• The Journal of the Convergence on Culture Technology
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• v.4 no.2
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• pp.197-204
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• 2018

One of the hottest issues in our 21st century is AI. Just as the automation of manual labor has been achieved through the Industrial Revolution in the agricultural society, the intelligence information society has come through the SW Revolution in the information society. With the advent of Google 'Alpha Go', the computer has learned and predicted its own machine learning, and now the time has come for the computer to surpass the human, even to the world of Baduk, in other words, the computer. Machine learning ML (machine learning) is a field of artificial intelligence. Machine learning ML (machine learning) is a field of artificial intelligence, which means that AI technology is developed to allow the computer to learn by itself. The time has come when computers are beyond human beings. Many companies use machine learning, for example, to keep learning images on Facebook, and then telling them who they are. We also used a neural network to build an efficient energy usage model for Google's data center optimization. As another example, Microsoft's real-time interpretation model is a more sophisticated translation model as the language-related input data increases through translation learning. As machine learning has been increasingly used in many fields, we have to jump into the AI industry to move forward in our 21st century society.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.7
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• pp.688-698
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• 2017

This study was conducted to identify the conceptual definitions and attributes of fatigue in hemodialysis patients based on the Hybrid Model of concept development. The Hybrid Model was used to investigate the main attributes and indicators of the concept by applying three stages. After a literature review, data were collected through observation and interviews including qualitative research in the field work stage. The participants included 10 patients in hemodialysis center of two hospitals in Gwang-ju, Korea. The attributes of fatigue concept in the hemodialysis patients were divided into four dimensions, physical activity, affective mood, social role, and cognitive reflection. The definition of fatigue by hemodialysis patients was defined as 'subjective feeling usually experienced in four dimensions during the process to recognize and adjust energy deficiency and limited functions caused by uremia and repeated hemodialysis for chronic renal failure'. Considering the dimensions and attributes derived from this study, it may be possible to develop an effective intervention program for fatigue in hemodialysis patients.