• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.3
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• pp.162-170
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• 2014

Appearance-based subspace models such as eigenfaces have been widely recognized as one of the most successful approaches to face recognition and tracking. The success of eigenfaces mainly has its origins in the benefits offered by principal component analysis (PCA), the representational power of the underlying generative process for high-dimensional noisy facial image data. The sparse extension of PCA (SPCA) has recently received significant attention in the research community. SPCA functions by imposing sparseness constraints on the eigenvectors, a technique that has been shown to yield more robust solutions in many applications. However, when SPCA is applied to facial images, the time and space complexity of PCA learning becomes a critical issue (e.g., real-time tracking). In this paper, we propose a very fast and scalable greedy forward selection algorithm for SPCA. Unlike a recent semidefinite program-relaxation method that suffers from complex optimization, our approach can process several thousands of data dimensions in reasonable time with little accuracy loss. The effectiveness of our proposed method was demonstrated on real-world face recognition and tracking datasets.

• International Journal of Advanced Culture Technology
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• v.10 no.1
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• pp.294-301
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• 2022

COVID-19 is a crisis with numerous casualties. The World Health Organization (WHO) has declared the use of masks as an essential safety measure during the COVID-19 pandemic. Therefore, whether or not to wear a mask is an important issue when entering and exiting public places and institutions. However, this makes face recognition a very difficult task because certain parts of the face are hidden. As a result, face identification and identity verification in the access system became difficult. In this paper, we propose a system that can detect masked face using transfer learning of Yolov5s and recognize the user using transfer learning of Facenet. Transfer learning preforms by changing the learning rate, epoch, and batch size, their results are evaluated, and the best model is selected as representative model. It has been confirmed that the proposed model is good at detecting masked face and masked face recognition.

• Journal of Korea Game Society
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• v.12 no.2
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• pp.63-74
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• 2012

Two legal issues of the game industry in Korea are intersted in theses days. Open market & Shut-down. This article is studying for the impacts and the meaning of the game market that the institutionalization of two legal issue produce a powerful effect on. Social environment & recognition bring up the subject. This article is focusing at social environment & recognition and the forecasting game market. With the coming of smart-phone, the mobile contents market is changed. The open market for game is the issue for this changing market and assists the activation of the mobile-market with rational and futuristic perspectives. Shut-down(prohibition of the access of the young people in midnight) is the issue for game addiction and aggravates the game market and the perception on game with the focusing of the happening. This article points out the importance of institutionalization in consequence of the opposite direction of the market effects.

• Journal of Information Processing Systems
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• v.9 no.2
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• pp.333-348
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• 2013

Mobile authentication/identification has grown into a priority issue nowadays because of its existing outdated mechanisms, such as PINs or passwords. In this paper, we introduce gait recognition by using a mobile accelerometer as not only effective but also as an implicit identification model. Unlike previous works, the gait recognition only performs well with a particular mobile specification (e.g., a fixed sampling rate). Our work focuses on constructing a unique adaptive mechanism that could be independently deployed with the specification of mobile devices. To do this, the impact of the sampling rate on the preprocessing steps, such as noise elimination, data segmentation, and feature extraction, is examined in depth. Moreover, the degrees of agreement between the gait features that were extracted from two different mobiles, including both the Average Error Rate (AER) and Intra-class Correlation Coefficients (ICC), are assessed to evaluate the possibility of constructing a device-independent mechanism. We achieved the classification accuracy approximately $91.33{\pm}0.67%$ for both devices, which showed that it is feasible and reliable to construct adaptive cross-device gait recognition on a mobile phone.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.6
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• pp.755-759
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• 2009

The ability to recognize human emotion is one of the hallmarks of human-robot interaction. Especially, speaker-independent emotion recognition is a challenging issue for commercial use of speech emotion recognition systems. In general, speaker-independent systems show a lower accuracy rate compared with speaker-dependent systems, as emotional feature values depend on the speaker and his/her gender. Hence, this paper describes the realization of speaker-independent emotion recognition by rejection using confidence measure to make the emotion recognition system be homogeneous and accurate. From comparison of the proposed methods with conventional method, the improvement and effectiveness of proposed methods were clearly confirmed.

• Journal of Arbitration Studies
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• v.23 no.1
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• pp.1-23
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• 2013

When a court recognizes an arbitral award, it acknowledges that the award is valid and binding, and thereby gives it a set of effects similar to those of a court's judgment, among which res judicata is the most important. The res judicata effect of an arbitral award generally forbids parties to an action from subsequently litigating claims that were raised in a prior arbitration. In common law countries, res judicata may also preclude re-adjudication of issues raised and decided in a prior arbitration. The Korean Arbitration Act acknowledges the rights of parties to an arbitral award to seek not only an enforcement judgment but also a recognition judgment on an arbitral award. Therefore, the question arises whether or not the winning party in an arbitration must acquire a recognition judgment on the arbitral award in order to enjoy the effects of a recognized award. However, according to the case law and generally accepted views, an arbitral award is automatically recognized without any additional procedure, as long as it satisfies the requirements for recognition. Therefore, in order to resolve this question, it is desirable to eliminate the statutory clause that stipulates the right to seek recognition judgment.

• Hwankyungkyoyuk
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• v.20 no.1
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• pp.90-105
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• 2007

The purpose of this study is to find the influence of environmental issue analysis instruction on the environmental decision making ability for grade 5 elementary school students. The study was done through pre and post testing control group structure. The object of this study is grade 5 of I elementary school students which were divided into 35 student test group and 54 student control group. Through studying references, the selection standard of appropriate environment issue and the environmental issue analysis instructing objective. Conducted the environment issue instructing based on the selected environment issue and instructing objective. The classes were held in total of 6 sessions in the chapters related to class objective and class content within the curriculum. The pre and post testing was done using environment decision making ability test sheet which was reconstructed by myself and the results were analyzed by t-test. As a result of comparing pre and post testing the students in test group showed significant results in the processes of problem recognition, evaluation of alternatives, behave planing (p<.001). As a result of comparing the differences of environment decision making ability of pre and post test of test group and control group, it showed significant results in the process of evaluation of alternatives(p<.00l). The environment issue analysis class has positive influence on the environment decision making abilities of the students but since the outcome of environment decision making ability is lower, there is a need for long term environment education plan and further studies to find whether the environment issues within the textbook is appropriate in the elementary student level, useful school aspect and the influence of environment issue analysis class on the change of values for individuals.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.31 no.3
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• pp.119-132
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• 2023

In recent years, the competition for employment among college students has become more intense. It is also the time when strong personal beliefs and will to develop careers are required for successful employment through stable major study. Therefore, in this study, we tried to find out the effect on major attitude and employment efficacy according to the level of aviation safety perception, which is an important issue in the aviation industry. For analysis, survey is conducted targeting college students majoring in aviation service who are enrolled in universities in the metropolitan area and Chungcheong area. To verify the hypotheses of the study, demographic characteristics are identified based on questionnaires, reliability and validity of measurement items are verified, and structural equation model analysis is performed to verify the hypotheses. The analysis results are as follows. First, it is found that safety knowledge and safety consciousness, which are sub-factors of aviation safety perception of college students majoring in aviation service, have a positive (+) effect on subject recognition, learning process recognition, and career recognition of major recognition. Second, subject recognition, learning process recognition, and career recognition, which are sub-factors of major recognition, are found to have a positive effect on major commitment. Third, it is found that major commitment have a positive (+) effect on employment efficacy. Based on the research results, practical support plans and strategies for effective major study and successful employment are presented.

• IEMEK Journal of Embedded Systems and Applications
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• v.9 no.6
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• pp.345-351
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• 2014

This paper presents pedestrian recognition to improve performance for vehicle safety system or surveillance system. Pedestrian detection method using HOG (Histograms of Oriented Gradients) has showed 90% recognition rate. But if someone takes a picture in the rain, the image may be distorted by rain streaks and recognition rate goes down by 62%. To solve this problem, we applied image decomposition method using MCA (Morphological Component Analysis). In this case, rain removal method improves recognition rate from 62% to 70%. However, it is difficult to apply conventional image decomposition method using MCA on vehicle safety system or surveillance system as conventional method is too slow for real-time system. To alleviate this issue, we propose a rain removal method by using low-pass filter and DCT (Discrete Cosine Transform). The DCT helps separate the image into rain components. The image is removed rain components by Butterworth filtering. Experimental results show that our method achieved 90% of recognition rate. In addition, the proposed method had accelerated processing time to 17.8ms which is acceptable for real-time system.

• Journal of Korea Multimedia Society
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• v.22 no.11
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• pp.1233-1241
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• 2019

The goal of the sound-based mechanical fault diagnosis technique is to automatically find abnormal signals in the machine using acoustic emission. Conventional methods of using mathematical models have been found to be inaccurate due to the complexity of industrial mechanical systems and the existence of nonlinear factors such as noise. Therefore, any fault diagnosis issue can be treated as a pattern recognition problem. We propose an automatic fault diagnosis method using discrete wavelet transform and power spectrum density using multi pattern recognition. First, we perform DWT-based filtering analysis for noise cancelling and effective feature extraction. Next, the power spectral density(PSD) is performed on each subband of the DWT in order to effectively extract feature vectors of sound. Finally, each PSD data is extracted with the features of the classifier using multi pattern recognition. The results show that the proposed method can not only be used effectively to detect faults as well as apply to various automatic diagnosis system based on sound.