• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.10
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• pp.1331-1340
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• 2020

Object detection in maritime means that the captain detects floating objects that has a risk of colliding with the ship using the computer automatically and as accurately as human eyes. In conventional ships, the presence and distance of objects are determined through radar waves. However, it cannot identify the shape and type. In contrast, with the development of AI, cameras help accurately identify obstacles on the sea route with excellent performance in detecting or recognizing objects. The computer must calculate high-volume pixels to analyze digital images. However, the CPU is specialized for sequential processing; the processing speed is very slow, and smooth service support or security is not guaranteed. Accordingly, this study developed maritime object detection software and implemented it with FPGA to accelerate the processing of large-scale computations. Additionally, the system implementation was improved through embedded boards and FPGA interface, achieving 30 times faster performance than the existing algorithm and a three-times faster entire system.

• Journal of the Korean Institute of Landscape Architecture
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• v.50 no.2
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• pp.116-126
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• 2022

Although the 'Act on Urban Parks and Green Spaces' was revised in 2016 to provide a legal foundation for national urban parks, there was no further discussion or follow-up research for the implementation of national urban parks. This study investigates Korea's park and green space regulations and national urban park cases from across the world. It aims to analyze worldwide cases and set a course for a viable national urban park system in Korea. The importance and characteristics of national urban parks were evident after reviewing the cases of Japan, Sweden, Finland, and Canada, which have national urban park systems, and the United States and Germany, which aid city parks with national budgets. Each country determined the plans and procedures by assessing the scope of government intervention and the government's role. The importance of communication between the state and municipal governments and private sector participation and governance was recognized. A system was also formed in which local governments actively participate in the nomination, establishment, administration, and management of national urban parks. The results of this study are as follows. First, the concept of equitable national development should be implemented to activate the national urban park system. Second, the national urban park should be a land management tool that may be used to balance development and preservation. Third, a specific method of securing, constructing, administering, and operating national urban parks should be supplemented by the current legislative framework amendment. Furthermore, the establishment of a sustainable research institute is needed to comprehensively analyze parks and green space systems and make appropriate decisions.

• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.95-106
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• 2021

The purpose of this study is to derive major topics in content R&D and provide directions for academic development by exploring research trends over the past 20 years using topic modeling targeting 9,858 papers published in the Journal of the Korean Contents Association. To secure the reliability and validity of the extracted topics, not only the quantitative evaluation technique but also the qualitative technique were applied step-by-step and repeated until a corpus of the level agreed upon by the researchers was generated, and detailed analysis procedures were presented accordingly. As a result of the analysis, 8 core topics were extracted. This shows that the Korean Contents Association is publishing convergence and complex research papers in various fields without limiting to a specific academic field. Also, before 2012, the proportion of topics in the field of engineering and technology appeared relatively high, while after 2012, the proportion of topics in the field of social sciences appeared relatively high. Specifically, the topic of 'social welfare' showed a fourfold increase in the second half compared to the first half. Through topic-specific trend analysis, we focused on the turning point in time at which the inflection point of the trend line appeared, explored the external variables that affected the research trend of the topic, and identified the relationship between the topic and the external variable. It is hoped that the results of this study can provide implications for active discussions in domestic content-related R&D and industrial fields.

• Journal of Convergence for Information Technology
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• v.11 no.8
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• pp.36-41
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• 2021

Although the technology for prediction or analysis using artificial intelligence is constantly developing, a black-box problem does not interpret the decision-making process. Therefore, the decision process of the AI model can not be interpreted from the user's point of view, which leads to unreliable results. We investigated the problems of artificial intelligence and explainable artificial intelligence using Blockchain to solve them. Data from the decision-making process of artificial intelligence models, which can be explained with Blockchain, are stored in Blockchain with time stamps, among other things. Blockchain provides anti-counterfeiting of the stored data, and due to the nature of Blockchain, it allows free access to data such as decision processes stored in blocks. The difficulty of creating explainable artificial intelligence models is a large part of the complexity of existing models. Therefore, using the point cloud to increase the efficiency of 3D data processing and the processing procedures will shorten the decision-making process to facilitate an explainable artificial intelligence model. To solve the oracle problem, which may lead to data falsification or corruption when storing data in the Blockchain, a blockchain artificial intelligence problem was solved by proposing a blockchain-based explainable artificial intelligence model that passes through an intermediary in the storage process.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.6
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• pp.1215-1225
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• 2021

Although Artificial Intelligence (AI) techniques have shown impressive performance in various fields, they are vulnerable to adversarial examples which induce misclassification by adding human-imperceptible perturbations to the input. Previous studies to defend the adversarial examples can be classified into three categories: (1) model retraining methods; (2) input transformation methods; and (3) adversarial examples detection methods. However, even though the defense methods against adversarial examples have constantly been proposed, there is no research to classify the type of adversarial attack. In this paper, we proposed an adversarial attack family classification method based on dimensionality reduction and clustering. Specifically, after extracting adversarial perturbation from adversarial example, we performed Linear Discriminant Analysis (LDA) to reduce the dimensionality of adversarial perturbation and performed K-means algorithm to classify the type of adversarial attack family. From the experimental results using MNIST dataset and CIFAR-10 dataset, we show that the proposed method can efficiently classify five tyeps of adversarial attack(FGSM, BIM, PGD, DeepFool, C&W). We also show that the proposed method provides good classification performance even in a situation where the legitimate input to the adversarial example is unknown.

• Journal of Navigation and Port Research
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• v.45 no.6
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• pp.333-345
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• 2021

Amid the rapidly changing logistics environment and demand changes in the post-corona-19 era, the importance of the cold chain logistics sector is being highlighted. The scope of cold chain is not limited to food, but is expanding to various fields such as pharmaceuticals, semiconductors, and flowers. The demand on the storage and transportation of corona vaccines is rapidly increasing. The rapid increase in domestic low-temperature facility construction and renovation may lead to the saturation of the cold chain related industry in the future and slow growth. In preparation for this, it is necessary to accumulate infrastructure know-how using IT technologies, and to consider entering into the UN procurement market as a potential niche market, by taking advantage of Korea's recent global status. The demand for cold chain in the UN procurement market is increasing mainly in underdeveloped countries, and it is expected to continue to grow. In this paper, the capabilities of domestic cold chain related companies were analyzed, domestic and overseas cold chain logistics market trends and overseas market entry status were investigated. An in-depth survey was conducted to present strategies for domestic cold chain logistics related companies to enter the UN procurement market.

• Advanced Industrial SCIence
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• v.1 no.1
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• pp.7-15
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• 2022

To adopt the development in the medical scenario IoT developed towards the advancement with the processing of a large amount of medical data defined as an Internet of Medical Things (IoMT). The vast range of collected medical data is stored in the cloud in the structured manner to process the collected healthcare data. However, it is difficult to handle the huge volume of the healthcare data so it is necessary to develop an appropriate scheme for the healthcare structured data. In this paper, a machine learning mode for processing the structured heath care data collected from the IoMT is suggested. To process the vast range of healthcare data, this paper proposed an MTGPLSTM model for the processing of the medical data. The proposed model integrates the linear regression model for the processing of healthcare information. With the developed model outlier model is implemented based on the FinTech model for the evaluation and prediction of the COVID-19 healthcare dataset collected from the IoMT. The proposed MTGPLSTM model comprises of the regression model to predict and evaluate the planning scheme for the prevention of the infection spreading. The developed model performance is evaluated based on the consideration of the different classifiers such as LR, SVR, RFR, LSTM and the proposed MTGPLSTM model and the different size of data as 1GB, 2GB and 3GB is mainly concerned. The comparative analysis expressed that the proposed MTGPLSTM model achieves ~4% reduced MAPE and RMSE value for the worldwide data; in case of china minimal MAPE value of 0.97 is achieved which is ~ 6% minimal than the existing classifier leads.

• Journal of the Society of Disaster Information
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• v.19 no.3
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• pp.665-672
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• 2023

Purpose: Underground utility tunnel is facility that is jointly house infrastructure such as electricity, water and gas in city, causing condensation problems due to lack of airflow. This paper aims to prevent electricity leakage fires caused by condensation by detecting whether the control panel door in the underground utility tunnel is open using a deep learning model. Method: YOLO, a deep learning object recognition model, is trained to recognize the opening and closing of the control panel door using video data taken by a robot patrolling the underground utility tunnel. To improve the recognition rate, image augmentation is used. Result: Among the image enhancement techniques, we compared the performance of the YOLO model trained using mosaic with that of the YOLO model without mosaic, and found that the mosaic technique performed better. The mAP for all classes were 0.994, which is high evaluation result. Conclusion: It was able to detect the control panel even when there were lights off or other objects in the underground cavity. This allows you to effectively manage the underground utility tunnel and prevent disasters.

• Journal of Life Science
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• v.33 no.8
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• pp.663-679
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• 2023

This review analyzes research trends related to new drug development using artificial intelligence from 2010 to 2022. This analysis organized the abstracts of 2,421 studies into a corpus, and words with high frequency and high connection centrality were extracted through preprocessing. The analysis revealed a similar word frequency trend between 2010 and 2019 to that between 2020 and 2022. In terms of the research method, many studies using machine learning were conducted from 2010 to 2020, and since 2021, research using deep learning has been increasing. Through these studies, we investigated the trends in research on artificial intelligence utilization by field and the strengths, problems, and challenges of related research. We found that since 2021, the application of artificial intelligence has been expanding, such as research using artificial intelligence for drug rearrangement, using computers to develop anticancer drugs, and applying artificial intelligence to clinical trials. This article briefly presents the prospects of new drug development research using artificial intelligence. If the reliability and safety of bio and medical data are ensured, and the development of the above artificial intelligence technology continues, it is judged that the direction of new drug development using artificial intelligence will proceed to personalized medicine and precision medicine, so we encourage efforts in that field.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.1
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• pp.1-12
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• 2023

The ongoing Yongsan Park development project began in 1988 with the development of a utilization plan for the US Army base in Yongsan after the Army relocation. This study aimed to draw implications for the Yongsan Park project by focusing on Yongsan Family Park. Among the public records of Yongsan Park and Yongsan Family Park transferred to the Seoul Metropolitan Archives, 53 major records were analyzed. The results are as follows. First, Yongsan Family Park, built on the site of the US Army golf course in 1992, was considered a part of the Yongsan Park plan and holds status as the first phase of the Yongsan Park project. Second, despite its status, Yongsan Family Park opened as a temporary park occupied by urban facilities. A design and detailed roadmap of the development process is necessary to make Yongsan Park more resilient. Third, organizing and systematizing public records is necessary because lessons learned through past park development processes can be applied to the current project. This study is meaningful since it uncovered important issues of urban planning discussed in the process of Yongsan Family Park development through a complete analysis of public records, examined the linkage between Yongsan Family Park, which was not known until now, and the ongoing Yongsan Park project, and reaffirmed the importance of park archiving for long-term development projects.