• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.6
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• pp.495-508
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• 2017

Today, MMS (Mobile Mapping System) uses the strengths of individual sensor technologies on a variety of platforms to increase the efficiency of geospatial data collection. In this paper, we analyzed the market size and technology trend of mobile mapping market in Korea and abroad, and analyzed frequency, trend, and characteristics of MMS related patents. The results of the analysis are as follows: First, it is expected that the domestic and overseas mobile mapping market will continue to grow in the future, and MMS-related technologies and applications are rapidly developing. Active research and development investment is required to preoccupy future market through technology development and patent competition. Second, the frequency of filing domestic patents is highly correlated with the results of national R&D, and industrial patent applications are highly related to national projects. It is analyzed as the result of introduction of preemptive technologies and research and development of companies for preemption in related industry rather than market development. Lastly, in Korean geospatial information industry survey, It is necessary to maintain the data so that it can be compared with the data of foreign institutions. In particular, statistical data that can grasp the market size in terms of geospatial information utilization and technical aspects are desperately needed.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.1
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• pp.70-79
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• 2014

Following the technology developments of traffic network and communication for the wide area, the importance of the cooperation system to vitalize the wide area economy is increasing. Therefore, in this study, DongNam Kwon industry information system is established for the industrial information sharing based on GIS in the DongNam Kwon wide area economy. The DongNam Kwon is an industrial integration area centered with the manufacturing so that the operation of effective industrial cluster and cooperation systems are required across the administrational boundaries. To establish the database of the information, the information system was established utilizing already established industrial databases in Busan, Ulsan and Gyeongnam. But, various issues caused by the discordances among the data of each local government and the insufficiency of GIS based location information have been found. According to the analysis, the standardization considering the courses of collection, distributions and utilization are required immediately to solve the issues. This study establishes an 2-way industrial information system enabling the information creation and the phased approach between the administrator and the user in the bi-directions on the web by utilizing cadastral and numerical maps. The result of this study would have a meaning in providing a fundamental frame for cooperative responses and cooperation system for DongNam Kwon's industrial promotion using industrial information sharing.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.2
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• pp.22-34
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• 2011

This paper presents the investigation results of a research on how engineers can analyze the economic effect of the ETCS(Electronic Toll Collection System) installed to minimize the vehicle delays on freeway tollgates during toll payments. This research considered this economic effect to occur in the form of vehicle passing time reductions at the ETCS, and the multi-service queuing theory was applied to estimate these values. This research found: 1) When vehicles approaching tollgates show Poisson distribution and the service time of the ETCS shows Exponential distribution, the multi-service queuing theory would be applicable for estimating vehicle passing times at toll-gates, 2) Despite the ETCS placement, exit sections of tollgates give a greater reduction of vehicle passing times than entering sections due to more delays at conventional toll payments, and 3)The ETCS would not guarantee vehicle passing time reductions all the time, because in such a case as many vehicles were queuing at the ETCS, the total delay level for a toll gate would increase greatly. In addition, in order to examine the accuracy of the estimated vehicle passing values, this research compared the values from the multi-service queuing theory with the observed values from a set of field survey values at freeway toll-gates, and found that the two values were in a good agreement with a very low error range of 1-3 seconds per vehicle. Based on this result, the multi-service queuing theory was recommended for practice.

• Journal of Korean Society for Atmospheric Environment
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• v.17 no.1
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• pp.85-96
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• 2001

The objective of this study is to develop the water spraying which can effectively by applied to the control or suppression of the fugitive dust generated from the scrap metal handling area at the Port of Inchon. As a first step toward this goal, we carried out some preliminary analyses on the chemical composition, physical shape, and particle size distribution of the sample dust. Next, to quantitatively investigate the effect of adding surfactants to the spraying water on the wettability of the sample dust, the Standard Sink Test was carried out for four different surfactants and at six different concentrations using the surfactants considered in this study. Results of from the preliminary analysis indicated that the main chemical component consisting of the sample dust is Goethite(FeO(OH)) and that the particles smaller than 10 ${\mu}{\textrm}{m}$ in geometric diameter occupy about 36% of the sample dust in mass. This result implies that the fugitive dust generated from the scrap metal handling area at the Port of Inchon should affect the environment nearby more than we have expected. This is because of relatively large mass percentage of the small metal particles less than 10${\mu}{\textrm}{m}$ in geometric diameter, what we may call respirable particles. As for the results of the Standard Sink Test, higher surfactant concentration tends to result in the higher wettability of the sample dust for the surfactants considered in this study, which in turn ensures the high particle collection efficiency of the droplets generated from the water spraying system. Based upon this preliminary results, studies to develop more sophisticated scaled model for dynamic test in underway and the effort to find the best surfactants as well as the optimum operating conditions are being made at the same time.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.21 no.4
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• pp.149-160
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• 2010

In 1997, Lavagnino defined four stages of technology trends in libraries; but, he left a question about the fifth stage. Based on literature review, the following; Web technology, open source application, library consortia, digitization, wireless, and social media are the main trends in the fifth stage. Analyzing the job advertisements (ads) dating from 2006 to 2010 in systems librarianship, the analysis showed that there are three patterns. The first pattern is that the title of 'system librarian' is no longer specific to managing only the ILS at many libraries. The second pattern - network management skills - is not highly required in the job ads. And the last pattern - especially academic institutions which have archive or special collection departments - was looking for a systems librarian. In addition, Web technology has evolved as the most required skill according to the advertisements, as well as inter-personal skills in a team environment.

• The Journal of the Korea Contents Association
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• v.12 no.3
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• pp.25-33
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• 2012

In this study, we analyzed the effects of game-based visual feedback training on postural balance control in young adults. We provided postural balance training for four weeks in fifth minute a day and three days a week using training system of postural balance based forceplate. We evaluated the ability of postural balance using balance SD(Biodex, medicalscience Inc., USA) for the validation of game contents based visual feedback training program. The results showed that postural stability and limits of stability were improved significantly before and after the training(p<0.05). Our study indicates that postural balance training of visual feedback based game could be adapted for improving postural balance. Also, for application of this game-based visual feedback training in older adults, we could develope of various game contents for disease types and conduct quantitative analysis and data collection of postural balance in the aged.

• Journal of Digital Convergence
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• v.19 no.9
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• pp.181-188
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• 2021

Research and importance of legal services applied with AI so that it can be easily understood and predictable in difficult legal fields is increasing. In this study, based on the decision of the Tax Tribunal in the field of tax law, a model was built through self-learning through information collection and data processing, and the prediction results were answered to the user's query and the accuracy was verified. The proposed model collects information on tax decisions and extracts useful data through web crawling, and generates word vectors by applying Word2Vec's Fast Text algorithm to the optimized output through NLP. 11,103 cases of information were collected and classified from 2017 to 2019, and verified with 70% accuracy. It can be useful in various legal systems and prior research to be more efficient application.

• The korean journal of orthodontics
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• v.52 no.4
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• pp.268-277
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• 2022

Objective: Poor experience with Invisalign treatment affects patient compliance and, thus, treatment outcome. Knowing the potential discomfort level in advance can help orthodontists better prepare the patient to overcome the difficult stage. This study aimed to construct artificial neural networks (ANNs) to predict patient experience in the early stages of Invisalign treatment. Methods: In total, 196 patients were enrolled. Data collection included questionnaires on pain, anxiety, and quality of life (QoL). A four-layer fully connected multilayer perception with three backpropagations was constructed to predict patient experience of the treatment. The input data comprised 17 clinical features. The partial derivative method was used to calculate the relative contributions of each input in the ANNs. Results: The predictive success rates for pain, anxiety, and QoL were 87.7%, 93.4%, and 92.4%, respectively. ANNs for predicting pain, anxiety, and QoL yielded areas under the curve of 0.963, 0.992, and 0.982, respectively. The number of teeth with lingual attachments was the most important factor affecting the outcome of negative experience, followed by the number of lingual buttons and upper incisors with attachments. Conclusions: The constructed ANNs in this preliminary study show good accuracy in predicting patient experience (i.e., pain, anxiety, and QoL) of Invisalign treatment. Artificial intelligence system developed for predicting patient comfort has potential for clinical application to enhance patient compliance.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.3
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• pp.175-186
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• 2019

Efforts have been made to introduce the climate smart agriculture (CSA) for adaptation to future climate conditions, which would require collection and management of site specific meteorological data. The objectives of this study were to identify requirements for construction of agricultural meteorology information service system (AMISS) using technologies that lead to the fourth industrial revolution, e.g., internet of things (IoT), artificial intelligence, and cloud computing. The IoT sensors that require low cost and low operating current would be useful to organize wireless sensor network (WSN) for collection and analysis of weather measurement data, which would help assessment of productivity for an agricultural ecosystem. It would be recommended to extend the spatial extent of the WSN to a rural community, which would benefit a greater number of farms. It is preferred to create the big data for agricultural meteorology in order to produce and evaluate the site specific data in rural areas. The digital climate map can be improved using artificial intelligence such as deep neural networks. Furthermore, cloud computing and fog computing would help reduce costs and enhance the user experience of the AMISS. In addition, it would be advantageous to combine environmental data and farm management data, e.g., price data for the produce of interest. It would also be needed to develop a mobile application whose user interface could meet the needs of stakeholders. These fourth industrial revolution technologies would facilitate the development of the AMISS and wide application of the CSA.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.107-120
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• 2014

This study proposes a novel recommender system using the structural hole analysis to reflect qualitative and emotional information in recommendation process. Although collaborative filtering (CF) is known as the most popular recommendation algorithm, it has some limitations including scalability and sparsity problems. The scalability problem arises when the volume of users and items become quite large. It means that CF cannot scale up due to large computation time for finding neighbors from the user-item matrix as the number of users and items increases in real-world e-commerce sites. Sparsity is a common problem of most recommender systems due to the fact that users generally evaluate only a small portion of the whole items. In addition, the cold-start problem is the special case of the sparsity problem when users or items newly added to the system with no ratings at all. When the user's preference evaluation data is sparse, two users or items are unlikely to have common ratings, and finally, CF will predict ratings using a very limited number of similar users. Moreover, it may produces biased recommendations because similarity weights may be estimated using only a small portion of rating data. In this study, we suggest a novel limitation of the conventional CF. The limitation is that CF does not consider qualitative and emotional information about users in the recommendation process because it only utilizes user's preference scores of the user-item matrix. To address this novel limitation, this study proposes cluster-indexing CF model with the structural hole analysis for recommendations. In general, the structural hole means a location which connects two separate actors without any redundant connections in the network. The actor who occupies the structural hole can easily access to non-redundant, various and fresh information. Therefore, the actor who occupies the structural hole may be a important person in the focal network and he or she may be the representative person in the focal subgroup in the network. Thus, his or her characteristics may represent the general characteristics of the users in the focal subgroup. In this sense, we can distinguish friends and strangers of the focal user utilizing the structural hole analysis. This study uses the structural hole analysis to select structural holes in subgroups as an initial seeds for a cluster analysis. First, we gather data about users' preference ratings for items and their social network information. For gathering research data, we develop a data collection system. Then, we perform structural hole analysis and find structural holes of social network. Next, we use these structural holes as cluster centroids for the clustering algorithm. Finally, this study makes recommendations using CF within user's cluster, and compare the recommendation performances of comparative models. For implementing experiments of the proposed model, we composite the experimental results from two experiments. The first experiment is the structural hole analysis. For the first one, this study employs a software package for the analysis of social network data - UCINET version 6. The second one is for performing modified clustering, and CF using the result of the cluster analysis. We develop an experimental system using VBA (Visual Basic for Application) of Microsoft Excel 2007 for the second one. This study designs to analyzing clustering based on a novel similarity measure - Pearson correlation between user preference rating vectors for the modified clustering experiment. In addition, this study uses 'all-but-one' approach for the CF experiment. In order to validate the effectiveness of our proposed model, we apply three comparative types of CF models to the same dataset. The experimental results show that the proposed model outperforms the other comparative models. In especial, the proposed model significantly performs better than two comparative modes with the cluster analysis from the statistical significance test. However, the difference between the proposed model and the naive model does not have statistical significance.