• The Journal of the Korea Contents Association
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• v.9 no.8
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• pp.57-63
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• 2009

Object recognition technologies using PCA(principal component analysis) recognize objects by deciding representative features of objects in the model image, extracting feature vectors from objects in a image and measuring the distance between them and object representation. Given frequent recognition problems associated with the use of point-to-point distance approach, this study adopted the k-nearest neighbor technique(class-to-class) in which a group of object models of the same class is used as recognition unit for the images in-putted on a continual input image. However, the robustness of recognition strategies using PCA depends on several factors, including illumination. When scene constancy is not secured due to varying illumination conditions, the learning performance the feature detector can be compromised, undermining the recognition quality. This paper proposes a new PCA recognition in which database of objects can be detected under different illuminations between input images and the model images.

• Journal of Korea Multimedia Society
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• v.4 no.4
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• pp.297-305
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• 2001

Recently advances in high-speed networks and multimedia computer technologies allow new types of multimedia applications to manipulate large volumes of multimedia data. However, in the real time and/or the heterogeneous data transmissions, there are many difficulties such as network transmission delay, the implementation difficulties, and so on. To solve these problems, in this paper, we extend the method of the multimedia service design which is proposed by OMG. To do this, we suggest an efficient real time audio/video stream framework, called Smart Explorer, based un CORBA and JMF Java Media API. And we separate the transmission path of control data from that of media data and use RTP/RTCP protocol for efficient real time audio/video transmission. Also we show the appropriate implementation of the audio/video stream system based on our suggested framework Smart Explorer. In the future, we expect our audio/video stream system to be applied to the real time communication software such as broadcasting, distance learning, and video conferencing.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.332-335
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• 2018

In recent years, artificial intelligence using big data has become a big issue in IT. Various studies are being conducted on services or technologies to effectively handle big data. The educational field, there is big data about students, but it is only a simple process to collect, lookup and store such data. In the future, it makes extensive use of artificial intelligence, machine learning, and statistical analysis to find meaningful rules, patterns, and relationships in the big data of the educational field, and to produce intelligent and useful data for the actual students. Accordingly, this study aims to design a program to predict the career of students using a decision tree algorithm based on the data from the student's classroom observations. Through a career prediction program, it is believed to be helpful to present application paths to students ' counseling and to also provide classroom behavior and direction based on the desired courses.

• Journal of Korean Society of Transportation
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• v.18 no.4
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• pp.75-85
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• 2000

The Purpose of this study is to analyze wether the composition of training sample have a relation with the Predictive ability and the learning results of ANNs(Artificial Neural Networks) fur predicting one cycle ahead of the queue length(veh.) in a signalized intersection. In this study, ANNs\` training sample is classified into the assumption of two cases. The first is to utilize time-series(Per cycle) data of queue length which would be detected by one detector (loop or video) The second is to use time-space correlated data(such as: a upstream feed-in flow, a link travel time, a approach maximum stationary queue length, a departure volume) which would be detected by a integrative vehicle detection systems (loop detector, video detector, RFIDs) which would be installed between the upstream node(intersection) and downstream node. The major findings from this paper is In Daechi Intersection(GangNamGu, Seoul), in the case of ANNs\` training sample constructed by time-space correlated data between the upstream node(intersection) and downstream node, the pattern recognition ability of an interrupted traffic flow is better.

• Journal of The Korean Association of Information Education
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• v.21 no.5
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• pp.567-581
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• 2017

The purpose of this study is to analyze the facilitating and conflicting factors on the emerging technologies and trends predicted to impact future education in Korea. To do this, open online questionnaires on 20 emerging technologies and trends derived from a comprehensive literature review were completed by 24 experts in research, policy, schools, and corporate fields, and a content analysis of the collected qualitative data was conducted. As a result of the study, the effectiveness of the content and the maturity of technology were found to be the most important facilitating factors and obstacles. In addition, the potential for innovative teaching and learning methods and motivation, and the maturity and popularity of technology were found to be the main facilitating factors. On the other hand, health problems and negative effects on students in ethical aspects, the lack of research and development, and poor networks and infrastructures in terms of education environment were found to be the main impeding factors of emerging technologies and trends.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.4 no.1
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• pp.27-38
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• 1993

Pervasive developmental disorder is one of the most severe clinical disorder in child psychiatry and is associated with deviancies in multiple areas of development. Medication does not cure pervasive developmental disorder and its effectiveness is generally nonspecific. But psychopharmacological treatment can be important for some children with pervasive developmental disorder and can make many young autistics more amenable to behavior modification and education. Haloperidol, the most widely studied antipsychotics, was statistically and clinically superior to placebo, and furthermore, was known to facilitate the positive functioning such as, discrimination learning and imitative communication, without side effects. However, administration of haloperidol is associated with drug related dyskinesia, and it warrants the introduction and use of the other novel drugs. Several biochemical studies suggest that subgroups of children with pervasive developmental disorder show hyperserotonemia and increased endogenous opioid level as compared with controls. Psychopharmacological trials were conducted according to these findings(ex : fenfluramine, naltrexone), with mixed results till now. These and another drugs that have been used in children with pervasive developmental disorder and their effectiveness are reviewed.

• Journal of the East Asian Society of Dietary Life
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• v.20 no.1
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• pp.1-10
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• 2010

This was conducted to investigate the dietary assessment, food preferences, snack intake, priority order in food purchase, and knowledge of diet of full-time housewives and working housewives through the use of a questionnaire. The participants (127 working housewives and 86 housewives) were selected at random from Seoul and its vicinity. The predominant job reported by working housewives was saleswomen and specialized job (20.7%). The average monthly income of both housewives and working housewives ranged from 3,000,000 to 5,000,000 won. Forty percent of housewives consumed more meat, fish, eggs, beans, and tofu, while 50.0% of housewives ate vegetables other than kimchi at every meal, 51.2% of housewives consumed one serving of fruit and one cup of fruit juice, 45.3% of housewives consumed three regular meals, and 60.5% of housewives consumed a balanced diet when compared with working housewives (p<0.05). Working housewives consumed beverages, ice cream, milk, and dairy products, while housewives consumed breads, sweet potato, potato, and fruit as snacks. The preference that most often led to food selection was flavor among working housewives (67.7%) and housewives (64.0%). Both working housewives and housewives always confirmed the day of food production. Generally, housewives were more interested in learning about food, creating a dietary plan, nutrient loss during cooking and reducing waste food when compared with working housewives. Housewives appeared to have better dietary assessment and knowledge than working housewives. Accordingly, it is advisable to prepare more systemic education programs for working housewives.

• Journal of Digital Contents Society
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• v.18 no.7
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• pp.1419-1425
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• 2017

The ultimate goal of legal knowledge search is to obtain optimal legal information based on laws and precedent. Text mining research is actively being undertaken to meet the needs of efficient retrieval from large scale data. A typical method is to use a word embedding algorithm based on Neural Net. This paper demonstrates how to search relevant information, applying Korean law information to word embedding. First, we extracts reference laws from precedents in order and takes reference laws as input of Law2Vec. The model learns a law by predicting its surrounding context law. The algorithm then moves over each law in the corpus and repeats the training step. After the training finished, we could infer the relationship between the laws via the embedding method. The search performance was evaluated based on precision and the recall rate which are computed from how closely the results are associated to the search terms. The test result proved that what this paper proposes is much more useful compared to existing systems utilizing only keyword search when it comes to extracting related laws.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.4
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• pp.399-407
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• 2002

In this paper, a novel algorithm is proposed to reduce the blocking artifacts of block-based coded images by using block classification and MLP. In the proposed algorithm, we classify the block into four classes based on a characteristic of DCT coefficients. And then, according to the class information of neighborhood block, adaptive neural network filter is performed in horizontal and vertical block boundary. That is, for smooth region, horizontal edge region, vertical edge region, and complex region, we use a different two-layer neural network filter to remove blocking artifacts. Experimental results show that the proposed algorithm gives better results than the conventional algorithms both subjectively and objectively.

• The Journal of Korean Association of Computer Education
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• v.17 no.4
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• pp.59-67
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• 2014

With the development of SNS, many different areas including education are utilizing SNS in various ways. And there are more and more learners and teachers who intend to use it for learning. Lately, however, the students using SNS environment hardly consider the issues regarding copyright, so this is raising even legal issues, too. Therefore, this study has examined the degree of recognition of undergraduates on copyright and extracted the general cases of copyright which undergraduates may face in the actual class or everyday life. The cases extracted are expressed in the rules of "If ~ Then", stored in the knowledge base of rules in the rule-based system, and realized as the mobile web. And regarding the copyright-related problems inputted by the students, similar rules are drawn from the knowledge base of rules so that they can solve copyright-related problems anytime, anywhere with the mobile web in a self-directed way.