• Smart Media Journal
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• v.5 no.2
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• pp.84-89
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• 2016

For a place-recommendation model based on user's behavior and multi-attribute attitude in this thesis. We focus groups that show similar patterns of visiting restaurants and then compare one and the other. We make use of The Fishbein Equation, Pearson's Correlation Coefficient to calculate multi-attribute attitude scores. Furthermore, We also make use of Preference Prediction Algorithm and Distance based method named "Euclidean Distance" to provide accurate results. We can demonstrate how excellent this system is through several experiments carried out with actual data.

• Journal of KIISE:Software and Applications
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• v.31 no.2
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• pp.153-163
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• 2004

Many recommender systems are based on Content-based Filtering and Social Filtering Both methods have their own advantages and disadvantages, and they complement each other rather than compete. So incorporating of both methods can make the better system and combination technique controls the quality of the entire recommender system. In this paper, we presented each user has his own tendency to decide which is the better recommendation for himself among the various recommendation results, and suggested the Personalized combination technique. To represent user tendency, we defined and used loyalty, diversity and pioneerity and showed by experiments that our combination technique is useful. This combination technique improved the average coverage 23% and for the ceiling 40%.

• Information Systems Review
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• v.5 no.2
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• pp.151-168
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• 2003

A knowledge portal is an integrated gateway for accessing relevant knowledge, collaborating and communicating with other users, and also linking internal applications which is becoming crucial in the age of information abundance. Research and development is a typical knowledge-intensive activity. However, knowledge management support in R&D has been minimal in most research organizations. In this paper, a knowledge portal is designed to support team-based researches in science and technology for searching and browsing knowledge, and also communicating with other team members, coordinating research project and collaborating with other researchers. Automating knowledge acquisition from various knowledge sources, knowledge categorization by applying text categorization method, and knowledge recommendation can help to relieve management effort and increase the efficiency of knowledge management processes. A prototype system based on the suggested model is also presented.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.5
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• pp.2299-2318
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• 2019

Location-aware networks are of great importance for both civil lives and military applications. Methods based on line-of-sight (LOS) measurements suffer sever performance loss in harsh environments such as indoor scenarios, where sensors can receive both LOS and non-line-of-sight (NLOS) measurements. In this paper, we propose a data association (DA) process based on the expectation maximization (EM) algorithm, which enables us to exploit multipath components (MPCs). By setting the mapping relationship between the measurements and scatters as a latent variable, coefficients of the Gaussian mixture model are estimated. Moreover, considering the misalignment of sensor position, we propose a space-alternating generalized expectation maximization (SAGE)-based algorithms to jointly update the target localization and sensor position information. A two dimensional (2-D) circularly symmetric Gaussian distribution is employed to approximate the probability density function of the sensor's position uncertainty via the minimization of the Kullback-Leibler divergence (KLD), which enables us to calculate the expectation step with low computational complexity. Moreover, a distributed implementation is derived based on the average consensus method to improve the scalability of the proposed algorithm. Simulation results demonstrate that the proposed centralized and distributed algorithms can perform close to the Monte Carlo-based method with much lower communication overhead and computational complexity.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.216-216
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• 2015

Frequent hydro-meteorological events caused by global climate change and human exacerbate activities, make the water resource problem more complicated. The increasing speed urbanization brings a significant impact on the city flood control and security, water supply safety, water ecological security, water environment safety and the water engineering security in China, and puts forward higher requirements to urban water integrated management, undoubtedly which become the biggest obstacle for water ecological civilization construction, thus urgent requiring an advanced methods to enhance the effectiveness of the water integrated management. The other fields of smart ideas point out a development path for water resource development. The construction demand of smart water resource is expounded in the paper, combining the philosophy of modern Internet of things with the application of cloud computing technology. The concept of smart water resource is analyzed, the connotation characteristics of smart water resource is extracted, and the general model of smart water resource is refined. Then, the frame structure of smart water resource is put forward. The connotation and the overall framework of the smart water resource represent a higher level of water resource informationization development and provide a comprehensive scientific and technological support to transform water resource management from an extensive, passive, static, branch and traditional management to a fine, active, dynamic, collaborative and modern management.

• Journal of Information Processing Systems
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• v.17 no.3
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• pp.462-472
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• 2021

With an increase in the scale of recommender systems, users' rating data tend to be extremely sparse. Some methods have been utilized to alleviate this problem; nevertheless, it has not been satisfactorily solved yet. Therefore, we propose an effective pre-rating method based on users' dichotomous preferences and average ratings fusion. First, based on a user-item ratings matrix, a new user-item preference matrix was constructed to analyze and model user preferences. The items were then divided into two categories based on a parameterized dynamic threshold. The missing ratings for items that the user was not interested in were directly filled with the lowest user rating; otherwise, fusion ratings were utilized to fill the missing ratings. Further, an optimized parameter λ was introduced to adjust their weights. Finally, we verified our method on a standard dataset. The experimental results show that our method can effectively reduce the prediction error and improve the recommendation quality. As for its application, our method is effective, but not complicated.

• The Journal of Korean Institute of Information Technology
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• v.17 no.1
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• pp.149-156
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• 2019

Mixed reality technology (MR) has become one of the fourth industrial revolution element technologies. MR technology has been widely applied not only as a digital contents industry but also in the fields of architecture, tourism, medical field, and education. In this paper, we propose a collaborative service platform for architectural applications that inter-operate with heterogeneous devices such as MR device, PC and mobile, and develop prototype system and verify it. As a result, the 3D model using the skp extension, which is mainly used in architecture design office, was created by using developed prototype system and generate the MR contents for the hololens, which is the MR device, and the conversion time and normal operation were confirmed.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.1
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• pp.219-228
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• 2021

The aim of this study was to investigate the learning styles with personalities of medical students which may affect the efficiency of teaching-learning system of clinical education to determine the association with the clinical performance examination achievement of the students. The learning styles and personality traits of 147 students of medical college were investigated. The obtained data were analyzed by statistical analysis including independent t-test and correlation analysis. The results of the analyses are as follows: there was significant difference in the participation model in the different genders; of the personality traits, there was significant difference in self-transcendence in the different genders, whereas there was significant difference in the persistence for past failure experiences; and there was significant association between the 6 sub-learning models(Independent vs. Dependent, Collaborative vs. Competitive, and Participant vs. Avoidant learning styles) and the personality traits(Novelty Seeking, Harm Avoidance, Reward Dependence, Persistence, Self-directedness, Cooperativeness and Self-transcendence). In addition, the participant type of students had higher scholastic achievements in clinical performance, and the students who scored high in self-transcendence and persistence also had higher clinical performance. In conclusion, the student's learning style and personalities affected the clinical scholastic performance. We believe that considering this current study, it would be possible to improve the quality of clinical education of medical teaching as well as helping medical students to choose career paths that are suitable for their personalities.

• Research in Community and Public Health Nursing
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• v.32 no.2
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• pp.205-219
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• 2021

Purpose: This concept analysis was conducted to clarify 'parents' treatment adherence for an epileptic child or adolescent'. Methods: The analysis used a hybrid model comprising three phases: theoretical phase, fieldwork phase, and integration phase. In the theoretical phase, fifty studies were reviewed. Interviews with four parents of epileptic children or adolescents were conducted during the fieldwork phase. In the integration phase, the results derived from prior phases were synthesized and clarified. All phases were performed cyclically. Results: The concept, 'parents' treatment adherence for an epileptic child or adolescent' was defined as parents' voluntary and goal-directed behavior towards the epilepsy treatment for their children: a collaborative decision-making process with health-care providers, establishing a support system, adaptability to the treatment plans, and appraisals of the child's health condition. Conclusion: This achievement is thought to contribute to improving the accuracy and validity of the concept measurement. It has implications for additional research on how the concept 'treatment adherence' differs in diverse health problems and other population groups than parents of children and adolescents with epilepsy.

• The Journal of Korea Robotics Society
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• v.17 no.3
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• pp.339-346
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• 2022

To operate in real environment, humanoid robots should be able to react to unknown disturbances. To deal with disturbances, various robust control algorithms have been developed for decades. But for collaborative works such as teleoperation system, a compliance control can be the better solution for disturbance reactions. In this paper, a center of mass (CoM) compliance control algorithm for humanoid robots is proposed. The proposed algorithm is based on the state observer and positive feedback of disturbance. With the state observer based on humanoid CoM control performance model, disturbance in each direction can be observed. The positive feedback of disturbances to the reference CoM trajectory enables compliant motion. The main contributions of this algorithm are achieving compliance independently in each axis and maintaining balance against external force. Through dynamic simulations, the performance of the proposed method was demonstrated. Under two types of disturbance conditions, humanoid robot DYROS-JET reacted with compliant motion via the proposed algorithm.