• Journal of Service Research and Studies
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• v.11 no.4
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• pp.1-20
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• 2021

This study was conducted to derive a model of the legal system that is the basis for realizing the service economy, political administration, and social education system. Based on the experience of mankind's legal system operation in the historical era for the past 5,000 years, a legal system model that will make the future human society sustainable has been established. The problems of the current legal system were analyzed at the fundamental level. The root cause of injustice and unfairness was analyzed and a new legal system was designed. Through the legal systems of various national societies that have been attempted in the history of mankind, the structure of the legal system that is desirable for the modern society was designed. Human society, which has experienced how much good legal system has been and is being abused by human irrationality and nonsense, needs to make an effort to change the legal system paradigm itself by learning lessons from failure. This study derives the basis for a legal system that can realize justice and a fair society in the long term. It proposed a model for improving the legal system that allows human society to be happy for a long time. To this end, the fundamental role of the legal system was analyzed at the ideological level and the problems of the current legal system were presented. In addition, the problem of fundamental assumptions about human nature was analyzed and improved assumptions were presented. The structural system of the current legal system was analyzed and a new structure was proposed. In addition, a plan for the operation of a new legal system based on a new structure was suggested. The new legal system was named servicism system. This is because it is a model centered on thorough checks and balances between all opponents, not a simple linear one-dimensional legal system, but a multidimensional legal system, and because it is a viewpoint that clearly recognizes both human reason and desire. The new system is a model that reflects the confrontation between the rule of law and the non-law rule and the confrontation between the power people and the general public. A follow-up study is needed on a concrete plan for transitioning from the current legal system to a new legal system.

• Journal of Intelligence and Information Systems
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• v.16 no.2
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• pp.129-141
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• 2010

An Internet shopping mall for clothing operates a warehouse for packing and shipping products to fulfill its orders. All the products in the warehouse are put into the boxes of same brands and the boxes are stored in a row on shelves equiped in the warehouse. To make picking and managing easy, boxes of the same brands are located side by side on the shelves. When new products arrive to the warehouse for storage, the products of a brand are put into boxes and those boxes are located adjacent to the boxes of the same brand. If there is not enough space for the new coming boxes, however, some boxes of other brands should be moved away and then the new coming boxes are located adjacent in the resultant vacant spaces. We want to minimize the movement of the existing boxes of other brands to another places on the shelves during the warehousing of new coming boxes, while all the boxes of the same brand are kept side by side on the shelves. Firstly, we define the adjacency of boxes by looking the shelves as an one dimensional series of spaces to store boxes, i.e. cells, tagging the series of cells by a series of numbers starting from one, and considering any two boxes stored in the cells to be adjacent to each other if their cell numbers are continuous from one number to the other number. After that, we tried to formulate the problem into an integer programming model to obtain an optimal solution. An integer programming formulation and Branch-and-Bound technique for this problem may not be tractable because it would take too long time to solve the problem considering the number of the cells or boxes in the warehouse and the computing power of the Internet shopping mall. As an alternative approach, we designed a fast heuristic method for this reallocation problem by focusing on just the unused spaces-empty cells-on the shelves, which results in an assignment problem model. In this approach, the new coming boxes are assigned to each empty cells and then those boxes are reorganized so that the boxes of a brand are adjacent to each other. The objective of this new approach is to minimize the movement of the boxes during the reorganization process while keeping the boxes of a brand adjacent to each other. The approach, however, does not ensure the optimality of the solution in terms of the original problem, that is, the problem to minimize the movement of existing boxes while keeping boxes of the same brands adjacent to each other. Even though this heuristic method may produce a suboptimal solution, we could obtain a satisfactory solution within a satisfactory time, which are acceptable by real world experts. In order to justify the quality of the solution by the heuristic approach, we generate 100 problems randomly, in which the number of cells spans from 2,000 to 4,000, solve the problems by both of our heuristic approach and the original integer programming approach using a commercial optimization software package, and then compare the heuristic solutions with their corresponding optimal solutions in terms of solution time and the number of movement of boxes. We also implement our heuristic approach into a storage location assignment system for the Internet shopping mall.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.105-122
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• 2019

Dimensionality reduction is one of the methods to handle big data in text mining. For dimensionality reduction, we should consider the density of data, which has a significant influence on the performance of sentence classification. It requires lots of computations for data of higher dimensions. Eventually, it can cause lots of computational cost and overfitting in the model. Thus, the dimension reduction process is necessary to improve the performance of the model. Diverse methods have been proposed from only lessening the noise of data like misspelling or informal text to including semantic and syntactic information. On top of it, the expression and selection of the text features have impacts on the performance of the classifier for sentence classification, which is one of the fields of Natural Language Processing. The common goal of dimension reduction is to find latent space that is representative of raw data from observation space. Existing methods utilize various algorithms for dimensionality reduction, such as feature extraction and feature selection. In addition to these algorithms, word embeddings, learning low-dimensional vector space representations of words, that can capture semantic and syntactic information from data are also utilized. For improving performance, recent studies have suggested methods that the word dictionary is modified according to the positive and negative score of pre-defined words. The basic idea of this study is that similar words have similar vector representations. Once the feature selection algorithm selects the words that are not important, we thought the words that are similar to the selected words also have no impacts on sentence classification. This study proposes two ways to achieve more accurate classification that conduct selective word elimination under specific regulations and construct word embedding based on Word2Vec embedding. To select words having low importance from the text, we use information gain algorithm to measure the importance and cosine similarity to search for similar words. First, we eliminate words that have comparatively low information gain values from the raw text and form word embedding. Second, we select words additionally that are similar to the words that have a low level of information gain values and make word embedding. In the end, these filtered text and word embedding apply to the deep learning models; Convolutional Neural Network and Attention-Based Bidirectional LSTM. This study uses customer reviews on Kindle in Amazon.com, IMDB, and Yelp as datasets, and classify each data using the deep learning models. The reviews got more than five helpful votes, and the ratio of helpful votes was over 70% classified as helpful reviews. Also, Yelp only shows the number of helpful votes. We extracted 100,000 reviews which got more than five helpful votes using a random sampling method among 750,000 reviews. The minimal preprocessing was executed to each dataset, such as removing numbers and special characters from text data. To evaluate the proposed methods, we compared the performances of Word2Vec and GloVe word embeddings, which used all the words. We showed that one of the proposed methods is better than the embeddings with all the words. By removing unimportant words, we can get better performance. However, if we removed too many words, it showed that the performance was lowered. For future research, it is required to consider diverse ways of preprocessing and the in-depth analysis for the co-occurrence of words to measure similarity values among words. Also, we only applied the proposed method with Word2Vec. Other embedding methods such as GloVe, fastText, ELMo can be applied with the proposed methods, and it is possible to identify the possible combinations between word embedding methods and elimination methods.

• Composites Research
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• v.15 no.4
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• pp.23-31
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• 2002

The two dimensional size effect of specimen gauge section ($length{\;}{\times}{\;}width$) was investigated on the compressive behavior of a T300/924 $\textrm{[}45/-45/0/90\textrm{]}_{3s}$, carbon fiber-epoxy laminate. A modified ICSTM compression test fixture was used together with an anti-buckling device to test 3mm thick specimens with a $30mm{\;}{\times}{\;}30mm,{\;}50mm{\;}{\times}{\;}50mm,{\;}70mm{\;}{\times}{\;}70mm{\;}and{\;}90mm{\;}{\times}{\;}90mm$ gauge length by width section. In all cases failure was sudden and occurred mainly within the gauge length. Post failure examination suggests that $0^{\circ}$ fiber microbuckling is the critical damage mechanism that causes final failure. This is the matrix dominated failure mode and its triggering depends very much on initial fiber waviness. It is suggested that manufacturing process and quality may play a significant role in determining the compressive strength. When the anti-buckling device was used on specimens, it was showed that the compressive strength with the device was slightly greater than that without the device due to surface friction between the specimen and the device by pretoque in bolts of the device. In the analysis result on influence of the anti-buckling device using the finite element method, it was found that the compressive strength with the anti-buckling device by loaded bolts was about 7% higher than actual compressive strength. Additionally, compressive tests on specimen with an open hole were performed. The local stress concentration arising from the hole dominates the strength of the laminate rather than the stresses in the bulk of the material. It is observed that the remote failure stress decreases with increasing hole size and specimen width but is generally well above the value one might predict from the elastic stress concentration factor. This suggests that the material is not ideally brittle and some stress relief occurs around the hole. X-ray radiography reveals that damage in the form of fiber microbuckling and delamination initiates at the edge of the hole at approximately 80% of the failure load and extends stably under increasing load before becoming unstable at a critical length of 2-3mm (depends on specimen geometry). This damage growth and failure are analysed by a linear cohesive zone model. Using the independently measured laminate parameters of unnotched compressive strength and in-plane fracture toughness the model predicts successfully the notched strength as a function of hole size and width.

• The Journal of Korean Academy of Prosthodontics
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• v.47 no.2
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• pp.125-135
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• 2009

Statement of problem: Loosening or fracture of the abutment screw is one of the common problems related to the dental implant. Generally, in order to make the screw joint stable, the preload generated by tightening torque needs to be increased within the elastic limit of the screw. However, additional tensile forces can produce the plastic deformation of abutment screw when functional loads are superimposed on preload stresses, and they can elicit loosening or fracture of the abutment screw. Therefore, it is necessary to find the optimum tightening torque that maximizes a fatigue life and simultaneously offer a reasonable degree of protection against loosening. Purpose: The purpose of this study was to present the influence of tightening torque on the implant-abutment screw joint stability with the 3 dimensional finite element analysis. Material and methods: In this study, the finite element model of the implant system with external butt joint connection was designed and verified by comparison with additional theoretical and experimental results. Four different amount of tightening torques(10, 20, 30 and 40 Ncm) and the external loading(250 N, $30^{\circ}$) were applied to the model, and the equivalent stress distributions and the gap distances were calculated according to each tightening torque and the result was analyzed. Results: Within the limitation of this study, the following results were drawn; 1) There was the proportional relation between the tightening torque and the preload. 2) In case of applying only the tightening torque, the maximum stress was found at the screw neck. 3) The maximum stress was also shown at the screw neck under the external loading condition. However in case of applying 10 Ncm tightening torque, it was found at the undersurface of the screw head. 4) The joint opening was observed under the external loading in case of applying 10 Ncm and 20 Ncm of tightening torque. 5) When the tightening torque was applied at 40 Ncm, under the external loading the maximum stress exceeded the allowable stress value of the titanium alloy. Conclusion: Implant abutment screw must have a proper tightening torque that will be able to maintain joint stability of fixture and abutment.

• Progress in Medical Physics
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• v.14 no.1
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• pp.34-42
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• 2003

In medical imaging, three-dimensional (3D) display using Virtual Reality Modeling Language (VRML) as a portable file format can give intuitive information more efficiently on the World Wide Web (WWW). The web-based 3D visualization of functional images combined with anatomical images has not studied much in systematic ways. The goal of this study was to achieve a simultaneous observation of 3D anatomic and functional models with planar images on the WWW, providing their locational information in 3D space with a measuring implement using VRML. MRI and ictal-interictal SPECT images were obtained from one epileptic patient. Subtraction ictal SPECT co-registered to MRI (SISCOM) was performed to improve identification of a seizure focus. SISCOM image volumes were held by thresholds above one standard deviation (1-SD) and two standard deviations (2-SD). SISCOM foci and boundaries of gray matter, white matter, and cerebrospinal fluid (CSF) in the MRI volume were segmented and rendered to VRML polygonal surfaces by marching cube algorithm. Line profiles of x and y-axis that represent real lengths on an image were acquired and their maximum lengths were the same as 211.67 mm. The real size vs. the rendered VRML surface size was approximately the ratio of 1 to 605.9. A VRML measuring tool was made and merged with previous VRML surfaces. User interface tools were embedded with Java Script routines to display MRI planar images as cross sections of 3D surface models and to set transparencies of 3D surface models. When transparencies of 3D surface models were properly controlled, a fused display of the brain geometry with 3D distributions of focal activated regions provided intuitively spatial correlations among three 3D surface models. The epileptic seizure focus was in the right temporal lobe of the brain. The real position of the seizure focus could be verified by the VRML measuring tool and the anatomy corresponding to the seizure focus could be confirmed by MRI planar images crossing 3D surface models. The VRML application developed in this study may have several advantages. Firstly, 3D fused display and control of anatomic and functional image were achieved on the m. Secondly, the vector analysis of a 3D surface model was defined by the VRML measuring tool based on the real size. Finally, the anatomy corresponding to the seizure focus was intuitively detected by correlations with MRI images. Our web based visualization of 3-D fusion image and its localization will be a help to online research and education in diagnostic radiology, therapeutic radiology, and surgery applications.

• The korean journal of orthodontics
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• v.35 no.6 s.113
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• pp.475-484
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• 2005

This study was performed to investigate the reproducibility of the horizontal and midsagittal planes, and to suggest a stable coordinate system for three-dimensional (3D) cephalometric analysis. Eighteen CT scans were taken and the coordinate system was established using 7 reference points marked by a volume model, with no more than 4 points on the same plane. The 3D landmarks were selected on V works (Cybermed Inc., Seoul, Korea), then exported to V surgery (Cybermed Inc., Seoul, Korea) to calculate the coordinate values. All the landmarks were taken twice with a lapse of 2 weeks. The horizontal and midsagittal planes were constructed and its reproducibility was evaluated. There was no significant difference in the reproducibility of the horizontal reference planes, But, FH planes were more reproducible than other horizontal planes. FH planes showed no difference between the planes constructed with 3 out of 4 points. The angle of intersection made by 2 FH planes, composed of both Po and one Or showed less than $1^{\circ}$ difference. This was identical when 2 FH planes were composed of both Or and one Po. But, the latter cases showed a significantly smaller error. The reproducibility of the midsagittal plane was reliable with an error range of 0.61 to $1.93^{\circ}$ except for 5 establishments (FMS-Nc, Na-Rh, Na-ANS, Rh-ANS, and FR-PNS). The 3D coordinate system may be constructed with 3 planes; the horizontal plane constructed by both Po and right Or; the midsagittal plane perpendicular to the horizontal plane, including the midpoint of the Foramen Spinosum and Nc; and the coronal plane perpendicular to the horizontal and midsagittal planes, including point clinoidale, or sella, or PNS.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.59-77
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• 2012

This study focuses on predicting which firms will increase capital by issuing new stocks in the near future. Many stakeholders, including banks, credit rating agencies and investors, performs a variety of analyses for firms' growth, profitability, stability, activity, productivity, etc., and regularly report the firms' financial analysis indices. In the paper, we develop predictive models for rights issues using these financial analysis indices and data mining techniques. This study approaches to building the predictive models from the perspective of two different analyses. The first is the analysis period. We divide the analysis period into before and after the IMF financial crisis, and examine whether there is the difference between the two periods. The second is the prediction time. In order to predict when firms increase capital by issuing new stocks, the prediction time is categorized as one year, two years and three years later. Therefore Total six prediction models are developed and analyzed. In this paper, we employ the decision tree technique to build the prediction models for rights issues. The decision tree is the most widely used prediction method which builds decision trees to label or categorize cases into a set of known classes. In contrast to neural networks, logistic regression and SVM, decision tree techniques are well suited for high-dimensional applications and have strong explanation capabilities. There are well-known decision tree induction algorithms such as CHAID, CART, QUEST, C5.0, etc. Among them, we use C5.0 algorithm which is the most recently developed algorithm and yields performance better than other algorithms. We obtained data for the rights issue and financial analysis from TS2000 of Korea Listed Companies Association. A record of financial analysis data is consisted of 89 variables which include 9 growth indices, 30 profitability indices, 23 stability indices, 6 activity indices and 8 productivity indices. For the model building and test, we used 10,925 financial analysis data of total 658 listed firms. PASW Modeler 13 was used to build C5.0 decision trees for the six prediction models. Total 84 variables among financial analysis data are selected as the input variables of each model, and the rights issue status (issued or not issued) is defined as the output variable. To develop prediction models using C5.0 node (Node Options: Output type = Rule set, Use boosting = false, Cross-validate = false, Mode = Simple, Favor = Generality), we used 60% of data for model building and 40% of data for model test. The results of experimental analysis show that the prediction accuracies of data after the IMF financial crisis (59.04% to 60.43%) are about 10 percent higher than ones before IMF financial crisis (68.78% to 71.41%). These results indicate that since the IMF financial crisis, the reliability of financial analysis indices has increased and the firm intention of rights issue has been more obvious. The experiment results also show that the stability-related indices have a major impact on conducting rights issue in the case of short-term prediction. On the other hand, the long-term prediction of conducting rights issue is affected by financial analysis indices on profitability, stability, activity and productivity. All the prediction models include the industry code as one of significant variables. This means that companies in different types of industries show their different types of patterns for rights issue. We conclude that it is desirable for stakeholders to take into account stability-related indices and more various financial analysis indices for short-term prediction and long-term prediction, respectively. The current study has several limitations. First, we need to compare the differences in accuracy by using different data mining techniques such as neural networks, logistic regression and SVM. Second, we are required to develop and to evaluate new prediction models including variables which research in the theory of capital structure has mentioned about the relevance to rights issue.

• Journal of Global Scholars of Marketing Science
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• v.18 no.1
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• pp.1-31
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• 2008

Trust is central to human relationships, at all times and places. The importance of trust is fundamental in all areas of human life, not only in the area of business administration. 2,500 years ago in China, Confucius taught that the foundation of politics was the trust of the people, more important even than military strength or the supply of food. Shakespeare's play, "Much Ado about Nothing' is about trust and deception. These days, trust and transparency in a commercial organization's business culture form the basis of the 'social capital' by which that organization increases its productivity. A successful company raises productivity by the accumulation of social capital, derived from a trust relationship between business partners, and between the company and consumers. Trust is the crucial factor. At the national level, building trust determines a nation's competitiveness. For a company, long term trust relationships with customers are essential for its survival in a business environment of rapid change. Such relationships, based on trust, are important assets to ensure a company's competitive advantage, and need to be organic to that company's business culture. Because of this importance, trust relationships have been studied in diverse areas within business administration, and especially within marketing, where they form the basis of a successful relationship between producer and consumer. However, what has been lacking is a unified definition of trust. Research has been conducted on the basis of various definitions and models. The majority of researchers have not considered the multidimensional character of the concept of trust until now. Approaches based on a one dimensional model have undermined the value of research results. Furthermore, researchers have only considered trust and trustworthiness as a single component. The majority of research has explored the consequences of perceived trust for outcomes such as loyalty or cooperation, but has neglected the effects of trustworthiness upon the mechanisms of consumer trust. This study focuses on the dimension of trust from such a perspective. It seeks to verify the effect of trust on customer intentions by breaking it down into three separate components: 1) the salesperson, 2) the product/service, and 3) the company. The purposes of this paper are as follows: Firstly, we review the multidimensional nature of trust objects: the salesperson, the product/service, and the company. Secondly, we analyze the relationship between multidimensional trust and trustworthiness. Thirdly, we analyze the connection between trust and repeat purchase intentions for the maintenance of long term relationships. For these purposes the author has developed several hypotheses as follows: H1-1: The competence of a salesperson is positively associated with the trust given by the consumer to the salesperson. H1-2: The benevolence of a salesperson is positively associated with the trust given by the consumer to the salesperson. H2-1: The competence of product/service is positively associated with the trust given by the consumer to the product/service. H2-2: The benevolence of product/service is positively associated with the trust given by the consumer to the product/service. H3-1: The reputation of a company is positively associated with the trust given by the consumer to the company. H3-2: The physical environment of a company is positively associated with the trust given by the consumer to the company. H4-1: Trust in a salesperson is positively associated with repeat purchase intentions. H4-2: Trust in a product/service is positively associated with repeat purchase intentions. H4-3: Trust in a company is positively associated with repeat purchase intentions. The data was compiled from 366 questionnaires. 500 questionnaires were collected, but some of the data was considered unsuitable and inappropriate. The subjects of the survey were male and female customers purchasing products at department stores in Seoul, Daegu and Gyeongbuk. It was carried out between Oct. 25 and 29, 2007. The data was analyzed by frequency analysis using SPSS 12.0 and structural equation modeling using LISREL 8.7. The result of the overall model analysis is as follows: Chi-Square=445.497, d.f.=185, p-value=0.0, GFI=.901, RMSEA=.0617, NNFI=.986, NFI=.981, CFI=.989, AGFI=.864, RMR=.0872. The results of the overall model analysis were coherent. It was found that trust is a multi-dimensional construct, that each of the dimensions of trust are meaningful influences on customer's repurchase intention. Trust in a company may be the most relevant, while trust in a product/service and a salesperson may be less relevant to repurchase intentions. The effective factors in determining trust in a salesperson and a company's product/service were found to be competence and benevolence. Factors in determining trust in a company were its reputation and physical environment, and the relationship of each effective trust factor has been verified in this research. As a result, it was found that competence and benevolence have a meaningful influence on trust in a salesperson and in product/service. It was also found that a company's reputation influences the overall trust in the company significantly but a company's physical environment does not have much effect.

• Korean Journal of Psychosomatic Medicine
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• v.28 no.1
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• pp.20-28
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• 2020

Objectives : The aim of this study was to compare psychosocial characteristics of the functional gastrointestinal disorders FGID group, non-FGID group, and control group and determine factors affecting the QOL of patients with FGID. Methods : 135 patients diagnosed with FGID were selected. 79 adults had no observable symptoms of FGID (control group) and 88 adults showed symptoms of FGID (non-FGID group). Demographic factors were investigated. The Korean-Beck Depression Inventory-II, Korean-Beck Anxiety Inventory, Korean-Childhood Trauma Questionnaire, Multidimensional Scale of Perceived Social Support, Connor-Davidson Resilience Scale, Patient Health Questionnaire-15 and WHO Quality of Life Assessment Instrument Brief Form were used to assess psychosocial factors. A one-way ANOVA was used to compare differences among groups. Pearson correlation test was performed to analyze the correlation of psychosocial factors and QOL of the FGID group. Further, a hierarchical regression analysis was conducted to determine factors affecting the QOL of the FGID group. Results : Between-group differences were not significant in demographic characteristics. Depression (F=48.75, p<0.001), anxiety (F=14.48, p<0.001), somatization (F=24.42, p<0.001) and childhood trauma (F=12.71, p<0.001) were significantly higher in FGID group than in other groups. Social support (F=39.95, p<0.001) and resilience (F=17.51, p<0.001) were significantly lower in FGID group than in other groups. Resilience (β=0.373, p<0.01) was the most important explanatory variable. The explained variance was 47.2%. Conclusions : Significantly more symptoms of depression, anxiety, childhood trauma, and somatization were observed for the FGID group. This group also had less social support, resilience, and quality of life than the non-FGID and control groups. The key factor for quality of life of the FGID group was resilience.