• 동의생리병리학회지
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• 제19권4호
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• pp.878-883
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• 2005

The dream is a well-known experience in the routine life. It is the image and thought being occurred during the sleep, and the complex reaction of our mental world to the event of everyday. In particular, there are so many opinions of the reason why people have a dream and this thesis is telling about the physical and pathological changes in the human as one of that various opinions. The aspects of this thesis are often founded in the diverse texts of oriental Medicine, including the Internal Classics(내경), and there were some cases that regarded the dream as diagnostic object and put to clinical uses. These attempts were not only tried out by particular orient thoght, also the ancient Greeks thought that the dream would represent important informations about the health. But, these ideas have been treated lightly by the impacts of the western medicine since the modern age. Straightforwardly, before the psycho-analytics was not development, most of the doctors and scientists regarded the dream as things like dregs of mind. The central operating bodies of the dream are the Spirit(신) and Hon and Beak(혼백), and the Spirit(신) is more essential part between the two.

• 산업경영시스템학회지
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• 제39권2호
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• pp.54-63
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• 2016

As technology has developed and cost for data processing has reduced, big data market has grown bigger. Developed countries such as the United States have constantly invested in big data industry and achieved some remarkable results like improving advertisement effects and getting patents for customer service. Every company aims to achieve long-term survival and profit maximization, but it needs to establish a good strategy, considering current industrial conditions so that it can accomplish its goal in big data industry. However, since domestic big data industry is at its initial stage, local companies lack systematic method to establish competitive strategy. Therefore, this research aims to help local companies diagnose their big data capabilities through a reference model and big data capability assessment system. Big data reference model consists of five maturity levels such as Ad hoc, Repeatable, Defined, Managed and Optimizing and five key dimensions such as Organization, Resources, Infrastructure, People, and Analytics. Big data assessment system is planned based on the reference model's key factors. In the Organization area, there are 4 key diagnosis factors, big data leadership, big data strategy, analytical culture and data governance. In Resource area, there are 3 factors, data management, data integrity and data security/privacy. In Infrastructure area, there are 2 factors, big data platform and data management technology. In People area, there are 3 factors, training, big data skills and business-IT alignment. In Analytics area, there are 2 factors, data analysis and data visualization. These reference model and assessment system would be a useful guideline for local companies.

• 대한영양사협회학술지
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• 제25권1호
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• pp.44-58
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• 2019

Predicting the number of meals in a foodservice organization is an important decision-making process that is essential for successful food production, such as reducing the amount of residue, preventing menu quality deterioration, and preventing rising costs. Compared to other demand forecasts, the menu of dietary personnel includes diverse menus, and various dietary supplements include a range of side dishes. In addition to the menus, diverse subjects for prediction are very difficult problems. Therefore, the purpose of this study was to establish a method for predicting the number of meals including predictive modeling and considering various factors in addition to menus which are actually used in the field. For this purpose, 63 variables in eight categories such as the daily available number of people for the meals, the number of people in the time series, daily menu details, weekdays or seasons, days before or after holidays, weather and temperature, holidays or year-end, and events were identified as decision variables. An ensemble model using six prediction models was then constructed to predict the number of meals. As a result, the prediction error rate was reduced from 10%~11% to approximately 6~7%, which was expected to reduce the residual amount by approximately 40%.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권7호
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• pp.2414-2433
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• 2021

This article focuses on providing remedial solutions for COVID disease through the data collection process. Recently, In India, sudden human losses are happening due to the spread of infectious viruses. All people are not able to differentiate the number of affected people and their locations. Therefore, the proposed method integrates robotic technology for monitoring the health condition of different people. If any individual is affected by infectious disease, then data will be collected and within a short span of time, it will be reported to the control center. Once, the information is collected, then all individuals can access the same using an application platform. The application platform will be developed based on certain parametric values, where the location of each individual will be retained. For precise application development, the parametric values related to the identification process such as sub-interval points and intensity of detection should be established. Therefore, to check the effectiveness of the proposed robotic technology, an online monitoring system is employed where the output is realized using MATLAB. From simulated values, it is observed that the proposed method outperforms the existing method in terms of data quality with an observed percentage of 82.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권8호
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• pp.3270-3294
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• 2020

Some things come easily to humans, one of them is the ability to navigate around. This capability of navigation suffers significantly in case of partial or complete blindness, restricting life activity. Advances in the technological landscape have given way to new solutions aiding navigation for the visually impaired. In this paper, we analyze the existing works and identify the challenges of path selection, context awareness, obstacle detection/identification and integration of visual and nonvisual information associated with real-time assisted mobility. In the process, we explore machine learning approaches for robotic path planning, multi constrained optimal path computation and sensor based wearable assistive devices for the visually impaired. It is observed that the solution to problem is complex and computationally intensive and significant effort is required towards the development of richer and comfortable paths for safe and smooth navigation of visually impaired people. We cannot overlook to explore more effective strategies of acquiring surrounding information towards autonomous mobility.

• 조명전기설비학회논문지
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• 제29권11호
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• pp.96-101
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• 2015

In recent years, researches regarding optimal placement of CCTV(Closed-circuit Television) cameras via architecture modeling has been conducted. However, for analyzing surveillance coverage through actual human movement, the application of VA(Video Analytics) function of IP(Internet Protocol) cameras has not been studied. This paper compares two methods using data captured from real-world cameras and data acquired from a virtual environment. In using real cameras, we develop GUI(Graphical User Interface) to be used as a logfile which is stored hourly and daily through VA functions and to be used commercially for placement of products inside a shop. The virtual environment was constructed to emulate an real world such as the building structure and the camera with its specifications. Moreover, suitable placement of the camera is done by recognizing obstacles and the number of people counted within the camera's range of view. This research aims to solve time and economic constraints of actual installation of surveillance cameras in real-world environment and to do feasibility study of virtual environment.

• 인간식물환경학회지
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• 제24권4호
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• pp.415-427
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• 2021

Background and objective: This study examined the changes in the cultural trend of use for green infrastructure in Seoul due to COVID-19 pandemic. Methods: The subjects of this study are 8 sites of green infrastructure selected by type: Forested green infrastructure, Watershed green infrastructure, Park green infrastructure, Walkway green infrastructure. The data used for analysis was blog posts for a total of four years from August 1, 2016 to July 31, 2020. The analysis method was conducted keyword frequency analysis, topic modeling, and related keyword analysis. Results: The results of this study are as follows. First, the number of posts on green infrastructure has increased since COVID-19, especially forested green infrastructure and watershed green infrastructure with abundant naturalness and high openness. Second, the cultural trend keywords before and after COVID-19 changed from large-scale to small-scale, community-based to individual-based activities, and nondaily to daily culture. Third, after COVID-19, topics and keywords related to coronavirus showed that the cultural trends were reflected on appreciation, activities, and dailiness based on natural resources. In sum, the interest in green infrastructure in Seoul has increased after COVID-19. Also, the change of green infrastructure represents the increased demand for experience that reflects the need and expectation for nature. Conclusion: The new trend of green Infrastructure in the pandemic era should be considered in the the individual relaxations & activities.

• 치위생과학회지
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• 제21권3호
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• pp.185-197
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• 2021

Background: This study aimed at investigating the meal regularity, health, and oral health habits of single Korean households to understand the impact of these factors on the risk of metabolic syndrome, in addition to preventing and managing metabolic syndrome. Methods: Using raw data from the 8th Korea National Health and Nutrition Examination Survey (2019), 274 study subjects, aged 19 to 64, were selected primarily from single adult households. Complex sample statistical analysis was performed using the Predictive Analytics Software Statistics ver. 18.0 program. Results: Regarding the meal regularity in single-person households in Korea, the younger group outperformed the middle-aged group, and those who drank more than once a month performed better than those who drank less than once a month. In terms of oral health, regardless of the age and the income level, participants who ate three meals a day had a higher rate of speech problems and chewing difficulties than those who ate irregularly or regularly on a regular day. Factors influencing the risk of developing metabolic syndrome were age, speech problems, and frequency of toothbrushing. Compared to the younger group, there were 0.361 times more people in the middle-aged group; and compared to those without speech problems, there were 1.161 more people with speech problem. Compared to those who tooth brushed more than four times a day, there were 1.284 more people who tooth brushed 2 to 3 times a day and there were 5.673 times more people who tooth brushed less than once. Conclusion: Based on the study results, it is necessary to implement a program that can plan and apply customized management measures and prevent metabolic syndrome by improving and correcting the health and oral health behaviors of single-person households in Korea. Therefore, active mediation measures, such as support and publicity at the local or national level, should be planned.

• 한국융합학회논문지
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• 제6권4호
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• pp.121-126
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• 2015

한국청소년패널(2008)의 중2 패널 5차년도 자료를 가지고 기술통계 분석과 회귀분석을 실시하여 가족의 기능적 결손이라는 위험상황에서 위험요인, 보호요인, 심리적응 간의 관계와 보호요인의 매개효과의 기제를 검증하고, 심리적응 수준이 높은 청소년을 보호해주는 보호요인을 분석하는 데에 그 목적이 있다. 분석방법으로는 대상자의 빈도분석과 개인특성에 따른 차이를 알아보기 위해 PASW(Predictive Analytics Software) 18.0을 이용해 t검증을 실시하였다. 또한 적응에 대한 보호요인의 작용 검증을 위하여 위계적 회귀분석을 실시하여 매개효과를 검증하였다. 연구결과 사회복지실천 현장에서 청소년의 위험요인에 초점을 맞추기보다는 위험요인을 완화시키는 과정이나 보호요인에 초점을 맞춤으로써 위험요인에 노출된 청소년을 바라보는 시각을 전환시킬 수 있으며 이들에 대한 개입도 달라질 것으로 판단된다. 사회복지실천 현장에서 청소년의 위험요인에 초점을 맞추기보다는 위험요인을 완화시키는 과정이나 보호요인에 초점을 맞춤으로써 위험요인에 노출된 청소년을 바라보는 시각을 전환시킬 수 있다. 또한, 가족의 기능적 결손이라는 어려움을 경험하는 청소년을 대상으로 사회복지 실천적 개입 방향을 마련 할 수 있는 기초를 마련한 것으로 판단된다.

• 인터넷정보학회논문지
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• 제22권1호
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• pp.65-77
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• 2021

최근 COVID-19으로 인하여 전세계적으로 수많은 감염자와 사망자가 발생하였다. 아직까지도 효과적인 COVID-19에 대한 백신의 개발은 성공하지 못한 상태이다. 따라서 사람들은이 질병의 감염에 크게 우려하고 있다. 그간 정부 공공기관이 제공한 감염 정보는 거의 단순한 합산 및 통계 숫자에 불과하다. 따라서, 개인이나 개인이 있는 장소의 구체적인 위험도는 판단하기 어렵다. 본 논문에서는 머신러닝 알고리즘 기반 COVID-19의 위험도 분석과 안전 활동에 대한 정보 제공에 대한 방법을 제안한다. 이 논문은COVID-19 감염 및 사망 위험도와 관련된 포괄적인 메트릭 체계를 제안하고, 이를 통해 개인 및 그룹에 대한 위험도를 정량적으로 제공하는 기법을 제시한다. 제시된 시스템은 개인 및 지역 정보와 특성을 반영한 한 클러스터링 알고리즘 등 효과적인 SW 기법들을 활용한다.