• Journal of the Korea Society of Computer and Information
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• v.19 no.1
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• pp.141-148
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• 2014

As the quality of the medical treatment service provided by large hospitals grow, the number of patients utilizing the facilities is increasing dramatically. Various studies such as order communication system and treatment guidance system are under their process in order to shorten the waiting time for patients. However, the existing methods assign the treatments in successive order without recognizing the situation of each treatment, therefore increasing a patient's standby time at a hospital. This paper proposes a context-aware treatment guidance system, which recognizes the previously undermined estimated waiting time of each treatment for a patient and recommends a treatment with shorter estimated sojourn time first. This context-aware treatment guidance system provides detailed information of treatment services based on the recommended order of treatments to a patient's smartphone. By utilizing the context-aware treatment guidance system introduced in this paper, patients can reduce their standby time at hospitals to the minimum while hospitals can efficiently service more patients at the same amount of time. The proposed context-aware treatment guidance system proves to be outstanding in treatment order recommendation through comparisons to previously used methods.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.18 no.3 s.118
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• pp.334-340
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• 2007

The prediction for vegetation attenuation using the RET model recommended in the ITU-R requires six RET input parameters. Among these, 4 parameters are related to the scattering characteristics of vegetation. To extract these parameters, two methods can be used. One is to extract the parameters by curve fitting of the measured vegetation-attenuation curve with the RET prediction model, and the other is to use the additional phase function measurement data. In the former method, fitting is quite complex and it does not result in the unique results in some cases. In addition, the extracted parameters lack the physical meaning as well. Thus, in this paper, the measurement method of phase function, and the method of extracting the RET model parameters which lead to more accurate and physically more meaningful results are presented. The extracted RET model parameters are also presented. The RET modeling method, measurement data, and the extracted RET model parameters presented in this paper were submitted to the ITU-R meeting in 2006, and adapted for ITU-R report and recommendation P.833.

• The KIPS Transactions:PartB
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• v.13B no.7 s.110
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• pp.633-642
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• 2006

In the Internet environment many interactions between many users and unknown users take place and it is usually rare to have the trust information about others. Due to the lack of trust information, entities have to take some risks in transactions with others. In this perspective, it is crucial for the entities to be equipped with functionality to accumulate and manage the trust information on other entities in order to reduce risks and uncertainty in their transactions. This paper is concerned with a quantitative computational trust model which takes into account multiple evaluation criteria and uses the recommendation from others in order to get the trust for an entity. In the proposed trust model, the trust for an entity is defined as the expectation for the entity to yield satisfactory outcomes in the given situation. Once an interaction has been made with an entity, it is assumed that outcomes are observed with respect to evaluation criteria. When the trust information is needed, the satisfaction degree, which is the probability to generate satisfactory outcomes for each evaluation criterion, is computed based on the empirical outcome outcome distributions and the entity's preference degrees on the outcomes. Then, the satisfaction degrees for evaluation criteria are aggregated into a trust value. At that time, the reputation information is also incorporated into the trust value. This paper also shows that the model could help the entities effectively choose other entities for transactions with some experiments in e-commerce.

• Journal of Environmental Policy
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• v.9 no.1
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• pp.57-81
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• 2010

Since the Republic of Korea is highly dependent on fossil fuels despite high oil prices, it urgently needs to renew its economic and social system to cut carbon emissions and achieve green growth. Therefore, reforming or eliminating subsidies related to the use of fossil fuels is a timely and oppropriate policy recommendation for Korea. It would be a win-win deal for Korean society as it would not only reduce the use of environmentally harmful fossil fuels but also enhance economic efficiency. In particular, cross-subsidies for industrial, agricultural and night thermal-storage power services make up more than 80 percent of all subsidies provided to the entire electric power industry sector of Korea. Of these cross-subsidies, this paper analyzes the electricity subsidy for industries, which takes up the largest share (about KRW 1.6583 trillion yearly), among the environmentally harmful subsidies in the electric power sector. Thus, the paper focuses on the analysis of ripple effect anticipated when this is reformed. To examine the effects of this subsidy reform, price elasticities were estimated using the ARDL (autoregressive distributed lag) model and quarterly data from 1990 to 2007. The main results of this study show that 1) annual energy demand for electric power in the industrial sector would drop by 12,475,930MWh and 2) $CO_2$ emissions would plummet by 2,644,897 tons per year if the subsidy were reformed. We can deduct from this that the abolition of environmentally harmful subsidies in the electric power sector in the Republic of Korea would considerably contribute to $CO_2$ emissions abatement in the country.

• Journal of IKEEE
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• v.23 no.2
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• pp.739-742
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• 2019

In this paper, we propose enhanced DAP(Dose Area Product). The development of enhanced DAP proposed in this paper has optimized the area dose meter that was developed previously. The development of enhanced DAP performed Optimized design of charge integrator and ADC circuit, optimization of line transceiver for RS-485 communication, optimization of display circuit, and optimization of PC-based control program for interlocking and aging. As a result of evaluating the performance of the proposed system in an accredited testing laboratory, Radiation dose dependence and Radiation quality dependence were measured to be 4.2%, which is below ${\pm}15%$ of international standard. Energy range/Tube voltage was confirmed in the range of 30~150kV. The sensitivity difference between sensor field and sensor field area dose sensitivity was measured to be 4.3%, and it was confirmed that it operates normally under ${\pm}15%$ of international standard. In order to measure the reproducibility of the area dosimeter, it was confirmed that it was 0% and it was operated normally at less than 2% of IEC60580 recommendation. Digital resolution was confirmed to be a minimum unit of $0.01{\mu}Gy{\cdot}m^2$ within the error range for the reference dose per hour.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.167-183
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• 2023

In the recent field of recommendation systems, various studies have been conducted to model sparse data effectively. Among these, GLocal-K(Global and Local Kernels for Recommender Systems) is a research endeavor combining global and local kernels to provide personalized recommendations by considering global data patterns and individual user characteristics. However, due to its utilization of kernel tricks, GLocal-K exhibits diminished performance on highly sparse data and struggles to offer recommendations for new users or items due to the absence of side information. In this paper, to address these limitations of GLocal-K, we propose the GEase-K (Global and EASE kernels for Recommender Systems) model, incorporating the EASE(Embarrassingly Shallow Autoencoders for Sparse Data) model and leveraging side information. Initially, we substitute EASE for the local kernel in GLocal-K to enhance recommendation performance on highly sparse data. EASE, functioning as a simple linear operational structure, is an autoencoder that performs highly on extremely sparse data through regularization and learning item similarity. Additionally, we utilize side information to alleviate the cold-start problem. We enhance the understanding of user-item similarities by employing a conditional autoencoder structure during the training process to incorporate side information. In conclusion, GEase-K demonstrates resilience in highly sparse data and cold-start situations by combining linear and nonlinear structures and utilizing side information. Experimental results show that GEase-K outperforms GLocal-K based on the RMSE and MAE metrics on the highly sparse GoodReads and ModCloth datasets. Furthermore, in cold-start experiments divided into four groups using the GoodReads and ModCloth datasets, GEase-K denotes superior performance compared to GLocal-K.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.2
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• pp.244-251
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• 2007

Intention reading technique is essential to provide personalized services toward more convenient and human-friendly services in complex ubiquitous environment such as a smart home. If a system has knowledge about an user's intention of his/her behavioral pattern, the system can provide mote qualified and satisfactory services automatically in advance to the user's explicit command. In this sense, learning capability is considered as a key function for the intention reading technique in view of knowledge discovery. In this paper, ore introduce a personalized media control method for a possible application iii a smart home. Note that data pattern such as human behavior contains lots of inconsistent data due to limitation of feature extraction and insufficiently available features, where separable data groups are intermingled with inseparable data groups. To deal with such a data pattern, we introduce an effective engineering approach with the combination of fuzzy logic and probabilistic reasoning. The proposed learning system, which is based on IFCS (Iterative Fuzzy Clustering with Supervision) algorithm, extract probabilistic fuzzy rules effectively from the given numerical training data pattern. Furthermore, an extended architectural design methodology of the learning system incorporating with the IFCS algorithm are introduced. Finally, experimental results of the media contents recommendation system are given to show the effectiveness of the proposed system.

• Journal of The Korean Association For Science Education
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• v.40 no.3
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• pp.347-358
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• 2020

He purpose of this study is to design and apply a pilot assessment tools for scientifically gifted and talented elementary school students with lower grades. The assessment tool consists of three parts: homeroom teachers' recommendation, paper and pencil test and performance tests. The tools are verified whether they are suitable for unique characteristics of young children and enable to attract active participation. For suitability check, students' performance tests were inductively analyzed and 30 behavioral patterns were shown which were included and partially exceeded the level of lower elementary students' performance expectation in NGSS. As a result, we concluded that assessment tool developed in this study will be effective in discriminating young pupils' scientific talents. Then for participation check, we compared the number of coding references as an indicator of participation. Two cases were found that students with high interest participated passively in performance tests. We found these 'passive participants' had excessive scientific experiences and extremely narrow region of interest, during the process of complex interpretation between the results of this assessment tool and in-depth interviews with homeroom teachers. We found out in this study that newly developed tools can be used in school scene after modifying and elaboration through accumulation of more case studies.

• Journal of the Economic Geographical Society of Korea
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• v.6 no.1
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• pp.1-20
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• 2003

This paper aims to examine the contribution that the ERVET System, composed of ERVET and real service centers, has made to both governing and enhancing regional innovation system in Emilia Romagna, Italy. ERVET and real service centers both establish and perform plans for regional development and innovation. But they also try to provide varieties of real services for local firms, mostly small and medium-sized firms. Attempting to promote innovation networks between industries, universities and administrative bodies, the ERVET System has become a core intermediary agency of Emilia Romagna in both governing regional innovation system and enhancing regional innovation capabilities. Based on the case of the ERVET System, we propose a policy recommendation. As local governments in Korea have still been less autonomous but hierarchical, it would be difficult for them to make the decision effectively on regional innovation and development initiatives. In this context, we suggest that regional development agencies need to be established on the basis of benchmarking advanced cases in Europe and North America such as the ERVET System.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.41 no.3
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• pp.200-209
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• 2013

In this paper, the types of B-dot controller and the review results of B-dot controller stability are summarized. Also, it is confirmed that B-dot controller is very useful and essential tool when a dawn-dusk low earth orbit(LEO) large satellite has especially to capture the Sun for a required power supply in a reliable way after anomaly and that its algorithm is very simple for on-board implementation. New physical interpretation of B-dot controller is presented as a result of extensive theoretical investigation introducing the concept of transient control torque and steady state control torque. Also, the failure effect analysis results of magnetic torquers as well as a simulation verification are included. And the design recommendation for optimal design is provided to cope with the failure of magnetic torquer. Nonlinear simulation results are included to justify its capability as well as its performance for an application to a dawn-dusk LEO large satellite.