• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.32 no.2
• /
• pp.112-119
• /
• 2009

Telecare, one of the e-healthcare services with lCT, is a promising technology which aims to monitor the state of patients and then provide the medical services appropriately in remote sites. Virtual telecare team based on the concept of virtual collaborative teams which consist of a patient, a doctor, and a telecare team, operates on a temporary basis in need. Reputation, which means the degree of a patient's belief to a doctor in consideration, is the most important factor to make the virtual telecare team trustable. In this paper, we propose the fuzzy reputation model of a virtual telecare team, which is a reputation-based trust model based on fuzzy set theory. An illustrative example is also given in order to show the applicability of the model to the concept of a virtual telecare team.

• Annual Conference of KIPS
• /
• 2013.05a
• /
• pp.1100-1102
• /
• 2013

현대사회에서는 외모가 내 외적으로 자신을 나타내는 지표이자 상징이며, 사회적 위치나 경제적 상황, 자아정체성을 대변할 수 있다. 또한 경제능력이 향상되고 기존의 성역할 개념의 약화, 사회진출과 인간관계 유지를 위해 남성들도 외모관리에 대한 관심이 높아지기 시작했다. 본 논문은 비교적 화장품에 대한 정보를 잘 알지 못하는 남성들을 대상으로 웹에서 사용자의 나이, 피부톤, 피부타입에 알맞은 화장품을 추천해주는 시스템을 소개한다.

• Journal of Internet Computing and Services
• /
• v.18 no.3
• /
• pp.19-28
• /
• 2017

Collaborative filtering (CF) is a system that interprets the relationship between a user and a product and recommends the product to a specific user. The CF model is advantageous in that it can recommend products to users with only rating data without any additional information such as contents. However, there are many cases where a user does not give a rating even after consuming the product as well as consuming only a small portion of the total product. This means that the number of ratings observed is very small and the user rating matrix is very sparse. The sparsity of this rating data poses a problem in raising CF performance. In this paper, we concentrate on raising the performance of latent factor model (especially SVD). We propose a new model that includes product similarity information and co occurrence information in SVD. The similarity and concurrence information obtained from the rating data increased the expressiveness of the latent space in terms of latent factors. Thus, Recall increased by 16% and Precision and NDCG increased by 8% and 7%, respectively. The proposed method of the paper will show better performance than the existing method when combined with other recommender systems in the future.

• Journal of Information Technology Applications and Management
• /
• v.27 no.2
• /
• pp.23-36
• /
• 2020

The promulgation of the overall framework of Chinese students' development of core literacy has made the implementation of core literacy into specific teaching activities an urgent problem to be solved in the field of education. Based on the analysis of the problems existing in the undergraduate education under the mode of emphasizing theory and neglecting practice, this paper constructs the practical teaching system of Database Principle Course Based on the core quality, expounds the implementation strategy of practical teaching, and probes into how to train the students in the practical teaching of database principle Cultivate scientific spirit, learning ability, practical innovation, responsibility and other core literacy. After 5 rounds of practice, students have achieved better development in independent development and collaborative work, and their awareness of practical innovation has been significantly improved.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.11
• /
• pp.4453-4468
• /
• 2015

This paper investigates optimization-based base station (BS) placement. An optimization model is defined and the BS placement problem is transformed to a lexicographical stratified programming (LSP) model for a given trajectory, according to different accuracy requirements. The feasible region for BS deployment is obtained from the positioning system requirement, which is also solved with signal coverage problem in BS placement. The LSP mathematical model is formulated with the average geometric dilution of precision (GDOP) as the criterion. To achieve an optimization solution, a tolerant factor based complete stratified series approach and grid searching method are utilized to obtain the possible optimal BS placement. Because of the LSP model utilization, the proposed algorithm has wider application scenarios with different accuracy requirements over different trajectory segments. Simulation results demonstrate that the proposed algorithm has better BS placement result than existing approaches for a given trajectory.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.27 no.4
• /
• pp.499-506
• /
• 2003

The design cycle associated with large engineering systems requires an initial decomposition of the complex system into design processes which are coupled through the transference of output data. Some of these design processes may be grouped into iterative subcycles. In analyzing or optimizing such a coupled system, it is essential to determine the best order of the processes within these subcycles to reduce design cycle time and cost. This is accomplished by decomposing large multidisciplinary problems into several sub design structure matrices (DSMs) and processing them in parallel This paper proposes a new method for parallel decomposition of multidisciplinary problems to improve design efficiency by using the multi-objective genetic algorithm and two sample test cases are presented to show the effect of the suggested decomposition method.

• Journal of Korea Multimedia Society
• /
• v.21 no.12
• /
• pp.1448-1458
• /
• 2018

Vehicular Ad-Hoc Networks (VANETs) have become one of the active areas of research, standardization, and development because they have tremendous potentials to improve vehicle and road safety, traffic efficiency, and convenience as well as comfort to both drivers and passengers. However, message trustfulness is a challenge because the propagation of false message by malicious vehicles induces unreliable and ineffectiveness of VANETs, Therefore, we need a reliable reputation method to ensure message trustfulness. In this paper, we consider a vulnerability against the Sybil attack of the previous reputation systems based on blockchain and suggest a new reputation system which resists against Sybil attack on the previous system. We propose an initial authentication process as a countermeasure against a Sybil attack and provide a reliable reputation with a cooperative message delivery to cope with message omission. In addition, we use Homomorphic Commitment to protect the privacy breaches in VANETs environment.

• Korean Journal of Computational Design and Engineering
• /
• v.15 no.2
• /
• pp.157-165
• /
• 2010

In the manufacturing industries, CAE analysis results are frequently required during the product development process for design verification. CAE data which include all related information of an analysis is, however, not efficiently shared among engineers because CAE data size is in general very large to deal with. At first, we represent a proposed lightweight format which is capable to include all the types of CAE analysis results and to support hierarchical data structure. Since each CAE system has different data structures of its own, a translator which translates to the proposed format is also represented. Unlike the design environment with CAD system, many CAE systems are used in a manufacturing company because many sorts of analysis are performed usually for a product design. Thus, lots of CAE results are generated and occupy huge size within storage, and they make it harder to manage or share many CAE results efficiently. A multi-CAE management system which is able to share many types of CAE data simultaneously using lightweight format is proposed in this paper. Finally, an implementation of the system for this will be introduced.

• Journal of Korean Institute of Industrial Engineers
• /
• v.36 no.3
• /
• pp.193-202
• /
• 2010

The recommender system is a typical software solution for personalized services which are now popular in e-commerce sites. Most of the existing recommender systems are based on customers' explicit rating data on items (e.g., ratings on movies), and it is only recently that recommender systems based on implicit ratings have been proposed as a better alternative. Implicit ratings of a customer on those items that are clicked but not purchased can be inferred from the customer's navigational and behavioral patterns. In this article, a dimensionality reduction (DR) technique is newly applied to the implicit rating-based recommender system, and its effectiveness is assessed using an experimental e-commerce site. The experimental results indicate that the performance of the proposed approach is superior or at least similar to the conventional collaborative filtering (CF)-based approach unless the number of recommended products is 'large.' In addition, the proposed approach requires less memory space and is computationally more efficient.

• Journal of Intelligence and Information Systems
• /
• v.17 no.3
• /
• pp.79-98
• /
• 2011

This paper proposes a semantic recommendation technique for a personalized e-commerce portal. Semantic recommendation is achieved by utilizing the attributes of products. The semantic similarity of the products is merged with the rating information of the products to provide an accurate recommendation. The recommendation technique also analyzes various attitudes of the customer to evaluate the implicit rating of products. Attitudes are classifies into three types such as "purchasing product", "adding product to shopping cart", and "viewing the product information." We implicitly track customer attitude to estimate the rating of products for recommending products. Also we implement a session validation process to identify the valid sessions that are highly important for giving an accurate recommendation. Our recommendation technique shows a high degree of accuracy as we use age groupings of customers with similar preferences. The experimental section shows that our proposed recommendation method outperforms well known collaborative filtering methods not only for the existing customer, but also for the new user with no previous purchase record.