Cloud computing aims to maximize the benefit of distributed resources and aggregate them to achieve higher throughput to solve large scale computation problems. In this technology, the customers rent the resources and...Cloud computing aims to maximize the benefit of distributed resources and aggregate them to achieve higher throughput to solve large scale computation problems. In this technology, the customers rent the resources and only pay per use. Job scheduling is one of the biggest issues in cloud computing. Scheduling of users’ requests means how to allocate resources to these requests to finish the tasks in minimum time. The main task of job scheduling system is to find the best resources for user’s jobs, taking into consideration some statistics and dynamic parameters restrictions of users’ jobs. In this research, we introduce cloud computing, genetic algorithm and artificial neural networks, and then review the literature of cloud job scheduling. Many researchers in the literature tried to solve the cloud job scheduling using different techniques. Most of them use artificial intelligence techniques such as genetic algorithm and ant colony to solve the problem of job scheduling and to find the optimal distribution of resources. Unfortunately, there are still some problems in this research area. Therefore, we propose implementing artificial neural networks to optimize the job scheduling results in cloud as it can find new set of classifications not only search within the available set.展开更多
We suggest that employees’ job satisfaction has relationship to friendship network other than professional commitment, and argue that friendship network in the same ward and across wards will have different effects o...We suggest that employees’ job satisfaction has relationship to friendship network other than professional commitment, and argue that friendship network in the same ward and across wards will have different effects on employees’ job satisfaction. A cross-sectional survey design utilizing questionnaires was selected to fulfill the research objectives. All of the 405 nurses in the En Chou Kong Hospital were surveyed. Three hundred and three nurses completed the questionnaire representing a response rate of 74.8%. The instruments included friendship network nomination, professional commitment scale, and nurses’ job satisfaction scale (NJSS). The regression model of job satisfaction was constructed, using friendship network variables in the ward and across wards and professional commitment as independent variables. R square for each model is 0.22-0.36 for the four dimensions of job satisfaction. Professional commitment is the robust predictor. The efficiency of friendship network in the ward is a good predictor, while it is negative related to satisfaction of work load. Further, the indegree in the ward is negative related to work load. Implication was discussed.展开更多
文摘Cloud computing aims to maximize the benefit of distributed resources and aggregate them to achieve higher throughput to solve large scale computation problems. In this technology, the customers rent the resources and only pay per use. Job scheduling is one of the biggest issues in cloud computing. Scheduling of users’ requests means how to allocate resources to these requests to finish the tasks in minimum time. The main task of job scheduling system is to find the best resources for user’s jobs, taking into consideration some statistics and dynamic parameters restrictions of users’ jobs. In this research, we introduce cloud computing, genetic algorithm and artificial neural networks, and then review the literature of cloud job scheduling. Many researchers in the literature tried to solve the cloud job scheduling using different techniques. Most of them use artificial intelligence techniques such as genetic algorithm and ant colony to solve the problem of job scheduling and to find the optimal distribution of resources. Unfortunately, there are still some problems in this research area. Therefore, we propose implementing artificial neural networks to optimize the job scheduling results in cloud as it can find new set of classifications not only search within the available set.
文摘We suggest that employees’ job satisfaction has relationship to friendship network other than professional commitment, and argue that friendship network in the same ward and across wards will have different effects on employees’ job satisfaction. A cross-sectional survey design utilizing questionnaires was selected to fulfill the research objectives. All of the 405 nurses in the En Chou Kong Hospital were surveyed. Three hundred and three nurses completed the questionnaire representing a response rate of 74.8%. The instruments included friendship network nomination, professional commitment scale, and nurses’ job satisfaction scale (NJSS). The regression model of job satisfaction was constructed, using friendship network variables in the ward and across wards and professional commitment as independent variables. R square for each model is 0.22-0.36 for the four dimensions of job satisfaction. Professional commitment is the robust predictor. The efficiency of friendship network in the ward is a good predictor, while it is negative related to satisfaction of work load. Further, the indegree in the ward is negative related to work load. Implication was discussed.
