Physical fitness and health of white collar business person is getting worse and worse in recent years. Therefore, it is necessary to develop a system which can enhance physical fitness and health for people. Although the exercise prescription can be generated after diagnosing for customized physical fitness and healthcare. It is hard to meet individual execution needs for general scheduling of physical fitness and healthcare system. So the main purpose of this research is to develop an intelligent scheduling of execution for customized physical fitness and healthcare system. The results of diagnosis and prescription for customized physical fitness and healthcare system will be generated by fuzzy logic Inference. Then the results of diagnosis and prescription for customized physical fitness and healthcare system will be scheduled and executed by intelligent computing. The scheduling of execution is generated by using genetic algorithm method. It will improve traditional scheduling of exercise prescription for physical fitness and healthcare. Finally, we will demonstrate the advantages of the intelligent scheduling of execution for customized physical fitness and healthcare system.

In the paper, a cloud-dust based intelligent maximum power analysis system for photovoltaic is proposed. In order to resolve NP problem for photovoltaic, factors of photovoltaic are integrated to cloud-dust based intelligent maximum power analysis system for computing. This study is the development of the maximum power analysis system for photovoltaic, to improve the solar panels effects of the different region and enable them to get maximum efficiency of the power generation. The design methodology of this study includes: (1) The monitoring and control Module (2) The prediction and evaluation module (3) The performance diagnosis module (4) The maintenance prescription module. At last, we can find the advantages of the cloud-dust based intelligent maximum power analysis system for photovoltaic. It increases overall competitive performance of products, reduces cost of products and consummation rates of human resources.

Knowledge graphs are useful sources for various AI applications, however the basic paradigm to support pilot training is still unclear. In the paper, It is proposed to generate the customized knowledge graph of flight trainings using machine learning method for the flight training program. In order to provide the successful key to the further understanding of the learning problems between the students and the instructors. In this research, we collected data from an aeronautical academic in Taiwan that students were trained for Recreation Pilot License Program. We performed a test on 24 students at the first of each training course, 16 data of collected been used on building the module, 8 of them used to exam the module. There are 12 courses in the training program, and 30 hours total time were suggested by academic. The score which we applied on test were based on LCG method which is the sum of Maneuver and SRM Grades. For the indicators of course component in Learner Centered Grading, namely (a) CCS1: Operation & Effect of Controls; (b) CCS2: Straight & Level; (c) CCS3: Climbing & Descending; (d) CCS4: Turning; (e) CCS5: Stalling; (f) CCS6: Revision; (g) CCS7: Circuits; (h) CCS8: Cross-Wind Training; (i) CCS9: Circuit Emergency; (j) CCS10: Solo Circuit; (k) CCS11: Forced Landing; and (l) CCS12: Precautionary & Searching Landing. Through the method of Knowledge Graph, we deduct and predict the number of hours that need to be added for each student’s learning. Using the dynamic knowledge graph to display the key issues of the course learning continuously, and make follow-up decisions for the students, instructors and airliners.

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In recent years, it is quite important to develop a customized system which can enhance physical fitness and health for people. And the system reliability is more important. In the paper, a fool-proofing design and crisis management for customized physical fitness and healthcare system is proposed. It is designed to prevent the failure of the various mechanisms of customized physical fitness and healthcare system, including records, surveillance, assessments, predictions, diagnosis, prescription, and scheduling. It is separated into (1) fool-proofing design module (2) crisis management module. The fool-proofing indexes are set to prevent the failure of the various mechanisms. The states of the various mechanisms are managed by the auto-checked fool-proofing indexes. If mistakes prevention was fail, we have to execute the crisis management for stopping harmful results. The crisis management will find the error level and response the solution by using fuzzy method. By the experiments, we can find the advantages of the fool-proofing design and crisis management for customized physical fitness and healthcare system. And it is effective to prevent the failure of the various mechanisms of intelligent customized physical fitness and healthcare system.

With the advent of the era of global high-tech industry and commerce and its associated sedentary lifestyle, opportunities for physical activity are reduced. People's physical fitness and health is deteriorating. Therefore, it is necessary to develop a system that can enhance people's physical fitness and health. However, it is difficult for general physical fitness and healthcare systems to meet individualized needs. The main purpose of this research is to develop a method of intelligent diagnosis and prescription for a customized physical fitness and healthcare system. The proposed system records all processes of the physical fitness and healthcare system via a wireless sensor network and the results of the diagnosis and prescription will be generated by fuzzy logic inference. It will improve individualized physical fitness and healthcare. Finally, we demonstrate the advantages of intelligent diagnosis and prescription for a customized physical fitness and healthcare system.

The system thinking has been applied to many aspects of organization, and this paper examines the potential for using these ideas in the area of organizational problem solving and human resource control. This study finds that systems methodologies can help manager to produce an efficient, effective, profitable and ethically fair organization for manufacturing industry. However, this requires using a variety of systems approaches based on different paradigmatic assumptions to help the different human interests. Critical awareness must be brought into group leadership, motivation and interactions. Challenging of ideas can avoid obstructing learning and can improve decision making. This research recommends that human resource would be improved by adopting a critical systemic perspective.

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