• IE interfaces
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• v.18 no.4
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• pp.390-401
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• 2005

In this paper, we propose an efficient internet-based logistics brokerage concept which can overcome the weakness of the traditional off-line method to intermediate between vehicle owners and shippers for matching empty vehicles and freights. For defining a business model based on the new concept and implementing an information system, it is necessary to analyze the business process for the internet-based logistics brokerage using a modeling methodology. In this paper, we analyze the logistics brokerage process using the UN/CEFACT Modeling Methodology (UMM) being utilized as a standard modeling methodology in the area of electronic commerce. After analyzing the business process, we can expect that the UMM can be used as a useful tool for modeling the business process of electronic commerce in which the description of the collaborative work is very important.

• Journal of Ocean Engineering and Technology
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• v.29 no.3
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• pp.249-254
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• 2015

Buoys are widely used in marine areas because they can mark positions and simultaneously acquire and exchange underwater, surface, and airborne information. Recently, the need for controlling and optimizing a buoy's position and attitude has been raised to achieve successful communication in a heterogeneous collaborative network composed of an underwater robot, a surface robot, and an airborne robot. A buoy in the form of a marine robot would be ideal to address this issue, as it can serve as a moving node of the communication network. Therefore, a buoy-based autonomous surface robot-kit with the abilities of sonar-based avoidance, dynamic position control, and static attitude control was developed and is discussed in this paper. The test and evaluation results of this kit show the possibility of real-world applications and the need for additional studies.

• Annual Conference of KIPS
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• 2010.04a
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• pp.1113-1114
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• 2010

협업필터링 방법은 가장 일반적으로 사용되는 추천 시스템이다. 그런데 협업필터링 방법은 희박성, 확장성 그리고 투명성 등의 문제점을 가지고 있다. 본 논문에서는 개인 성향 중 장르, 성격, 나이, 성별, 혈액형, 지역 등을 고려하여 희박성 문제를 개선한 영화 추천 시스템을 제시한다. 즉, 개인 성향 정보에 따라 가장 성향이 비슷한 사용자들을 분류하고, 그 분류된 정보를 이용하여 개인에게 가장 적합한 개선된 영화추천 기법을 제안한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.159-160
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• 2021

From the simulation results, under the collaborative platform of big data based on coordination of the beer industry to mobilize the supply chain operation condition, supply chain direct logistics inventory are in a relatively stable value, and there is no zero inventory or even a serious lack of beer in the stock situations like traditional beer supply chain operation, which avoid the situation of demand information expansion caused by chain inventory levels report because of the serious lack of supply.

• Journal of Information Technology and Architecture
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• v.10 no.3
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• pp.371-378
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• 2013

Video-demand learning through E-learning continuously increases on these days. However, not all video-demand learning systems can be utilized properly. When students study by education videos not matched to level of their own, it is possible for them to lose interest in learning. It causes to reduce the learning efficiency. In order to solve the problem, we need to develop a recommendation system which recommends customized education videos according the study levels of students. In this paper, we estimate the study level based on the history of students' watching behaviors such as average watching time, skipping and rewinding of videos. In the experimental section, we demonstrate our recommendation system using real students' video watching history to show that our system is feasible in a practical environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.6
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• pp.1706-1727
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• 2023

Under Water Sensor Networks (UWSN) has gained attraction among various communities for its potential applications like acoustic monitoring, 3D mapping, tsunami detection, oil spill monitoring, and target tracking. Unlike terrestrial sensor networks, it performs an acoustic mode of communication to carry out collaborative tasks. Typically, surface sink nodes are deployed for aggregating acoustic phenomena collected from the underwater sensors through the multi-hop path. In this context, UWSN is constrained by factors such as lower bandwidth, high propagation delay, and limited battery power. Also, the vulnerabilities to compromise the aquatic environment are in growing numbers. The paper proposes an Energy-Efficient standalone Intrusion Detection System (EEIDS) to entail the acoustic environment against malicious attacks and improve the network lifetime. In EEIDS, attributes such as node ID, residual energy, and depth value are verified for forwarding the data packets in a secured path and stabilizing the nodes' energy levels. Initially, for each node, three agents are modeled to perform the assigned responsibilities. For instance, ID agent verifies the node's authentication of the node, EN agent checks for the residual energy of the node, and D agent substantiates the depth value of each node. Next, the classification of normal and malevolent nodes is performed by determining the score for each node. Furthermore, the proposed system utilizes the sheep-flock heredity algorithm to validate the input attributes using the optimized probability values stored in the training dataset. This assists in finding out the best-fit motes in the UWSN. Significantly, the proposed system detects and isolates the malicious nodes with tampered credentials and nodes with lower residual energy in minimal time. The parameters such as the time taken for malicious node detection, network lifetime, energy consumption, and delivery ratio are investigated using simulation tools. Comparison results show that the proposed EEIDS outperforms the existing acoustic security systems.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.2
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• pp.277-284
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• 2017

In a flood of information, most users will want to get a proper recommendation. If a recommender system fails to give appropriate contents, then quality of experience (QoE) will be drastically decreased. In this paper, we propose a recommender system based on the intra-cluster users' item preference for improving recommendation accuracy indices such as precision, recall, and F1 score. To this end, first, users are divided into several clusters based on the actual rating data and Pearson correlation coefficient (PCC). Afterwards, we give each item an advantage/disadvantage according to the preference tendency by users within the same cluster. Specifically, an item will be received an advantage/disadvantage when the item which has been averagely rated by other users within the same cluster is above/below a predefined threshold. The proposed algorithm shows a statistically significant performance improvement over the item-based collaborative filtering algorithm with no clustering in terms of recommendation accuracy indices such as precision, recall, and F1 score.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2008.04a
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• pp.241-246
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• 2008

Design of a high-speed railway line requires collaboration of heterogeneous application systems and of engineers with different background. Object-based 3D models with metadata can be a shared information model for the effective collaborative design. In this paper, railway infrastructure information model is proposed to enable integrated and inter-operable works throughout the life-cycle of the railway infrastructures, from planning to maintenance. In order to develop the model, object-based 3-D models were built for a 10km railway among Korea high-speed railway lines. The model has basically three information layers for designers, contractors and an owner, respectively. Prestressed concrete box-girders are the most common superstructure of bridges. The design information layer has metadata on requirements, design codes, geometry, analysis and so on. The construction layer has data on drawings, real data for material and products, schedules and so on. The maintenance layer for the owner has the final geometry, material data, products and their suppliers and so on. These information has its own data architecture which is derived from similar concept of product breakdown structure(PBS) and work breakdown structure(WBS). The constructed RIIM for the infrastructures of the high-speed railway was successfully applied to various areas such as design check, structural analysis, automated estimation, construction simulation, virtual viewing, and digital mock-up. The integrated information model can realize virtual construction system for railway lines and dramatically increase the productivity of the whole engineering process.

• Journal of Microbiology and Biotechnology
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• v.14 no.5
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• pp.1081-1085
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• 2004

Genome research has become very popular in most nations. In order to enhance the efficiency of collaboration among genome research groups, ways to store and share data, communicate with each other, be guided through right research strategies, and to easily use well-established databases. In addition, since techniques and softwares for genome research groups are well established, a similar research road map could commonly be applied. In this study, we developed a web-based work place for effective genome research, named 'BioPlace.' From the beginning of writing a proposal, research members can work on the same environment with convenient aid to share files or data. BioPlace provides various ways of collaboration methods among genome researchers. The BioPlace system supports two types of workplaces, namely 'Personal Workspace' and 'Team Workspace.' For each BioPlace user, a Persona] Workspace is provided, while a Team Workspace is provided for each group with the same purpose. In addition, BioPlace provides a 'General Research Road Map' for genome research, and several Korean user interfaces for BLAST, PDB, and Primer3. We expect that BioPlace may facilitate collaboration of genome research among the experienced scientists and help beginners in many different ways as well.

• Annual Conference of KIPS
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• 2002.11c
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• pp.2133-2136
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• 2002

인터넷 특성상 방대한 양의 정보와 상품 등으로 사용자들이 원하는 정보를 찾기 위해서 많은 시간을 낭비하고 있는 실정이다. 이러한 사용자의 시간 소모를 중이기 위해서 추천 시스템이 개발되었다. 현재 인터넷 상의 추천 기술 중에서 가장 많이 사용하는 기법으로는 협력적 여과(Collaborative filtering) 방법이다. 그러나, 협력적 추천 방법으로 추천 받기 위해서는 특정수 이상의 아이템에 대한 평가가 필요하며, 또한 비슷한 성향을 가지는 일부 사용자 정보에 근거하여 추천함으로써 나머지 사용자 정보를 무시하는 경향이 있다. 이러한 문제점이 발생되므로 최근에는 데이터 마이닝(Data Mining) 기법 중 연관 규칙(Association Rule)을 이용한 추천 시스템이 개발되고 있다[1,10]. 그러나, 연관 규칙 기법은 개인별 사용자의 성향을 반영하지 못하는 단점이 있다[4]. 연관 규칙은 단지 대용량 데이터 베이스에서 아이템간의 지지도(Support)와 신뢰도(Confidence)에 근거하여 규칙을 발견하는 특징을 가지고 있기 때문이다. 즉 개인성향을 무시하고 아이템간의 연관성만을 근거로 하여 아이템을 추천하기 때문이다. 본 논문에서는 효율적인 연관 규칙을 이용한 개인화 추천 시스템을 구현하기 위해서 연관 규칙과 여과 방법을 통합한 시스템을 제안한다. 본 시스템에 대하여 성능 비교 실험을 수행함으로써 제안한 방법의 타당성을 제시한다.