Expert system technology

The expert system is a computer program which attempts to reproduce the problem-solving behavior of an expert, who is able to view problems from a broad perspective and arrive at conclusions rapidly, using intuition, shortcuts, and analogies to previous situations. Expert systems are a departure from the usual artificial intelligence approach to problem solving. Researchers have traditionally tried to develop general modes of human intelligence that could be applied to many different situations. Expert systems, on the other hand, tend to rely on large quantities of domain specific knowledge, much of it heuristic. The reasoning component of the system is relatively simple and straightforward. For this reason, expert systems are often called knowledge based systems. The report expands on the foregoing. Section 1 discusses the architecture of a typical expert system. Section 2 deals with the characteristics that make a problem a suitable candidate for expert system solution. Section 3 surveys current technology, describing some of the software aids available for expert system development. Section 4 discusses the limitations of the latter. The concluding section makes predictions of future trends

Solving large scale Max Cut problems via tabu search

In recent years many algorithms have been proposed in the literature for solving the Max-Cut problem. In this paper we report on the application of a new Tabu Search algorithm to large scale Max-cut test problems. Our method provides best known solutions for many well-known test problems of size up to 10,000 variables, although it is designed for the general unconstrained quadratic binary program (UBQP), and is not specialized in any way for the Max-Cut problem

Building a four year post-secondary curriculum in educational science and technology

This report begins by providing background information on educational technology in the Netherlands, differences between a four-year program in the Netherlands and undergraduate programs in the United States, and the structure of Dutch university programs. The need for a Department of Educational Science and Technology at the Twente University of Technology and characteristics of the department are then addressed, followed by a discussion of the starting points and procedure of curriculum planning and a description of the structure of the curriculum. Activities involved in carrying out the plans--course construction, development of the TO-laboratory (a computer, audiovisual, and learning resource center), and student recruitment--are also discussed. The report concludes with an evaluation of the program at the end of the first year of operation. This evaluation focused on the effects of modular course construction, and the interrelationships of courses, study load, and number of possible drop-outs. Four appendixes provide: (1) the results of a job analysis of the tasks performed by professionals in the field that was undertaken as part of the curriculum planning process; (2) an outline of the department's curriculum; (3) a general model for structured problem solving; and (4) a floor plan of the TO-laboratory. (MES

MAD Version 9

The program MAD is widely used for accelerator design and beam dynamics studies. For many years, its input language has been the nearest thing to a world-wide standard for describing accelerator structures. The new Version 9 is a complete rewrite using a systematic object-oriented methodology based on the CLASSIC classes [2] for accelerator physics. It provides many improvements over the previous MAD Version 8. These include: (i) support for multiple beam-lines simultaneously, facilitating, for example, matching constraints that couple the two rings of a two-ring collider, (ii) much improved Lie-algebraic map calculations, (iii) a uniform method and format for exchanging many kinds of structured data with other programs, (iv) an improved and more consistent input language. In addition, we report on a parallel 3D Poisson field solver for space charge calculations in high intensity particle beams. Applied to the PSI injector cyclotron, this shows the general nature of MAD Version 9 as a state-of- the-art problem-solving environment. We describe the current status of the program and how to get it, outline future plans and illustrate some of the new features

Systems Engineering Self Assessment of an Air Force Acquisition Unit

In February of 2009, our unit performed a Systems Engineering {SE} Self Assessment using the Air Force Systems Engineering Assessment Model (AF SEAM}. The AF SEAM consists of 190 SE best practices spanning the following ten SE Process Areas: Configuration Management, Decision Analysis, Design, Manufacturing, Project Planning, Requirements, Risk Management, Sustainment, Technical Management and Control, and Verification and Validation. During the SE Self Assessment, we graded our unit on a pass/fail basis for each SE best practice. The SE best practices are split into Specific Practices and General Practices. The former only apply to one of the ten SE Process Areas, while the later apply to all ten SE Process Areas. The unit\u27s score for each SE Process Area is an average of the percentage of passing Specific Practices and the percentage of passing General Practices. Our unit received passing grades for Configuration Management, Manufacturing, and Sustainment; and failing grades for Decision Analysis, Design, Project Planning, Requirements, Risk Management, Technical Management and Control, and Verification and Validation. In addition to grading the unit\u27s SE based on best practices, the SE Self Assessment collected the participants\u27 comments. This report is an analysis of these comments; the intent of this report is to capture useful comments and distill them into actionable findings. Analysis of the SE Self Assessment uncovered 120 key findings that fall into 20 SE problems. In an attempt to hone in on the most pressing SE problems, each problem was evaluated based on the number of findings per problem, the feasibility of solving the problem, and the potential gain for solving the problem. As a result of this evaluation, the top SE problems facing our unit are as follows: inadequate communication, insufficient training, and unclear roles and responsibilities. In order to address these SE problems, this report recommends the following: Inadequate Communication: The unit should matrix four people into the Development Squadron covering the following disciplines: Configuration Management, Information Assurance, Requirements, and Test and Evaluation. These Systems Engineers would report to the Engineering Division Chief, but they would work with the Development Squadron on a day to day basis. Insufficient Training: The unit should pursue an aggressive training program to improve general and SE knowledge. The following courses and presentations should be developed: Unit 101 as a newcomers orientation, Intro to the Systems Engineering Plan and Intro to the Systems Test Plan to socialize these important documents, Integrated Product/Process Team (IPT) Training to improve our teaming skills, Eight Step Problem Solving Method as a Decision Analysis tool, and AF SEAM Mastery as a way to use the model to teach basic SE principles. Also, the unit leadership should encourage personnel to enroll in SE certificate and masters programs. Unclear Roles and Responsibilities:The unit should assign a SE Process Champion to each of the ten SE Process Areas. These champions would be the focal people for improving each area. Also, a SE Process Improvement Lead should be created. The SE Process Improvement Lead and the SE Process Area Champions would work towards the goal of achieving passing marks in the next SE Self Assessment held in February, 2010. Note: All of the material contained in this report has been scrubbed to remove references to people, as well as project names. For example, a specific hardware intensive project is described as hardware project instead of its name. Other generalizations include the following: software project, technology demonstration (tech demo} project, component, contractor, and FFRDC. The reader\u27s patience is appreciated when these sanitization efforts sometimes result in incongruent phrases. A note on tense: This paper uses the first person tense. This is intentional. I am a member of the unit studied, and thus I stand to benefit or suffer from the consequences of any implementation suggested in this report. Exclusive use of the third person would imply a distance and impartiality that does not exist

Workforce Preparedness of Information Systems Students: Perceptions of Students, Alumni, and Employers

Employers of newly hired higher education graduates report their new workforce is not prepared. Further research was required to discover insights to the workforce readiness gap. This concurrent mixed methods study explored what competencies influenced employer\u27s perceptions of the work-readiness of Information Systems (ISYS) undergraduate students and discovered ISYS graduates\u27 and current ISYS students\u27 perceptions of their work-readiness. Participants consisted of a convenience sample including 69 ISYS program upperclassmen, 20 ISYS program alumni, and 8 employers of the ISYS program graduates. ISYS program alumni completed an online Qualtrics survey to measure the participants\u27 perception of their workforce preparedness. ISYS program upperclassmen completed a similar paper-based survey to measure the students\u27 current perception of their workforce readiness. Employers of ISYS program graduates were interviewed to determine (1) how they defined workforce readiness, (2) the competencies associated with being workforce-ready, and (3) the degree to which the Sam M. Walton College of Business graduates demonstrated workforce readiness. The instrument used in this study was adopted from the employer survey used in the Are They Really Ready to Work?: Employers\u27 Perspectives on the Basic Knowledge and Applied Skills of New Entrants to the 21st Century U.S. Workforce report by Casner-Lotto, Barrington, & Wright (2006) and the Ill-Prepared U.S. Workforce: Exploring the Challenges of Employer-Provided Workforce Readiness Training report by Casner-Lotto, Rosenblum, & Wright (2009). The reports were produced by ASTD, The Conference Board, Corporate Voices for Working Families, Partnership for 21st Century Skills, and SHRM. Research findings demonstrated 91% of ISYS program alumni and 86.9% of upperclassmen believed they were adequately to well prepared for the workforce by the ISYS program. Additionally, 75% of ISYS graduates\u27 employers felt the students were adequately to somewhat well prepared for the workforce. Workforce readiness skills measured in this study included English Language (spoken), Writing in English, Problem Solving, Critical Thinking, Collaboration/Working with Others, Computer/Technical, Project Management, Knowledge within Major, General Business Knowledge, Willingness to Learn, Ability to Learn, Responsibility/Dependability, Initiative, Attitude Toward Work, Attendance/Punctuality, and Other skills not mentioned

Human-Centered Technologies and Procedures for Future Air Traffic Management: A Preliminary Overview of 1996 Studies and Results

In this project, we have been exploring the use of a general methodology to predict the impact of future Air Traffic Management (ATM) concepts and technologies. In applying this methodology, our emphasis has been on the importance of modeling coordination and cooperation among the multiple agents within this system, and on understanding how the interactions among these agents will be influenced as new roles, responsibilities, procedures and technologies are introduced. To accomplish this, we have been collecting data on performance under the current air traffic management system, trying to identify critical problem areas and looking for exemplars suggestive of general approaches for solving such problems. Based on the results of these field studies, we have developed a set of scenarios centered around potential future system designs, and have conducted studies using these scenarios involving a total 40 controllers, dispatchers, pilots and traffic managers. The purpose of this report is to provide NASA with an early summary of the major recommendations that have resulted from our research under the AATT Program thus far. Recommendations 1-3 deal with general approaches that our findings suggest should be incorporated in future AATT Program activities, while Recommendations 4-11 identify some specific topics and technologies that merit research and development activities. Detailed technical reports containing supporting data, as well as the results of our still ongoing analyses, will be provided at a later date. The remainder of this report is organized as follows. Section 1 briefly describes the general design philosophy supported by our empirical studies. Section 2 presents the research methods we have used for identifying requirements for future system designs and for evaluating alternative design solutions. Section 3 discusses preliminary results from an initial set of investigations that we have conducted using these research methods. Section 4 then provides an overall summary. An outline of the rest of this preliminary project summary is provided on the following page

What Makes A Court Problem-Solving: Universal Performance Indicators for Problem-Solving Justice

This report identifies a set of universal performance indicators for specialized "problem-solving courts" and related experiments in problem-solving justice. Traditional performance indicators related to caseload and processing efficiency can assist court managers in monitoring case flow, assigning cases to judges, and adhering to budgetary and statutory due process guidelines. Yet, these indicators are ultimately limited in scope. Faced with the recent explosion of problem solving courts and other experiments seeking to address the underlying problems of litigants, victims, and communities, there is an urgent need to complement traditional court performance indicators with ones of a problem-solving nature. With funding from the State Justice Institute (SJI), the Center for Court Innovation conducted an investigation designed to achieve three purposes. The first was to establish a set of universal performance indicators against which to judge the effectiveness of specialized problem-solving courts, of which there are currently more than 3,000 nationwide. The second purpose was to develop performance indicators specific to each of the four major problem-solving court models: drug, mental health, domestic violence, and community courts. The third purpose was to assist traditional court managers by establishing a more limited set of indicators, designed to capture problem-solving activity throughout the courthouse, not only within a specialized court context

Problem Lah! Learning to Tell the Story of Continuous Assessment and Improvement

To succeed organizations rely on the purposeful application of the management functions, planning, organizing, leading and controlling, i.e., assessment. Assessment involves the collection and analysis of service and performance data to inform planning, organizing and leading-- opening the door to a culture of assessment and continuous improvement. Like other organizations responding to ever challenging economies and ever changing customer expectations, libraries are examining continuous improvement methods such as Lean, or Six Sigma, to ensure operations and services are customer focused and can be continuously assessed and improved with limited resources. Librarians though, often lack a general understanding of assessment and continuous improvement methods and may be reluctant to implement. At the Li Ka Shing Library, staff and librarians are taking advantage of the University’s Lean Six Sigma green belt certification program to learn the methods of data gathering and measuring performance outcomes to continually assess and improve services and processes, i.e., ensure operational strength (a University strategic initiative). To help staff and librarians tell the story of their improvements and to reinforce management competencies learned in the Lean Six Sigma training, the A3 method of problem solving is being used to report progress and practice demonstrating the value of their contributions to the University’s stakeholders