• Journal of Family Resource Management and Policy Review
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• v.26 no.3
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• pp.1-17
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• 2022

This study focused on the heterogeneity of groups in single-person households, to identify how middle-aged single-person households is categorized by sub-groups and to come up with policy measures to overcome social exclusion by examining predictive factors for the type of social exclusion. Potential class analysis and multinomial logistic regression analysis were conducted on a total of 361 middle-aged single-person households using the 14th Korea Replication Panel data. The social exclusion index of these households was measured consisting of 10 six-dimensional indicators. The results showed that middle-aged single-person households had five different types: "non-exclusion"(29.6%), "health restriction"(14.3%), "interact restriction and middle-risk multiple-exclusion" (12.0%), "income and health exclusion"(14.1%), and "high-risk multiple-exclusion"(30.0%). More than 70% of the respondents experienced social exclusion, and most of the exclusion types were multiple exclusion. When examining the factors affecting each exclusion type, the 'subjective health level' was a common major predictor, and family interact, age and leisure activity satisfaction variables were significant predictors of the 'high-risk multiple exclusion type' and 'the interact restriction and middle-risk multiple-exclusion type'. Based on these results, a multidimensional intervention strategy is an effective measure to solve the social exclusion problem of middle-aged single-person households, and practical measures should be considered by strengthening 'health' and exchanges.

• Korean Journal of Culture and Social Issue
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• v.16 no.2
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• pp.125-146
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• 2010

A total of 181 college students(61 males 121 females) with at least 5 years of living abroad (Returnee Group) and another group of 181 students (92 males and 93 females) without extended period of living abroad (Comparison Group) participated in the study by completing a questionnaire consisting of Acculturation Index, Multidimensional Acculturation Scale, Student Adaptation to College Questionnaire, Revised UCLA Loneliness Scale, CES-D, and WHOQOL. The results indicated that the Returnee Group, compared to the Comparison Group, reported as good adjustment toward college life in Korea and positive attitude toward the Korean identity, but a higher level of loneliness. When the Returnee Group were divided into 4 different groups on the basis of acculturation pattern, the Integration and Assimilation Type reported a better adjustment to college life, lower depression and loneliness and better quality of life than the Marginalization Type. The Mariginalization Type appears to be the most vulnerable group, experiencing difficulties in all areas of adjustment, and is clearly in need of interventions. Limitations of the present study and suggestions for future research were discussed.

• Korean Journal of Psychosomatic Medicine
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• v.32 no.1
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• pp.1-9
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• 2024

Frailty is a clinical syndrome as an increased vulnerability to stressors, leading to a decrease in physiologic reserves and a decline in the ability to maintain a good homeostasis. This condition leads to an increased risk of hospitalization, disability and mortality. Frailty occurs due to various causes and requires a multidimensional approach. It is also important to detect and manage it early. Frailty is also deeply related to neuropsychiatric problems such as pain and depression. In evaluating frailty, it is desirable to comprehensively consider not only physical areas such as disease, nutrition, movement, and sensory functions, but also psychosocial areas, and representative scales include Fried's physical frailty phenotype and Rockwood's frailty index. Physical activity and appropriate protein intake are important for frailty management, and inappropriate drug use should be reduced and oral care, cognitive function, and falls should also be noted. Frailty and pain can affect each other, and pain can promote frailty. Evidence has been published that hormone and protein abnormalities, immune system activity and inflammatory response, and epigenetic mechanisms work in common in the field of frailty and pain. More extensive and high-quality research should be conducted in the future, and the quality of life will be improved if the results are applied to the suppression and treatment of old age and pain.

• Korean Journal of Ecology and Environment
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• v.53 no.1
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• pp.31-45
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• 2020

The biological indices based on the community structure with species richness and/or abundance are commonly used to assess aquatic ecosystem health. Meanwhile, recently functional traits-based approach is considered in ecosystem health assessment to reflect ecosystem functioning. In this study, we developed a database of biological traits for 136 taxa consisting of major stream insects (Ephemeroptera, Plecoptera, Trichoptera, Coleoptera, and Odonata) collected at Korean streams on the nationwide scale. In addition, we obtained environmental variables in five categories (geography, climate, land use, hydrology and physicochemistry) measured at each sampling site. We evaluated the relationships between community indices based on taxonomic diversity and functional diversity estimated from biological traits. We classified sampling sites based on similarities of their environmental variables and evaluated relations between clusters of sampling sites and diversity indices and biological traits. Our results showed that functional diversity was highly correlated with Shannon diversity index and species richness. The six clusters of sampling sites defined by a hierarchical cluster analysis reflected differences of their environmental variables. Samples in cluster 1 were mostly from high altitude areas, whereas samples in cluster 6 were from lowland areas. Non-metric multidimensional scaling (NMDS) displayed similar patterns with cluster analysis and presented variation of taxonomic diversity and functional diversity. Based on NMDS and community-weighted mean trait value matrix, species in clusters 1-3 displayed the resistance strategy in the life history strategy to the environmental variables whereas species in clusters 4-6 presented the resilience strategy. These results suggest that functional diversity can complement the biological monitoring assessment based on taxonomic diversity and can be used as biological monitoring assessment tool reflecting changes of ecosystem functioning responding to environmental changes.

• Korean Journal of Environmental Biology
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• v.36 no.3
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• pp.400-411
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• 2018

This study was a survey of the Wonju stream in Wonju city from May 2015 to September 2016. A total of three sites were selected from the upstream area Gwanseol-dong to the downstream area Hojeo-myeon. Physicochemical analysis, aquatic insect changes, cluster analysis, functional group analysis, rarefaction curve, and statistical analysis were compared between 2004 and 2016. A total of 19 species (38.78%) in 2004 and 22 species (36.67%) in 2016 were analyzed, with the largest number belonging to ephemeroptera. The individual ratio ranged from 27,759.2 (ind. $m^{-2}$, 84.30%) in 2004 to 4,573.2 (ind. $m^{-2}$, 41.64%) in 2016, with the highest number involving diptera. As a result of the community analysis, significant differences were detected in the indices of dominance, diversity, evenness, and richness in 2004 and 2016 (p<0.05). Burrowers of the habitat orientation groups showed the greatest variation with an average of -68.00% (${\pm}2.15$) and the collector-gatherers of the functional feeding groups showed the highest variation of -40.12% (${\pm}1.77$). The rarefaction curve analysis suggested that the species was the poorest in the midstream regions in 2004 and 2016. Physical factors and water quality showed a significant correlation with diversity index, evenness index, and the number of individuals. MDS analysis of the similarity of upstream and downstream regions was high in 2004, and low in 2016. The differences were attributed to physicochemical changes such as increase in flow velocity due to improvement of small dams and changes in bottom structure.

• Korean Journal of Ecology and Environment
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• v.52 no.2
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• pp.105-117
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• 2019

In order to investigate the characteristics of benthic macroinvertebrate communities in the Gihwa stream, a tributary of the Dong River, we surveyed the community and environmental factors in April and November 2013 at 6 sites. The benthic macroinvertebrate taxa represented total 63 species belonging to 29 families, 12 orders, 5 classes and 4 phyla. Total 48 (10~28 in each site) species were collected in April and 44 (13~24 in each site) in November. The number of individuals increased slightly from $560{\sim}2,290m^{-2}$ in April to $806{\sim}3,674m^{-2}$ in November. Chironomidae spp. was dominant species in April and Stenopsyche bergeri was dominant species in November. In the Functional Feeding Groups, Gathering-collector(53.9%) was dominant in April, while Filtering-collector (44.3%) increased in November. Intolerant order category (i.e. EPT species richness) in St.1, St.5 and St.6 increased in November compared to April due to the increase of Trichoptera. St.2, St.3 and St.4, which were located near the fish farm, were low EPT as a whole, but Benthic macroinvertebrate index (BMI) was good state in November than April due to decrease of Chironomidae spp.. The environmental factors in the survey site showed similar tendency except for St.1 between both seasons, and electrical conductivity, salinity, and water width showed seasonal differences. Cluster analysis and Nonmetric multidimensional scaling (NMDS) based on benthic macroinvertebrate community data were divided into two groups according to season. Electrical conductivity, salinity and substrate composition were the most influential factors determining the distribution patterns of macroinvertebrate communities.

• Progress in Medical Physics
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• v.9 no.4
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• pp.227-245
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• 1998

A most appropriate model of 3-D conformal radiotherapy has been induced by clinical evaluation and animal study, and therapeutic gains were evaluated by numerical equation of tumor control probability(TCP) and normal tissue complication probability (NTCP). The radiation dose to the tumor and the adjacent normal organs was accurately evaluated and compared using the dose volume histogram(DVH). The TCP and NTCP was derived from the distribution of given dosage and irradiated volume, and these numbers were used as the biological index for the assessment of the treatment effects. Ten patients with liver disease have been evaluated and 3 dogs were sacrificed for this study. Based on the 3-D images of the tumor and adjacent organs, the optimum radiation dose and the projection direction which could maximize the radiation effect while minimizing the effects to the adjacent organs could be decided. 3). The most effective collimation for the normal adjacent organs was made through the beams eye view with the use of multileaf collimator. When the dose was increased from 50Gy to 70Gy, the TCP for the conventional 2-port radiation and the 5-port multidimensional therapy was 0.982 and 0.995 respectively, while the NTCP was 0.725 and 0.142 respectively, suggesting that the 3-D conformal radiotherapy might be the appropriate therapy to apply sufficient radiation dose to the tumor while minimizing the damages to the normal areas of the liver. Positive correlation was observed between the NTCP and the actual complication of the normal liver in the animal study. The present study suggest that the use of 3-D conformal radiotherapy and the application of the mathematical models of TCP and NTCP may provide the improvements in the treatment of hepatoma with enhanced results.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.139-161
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• 2019

The utilization of the e-commerce market has become a common life style in today. It has become important part to know where and how to make reasonable purchases of good quality products for customers. This change in purchase psychology tends to make it difficult for customers to make purchasing decisions in vast amounts of information. In this case, the recommendation system has the effect of reducing the cost of information retrieval and improving the satisfaction by analyzing the purchasing behavior of the customer. Amazon and Netflix are considered to be the well-known examples of sales marketing using the recommendation system. In the case of Amazon, 60% of the recommendation is made by purchasing goods, and 35% of the sales increase was achieved. Netflix, on the other hand, found that 75% of movie recommendations were made using services. This personalization technique is considered to be one of the key strategies for one-to-one marketing that can be useful in online markets where salespeople do not exist. Recommendation techniques that are mainly used in recommendation systems today include collaborative filtering and content-based filtering. Furthermore, hybrid techniques and association rules that use these techniques in combination are also being used in various fields. Of these, collaborative filtering recommendation techniques are the most popular today. Collaborative filtering is a method of recommending products preferred by neighbors who have similar preferences or purchasing behavior, based on the assumption that users who have exhibited similar tendencies in purchasing or evaluating products in the past will have a similar tendency to other products. However, most of the existed systems are recommended only within the same category of products such as books and movies. This is because the recommendation system estimates the purchase satisfaction about new item which have never been bought yet using customer's purchase rating points of a similar commodity based on the transaction data. In addition, there is a problem about the reliability of purchase ratings used in the recommendation system. Reliability of customer purchase ratings is causing serious problems. In particular, 'Compensatory Review' refers to the intentional manipulation of a customer purchase rating by a company intervention. In fact, Amazon has been hard-pressed for these "compassionate reviews" since 2016 and has worked hard to reduce false information and increase credibility. The survey showed that the average rating for products with 'Compensated Review' was higher than those without 'Compensation Review'. And it turns out that 'Compensatory Review' is about 12 times less likely to give the lowest rating, and about 4 times less likely to leave a critical opinion. As such, customer purchase ratings are full of various noises. This problem is directly related to the performance of recommendation systems aimed at maximizing profits by attracting highly satisfied customers in most e-commerce transactions. In this study, we propose the possibility of using new indicators that can objectively substitute existing customer 's purchase ratings by using RFM multi-dimensional analysis technique to solve a series of problems. RFM multi-dimensional analysis technique is the most widely used analytical method in customer relationship management marketing(CRM), and is a data analysis method for selecting customers who are likely to purchase goods. As a result of verifying the actual purchase history data using the relevant index, the accuracy was as high as about 55%. This is a result of recommending a total of 4,386 different types of products that have never been bought before, thus the verification result means relatively high accuracy and utilization value. And this study suggests the possibility of general recommendation system that can be applied to various offline product data. If additional data is acquired in the future, the accuracy of the proposed recommendation system can be improved.

• Korean Journal of Ecology and Environment
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• v.55 no.1
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• pp.35-48
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• 2022

Fish assemblage of total 325 of Korean peninsula estuaries were surveyed to analyze the characteristics of community structure and diversity by sea areas for three years from 2016 to 2018. The scale (stream width) of Korean estuaries were various (14~3,356 m), and 68.9% of all estuaries showed salinity of less than 2 psu. Total 149 species classified into 52 families of fish were identified, and the dominant and sub-dominant species were Tribolodon hakonensis (relative abundance, RA, 12.5%) and Mugil cephalus (RA, 9.5%), respectively. The estuary of the Korean Peninsula had different physical and chemical habitat environments depending on the sea area, and accordingly, fish community structure also showed statistically significant differences (PERMANOVA, Pseudo-F=26.69, P=0.001). In addition, the NMDS (nonmetric multidimensional scaling) results showed the patterns that indicating fish community difference by sea areas, even though low community similarity within sea area (SIMPER, 21.79~26.39%). The estuaries of east sea areas were distinguished from the others in the aspects of which, the higher importance of migratory fishes and endangered species, and that of brackish species were characterized at south sea estuaries. However, the estuaries of west sea showed higher importance of species that have a relation with freshwater (primary freshwater species, exotic species), which is the result that associating with the lower salinity of west sea estuaries because of the high ratio of closed estuaries(78.2%). The SIMPER analysis, scoring the contribution rates of species to community similarity, also showed results corresponding to the tendency of different fish community structures according to each sea area. So far, In Korea, most studies on fish communities in estuaries have been conducted in a single estuary unit, which made it difficult to understand the characteristics of estuaries at the national level, which are prerequisite for policy establishment. In present study, we are providing fish community structure characteristics of Korean estuaries in a national scale, including diversity index, habitat salinity ranges of major species, distribution of migratory species. We are expecting that our results could be utilized as baseline information for establishing management policies or further study of Korean estuaries.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.1-21
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• 2020

With the rapid development of artificial intelligence technology, various techniques have been developed to extract meaningful information from unstructured text data which constitutes a large portion of big data. Over the past decades, text mining technologies have been utilized in various industries for practical applications. In the field of business intelligence, it has been employed to discover new market and/or technology opportunities and support rational decision making of business participants. The market information such as market size, market growth rate, and market share is essential for setting companies' business strategies. There has been a continuous demand in various fields for specific product level-market information. However, the information has been generally provided at industry level or broad categories based on classification standards, making it difficult to obtain specific and proper information. In this regard, we propose a new methodology that can estimate the market sizes of product groups at more detailed levels than that of previously offered. We applied Word2Vec algorithm, a neural network based semantic word embedding model, to enable automatic market size estimation from individual companies' product information in a bottom-up manner. The overall process is as follows: First, the data related to product information is collected, refined, and restructured into suitable form for applying Word2Vec model. Next, the preprocessed data is embedded into vector space by Word2Vec and then the product groups are derived by extracting similar products names based on cosine similarity calculation. Finally, the sales data on the extracted products is summated to estimate the market size of the product groups. As an experimental data, text data of product names from Statistics Korea's microdata (345,103 cases) were mapped in multidimensional vector space by Word2Vec training. We performed parameters optimization for training and then applied vector dimension of 300 and window size of 15 as optimized parameters for further experiments. We employed index words of Korean Standard Industry Classification (KSIC) as a product name dataset to more efficiently cluster product groups. The product names which are similar to KSIC indexes were extracted based on cosine similarity. The market size of extracted products as one product category was calculated from individual companies' sales data. The market sizes of 11,654 specific product lines were automatically estimated by the proposed model. For the performance verification, the results were compared with actual market size of some items. The Pearson's correlation coefficient was 0.513. Our approach has several advantages differing from the previous studies. First, text mining and machine learning techniques were applied for the first time on market size estimation, overcoming the limitations of traditional sampling based- or multiple assumption required-methods. In addition, the level of market category can be easily and efficiently adjusted according to the purpose of information use by changing cosine similarity threshold. Furthermore, it has a high potential of practical applications since it can resolve unmet needs for detailed market size information in public and private sectors. Specifically, it can be utilized in technology evaluation and technology commercialization support program conducted by governmental institutions, as well as business strategies consulting and market analysis report publishing by private firms. The limitation of our study is that the presented model needs to be improved in terms of accuracy and reliability. The semantic-based word embedding module can be advanced by giving a proper order in the preprocessed dataset or by combining another algorithm such as Jaccard similarity with Word2Vec. Also, the methods of product group clustering can be changed to other types of unsupervised machine learning algorithm. Our group is currently working on subsequent studies and we expect that it can further improve the performance of the conceptually proposed basic model in this study.