• Journal of KIBIM
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• v.13 no.3
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• pp.12-20
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• 2023

Deep learning-based anomaly detection technology is used in various fields such as computer vision, speech recognition, and natural language processing. In particular, this technology is applied in various fields such as monitoring manufacturing equipment abnormalities, detecting financial fraud, detecting network hacking, and detecting anomalies in medical images. However, in the field of construction and architecture, research on deep learning-based data anomaly detection technology is difficult due to the lack of digitization of domain knowledge due to late digital conversion, lack of learning data, and difficulties in collecting and processing field data in real time. This study acquires necessary data through IoT (Internet of Things) from the viewpoint of monitoring for environmental management of architectural spaces, converts them into a database, learns deep learning, and then supports anomaly patterns using AI (Artificial Infelligence) deep learning-based anomaly detection. We propose an implementation process. The results of this study suggest an effective environmental anomaly pattern detection solution architecture for environmental management of architectural spaces, proving its feasibility. The proposed method enables quick response through real-time data processing and analysis collected from IoT. In order to confirm the effectiveness of the proposed method, performance analysis is performed through prototype implementation to derive the results.

• Research in Plant Disease
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• v.30 no.1
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• pp.99-102
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• 2024

Integrated pest management is essential for controlling plant diseases that reduce crop yields. Rapid diagnosis is crucial for effective management in the event of an outbreak to identify the cause and minimize damage. Diagnosis methods range from indirect visual observation, which can be subjective and inaccurate, to machine learning and deep learning predictions that may suffer from biased data. Direct molecular-based methods, while accurate, are complex and time-consuming. However, the development of large multimodal models, like GPT-4, combines image recognition with natural language processing for more accurate diagnostic information. This study introduces GPT-4-based system for diagnosing plant diseases utilizing a detailed knowledge base with 1,420 host plants, 2,462 pathogens, and 37,467 pesticide instances from the official plant disease and pesticide registries of Korea. The AI plant doctor offers interactive advice on diagnosis, control methods, and pesticide use for diseases in Korea and is accessible at https://pdoc.scnu.ac.kr/.

• Journal of Legislation Research
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• no.53
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• pp.553-591
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• 2017

This article discussed whether so-called 'foreign judgments obtained by fraud' is in breach of public policy provided in Article 217(1)(3) of Civil Procedure Act and, if so, what the specific requirements could be. The summary of the conclusion is as follows. The 'foreign judgments obtained by fraud' is against the municipal procedural public policy and then shall not be recognized. In this regard one more question comes up whether reviewing if 'foreign judgments obtained by fraud' is in breach of the municipal procedural public policy is allowed in consideration of the principle of prohibition of $r{\acute{e}}vision$ au fond. Since the principle is applied entirely in the course of the above reviewing, it is allowed only when it does not breach the principle. The two instances that the reviewing is allowed are where the defendant was not able to produce evidences of fraud during foreign procedures and where the defendant's claim of fraud without evidences was rejected by the foreign court and then evidences of fraud were found after the foreign procedure was completed. On the other hand, the specific requirements for 'foreign judgments obtained by fraud' to be against public policy are following four requirements based on principle of strict interpretation of public policy. (1) plaintiff's intention to fraud, (2) preventing the defendant from being involved in the procedure by fraud or cheating the foreign court using manipulated evidences, (3) the defendant could not present himself in the foreign court procedure due to the plaintiff's extraneous fraud or the foreign court decided wrongly due to intrinsic fraud, and (4) defendant's fundamental procedural rights were breached to the extent that recognizing the effect of foreign judgments was against justice defendant's fundamental procedural rights. These results differ from the Supreme Court 2004. 10. 28. ruling 2002da74213 in many aspects. Most of all, in my opinion there is no need to distinguish between intrinsic fraud and extraneous fraud and reviewing 'foreign judgments obtained by fraud' is not in conflict with the principle of prohibition of $r{\acute{e}}vision$ au fond but the both may coexist. In this regard I expect the variation of the Supreme Court's position and hope to contribute to academia and practitioners.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.4
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• pp.77-84
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• 2012

Face classification has wide applications in intelligent video surveillance, content retrieval, robot vision, and human-machine interface. Pose and expression changes, and arbitrary illumination are typical problems for face recognition. When the face is captured at a distance, the image quality is often degraded by blurring and noise corruption. This paper investigates the efficacy of multi-classifier decision level fusion for face classification based on the photon-counting linear discriminant analysis with two different cost functions: Euclidean distance and negative normalized correlation. Decision level fusion comprises three stages: cost normalization, cost validation, and fusion rules. First, the costs are normalized into the uniform range and then, candidate costs are selected during validation. Three fusion rules are employed: minimum, average, and majority-voting rules. In the experiments, unfocusing and motion blurs are rendered to simulate the effects of the long distance environments. It will be shown that the decision-level fusion scheme provides better results than the single classifier.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.7
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• pp.655-663
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• 2017

With the development of ICT technology, the indoor utilization of robots is increasing. Research on transportation, cleaning, guidance robots, etc., that can be used now or increase the scope of future use will be advanced. To facilitate the use of mobile robots in indoor spaces, the problem of self-location recognition is an important research area to be addressed. If an unexpected collision occurs during the motion of a mobile robot, the position of the mobile robot deviates from the initially planned navigation path. In this case, the mobile robot needs a robust controller that enables the mobile robot to accurately navigate toward the goal. This research tries to address the issues related to self-location of the mobile robot. A robust position recognition system was implemented; the system estimates the position of the mobile robot using a combination of encoder information of the mobile robot and the absolute space coordinate transformation information obtained from external video sources such as a large number of CCTVs installed in the room. Furthermore, vector field histogram method of the pass traveling algorithm of the mobile robot system was applied, and the results of the research were confirmed after conducting experiments.

• Journal of Engineering Education Research
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• v.11 no.2
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• pp.79-89
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• 2008

The purpose of this study is to research the women engineers' recognition with a triangulation method and make suggestions on desirable education in engineering. The research period is for about 4 months from December 15, 2007 to April 4, 2008. The objects of the research are two groups of female engineers at D college located in the metropolitan area - the first group had 187 women engineering majors, 3 women graduate students and 2 women professors in engineering department, and the second group had 5 women engineering majors who once stayed out of school temporarily, 4 women engineering graduates, and 5 graduates who are currently working. The second group is intently selected in order to look into the detailed factors that affect the recognition of women engineers. The methods of the research varied and included were surveys on the web, personal interviews, focus meetings, surveys by e-mail and telephone, etc. The results of the study show what the women engineers want in engineering education includes to have role models of women engineers who can cast a vision to them, get a leadership training especially for when they lead a group that has both man and woman members. It was also found that experincing a cooperative learning through diverse projects is essential to build basic character training and competency, and practical education is required for the major or becoming a full time worker.

• KIPS Transactions on Computer and Communication Systems
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• v.2 no.10
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• pp.427-436
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• 2013

In this paper, a method of moving path control of an automatic guided vehicle in an indoor environment through recognition of marker images using vision sensors is presented. The existing AGV moving control system using infrared-ray sensors and landmarks have faced at two critical problems. Since there are many windows in a crematorium, they are going to let in too much sunlight in the main hall which is the moving area of AGVs. Sunlight affects the correct recognition of landmarks due to refraction and/or reflection of sunlight. The second one is that a crematorium has a narrow indoor environment compared to typical industrial fields. Particularly when an AVG changes its direction to enter the designated furnace the information provided by guided sensors cannot be utilized to estimate its location because the rotating space is too narrow to get them. To resolve the occurrences of such circumstances that cannot access sensing data in a WSN environment, a relative distance from marker to an AGV will be used as fingerprinting used for location estimation. Compared to the existing fingerprinting method which uses RSS, our proposed method may result in a higher reliable estimation of location. Our experimental results show that the proposed method proves the correctness and applicability. In addition, our proposed approach will be applied to the AGV system in the crematorium so that it can transport a dead body safely from the loading place to its rightful destination.

• KIPS Transactions on Software and Data Engineering
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• v.1 no.2
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• pp.127-136
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• 2012

Many research of hand gesture recognition based on vision system have been conducted which enable user operate various electronic devices more easily. 3D position calculation and meaningful gesture classification from similar gestures should be executed to recognize hand gesture accurately. A simple and cost effective method of 3D position calculation and gesture spotting (a task to recognize meaningful gesture from other similar meaningless gestures) is described in this paper. 3D position is achieved by calculation of two cameras relative position through pan/tilt module and a marker regardless with the placed position. Fuzzy garbage model is proposed to provide a variable reference value to decide whether the user gesture is the command gesture or not. The reference is achieved from fuzzy command gesture model and fuzzy garbage model which returns the score that shows the degree of belonging to command gesture and garbage gesture respectively. Two-stage user adaptation is proposed that off-line (batch) adaptation for inter-personal difference and on-line (incremental) adaptation for intra-difference to enhance the performance. Experiment is conducted for 5 different users. The recognition rate of command (discriminate command gesture) is more than 95% when only one command like meaningless gesture exists and more than 85% when the command is mixed with many other similar gestures.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.1-19
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• 2019

Artificial intelligence (AI) is one of the main driving forces leading the Fourth Industrial Revolution. The technologies associated with AI have already shown superior abilities that are equal to or better than people in many fields including image and speech recognition. Particularly, many efforts have been actively given to identify the current technology trends and analyze development directions of it, because AI technologies can be utilized in a wide range of fields including medical, financial, manufacturing, service, and education fields. Major platforms that can develop complex AI algorithms for learning, reasoning, and recognition have been open to the public as open source projects. As a result, technologies and services that utilize them have increased rapidly. It has been confirmed as one of the major reasons for the fast development of AI technologies. Additionally, the spread of the technology is greatly in debt to open source software, developed by major global companies, supporting natural language recognition, speech recognition, and image recognition. Therefore, this study aimed to identify the practical trend of AI technology development by analyzing OSS projects associated with AI, which have been developed by the online collaboration of many parties. This study searched and collected a list of major projects related to AI, which were generated from 2000 to July 2018 on Github. This study confirmed the development trends of major technologies in detail by applying text mining technique targeting topic information, which indicates the characteristics of the collected projects and technical fields. The results of the analysis showed that the number of software development projects by year was less than 100 projects per year until 2013. However, it increased to 229 projects in 2014 and 597 projects in 2015. Particularly, the number of open source projects related to AI increased rapidly in 2016 (2,559 OSS projects). It was confirmed that the number of projects initiated in 2017 was 14,213, which is almost four-folds of the number of total projects generated from 2009 to 2016 (3,555 projects). The number of projects initiated from Jan to Jul 2018 was 8,737. The development trend of AI-related technologies was evaluated by dividing the study period into three phases. The appearance frequency of topics indicate the technology trends of AI-related OSS projects. The results showed that the natural language processing technology has continued to be at the top in all years. It implied that OSS had been developed continuously. Until 2015, Python, C ++, and Java, programming languages, were listed as the top ten frequently appeared topics. However, after 2016, programming languages other than Python disappeared from the top ten topics. Instead of them, platforms supporting the development of AI algorithms, such as TensorFlow and Keras, are showing high appearance frequency. Additionally, reinforcement learning algorithms and convolutional neural networks, which have been used in various fields, were frequently appeared topics. The results of topic network analysis showed that the most important topics of degree centrality were similar to those of appearance frequency. The main difference was that visualization and medical imaging topics were found at the top of the list, although they were not in the top of the list from 2009 to 2012. The results indicated that OSS was developed in the medical field in order to utilize the AI technology. Moreover, although the computer vision was in the top 10 of the appearance frequency list from 2013 to 2015, they were not in the top 10 of the degree centrality. The topics at the top of the degree centrality list were similar to those at the top of the appearance frequency list. It was found that the ranks of the composite neural network and reinforcement learning were changed slightly. The trend of technology development was examined using the appearance frequency of topics and degree centrality. The results showed that machine learning revealed the highest frequency and the highest degree centrality in all years. Moreover, it is noteworthy that, although the deep learning topic showed a low frequency and a low degree centrality between 2009 and 2012, their ranks abruptly increased between 2013 and 2015. It was confirmed that in recent years both technologies had high appearance frequency and degree centrality. TensorFlow first appeared during the phase of 2013-2015, and the appearance frequency and degree centrality of it soared between 2016 and 2018 to be at the top of the lists after deep learning, python. Computer vision and reinforcement learning did not show an abrupt increase or decrease, and they had relatively low appearance frequency and degree centrality compared with the above-mentioned topics. Based on these analysis results, it is possible to identify the fields in which AI technologies are actively developed. The results of this study can be used as a baseline dataset for more empirical analysis on future technology trends that can be converged.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.11 no.6
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• pp.175-183
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• 2016

The government set up "national happiness, the hope of a new era of national vision under' job center of the creative economy" to achieve by national goals in the first and figure achieved through the establishment of new growth engines of the youth unemployment problem solve and national level there are a number of business start-up support. September 8, 2015 announced the Government's look at the '2016 Year of the budget, the government for new growth engines greatly promoted the venture entrepreneurship ecosystem revitalization and research and development (R & D) the business for enhanced performance in 2017. According to the direction of this study is to evaluate the current creative economy business incubator at the comparison whether the correct orientation mainly entrepreneurs, entrepreneurs preliminary recognition of student entrepreneurship ecosystem. Entrepreneurs 113 people in that way, 71 people pre-entrepreneurs, students 60, workers were founding agencies conducted an online survey of 47 people, 16 people Investors, 50 public and 11 additional persons including a total of 368 people. This study is in line with the orientation of these entrepreneurs to create economic status and recognition of the Republic of Korea entrepreneurship ecosystem, pre- entrepreneurs, students will examine the comparative analysis around. Analysis, social perception of entrepreneurship is somewhat higher than it was confirmed that the negative response of 32.2% to 36.3% of positive response. Social awareness of entrepreneurs showed a 2-fold higher response rate than the negative of response of 17.1% to 41.7% responding that positive recognition for the current start-up environment is bad, the response is good response to higher response rate than 23.5% to 41.1% It showed. The percentage of responses that better respect the entrepreneurship environment of the future Republic of Korea showed a higher response rate than the rate of 23% in response to deteriorate to 41.2%, with 52.9% awareness is the percentage that responded that the bad part about the ruthless Korea's entrepreneurship environment in China good part as response rate approximately three times greater than the 17.7% showed high response rates. Social awareness of entrepreneurs experience the presence of the founding start-up experience was confirmed that the more negative the number increases, the more the contrary the number of start-up experience increased awareness of the current and future environment of entrepreneurship was identified as a positive entrepreneurship environment. Also recognized was confirmed to change the parent of the more positive changes in the start-up of entrepreneurs doctor also positive about entrepreneurship, start-up entrepreneurs start with a doctor's motivation for founding non-economic reasons than for economic reasons has confirmed Higher. This study showed the overall level overview analysis of the status and recognition of the Republic of Korea entrepreneurship ecosystem. Future studies need to be a proposal for an existing previous studies for more precise direction to go forth to analyze the entrepreneurship ecosystem with a focus on problems and improvement of the Republic of Korea entrepreneurship ecosystem.