• 방송공학회논문지
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• 제16권5호
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• pp.797-800
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• 2011

MPEG에서 진행 중인 MPEG Media Transport(MMT) 표준화는 IP기반 방송통신융합망에서 효과적인 멀티미디어 전송을 목적으로 하고 있다. 본 고에서는 MMT 제안 기술로서, 유선망에 비해 채널의 변화가 많은 무선망에서 효과적인 멀티미디어 전송을 위해 제안된 크로스레이어 디자인(Cross Layer Design-CLD)에서의 신호세기(signal strength information) 활용 방법을 소개한다. 무선환경에서 신호세기를 활용하면 매우 효율적인 멀티미디어 전송이 가능함은 관련 연구 논문[1]-[5]을 통해 증명되었다. 하지만, 무선채널의 특성상 서로 다른 신호세기의 범위를 사용함으로써 신호세기 정보의 유용성에도 불구하고 레이트 어댑테이션 애플리케이션에서 활용하는데 제한이 있어왔다. 따라서 본 논문에서는 MMT 표준화 기술 기고로 제안된 무선채널 신호세기 정보의 범위를 표준화된 형식으로 활용하는 방법에 대하여 기술한다.

• International Journal of Computer Science & Network Security
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• 제23권7호
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• pp.155-164
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• 2023

Machine learning with its high precision algorithms, Precision agriculture (PA) is a new emerging concept nowadays. Many researchers have worked on the quality and quantity of PA by using sensors, networking, machine learning (ML) techniques, and big data. However, there has been no attempt to work on trends of artificial intelligence (AI) techniques, dataset and crop type on precision agriculture using internet of things (IoT). This research aims to systematically analyze the domains of AI techniques and datasets that have been used in IoT based prediction in the area of PA. A systematic literature review is performed on AI based techniques and datasets for crop management, weather, irrigation, plant, soil and pest prediction. We took the papers on precision agriculture published in the last six years (2013-2019). We considered 42 primary studies related to the research objectives. After critical analysis of the studies, we found that crop management; soil and temperature areas of PA have been commonly used with the help of IoT devices and AI techniques. Moreover, different artificial intelligence techniques like ANN, CNN, SVM, Decision Tree, RF, etc. have been utilized in different fields of Precision agriculture. Image processing with supervised and unsupervised learning practice for prediction and monitoring the PA are also used. In addition, most of the studies are forfaiting sensory dataset to measure different properties of soil, weather, irrigation and crop. To this end, at the end, we provide future directions for researchers and guidelines for practitioners based on the findings of this review.

• Asian review of World Histories
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• 제4권1호
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• pp.3-34
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• 2016

This introduction is both a statement of a research problem and an account of the first research results for its solution. As more historical databases come online and overlap in coverage, we need to discuss the two main issues that prevent 'big' results from emerging so far. Firstly, historical data are seen by computer science people as unstructured, that is, historical records cannot be easily decomposed into unambiguous fields, like in population (birth and death records) and taxation data. Secondly, machine-learning tools developed for structured data cannot be applied as they are for historical research. We propose a complex network, narrative-driven approach to mining historical databases. In such a time-integrated network obtained by overlaying records from historical databases, the nodes are actors, while thelinks are actions. In the case study that we present (the world as seen from Venice, 1205-1533), the actors are governments, while the actions are limited to war, trade, and treaty to keep the case study tractable. We then identify key periods, key events, and hence key actors, key locations through a time-resolved examination of the actions. This tool allows historians to deal with historical data issues (e.g., source provenance identification, event validation, trade-conflict-diplomacy relationships, etc.). On a higher level, this automatic extraction of key narratives from a historical database allows historians to formulate hypotheses on the courses of history, and also allow them to test these hypotheses in other actions or in additional data sets. Our vision is that this narrative-driven analysis of historical data can lead to the development of multiple scale agent-based models, which can be simulated on a computer to generate ensembles of counterfactual histories that would deepen our understanding of how our actual history developed the way it did. The generation of such narratives, automatically and in a scalable way, will revolutionize the practice of history as a discipline, because historical knowledge, that is the treasure of human experiences (i.e. the heritage of the world), will become what might be inherited by machine learning algorithms and used in smart cities to highlight and explain present ties and illustrate potential future scenarios and visionarios.

• International Journal of Computer Science & Network Security
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• 제22권12호
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• pp.185-196
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• 2022

The Internet of Things (IoT) has become more and more widespread in recent years, thus attackers are placing greater emphasis on IoT environments. The IoT connects a large number of smart devices via wired and wireless networks that incorporate sensors or actuators in order to produce and share meaningful information. Attackers employed IoT devices as bots to assault the target server; however, because of their resource limitations, these devices are easily infected with IoT malware. The Distributed Denial of Service (DDoS) is one of the many security problems that might arise in an IoT context. DDOS attempt involves flooding a target server with irrelevant requests in an effort to disrupt it fully or partially. This worst practice blocks the legitimate user requests from being processed. We explored an intelligent intrusion detection system (IIDS) using a particular sort of machine learning, such as Artificial Neural Networks, (ANN) in order to handle and mitigate this type of cyber-attacks. In this research paper Feed-Forward Neural Network (FNN) is tested for detecting the DDOS attacks using a modified version of the KDD Cup 99 dataset. The aim of this paper is to determine the performance of the most effective and efficient Back-propagation algorithms among several algorithms and check the potential capability of ANN- based network model as a classifier to counteract the cyber-attacks in IoT environments. We have found that except Gradient Descent with Momentum Algorithm, the success rate obtained by the other three optimized and effective Back- Propagation algorithms is above 99.00%. The experimental findings showed that the accuracy rate of the proposed method using ANN is satisfactory.

• 국제학술발표논문집
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• The 9th International Conference on Construction Engineering and Project Management
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• pp.516-524
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• 2022

The construction industry is considered the most hazardous industry globally. Therefore, safety education is crucial for raising the safety awareness of construction workers working at construction sites and creating a safe working environment. However, the current safety education method and tools cannot provide trainees with realistic and practical experiences that might help better safety awareness in practice. A metaverse, a real-time network of 3D virtual worlds focused on social connection, was created for more interactive communication, collaboration, and coordination between users. Several previous studies have noted that the metaverse has excellent potential for improved safety education performance, but its required functions and practical applications have not been thoroughly researched. In order to fill the research gap, this paper reviewed the potential benefits of a metaverse based on the current research and suggested its application for safety education purposes. This paper scrutinized the metaverse's key functions, particularly its information and knowledge sharing function and reality capture function. Then, the authors created a metaverse prototype based on the two key functions described above. The main contribution of this paper is reviewing the potential benefits of a metaverse for safety education. A realistic and feasible metaverse platform should be developed in future studies, and its impact on safety education should be quantitatively verified.

• 한국통신학회논문지
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• 제40권6호
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• pp.1091-1101
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• 2015

오랜기간 컴퓨터 분야의 연구주제였던 캐시 메커니즘은 네트워크 영역에서 웹 캐시로 응용되었다. 응답시간 감소, 네트워크 자원 절약 등의 다양한 이점을 갖는 웹 캐시는 교체정책에 의해 성능이 좌우되므로, 보다 나은 교체정책의 설계를 위해 웹 캐시가 운용되는 환경에 대한 분석과 고찰이 필수적이다. 따라서 과거에 비해 급속도로 다변화된 현재 웹 환경에서는 그러한 변화를 반영할 수 있는 교체정책이 요구된다. 따라서 본 논문에서는 현재 웹 환경의 특성을 규정하고, 이에 적합한 캐시 교체정책을 설계하고 평가한다.

• International Journal of Computer Science & Network Security
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• 제22권7호
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• pp.294-300
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• 2022

The article highlights the European experience of innovative educational technologies of training management specialists. Based on existing strategies, relevant in the European educational space, the introduction of regulatory elements to maintain a balance between the traditional and innovative format of the educational process, which is typical for the Ukrainian education system is proposed. The article aims to single out educational and technological innovations into a separate cluster of managerial training at different levels in the context of the principles of the modern synergetic sociocultural paradigm. The main objectives of the work are to develop settings to ensure the effective functioning of innovative educational technologies. Among the synergetic principles of educational technologies, providing the formation of necessary competencies of future managers, are: self-organization, interdisciplinarity, nonlinearity, individuality, and technologization. The methods used in the scientific study can be attributed to the group of scientific synergetic methodology. So, the training of specialists in management, implemented in the European practice assumes the use of new educational strategies. These technologies provide both the necessary skills of different levels (hard-soft-digital skills) and the observance of value components (solidarity, ethics, inclusiveness, openness).

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2007년도 춘계종합학술대회
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• pp.773-777
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• 2007

네트워크를 기반으로 하는 시스템들의 발전으로 인하여 매우 다양한 침입이 확산되고 있다. 따라서, 침입자들로부터 위험을 줄이기 위해 평가도구에 관한 연구가 활발하다. 본 논문에서는 위험평가시 동일한 가중치를 적용한 평가와 조직의 특성에 따라 보안요소의 가중치를 가변적으로 적용한 평가를 할 수 있도록 하였으며 각 조직이 자체적으로 보안 점검을 할 수 있도록 설계함으로서 관리 측면에서 취약점을 쉽게 찾을 수 있도록 지원하며, 수행해야 할 권고를 제시한다.

• 한국BIM학회 논문집
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• 제7권1호
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• pp.28-35
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• 2017

Cities have complex system composed diverse activities. The activities in cities have complex relationship that creates diverse urban phenomena. Big Data is emerging technology in order to understand such complex network. This research aims to understand such relations by analysing the diverse city indexes. 28 indexes were collected in 25 of districts in Seoul city and analysed to find a weighted correlation. By defining the correlation values of certain years, it tries to predict the missed index values, "happiness" of each districts in other years. The result presents that the overall prediction accuracy 70.25%. However, for further discussion, the result is considered that this methods may not enough to use in practice, since the data has inconstant accuracy by different learning years.

• Journal of Information Technology Applications and Management
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• 제21권3호
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• pp.19-33
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• 2014

Crowdsourcing is a popular tool for firms to harness external knowledge and resources. One variation of crowdsourcing entails the use of corporate channels in social network services (SNS) such as Twitter to hold public idea competitions. This study examined the role of feedback interaction between participants of idea competitions. More specifically, the study examined the impact of incentives to provide feedback on other participants' ideas. We found that idea competitions where explicit incentives were introduced to elicit crowdsourced feedback in the form of qualitative comments resulted in improved idea generation performance-with more ideas generated overall, and more ideas generated through participant collaborations, through increased comment-posting activities. Based on the findings, implications for theory and practice are discussed.