• Archives of design research
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• v.18 no.2 s.60
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• pp.79-90
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• 2005

The aim of this study was to investigate how the psychological factors of human interrelation or human socialization are associated with the visual design based on sociological and psychological theories. To accomplish this goal, human socialization was examined on the basis of physiology, philosophy, and psychology. Then a case study was employed to assess how they function in the area of visual design. In literature, the sources of psychological factors of human socialization were categorized into 11 items including the sexual hedonic pursuit. These items were used for the evaluation of 40 printed media advertisements, all of which were the winners of the Korea Advertising Awards from 1994 to 2003. As a result, it was revealed that most advertisements responded to the items of adaptive value and cultural imprinting as biological bases. Also, it was discovered that the existential foundation of advertising has been based on mutual distrust and the payoff matrix as a mind of social unrest. In conclusions, it was illustrated that future advertising will remain based on adaptive value, cultural imprinting, social learning, and imitation learning, as long as advertising continue to hold its reason for existence.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.7
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• pp.655-661
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• 2017

It is a very important task to extract character regions contained in various input color images, because characters can provide significant information representing the content of an image. In this paper, we propose a new method for extracting character regions from various input images using MCT features and an AdaBoost algorithm. Using geometric features, the method extracts actual character regions by filtering out non-character regions from among candidate regions. Experimental results show that the suggested algorithm accurately extracts character regions from input images. We expect the suggested algorithm will be useful in multimedia and image processing-related applications, such as store signboard detection and car license plate recognition.

• Journal of Korean Library and Information Science Society
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• v.8
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• pp.155-184
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• 1981

The publication of the result of scholarly research is an integral part of the process by which learning is advanced. The university presses, as one of the major scholarly publishers are now confronted with many critical problems, such as the declining unit sales, the explosion of manuscripts, the challenge of new publishing technologies, etc., in performing the role of the scholarly communication system. The purpose of this study is to identify the problems imposed on the university presses and alternative strategies for them. For the study, the related literature to the subject were read, analyzed and synthesized, from which the overall prospect of the problems and alternative strategies are derived. The conclusion of the study can be summarized as follows: (1) The faith of the university should lie in its role to advance scholarly learning through production and dissemination of high-quality knowledge, and the university press should materialize such a faith. (2) The scholarly books, though not the best media of scholarly communication taking a side view of its timeliness and brevity, can perform the function of the best media for the specific subject and readers. (3) The scholarly books as national resource must be published for the scholars demanding them even though the publication can't help depending on the subsidiary fund. (4) For the survival and activation of the university presses, the following strategies should be examined, and put in force if necessary. (a) The role of the foundation su n.0, pporting the university presses should be expanded (b) The Co-operative system among the operations of the presses should be established. (c) It is desirable that the university without the press should participate in the university with the press for both the financial su n.0, pporting and the publicizing its faculty's manuscripts. (d) The positive efforts should be made for the increase of sales copies by implementing the dual-system of publication. (e) It is desirable that 'recording system' should be incorporated in the traditional publication system both for the lightening of financial problems and the explosion of publications. (f) It is necessary that the effective methods of the bibliographical control should be developed for the improvement of the scholarly communication. (g) Any kind of the permanent organization composed of the representatives from all the infrastructures of information industry should be established to study the character and direction of technological changes and to discern the better choice of specific, technologies in the scholarly communication system.

• International Journal of Advanced Culture Technology
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• v.8 no.3
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• pp.61-72
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• 2020

The fear of crime, discussed in the early 1960s in the United States, is a psychological response, such as anxiety or concern about crime, the potential victim of a crime. These anxiety factors lead to the burden of the individual in securing the psychological stability and indirect costs of the crime against the society. Fear of crime is not a good thing, and it is a part that needs to be adjusted so that it cannot be exaggerated and distorted by the policy together with the crime coping and resolution. This is because fear of crime has as much harm as damage caused by criminal act. Eric Pawson has argued that the popular impression of violent crime is not formed because of media reports, but by official statistics. Therefore, the police should watch and analyze news related to fear of crime to reduce the social cost of fear of crime and prepare a preemptive response policy before the people have 'fear of crime'. In this paper, we propose a deep - based news classification system that helps police cope with crimes related to crimes reported in the media efficiently and quickly and precisely. The goal is to establish a system that can quickly identify changes in security issues that are rapidly increasing by categorizing news related to crime among news articles. To construct the system, crime data was learned so that news could be classified according to the type of crime. Deep learning was applied by using Google tensor flow. In the future, it is necessary to continue research on the importance of keyword according to early detection of issues that are rapidly increasing by crime type and the power of the press, and it is also necessary to constantly supplement crime related corpus.

• Journal of The Korean Association For Science Education
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• v.25 no.3
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• pp.353-363
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• 2005

In this thesis, the cognition of students gifted in science on pseudo science was studied in order to acquire basic data to develop a learning program. As a first step, the difference of cognition on pseudo science between science-gifted students and general students in elementary, middle and high schools was studied. Findings revealed that science-gifted students had more negative thought on pseudo science than general students. In addition, there was no progress in their cognition on pseudo science as entered higher grades. Secondly, the cognition of students in a science high school, three times over a 6-month period, was studied. Through this study, it was found that student concepts of pseudo science was not firm, and it is quite possible to induce students to think logically and rationally with the help of a well-organized learning program. Lastly, the factors that might affect student ideas on pseudo science were researched. Students were affected by media such as television and books and also by personal experience. Therefore, students should be trained to correctly judge information presented in the media as authentic or false. Moreover, they should also be provided chances to look back on positive astrological experiences.

• Smart Media Journal
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• v.5 no.4
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• pp.75-82
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• 2016

Although Korea's economic and domestic automobile market through the change of road environment are growth, the traffic accident rate has also increased, and the casualties is at a serious level. For this reason, the government is establishing and promoting policies to open traffic accident data and solve problems. In this paper, describe the method of predicting traffic accidents by eliminating the class imbalance using the traffic accident data and constructing the Hybrid Model. Using the original traffic accident data and the sampled data as learning data which use FP-Growth algorithm it learn patterns associated with traffic accident injury severity. Accordingly, In this paper purpose a method for predicting the severity of a victim of a traffic accident by analyzing the association patterns of two learning data, we can extract the same related patterns, when a decision tree and multinomial logistic regression analysis are performed, a hybrid model is constructed by assigning weights to related attributes.

• Smart Media Journal
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• v.9 no.3
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• pp.46-51
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• 2020

Pine wilt disease is one of the reasons that results in huge damage on pine trees in east Asia including Korea, Japan, and China, and early finding and removing the diseased trees is an efficient way to prevent the forest from wide spreading. This paper proposes a searching method of the damaged pine trees from wilt disease in ortho-images corrected from RGB images, which are captured by unmanned aviation vehicles. The proposed method constructs patch-based classifier using ResNet18 backbone network, classifies the RGB ortho-image patches, and make the results as a heat map. The heat map can be used to find the distribution of diseased pine trees, to show the trend of spreading disease, and to extract the RGB distribution of the diseased areas in the image. The classifier in the work shows 94.7% of accuracy.

• Smart Media Journal
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• v.9 no.3
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• pp.90-97
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• 2020

With the development of the Internet and smartphones, digital sound sources are easily accessible, and accordingly, interest in music search and recommendation is increasing. As a method of recommending music, research using melodies such as pitch, tempo, and beat to classify genres or emotions is being conducted. However, since lyrics are becoming one of the means of expressing human emotions in music, the role of the lyrics is increasing, so a study of emotion classification based on lyrics is needed. Therefore, in this thesis, we analyze the emotions of the farewell lyrics in order to subdivide the farewell emotions based on the lyrics. After constructing an emotion dictionary by vectoriziong the similarity between words appearing in the parting lyrics through Word2Vec learning, we propose a method of classifying parting lyrics emotions using Word2Vec and LSTM, which classify lyrics by similar emotions by learning lyrics using LSTM.

• Smart Media Journal
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• v.7 no.1
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• pp.31-36
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• 2018

In this paper, we propose automatic screen on / off method of OST-HMD screen using gaze depth estimation technique. The proposed method uses MLP (Multi-layer Perceptron) to learn the user's gaze information and the corresponding distance of the object, and inputs the gaze information to estimate the distance. In the learning phase, eye-related features obtained using a wearable eye-tracker. These features are then entered into the Multi-layer Perceptron (MLP) for learning and model generation. In the inference step, eye - related features obtained from the eye tracker in real time input to the MLP to obtain the estimated depth value. Finally, we use the results of this calculation to determine whether to turn the display of the HMD on or off. A prototype was implemented and experiments were conducted to evaluate the feasibility of the proposed method.

• Smart Media Journal
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• v.9 no.1
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• pp.16-22
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• 2020

In this study, a neural network method performing both Detection and Classification of diseases and insects in paprika is proposed with Multi-Tasking U-net. Paprika on farms does not have a wide variety of diseases in this study, only two classes such as powdery mildew and mite, which occur relatively frequently are made as the targets. Aiming to this, a U-net is used as a backbone network, and the last layers of the encoder and the decoder of the U-net are utilized for classification and segmentation, respectively. As the result, the encoder of the U-net is shared for both of detection and classification. The training data are composed of 680 normal leaves, 450 mite-damaged leaves, and 370 powdery mildews. The test data are 130 normal leaves, 100 mite-damaged leaves, and 90 powdery mildews. Its test results shows 89% of recognition accuracy.