Location of concentrators in a computer communication network: a stochastic automation search method

The following problem is considered. Given the locations of the Central Processing Unit (ar;the terminals which have to communicate with it, to determine the number and locations of the concentrators and to assign the terminals to the concentrators in such a way that the total cost is minimized. There is alao a fixed cost associated with each concentrator. There is ail upper limit to the number of terminals which can be connected to a concentrator. The terminals can be connected directly to the CPU also In this paper it is assumed that the concentrators can bo located anywhere in the area A containing the CPU and the terminals. Then this becomes a multimodal optimization problem. In the proposed algorithm a stochastic automaton is used as a search device to locate the minimum of the multimodal cost function . The proposed algorithm involves the following. The area A containing the CPU and the terminals is divided into an arbitrary number of regions (say K). An approximate value for the number of concentrators is assumed (say m). The optimum number is determined by iteration later The m concentrators can be assigned to the K regions in (mk) ways (m > K) or (km) ways (K>m).(All possible assignments are feasible, i.e. a region can contain 0,1,…, to concentrators). Each possible assignment is assumed to represent a state of the stochastic variable structure automaton. To start with, all the states are assigned equal probabilities. At each stage of the search the automaton visits a state according to the current probability distribution. At each visit the automaton selects a 'point' inside that state with uniform probability. The cost associated with that point is calculated and the average cost of that state is updated. Then the probabilities of all the states are updated. The probabilities are taken to bo inversely proportional to the average cost of the states After a certain number of searches the search probabilities become stationary and the automaton visits a particular state again and again. Then the automaton is said to have converged to that state Then by conducting a local gradient search within that state the exact locations of the concentrators are determined This algorithm was applied to a set of test problems and the results were compared with those given by Cooper's (1964, 1967) EAC algorithm and on the average it was found that the proposed algorithm performs better.

Computer-Aided Reliability Analysis of Complicated Networks

A computer-aided procedure is described for analyzing the reliability of complicated networks. This procedure breaks down a network into small subnetworks whose reliability can be more readily calculated. The subnetworks which are searched for are those with only two nodes; this allows the original network to be considerably simplified.

Computer-Aided Reliability Analysis of Complicated Networks

A computer-aided procedure is described for analyzing the reliability of complicated networks. This procedure breaks down a network into small subnetworks whose reliability can be more readily calculated. The subnetworks which are searched for are those with only two nodes; this allows the original network to be considerably simplified.

A Perspective on Computer Assisted Assessment Techniques for Short Free-Text Answers

Computer Assisted Assessment (CAA) has been existing for several years now. While some forms of CAA do not require sophisticated text understanding (e.g., multiple choice questions), there are also student answers that consist of free text and require analysis of text in the answer. Research towards the latter till date has concentrated on two main sub-tasks: (i) grading of essays, which is done mainly by checking the style, correctness of grammar, and coherence of the essay and (ii) assessment of short free-text answers. In this paper, we present a structured view of relevant research in automated assessment techniques for short free-text answers. We review papers spanning the last 15 years of research with emphasis on recent papers. Our main objectives are two folds. First we present the survey in a structured way by segregating information on dataset, problem formulation, techniques, and evaluation measures. Second we present a discussion on some of the potential future directions in this domain which we hope would be helpful for researchers.

The computer simulation of primate (Macaca mulatta) spatial visual delayed response and cerebral prefrontal control function

Cerebral prefrontal function is one of the important aspects in neurobiology. Based on the experimental results of neuroanatomy, neurophysiology, behavioral sciences, and the principles of cybernetics and information theory after constructed a simple model simulating prefrontal control function, this paper simulated the behavior of Macaca mulatta completing delayed tasks both before and after its cerebral prefrontal cortex being damaged. The results indicated that there is an obvious difference in the capacity of completing delayed response tasks for the normal monkeys and those of prefrontal cortex cut away. The results are agreement with experiments. The authors suggest that the factors of affecting complete delayed response tasks might be in information keeping and extracting of memory including information storing, keeping and extracting procedures rather than in information storing process.

Evolution feature oriented model driven product line engineering approach for synergistic and dynamic service evolution in Clouds: four kinds of schema.

The proposed research will focus on developing a novel approach to solve Software Service Evolution problems in Computing Clouds. The approach will support dynamic evolution of the software service in clouds via a set of discovered evolution patterns. An initial survey informed us that such an approach does not exist yet and is in urgent need. Evolution Requirement can be classified into evolution features; researchers can describe the whole requirement by using evolution feature typology, the typology will define the relation and dependency between each features. After the evolution feature typology has been constructed, evolution model will be created to make the evolution more specific. Aspect oriented approach can be used for enhance evolution feature-model modularity. Aspect template code generation technique will be used for model transformation in the end. Product Line Engineering contains all the essential components for driving the whole evolution process.

Experiences with a knowledge engineering toolkit: an assessment in industrial robotics

V. Robinson, N. W. Hardy, D. P. Barnes, C. J. Price, M. H. Lee. Experiences with a knowledge engineering toolkit: an assessment in industrial robotics. Knowledge Engineering Review, 2 (1):43-54, 1987.

Knowledge engineering in robot control

N. W. Hardy, M. H. Lee, and D. P. Barnes. Knowledge engineering in robot control. In Proceedings of Expert Systems '83, pages 70-77, Cambridge, 1983.

Computer-Based Diagnostic Systems: Computer-Based Troubleshooting

ISBN: 3-540-76198-5 (out of print)