• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권8호
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• pp.2253-2280
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• 2024

In the upcoming era of transportation, a groundbreaking technology, known as vehicle-to-everything (V2X) communication, is poised to redefine our driving experience and revolutionize traffic management. Real-time and secure communication plays a pivotal role in V2X networks, with the decision-making process being a key factor in establishing communication and determining malicious nodes. The proposed framework utilizes a directed acyclic graph (DAG) to facilitate real-time processing and expedite decision-making. This innovative approach ensures seamless connectivity among vehicles, the surrounding infrastructure, and various entities. To enhance communication efficiency, the entire roadside unit (RSU) region can be subdivided into various sub-regions, allowing RSUs to monitor and govern each sub-region. This strategic approach significantly reduces transaction approval time, thereby improving real-time communication. The framework incorporates a consensus mechanism to ensure robust security, even in the presence of malicious nodes. Recognizing the dynamic nature of V2X networks, the addition and removal of nodes are aligned. Communication latency is minimized through the deployment of computational resources near the data source and leveraging edge computing. This feature provides invaluable recommendations during critical situations that demand swift decision-making. The proposed architecture is further validated using the "veins" simulation tool. Simulation results demonstrate a remarkable success rate exceeding 95%, coupled with a significantly reduced consensus time compared to prevailing methodologies. This comprehensive approach not only addresses the evolving requirements of secure V2X communication but also substantiates practical success through simulation, laying the foundation for a transformative era in transportation.

• Journal of Information Processing Systems
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• 제12권1호
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• pp.1-34
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• 2016

Gene identification is at the center of genomic studies. Although the first phase of the Encyclopedia of DNA Elements (ENCODE) project has been claimed to be complete, the annotation of the functional elements is far from being so. Computational methods in gene identification continue to play important roles in this area and other relevant issues. So far, a lot of work has been performed on this area, and a plethora of computational methods and avenues have been developed. Many review papers have summarized these methods and other related work. However, most of them focus on the methodologies from a particular aspect or perspective. Different from these existing bodies of research, this paper aims to comprehensively summarize the mainstream computational methods in gene identification and tries to provide a short but concise technical reference for future studies. Moreover, this review sheds light on the emerging trends and cutting-edge techniques that are believed to be capable of leading the research on this field in the future.

• Structural Engineering and Mechanics
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• 제63권6호
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• pp.825-835
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• 2017

Significant improvements to methodologies on structural damage detection (SDD) have emerged in recent years. However, many methods are related to inversion computation which is prone to be ill-posed or ill-conditioning, leading to low-computing efficiency or inaccurate results. To explore a more accurate solution with satisfactory efficiency, a PSO-INM algorithm, combining particle swarm optimization (PSO) algorithm and an improved Nelder-Mead method (INM), is proposed to solve multi-sample objective function defined based on Bayesian inference in this study. The PSO-based algorithm, as a heuristic algorithm, is reliable to explore solution to SDD problem converted into a constrained optimization problem in mathematics. And the multi-sample objective function provides a stable pattern under different level of noise. Advantages of multi-sample objective function and its superior over traditional objective function are studied. Numerical simulation results of a two-storey frame structure show that the proposed method is sensitive to multi-damage cases. For further confirming accuracy of the proposed method, the ASCE 4-storey benchmark frame structure subjected to single and multiple damage cases is employed. Different kinds of modal identification methods are utilized to extract structural modal data from noise-contaminating acceleration responses. The illustrated results show that the proposed method is efficient to exact locations and extents of induced damages in structures.

• Journal of Preventive Medicine and Public Health
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• 제49권2호
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• pp.129-133
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• 2016

Objectives: The systematic review (SR) is a research methodology that aims to synthesize related evidence. Updating previously conducted SRs is necessary when new evidence has been produced, but no consensus has yet emerged on the appropriate update methodology. The authors have developed a new SR update method called 'adaptive meta-analysis' (AMA) using the 'cited by', 'similar articles', and 'related articles' citation discovery tools in the PubMed and Scopus databases. This study evaluates the usefulness of these citation discovery tools for updating SRs. Methods: Lists were constructed by applying the citation discovery tools in the two databases to the articles analyzed by a published SR. The degree of overlap between the lists and distribution of excluded results were evaluated. Results: The articles ultimately selected for the SR update meta-analysis were found in the lists obtained from the 'cited by' and 'similar' tools in PubMed. Most of the selected articles appeared in both the 'cited by' lists in Scopus and PubMed. The Scopus 'related' tool did not identify the appropriate articles. Conclusions: The AMA, which involves using both citation discovery tools in PubMed, and optionally, the 'related' tool in Scopus, was found to be useful for updating an SR.

• 정보과학회 컴퓨팅의 실제 논문지
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• 제23권7호
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• pp.424-427
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• 2017

애자일 개발 방법론이 확산되면서 초기에 불가능하다고 여겨진 대규모 IT 프로젝트에도 애자일 개발 방법론을 도입하고자 하는 노력이 있으며 이에 대한 사례도 다수 소개되고 있다. 본 논문에서는 2개의 대표적인 엔터프라이즈 애자일 방법론을 비교하고, 엔터프라이즈 애자일 개발 방법론의 하나인 학습 기반 애자일 프레임워크(DAD, Disciplined Agile Delivery)를 적용한 사례를 소개한다. 유사한 개발 과제를 수행한 2개의 프로젝트 간의 비교를 통해 폭포수 방법론을 사용한 프로젝트와 학습기반 애자일 프레임워크를 사용한 프로젝트의 개발 생산성을 정량적으로 측정하여 비교하였다.

• 정보과학회 컴퓨팅의 실제 논문지
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• 제20권12호
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• pp.706-710
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• 2014

사물인터넷(IoT)은 사람과 사물이 상호 연결되어 서비스를 제공하고 사용이 가능하다. DLNA는 오디오/비디오 등의 미디어 콘텐츠의 상호운용성을 지원하는 표준으로 사물과 연동할 필요가 있다. 본 논문은 서비스 지향 아키텍처 기반의 상호운용성을 제공하는 사물인터넷의 웹서비스 프레임워크에 다양한 기기의 미디어 콘텐츠를 양방향으로 연동하기 위한 양방향 DLNA 어댑터를 제안한다. DLNA 어댑터는 DLNA 기기의 서비스를 가상의 웹서비스로 변환하고 외부의 가상의 웹서비스를 DLNA 서비스로 변환하여 양방향성을 지원한다.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2007년도 춘계종합학술대회
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• pp.231-234
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• 2007

본 연구는 섬진강 하구역의 효율적이고 체계적인 해역환경관리를 위하여 해양관측데이터 및 수치모델링 자료 그리고 MGIS를 이용한 해역환경 DB 구축, 가시화, 체계화 및 SVG 언어를 이용한 MGIS기반 Web GUI 시스템을 구축하였다. 그 결과 섬진강 하구역의 물리해양학적 특성을 체계적으로 구현하여 파악할 수 있음을 확인하였다.

• Journal of Information Processing Systems
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• 제7권2호
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• pp.287-298
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• 2011

Efficient service description and modeling methodologies are essential for dynamic service composition to provide autonomous services for users in ubiquitous computing environments. In our previous research, we proposed a 'u-service' ontology which is an abstract and structured concept for device operations in ubiquitous environments. One of the problems that we faced during the design process was that there are not enough standards to analyze the effectiveness of a u-service ontology. In this paper, we propose a quality evaluation model to facilitate the design process of a uservice ontology. We extract modeling goals and evaluation indicators based on the uservice description specification. We also present quality metrics to quantify each of the design properties. The experiment result of the proposed quality model shows that we can use it to analyze the design of u-service ontology from various angles. Also, it shows that the model can provide a guideline, and offer appropriate recommendations for improvements.

• ETRI Journal
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• 제39권3호
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• pp.406-416
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• 2017

Malware propagated via the World Wide Web is one of the most dangerous tools in the realm of cyber-attacks. Its methodologies are effective, relatively easy to use, and are developing constantly in an unexpected manner. As a result, rapidly detecting malware propagation websites from a myriad of webpages is a difficult task. In this paper, we present LoGos, an automated high-interaction dynamic analyzer optimized for a browser-based Windows virtual machine environment. LoGos utilizes Internet Explorer injection and API hooks, and scrutinizes malicious behaviors such as new network connections, unused open ports, registry modifications, and file creation. Based on the obtained results, LoGos can determine the maliciousness level. This model forms a very lightweight system. Thus, it is approximately 10 to 18 times faster than systems proposed in previous work. In addition, it provides high detection rates that are equal to those of state-of-the-art tools. LoGos is a closed tool that can detect an extensive array of malicious webpages. We prove the efficiency and effectiveness of the tool by analyzing almost 0.36 M domains and 3.2 M webpages on a daily basis.

• 수산해양교육연구
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• 제28권1호
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• pp.172-179
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• 2016

The study of Mobile MGIS (Marine Geographic Information System) based on the Android Mobile Platform is mainly performed on effective methodologies which transform real world data to computing world data. Mobile GUI system has its own target on reliable data service by acquisition of geometric information using EFDC (Environmental Fluid Dynamics Code) Model, accurate measurement and graphical visualization. Even simple visualizations can aid in the interpretation of complex hydrodynamic relationships that are frequently encountered in the marine environment. The Mobile MGIS provides an easy way for hydrodynamics geoscientists to construct complex visualizations that can be viewed with free software. This study proposes a Mobile GUI MGIS using EFDC Model result of Seomjin River estuary. Finally, we design a Seomjin River estuarine Coastal Waters Mobile MGIS integrating above data models. It must adds more ecological information and the various service item for approach more easily in order to user.