International Journal of Computer Science & Network Security
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v.21
no.8
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pp.353-359
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2021
Information technology and the need for timely and effective communication during the Covid-19 have made most governments adopt technological approaches to provide their services. E-government services have been adopted by most governments especially in developed countries to quickly and effectively share information. This study discusses the reasons why governments in the Gulf region should develop a new model for information technology knowledge management practices. To achieve this, the author identified possible benefits of adopting information technology knowledge management practices and why most governments in the Gulf find it hard to adopt them. Knowledge management allows for learning, transfer as well as sharing of information between government organizations and citizens and with the development of technology, the effectiveness of electronic services can easily be achieved. Also, effective adoption of information technology can improve knowledge management with the help of techniques that enhance capture, storage, retrieval as well as sharing of information. The author used systematic literature review to select 28 journals and articles published post 2019. IEEE, Google Scholar and Science Direct were used to select potential studies from which 722 journals and articles were selected. Through screening and eligibility assessment, 21 articles were retained while the back and forward search had 7 more articles which were also included in the study. Using information gathered from these articles and journals a new conceptual model was developed to help improve information technology knowledge management for governments in the Gulf region to effectively deliver e-services during Covid-19. This model was developed based on the process of KM, Theory of Planned Behavior and Unified Theory of Acceptance and Use of Technology. Based on the developed model. From UTAUT model, performance expectancy, effort expectancy as well as social influence had a great impact.
The purpose of this study is to analyze the change of hospitals that patients safety and quality improvement by accreditation process and to examine the impact or interrelation of leadership, organizational culture, hospital management activities and recognition of hospital management performances. The data were collected through a review of the literature, and selfadministered survey with a structured questionnaires to 714 subjects from several medical staff members, administration staff members, nursing staff members, medical technicians and other staff members working in 23 accredited hospitals in Korea. In this analysis hierarchical multiple regression and structural equation model were used. The conclusion of this study provides a theoretical model for understanding organizational changes brought about by accreditation system. Factor on improvement of efficiency and raise the morale, rather than increase of medical income and reduce of the cost factors, had a stronger influence on the accreditation process. In the future, the hospital's participation to induce the accreditation program voluntarily will come up with an alternative policy concern about financial perspective. Also, the hospitals which preparing accreditation program to achieve the goal efficiently, will make use of transformational leadership through enhancing individual consideration and intellectual development to leading members participation. Additionally, non-accredited hospitals should aim at professional culture by innovative and creative approaches, and inviting members to learning and growth in the organization.
Journal of Korean Society of Industrial and Systems Engineering
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v.39
no.1
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pp.25-30
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2016
It is critical to forecast the maximum daily and monthly demand for power with as little error as possible for our industry and national economy. In general, long-term forecasting of power demand has been studied from both the consumer's perspective and an econometrics model in the form of a generalized linear model with predictors. Time series techniques are used for short-term forecasting with no predictors as predictors must be predicted prior to forecasting response variables and containing estimation errors during this process is inevitable. In previous researches, seasonal exponential smoothing method, SARMA (Seasonal Auto Regressive Moving Average) with consideration to weekly pattern Neuron-Fuzzy model, SVR (Support Vector Regression) model with predictors explored through machine learning, and K-means clustering technique in the various approaches have been applied to short-term power supply forecasting. In this paper, SARMA and intervention model are fitted to forecast the maximum power load daily, weekly, and monthly by using the empirical data from 2011 through 2013. $ARMA(2,\;1,\;2)(1,\;1,\;1)_7$ and $ARMA(0,\;1,\;1)(1,\;1,\;0)_{12}$ are fitted respectively to the daily and monthly power demand, but the weekly power demand is not fitted by AREA because of unit root series. In our fitted intervention model, the factors of long holidays, summer and winter are significant in the form of indicator function. The SARMA with MAPE (Mean Absolute Percentage Error) of 2.45% and intervention model with MAPE of 2.44% are more efficient than the present seasonal exponential smoothing with MAPE of about 4%. Although the dynamic repression model with the predictors of humidity, temperature, and seasonal dummies was applied to foretaste the daily power demand, it lead to a high MAPE of 3.5% even though it has estimation error of predictors.
This paper is to evaluate the usability of two representative video meeting services currently used by university for research to improve the quality of university remote lecture. questionnaires based on Kano Model were designed and in-depth interviews were conducted to provide qualitative approaches. Screen-sharing functions, the one-dimensional functions was the most important function. and attractive functions had relatively diverse directions. For essential functions, there was a wide gap in quality due to user-specific equipment. The function in which other platforms exist or business-related was not important. Webex reacted negatively to the aging UI, while Zoom responded negatively to the unilateral mute function. In addition, the development direction was presented in five ways as a result of analysis of these results. under Corona-19 situation, I hope this study will lead to continuous research to make stepping stone for remoted educational development.
This paper considers the possibilities of health promotion from the following perspectives; (1) IUHPE, (2) socio-cultural similarities, (3) action research, and (4) learning from our past. 1. The IUHPE values decentralized activities through regions, and countries such as Japan, Korea, Hong Kong, Taiwan and China belong to NPWP region. Since IUHPE World Conference was held in Japan in 1995, Japan used to occupy more than 60% of NPWP membership. After 2001, membership is increasing rapidly in Chinese speaking sub-region. The transnational collaboration is still in its beginning phase. 2. Confucianism is one of key points. Confucian tradition should not be seen only as obstacles but as advantages to seek a form of health promotion more acceptable in East Asia. 3 Within the new public health framework, people are expected to create and live their health. However, especially in Japan, the tendency of 'lacking of face-to-face explicit interactions' is still common at health-promotion settings as well as academic settings. Therefore, the author tried participatory approaches such as asking WIFY(interactive questions designed for subjects to review their daily life and environment) and as introducing round table interactions. So far, majority of participants welcome new trials. 4. The following social phenomena are comparatively discussed after Japanese invasion and occupation of Korea ended in 1945; status of oriental medicine, separation of dispensary services, and health promotion specialist as a national license. In contrast to Japanese' tendency of maintaining the status quo and postponing of substantial social change, trend toward rapid and dynamic social changes are more commonly observed in Korea. Although all of above possibilities are still in their beginning stages, they are going to offer interesting directions waiting for further challenges and accompanying researches.
My responses to Kim Kyung-Ok's Critique on my critique on the Hungerford approach can be summarized as follows; First, it was argued that possible confusions and misunderstandings around the concept of behavior in REB were mainly caused by Hungerford himself who has used the word in several different ways, from a bunch of overt actions to almost all kinds of responses including cognitive skills, without any clear operational definition of it for more than 20 years. It seems to be needed for future users of the word, 'Behavior' to Prevent unnecessary confusions by providing their operational definition of it. Second, REB is too ambiguous to be a legitimate goal of environmental education and too outcome-oriented to be a meaningful measure for environmental education research. Anyone who accept REB as a goal of EE or a measure for research should clearly suggest procedures and criteria for judging the environmental responsibility of actions under consideration. Third, the Hungerford approach has begun by realizing the limit of a linear traditional behavior change system and has been evolving toward a complex model with dynamic interactions among/between cognitive variables and affective variables. However, it still has one-way structural orientation toward 'Behavior' with no feedbacks. Addition of some feedback processes would make the model more flexible and realistic. Finally, both the Hines model and the Hungeford model were established based on a series of behavioristic studies including three doctoral dissertations equiped with a list of actions which were prejudged to be environmentally responsible by the researchers, not by the learners. What they were primarily interested in was not how mind functions during the learning processes but how learners' behavior can be effectively changed. Considering uncertainty and complexity associated with environmental problems, a great deal of efforts ought to be made toward more context-based and less normative studies applying cognitive psychology and quantitative approaches.
This study was attempted to identify the essence of the mixed practice experience that replaces the clinical practice of nursing students in the COVID-19 situation. From December 17, 2020 to December 31, 2020, eight nursing students were individually interviewed to collect data, and the data were analyzed by applying Colaizzi's phenomenological analysis methodology. The study's finding derived 6 categories. The specific categories were 'Accepting in anxiety', 'Autonomy at the fore', 'Straining non-face-to-face practice', 'Fill your knowledge', 'A variety of approaches to achieve goals', 'The best practice left with regret'. In the pendemic situation, nursing students accepted clinical practice substitution with anxiety and concern about mixed practice, and experienced a way to adapt to practice through self-directed learning and to achieve the goal of clinical practice.
Purpose: The purpose of this paper is to present implications by analyzing research trends on smart factories by text analysis and visual analysis(Comprehensive/ Fields / Years-based) which are big data analyses, by collecting data based on previous studies on smart factories. Methods: For the collection of analysis data, deep learning was used in the integrated search on the Academic Research Information Service (www.riss.kr) to search for "SMART FACTORY" and "Smart Factory" as search terms, and the titles and Korean abstracts were scrapped out of the extracted paper and they are organize into EXCEL. For the final step, 739 papers derived were analyzed using the Rx64 4.0.2 program and Rstudio using text mining, one of the big data analysis techniques, and Word Cloud for visualization. Results: The results of this study are as follows; Smart factory research slowed down from 2005 to 2014, but until 2019, research increased rapidly. According to the analysis by fields, smart factories were studied in the order of engineering, social science, and complex science. There were many 'engineering' fields in the early stages of smart factories, and research was expanded to 'social science'. In particular, since 2015, it has been studied in various disciplines such as 'complex studies'. Overall, in keyword analysis, the keywords such as 'technology', 'data', and 'analysis' are most likely to appear, and it was analyzed that there were some differences by fields and years. Conclusion: Government support and expert support for smart factories should be activated, and researches on technology-based strategies are needed. In the future, it is necessary to take various approaches to smart factories. If researches are conducted in consideration of the environment or energy, it is judged that bigger implications can be presented.
There have been active research activities to use neural networks to analyze OCT images and make medical decisions. One requirement for these approaches to be promising solutions is that the trained network must be generalized to new devices without a substantial loss of performance. In this paper, we use a deep convolutional neural network to distinguish AMD from normal patients. The network was trained using a data set generated from an OCT device. We observed a significant performance degradation when it was applied to a new data set obtained from a different OCT device. To overcome this performance degradation, we propose an image normalization method which performs segmentation of OCT images to identify the retina area and aligns images so that the retina region lies horizontally in the image. We experimentally evaluated the performance of the proposed method. The experiment confirmed a significant performance improvement of our approach.
Journal of The Korean Association For Science Education
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v.34
no.4
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pp.335-347
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2014
Size/scale is a central idea in the science curriculum, providing explanations for various phenomena. However, few studies have been conducted to explore student understanding of this concept and to suggest instructional approaches in scientific contexts. In contrast, there have been more studies in mathematics, regarding the use of number lines to relate the nature of numbers to operation and representation of magnitude. In order to better understand variations in student conceptions of size/scale in scientific contexts and explain learning difficulties including alternative conceptions, this study suggests an approach that links mathematics with the analysis of student conceptions of size/scale, i.e. the analysis of mathematical structure and reasoning for a number line. In addition, data ranging from high school to college students facilitate the interpretation of conceptual complexity in terms of mathematical development of a number line. In this sense, findings from this study better explain the following by mathematical reasoning: (1) varied student conceptions, (2) key aspects of each conception, and (3) potential cognitive dimensions interpreting the size/scale concepts. Results of this study help us to understand the troublesomeness of learning size/scale and provide a direction for developing curriculum and instruction for better understanding.
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