• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.6D
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• pp.571-577
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• 2012

Recently, improving public transport service at disabled people has emerged as a social issue in rural areas. By improving expensive and inefficient existing operating system, the rural bus have to change a personalized service. Under these circumstances, government and local governments are promoting the introduction of DRT(Demand response transport). DRT system is intended to promote the user's convenience. But, until now, in-depth research on the operating costs for the introduction of DRT is not well known. This study aims to look at changes in number of vehicle and operating costs before and after introduction of DRT. The results are as follows. Even though introducing DRT, total number of vehicles increases because it does not reduce the existing number of vehicles. And this study estimated to about 5 to 12 percent of the increase in the operating cost comparing before introduction of DRT. Therefore, The introduction of DRT in rural areas is a need to set the exact purpose as promote transportation convenience or cost efficiency.

• Journal of Acupuncture Research
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• v.27 no.6
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• pp.115-122
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• 2010

Objectives : The purpose of this study was to propose the utilization plan of Ryodoraku in the U-health care systems. Methods : Computerized literature searches were performed for Ryodoraku related articles using the following databases: KISS, RISS, DBPIA, NDSL from 1990 to Oct 2010. Search terms were '양도락' or 'Ryodoraku' or 'U-health'. Due to Ryodoraku coming from Japan, additional literature review(articles published by 2008) on Japanese journal of Ryodoraku medicine was done for compensation. Results : 1. Introduction of U-health : As rapid progress of population aging and strong interest in health, the demand for the traditional Korean medical service is increasing. Until now healthcare service has provided post treatment by face-to-face manner. But according to related researches, proactive treatment is resulted to be more effective for preventing diseases. Particularly, the existing healthcare services have limitations in preventing and managing chronic geriatric degenrative diseases such as metabolic syndrome, CVA, coronary heart diseases, parkinson's diseases, degenerative joint disease, spondylosis, etc., because the cause of the above is complex and even related to life habit. As the advent of ubiquitous technology, patients with the chronic geriatric degenrative diseases can improve life habit such as poor eating habits and physical inactivity without the constraints of time and space through u-healthcare service. Therefor, lots of researches for u-healthcare service focus on providing the personalized healthcare service for preventing and managing that. To cope with this situations, The concept of u-healthcare service should be adopted in the traditional korean medicine and diagnostic devices suitable for it should be also devised and developed based on traditonal korean medine. 2. Review of existing Ryodoraku related articles for applying to U-health : articles investigating feasibility applying Ryodoraku to meridian diagnosis and raising problems of it, articles providing recent research trends of Ryodoraku, Ryodoraku related articles considering usefulness for U-health, and articles confirming the repeatability and reproducity of Ryodoraku were included. Based on the review of the above Ryodoraku related articles, several application of Ryodoraku in the U-health care system. Conclusions : To make preparations for the increasing need of traditional Korean medicine due to rising morbidity rate of chronic geriatric degenerative diseases, it is necessary to appropriately apply Ryodoraku to the U-health care system. The application of Ryodoraku is as follows. 1. To use Ryodoraku additionally to the established diagnostic device of metabolic syndrome, CVA, coronary heart diseases, parkinson's diseases, degenerative joint disease, spondylosis. 2. To apply Ryodoraku to the symptoms or diseases having a tendency to be diagnosed by correlation between the affected meridian and the lesion such as headache, nuchal pain, shoulder pain, low back pain, sciatica, HNP, etc. 3. To secure the repeatability and reproducity of Ryodoraku. 4. To devise and develop Ryodoraku appliance in order to overcome the known drawbacks and to improve error of measurement.

• Journal of Digital Convergence
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• v.15 no.4
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• pp.91-105
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• 2017

Korea is rapidly becoming a multicultural society in recent years, and the number of multicultural families in 2015 exceeds 3.5% and 800,000. Also, as international marriage rate exceeds 10% by 2016, the number of multicultural families is expected to steadily increase. This study is a design of a metadata application profile as part of the foundation for providing learning resources and content tailored to the needs and preferences of married immigrant women and multicultural family members who need to adapt to Korean society. In order to verify the necessity of the research, we conducted an in-depth interview by screening consumer groups, and analyzed the relevant international and Korean national standards as de-jure standards for the design of metadata standard profiles. Then, we analyzed the contents characteristics for multicultural members, and organized the necessary metadata elements into profiles. We defined the mandatory/optional conditions to reflect the needs of content providers. This study is meaningful in that the study analyzes the educational needs of married immigrant women and presents the necessary metadata standards to develop and service effective educational content, such as korean-to-korean conversion system, personalized learning contents recommendation service, and learning management system.

• The KIPS Transactions:PartD
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• v.14D no.7
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• pp.707-718
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• 2007

Recently, much studies for providing mobile users with suitable and useful content services, LBS(Location Based Service) corresponding to the change of users' location, are actively going on. First and foremost, this is basically owing to the progress of location management technologies such as GPS, mobile communication technology and the spread of personal devices like PDA and the cellular phones. Besides, the research scope of LBS has been changed from vehicle tracking and navigation services to intelligent and personalized services considering the changing information of conditions or environment where the users' are located. For example, it inputs the information such as heavy traffic, pollution, and accidents. The query languages which effectively search the stored vehicle and environment information have been studied depending on the increase of the information utilization. However, most of existing moving object query languages are not enough to provide a recommendation service for a user, because they can not be tested and evaluated in real world and did not consider changed environment information. In order to retrieve not only a vehicle location and environment condition but also use them, we suggest a moving object query language for recommendation service and implement a moving object query process system for supporting a query language. It can process a nearest neighbor query for recommendation service which considers various attributes such as a vehicle's location and direction, environment information. It can be applied to location based service application which utilizes the recommended factors based on environmental conditions.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.15-28
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• 2015

As personal devices and pervasive technologies for interacting with networked objects continue to proliferate, there is an unprecedented world of scattered pieces of contextualized information available. However, the explosive growth and variety of information ironically lead users and service providers to make poor decision. In this situation, recommender systems may be a valuable alternative for dealing with these information overload. But they failed to utilize various types of contextual information. In this study, we suggest a methodology for context-aware recommender systems based on the concept of contextual boundary. First, as we suggest contextual boundary-based profiling which reflects contextual data with proper interpretation and structure, we attempt to solve complexity problem in context-aware recommender systems. Second, in neighbor formation with contextual information, our methodology can be expected to solve sparsity and cold-start problem in traditional recommender systems. Finally, we suggest a methodology about context support score-based recommendation generation. Consequently, our methodology can be first step for expanding application of researches on recommender systems. Moreover, as we suggest a flexible model with consideration of new technological development, it will show high performance regardless of their domains. Therefore, we expect that marketers or service providers can easily adopt according to their technical support.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.5
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• pp.1235-1241
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• 2016

Personalized App recommendation system is recently famous since the number of various apps that can be used in smart phones that increases exponentially. However, the site users using google play site with malwares have experienced severe damages of privacy exposure and extortion as well as a simple damage of satisfaction descent at the same time. In addition, Sybil attack (Sybil) manipulating the score (rating) of each app with falmay also present because of the social networks development. Up until now, the sybil detection studies and malicious apps studies have been conducted independently. But it is important to determine finally the existence of intelligent attack with Sybil and malware simultaneously when we consider the intelligent attack types in real-time. Therefore, in this paper we experimentally evaluate the relationship between malware and sybils based on real cralwed dataset of goodlplay. Through the extensive evaluations, the correlation between malware and sybils is low for malware providers to hide themselves from Anti-Virus (AV).

• Korean Chemical Engineering Research
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• v.57 no.4
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• pp.445-454
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• 2019

Layered double hydroxides (LDHs) nanoparticles have emerged as novel nanomaterials for bio-imaging applications due to its unique layered structure, physicochemical properties, and good biocompatibility. Bio-imaging is one of the most important fields for medical applications in clinical diagnostics and therapeutics of various diseases. Enhanced diagnostic techniques are needed to realize new paradigm for next-generation personalized medicine through nanoscale materials. When nanotechnology is introduced into bio-imaging system, nanoparticle probes can endow imaging techniques with enhanced ability to obtain information about biological system at the molecular level. In this review, we summarize structural features of LDH nanoparticles with current issues of bio-imaging system. LDH nanoparticle probes are also discussed through in vitro as well as in vivo studies in various bio-imaging techniques including fluorescence imaging, magnetic resonance imaging (MRI), positron emission tomography (PET), and computed X-ray tomography (CT), which will have the potential in the development of the advanced nanoparticles with high sensitivity and selectivity.

• The Journal of Korean Academy of Prosthodontics
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• v.57 no.3
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• pp.245-253
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• 2019

Orthognathic surgery of skeletal Class III malocclusion improves oral function and facial appearance. The greater amount of skeletal discrepancy, the greater amount of teeth movement required for decompensation, and this often causes pathological changes in periodontal tissue especially in lower anterior dentition. We made a Top-Down treatment plan with personalized analysis using Face Hunter, Plane System and ARCUS Digma II, in order to resolve severe mobility and cross-bite of lower anterior teeth for 49-year-old female patient who had undergone orthognathic surgery 20 years ago due to skeletal Class III malocclusion and mandibular prognathism. Lower anterior teeth were extracted and alveoloplasty was done. After healing of the wound, immediate loading was conducted immediately after implant placement. Final restorations were fabricated Zirconia using CAD/CAM, and inserted intraorally screw-retained type. During 6-month follow-up, no abnormal episodes of restorations were observed, and obtained satisfactorily both of functional and esthetic outcomes.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.139-152
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• 2011

Recommender systems have become an important research field since the emergence of the first paper on collaborative filtering in the mid-1990s. In general, recommender systems are defined as the supporting systems which help users to find information, products, or services (such as books, movies, music, digital products, web sites, and TV programs) by aggregating and analyzing suggestions from other users, which mean reviews from various authorities, and user attributes. However, as academic researches on recommender systems have increased significantly over the last ten years, more researches are required to be applicable in the real world situation. Because research field on recommender systems is still wide and less mature than other research fields. Accordingly, the existing articles on recommender systems need to be reviewed toward the next generation of recommender systems. However, it would be not easy to confine the recommender system researches to specific disciplines, considering the nature of the recommender system researches. So, we reviewed all articles on recommender systems from 37 journals which were published from 2001 to 2010. The 37 journals are selected from top 125 journals of the MIS Journal Rankings. Also, the literature search was based on the descriptors "Recommender system", "Recommendation system", "Personalization system", "Collaborative filtering" and "Contents filtering". The full text of each article was reviewed to eliminate the article that was not actually related to recommender systems. Many of articles were excluded because the articles such as Conference papers, master's and doctoral dissertations, textbook, unpublished working papers, non-English publication papers and news were unfit for our research. We classified articles by year of publication, journals, recommendation fields, and data mining techniques. The recommendation fields and data mining techniques of 187 articles are reviewed and classified into eight recommendation fields (book, document, image, movie, music, shopping, TV program, and others) and eight data mining techniques (association rule, clustering, decision tree, k-nearest neighbor, link analysis, neural network, regression, and other heuristic methods). The results represented in this paper have several significant implications. First, based on previous publication rates, the interest in the recommender system related research will grow significantly in the future. Second, 49 articles are related to movie recommendation whereas image and TV program recommendation are identified in only 6 articles. This result has been caused by the easy use of MovieLens data set. So, it is necessary to prepare data set of other fields. Third, recently social network analysis has been used in the various applications. However studies on recommender systems using social network analysis are deficient. Henceforth, we expect that new recommendation approaches using social network analysis will be developed in the recommender systems. So, it will be an interesting and further research area to evaluate the recommendation system researches using social method analysis. This result provides trend of recommender system researches by examining the published literature, and provides practitioners and researchers with insight and future direction on recommender systems. We hope that this research helps anyone who is interested in recommender systems research to gain insight for future research.

• Journal of Intelligence and Information Systems
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• v.18 no.1
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• pp.39-57
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• 2012

Recently, due to the introduction of high-tech equipment in interactive exhibits, many people's attention has been concentrated on Interactive exhibits that can double the exhibition effect through the interaction with the audience. In addition, it is also possible to measure a variety of audience reaction in the interactive exhibition. Among various audience reactions, this research uses the change of the facial features that can be collected in an interactive exhibition space. This research develops an artificial neural network-based prediction model to predict the response of the audience by measuring the change of the facial features when the audience is given stimulation from the non-excited state. To present the emotion state of the audience, this research uses a Valence-Arousal model. So, this research suggests an overall framework composed of the following six steps. The first step is a step of collecting data for modeling. The data was collected from people participated in the 2012 Seoul DMC Culture Open, and the collected data was used for the experiments. The second step extracts 64 facial features from the collected data and compensates the facial feature values. The third step generates independent and dependent variables of an artificial neural network model. The fourth step extracts the independent variable that affects the dependent variable using the statistical technique. The fifth step builds an artificial neural network model and performs a learning process using train set and test set. Finally the last sixth step is to validate the prediction performance of artificial neural network model using the validation data set. The proposed model is compared with statistical predictive model to see whether it had better performance or not. As a result, although the data set in this experiment had much noise, the proposed model showed better results when the model was compared with multiple regression analysis model. If the prediction model of audience reaction was used in the real exhibition, it will be able to provide countermeasures and services appropriate to the audience's reaction viewing the exhibits. Specifically, if the arousal of audience about Exhibits is low, Action to increase arousal of the audience will be taken. For instance, we recommend the audience another preferred contents or using a light or sound to focus on these exhibits. In other words, when planning future exhibitions, planning the exhibition to satisfy various audience preferences would be possible. And it is expected to foster a personalized environment to concentrate on the exhibits. But, the proposed model in this research still shows the low prediction accuracy. The cause is in some parts as follows : First, the data covers diverse visitors of real exhibitions, so it was difficult to control the optimized experimental environment. So, the collected data has much noise, and it would results a lower accuracy. In further research, the data collection will be conducted in a more optimized experimental environment. The further research to increase the accuracy of the predictions of the model will be conducted. Second, using changes of facial expression only is thought to be not enough to extract audience emotions. If facial expression is combined with other responses, such as the sound, audience behavior, it would result a better result.