• The Journal of Korean society of community based occupational therapy
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• v.8 no.1
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• pp.33-44
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• 2018

Objective : This study aims to review research trends in driving rehabilitation for the disabled in South Korea since 2000 suggesting research directions for clinicians and researchers. Methods : Fifty eight articles in 16 journals listed in accredited or candidate journal lists of National Research Foundation of Korea from January, 2000 to December, 2016 were reviewed. 'Driving rehabilitation' and 'driving for disabled' were used as search terms. Descriptive statistics were used to classify articles according to study methodology, levels of evidence, study participants, research topics, and academic associations or official journals. Results : Fifty percent of analyzed researches have been published since 2012. Twenty-two studies (37.9%) were published as group comparison and correlational research. Only seven studies (12.1%) were included in evidence level I. There were 19 studies (38.8%) conducted with brain-injured patients among 49 studies including participants. The Korean Society of Occupational Therapy Journal, having published 15 studies (25.9%) about driving rehabilitation, ranked first among the analyzed journals. In research topic, 15 (25.9%) studies were performed about clinical evaluation. Conclusion : The present study showed that the quality of driving rehabilitation-related studies has been increasing, but more intervention-based researches need to be carried out and it is also necessary to carry out various researches in related fields in order to establish efficient driving rehabilitation in Korea.

• Journal of Oral Medicine and Pain
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• v.34 no.4
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• pp.387-395
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• 2009

Nerve growth factor (NGF) and sensory neuropeptides are involved in the process of nociception at peripheral nerve fibers and wide spread in central nervous system. The aims of this study were to investigate NGF and sensory neuropeptides (substance P [SP] and calcitonin gene-related peptide [CGRP]) levels in human plasma and saliva, and the associations between these sensory neuropeptides levels and chronic orofacial pain symptoms. NGF, SP, and CGRP levels in plasma and resting whole saliva samples collected from 67 orofacial pain patients (joint pain, dental or periodontal pain, mucosal pain) and 36 pain free control subjects were measured by enzyme immunoassay. The characteristic pain intensity of each subject was measured using the Graded Chronic Pain Scale and the flow rate of resting whole saliva was measured. Joint pain patients group showed significantly higher plasma NGF level compared to each of dental pain patients (p<0.01), mucosal pain patients (p<0.01), and control group (p<0.01). Plasma NGF level of dental pain patients group was significantly higher than that of control group (p<0.01). Saliva SP level of dental pain patients group (p<0.05) and saliva CGRP level of mucosal pain group (p<0.05) were significantly higher than that of control group. Plasma and saliva SP levels of joint pain patients was significantly associated with pain intensity (plasma: standardized coefficient=0.599, p<0.01, saliva: standardized coefficient=0.504, p=0.05). In dental pain patients group, plasma SP (standardized coefficient=0.559, p<0.01), saliva SP (standardized coefficient=0.520, p<0.01) and saliva CGRP (standardized coefficient=0.599, p<0.01) levels were significantly associated with age. In mucosal pain patients group, plasma SP (standardized coefficient=0.495, p<0.05), saliva SP (standardized coefficient=0.500, p<0.05), and saliva CGRP (standardized coefficient=0.717, p<0.01) levels were significantly associated with age. NGF and neuropeptides may play a role in the maintenance of various orofacial pain symptoms. The examination of those levels in plasma and saliva helps understanding the mechanism of orofacial pain, and furthermore, can be applied to the diagnosis and therapy of orofacial pain.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.179-192
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• 2014

Keeping in line with the recent changes in the information technology environment, the online learning environment that supports multiple users' participation such as MOOC (Massive Open Online Courses) has become important. One of the largest professional associations in Information Technology, IEEE Computer Society, announced that "Supporting New Learning Styles" is a crucial trend in 2014. Popular MOOC services, CourseRa and edX, have continued to build active learning environment with a large number of lectures accessible anywhere using smart devices, and have been used by an increasing number of users. In addition, collaborative web services (e.g., blogs and Wikipedia) also support the creation of various user-uploaded learning materials, resulting in a vast amount of new lectures and learning materials being created every day in the online space. However, it is difficult for an online educational system to keep a learner' motivation as learning occurs remotely, with limited capability to share knowledge among the learners. Thus, it is essential to understand which materials are needed for each learner and how to motivate learners to actively participate in online learning system. To overcome these issues, leveraging the constructivism theory and collective intelligence, we have developed a social bookmarking system called WeStudy, which supports learning material sharing among the users and provides personalized learning material recommendations. Constructivism theory argues that knowledge is being constructed while learners interact with the world. Collective intelligence can be separated into two types: (1) collaborative collective intelligence, which can be built on the basis of direct collaboration among the participants (e.g., Wikipedia), and (2) integrative collective intelligence, which produces new forms of knowledge by combining independent and distributed information through highly advanced technologies and algorithms (e.g., Google PageRank, Recommender systems). Recommender system, one of the examples of integrative collective intelligence, is to utilize online activities of the users and recommend what users may be interested in. Our system included both collaborative collective intelligence functions and integrative collective intelligence functions. We analyzed well-known Web services based on collective intelligence such as Wikipedia, Slideshare, and Videolectures to identify main design factors that support collective intelligence. Based on this analysis, in addition to sharing online resources through social bookmarking, we selected three essential functions for our system: 1) multimodal visualization of learning materials through two forms (e.g., list and graph), 2) personalized recommendation of learning materials, and 3) explicit designation of learners of their interest. After developing web-based WeStudy system, we conducted usability testing through the heuristic evaluation method that included seven heuristic indices: features and functionality, cognitive page, navigation, search and filtering, control and feedback, forms, context and text. We recruited 10 experts who majored in Human Computer Interaction and worked in the same field, and requested both quantitative and qualitative evaluation of the system. The evaluation results show that, relative to the other functions evaluated, the list/graph page produced higher scores on all indices except for contexts & text. In case of contexts & text, learning material page produced the best score, compared with the other functions. In general, the explicit designation of learners of their interests, one of the distinctive functions, received lower scores on all usability indices because of its unfamiliar functionality to the users. In summary, the evaluation results show that our system has achieved high usability with good performance with some minor issues, which need to be fully addressed before the public release of the system to large-scale users. The study findings provide practical guidelines for the design and development of various systems that utilize collective intelligence.

• Korean Journal of Environment and Ecology
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• v.26 no.4
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• pp.512-527
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• 2012

Jangdo Island (area $1.54km^2$) located in the western end of Dadohae Haesang National Park has been recognized as an prominent ecoregion possessing high moor and national biodiversity hotspot. In terms of the Z$\ddot{u}$rich-Montpellier School's phytosociology, we investigate the diversity of plant communities on the island and reevaluate the Jangdo wetland designated as Ramsar site. Ten physiognomic types of the Jangdo's vegetation were classified into 22 syntaxa (3 associations, 15 communities and 4 subcommunities). Jangdo wetland was actually denominated as 'eutrophic wetland' by Pharagmitetea and Orizetea rather than 'high moor'. Nevertheless, existence value of the Jangdo wetland is evaluated very high as a stepping stone for migratory birds and even plant dispersions. A new site of the northernmost distribution of Arachniodo-Castanopsietum sieboldii, which is a kind of cold-resistant phytocoenosis among the Camellietea japonicae of the warm-temperate broad-leaved forests, was described. Hosta yingeri-Carpinus turczaninovii var. coreana community and Carex wahuensis var. robusta-Juniperus chinensis var. procumbens community were described specifically as an endemic and an edaphic vegetation type, respectively. The unique Jangdo's vegetation reflects regional environmental conditions such as much higher frequency of frost-free days and the highest number of annual average foggy days in Korea and a well-developed aquifer in the depressed basin formed by differential erosion. We identified that human interventions (pasture, logging, forest fire, cultivation, etc.) has been involved intensively on every vegetation types, even though a rugged and inaccessible topography of the island. Particularly the Jangdo wetland has been recently threatened by fundamental distortion on hydrological system. We request an immediate establishment of the conservation prescription manual.

• Tuberculosis and Respiratory Diseases
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• v.55 no.3
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• pp.267-279
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• 2003

Background : The purpose of this study was to analyze the smoking habits in patients with lung cancer and identify any difference of prevalence according to histologic types of lung cancer. Methods : The data were calculated by total amounts of tar and nicotine inhaled during the whole lifetime according to variation of smoking habit. This study was to investigated any difference of prevalence in lung cancer according to smoking habits. The subjects comprised 150 lung cancer cases and 300 hospital control cases that were matched by age and sex. Smoking habits during the whole lifetime were surveyed by standardized questionnaire. Odds ratios were estimated by unconditional logistic regression analysis. Results : There were 104 male and 34 female lung cancer cases. By histologic type, there were 53 cases of squamous cell carcinoma, 67 of adenocarcinoma and 30 of small cell lung carcinoma. The differences between lung cancer cases and controls according to smoking habits were total duration of smoking, total pack years of smoking and number of cigarettes smoked per day during the previous two years. The odds ratio were higher in Kreyberg I, but not in Kreyberg II, for the longer duration of smoking, the greater total pack years of cigarettes consumed, the more cigarettes smoked per day during the previous two years, the longer duration on non-filter smoking, the earlier life cases who began to smoke, and the higher amounts of calculated total tar and nicotine inhaled over the whole lifetime. When we added grade of inhalation to calculation of amounts of tar and nicotine inhaled over the lifetime, the odds ratios of total inhalation amounts of tar and nicotine were as high as those the without them. Conclusions : This study reconfirmed that smoking habits were strongly associated with lung cancer and that there were different associations between smoking habits and histologic types of lung cancer. In particular, calculations of total tar and nicotine amounts inhaled over the whole lifetime were calculated for the first time in trials from lung cancer epidemiologic studies.

• Journal of Life Science
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• v.20 no.7
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• pp.1078-1085
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• 2010

Polychlorinated dibenzo-p-dioxins (PCDDs), polychlorinated dibenzofurans (PCDFs) and dioxin-like polychlorinated biphenyls (dl-PCBs) are bioaccumulative chemicals that are considered to be toxic contaminants based on several epidemiological studies. These chemicals in colostrum were investigated and estimated for their residual consistencies by maternal characteristics like parity and maternal ages. Test subjects were healthy primipara and multipara mothers with a mean age of 31.5 (S.D=3.6) in 2007. Seven isomers of PCDDs, 10 of PCDFs, 4 of non-orthopolychlorinated biphenyls(non-ortho PCBs) and 8 of mono-orthochlorinated polychlorinated biphenyls (mono-ortho PCBs) were analyzed by HRGC/HRMS. From the analyzed data, the mean level of total WHO-TEQs was 9.41 pg TEQ/g lipid, which is significantly lower than the level found in individuals from other countries. The main contributors to the total WHO-TEQs with increasing percentages were 2,3,4,7,8-PeCDF, 1,2,3,7,8-PeCDD and 3,3',4,4',5-PCB (#126), and they accounted for more than 60% of the total WHO-TEQs. PCDFs concentrations and total WHO-TEQs were negatively associated with parity (p<0.05), and maternal age was positively associated with total WHO-TEQs (p<0.01). However, the associations with body mass index (BMI) and fish intake during pregnancy were not significant. These results were suggested that parity and maternal age are an important factor affecting the concentrations of PCDD/DFs and dl-PCBs in these specimens.

• Journal of Preventive Medicine and Public Health
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• v.9 no.1
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• pp.129-138
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• 1976

The causes and problems underlying deaths in perinatal period are often similar and might be expected to yield to same type of preventive measures. This is one of the reasons for attempting to develop a reporting of perinatal mortality and its related matters. This study aims at figuring out the biologic risk factors onto the perinatal death. Considering stillbirth and early neonatal mortality separately, considerable associations between stillbirth and reproductive history of women, are observed, ana it is found that prematurity is the the far most important factor in the early neonatal mortality.

• The Korean Journal of Ecology
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• v.27 no.6 s.122
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• pp.325-333
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• 2004

Birds were censused to investigate the composition of landscape structure for bird diversity around Ulsan between May and November 2002. Associations with three main categories of habitat variables were evaluated: 1) amount and type of forest; 2) residual habitats not classified as forest or crops; 3) land-use variables. Cluster analysis of bird community shows the highest forest variables of $79.06\%$, and the others are residual habitat variables ($17.98\%$), land-use variables ($2.94\%$) in spring, and forest variables of $57.77\%$, land-use variables ($23.16\%$), residual habitat variables ($18.47\%$) in autumn, respectively. In Principal Component Analysis of a total of 196 sites, the populations are strongly correlated to Component I ($54.8\%$) based forest habitats and to Component II based on land-use. Species preferring sites were clearly separated with heterogenous forest along the first axis. In autumn, the populations are moderately correlated to Component I based land-use and to component II based forest habitats. Species preferring local habitats were also clearly separated. Fifty three species of 1,700 birds were recorded: Brown-eared Bulbul, Vinous-throated Parrotbill, Great Tit, Tree Sparrow and Black-billed Magpie accounted for over $60\%$ of the observed birds in spring and autumn. The important species were Brown-eared Bulbul, Vinous-throated Parrotbill, Great Tit and Tree Sparrow in spring and autumn. Four habitats in terms of their species richness were computed as follows: Wonhyosan has the highest an expected species number, $E[S_{59}]=19$. Moonsusan has the lowest expected species number, $E[S_{59}]=17$ in spring. In autumn, Kuenamsan has the highest expected species number, $E[S_{63}]=16$. Moonsusan has the lowest expected species number, $E[S_{63}]=12$. Pairwise similarity declined with increasing distance between recording site and recording site from Moonsusan-Wonhyosan (0.62), the same geographical regions clustered separately in a UPGMA cluster tree in spring, and in autumn from Moonsusan-ChungJoksan (0.53).

• Journal of the Korean Society of Food Science and Nutrition
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• v.39 no.10
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• pp.1459-1466
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• 2010

This study was performed to identify the association between the metabolic syndrome and the biochemical measurements and nutrient intakes. A total of 1,431 people (533 males, 898 females) aged over 45 years living in Andong rural area participated in this study in 2003. Plasma aspartate aminotransferase (AST), alanine aminotransferase (ALT), $\gamma$-glutamyl transferase ($\gamma$-GT) and thiobarbituric acid reactive substances (TBARS) levels in metabolic syndrome were significantly higher than those in normal group. In multiple logistic regression, those biochemical measurements were found to be positively associated with the metabolic syndrome as the adjusted odds ratios (OR) 1.839 (p<0.001) by AST, 2.302 (p<0.01) by ALT, 2.143 (p<0.001) by $\gamma$-GT, and 1.874 (p<0.001) by TBARS. We also found that the increased level of those measurements tended to be strongly associated with high triglyceride among the metabolic syndrome components. However, the nutrient intakes between the metabolic syndrome and the normal group were not significantly different. Also, we could not find any nutrient intakes significantly associated with the metabolic syndrome, except high carbohydrate intake (>70% of kcal) compared to normal intake (55~70% of kcal) showed OR 0.781 (p<0.05). In analyzing the association of nutrient intakes with metabolic syndrome components, we found that the calorie intake was negatively associated with abdominal obesity (OR 0.696, p<0.05) and high fat intake (>25% of kcal) was positively associated with low HDL-cholesterol (OR 1.864, p<0.05). This study revealed that the biochemical measurements, such as plasma AST, ALT, $\gamma$-GT, and TBARS, are associated with metabolic syndrome, but considering the nutrient intakes, we suggest that further studies are needed to identify the associations.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.161-177
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• 2015

With the rapid evolution of technology, the size, number, and the type of databases has increased concomitantly, so data mining approaches face many challenging applications from databases. One such application is discovery of fraud patterns from agricultural product wholesale transaction instances. The agricultural product wholesale market in Korea is huge, and vast numbers of transactions have been made every day. The demand for agricultural products continues to grow, and the use of electronic auction systems raises the efficiency of operations of wholesale market. Certainly, the number of unusual transactions is also assumed to be increased in proportion to the trading amount, where an unusual transaction is often the first sign of fraud. However, it is very difficult to identify and detect these transactions and the corresponding fraud occurred in agricultural product wholesale market because the types of fraud are more intelligent than ever before. The fraud can be detected by verifying the overall transaction records manually, but it requires significant amount of human resources, and ultimately is not a practical approach. Frauds also can be revealed by victim's report or complaint. But there are usually no victims in the agricultural product wholesale frauds because they are committed by collusion of an auction company and an intermediary wholesaler. Nevertheless, it is required to monitor transaction records continuously and to make an effort to prevent any fraud, because the fraud not only disturbs the fair trade order of the market but also reduces the credibility of the market rapidly. Applying data mining to such an environment is very useful since it can discover unknown fraud patterns or features from a large volume of transaction data properly. The objective of this research is to empirically investigate the factors necessary to detect fraud transactions in an agricultural product wholesale market by developing a data mining based fraud detection model. One of major frauds is the phantom transaction, which is a colluding transaction by the seller(auction company or forwarder) and buyer(intermediary wholesaler) to commit the fraud transaction. They pretend to fulfill the transaction by recording false data in the online transaction processing system without actually selling products, and the seller receives money from the buyer. This leads to the overstatement of sales performance and illegal money transfers, which reduces the credibility of market. This paper reviews the environment of wholesale market such as types of transactions, roles of participants of the market, and various types and characteristics of frauds, and introduces the whole process of developing the phantom transaction detection model. The process consists of the following 4 modules: (1) Data cleaning and standardization (2) Statistical data analysis such as distribution and correlation analysis, (3) Construction of classification model using decision-tree induction approach, (4) Verification of the model in terms of hit ratio. We collected real data from 6 associations of agricultural producers in metropolitan markets. Final model with a decision-tree induction approach revealed that monthly average trading price of item offered by forwarders is a key variable in detecting the phantom transaction. The verification procedure also confirmed the suitability of the results. However, even though the performance of the results of this research is satisfactory, sensitive issues are still remained for improving classification accuracy and conciseness of rules. One such issue is the robustness of data mining model. Data mining is very much data-oriented, so data mining models tend to be very sensitive to changes of data or situations. Thus, it is evident that this non-robustness of data mining model requires continuous remodeling as data or situation changes. We hope that this paper suggest valuable guideline to organizations and companies that consider introducing or constructing a fraud detection model in the future.