• Korean Journal of Social Welfare
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• v.52
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• pp.241-272
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• 2003

The Self-Support Program was introduced as an antipoverty policy at 2002 year in Korea. But, the Self-Support Program's negative or positive effects have been debated from diverse perspectives to the present. Thus, in this paper, we analyzed the effects of the Self-Support Program using the survey data from program participants. Even though the effects of Workfare Programs can be evaluated by various indicators(ex. income, employment status, poverty status, etc.), in our analysis the effects of the Self-Support Program are evaluated by participants' self-reliant attitudes and behaviors. Major findings are as follows. First, we found that some kinds of self-reliant attitudes(ex. work commitment, self-esteem, etc.) were build up through participation on the Self-Support program, but some kinds of self-reliant factors(job competence and skill, self-sufficiency prospect, etc.) which are more relevant to the self-sufficiency were not build up thorough it. Second, we found the positive effects of the program among people who are females, olders, less educated, more healthy, and the participants who have acquired more certificate of qualifications. Third, we also found that self-support center's job training program, adequate task matching, agency climates and intra-networks influence on the positive effects of the Self-Support Program. These findings suggest that the Self-Support Program has not been successful up to now and it's reformations are required. It means that objectives of the Self-Support Program as an anti-poverty policy must be obvious and program contents must be diverse. And also program administration systems need to be reformed in oder to raise the effectiveness of the Self-Support Program.

• Journal of the Korean Institute of Landscape Architecture
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• v.40 no.3
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• pp.1-11
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• 2012

This study focused on establishing a natural rainwater circulation system using rainwater meant for relatively large urban development projects such as a new town development. In particular, when the location selection techniques for individual elements of a natural rainwater circulation system are developed for the integrated rainwater management, changes in hydrological environment will be minimized and the natural water circulation would be restored to realize the low impact development (LID). In that case, not only the excess will be reduced but water space and green areas in a city would also increase to improve the urban sustainability. First of all, there were five elements selected for the location selection of a rainwater circulation system intended for the integrated rainwater management: rainwater collection, infiltration, filtration, retention and movement spaces. After generating these items, the location selection items and criteria were defined for each of the five elements. For a technique to apply the generated evaluation items and criteria, a grid cell analysis was conducted based m the suitability index theory, and thematic maps were overlapped through suitability assessment of each element and graded based on the suitability index. The priority areas were identified for each element. The developed technique was applied to a site where Gim-cheon Innovation City development is planned to review its feasibility and limitations. The combined score of the overlapped map for each element was separated into five levels: very low, low, moderate, high and very high. Finally, it was concluded that creating a rainwater circulation system conceptual map m the current land use plan based on the outcome of the application would be useful in building a water circulation system at the de1ailed space planning stage after environmental and ecological planning. Furthermore, we use the results of this study as a means for environment-friendly urban planning for sustainable urban development.

• Journal of The Korean Ophthalmological Society
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• v.59 no.12
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• pp.1129-1136
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• 2018

Purpose: To compare the postoperative clinical outcomes after cataract surgery and implantation using the BunnyLens $MF^{(R)}$ and $ReSTOR^{(R)}$ multifocal intraocular lenses. Methods: Sixty-five eyes implanted with multifocal intraocular lenses were divided into two groups involving either $ReSTOR^{(R)}$ (39 eyes) or BunnyLens $MF^{(R)}$ (26 eyes) lenses. In these two groups, the distant and near visual acuity, astigmatism, spherical equivalent, and contrast sensitivity test were examined at preoperative and postoperative 1 week, 8 weeks, and 24 weeks. We compared the clinical efficacy between the two groups before and after cataract surgery using statistical analysis. Results: The mean value of distant and near visual acuity, and spherical equivalent of both groups after intraocular lens implantation were significantly improved, compared with the preoperative values (p < 0.05), while there was no significant differences between the two groups (p > 0.05). The means of postoperative distant and near visual acuity, astigmatism, and contrast sensitivity test were not significantly different between $ReSTOR^{(R)}$ and BunnyLens $MF^{(R)}$ lenses (p > 0.05). The mean numeric error of spherical equivalent at the final postoperative 24 weeks was $-0.17{\pm}0.50$ diopters (D) for the $ReSTOR^{(R)}$ lenses and $-0.34{\pm}0.52D$ for the BunnyLens $MF^{(R)}$ lenses (p > 0.05). Conclusions: BunnyLens $MF^{(R)}$ and $ReSTOR^{(R)}$ lenses showed no significant difference in clinical efficacy, including distance and near vision, spherical equivalent error, and contrast sensitivity test after cataract surgery. However, it should be noted that BunnyLens $MF^{(R)}$ lenses had a tendency toward myopic shift compared with $ReSTOR^{(R)}$ lenses.

• Korean Journal of Remote Sensing
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• v.17 no.1
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• pp.33-44
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• 2001

The paper presents several satellite models and satellite image decomposition methods for inaccessible area where ground control points can hardly acquired in conventional ways. First, 10 different satellite sensor models, which were extended from collinearity condition equations, were developed and then behavior of each sensor model was investigated. Secondly, satellite images were decomposed and also pseudo images were generated. The satellite sensor model extended from collinearity equations was represented by the six exterior orientation parameters in $1^{st}$, $2^{nd}$ and $3^{rd}$ order function of satellite image row. Among them, the rotational angle parameters such as $\omega$(omega) and $\Phi$(phi) correlated highly with positional parameters could be assigned to constant values. For inaccessible area, satellite images were decomposed, which means that two consecutive images were combined as one image, The combined image consists of one satellite image with ground control points and the other without ground control points. In addition, a pseudo image which is an imaginary image, was prepared from one satellite image with ground control points and the other without ground control points. In other words, the pseudo image is an arbitrary image bridging two consecutive images. For the experiments, SPOT satellite images exposed to the similar area in different pass were used. Conclusively, it was found that 10 different satellite sensor models and 5 different decomposed methods delivered different levels of accuracy. Among them, the satellite camera model with 1st order function of image row for positional orientation parameters and rotational angle parameter of kappa, and constant rotational angle parameter omega and phi provided the best 60m maximum error at check point with pseudo images arrangement.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.1
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• pp.147-159
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• 2021

After the 2020 Corona 19 pandemic, consumers' online consumption is increasing rapidly, and non-store online retail channels are showing high growth. In particular, social media is gaining its status as a social media market where direct transactions take place in the means of promoting companies' brands and products. In this study, changes in consumer behavior after the Corona 19 pandemic are different in choosing online shopping media such as existing online shopping malls and SNS markets that can be classified into open social media and closed social media when purchasing agri-food online. We tried to find out what type of product is preferred in the selection of agri-food products. For this study, demographic characteristics of consumers, perceived risk of consumers, and dietary lifestyle were set as independent variables to investigate the effect on online shopping media type and product selection. The summary of the empirical analysis results is as follows. When consumers purchase agri-food online, there are significant differences in demographic characteristics, consumer perception risks, and detailed factors of dietary lifestyle in selecting shopping channels such as online shopping malls, open social media, and closed social media. Appeared to be. The consumers who choose the open SNS market are higher in men than in women, with lower household income, and higher in consumers seeking health and taste. Consumers who choose the closed SNS market were analyzed as consumers who live in rural areas and have a high degree of risk perception for delivery. Consumers who choose existing online shopping malls have high educational background, high personal income, and high consumers seeking taste and economy. Through this study, we tried to provide practical assistance by providing a basis for judgment to farmers who have difficulty in selecting an online shopping medium suitable for their product characteristics. As a shopping channel for agri-food, social media is not a simple promotional channel, but a direct transaction. It can be differentiated from existing studies in that it is approached as a market that arises.

• Journal of the Korean Society of Radiology
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• v.18 no.2
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• pp.73-81
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• 2024

This study compared the cortical thickness of patients with mood disorders and a control group to assess structural abnormalities. A retrospective study was conducted from September 2020 to August 2022 at the Department of Psychiatry, P Hospital in Yangsan, Gyeongsangnam-do. The study included 44 individuals diagnosed with mood disorders and 59 healthy individuals without any pathological lesions. The 3D-T1 MPRAGE images obtained from magnetic resonance imaging examinations were utilized, and FreeSurfer software was employed to measure cortical thickness. Statistical analysis involved independent samples t-tests to measure the differences in means between the two groups, and Cohen's d test was used to compare the effect sizes of the differences. Furthermore, the correlation between the measured average cortical thickness and Positive and Negative Syndrome Scale scores was analyzed. The research results revealed that patients with mood disorders exhibited decreased cortical thickness compared to the normal control group in both superior frontal regions, both rostral middle frontal regions, both caudal middle frontal regions, both pars opercularis, pars orbitals, pars triangularis regions, both superior temporal regions, both inferior temporal regions, both lateral orbitofrontal regions, both medial orbitofrontal regions, both fusiform regions, both posterior cingulate regions, both isthmus cingulate regions, both superior parietal regions, both inferior parietal regions, both supramarginal regions, left postcentral region, right bank of the superior temporal sulcus region, right middle temporal region, right rostral anterior cingulate region, and right insula region. Among them, regions that showed differences with effect sizes of 0.8 or higher were left fusiform (d=0.82), pars opercularis (d=0.94), superior frontal (d=0.88), right lateral orbitofrontal (d=0.85), and pars orbitalis (d=0.89). Additionally, there was a weak negative correlation between PANSS scores and average cortical thickness in both the left hemisphere (r=-0.234) and right hemisphere (r=-0.230). These findings are expected to be helpful in identifying areas of cortical thickness reduction in patients with mood disorders compared to healthy individuals and understanding the relationship between symptom severity and cortical thickness changes.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.27-42
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• 2020

Traditional companies with offline stores were unable to secure large display space due to the problems of cost. This limitation inevitably allowed limited kinds of products to be displayed on the shelves, which resulted in consumers being deprived of the opportunity to experience various items. Taking advantage of the virtual space called the Internet, online shopping goes beyond the limits of limitations in physical space of offline shopping and is now able to display numerous products on web pages that can satisfy consumers with a variety of needs. Paradoxically, however, this can also cause consumers to experience the difficulty of comparing and evaluating too many alternatives in their purchase decision-making process. As an effort to address this side effect, various kinds of consumer's purchase decision support systems have been studied, such as keyword-based item search service and recommender systems. These systems can reduce search time for items, prevent consumer from leaving while browsing, and contribute to the seller's increased sales. Among those systems, recommender systems based on association rule mining techniques can effectively detect interrelated products from transaction data such as orders. The association between products obtained by statistical analysis provides clues to predicting how interested consumers will be in another product. However, since its algorithm is based on the number of transactions, products not sold enough so far in the early days of launch may not be included in the list of recommendations even though they are highly likely to be sold. Such missing items may not have sufficient opportunities to be exposed to consumers to record sufficient sales, and then fall into a vicious cycle of a vicious cycle of declining sales and omission in the recommendation list. This situation is an inevitable outcome in situations in which recommendations are made based on past transaction histories, rather than on determining potential future sales possibilities. This study started with the idea that reflecting the means by which this potential possibility can be identified indirectly would help to select highly recommended products. In the light of the fact that the attributes of a product affect the consumer's purchasing decisions, this study was conducted to reflect them in the recommender systems. In other words, consumers who visit a product page have shown interest in the attributes of the product and would be also interested in other products with the same attributes. On such assumption, based on these attributes, the recommender system can select recommended products that can show a higher acceptance rate. Given that a category is one of the main attributes of a product, it can be a good indicator of not only direct associations between two items but also potential associations that have yet to be revealed. Based on this idea, the study devised a recommender system that reflects not only associations between products but also categories. Through regression analysis, two kinds of associations were combined to form a model that could predict the hit rate of recommendation. To evaluate the performance of the proposed model, another regression model was also developed based only on associations between products. Comparative experiments were designed to be similar to the environment in which products are actually recommended in online shopping malls. First, the association rules for all possible combinations of antecedent and consequent items were generated from the order data. Then, hit rates for each of the associated rules were predicted from the support and confidence that are calculated by each of the models. The comparative experiments using order data collected from an online shopping mall show that the recommendation accuracy can be improved by further reflecting not only the association between products but also categories in the recommendation of related products. The proposed model showed a 2 to 3 percent improvement in hit rates compared to the existing model. From a practical point of view, it is expected to have a positive effect on improving consumers' purchasing satisfaction and increasing sellers' sales.

• Journal of Global Scholars of Marketing Science
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• v.18 no.4
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• pp.119-155
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• 2008

Customer Relationship Management(CRM) has been a sustainable competitive edge of many companies. CRM analyzes customer data for designing and executing targeted marketing analysing customer behavior in order to make decisions relating to products and services including management information system. It is critical for companies to get and maintain profitable customers. How to manage relationships with customers effectively has become an important issue for both academicians and practitioners in recent years. However, the existing academic literature and the practical applications of customer relationship management(CRM) strategies have been focused on the technical process and organizational structure about the implementation of CRM. These limited focus on CRM lead to the result of numerous reports of failed implementations of various types of CRM projects. Many of these failures are also related to the absence of marketing approach. Identifying successful factors and outcomes focused on marketing concept before introducing a CRM project are a pre-implementation requirements. Many researchers have attempted to find the factors that contribute to the success of CRM. However, these research have some limitations in terms of marketing approach without explaining how the marketing based factors contribute to the CRM success. An understanding of how to manage relationship with crucial customers effectively based marketing approach has become an important topic for both academicians and practitioners. However, the existing papers did not provide a clear antecedent and outcomes factors focused on marketing approach. This paper attempt to validate whether or not such various marketing factors would impact on relational quality and CRM performance in terms of marketing oriented perceptivity. More specifically, marketing oriented factors involving market orientation, customer orientation, customer information orientation, and core customer orientation can influence relationship quality(satisfaction and trust) and CRM outcome(customer retention and customer share). Another major goals of this research are to identify the effect of relationship quality on CRM outcomes consisted of customer retention and share to show the relationship strength between two factors. Based on meta analysis for conventional studies, I can construct the following research model. An empirical study was undertaken to test the hypotheses with data from various companies. Multiple regression analysis and t-test were employed to test the hypotheses. The reliability and validity of our measurements were tested by using Cronbach's alpha coefficient and principal factor analysis respectively, and seven hypotheses were tested through performing correlation test and multiple regression analysis. The first key outcome is a theoretically and empirically sound CRM factors(marketing orientation, customer orientation, customer information orientation, and core customer orientation.) in the perceptive of marketing. The intensification of ${\beta}$coefficient among antecedents factors in terms of marketing was not same. In particular, The effects on customer trust of marketing based CRM antecedents were significantly confirmed excluding core customer orientation. It was notable that the direct effects of core customer orientation on customer trust were not exist. This means that customer trust which is firmly formed by long term tasks will not be directly linked to the core customer orientation. the enduring management concerned with this interactions is probably more important for the successful implementation of CRM. The second key result is that the implementation and operation of successful CRM process in terms of marketing approach have a strong positive association with both relationship quality(customer trust/customer satisfaction) and CRM performance(customer retention and customer possession). The final key fact that relationship quality has a strong positive effect on customer retention and customer share confirms that improvements in customer satisfaction and trust improve accessibility to customers, provide more consistent service and ensure value-for-money within the front office which result in growth of customer retention and customer share. Particularly, customer satisfaction and trust which is main components of relationship quality are found to be positively related to the customer retention and customer share. Interactive managements of these main variables play key roles in connecting the successful antecedent of CRM with final outcome involving customer retention and share. Based on research results, This paper suggest managerial implications concerned with constructions and executions of CRM focusing on the marketing perceptivity. I can conclude in general the CRM can be achieved by the recognition of antecedents and outcomes based on marketing concept. The implementation of marketing concept oriented CRM will be connected with finding out about customers' purchasing habits, opinions and preferences profiling individuals and groups to market more effectively and increase sales changing the way you operate to improve customer service and marketing. Benefiting from CRM is not just a question of investing the right software, but adapt CRM users to the concept of marketing including marketing orientation, customer orientation, and customer information orientation. No one deny that CRM is a process or methodology used to develop stronger relationships being composed of many technological components, but thinking about CRM in primarily technological terms is a big mistake. We can infer from this paper that the more useful way to think and implement about CRM is as a process that will help bring together lots of pieces of marketing concept about customers, marketing effectiveness, and market trends. Finally, a real situation we conducted our research may enable academics and practitioners to understand the antecedents and outcomes in the perceptive of marketing more clearly.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.141-166
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• 2019

Recently, channels like social media and SNS create enormous amount of data. In all kinds of data, portions of unstructured data which represented as text data has increased geometrically. But there are some difficulties to check all text data, so it is important to access those data rapidly and grasp key points of text. Due to needs of efficient understanding, many studies about text summarization for handling and using tremendous amounts of text data have been proposed. Especially, a lot of summarization methods using machine learning and artificial intelligence algorithms have been proposed lately to generate summary objectively and effectively which called "automatic summarization". However almost text summarization methods proposed up to date construct summary focused on frequency of contents in original documents. Those summaries have a limitation for contain small-weight subjects that mentioned less in original text. If summaries include contents with only major subject, bias occurs and it causes loss of information so that it is hard to ascertain every subject documents have. To avoid those bias, it is possible to summarize in point of balance between topics document have so all subject in document can be ascertained, but still unbalance of distribution between those subjects remains. To retain balance of subjects in summary, it is necessary to consider proportion of every subject documents originally have and also allocate the portion of subjects equally so that even sentences of minor subjects can be included in summary sufficiently. In this study, we propose "subject-balanced" text summarization method that procure balance between all subjects and minimize omission of low-frequency subjects. For subject-balanced summary, we use two concept of summary evaluation metrics "completeness" and "succinctness". Completeness is the feature that summary should include contents of original documents fully and succinctness means summary has minimum duplication with contents in itself. Proposed method has 3-phases for summarization. First phase is constructing subject term dictionaries. Topic modeling is used for calculating topic-term weight which indicates degrees that each terms are related to each topic. From derived weight, it is possible to figure out highly related terms for every topic and subjects of documents can be found from various topic composed similar meaning terms. And then, few terms are selected which represent subject well. In this method, it is called "seed terms". However, those terms are too small to explain each subject enough, so sufficient similar terms with seed terms are needed for well-constructed subject dictionary. Word2Vec is used for word expansion, finds similar terms with seed terms. Word vectors are created after Word2Vec modeling, and from those vectors, similarity between all terms can be derived by using cosine-similarity. Higher cosine similarity between two terms calculated, higher relationship between two terms defined. So terms that have high similarity values with seed terms for each subjects are selected and filtering those expanded terms subject dictionary is finally constructed. Next phase is allocating subjects to every sentences which original documents have. To grasp contents of all sentences first, frequency analysis is conducted with specific terms that subject dictionaries compose. TF-IDF weight of each subjects are calculated after frequency analysis, and it is possible to figure out how much sentences are explaining about each subjects. However, TF-IDF weight has limitation that the weight can be increased infinitely, so by normalizing TF-IDF weights for every subject sentences have, all values are changed to 0 to 1 values. Then allocating subject for every sentences with maximum TF-IDF weight between all subjects, sentence group are constructed for each subjects finally. Last phase is summary generation parts. Sen2Vec is used to figure out similarity between subject-sentences, and similarity matrix can be formed. By repetitive sentences selecting, it is possible to generate summary that include contents of original documents fully and minimize duplication in summary itself. For evaluation of proposed method, 50,000 reviews of TripAdvisor are used for constructing subject dictionaries and 23,087 reviews are used for generating summary. Also comparison between proposed method summary and frequency-based summary is performed and as a result, it is verified that summary from proposed method can retain balance of all subject more which documents originally have.

• International Journal of Highway Engineering
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• v.13 no.3
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• pp.21-30
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• 2011

As well known, dowel bars are used to transfer traffic load acting on one edge to another edge of concrete slab in concrete pavement system. The dowel bars widely used in South Korea are round shape steel bar and they shows satisfactory performance under bending stress which is developed by repetitive traffic loading and environment loading. However, they are not invulnerable to erosion that may be caused by moisture from masonry joint or bottom of the pavement system. Especially, the erosion could rapidly progress with saline to prevent frost of snow in winter time. The problem under this circumstance is that the erosion not only drops strength of the steel dower bar but also comes with volume expansion of the steel dowel bar which can reduce load transferring efficiency of the steel dowel bar. To avoid this erosion problem in reasonable expenses, dowers bars with various materials are being developed. Fiber reinforced plastic(FRP) dower that is presented in this paper is suggested as an alternative of the steel dowel bar and it shows competitive resistance against erosion and tensile stress. The FRP dowel bar is developed in tube shape and is filled with high strength no shrinkage. Several slab thickness designs with the FRP dowel bars are performed by evaluating bearing stress between the dowel bar and concrete slab. To calculated the bearing stresses, theoretical formulation and finite element method(FEM) are utilized with material properties measured from laboratory tests. The results show that both FRP tube dowel bars with diameters of 32mm and 40mm satisfy bearing stress requirement for dowel bars. Also, with consideration that lean concrete is typical material to support concrete slab in South Korea, which means low load transfer efficiency and, therefore, low bearing stress, the FRP tube dowel bar can be used as a replacement of round shape steel bar.