• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.3 no.1
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• pp.57-72
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• 2008

Serve and do so that graft together specialists' view application field of computer and developmental disability diagnosis estimation data to construct developmental disability diagnosis estimation system in this Paper and constructed developmental disability diagnosis estimation system. Developmental disability diagnosis estimation must supply information of specification area that specialists are having continuously. Developmental disability diagnosis estimation specialist system need multimedia data processing that is specialized little more for developmental disability classification diagnosis and decision-making and is atomized for this. Characteristic of developmental disability diagnosis estimation system that study in this paper can supply quick feedback about result, and can reduce mistake on recording and calculation as well as can shorten examination's enforcement time, and background of training is efficient system fairly in terms of nonprofessional who is not many can use easily. But, as well as when multimedia information that is essential data of system construction for developmental disability diagnosis estimation is having various kinds attribute and a person must achieve description about all developmental disability diagnosis estimation informations, great amount of work done is accompanied, technology about equal data can become different according to management. Because of these problems, applied search technology of contents base (Content-based) that search connection information by contents of edit target data for developmental disability diagnosis estimation data processing multimedia data processing technical development. In the meantime, typical access way for conversation style data processing to support fast image search, after draw special quality of data by N-dimension vector, store to database regarding this as value of N dimension and used data structure of Tree techniques to use index structure that search relevant data based on this costs. But, these are not coincided correctly in purpose of developmental disability diagnosis estimation because is developed focusing in application field that use data of low dimension such as original space DataBase or geography information system. Therefore, studied save structure and index mechanism of new way that support fast search to search bulky good physician data.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.5
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• pp.1087-1097
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• 2017

As the penetration rate of smartphones increases, the number of malicious codes targeting smartphones is increasing. I 360 Security 's smartphone malware statistics show that malicious code increased 437 percent in the first quarter of 2016 compared to the fourth quarter of 2015. In particular, malicious applications, which are the main means of distributing malicious code on smartphones, are aimed at leakage of user information, data destruction, and money withdrawal. Often, it is operated by an API, which is an interface that allows you to control the functions provided by the operating system or programming language. In this paper, we propose a mechanism to detect malicious application based on the similarity of API pattern in normal application and malicious application by learning pattern of API in application derived from static analysis. In addition, we show a technique for improving the detection rate and detection rate for each label derived by using the corresponding mechanism for the sample data. In particular, in the case of the proposed mechanism, it is possible to detect when the API pattern of the new malicious application is similar to the previously learned patterns at a certain level. Future researches of various features of the application and applying them to this mechanism are expected to be able to detect new malicious applications of anti-malware system.

• Korean Journal of Remote Sensing
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• v.14 no.4
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• pp.376-391
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• 1998

Images from satellites will have 1 to 3 meter ground resolution and will be very useful for analyzing current status of earth surface. An image processing system named GeoWatch with more intelligent image processing algorithms has been designed and implemented to support the detailed analysis of the land surface using high-resolution satellite imagery. The GeoWatch is a valuable tool for satellite image processing such as digitizing, geometric correction using ground control points, interactive enhancement, various transforms, arithmetic operations, calculating vegetation indices. It can be used for investigating various facts such as the change detection, land cover classification, capacity estimation of the industrial complex, urban information extraction, etc. using more intelligent analysis method with a variety of visual techniques. The strong points of this system are flexible algorithm-save-method for efficient handling of large size images (e.g. full scenes), automatic menu generation and powerful visual programming environment. Most of the existing image processing systems use general graphic user interfaces. In this paper we adopted visual program language for remotely sensed image processing for its powerful programmability and ease of use. This system is an integrated raster/vector analysis system and equipped with many useful functions such as vector overlay, flight simulation, 3D display, and object modeling techniques, etc. In addition to the modules for image and digital signal processing, the system provides many other utilities such as a toolbox and an interactive image editor. This paper also presents several cases of image analysis methods with AI (Artificial Intelligent) technique and design concept for visual programming environment.

• Korean Journal of Remote Sensing
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• v.15 no.2
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• pp.159-174
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• 1999

An important aspect of remote sensing research would be ultimately the production of research output so that operational people can directly use it. However, for the strip target, it is not certain how the research output in remote sensing helps the field user in adopting and utilizing the technology successfully. The relative limitation of traditional remote sensing systems for such a linear application is briefly discussed and the strength of videography are highlighted. Based on the postulated advantages of video as corridor sensor, a careful and extensive investigation has been made of research trends for airborne videography to identify how past research matches to demand of field clients. It is found that while video has been operationally used for strip target in field client communities, much research effort has been directed to area target, and relatively little towards the classification and monitoring of linear target. From this critical review, a very important step has been made concerning the practicality of airborne videography. The value of this paper is warranted in proposing a new concept of video strip monitoring(VSM) as future research direction in recognition of sensor characteristics and limitations. Ultimately, the suggestion in this paper will greatly contribute to opening new possibilities for implementing VSM, proposed as an initial aim of this paper.

• Review of Culture and Economy
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• v.21 no.2
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• pp.53-88
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• 2018

Among the cultural industries, the game industry is the most economically valuable industry. It has been about twenty years since the game policy has been implemented and the game laws have been enacted. If the law is a willing expression for the realization of the policy, the orientation of the game policy can be grasped through revision of the game laws. SOUND RECORDS, VIDEO PRODUCTS, AND GAME SOFTWARE ACT, established in 1999, and GAME INDUSTRY PROMOTION ACT, which was enacted in 2006, are regulated by many revisions. In this paper, I try to understand the direction and meaning of Korean game policy(classification, game dysfunction, gambling, industry growth) through the contents of the revision of the game law for 20 years. The game policy shown through the amendment of the game law is intended to protect the game by regulating the game, and to protect the game user by preventing the gambling and preventing the game dysfunction, and to increase autonomy of users and choice of producers by switching to self rating system, and based on this, an environment for continuous industrial growth is created. In the future, game policies should consider cooperation with social areas beyond game-specific areas. On the other hand, it needs to respond to new agendas such as polarization of industrial structure, fair environment, employment environment.

• 한국노년학
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• v.38 no.4
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• pp.871-889
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• 2018

This study aims to explore social participation needs among the elderly in Korea from the perspective of the elderly participant's. 40 Q-samples are drawn from the Q-population including attitudes and needs toward social participation in later life based on news articles, essays, research, documentary, and television shows. 35 subjects are analysed by the QUANL program and the types of social participation needs are divided into four patterns which accounted for 60.16% of the total variance. The elderly's portrayal of an ideal social participation is about making independent decisions and being able to actively participate in the activities they chose to do. However, their most undesirable scenario would be being confused and uncertain of what they should do the remainder of their lives. The needs of social participation among the elderly varies on four indicators such as ego, social capital, life satisfaction, life vitality and these four indicators have two sub-categories with a total of 8 types of classification. These 8 types differ by priorities, adaptation to life changes, motivation to social participation, and desired activity. Findings suggest that researchers and policy makers need to consider service user perspective on social participation in later life, not service provider perspective.

• Journal of Korean Neurosurgical Society
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• v.62 no.4
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• pp.442-449
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• 2019

Objective : Bone mineral density (BMD) is an important consideration during fusion surgery. Although dual X-ray absorptiometry is considered as the gold standard for assessing BMD, quantitative computed tomography (QCT) provides more accurate data in spine osteoporosis. However, QCT has the disadvantage of additional radiation hazard and cost. The present study was to demonstrate the utility of artificial intelligence and machine learning algorithm for assessing osteoporosis using Hounsfield units (HU) of preoperative lumbar CT coupling with data of QCT. Methods : We reviewed 70 patients undergoing both QCT and conventional lumbar CT for spine surgery. The T-scores of 198 lumbar vertebra was assessed in QCT and the HU of vertebral body at the same level were measured in conventional CT by the picture archiving and communication system (PACS) system. A multiple regression algorithm was applied to predict the T-score using three independent variables (age, sex, and HU of vertebral body on conventional CT) coupling with T-score of QCT. Next, a logistic regression algorithm was applied to predict osteoporotic or non-osteoporotic vertebra. The Tensor flow and Python were used as the machine learning tools. The Tensor flow user interface developed in our institute was used for easy code generation. Results : The predictive model with multiple regression algorithm estimated similar T-scores with data of QCT. HU demonstrates the similar results as QCT without the discordance in only one non-osteoporotic vertebra that indicated osteoporosis. From the training set, the predictive model classified the lumbar vertebra into two groups (osteoporotic vs. non-osteoporotic spine) with 88.0% accuracy. In a test set of 40 vertebrae, classification accuracy was 92.5% when the learning rate was 0.0001 (precision, 0.939; recall, 0.969; F1 score, 0.954; area under the curve, 0.900). Conclusion : This study is a simple machine learning model applicable in the spine research field. The machine learning model can predict the T-score and osteoporotic vertebrae solely by measuring the HU of conventional CT, and this would help spine surgeons not to under-estimate the osteoporotic spine preoperatively. If applied to a bigger data set, we believe the predictive accuracy of our model will further increase. We propose that machine learning is an important modality of the medical research field.

• Journal of Digital Convergence
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• v.19 no.8
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• pp.235-240
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• 2021

Currently, the number of visitors to Oreum is increasing and the trend of tourism is changing rapidly. The motivation for visiting Oreum is also changing from relaxation and pleasure to experiences. In line with this change, people visit the mountain by selecting motivation such as marriage and family photos, not just exercise. However, it is difficult to search for an Oreum that matches the tourists' motivation. In order to solve these problems, we proposed a system that provides the association between Oreum and concept based on the number of search results from web search engines in real time. User can select the desired date to check the associations for past or selected periods and concepts. Through this research, visitors to Oreum, Jeju's natural heritage, can contribute to the development of tourism in Jeju. In the future, the concept of visiting beaches or seas, not just Jeju Oreum, can be provided. In this work, search results from websites are collected, stored in a database, and search results of Oreum and concept are provided on the homepage to classify Oreum trends.

• Journal of Convergence for Information Technology
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• v.11 no.6
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• pp.33-39
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• 2021

Speech recognition technology is being combined with deep learning and is developing at a rapid pace. In particular, voice recognition services are connected to various devices such as artificial intelligence speakers, vehicle voice recognition, and smartphones, and voice recognition technology is being used in various places, not in specific areas of the industry. In this situation, research to meet high expectations for the technology is also being actively conducted. Among them, in the field of natural language processing (NLP), there is a need for research in the field of removing ambient noise or unnecessary voice signals that have a great influence on the speech recognition recognition rate. Many domestic and foreign companies are already using the latest AI technology for such research. Among them, research using a convolutional neural network algorithm (CNN) is being actively conducted. The purpose of this study is to determine the non-voice section from the user's speech section through the convolutional neural network. It collects the voice files (wav) of 5 speakers to generate learning data, and utilizes the convolutional neural network to determine the speech section and the non-voice section. A classification model for discriminating speech sections was created. Afterwards, an experiment was conducted to detect the non-speech section through the generated model, and as a result, an accuracy of 94% was obtained.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.34 no.5
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• pp.144-155
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• 2022

The Korea Coast Guard evaluates the risk of major coastal activity places to prevent coastal accidents, and patrols and manages them based on that, but it is not responding properly to the continuously increasing number of coastal accidents. The reason for this is that, despite the gradual expansion of coastal activity places, there is a lack of manpower to manage and supervise them, resulting in blind spots in coastal accident safety management. Therefore, in order to solve this problem, it is necessary to prepare more efficient and effective measures that check and supplement the current coastal safety management system. Coastal accidents show different characteristics of accident causes and places due to differences in the activity characteristics of users according to time. As a result of analyzing coastal accident data (2017~2021), the frequency of daytime accidents is high in the case of sea rock, beach, and offshore, where family leisure activities are frequent. In the case of wharf, tidal flat and bridge, where accidents due to drinking, disorientation, and suicide mainly occur, the frequency of accidents at night is high. In addition, there were more accidents on weekends when the number of users increased compared to weekdays. This trend indicates that the user's temporal activity characteristics must be reflected in the risk assessment of coastal activity places. Therefore, in this study, based on the case of coastal accidents, the characteristics of accidents at coastal activity places according to time were identified, and the criteria were presented for risk evaluation by grading them. It is expected that it will be possible to lay the foundation for reducing coastal accidents by efficiently managing and supervising coastal activity places over time using the presented evaluation criteria.