• 한국인터넷방송통신학회논문지
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• 제9권4호
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• pp.1-8
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• 2009

본 연구 이전에 제안되었던 실시간 교량 모니터링 시스템은 교량 곳곳에 배치되어 있는 센서들로부터 중앙서버로 동축 케이블을 통해 데이터를 송수신하였는데, 동축 케이블을 이용하여 교량 전체의 센서들의 네트워크를 구성하기 위해서는 막대한 인력과 비용이 따르게 된다. 본 연구에서는 USN을 기반으로 한 교량 모니터링 시스템 제안하고, 이에 대한 프로토타입을 설계 및 구현하였다. HSDPA를 통해 얻은 센싱 데이터 값을 TCP/IP 소켓을 통해 교량 모니터링 서버에 전달함으로써 양방향 통신을 구축하여 그래프 변환을 하는 전체 시스템을 구현하였다.

• 정보처리학회논문지C
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• 제9C권6호
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• pp.945-952
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• 2002

For a successful inter-system handoff, several important issues must be handled and additional new features must be considered. This paper focuses on the cellular structure of small cells which are required for the high density of population and a handoff scheme designed between two heterogenous networks. Incase of inter-system handoff (ISHO), the time required to complete the handoff can vary and depends on the structure of networks. And also the transmission of additional signals can increase the probability of failure for ISHO. Here we propose the sub-boundary cell base station (Sub-BBS) to alleviate the role of the BBS. The Sub-BBS is adjacent to BBS in the same regional mobile network. 쪼en the mobile terminal enters Sub-BBS, the network starts finding a new route and after entering BBS, it initiates the transformation process. The proposed scheme significantly reduces the ISHO failure rate compared to the existing one which is the most recent and known as efficient.

• 전기학회논문지
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• 제58권11호
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• pp.2107-2114
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• 2009

It is impossible to take the instant action in the distribution system When fault occures in a substation because operation of the substation and the distribution system are separated. However the power system automation has been studying about unity operation and co-operation between SCADA and DAS(Distribution Automation System). In this paper proposes a new algorithm of efficiency restoration using a outage load switching to a healthy MTR a fault occurrence at a MTR in united system between DAS and SCADA. In addtion, proposed algorithm includes a outage restoration method which keeps MTR optimal capacity with reorganization of distribution network in case it can not restore outage state loads caused by shortage of healthy MTR remain capacity. In case that proposed sequence still can not complete restoration, this paper suggests a efficiency outage restoration with objective function included priority in outage loads. In the case studies, the proposed algorithm have been verified in 2 MTR and 3 MTR substation

• 한국건축시공학회지
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• 제10권2호
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• pp.51-57
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• 2010

건설공사의 일정관리는 주어진 기간 내에 프로젝트를 완수하기 위한 중요한 수단이다. 액티비티의 수가 많아지고 복잡한 선후행 관계가 형성될수록 일정관리 소프트웨어를 활용해야 하는 필요성이 증대되고 있다. 또한 정보통신기술이 발달하면서 웹기반의 프로젝트관리 기술과 도구도 발전하고 있고 다수의 프로그램도 개발되어 있다. 본 연구는 웹 기반에서 일정관리 도구를 개발하기 위해 상호작용성이 우수한 플래시를 이용하는 방법을 제안하였다. 제안된 방법을 구현하기 위해 플래시와 액션스크립트로 프로토타입을 작성하였고 웹 화면에서 공정표를 표현하여 적용성을 검토하였다.

• International Journal of Computer Science & Network Security
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• 제21권12spc호
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• pp.549-555
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• 2021

Machine Learning(ML) splits data into 3 parts, which are usually 60% for training, 20% for validation, and 20% for testing. It just splits quantitatively instead of selecting each set of data by a criterion, which is very important concept for the adequacy of test data. ML measures a model's accuracy by applying a set of validation data, and revises the model until the validation accuracy reaches on a certain level. After the validation process, the complete model is tested with the set of test data, which are not seen by the model yet. If the set of test data covers the model's attributes well, the test accuracy will be close to the validation accuracy of the model. To make sure that ML's set of test data works adequately, we design an experiment and see if the test accuracy of model is always close to its validation adequacy as expected. The experiment builds 100 different SVM models for each of six data sets published in UCI ML repository. From the test accuracy and its validation accuracy of 600 cases, we find some unexpected cases, where the test accuracy is very different from its validation accuracy. Consequently, it is not always true that ML's set of test data is adequate to assure a model's quality.

• International Journal of Computer Science & Network Security
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• 제21권7호
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• pp.267-272
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• 2021

The current study aimed at measuring the rate of loss in search results of the actual number of publications in journals indexed by Web of Science when not using the accurate official authority name as indicated by the Ministry of Education. Conducting a search using the authority name does not always yield complete results of all existing publications. Researchers in Saudi universities tend to use up to 10 different random names of universities when searching. This interesting fact has prompted the authors of this paper to conduct a study on the search results of 30 Saudi universities using the authority name as indicated by the Ministry of Education. The statistical analyses revealed that there is a high tendency for the wrong use of authority names. Results show that 8 universities were not found in the search results. Furthermore, other universities are losing between 10 and 30% of search results that reflect the actual number of publications. Consequently, the rank of each university, as well as the general rank of Saudi universities in the Web of Science, will be affected.

• International Journal of Computer Science & Network Security
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• 제21권4호
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• pp.123-130
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• 2021

A novel approach for the detection of cheating during e-Exams is presented here using convolutional neural networks (CNN) based systems. This system will help the proctors to identify any kind of uncertain event at the time of online exams, for which most of the government's across the globe are recommending due to the Covid-19 pandemic. Most of the institutions and students across the globe are badly affected by their academic programs and it is a challenging task for universities to conduct examinations using the traditional methods. Therefore, the students are attending most of their classes using different types of third party applications that are available online. However, to conduct online exams the universities cannot rely on these service providers for a long time. Therefore, in this work, a complete setup of the software tools is provided for the students, which can be used by students at their respective laptops/personal computers with strict guidelines from the university. The proposed approach helps most of the universities in Saudi Arabia to maintain their database of different events/activities of students at the time of E-Exams. This method proved to be more accurate and CNN based detection proved to be more sensitive with an accuracy of 97% to detect any kind of uncertain activity of the students at the time of e-Exam.

• 유통과학연구
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• 제20권2호
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• pp.19-29
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• 2022

Purpose: Understanding the distribution channel is a foundational element of successful hotel revenue management. This study aims to assess hotel distribution network partnerships and develops a model that can be utilized to ensure hoteliers are not becoming increasingly reliant on a single channel, optimize their market exposure, and maximize their portion of the overall worth of the network. Research design, data and methodology: This study utilizes a grounded theory approach to form a theoretical model by analyzing and examining the current practice of hotel distribution management through interviews with 15 stakeholders in Indonesia, such as hoteliers, online travel agents, wholesalers, and connectivity managers. Results: Based on data analysis, we describe hotel distribution elements, revenue team, managed channels, and channel prioritization for a different type of hotel. Finally, we propose a distribution channel model that comprises hotel teams, customer types, indirect channels, and direct channels. Conclusions: The model contributes to the literature by exploring the options of distribution channels for various hotel types to support hotel revenue management practice. By utilizing our model, practitioners can have a complete picture regarding the strategic choice of the channel by considering their hotel capacity and market target.

• 동아시아경상학회지
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• 제11권1호
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• pp.41-51
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• 2023

Purpose - The prior literature has shown that there is a lack of a complete assessment of the key decisions in cold chain logistics. Such a study is required to offer recommendations for research in this expanding but under-researched topic with potentially significant management ramifications. Research design, Data, and methodology - The current researcher accumulated peer-reviewed sources from databases to augment each chosen study's validity. Selection varied between seminal works and much of the existing literature. The selection process was consistent with using a content checklist that established the inclusion and exclusion criteria. Result - The research findings indicate total five solutions regarding better decision in Cold Chain Logistics (CCL), such as (1) Pricing Decision in Cold Chain Logistics, (2) Decision on Temperature Control Decision in Cold Chain Logistics, (3) Supply Chain Network Design in Cold Chain Logistics, (4) Decision on Minimizing Inventory in Cold Chain Logistics, (5) Decision on Logistics Distribution. Conclusion - Stability of a cold chain should be maintained from manufacture or via logistical components and cold logistics products are susceptible to several variables, such as temperature, and degradation can easily harm food supply, product prices, and human health. Product safety infractions substantially impact human health, among other losses linked with a functioning CCL.

• 한국멀티미디어학회논문지
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• 제25권2호
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• pp.145-156
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• 2022

Nowadays, the complexity of object tracking models among hardware applications has become a more in-demand duty to complete in various indeterminable environment tracking situations with multifunctional algorithm skills. In this paper, we propose a virtual city environment using AirSim (Aerial Informatics and Robotics Simulation - AirSim, CityEnvironment) and use the DQN (Deep Q-Learning) model of deep reinforcement learning model in the virtual environment. The proposed object tracking DQN network observes the environment using a deep reinforcement learning model that receives continuous images taken by a virtual environment simulation system as input to control the operation of a virtual drone. The deep reinforcement learning model is pre-trained using various existing continuous image sets. Since the existing various continuous image sets are image data of real environments and objects, it is implemented in 3D to track virtual environments and moving objects in them.