• 전기전자학회논문지
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• 제27권4호
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• pp.644-649
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• 2023

DRAM(Dynamic Random Access Memory) 스케일링 과정에서 발생하는 셀간 거리의 감소에 따라 STI(Shallow Trench Isolation)두께 감소는 문턱이하 누설이 증가되는 패싱워드라인 효과를 유발한다. 인접한 패싱워드라인에 인가된 전압으로 인한 문턱이하누설 전류의 증가는 데이터 보존시간에 영향을 주며, 리프레시의 동작 횟수가 증가되어 DRAM의 소비 전력을 증가시키는 요인이 된다. 본 논문에서는 TCAD Simulation을 통해 패싱워드라인 효과에 대한 원인을 확인한다. 결과적으로, 패싱워드라인 효과가 발생하는 DRAM 동작상황을 확인하고, 이때 패싱워드라인 효과로 인해 전체 누설전류의 원인에 따른 비중이 달라지는 것을 확인하였다. 이를 통해, GIDL(Gate Induced Drain Leakage)에 의한 누설전류뿐만 아니라 문턱이하 누설전류를 고려의 필요성을 확인하며 이에 따른 DRAM 구조의 개선 방향의 지침이 될 수 있다.

• Asia pacific journal of information systems
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• 제18권3호
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• pp.91-121
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• 2008

Electronic commerce, commonly known as e-commerce or eCommerce, has become a major business trend in these days. The amount of trade conducted electronically has grown extraordinarily by developing the Internet technology. Most electronic commerce has being conducted between businesses to customers; therefore, the researches with respect to e-commerce are to find customer's needs, behaviors through statistical methods. However, the statistical researches, mostly based on a questionnaire, are the static researches, They can tell us the dynamic relationships between initial purchasing and repurchasing. Therefore, this study proposes dynamic research model for analyzing the cause of initial purchasing and repurchasing. This paper is based on the System-Dynamic theory, using the powerful simulation model with some restriction, The restrictions are based on the theory TAM(Technology Acceptance Model), PAM, and TPB(Theory of Planned Behavior). This article investigates not only the customer's purchasing and repurchasing behavior by passing of time but also the interactive effects to one another. This research model has six scenarios and three steps for analyzing customer behaviors. The first step is the research of purchasing situations. The second step is the research of repurchasing situations. Finally, the third step is to study the relationship between initial purchasing and repurchasing. The purpose of six scenarios is to find the customer's purchasing patterns according to the environmental changes. We set six variables in these scenarios by (1) changing the number of products; (2) changing the number of contents in on-line shopping malls; (3) having multimedia files or not in the shopping mall web sites; (4) grading on-line communities; (5) changing the qualities of products; (6) changing the customer's degree of confidence on products. First three variables are applied to study customer's purchasing behavior, and the other variables are applied to repurchasing behavior study. Through the simulation study, this paper presents some inter-relational result about customer purchasing behaviors, For example, Active community actions are not the increasing factor of purchasing but the increasing factor of word of mouth effect, Additionally. The higher products' quality, the more word of mouth effects increase. The number of products and contents on the web sites have same influence on people's buying behaviors. All simulation methods in this paper is not only display the result of each scenario but also find how to affect each other. Hence, electronic commerce firm can make more realistic marketing strategy about consumer behavior through this dynamic simulation research. Moreover, dynamic analysis method can predict the results which help the decision of marketing strategy by using the time-line graph. Consequently, this dynamic simulation analysis could be a useful research model to make firm's competitive advantage. However, this simulation model needs more further study. With respect to reality, this simulation model has some limitations. There are some missing factors which affect customer's buying behaviors in this model. The first missing factor is the customer's degree of recognition of brands. The second factor is the degree of customer satisfaction. The third factor is the power of word of mouth in the specific region. Generally, word of mouth affects significantly on a region's culture, even people's buying behaviors. The last missing factor is the user interface environment in the internet or other on-line shopping tools. In order to get more realistic result, these factors might be essential matters to make better research in the future studies.