suggest a structure and the first elements of a toolbox aimed at allowing an easier development of additional pieces of information/decision support system (DSS) by reuse of standard software components. This toolbox allows the implementation of workflow and groupware facilities and the communication between modules is achieved through a database which provides the integration with the main information system. The first decision support modules developed include an expert system generator, a neural network simulator, a simplex module and a Case-Based Reasoning (CBR) module. Examples of applications developed using this toolbox are described, and a development methodology is suggested.

An expert system for generation of anti-G control schedule for jet fighter pilots

Abstract The high maneuverability of modern jet fighters often subjects the pilots to high G z acceleration. One of the adverse effects of G z acceleration is the G -induced loss of consciousness. The current protection scheme includes a pressure mask that supplies the pilots with nominal positive pressure breathing and a nominal pressurized G -suit. This paper presents a novel approach based on a combination of expert knowledge, pilots' anthropometric and physiologic data to generate control schedules of the G -suit and mask pressures of jet fighter pilots.

Research on hybrid expert system application to blanking technology

This paper introduces the application of a second generation expert system in blanking technology. Depending on the empirical knowledge of domain experts and field literature, an expert system can play an important role in the field of blanking technology. An object-oriented blackboard model is given which can realize hybrid knowledge representation, such as production rules, frameworks and procedures. This paper mainly discusses the structure of the blackboard model and hybrid knowledge representation in blanking technology expert system. Since strip layout is a crucial and determining part in blanking technology, given here is an example of a blackboard model supporting hybrid knowledge representation about the strip layout process.

Diagnostics and a qualitative model

First generation expert systems were using shallow knowledge based on heuristic information to solve a diagnostic problem. This approach has many disadvantages, which can be avoided by using deep knowledge. Diagnostic reasoning based on deep knowledge is called model-based diagnostics. Recently, the use of qualitative modeling in relation to deep knowledge in expert systems has become increasingly important. The main purpose of our contribution is to present the model-based diagnostic approach at a formal level. The originality of the presented formalization is the concept of the diagnostic space, the characterization of the minimal diagnoses, and the measurement. The formalization serves as the theoretical background to prove our view to the design of qualitative system models and to establish the diagnostic architecture called DISY. The qualitative system model in our diagnostic approach needs not to be specially adopted for use in the diagnostic domain. The only requirement is that it must simulate the system behavior expressed by normal or abnormal functioning of its components. Proposed DISY architecture is not complex and simply takes into an account the previous diagnostic result to obtain a new one from the additional observation-measurement (medical tests or examinations) of the system.