• 예술인문사회 융합 멀티미디어 논문지
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• 제7권8호
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• pp.305-314
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• 2017

Clustering is a method that collects data objects into groups based on their similary. Performance of the state-of-the-art clustering methods is different according to the data characteristics. There have been numerous studies that performed experiments to compare the accuracy of the state-of-the-art clustering methods by applying various kinds of datasets. A common problem of these studies is that they only consider clustering algorithms that yield the most accurate results for a particular dataset. They do not consider what factors affect the execution time of each clustering method and how they are affected. Nevertheless, execution time is an important factor in clustering performance if there is no significant difference in accuracy. In order to solve the problems of the existing research, through a series of experiments using various types of datasets, we compare the accuracy of four representative clustering methods. In addition, we perform practical clustering performance comparisons by deriving time complexity and identifying factors that influences to its performance.

• International journal of advanced smart convergence
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• 제8권4호
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• pp.188-193
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• 2019

This paper is about environment-based low-code and no-code execution platform and execution method that combines hybrid and native apps. In detail, this paper describes the Low-Code/No-Code execution structure that combines the advantages of hybrid and native apps. It supports the iPhone and Android phones simultaneously, supports various templates, and avoids developer-oriented development methods based on the production process of coding-free apps and the produced apps play the role of Java virtual machine (VM). The Low-Code /No-Code (LCNC) development platform is a visual integrated development environment that allows non-technical developers to drag and drop application components to develop mobile or web applications. It provides the functions to manage dependencies that are packaged into small modules such as widgets and dynamically loads when needed, to apply model-view-controller (MVC) pattern, and to handle document object model (DOM). In the Low-Code/No-Code system, the widget calls the AppOS API provided by the UCMS platform to deliver the necessary requests to AppOS. The AppOS API provides authentication/authorization, online to offline (O2O), commerce, messaging, social publishing, and vision. It includes providing the functionality of vision.

• 보건교육건강증진학회지
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• 제23권3호
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• pp.85-97
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• 2006

Objectives: This study was done for the purpose of revitalization of the health improvement project by looking into major influence factors on the health examination of local residents in a city area. Methods: The research data was collected using a survey of the local residents in Wonju-City, Gangwondo. The survey was held between Oct. 4th to Oct. 15th, 2004. And, it was done as a household interview survey. The independent variables used were socio-demographic characteristics, health status, health concern, and health behaviors. The dependent variable was whether or not the respondent did take a cancer screening test. Results: In case of men, the execution rate of cancer screening was higher for those who had spouses, who were having no experience of a disease, who drank, and who did exercise. In the case of women, the execution rate of cancer screening was higher in the cases who had spouses, who had high income levels, and who were making an effort for their health. Conclusion: To raise the execution rate of health examination, more research on the major factor of cancer screening is necessary.

• 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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• 제16권6호
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• pp.722-726
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• 2010

최근 RIA(Rich Internet Application)의 등장으로 인해 자바스크립트 코드의 복잡도가 증가함에 따라 이를 위한 고성능 자바스크립트 엔진들이 경쟁적으로 발표되고 있다. 또한 이들 엔진의 성능 측정을 위한 도구로서 SunSpider 벤치마크가 널리 사용되고 있다. 본 논문에서는 대표적인 고성능 자바스크립트 엔진인 Mozilla의 Trace-Monkey, Google의 V8, 그리고 Apple의 SquirrelFish Extreme에 대해 자바스크립트 코드 수행 방식을 비교하고 SunSpider 벤치마크를 이용해 각 엔진의 성능을 측정한다. 또한 각 엔진들의 수행 방식과 SunSpider 각각의 코드 특성을 토대로 하여 성능 결과를 분석하여 각 엔진의 장단점을 평가한다.

• Journal of Information Processing Systems
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• 제17권4호
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• pp.721-736
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• 2021

For the mobile edge computing (MEC) system supporting dense network, a joint allocation algorithm of computing and communication resources based on reinforcement learning is proposed. The energy consumption of task execution is defined as the maximum energy consumption of each user's task execution in the system. Considering the constraints of task unloading, power allocation, transmission rate and calculation resource allocation, the problem of joint task unloading and resource allocation is modeled as a problem of maximum task execution energy consumption minimization. As a mixed integer nonlinear programming problem, it is difficult to be directly solve by traditional optimization methods. This paper uses reinforcement learning algorithm to solve this problem. Then, the Markov decision-making process and the theoretical basis of reinforcement learning are introduced to provide a theoretical basis for the algorithm simulation experiment. Based on the algorithm of reinforcement learning and joint allocation of communication resources, the joint optimization of data task unloading and power control strategy is carried out for each terminal device, and the local computing model and task unloading model are built. The simulation results show that the total task computation cost of the proposed algorithm is 5%-10% less than that of the two comparison algorithms under the same task input. At the same time, the total task computation cost of the proposed algorithm is more than 5% less than that of the two new comparison algorithms.

• International Journal of Computer Science & Network Security
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• 제23권11호
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• pp.190-194
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• 2023

By looking the importance of communication, data delivery and access in various sectors including governmental, business and individual for any kind of data, it becomes mandatory to identify faults and flaws during cyber communication. To protect personal, governmental and business data from being misused from numerous advanced attacks, there is the need of cyber security. The information security provides massive protection to both the host machine as well as network. The learning methods are used for analyzing as well as preventing various attacks. Machine learning is one of the branch of Artificial Intelligence that plays a potential learning techniques to detect the cyber-attacks. In the proposed methodology, the Decision Tree (DT) which is also a kind of supervised learning model, is combined with the different cross-validation method to determine the accuracy and the execution time to identify the cyber-attacks from a very recent dataset of different network attack activities of network traffic in the UNSW-NB15 dataset. It is a hybrid method in which different types of attributes including Gini Index and Entropy of DT model has been implemented separately to identify the most accurate procedure to detect intrusion with respect to the execution time. The different DT methodologies including DT using Gini Index, DT using train-split method and DT using information entropy along with their respective subdivision such as using K-Fold validation, using Stratified K-Fold validation are implemented.

• 한국치위생학회지
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• 제16권4호
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• pp.559-566
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• 2016

Objectives: This research has executed a new oral health promotion program among the elderly residents of a long-term care center, which purpose was to verify its effectiveness of oral health promotion through the improvement of their oral function. Methods: This study has selected the elderly over the age of 65, capable of communication, who use a long-term care center over the period of two months between July and September 2014. The subjects who remained until the final analysis numbered 50 excluding the dropouts during the program session (experimental: 33, control : 17). The oral stretching program was exercised two days a week, for total of two months. Each function was assessed by the standardized methods and measurement equipment. Also the sum of each function was converted into the oral health grade. Results: The oral function score of the experimental group also showed a statistically significant difference after the execution of the program, where the oral function score of experimental group increased $6.70{\pm}1.30$ from $4.95{\pm}0.89$ after the execution of the program (p<0.05), while the comparison group showed no valid statistical difference with the score result of $5.00{\pm}0.87$ down from $5.11{\pm}0.93$ after the execution of the program (p>0.05). Conclusions: Therefore if the oral health promotion program is reflected to the welfare policy in the future, it can be said that it contributes to the improved health status of the elderly who reside in the long-term care centers.

• Journal of Computing Science and Engineering
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• 제1권1호
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• pp.56-73
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• 2007

Demands have been growing in safety-critical application fields for producing networked real-time embedded computing (NREC) systems together with acceptable assurances of tight service time bounds (STBs). Here a service time can be defined as the amount of time that the NREC system could take in accepting a request, executing an appropriate service method, and returning a valid result. Enabling systematic composition of large-scale NREC systems with STB certifications has been recognized as a highly desirable goal by the research community for many years. An appealing approach for pursuing such a goal is to establish a hard-real-time (HRT) component model that contains its own STB as an integral part. The TMO (Time-Triggered Message-Triggered Object) programming scheme is one HRT distributed computing (DC) component model established by the first co-author and his collaborators over the past 15 years. The TMO programming scheme has been intended to be an advanced high-level RT DC programming scheme that enables development of NREC systems and validation of tight STBs of such systems with efforts far smaller than those required when any existing lower-level RT DC programming scheme is used. An additional goal is to enable maximum exploitation of concurrency without damaging any major structuring and execution approaches adopted for meeting the first two goals. A number of previously untried program structuring approaches and execution rules were adopted from the early development stage of the TMO scheme. This paper presents new concrete justifications for those approaches and rules, and also discusses new extensions of the TMO scheme intended to enable further exploitation of concurrency in NREC system design and programming.

• 정보처리학회논문지D
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• 제12D권2호
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• pp.283-288
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• 2005

테스트 케이스 우선 순위화는 회귀 테스팅이 시간 제약 하에서 주어진 모든 테스트 케이tm를 수행할 수 없을 때 테스트 케이스의 실행 순서를 스캐쥴링하는 것이다. 본 논문에서는 장기적인 회귀 테스팅 환경에서 과거의 테스트 실행 및 오류 검출 정보를 활용한 HED우선 순위화 방법을 제안하고, 이를 기존의 Random 및 LRU 방법과 비교하였다. 본 실험을 통해 몇 가지 중요한 통찰을 얻을 수 있었다. 첫째, 우선 순위화 방법들이 프로그램의 특성에 따라 성능 면에서 상호 보완적이라는 점이다. 오류를 찾는 테스트 케이스들을 많이 갖고 있는 프로그램의 경우에는 Random이 효과적이고, 상대적으로 오류를 찾는 테스트 케이스의 비율이 작은 경우에는 제안된 HED방법이 좋은 성능을 보였으며, 중간 정도인 경우에는 LRU 방법이 효과적이었다. 둘째, 전체적인 성능이 테스트 스위트의 크기에 영향을 많이 받는다는 점이다. 테스트 스위트의 크기를 달리하여 실험한 결과 오류의 수명 값과 그 성능 순위에 차이를 보였다. 마지막으로 전체 테스트 케이스의 $20\%$만을 실행하여도 전체 테스트 케이스 모두를 실행하는 것과 성능 면에서 유사한 결과를 얻을 수 있다는 점 등이다.

• 문화기술의 융합
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• 제6권4호
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• pp.693-701
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• 2020

본 논문에서는 현재 운영되는 수강신청 시스템에서의 데이터베이스 성능을 향상시키기 위하여 SQL문 분석을 하였다. 수강신청 업무와 관련된 트랜잭션들에서 사용 중인 SQL문장들을 실행계획을 통하여 현행 데이터베이스 성능을 측정하였으며, SQL 분석을 통하여 보완한 SQL문장들이 성능이 향상된 결과를 확인하였다. 전반적으로 실행계획 분석을 통하여 수강신청 데이터베이스 시스템의 성능을 향상시켰으며, 수강신청 SQL 의 일부 개선방법을 시험결과로 보였다. 개선된 방법은 데이터베이스 튜닝 작업을 통하여 수강신청과 관련된 테이블들과 인덱스 테이블들을 재조정하고, SQL의 기능을 활용함으로서 성능이 향상된 수강신청 데이터베이스 시스템으로 진화한 최적화된 시스템을 구현할 수 있게 되었다. 제안된 방법으로 재조정된 수강신청 시스템은 이전에 운영하던 수강신청시스템에 비하여 성능적 측면에서 우수한 결과를 나타내었으며, 통합 성능 시험 결과 1.8배 ~ 18배의 응답시간 단축을 가져왔다.