• Journal of Information Processing Systems
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• v.19 no.3
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• pp.289-301
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• 2023

Due to the development and dissemination of modern technology, anyone can easily communicate using services such as social network service (SNS) through a personal computer (PC) or smartphone. The development of these technologies has caused many beneficial effects. At the same time, bad effects also occurred, one of which was the spam problem. Spam refers to unwanted or rejected information received by unspecified users. The continuous exposure of such information to service users creates inconvenience in the user's use of the service, and if filtering is not performed correctly, the quality of service deteriorates. Recently, spammers are creating more malicious spam by distorting the image of spam text so that optical character recognition (OCR)-based spam filters cannot easily detect it. Fortunately, the level of transformation of image spam circulated on social media is not serious yet. However, in the mail system, spammers (the person who sends spam) showed various modifications to the spam image for neutralizing OCR, and therefore, the same situation can happen with spam images on social media. Spammers have been shown to interfere with OCR reading through geometric transformations such as image distortion, noise addition, and blurring. Various techniques have been studied to filter image spam, but at the same time, methods of interfering with image spam identification using obfuscated images are also continuously developing. In this paper, we propose a deep learning-based spam image detection model to improve the existing OCR-based spam image detection performance and compensate for vulnerabilities. The proposed model extracts text features and image features from the image using four sub-models. First, the OCR-based text model extracts the text-related features, whether the image contains spam words, and the word embedding vector from the input image. Then, the convolution neural network-based image model extracts image obfuscation and image feature vectors from the input image. The extracted feature is determined whether it is a spam image by the final spam image classifier. As a result of evaluating the F1-score of the proposed model, the performance was about 14 points higher than the OCR-based spam image detection performance.

• Journal of the Korea Society of Computer and Information
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• v.10 no.6 s.38
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• pp.239-252
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• 2005

Ubiquitous Sensor Network(USN) , the core technology for the Ubiquitous environments ,must be operated in the restrictive battery capacity and computing. From this cause, USN needs the lightweight design for low electric energy and the minimum computing. The previous mutual authentication. based on J$\emptyset$sang's trust model, in USN has a character that makes the lightweight mutual authentication possible in conformity with minimum computing. But, it has an imperfection at the components of representing the trust from a lightweight point of view. In this paper, we improve on the J$\emptyset$sang's trust model to apply a lightweight mutual authentication in USN. The proposed trust model in USN defines the trust information with the only degree of trust-entity(x)'s belief. The defined trust information has a superiority over the J$\emptyset$sang's trust model from a computing Point of view. because it computes information by Probability and logic operation(AND).

• Journal of the Ergonomics Society of Korea
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• v.31 no.1
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• pp.49-61
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• 2012

Objective: The aim of this study is to offer a holism based Service Experience Analysis System(HSEAS) for service design. Background: Customer experience has been focused in a lot of service area. But it is difficult to understand the customer's needs and their experiences because it's so complex and uncertain. Thus it needs holistic approach that means it's difficult to explain general character merely through the understanding of small parts that composes an object and it must be analyzed within the overall context. Method: Accordingly, the thesis paper proposes the Service Experience Analysis System that satisfies the four following needs. (1) Need of solid Experience Framework in which the special quality of the service experience is considered, (2) need of support for the semantic cohesion between different kinds of data, (3) need of support for the management and search of vast data, and (4) need of building the knowledge base system for collaborative research. Results: HSEAS combines the short information in the customers' words and behaviors or situations and circumstances and provides a place of analysis where the context of the general experience can be read and allows concrete understanding of the actual state and factor of the problem as a Combined Data Analysis Tool. Conclusion: HSEAS becomes the center of information management, analysis and connection and it provides a free collaboration place where physical condition has no relations to as a knowledge base system based on network. Application: It is expected that length and width will be added to the analysis and assistance for effectively accumulating information will be provided in the area of diverse service.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.12
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• pp.51-57
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• 1999

In this paper, an adaptive thresholding of the nonuniformly contrasted images is proposed through using the contrast pre-enhancement of the local regions and the bilinear interpolation between the local threshold values. The nonuniformly contrasted image is decomposed into 9${\times}$9 sized local regions, and the contrast is enhanced by intensifying the gray level difference of each low contrasted or blurred region. Optimal threshold values are obtained by iterative method from the gray level distribution of each contrast-enhanced local region. Discontinuities are reduced at the region of interest or at the characters by using bilinear interpolation between the neighboring threshold surfaces. Character recognition experiments are conducted using backpropagation neural network on the characters extracted from the nonuniformly contrasted document, PCB, and wafer images binarized through using the proposed thresholding and the conventional thresholding methods, and the results prove the relative effectiveness of the proposed scheme.

• Journal of the Korean Institute of Landscape Architecture
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• v.48 no.6
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• pp.16-24
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• 2020

The purpose of this study is to analyze the usage behavior of Seoullo 7017, the first public garden in Korea, to understand the usage status by analyzing blogs, and to present usage behavior and improvement plans for Seoullo 7017. From June 2017 to May 2020, after Seoullo 7017 was open to citizens, character data containing 'Seoullo 7017' in the title and contents of NAVER and·DAUM blogs were converted to text mining and socialization, a Big Data technique. The analysis was conducted using social network analysis. The summary of the research results is as follows. First of all, the ratio of men and women searching for Seoullo 7017 online is similar, and the regions that searched most are in the order of Seoul and Gyeonggi, and those in their 40s and 50s were the most interested. In other words, it can be seen that there is a lack of interest in regions other than Seoul and Gyeonggi and among those in their 10s, 20s, and 30s. The main behaviors of Seoullo 7017 are' night view' and 'walking', and the factors that affect culture and art are elements related to culture and art. If various programs and festivals are opened and actively promoted, the main behavior will be more varied. On the other hand, the main behavior that the users of Seoullo 7017 want is 'sit', which is a static behavior, but the physical conditions are not sufficient for the behavior to occur. Therefore, facilities that can cause sitting behavior, such as shades and benches must be improved to meet the needs of visitors. The peculiarity of the change in the behavior of Seoullo 7017 is that it is recognized as a good place to travel alone and a good place to walk alone as a public multi-use facility and group activities are restricted due to COVID-19. Accordingly, in a situation like the COVD-19 pandemic, more diverse behaviors can be derived in facilities where people can take a walk, etc., and the increase of various attractions and the satisfaction of users can be increased. Seoullo 7017, as Korea's first public pedestrian area, was created for urban regeneration and the efficient use of urban resources in areas beyond the meaning of public spaces and is a place with various values such as history, nature, welfare, culture, and tourism. However, as a result of the use behavior analysis, various behaviors did not occur in Seoullo 7017 as expected, and elements that hinder those major behaviors were derived. Based on these research results, it is necessary to understand the usage behavior of Seoullo 7017 and to establish a plan for spatial system and facility improvement, so that Seoullo 7017 can be an important place for urban residents and a driving force to revitalize the city.

• The Korean Journal of Coaching Psychology
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• v.6 no.2
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• pp.93-114
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• 2022

The purpose of this study is to investigate whether there was a difference between men and women in conceptualizing a calling in childrearing through social network analysis. The results are as follows. IAs a result of the study, it was found that mothers showed significantly larger networks and higher density than fathers did, indicating that mothers, more than fathers do, experience parenting and child-rearing based more on a concept of calling in childrearing. Parents directly linked responsibility, children's growth, direction, commitment, and parental character to a calling in childrearing. In addition, mothers also linked a sense of identity and parental growth to it. In the case of fathers, only four concepts were directly connected with a calling in childrearing. This shows that mothers, in comparison to fathers, connect essential self-concepts, such as identity as a parent and themes of growth, to a calling in childrearing. In centrality, similar concepts also were evaluated as important. The common parental closeness centrality is composed of responsibility, child growth, direction, and belief starting from the center. In the case of fathers, child growth, responsibility, and belief were evaluated in order, and in the case of mothers, responsibility, parental growth, and identity were evaluated as relatively important concepts.

• Proceedings of the KWS Conference
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• 2002.10a
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• pp.250-254
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• 2002

Intergranular corrosion of austenitic stainless steels is a conventional and momentous problem during welding and high temperature use. One of the major reasons for such intergranular corrosion is so-called sensitization, i.e., chromium depletion due to chromium carbide precipitation at grain boundaries. Conventional methods for preventing sensitization of austenitic stainless steels include reduction of carbon content in the material, stabilization of carbon atoms as non-chromium carbides by the addition of titanium, niobium or zirconium, local solution-heat-treatment by laser beam, etc. These methods, however, are not without drawbacks. Recent grain boundary structure studies have demonstrated that grain boundary phenomena strongly depend on the crystallographic nature and atomic structure of the grain boundary, and that grain boundaries with coincidence site lattices are immune to intergranular corrosion. The concept of "grain boundary design and control", which involves a desirable grain boundary character distribution, has been developed as grain boundary engineering. The feasibility of grain boundary engineering has been demonstrated mainly by thermomechanical treatments. In the present study, a thermomechanical treatment was tried to improve the resistance to the sensitization by grain boundary engineering. A type 304 austenitic stainless steel was pre-strained and heat-treated, and then sensitized, varying the parameters (pre-strain, temperature, time, etc.) during the thermomechanical treatment. The grain boundary character distribution was examined by orientation imaging microscopy. The intergranular corrosion resistance was evaluated by electrochemical potentiokinetic reactivation and ferric sulfate-sulfuric acid tests. The sensitivity to intergranular corrosion was reduced by the thermomechanical treatment and indicated a minimum at a small roll-reduction. The frequency of coincidence-site-lattice boundaries indicated a maximum at a small strain. The ferric sulfate-sulfuric acid test showed much smaller corrosion rate in the thermomechanically-treated specimen than in the base material. An excellent intergranular corrosion resistance was obtained by a small strain annealing at a relatively low temperature for long time. The optimum parameters created a uniform distribution of a high frequency of coincidence site lattice boundaries in the specimen where corrosive random boundaries were isolated. The results suggest that the thermomechanical treatment can introduce low energy segments in the grain boundary network by annealing twins and can arrest the percolation of intergranular corrosion from the surface.

• The Journal of the Korea Contents Association
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• v.6 no.9
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• pp.98-107
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• 2006

By improving performance of mobile machine(3D engine, 3D accelerator chip set, etc) and developing wireless network technology, a demand for actual contents of users is being increased rapidly. But, there are some difficulties yet for the speedy development of actual contents because of the limitation of development resources that is dependent on each mobile device's different performance. In general, much of the animated character-creation work for mobile environment is still done manually by experienced animator with the method of key frame processing. However, it needs a lot of time and more costs for creating motion. Additionally, it is possible to cause a distortion of motion. In this paper, I solved the difficulties by using a optical motion capture system, it was able to acquire accurate motion data more easily and quickly, and then it was possible to make 3D dance contents efficiently. Also, I showed techniques of key reduction and controlling frame number for using huge amounts of motion capture data in mobile environment which requires less resources. In making 3D dance contents, using an optical motion capture system was verified that it was more efficient to make and use actual-reality contents by creating actual character motion and by decreasing processing time than existing method.

• Journal of the Korean Data and Information Science Society
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• v.8 no.2
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• pp.163-171
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• 1997

Function approximation from a set of input-output pairs has numerous applications in scientific and engineering areas. Multilayer feedforward neural networks have been proposed as a good approximator of nonlinear function. The back propagation(BP) algorithm allows multilayer feedforward neural networks to learn input-output mappings from training samples. It iteratively adjusts the network parameters(weights) to minimize the sum of squared approximation errors using a gradient descent technique. However, the mapping acquired through the BP algorithm may be corrupt when errorneous training data we employed. When errorneous traning data are employed, the learned mapping can oscillate badly between data points. In this paper we propose a robust BP learning algorithm that is resistant to the errorneous data and is capable of rejecting gross errors during the approximation process, that is stable under small noise perturbation and robust against gross errors.

• Journal of the HCI Society of Korea
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• v.13 no.3
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• pp.65-73
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• 2018

Game balance settings are crucial to game design. Game balancing must take into account a large amount of numerical values, configuration data, and the relationship between elements. Once released and served, a game - even for a balanced game - often requires calibration according to the game player's preference. To achieve sustainability, game balance needs adjustment while allowing for small changes. In fact, from the producers' standpoint, game balance issue is a critical success factor in game production. Therefore, they often invest much time and capital in game design. However, if such a costly game cannot provide players with an appropriate level of difficulty, the game is more likely to fail. On the contrary, if the game successfully identifies the game players' propensity and performs self-balancing to provide appropriate difficulty levels, this will significantly reduce the likelihood of game failure, while at the same time increasing the lifecycle of the game. Accordingly, if a novel technology for game balancing is developed using artificial intelligence (AI) that offers personalized, intelligent, and customized service to individual game players, it would bring significant changes to the game production system.