{"title":"The Systems Approach to Test Evaluation","authors":"David Bradley","doi":"10.1109/TSSC.1969.300264","DOIUrl":"https://doi.org/10.1109/TSSC.1969.300264","url":null,"abstract":"The evolution of large and sophisticated systems has created a requirement for extensive system tests programs. The argument that the change in scale of testing affects organizational communications so as to decrease the visibility provided by traditional management tools is presented. To attack this problem, a recommendation is made to establish a central test evaluation group with the primary goal of feeding back intelligence from the test program to the designers and managers. The concept of test \"intelligence\" is defined and a typical activity flow for the evaluation group is described. The general factors which determine the value of information are related to the specific variables of a test program. A rationale is developed for planning an evaluation approach based on the tradeoff between time invested in evaluation and the change in the value of the evaluation product (intelligence) as it ages. A functional approach to the reporting scheme is given. Report contents and timing are keyed to the program decision requirements. The potential benefits of a central, independent, and objective test evaluation are suggested for the designer, the manager, and the customer.","PeriodicalId":120916,"journal":{"name":"IEEE Trans. Syst. Sci. Cybern.","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1969-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122604634","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Strategy and a Tactic for Generation of Transportation Alternatives","authors":"P. Shuldiner, R. Nutter","doi":"10.1109/TSSC.1969.300271","DOIUrl":"https://doi.org/10.1109/TSSC.1969.300271","url":null,"abstract":"Transportation planning strategy is discussed in its relationship to overall regional development policy in the Northeast Corridor. A tactic currently being applied in the Northeast Corridor Transportation Project to generate alternative transportation system descriptions is presented.","PeriodicalId":120916,"journal":{"name":"IEEE Trans. Syst. Sci. Cybern.","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1969-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122666470","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Every norm is not logarithmically convex","authors":"A. Klinger","doi":"10.1109/TSSC.1969.300269","DOIUrl":"https://doi.org/10.1109/TSSC.1969.300269","url":null,"abstract":"This correspondence relates to the remark in a recent paper by D.G. Luenberger [ibid., vol. SSC-4, pp. 182-188, July 1968] that any norm defined on a vector space is a real convex function. Although this is a well-known fact in mathematics, a less well-known fact is that every logarithmically convex function is positive and convex, but not conversely, i.e., there are positive convex functions which are not logarithmically convex. As the above title indicates, norms are such functions. This mathematical remark relates to systems science through several areas of application where logarithmic convexity is a highly useful property. In particular, Klinger and Mangasarian [\"Logarithmic convexity and geometric programming,\" J. Math. Anal. and Appl., vol. 24, pp. 388-408, November 1968] mention optimization of multiplicative criteria, reliability theory, and electrical network synthesis, and examine geometric programming in detail.","PeriodicalId":120916,"journal":{"name":"IEEE Trans. Syst. Sci. Cybern.","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1969-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115031897","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Recursive Estimates of Probability Densities","authors":"C. Wolverton, T. Wagner","doi":"10.1109/TSSC.1969.300267","DOIUrl":"https://doi.org/10.1109/TSSC.1969.300267","url":null,"abstract":"","PeriodicalId":120916,"journal":{"name":"IEEE Trans. Syst. Sci. Cybern.","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1969-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127694928","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Development of a Community Health Service System Simulation Model","authors":"F. D. Kennedy","doi":"10.1109/TSSC.1969.300261","DOIUrl":"https://doi.org/10.1109/TSSC.1969.300261","url":null,"abstract":"The feasibility of using simulation techniques in community health planning by investigating problems associated with the development of a community health service system simulation model is examined. Two preliminary tasks were completed: a general systems analysis of the community health services and the preparation of a simulation model of one segment of this system. The system is described in terms of needs, demands, and resources. Various factors determine extent of the needs, conversion of the needs into demands, and availability of resources for satisfying the demands. This conceptual framework, the various factors, their significance, and an estimate of the extent of their control by a health planner were derived. A simulation model was developed using this framework and was based on a maternal and infant care program conducted by the North Carolina State Board of Health. The model was verified using data from three different communities within the program. Model processes are described; outputs are discussed; and potential model uses within a planning environment are presented.","PeriodicalId":120916,"journal":{"name":"IEEE Trans. Syst. Sci. Cybern.","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1969-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126679632","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Stochastic Learning of Time-Varying Parameters in Random Environment","authors":"Y. Chien, K. Fu","doi":"10.1109/TSSC.1969.300266","DOIUrl":"https://doi.org/10.1109/TSSC.1969.300266","url":null,"abstract":"The problem of learning in nonstationary environment is formulated as that of estimating time-varying parameters of a probability distribution which characterizes the process under study. Dynamic stochastic approximation algorithms are proposed to estimate the unknown time-varying parameters in a recursive fashion. Both supervised and nonsupervised learning schemes are discussed and their convergence properties are investigated. An accelerated scheme for the possible improvement of the dynamic algorithm is given. Numerical examples and an application of the proposed algorithm to a problem in weather forecasting are presented.","PeriodicalId":120916,"journal":{"name":"IEEE Trans. Syst. Sci. Cybern.","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1969-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129309037","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Additional Features of an Adaptive, Multicategory Pattern Classification System","authors":"J. M. Pitt, B. Womack","doi":"10.1109/TSSC.1969.300259","DOIUrl":"https://doi.org/10.1109/TSSC.1969.300259","url":null,"abstract":"Some additional features of an adaptive, multicategory pattern classification system are presented. No a priori knowledge of the class probability densities or a priori probabilities of occurrence of the categories is required. The system utilizes a set of functions selected by the user to form discriminant functions. Adaptation of the system is accomplished using a set of independent pattern samples of known classification in such a manner that the system discriminant functions form minimum mean-square approximations to the Bayes discriminant functions as the number of samples of known classification increases. The convergence rate of the system is examined, and conditions are established under which the expected loss due to misclassification by the system is asymptotically equivalent to the minimum loss achievable when using the Bayes discriminant functions. In addition, a simulation of the system for a three-category problem is presented to demonstrate system performance for a finite number of adaptions.","PeriodicalId":120916,"journal":{"name":"IEEE Trans. Syst. Sci. Cybern.","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1969-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126266812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Three-Dimensional Morphology of Systems Engineering","authors":"A. D. Hall","doi":"10.1109/TSSC.1969.300208","DOIUrl":"https://doi.org/10.1109/TSSC.1969.300208","url":null,"abstract":"A study of the structure and form of systems engineering using the technique of morphological analysis is presented. The result is a model of the field of systems engineering that may be rich in applications. Three uses given for illustration are in taxonomy, discovery of new sets of activities, and systems science curriculum design.","PeriodicalId":120916,"journal":{"name":"IEEE Trans. Syst. Sci. Cybern.","volume":"59 8","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1969-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114041095","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Calamity Detection Using Nonparametric Statistics","authors":"E. Henrichon, K. Fu","doi":"10.1109/TSSC.1969.300207","DOIUrl":"https://doi.org/10.1109/TSSC.1969.300207","url":null,"abstract":"The problem of detecting a sudden change or calamity in the normal operation of a control system is investigated for the case of a deterministic system with measurements corrupted by unknown stationary noise. The basic technique concerns the use of nonparametric two-sample tests. As a consequence, the system under observation does not need to be known in detail; all that is required is a set of observations corresponding to the normal operation of the system.","PeriodicalId":120916,"journal":{"name":"IEEE Trans. Syst. Sci. Cybern.","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1969-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131836643","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Unsupervised Learning Minimum Risk Pattern Classification for Dependent Hypotheses and Dependent Measurements","authors":"C. Hilborn, D. Lainiotis","doi":"10.1109/TSSC.1969.300201","DOIUrl":"https://doi.org/10.1109/TSSC.1969.300201","url":null,"abstract":"A recursive Bayes optimal solution is found for the problem of sequential multicategory pattern recognition when unsupervised learning is required. An unknown parameter model is developed which, for the pattern classification problem, allows for 1) both constant and time-varying unknown parameters, 2) partially unknown probability laws of the hypotheses and time-varying parameter sequences, 3) dependence of the observations on past as well as present hypotheses and parameters, and most significantly, 4) sequential dependencies in the observations arising from either (or both) dependency in the pattern or information source (context dependence) or in the observation medium (sequential measurement correlation), these dependencies being up to any finite Markov orders. For finite parameter spaces, the solution which is Bayes optimal (minimum risk) at each step is found and shown to be realizable in recursive form with fixed memory requirements. The asymptotic properties of the optimal solution are studied and conditions established for the solution (in addition to making best use of available data at each step) to converge in performance to operation with knowledge of the (unobservable) constant unknown parameters.","PeriodicalId":120916,"journal":{"name":"IEEE Trans. Syst. Sci. Cybern.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1969-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125829152","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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