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In genetic programming, a population of computer programs (individuals) is created and these programs are evolved to gain higher fitnesses through an evolutionary process.
This is the first study investigating the prevalence of CANS in a population of computer office workers in Sudan.
This is the first study investigating the prevalence of CANS in a population of computer office workers in Sri Lanka.
The investigation enabled a detailed study of a population of computer users gaining information on the relations between anthropometrics, work-related variables, work ability, productivity, musculoskeletal pain, health-related variables, lifestyle variables, and physical activity during leisure time.
The objective of this study was to assess the effectiveness of this intervention programme on the prevalence of arm, shoulder and neck symptoms, reduction of exposure to risk factors, and sick leave in a population of computer workers.
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The algorithm is designed typically to simulate the biological evolution of a population of individual computer programs through successive generations to improve their "fitness" for carrying out a designated task.
This is accomplished by first generating or initializing a population of random computer programs that are composed of the basic building blocks needed to solve or approximate a solution to the problem.
The purpose of the present study was to investigate the prevalence of CANS in a Dutch population of computer workers and to develop a questionnaire aimed at measuring workplace physical and psychosocial risk factors for the presence of these complaints.
But for a huge population of computer users, Google's Chome OS — and no doubt countless hangers-on that will follow — provides everything they need.
Create a new offspring population of computer programs by copying the best programs and creating new ones by mutation and crossover.
By simulating the dynamics of recurrence in a population of patients, a realistic computer simulation model could function as a virtual laboratory within which an unlimited number of experiments comparing hypothetical surveillance strategies could be run in silico within a compressed timeframe.
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