• 한국직업건강간호학회지
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• 제6권1호
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• pp.23-43
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• 1997

The work-related diseases due to continuous overwork are mainly cerebro- and cardio-vascular ones, which is commonly called 'Karoshi', death from overwork. Many factors are capable for Karoshi : occupational stress in relation to technological renovation and industrial rationalization, competitive social structure, and accumulated fatigue accured to long time or irregular working. And its occurence is on the rise. The World Labor Report 1993 released by ILO, pointed out the diseases related to overwork and stress as one of the most important occupational health problem. In Korea, social awareness of Karoshi is at an infant stage, and reliable statistics for its occurence are not compiled in a convenient manner. Despite the rising Karoshi, there are no reliable clauses in workmen's compensation enough to settle down the disputes. Therefore, it is not uncommon that the Labour Ministry and Civil Court find difficulties in reaching an agreement. This study was intended to provide proper compensation and prevention program for workers by suggesting reasonable compensation clauses for the death from overwork. This study consists of two comparative reviews on the compensaton clauses for the death from overwork. One is to review legal standards of Karoshi among three countries, such as Korea, Japan and Taiwan. The other is to investigate the cases of Karoshi in Korea, 121 cases identified at the Labor Welfare Corperation and the Labour Ministrial process of examination and reexamination, and 73 leading cases at the High Court of Justice. The main findings of the study are as follows : 1. Comparisons of comperative review on compensation clauses for the death from overwork among three countries. 1) All of three countries have the same kinds of disease for compensation, which were cerebro-and cardiao-vascular diseases, while for cardiac disease group, Korea has the smaller number of diseases for compensation than Japan. 2) As for the definition of overwork, the three countries share equally that overload for one week prior to collapse is considered as an important factor, but accumulated chronic fatigue is disregarded. 3) As the basis of overwork, in Japan, there is a tendency to move from the conditions of an ordinary healthy adult to those of the individual concerned in Japan, whereas there is no such concern yet in Korea. 4) All the three countries use a common standard of medical judgement in demonstrating causal relationship between a job and a disease. However, Korea is progressive in the sense that in the case of CVA at worksite, the worker himself has no obligation to prove the cause. 2. The results of a comparative review on excutive decisions by Labor Ministry and judicial decisions by the Court in Korea : A judicial decision is based on the legalistic probability, but a excutive decision is not. Therefore, excutive decisions have such restrictions that : 1) TIA (transitory ischemic cerebral attack) and myocarditis are excluded from compensation, and there is little consistency of decision in the case of cause-unknown death. 2) There is a tendency not to compensate for the death from overwork since the work terms such as repeated long-time working, shift work or night-shift work are not considered as overloading. 3) There is a tendency to regard the conditions of a ordinary healthy adult rather than those of the individual concerned(age, existing diseases, health state, etc.) as the comparative basis of overload. 4) There remains a tendency not to compensate for the death from overwork in the case of collapse occuring out of workplace, on the ground of 'on the course of working' and 'in the cause of accident'. Through the study, the fact manifests itself that Korea's compensation clauses for work-related diseases due to overwork are very restrictive. So, it is necessary to extend the Labor Ministry's clauses of compensation for the death from overwork following to the recent changes of other countries and internal judicial decisions. This is very important in the perspective of occupational health that aims at health promotion of workers including prevention of the Karoshi.

• Asia pacific journal of information systems
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• 제18권3호
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• pp.123-145
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• 2008

Recently, as the information communication technology develops, the discussion regarding the ubiquitous environment is occurring in diverse perspectives. Ubiquitous environment is an environment that could transfer data through networks regardless of the physical space, virtual space, time or location. In order to realize the ubiquitous environment, the Pervasive Sensing technology that enables the recognition of users' data without the border between physical and virtual space is required. In addition, the latest and diversified technologies such as Context-Awareness technology are necessary to construct the context around the user by sharing the data accessed through the Pervasive Sensing technology and linkage technology that is to prevent information loss through the wired, wireless networking and database. Especially, Pervasive Sensing technology is taken as an essential technology that enables user oriented services by recognizing the needs of the users even before the users inquire. There are lots of characteristics of ubiquitous environment through the technologies mentioned above such as ubiquity, abundance of data, mutuality, high information density, individualization and customization. Among them, information density directs the accessible amount and quality of the information and it is stored in bulk with ensured quality through Pervasive Sensing technology. Using this, in the companies, the personalized contents(or information) providing became possible for a target customer. Most of all, there are an increasing number of researches with respect to recommender systems that provide what customers need even when the customers do not explicitly ask something for their needs. Recommender systems are well renowned for its affirmative effect that enlarges the selling opportunities and reduces the searching cost of customers since it finds and provides information according to the customers' traits and preference in advance, in a commerce environment. Recommender systems have proved its usability through several methodologies and experiments conducted upon many different fields from the mid-1990s. Most of the researches related with the recommender systems until now take the products or information of internet or mobile context as its object, but there is not enough research concerned with recommending adequate store to customers in a ubiquitous environment. It is possible to track customers' behaviors in a ubiquitous environment, the same way it is implemented in an online market space even when customers are purchasing in an offline marketplace. Unlike existing internet space, in ubiquitous environment, the interest toward the stores is increasing that provides information according to the traffic line of the customers. In other words, the same product can be purchased in several different stores and the preferred store can be different from the customers by personal preference such as traffic line between stores, location, atmosphere, quality, and price. Krulwich(1997) has developed Lifestyle Finder which recommends a product and a store by using the demographical information and purchasing information generated in the internet commerce. Also, Fano(1998) has created a Shopper's Eye which is an information proving system. The information regarding the closest store from the customers' present location is shown when the customer has sent a to-buy list, Sadeh(2003) developed MyCampus that recommends appropriate information and a store in accordance with the schedule saved in a customers' mobile. Moreover, Keegan and O'Hare(2004) came up with EasiShop that provides the suitable tore information including price, after service, and accessibility after analyzing the to-buy list and the current location of customers. However, Krulwich(1997) does not indicate the characteristics of physical space based on the online commerce context and Keegan and O'Hare(2004) only provides information about store related to a product, while Fano(1998) does not fully consider the relationship between the preference toward the stores and the store itself. The most recent research by Sedah(2003), experimented on campus by suggesting recommender systems that reflect situation and preference information besides the characteristics of the physical space. Yet, there is a potential problem since the researches are based on location and preference information of customers which is connected to the invasion of privacy. The primary beginning point of controversy is an invasion of privacy and individual information in a ubiquitous environment according to researches conducted by Al-Muhtadi(2002), Beresford and Stajano(2003), and Ren(2006). Additionally, individuals want to be left anonymous to protect their own personal information, mentioned in Srivastava(2000). Therefore, in this paper, we suggest a methodology to recommend stores in U-market on the basis of ubiquitous environment not using personal information in order to protect individual information and privacy. The main idea behind our suggested methodology is based on Feature Matrices model (FM model, Shahabi and Banaei-Kashani, 2003) that uses clusters of customers' similar transaction data, which is similar to the Collaborative Filtering. However unlike Collaborative Filtering, this methodology overcomes the problems of personal information and privacy since it is not aware of the customer, exactly who they are, The methodology is compared with single trait model(vector model) such as visitor logs, while looking at the actual improvements of the recommendation when the context information is used. It is not easy to find real U-market data, so we experimented with factual data from a real department store with context information. The recommendation procedure of U-market proposed in this paper is divided into four major phases. First phase is collecting and preprocessing data for analysis of shopping patterns of customers. The traits of shopping patterns are expressed as feature matrices of N dimension. On second phase, the similar shopping patterns are grouped into clusters and the representative pattern of each cluster is derived. The distance between shopping patterns is calculated by Projected Pure Euclidean Distance (Shahabi and Banaei-Kashani, 2003). Third phase finds a representative pattern that is similar to a target customer, and at the same time, the shopping information of the customer is traced and saved dynamically. Fourth, the next store is recommended based on the physical distance between stores of representative patterns and the present location of target customer. In this research, we have evaluated the accuracy of recommendation method based on a factual data derived from a department store. There are technological difficulties of tracking on a real-time basis so we extracted purchasing related information and we added on context information on each transaction. As a result, recommendation based on FM model that applies purchasing and context information is more stable and accurate compared to that of vector model. Additionally, we could find more precise recommendation result as more shopping information is accumulated. Realistically, because of the limitation of ubiquitous environment realization, we were not able to reflect on all different kinds of context but more explicit analysis is expected to be attainable in the future after practical system is embodied.