• Journal of Internet Computing and Services
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• v.15 no.2
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• pp.87-94
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• 2014

Social media which includes Facebook enable users to construct relationships and networks as well as sharing of information. By enlisting Facebook users as proxy, this paper attempted to analyze the different emotional states experienced by social media users, specifically to gauge what effect their usage motivation and usage pattern had on the ambivalence level of the users. The quantitative survey result revealed that usage duration or the time of day when Facebook was accessed had no relevant impact on one's ambivalence level. However, there was a direct correlation between frequency of Facebook usage and the ambivalence level. The more the user logged onto Facebook the more suppressed his or her expression became due to fear of giving negative impressions to others and also receiving their negative feedbacks, which then subsequently added to the user's ambivalence. People's main reasons for using Facebook were identified as "chatting," "communicating," "maintaining relationships," "relationship building," "networking," and "finding information about friends," but only "maintaining relationships," "communicating," and "networking" had observable effect on ambivalence. There were no noticeable differences among genders with regards to ambivalence and usage levels, but there was a marked difference based on the user's age. For example, people in their forties showed higher levels of ambivalence than those in their twenties. This may be attributed to anxiety they face as they use Facebook primarily to expand their networks and to maintain relationships. As such, it is surmised that their fatigue level from using social media will only increase. Meanwhile, Korean Facebook user's emotional manifestation tended to skew toward relation-involved ambivalence rather than the self-defensive type. This relation-involved ambivalence might be something that can actually help prevent damage to relationships by limiting excessive emotional expressions. In other words, such ambivalence by Facebook users may be a positive element in a user's social media interaction.

• Fire Science and Engineering
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• v.26 no.4
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• pp.48-54
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• 2012

In order to study on the evacuation risk when connate fires caused by vertical fire spread of the exterior occurs, the egress simulations based on the relevant scenarios has carried out. As a result of it, ASET (permitted evacuation time) was reached in between 550 to 650 seconds in entire floors after vertical smoke spread from fire of combustible exteriors. In particular, ASET was 358 seconds in the first floor, 490 seconds in the six floor and 473 seconds in the tenth floor. In addition, five floors of all levels, the 1st floor, the 6th floor and the 28th floor ~30th floor, show RSET (minimum evacuation time) which is bigger than ASET as evacuation risk. This result presents occupants in high rise buildings with more than 15 floors might not be able to egress of them using staircases due to huge population attempting to evacuate simultaneously. Particularly, 699 people in the upper levels by smoke from the first floor are having difficulty escaping this building since ASET on the first floor adjacent to the ignition point was 358 seconds which is relatively reached fast. Considering a prevention method of the fire and smoke spread, architects have to use non-combustible exterior in the building's facade to be required as an active fire protection system.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.35 no.4
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• pp.88-97
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• 2017

The purpose of this study was to identify the development and transition of the Original landscape(始景觀) of Oeam Village based on the landscape that changes over time and the relevant factors and the following summarizes the findings: First, Original landscape perceived by the ancestors of Korea was identified in the description of topography and landscape of Oeam Village mentioned in various literature such as "Oeamgi(巍巖記)" and topography was analyzed to identify that the natural waters that flew before Oeam Village was formed aligned with the artificial waterway inside the village. Second, the landscape of Oeam Village was classified by characterized events: (1) expansion of the tribal town of the Yi Family of Yean, (2) stagnancy where the villagers formed an organic relationship without much change to the landscape, (3) the biggest change to the landscape by national policies, and (4) preservation and use of tourism resources based on preservation of cultural heritage. Third, the center of village moved from the east of village to the west of village. In the past, the east of village provided agricultural functions for the development and expansion of village. The center later shifted to the entrance to the west of village under the influence of industrialization and tourism. Further studies would be necessary to clarify the authenticity of resources through additional literature for better understanding of the past of Oeam Village and the transition of the village's landscape elements and the comparison of their characteristics could be possible topics for future studies.

• Journal of the Korea Computer Industry Society
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• v.3 no.3
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• pp.331-340
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• 2002

The web world is getting so huge and untractable that without an intelligent information extractor we would get more and more helpless. Conventional web spidering techniques for general purpose search engine may be too slow for the specific search engines, which concentrate only on specific areas or keywords. In this paper a new model for improving web spidering capabilities is suggested and experimented. How to select adequate reference web pages from the initial web Page set relevant to a given specific area (or keywords) can be very important to reduce the spidering speed. Our reference web page selection method DOPS dynamically and orthogonally selects web pages, and it can also decide the appropriate number of reference pages, using a newly defined measure. Even for a very specific area, this method worked comparably well almost at the level of experts. If we consider that experts cannot work on a huge initial page set, and they still have difficulty in deciding the optimal number of the reference web pages, this method seems to be very promising. We also applied reinforcement learning to web environment, and DOPS-based reinforcement learning experiments shows that our method works quite favorably in terms of both the number of hyper links and time.

• KIPS Transactions on Computer and Communication Systems
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• v.5 no.9
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• pp.211-216
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• 2016

Worldwide casualties caused by earthquakes, floods, fire or other disaster has been increasing. So many researchers are being actively done technical studies to ensure golden-time. In this paper if a disaster occurs, use the IoT technologies in order to secure golden-time and transmits the message after to find the user of the accident area first. When the previous job is finished, gradually finds a user of the surrounding area and transmits the message. For national emergency information, OPEN API of Korea Meteorological Administration was used. To collect detailed information on a relevant area in real time, this study established the system that connects and integrates Crowd Sensing technology with BLE (Bluetooth Low Energy) Beacon technology. Up to now, the CBS based on base station has been applied. However, this study designed and mapped DB in the integration of Beacon based user positioning and national administrative address system in order to estimate local users. In this experiment, the accuracy and speed of information dif6fusion algorithm were measured with a rise in the number of users. The experiments were conducted in a manner that increases the number of users by one thousand and was measured the accuracy and speed of the message spread transfer algorithm. Finally, became operational in less than one second in 20,000 users, it was confirmed that the notification message is sent.

• FLOWER RESEARCH JOURNAL
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• v.18 no.2
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• pp.136-141
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• 2010

In order to analyze the horticultural-therapy program, which was carried out targeting the mentally disabled, relevant 559 copies of 'Confirmation Note of horticultural activity' submitted for to be used the use in license examination to Korean Horticultural Therapy and Wellbeing Association were used as a tool. It contains 64 horticultural therapists for level 1 and 524 horticultural therapists for level 2 from May in 2000 to February in 2008. With the aim of examining difference depending on people covered by the program, license kind and horticultural therapy activity period in horticulture therapists, ${\chi}^2$ test was conducted on the basis of frequency in each. Data was analyzed by using SPSS (Statistical Package for the Social Science) Win 13.0 program, which was carried out targeting the mentally disabled, the 'art and craft activity' was the largest with 46.0%. In terms of 'growing activity', the 'normal growing' showed the highest ratio with 74.7%. In the 'art and craft activity', the 'flower decoration' showed the highest ratio with 37.5%. In the result of 'Cooking activity', the activity related to 'tea' was the largest ratio with 33.6%. As a result of 'learning activity', 'orientation' was the largest ratio with 47.6%. In the 'outdoor activity', 'excursion' was the largest ratio with 36.7%.

• Korean Chemical Engineering Research
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• v.57 no.6
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• pp.781-789
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• 2019

There are frequent accidents by chemicals during laboratory experiments and pilot plant and reactor operations. It is necessary to find and comprehend relevant information to prevent accidents before starting synthesis experiments. In the process design stage, reaction information is also necessary to prevent runaway reactions. Although there are various sources available for synthesis information, including the Internet, it takes long time to search and is difficult to choose the right path because the substances used in each synthesis method are different. In order to solve these problems, we propose an intelligent synthetic path search system to help researchers shorten the search time for synthetic paths and identify hazardous intermediates that may exist on paths. The system proposed in this study automatically updates the database by collecting information existing on the Internet through Web scraping and crawling using Selenium, a Python package. Based on the depth-first search, the path search performs searches based on the target substance, distinguishes hazardous chemical grades and yields, etc., and suggests all synthetic paths within a defined limit of path steps. For the benefit of each research institution, researchers can register their private data and expand the database according to the format type. The system is being released as open source for free use. The system is expected to find a safer way and help prevent accidents by supporting researchers referring to the suggested paths.

• Korean Journal of Plant Resources
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• v.32 no.4
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• pp.303-311
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• 2019

Various colors of fruit skin and flesh are the most popular commercial criteria for peach classification. In order to breed new red-fleshed peach cultivar, many cross seedlings and generations should be maintained. Therefore it is necessary to develop early selection markers to screen seedlings with target traits to increase breeding efficiency. For the comparison of transcription profiles in peach cultivars differing in flesh color expression, two cDNA libraries were constructed. Differences in gene expression between red-fleshed peach cultivar, 'Josanghyeoldo' and white-fleshed peach cultivar, 'Mibaekdo' were analyzed by next-generation sequencing (NGS). Expressed sequence tag (EST) of clones from the two cultivars were selected for nucleotide sequence determination and homology searches. Putative single nucleotide polymorphisms (SNP) were screened from peach EST contigs by high resolution melting (HRM) analysis displayed specific difference between 8 red-fleshed peach cultivars and 24 white-fleshed peach cultivars. All 72 pairs of SNPs were discriminated and the HRM profiles of amplicons were established. In the study reported here, the development of SNP markers for distinguishing between red and white fleshed peach cultivars by HRM analysis offers the opportunity to use DNA markers. This SNP marker could be useful for peach marker assisted breeding and provide a good reference for relevant research on molecular mechanisms of color variation in peach cultivars.

• Health Policy and Management
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• v.29 no.3
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• pp.303-311
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• 2019

Background: Cerebrovascular disease is included in four major diseases and is a disease that has high rates of prevalence and mortality around the world. Moreover, it is a disease that requires a high cost for long-term hospitalization and treatment. This study aims to figure out the correlation between grip strength, which was presented as a simple, cost-effective, and relevant predictor of cerebrovascular disease, and cerebrovascular disease based on the results of a prior study. And furthermore, our study compared model suitability of the model to measuring grip strength and relative grip strength as a predictor of cerebrovascular disease to improve the quality of cerebrovascular disease's predictor. Methods: This study conducted an analysis based on the generalized linear mixed model using the data from the Korea Longitudinal Study of Ageing from 2006 to 2016. The research subjects consisted of 9,132 middle old age people aged 45 years or older at baseline with no missing information of education level, gender, marital status, residential region, type of national health insurance, self-related health, smoking status, alcohol use, and economic activity. The grip strength was calculated the average which measured 4 times (both hands twice), and the relative grip force was divided by the body mass index as a variable considering the anthropometric figure that affects the cerebrovascular disease and the grip strength. Cerebrovascular diseases, a dependent variable, were investigated based on experiences diagnosed by doctors. Results: An analysis of the association between grip strength and found that about 0.972 (odds ratio [OR], 0.972; 95% confidence interval [CI], 0.963-0.981) was the incidence of cerebral vascular disease as grip strength increased by one unit increase and the association between relative grip strength and cerebrovascular disease found that about 0.418 (OR, 0.418; 95% CI, 0.342-0.511) was the incidence of cerebral vascular disease as relative grip strength increased by unit. In addition, the model suitability of the model for each grip strength and relative grip strength was 11,193 and 11,156, which means relative grip strength is the better application to the predictor of cerebrovascular diseases, irrespective of other variables. Conclusion: The results of this study need to be carefully examined and validated in applying relative grip strength to improve the quality of predictors of cerebrovascular diseases affecting high mortality and prevalence.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.871-884
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• 2021

The purpose of this study was to determine ways to increase efficiency in constructing and verifying artificial intelligence learning data on land cover using aerial and satellite images, and in applying the data to AI learning algorithms. To this end, multi-resolution datasets of 0.51 m and 10 m each for 8 categories of land cover were constructed using high-resolution aerial images and satellite images obtained from Sentinel-2 satellites. Furthermore, fine data (a total of 17,000 pieces) and coarse data (a total of 33,000 pieces) were simultaneously constructed to achieve the following two goals: precise detection of land cover changes and the establishment of large-scale learning datasets. To secure the accuracy of the learning data, the verification was performed in three steps, which included data refining, annotation, and sampling. The learning data that wasfinally verified was applied to the semantic segmentation algorithms U-Net and DeeplabV3+, and the results were analyzed. Based on the analysis, the average accuracy for land cover based on aerial imagery was 77.8% for U-Net and 76.3% for Deeplab V3+, while for land cover based on satellite imagery it was 91.4% for U-Net and 85.8% for Deeplab V3+. The artificial intelligence learning datasets on land cover constructed using high-resolution aerial and satellite images in this study can be used as reference data to help classify land cover and identify relevant changes. Therefore, it is expected that this study's findings can be used in the future in various fields of artificial intelligence studying land cover in constructing an artificial intelligence learning dataset on land cover of the whole of Korea.