• 한국정보시스템학회지:정보시스템연구
• /
• 제5권
• /
• pp.383-409
• /
• 1996

This study has two research objectives related to end-user computing (EUC). One of the research objectives was to investigate the current status of EUC of Korean firms. Another research objective was to examine the relationship between individual differences of end-users and EUC success. Using survey data from 752 end-users of 23 firms, the current status of EUC and the relationship between individual differences of end-users and EUC success were investigated. The current status of EUC was examined from six perspectives : 1) what is the characteristics of EUC strategy of Korean firms, 2) what are the individual characteristics of end-users in Korean firms 3) what are the characteristics of tasks performed by end-users computer, 4) what are the application areas of EUC, 5) How end-users are satisfied with the support of firm, 6) what are system usage and satisfaction of end-users. It was also found that individual differences of end-users are related to EUC success. More specifically, it was shown that the male gender, younger age, higher level of education, higher rank and organizational tenure, higher math ability, thinking type of cognitive style, positive and optimistic attitudes toward computer, more experience with computer, more computer education and knowledge are individual differences variables associated with EUC success. The results of stepwise regression analysis suggested that the individual difference variables accounted for 14%, 25%, 39%, and 30% of the variances of four EUC success variables, satisfaction for outcome, satisfaction for ability, frequency of computer use, and the number of tasks, respectively. Theses empirical findings suggest that EUC managers should consider individual differences of end-users in managing EUC, such as education, training support, and human resource management, to maximize potential benefits of EUC.

• 정보과학회 컴퓨팅의 실제 논문지
• /
• 제20권11호
• /
• pp.598-603
• /
• 2014

무선 센서 네트워크에서 객체의 위치 추적은 객체의 움직임 포착 및 동선 파악 등에 활용되는 중요한 어플리케이션이다. 따라서 객체의 정확한 동선을 파악하기 위해 추적의 정밀성이 중요하다. 하지만 기존의 연구들은 객체 추적을 위하여 사용자가 반복적으로 질의를 하기 때문에 에너지 효율성 및 정밀성이 떨어지게 된다. 따라서 본 논문에서는 객체 추적의 에너지 효율성 및 추적의 정밀성을 향상시키기 위하여, 각 노드들이 사용자의 질의를 객체의 예상 경로에 중계하는 방안을 제안한다. 이 방법은 객체 추적을 위하여 네트워크를 일정 크기로 클러스터링하고 각 클러스터 헤드를 트리로 구성한다. 객체를 감지한 클러스터 헤드는 트리를 통해 사용자에게 객체의 정보를 전달하고, 객체의 예상 경로에 위치한 클러스터 헤드에게 사용자의 질의를 중계해 줌으로써, 사용자의 반복적인 질의를 줄여준다. 시뮬레이션 결과, 제안방안이 기존의 객체 추적 연구에 비해 높은 에너지 효율과 추적 정밀성을 가지는 것을 보인다.

• 한국실내디자인학회논문집
• /
• 제21권2호
• /
• pp.186-196
• /
• 2012

Information technology has changed the human life as well as the societal and economic paradigm. New office environments have been proposed to cope with emerging changes and to support working performances by reducing costs of office operation and business. Recently, office environments have adopted ubiquitous computing with a focus on collaboration to promote real-time enterprises. They become equipped with various mobile devices and pervasive technologies in wireless networks. This study aims to propose a direction for the adoption of mobile and pervasive computing on the new office environment. We investigate relate works and analyze new office types including mobile offices, telework centers and home offices. Using a customized questionnaire, the current conditions of the office environments and officers' demands were investigated and analyzed. In the end, we propose the direction for a ubiquitous office environment with a focus on two attributes, ubiquity and mobility. This research will be a basis for the development of ubiquitous offices that support the professionalism of works in practices.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제5권10호
• /
• pp.1712-1732
• /
• 2011

Cloud provides dynamically scalable virtualized computing resources as a service over the Internet. To achieve higher resource utilization over virtualization technology, an optimized strategy that deploys virtual machines on physical machines is needed. That is, the total number of active physical host nodes should be dynamically changed to correspond to their resource usage rate, thereby maintaining optimum utilization of physical machines. In this paper, we propose a pattern-based prediction model for resource provisioning which facilitates best possible resource preparation by analyzing the resource utilization and deriving resource usage patterns. The focus of our work is on predicting future resource requests by optimized dynamic resource management strategy that is applied to a virtualized data center in a Cloud computing environment. To this end, we build a prediction model that is based on user request patterns and make a prediction of system behavior for the near future. As a result, this model can save time for predicting the needed resource amount and reduce the possibility of resource overuse. In addition, we studied the performance of our proposed model comparing with conventional resource provisioning models under various Cloud execution conditions. The experimental results showed that our pattern-based prediction model gives significant benefits over conventional models.

• 경영정보학연구
• /
• 제6권2호
• /
• pp.161-179
• /
• 2004

본 연구는 중소형 e-Learning시스템의 개발을 위한 실질적 경험을 제시하는 데 목적이 있다. 제안된 시스템은 교수자로 하여금 전문적인 컴퓨팅 관련 기술의 도움없이 인터페이스를 정의하고, 컨텐츠를 조직화하며, 문제의 출제 및 자동 채점이 가능하도록 설계되었다. 본 연구는 e-Learning의 도입을 어렵게 느끼거나, 학교당국의 정책적 결정에 의해서 수용하겠다는 교육현장의 교수자가 타인의 도움없이 본인 스스로 구현할 수 있는 방안을 제시한다. 또한, 교수-학습자 간의 상호작용이 가능하고 개인적으로 운영할 수 있는 저비용, 고효율의 e-Learning기반 사이트를 실질적으로 구현하고 운영할 수 있는 방안을 제안한다.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제16권8호
• /
• pp.2772-2786
• /
• 2022

We had researched an automatic authentication-supported medical information platform[6]. The proposed automatic authentication consists of user authentication and mobile terminal authentication, and the authentications are performed simultaneously in patients' emergency conditions. In this paper, we studied on finding emergency conditions for the automatic authentication by applying big data processing and AI mechanism on the extended medical information platform with an added edge computing system. We used big data processing, SVM, and 1-Dimension CNN of AI mechanism to find emergency conditions as authentication means considering patients' underlying diseases such as hypertension, diabetes mellitus, and arrhythmia. To quickly determine a patient's emergency conditions, we placed edge computing at the end of the platform. The medical information server derives patients' emergency conditions decision values using big data processing and AI mechanism and transmits the values to an edge node. If the edge node determines the patient emergency conditions, the edge node notifies the emergency conditions to the medical information server. The medical server transmits an emergency message to the patient's charge medical staff. The medical staff performs the automatic authentication using a mobile terminal. After the automatic authentication is completed, the medical staff can access the patient's upper medical information that was not seen in the normal condition.

• 한국정보시스템학회:학술대회논문집
• /
• 한국정보시스템학회 1996년도 추계학술발표회 발표논문집
• /
• pp.5-26
• /
• 1996

This study has two research objectives related to end-user computing (EUC). One of the research objectives was to investigate the current status of EUC of Korean firms. Another research objective was to examine the relationship between individual differences of end-users and EUC success. Using survey data from 752 end-users of 23 firms, the surrent status of EUC and the relationship between individual differences of end-users and EUC success were investigated. The current status of EUC was examined from six perspectives: 1). what is the characteristics of EUC strategy of Korean firms, 2). what are the individual characteristics of end-users in Korean Firms, #0. what are the characteristics of tasks performed by end-users using computer, 4). what are the application a areas of EUC, 5). How end-users are satisfied with the support of firms, 6). what are system usage and satisfaction of end-users. It was also foud that individual differences of end-users are related to EUC success. More specifically, it wat shown that the male gender, younger age, higher level of education, higher rank and organizational tenure, higher math ability, thinking type of cognitive style, positive and optimistic attitudes toward computer, more experience with computer, more computer education and knowledge are individual differences variables associated with EUC success. The results of stepwise regression analysis suggested that the individual difference variables accounted for 14%, 25%, 39% and 30% of the variances of four EUC success variables, satisfaction for outcome, satisfaction for ability, frequency of computer use, and the number of tasks, respectively. These empirical findings suggest that EUC managers should consider individual differences of end-users in managing EUC, such as education, training, support, and human resource management, to maximize potential benefits of EUC.

• 한국산업정보학회:학술대회논문집
• /
• 한국산업정보학회 1996년도 추계 학술 발표회 발표논문집
• /
• pp.5-26
• /
• 1996

This study has two research objectives related to end-user computing (EUC) . One of the research objectives was to investigate the current status of EUC of Korean firms. Another research objective was to examine the relationship between individual difference of end-users and EUC success. Using survey data from 752 end-users of 23 firms, the surrent status of EUC and the relationship between individualdifferences of end-users and EUC success were investigated. The current status of EUC was examined from six perspectives : 1) what is the characteristics of EC strategy of Korean firms , 2) what are the individual characteristics of end-users in Korean firms, 3) what are the characteristics of tasks performed by end-users using computer 4) what are the application a areas of EUC 5) How end-users are satisfied with the support of firms, 6) what are system usage and satisfaction of end-users. It was also found that individual differences of endf-users are related to EUC success.More specifically , it was shown that the male gender, younger age, higher level of education , higher ran아 and organizational tenure, higher math ability , thinking type of cognitive style, positive and optimistic attitudes toward computer, more experience with computer, more computer education and knowledge are individual differences variables associated with EUC success. The results of stepwise regression analysis suggested that the individuaal difference variables accounted for 14%, 25% 39% and 30% of the variances of four EUC success variables, satisfaction for outcome , satisfaction for ability , frequency of computer use, and thenuber of tasks, respectively. These empirical findings suggest that EUC managers should consider individual differences of end-users in managing EUC , such as education, training, support, and human resource management , to maximize potential benefits of EUC.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제11권5호
• /
• pp.2310-2345
• /
• 2017

With the emergence of the Internet of Things (IoT) the world is projecting towards a scenario where every object in the world (including humans) acts as a sender and receiver of data and if we were to see that concept mature we would soon be talking of billions more users of the cloud networks. The cloud technology is a very apt alternative to permanent storage when it comes to bulk storage and reporting. It has however shown weaknesses concerning real-time data accessibility and processing. The bandwidth availability of the cloud networks is limited and combined with the highly centralized storage structure and geographical vastness of the network in terms of distance from the end user the cloud just does not seem like a friendly environment for real-time IOT data. This paper aims at highlighting the importance of Flavio Bonomi's idea of Fog Computing which has been glamorized and marketed by Cisco but has not yet been given a proper service architecture that would explain how it would be used in terms of various service models i-e IaaS, PaaS and SaaS, of the Cloud. The main contribution of the paper would be models for IaaS, PaaS and SaaS for Fog environments. The paper would conclude by highlighting the importance of the presented models and giving a consolidated overview of how they would work. It would also calculate the respective latencies for fog and cloud to prove that our models would work. We have used CloudSim and iFogSim to show the effectiveness of the paradigm shift from traditional cloud architecture to our Fog architecture.

• International Journal of Computer Science & Network Security
• /
• 제21권1호
• /
• pp.137-142
• /
• 2021

The Internet of Things (IoT) paradigm is at the forefront of present and future research activities. The huge amount of sensing data from IoT devices needing to be processed is increasing dramatically in volume, variety, and velocity. In response, cloud computing was involved in handling the challenges of collecting, storing, and processing jobs. The fog computing technology is a model that is used to support cloud computing by implementing pre-processing jobs close to the end-user for realizing low latency, less power consumption in the cloud side, and high scalability. However, it may be that some resources in fog computing networks are not suitable for some kind of jobs, or the number of requests increases outside capacity. So, it is more efficient to decrease sending jobs to the cloud. Hence some other fog resources are idle, and it is better to be federated rather than forwarding them to the cloud server. Obviously, this issue affects the performance of the fog environment when dealing with big data applications or applications that are sensitive to time processing. This research aims to build a fog topology job scheduling (FTJS) to schedule the incoming jobs which are generated from the IoT devices and discover all available fog nodes with their capabilities. Also, the fog topology job placement algorithm is introduced to deploy jobs into appropriate resources in the network effectively. Finally, by comparing our result with the state-of-art first come first serve (FCFS) scheduling technique, the overall execution time is reduced significantly by approximately 20%, the energy consumption in the cloud side is reduced by 18%.