An Expert Systems Approach to Realtime, Active Management of a Target Resource

The application of expert systems techniques to process control domains represents a potential approach to managing the increasing complexity and dynamics which characterizes many process control environments. This thesis reports on one such application in a complex, multi-agent environment, with an eye toward generalization to other process control domains. The application concerns the automation of large computing system operation. The requirement for high availability, high performance, computing systems has created a demand for fast, consistent, expert quality response to operational problems, and effective, flexible automation of computer operations would satisfy this demand while improving the productivity of operations. However, like many process control environments, the computer operations environment is characterized by high complexity and frequent change, rendering it difficult to automate operations in traditional procedural software. These are among the characteristics which motivate an expert systems approach to automation. JESQ, the focus of this thesis, is a realtime expert system which continuously monitors the level of operating system queue space in a large computing system and takes corrective action as queue space diminishes. JESQ is one of several expert systems which comprise a system called Yorktown Expert System/MVS Manager (YES/MVS). YES/MVS automates many tasks in the domain of computer operations, and is among the first expert systems designed for continuous execution in realtime. The expert system is currently running at the IBM Thomas J. Watson Research Center, and has received a favorable response from operations staff. The thesis concentrates on several related issues. The requirements which distinguish continuous realtime expert systems that exert active control over their environments from more conventional session-oriented expert systems are identified, and strategies for meeting these requirements are described. An alternative methodology for managing large computing installations is presented. The problems of developing and testing a realtime expert system in an industrial environment are described

Geneplanner: A Prototype of an expert system to assist with chemical DNA gene synthesis planning

Expert systems are a popular area of artificial intelligence. The development of an expert system involves the selection of an appropriate problem, acquisition of knowledge from the expert, selection of control mechanisms and knowledge repre sentations, selection of tools, implementation, and testing. This thesis describes the development of a prototype expert system in the area of genetic engineering. The prototype system suggests the fragments of DNA to chemically synthesize and the steps for joining these fragments in order to make a gene. The system follows the hueristic rules of an expert to select the fragments and strategy for synthesis, backtracking where necessary. After reviewing expert systems and the problem area, the thesis focuses on the development process. Each of the steps is discussed, and the iterative nature of implementation, testing, and refinement is displayed. Results are reviewed, showing Geneplanner to handle simple to moder ate cases fairly well. Finally, shortcomings are discussed and future enhancements are suggested

Fuzzy Expert Advisory for E-Counselling

Fuzzy Expert is designed to mimic the human decision process of the modular system, maintains the value of based rules and using fuzzy logic control the describe uncertainty systems and utilizes the predominance of using expert systems to denote and control knowledge (Medeiros et. al., 1998). This paper presents the development of Fuzzy Expert Advisory for e-Counselling. The advisory model in counseling using a modular system for the psychology testing process for Behavioural Academic Self-Esteem (BASE) is used to test the prototype developed in this study. The system was constructed using a modular system for the psychology testing process for Behavioural Academic Self-Esteem (BASE)is used to test the prototype developed in this study. The system was constructed using hierarchical structural approach. The system was developed using web-based application language that is Microsoft's Active Server Pages (ASP) the server-side web scripting. The system comprises of five modules, namely Student Initiative of BASE Factor 1, Social Attention of BASE Factor 2, Success. Failure of BASE Factor 3, Social Attraction of BASE Factor 4, and Self-Confidence of BASE Factor 5. BASE test consists of sixteen items, categorized into the five main BASE factors. The Input to the system was first fuzzified and Fuzzy Associative Memory (FAM) table were constructed to handle the fuzzy rules of the five factors of BASE case study. The defuzzification known as Centre of Area (COA) is used to estimate the BASE factor and determine the level of academic self-esteem such as low self-esteem , moderate self-esteem, and high self-esteem. In addition, fuzzy expert advisory provides explanation and also explain how a diagnosis is reached for a particular case. The results showed that the fuzzy expert prototype system presented in this paper provided a reliable and accurate outcome after several test cases have been performed. Overall performance of this system was successfully tested and produced the results that were equal to an expert's judgment, thus accomplishing the set goals. The system has been verified by the counselors and the results produced by the system conform to the BASE factor rating scale and sub-scores

A Water Treatment Case Study for Quantifying Model Performance with Multilevel Flow Modeling

Decision support systems are a key focus of research on developing control rooms to aid operators in making reliable decisions and reducing incidents caused by human errors. For this purpose, models of complex systems can be developed to diagnose causes or consequences for specific alarms. Models applied in safety systems of complex and safety-critical systems require rigorous and reliable model building and testing. Multilevel flow modeling is a qualitative and discrete method for diagnosing faults and has previously only been validated by subjective and qualitative means. To ensure reliability during operation, this work aims to synthesize a procedure to measure model performance according to diagnostic requirements. A simple procedure is proposed for validating and evaluating the concept of multilevel flow modeling. For this purpose, expert statements, dynamic process simulations, and pilot plant experiments are used for validation of simple multilevel flow modeling models of a hydrocyclone unit for oil removal from produced water. Keywords: Fault Diagnosis, Model Validation, Multilevel Flow Modeling, Produced Water Treatmen

Development of automated test system for diesel engines based on fuzzy logic

© 2016 IEEE.To control a diesel engine during testing, the principles of fuzzy output, which are widely used in fuzzy-logic controller development, could be applied. The controller's main task is to monitor an external object, in which case the behavior of the monitored object is described with the fuzzy rules. The most important application area of the fuzzy set theory is the fuzzy logic controllers. Their operation slightly differs from the operation of common controllers. In order to describe the system, the expert knowledge is used instead of differential equations. Control of the automation systems for engine testing (AST) with the fuzzy-logic controller should be based on a knowledge database with fuzzy rules. Such database could be created with expert knowledge, neural network, or direct measuring method. Development of an adaptive control system for diesel engine testing process based on the fuzzy logic enables simplification of the system's structural components and provision of discrete control procedure with some uninterruptible properties, which could improve the control and reduce the scope of the knowledge database. Fuzzy logic makes it simple to input a priory information about an object in the form of fuzzy control rules into the adaptive control system. Similarity of form and natural language relatively easy allows obtaining necessary expert knowledge. A prior information provides one of the key initial conditions of the system developed according to adaptive control method-the condition of supreme initial adaptation

Design of Control System Trainer Based on IoT as Electronic Learning Media for Natural Science Course

The development of controller system trainer based on Internet of Things (IoT) is one of the online learning media for practical activities that can motivate students in the natural science learning process so the student’s competence in learning can be achieved. One indicator of quality education is that their alumnus has a good knowledge, skills and attitudes. This study aims to develop an IoT-based trainer controller systems as a learning media in electronic 2 of natural science course. The trainer control system in this study used a website developed in accordance with the electronic 2 course which is connected to the trainers in the Electronic’s Laboratory via arduino uno microcontroller on trainer. This control system trainer is a development of basic physical law theory that emphasizes Kirchoff's laws using Maxwell's equations. Where the discussion in the electronics course 2 emphasizes the working principle of transistors. The research method used is the Research and Development (R&D) method with the product development model used is the Borg and Gall model. Product testing describes the design of assessment, type of data, data collection instruments and data analysis techniques. The instrument used in this study is a questionnaire for the material expert test and the media expert test. The data analysis technique used the content validity ratio (CVR) method. Based on the test result of material experts and media experts, the result of high validity was obtained. The result of blackbox testing get 100% results. Based on the test results, it can be concluded that the tool can work well which can remotely from a far using Arduino Mega and ESP8255 with the delay about 2 seconds. The test results for students' psychomotor skills get an average of 63.20 which means Good. So that this trainer control system can be used as a student independent learning media in natural science cours

Objective assessment of pilling of nonwoven fabrics using the two dimensional discrete wavelet transform

Fabric pilling is a serious problem for the apparel industry, causing an unsightly appearance and premature wear. Woolen products are particularly prone to pilling. Recently, a process for production of woolen nonwoven apparel fabrics has been commercialized in Australia, and may lead to new markets for Australian wool. However, the success of such nonwoven fabrics will partly rely on their propensity to pill. A key element in the control of fabric pilling is the evaluation of resistance to pilling by testing. Resistance to pilling is normally tested in the laboratory by processes that simulate accelerated wear, followed by a manual assessment of the degree of pilling by an expert based on a visual comparison of the sample to a set of test images. To bring more objectivity into the pilling rating process, a number of automated systems based on image analysis have been developed. The authors previously proposed a new method of image analysis based on the two-dimensional discrete wavelet transform to objectively measure the pilling intensity for woven fabrics. This paper presents preliminary work in extending this method to nonwoven fabrics.<br /

SLIM: an alternative Web interface for MEDLINE/PubMed searches – a preliminary study

BACKGROUND: With the rapid growth of medical information and the pervasiveness of the Internet, online search and retrieval systems have become indispensable tools in medicine. The progress of Web technologies can provide expert searching capabilities to non-expert information seekers. The objective of the project is to create an alternative search interface for MEDLINE/PubMed searches using JavaScript slider bars. SLIM, or Slider Interface for MEDLINE/PubMed searches, was developed with PHP and JavaScript. Interactive slider bars in the search form controlled search parameters such as limits, filters and MeSH terminologies. Connections to PubMed were done using the Entrez Programming Utilities (E-Utilities). Custom scripts were created to mimic the automatic term mapping process of Entrez. Page generation times for both local and remote connections were recorded. RESULTS: Alpha testing by developers showed SLIM to be functionally stable. Page generation times to simulate loading times were recorded the first week of alpha and beta testing. Average page generation times for the index page, previews and searches were 2.94 milliseconds, 0.63 seconds and 3.84 seconds, respectively. Eighteen physicians from the US, Australia and the Philippines participated in the beta testing and provided feedback through an online survey. Most users found the search interface user-friendly and easy to use. Information on MeSH terms and the ability to instantly hide and display abstracts were identified as distinctive features. CONCLUSION: SLIM can be an interactive time-saving tool for online medical literature research that improves user control and capability to instantly refine and refocus search strategies. With continued development and by integrating search limits, methodology filters, MeSH terms and levels of evidence, SLIM may be useful in the practice of evidence-based medicine

ViSpec: A graphical tool for elicitation of MTL requirements

One of the main barriers preventing widespread use of formal methods is the elicitation of formal specifications. Formal specifications facilitate the testing and verification process for safety critical robotic systems. However, handling the intricacies of formal languages is difficult and requires a high level of expertise in formal logics that many system developers do not have. In this work, we present a graphical tool designed for the development and visualization of formal specifications by people that do not have training in formal logic. The tool enables users to develop specifications using a graphical formalism which is then automatically translated to Metric Temporal Logic (MTL). In order to evaluate the effectiveness of our tool, we have also designed and conducted a usability study with cohorts from the academic student community and industry. Our results indicate that both groups were able to define formal requirements with high levels of accuracy. Finally, we present applications of our tool for defining specifications for operation of robotic surgery and autonomous quadcopter safe operation.Comment: Technical report for the paper to be published in the 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems held in Hamburg, Germany. Includes 10 pages and 19 figure

Reinforcement learning for efficient network penetration testing

Penetration testing (also known as pentesting or PT) is a common practice for actively assessing the defenses of a computer network by planning and executing all possible attacks to discover and exploit existing vulnerabilities. Current penetration testing methods are increasingly becoming non-standard, composite and resource-consuming despite the use of evolving tools. In this paper, we propose and evaluate an AI-based pentesting system which makes use of machine learning techniques, namely reinforcement learning (RL) to learn and reproduce average and complex pentesting activities. The proposed system is named Intelligent Automated Penetration Testing System (IAPTS) consisting of a module that integrates with industrial PT frameworks to enable them to capture information, learn from experience, and reproduce tests in future similar testing cases. IAPTS aims to save human resources while producing much-enhanced results in terms of time consumption, reliability and frequency of testing. IAPTS takes the approach of modeling PT environments and tasks as a partially observed Markov decision process (POMDP) problem which is solved by POMDP-solver. Although the scope of this paper is limited to network infrastructures PT planning and not the entire practice, the obtained results support the hypothesis that RL can enhance PT beyond the capabilities of any human PT expert in terms of time consumed, covered attacking vectors, accuracy and reliability of the outputs. In addition, this work tackles the complex problem of expertise capturing and re-use by allowing the IAPTS learning module to store and re-use PT policies in the same way that a human PT expert would learn but in a more efficient way