• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.5
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• pp.274-286
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• 2022

Multi-object tracking has been studied for a long time under computer vision and plays a critical role in applications such as autonomous driving and driving assistance. Multi-object tracking techniques generally consist of a detector that detects objects and a tracker that tracks the detected objects. Various publicly available datasets allow us to train a detector model without much effort. However, there are relatively few publicly available datasets for training a tracker model, and configuring own tracker datasets takes a long time compared to configuring detector datasets. Hence, the detector is often developed separately with a tracker module. However, the separated tracker should be adjusted whenever the former detector model is changed. This study proposes a system that can train a model that performs detection and tracking simultaneously using only the detector training datasets. In particular, a Siam network with augmentation is used to compose the detector and tracker. Experiments are conducted on public datasets to verify that the proposed algorithm can formulate a real-time multi-object tracker comparable to the state-of-the-art tracker models.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.6
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• pp.259-266
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• 2023

It is very difficult to measure the performance of the machine learning model in the business service stage. Therefore, managing the performance of the model through the operational department is not done effectively. Academically, various studies have been conducted on the concept drift detection method to determine whether the model status is appropriate. The operational department wants to know quantitatively the performance of the operating model, but concept drift can only detect the state of the model in relation to the data, it cannot estimate the quantitative performance of the model. In this study, we propose a performance prediction model (PPM) that quantitatively estimates precision through the statistics of concept drift. The proposed model induces artificial drift in the sampling data extracted from the training data, measures the precision of the sampling data, creates a dataset of drift and precision, and learns it. Then, the difference between the actual precision and the predicted precision is compared through the test data to correct the error of the performance prediction model. The proposed PPM was applied to two models, a loan underwriting model and a credit card fraud detection model that can be used in real business. It was confirmed that the precision was effectively predicted.

• Journal of the Korea Society for Simulation
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• v.19 no.4
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• pp.151-159
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• 2010

Currently, by using the Internet, We can do varius things such as Web surfing, email, on-line shopping, stock trading on your home or office. However, as being out of the concept of security from the beginning, it is the big social issues that malicious user intrudes into the system through the network, on purpose to steal personal information or to paralyze system. In addition, network intrusion by ordinary people using network attack tools is bringing about big worries, so that the need for effective and powerful intrusion detection system becomes very important issue in our Internet environment. However, it is very difficult to prevent this attack perfectly. In this paper we proposed the algorithm for the detection of DoS attacks, and developed attack detection tools. Through learning in a normal state on Step 1, we calculate thresholds, the number of packets that are coming to each port, the median and the average utilization of each port on Step 2. And we propose values to determine how to attack detection on Step 3. By programing proposed attack detection algorithm and by testing the results, we can see that the difference between the median of packet mounts for unit interval and the average utilization of each port number is effective in detecting attacks. Also, without the need to look into the network data, we can easily be implemented by only using the number of packets to detect attacks.

• SUVANNABHUMI
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• v.2 no.1
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• pp.55-94
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• 2010

Even Faxian(法顯)'s Gaosengfaxianchuan (『高僧法顯傳』) and Iching(義淨)'s Nanhaijiguineifachuan (『南海寄歸內法傳』) are regarded as very important and useful documents to study the southeast asian buddhist culture, it is very difficult to grasp the contemporary state of those area because their descriptions are very brief and implicit. Therefore this essay aimed an in-depth reading their documents as original texts of modern understanding of those area, and tried to make a new views to approach the southeast asian buddhist culture by some more historically and concretely. At the early 5th century when Faxian(法顯) arrived, Buddhism was flourished in Sri Lanka. Because already a long time passed since the Saṇgha was schismatized into conservative and progressive at around the dominical year, he mentioned nothing about the conflict or disharmony of two orders. And the faith of Buddha tooth relic, which had been uprisen at 50 years ago from Faxian's visiting, was concretely established as a representative religion of Sri Lanka. According to his record, the carrying ritual of this Buddha tooth was performed very magnificently as similar with recent Korean Youngsan ceremony(靈山齋). In the mean time, it looks there were many sculptures of Buddha image made of precious stone of special product from Sri Lanka. The faith of Buddha-pāda(the Buddha's foot-prints) was also generalized at that time. The most famous monk of his contemporary Sir Lanka was Buddhaghosa, the author of Visuddhi-magga, but it is not sure that Faxian had met him. It can be suspected that the funeral in which Faxian participated could be belonged to him, or the Visuddhi-magga was writing at the peak during Faxian's staying. On the way to return to China, Faxian embarked an indigenous ship around Indonesia. It means there were no chinese trade ship which he can use. So the trade between china and southeast asia was advanced by south asian ships, and the chinese ships were not yet joined at that time so activity. And at least until that time, it looks there were no any remarkable buddhist movement in the southeast asian countries by where he stopped. In contrast, the southeast asian world which be seen by Iching had already experienced a lot of changes. He was impressed by the high quality buddhist culture of those area, and insisted to accept it to china. Further, he analyzed the sects of buddhism which were prevalent around the southeast asia in his contemporary time, and tried to make a good relationship with each native monks for learning from them. It looks the center of those exchanges may be Śrīvijaya of Indonesia. He also mentioned the situation of the late 7th century's Funan(扶南) in Cambodia. At that time, the buddhist Saṇgha was oppressed by newly rising Khmer(眞臘). On the other hand, he described the points of sameness and difference in detail between Indian and southeast asian buddhist culture in the field of ritual as like the practical use of garments, buddha images, and daily recited scriptures. There must be a lot of another aspects which this essay couldn't gather up or catch from these documents. Nevertheless, I hope this essay can help the researchers of this field and will wait for any advices and comments from them.

• Communications of Mathematical Education
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• v.37 no.2
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• pp.159-181
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• 2023

The purpose of this study is to explore secondary mathematics teachers' perceptions on Artificial Intelligence (AI). For this purpose, we conducted three focus group interviews with 18 secondary in-service mathematics teachers and analyzed their perceptions on AI for math and math for AI. The secondary in-service mathematics teachers perceive that AI allows to implement different types of mathematics instruction but has limitations in exploring students' mathematical thinking and having emotional interactions with students. They also perceive that AI makes it easy to develop assessment items for teachers but teachers' interventions are needed for grading essay-type assessment items. Lastly, the secondary in-service mathematics teachers agree the rationale of adopting the subject ＜Artificial Intelligence Mathematics＞ and its needs for students, but they perceive that they are not well prepared yet to teach the subject and do not have sufficient resources for teaching the subject and assessing students' understanding about the subject. The findings provide implications and insights for developing individualized AI learning tools for students in the secondary level, providing AI assessment tools for teachers, and offering professional development programs for teachers to increase their understanding about the subject.

• Trans-
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• v.14
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• pp.35-63
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• 2023

Parkinson's disease is a degenerative neurological disease that affects even basic daily life movements due to impairment of body function caused by a lack of dopamine, which is charge of the body movement. Presently, it is hard to cure Parkinson's disease entirely with medical technology, so movement therapy as a solution to delay and prevent disease is getting more attention. Therefore, this study aims at desiging and disseminating a body movement program that concentrates on individual self-care and balacing the state of body and mind by applying the Feldenkrais Method® to patients with Parkinson's disease. The Feldenkrais Method® is a mind-body perceptual learning method using body movements. It is a methodology that re-educates the nervous system by connecting the brain and behavior as a function of neuroplasticity. In this study, the body movement program developed and verified by the researcher was modified and supplemented with a focus on the self-awareness of the Feldenkrais Method®. A 24-session physical exercise program was composed of 5 stages to improve the self-management ability of patients with Parkinson's disease. The stages include self-awareness, self-observation, self-organization, self-control, and self-care. The overall changes recognize one's condition and improve one's ability to detect modifications in the internal sense and external environment. In conclusion, the body movement program improves the body movement program improves mental and physical functions and self-care for Parkinson's disease patients through the Feldenkrais method. The availability of the program's on-site applicability remains a follow-up task. Furthermore, it is necessary to establish a systematic structure to spread it more widely through convergent cooperation with the scientific field applied with metaverse as a reference for the wellness of the elderly.

• Journal of The Korean Association For Science Education
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• v.26 no.6
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• pp.691-702
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• 2006

The purposes of the study are to portray Korean beginning secondary science teachers' ways of arranging science content, sense-making strategy, and factors contributing to the tensions between teachers' intentions and actual practice. Six beginning secondary science teachers participated in this study. Science classes taught by the participating teachers were observed and videotaped. Semi-structured interviews were conducted for science teachers participated in this study after science classes were observed. Instructional materials were also collected for each science class. Video- and audio-taped data were transcribed and analyzed using conceptual framework developed by the Michigan State University. The findings of this study produce the following conclusions: (1) beginning teachers' science classes are arranged in ways compatible to traditional school science, (2) frequently used sense-making strategies are procedural display and narrative reasoning, (3) tensions between beginning teachers' intentions and practice arise from two factors such as assessment and differences in educational views with peer teachers, and (4) learning experiences, lack of perceptions and preparations on reform science teaching, and the absence of systematic program for professional development programs for beginning science teachers are major obstacles to reform science teaching for beginning teachers.

• Journal of Korean Home Economics Education Association
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• v.35 no.3
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• pp.169-190
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• 2023

Uzbekistan, one of the top five cotton-producing countries in the world, primarily focuses its textile and fashion industry on raw cotton exports and the sewing industry. For Uzbekistan to achieve high added value, it is essential for the textile and fashion industry, which is currently at the CMT(cut, make, and trim) stage, to upgrade to OEM (original equipment manufacturing), ODM (original design manufacturing), and OBM (original brand manufacturing). South Korea recognizes Uzbekistan as a potential manufacturing base and trading partner and has invested Official Development Assistance (ODA) funds for the development of Uzbekistan's textiles and apparel sector. This study aims to evaluate Uzbekistan's fashion higher education in the context of global competitiveness and measure the need and prospects for education ODA from the Korean government in this field. Comprehensive investigations, including surveys of academics, industry experts, and government officials, in-depth interviews, and focus group interviews, were conducted to understand Uzbekistan's current fashion education environment. According to the research results, despite the textile and fashion sectors playing a pivotal role in the Uzbek economy, there is room for improvement in the curricula and teaching and learning methods of the fashion higher education programs. This study holds significance as foundational data for establishing education ODA strategies.

• Journal of The Korean Association For Science Education
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• v.39 no.6
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• pp.777-790
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• 2019

The purpose of this study is to investigate the experience of teachers who apply Smart-technology in elementary school STEAM class and the reasons, difficulties when applying the technology and required support. Semi-structured in-depth interviews were conducted with six elementary school teachers with specialized knowledge in STEAM education who have experienced STEAM lessons several times before. The research findings are as follows: First, research participants utilized a variety of Smart-technology in STEAM class, most of which were experiential or interactive technology. Among the STEAM learning criteria, the Smart-technology in 'Creative Design' course was most often applied. Second, they adopted Smart Technology in STEAM class to encourage students to feel interested, actively participate in the class, enjoy indirect experience, and nurture interest in state-of-the-art technology. They used it to prepare for future societies and organize classes that are suitable for STEAM learning criteria. They also used Smart-technology because it was easy to use. Third, they found it difficult to find, secure, and use suitable Smart-technology when applying Smart-technology in the STEAM class. They also had trouble restructuring the curriculum. In addition, there were difficulties in using Smart-technology in the class such as lack of class hours, increased level of activity, insufficient physical environment and unexpected malfunction of Smart-technology, thus interrupted the class. After the class, it was hard to manage Smart-technology and also, there were difficulties in assessment, record, and negative awareness of surrounding people. Fourth, they mentioned that's suggesting education guidelines, develop, and distribute educational materials are required to enable 'Creative Design,' reduce educational content, provide training, secure Smart-technology equipment and provide Wi-Fi, support teacher's club and communities and create an atmosphere to emotionally support teachers in order to activate using Smart-technology in STEAM class.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.243-264
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• 2018

Although the worldwide battery market is recently spurring the development of lithium secondary battery, lead acid batteries (rechargeable batteries) which have good-performance and can be reused are consumed in a wide range of industry fields. However, lead-acid batteries have a serious problem in that deterioration of a battery makes progress quickly in the presence of that degradation of only one cell among several cells which is packed in a battery begins. To overcome this problem, previous researches have attempted to identify the mechanism of deterioration of a battery in many ways. However, most of previous researches have used data obtained in a laboratory to analyze the mechanism of deterioration of a battery but not used data obtained in a real world. The usage of real data can increase the feasibility and the applicability of the findings of a research. Therefore, this study aims to develop a model which predicts the battery deterioration using data obtained in real world. To this end, we collected data which presents change of battery state by attaching sensors enabling to monitor the battery condition in real time to dozens of golf carts operated in the real golf field. As a result, total 16,883 samples were obtained. And then, we developed a model which predicts a precursor phenomenon representing deterioration of a battery by analyzing the data collected from the sensors using machine learning techniques. As initial independent variables, we used 1) inbound time of a cart, 2) outbound time of a cart, 3) duration(from outbound time to charge time), 4) charge amount, 5) used amount, 6) charge efficiency, 7) lowest temperature of battery cell 1 to 6, 8) lowest voltage of battery cell 1 to 6, 9) highest voltage of battery cell 1 to 6, 10) voltage of battery cell 1 to 6 at the beginning of operation, 11) voltage of battery cell 1 to 6 at the end of charge, 12) used amount of battery cell 1 to 6 during operation, 13) used amount of battery during operation(Max-Min), 14) duration of battery use, and 15) highest current during operation. Since the values of the independent variables, lowest temperature of battery cell 1 to 6, lowest voltage of battery cell 1 to 6, highest voltage of battery cell 1 to 6, voltage of battery cell 1 to 6 at the beginning of operation, voltage of battery cell 1 to 6 at the end of charge, and used amount of battery cell 1 to 6 during operation are similar to that of each battery cell, we conducted principal component analysis using verimax orthogonal rotation in order to mitigate the multiple collinearity problem. According to the results, we made new variables by averaging the values of independent variables clustered together, and used them as final independent variables instead of origin variables, thereby reducing the dimension. We used decision tree, logistic regression, Bayesian network as algorithms for building prediction models. And also, we built prediction models using the bagging of each of them, the boosting of each of them, and RandomForest. Experimental results show that the prediction model using the bagging of decision tree yields the best accuracy of 89.3923%. This study has some limitations in that the additional variables which affect the deterioration of battery such as weather (temperature, humidity) and driving habits, did not considered, therefore, we would like to consider the them in the future research. However, the battery deterioration prediction model proposed in the present study is expected to enable effective and efficient management of battery used in the real filed by dramatically and to reduce the cost caused by not detecting battery deterioration accordingly.