• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.11
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• pp.3050-3063
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• 2023

Recommendation systems provide personalized products or services to online users by mining their past preferences. Collaborative filtering is a popular recommendation technique because it is easy to implement. However, with the rapid growth of the number of users in recommendation systems, collaborative filtering suffers from serious scalability and sparsity problems. To address these problems, a novel collaborative filtering recommendation algorithm is proposed. The proposed algorithm partitions the users using affinity propagation clustering, and searches for k nearest neighbors in the partition where active user belongs, which can reduce the range of searching and improve real-time performance. When predicting the ratings of active user's unrated items, mean deviation method is used to impute values for neighbors' missing ratings, thus the sparsity can be decreased and the recommendation quality can be ensured. Experiments based on two different datasets show that the proposed algorithm is excellent both in terms of real-time performance and recommendation quality.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.4
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• pp.1059-1074
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• 2024

The paper is an attempt to study the individual's intention to use mobile banking. In light of the results obtained from the study, the proposed model offers a better fit with the data and explains the intention of individuals to use mobile banking services. Government support, trust, and compatibility significantly contribute to the Perceived behavioral control of a bank customer to use mobile banking while Perceived ease of use, Perceived usefulness, Security and privacy, and risk have a significant positive impact on the attitude of the individuals to utilize mobile banking service. The study uses primary data and the final instrument was administered to 950 respondents, across the country of which 904 data were used for the analysis after editing to accommodate the missing values. The study has adopted structural equation modeling approach to analyze the relationships between the variables in the study. The proposed framework in this study can be utilized to identify the factors that promote the adoption of mobile banking practices and the study also has the potential to provide updated and comprehensive literature on mobile banking, which can accelerate future research in this field.

• Journal of the Korean Society of School Health
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• v.17 no.2
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• pp.11-22
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• 2004

Purpose: The aim of this study was to evaluate the effects of oral health care programs in 3 school-based oral health care center among primary schoolchildren. Methods: School-based oral health care programs included fluoride mouth rinsing, pit and fissure sealing for permanent premolars and molars, fluoride gel application and chewing of xylitol candy. All of the programs were carried out by one dental hygienist among 'D' primary schoolchildren in Daegu city under the supervision of a dentist. Baseline dental examinations were completed and preventive care was implemented for 544 children during one year. All of the children visited a school-based oral health care center every three months for a regular check-up. The final oral examination was conducted from March 15 to April 1, 2004. The data analysis data was made on the basis of SAS 8.01. Mean differences between 2003 and 2004 data were compared by paired t-test. Corresponding p-values were considered significant at values less than 0.05. Results: The DMF rate and DFT index were reduced to 8.0% and 8.4% during one year respectively, but there were no statistically significant differences. The DMF rate was significantly reduced (16.3%) after a one year program of school-based oral health care practice. The DMFT(Decay Missing Filling Tooth) index was also reduced compared to 2003 throughout the entire grade. Conclusion: School-based oral health care programs can reduce the prevalence of dental caries prevalence among schoolchildren during one year. This program also improved the oral health capacity of schoolchildren. It is recommend that the school-based oral health care program should be extended to every primary school in Korea.

• Journal of KIISE:Software and Applications
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• v.37 no.9
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• pp.659-668
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• 2010

Collaborative filtering systems grasp behaviors for a new user and need new information for the user in order to recommend interesting items to the user. For the purpose of acquiring the information the collaborative filtering systems learn behaviors for users based on the previous data and can obtain new information from the results. In this paper, we propose an inductive inference method to obtain new information for users and rank items by using the new information in the proposed method. The proposed method clusters users into groups by learning users through NMF among inductive machine learning methods and selects the group features from the groups by using chi-square. Then, the method classifies a new user into a group by using the bayesian probability model as one of inductive inference methods based on the rating values for the new user and the features of groups. Finally, the method decides the ranks of items by applying the Rocchio algorithm to items with the missing values.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2004.11a
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• pp.272-278
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• 2004

Recently, Pepe et al. (2003) employed the receiver operating characteristic (ROC) approach to rank candidate genes from a microarray experiment that can be used for the biomarker development with the ultimate purpose of the population screening of a cancer, In the cancer microarray experiment based on n patients the researcher often wants to compare the tumor tissue with the normal tissue within the same individual using a common reference RNA. This design is referred to as a reference design or an indirect design. Ideally, this experiment produces n pairs of microarray data, where each pair consists of two sets of microarray data resulting from reference versus normal tissue and reference versus tumor tissue hybridizations. However, for certain individuals either normal tissue or tumor tissue is not large enough for the experimenter to extract enough RNA for conducting the microarray experiment, hence there are missing values either in the normal or tumor tissue data. Practically, we have $n_1$ pairs of complete observations, $n_2$ 'normal only' and $n_3$ 'tumor only' data for the microarray experiment with n patients, where n=$n_1$+$n_2$+$n_3$. We refer to this data set as a mixed data set, as it contains a mix of fully observed and partially observed pair data. This mixed data set was actually observed in the microarray experiment based on human tissues, where human tissues were obtained during the surgical operations of cancer patients. Pepe et al. (2003) provide the rationale of using ROC approach based on two independent samples for ranking candidate gene instead of using t or Mann -Whitney statistics. We first modify ROC approach of ranking genes to a paired data set and further extend it to a mixed data set by taking a weighted average of two ROC values obtained by the paired data set and two independent data sets.

• Journal of Internet Computing and Services
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• v.13 no.5
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• pp.21-31
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• 2012

Threat Evaluation(TE) which has air intelligence attained by identifying friend or foe evaluates the target's threat degree, so it provides information to Weapon Assignment(WA) step. Most of TE data are passed by sensor measured values, but existing techniques(fuzzy, bayesian network, and so on) have many weaknesses that erroneous linkages and missing data may fall into confusion in decision making. Therefore we need to efficient Threat Evaluation system that can refine various sensor data's linkages and calculate reliable threat values under unpredictable war situations. In this paper, we suggest new threat evaluation system based on information fusion JDL model, and it is principle that combine fuzzy which is favorable to refine ambiguous relationships with bayesian network useful to inference battled situation having insufficient evidence and to use learning algorithm. Finally, the system's performance by getting threat evaluation on an air defense scenario is presented.

• Journal of Korean Society of Transportation
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• v.33 no.4
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• pp.417-429
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• 2015

Evaluation of traffic data quality is a backbone of better traffic information and management systems because it directly affects the reliability of traffic information. This study developed an integrated index for evaluating the quality of archived intelligent transportation systems (ITS) data. Two novel indices including spatio-temporal consistency and severity of missing data were devised and integrated with existing indices such as availability and completeness. An evaluation framework was proposed based on the developed integrated index. Both analytical hierarchical analysis (AHP) technique and entropy method were adopted to derive mixed weighting values to be used for the integrated index. It is expected that the proposed methodology would be effectively used in enhancing the quality of traffic data as a part of traffic information system.

• Environmental and Resource Economics Review
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• v.23 no.2
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• pp.249-280
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• 2014

IPCC requires the national uncertainties which show how credible the emission of greenhouse gases is. But the Korean government did not submit the total uncertainties, only the detailed uncertainties by items. Also it uses the default values of IPCC including some missing values. This paper tries to estimate the total uncertainties of energy by categories, which accounts for 85.3% in national emission of greenhouse gases. Concretely, it uses Tier 1 method suggested by IPCC. As a result of the analysis, the uncertainties in energy category are 3.4% similar to Finland's. But there was a big difference among greenhouse gases; carbon dioxide 2.7%, methane 116% and nitrous oxide 473%. So this paper suggests Korean government need to improve not only the activity but also the emission factor of data in order to reduce the national uncertainties in energy category.

• Journal of the Korean Society of Safety
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• v.27 no.6
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• pp.172-177
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• 2012

In areas around Deoksan Li and Deokjeon Li, Inje Eup, Inje Gun, located between $38^{\circ}2^{\prime}55^{{\prime}{\prime}}N$ and $38^{\circ}5^{\prime}50^{{\prime}{\prime}}N$ in latitude and $128^{\circ}11^{\prime}20^{{\prime}{\prime}}E$ and $128^{\circ}18^{\prime}20^{{\prime}{\prime}}E$ in longitude, large-sized avalanche disasters occurred due to Typhoon Ewiniar in 2006. As a result, 29 people were dead or missing, along with a total of 37.25 billion won of financial loss(Gangwon Province, 2006). To evaluate such landslide and debris flow risk areas and their vulnerability, this study applied a technique called 'Weight of Evidence' based on GIS. Especially based on the overlay analysis of aerial images before the occurrence of landslides and debris flows in 2005 and after 2006, this study extracted 475 damage-occurrence areas in a shape of point, and established a DB by using such factors as topography, hydrologic, soil and forest physiognomy through GIS. For the prediction diagram of debris flow and landslide risk areas, this study calculated W+ and W-, the weighted values of each factor of Weight Evidence, while overlaying the weighted values of factors. Besides, the diagram showed about 76% in prediction accuracy, and it was also found to have a relatively high correlationship with the areas where such natural disasters actually occurred.

• Structural Engineering and Mechanics
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• v.81 no.3
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• pp.293-303
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• 2022

As infrastructure ages and traffic load increases, serious public concerns have arisen for the well-being of bridges. The current health monitoring practice focuses on large-scale bridges rather than short span bridges. However, it is critical that more attention should be given to these behind-the-scene bridges. The relevant information about the construction methods and as-built properties are most likely missing. Additionally, since the condition of a bridge has unavoidably changed during service, due to weathering and deterioration, the material properties and boundary conditions would also have changed since its construction. Therefore, it is not appropriate to continue using the design values of the bridge parameters when undertaking any analysis to evaluate bridge performance. It is imperative to update the model, using finite element (FE) analysis to reflect the current structural condition. In this study, a FE model is established to simulate a concrete culvert bridge in New South Wales, Australia. That model, however, contains a number of parameter uncertainties that would compromise the accuracy of analytical results. The model is therefore updated with a neural network (NN) optimisation algorithm incorporating Monte Carlo (MC) simulation to minimise the uncertainties in parameters. The modal frequency and strain responses produced by the updated FE model are compared with the frequency and strain values on-site measured by sensors. The outcome indicates that the NN model updating incorporating MC simulation is a feasible and robust optimisation method for updating numerical models so as to minimise the difference between numerical models and their real-world counterparts.