• Journal of the Korean Society of Floral Art and Design
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• no.43
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• pp.101-122
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• 2020

In this paper, the social paradigm is rapidly changing with the expansion of human consciousness, which has emerged as the development of 20th century science and the influence of cutting-edge media as the search for new forms of flower art sculptures. Is becoming. Accordingly, the purpose of this study is to analyze the interaction relationship of the expression elements of environmentally friendly pressed sculptures in the space as interior materials in the space where customer service is provided. (Research method) After deriving the formative expression characteristics of environmentally friendly pressed flower sculptures, and deriving interactive analysis elements between the servicescape space and humans of the pressed flower sculptures through references, service the flower sculptures for 8 installation cases The expression patterns of the interrelationships in the space of the landscape of the landscape were analyzed. (Results) The characteristics of dynamic formation and continuity were emphasized in the environment-friendly pressed sculpture space, and the interaction that the sympathetic reaction to the natural motif element felt as a new experience in space appeared. In the future, commercial spaces can be actively experienced through natural elements, and users can experience active interactions to create differentiated spaces as spaces where humans and humans coexist.

• Journal of the Korean Society of Radiology
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• v.16 no.4
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• pp.453-462
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• 2022

In this paper, the artificial intelligence (AI) technology used in the medical image analysis field was analyzed through a literature review. Literature searches were conducted on PubMed, ResearchGate, Google and Cochrane Review using the key word. Through literature search, 114 abstracts were searched, and 98 abstracts were reviewed, excluding 16 duplicates. In the reviewed literature, AI is applied in classification, localization, disease detection, disease segmentation, and fit degree of registration images. In machine learning (ML), prior feature extraction and inputting the extracted feature values into the neural network have disappeared. Instead, it appears that the neural network is changing to a deep learning (DL) method with multiple hidden layers. The reason is thought to be that feature extraction is processed in the DL process due to the increase in the amount of memory of the computer, the improvement of the calculation speed, and the construction of big data. In order to apply the analysis of medical images using AI to medical care, the role of physicians is important. Physicians must be able to interpret and analyze the predictions of AI algorithms. Additional medical education and professional development for existing physicians is needed to understand AI. Also, it seems that a revised curriculum for learners in medical school is needed.

• Journal of Navigation and Port Research
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• v.46 no.4
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• pp.367-374
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• 2022

The purpose of this study was to propose a deep learning algorithm that applies to the fault diagnosis of fuel pumps and purifiers of autonomous ships. A deep learning algorithm reflecting the time dependence of the measured signal was configured, and the failure pattern was trained using the vibration signal, measured in the equipment's regular operation and failure state. Considering the sequential time-dependence of deterioration implied in the vibration signal, this study adopts Conv1D with sliding window computation for fault detection. The time dependence was also reflected, by transferring the measured signal from two-dimensional to three-dimensional. Additionally, the optimal values of the hyper-parameters of the Conv1D model were determined, using the grid search technique. Finally, the results show that the proposed data preprocessing method as well as the Conv1D model, can reflect the sequential dependency between the fault and its effect on the measured signal, and appropriately perform anomaly as well as failure detection, of the equipment chosen for application.

• Journal of Korean Medicine Rehabilitation
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• v.32 no.4
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• pp.19-32
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• 2022

Objectives This scoping review aimed to investigate the domestic clinical research trends of motion-style acupuncture treatment (MSAT), identify diseases and symptoms for which MSAT is used, summarize specific methods of MSAT, and suggest the direction of future studies. Methods The study was conducted in accordance with a previously specified methodology, using the preferred reporting items for systematic reviews and meta-analyses extension for scoping reviews (PRISMA-ScR) checklist. We searched nine electronic databases for studies on MSAT reported till March 21, 2022. The search terms were 'kinematic acupuncture,' 'MSAT,' 'motion style acupuncture,' and 'motion style treatment.' Results A total of 29 studies were included in our analyses; of them, 23 (79.3%) were before-after studies. Lumbosacral disease was the most common for which MSAT was applied (n=16). The frequency and duration of treatments differed depending on the researchers, and local acupoints (including ashi points) were used in 22 (75.9%) studies. In most cases, the method of mobilizing the joint or stretching the muscle in the disease area was used after inserting the acupuncture; however, in 7 studies, gait exercise was used. Most studies used MSAT in combination with other treatments. Conclusions This study supports the direction of future research by presenting the methodological applications of MSAT. To increase its clinical applicability, studies with a high level of evidence investigating the application to various body part, standardization and safety of MSAT are necessary.

• Journal of Internet Computing and Services
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• v.24 no.4
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• pp.25-36
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• 2023

Today, as AI (Artificial Intelligence) technology is introduced in various fields, including security, the development of technology is accelerating. However, with the development of AI technology, attack techniques that cleverly bypass malicious behavior detection are also developing. In the classification process of AI models, an Adversarial attack has emerged that induces misclassification and a decrease in reliability through fine adjustment of input values. The attacks that will appear in the future are not new attacks created by an attacker but rather a method of avoiding the detection system by slightly modifying existing attacks, such as Adversarial attacks. Developing a robust model that can respond to these malware variants is necessary. In this paper, we propose two methods of generating Adversarial attacks as efficient Adversarial attack generation techniques for improving Robustness in AI models. The proposed technique is the XAI-based attack technique using the XAI technique and the Reference based attack through the model's decision boundary search. After that, a classification model was constructed through a malicious code dataset to compare performance with the PGD attack, one of the existing Adversarial attacks. In terms of generation speed, XAI-based attack, and reference-based attack take 0.35 seconds and 0.47 seconds, respectively, compared to the existing PGD attack, which takes 20 minutes, showing a very high speed, especially in the case of reference-based attack, 97.7%, which is higher than the existing PGD attack's generation rate of 75.5%. Therefore, the proposed technique enables more efficient Adversarial attacks and is expected to contribute to research to build a robust AI model in the future.

• Journal of Korea Entertainment Industry Association
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• v.13 no.4
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• pp.207-216
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• 2019

The purpose of this study was to analyze the relationships among soccer media involvement experience(SMIE), purchase intent(PI) and continued participation intent(CPI) in soccer clubs and provide basic data necessary for the sustainable growth of soccer clubs and related goods companies. In order to accomplish such study purposes, the study employed a survey method with a total of 327 amateur soccer players residing in G metropolitan city. The data from the survey questionnaires were validated through exploratory factor analysis and reliability test. The data were analyzed through descriptive statistics, correlation analysis and multiple regression analysis at the significance level of .05. Accordingly, following findings were derived from the current study. First, the level of interest was the highest among SMIE factors, followed by challenge and technology. Second, the level of alternative evaluation was the highest among PI factors, followed by purchase recognition, problem recognition, and information search. Third, technology factor in SMIE had a negative effect on PI. Fourth, technology factor in SMIE had a positive effect on CPI. Lastly, among PI factors, problem recognition had a negative effect and alternative evaluation had a positive effect on CPI.

• Journal of the Korean Institute of Landscape Architecture
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• v.50 no.6
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• pp.42-57
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• 2022

This study aims to create a basic model for classifying the activity photos that urban park users shared on social media using Deep Learning through Artificial Intelligence. Regarding the social media data, photos related to urban parks were collected through a Naver search, were collected, and used for the classification model. Based on the indicators of Naturalness, Potential Attraction, and Activity, which can be used to evaluate the characteristics of urban parks, 21 classification categories were created. Urban park photos shared on Naver were collected by category, and annotated datasets were created. A custom CNN model and a transfer learning model utilizing a CNN pre-trained on the collected photo datasets were designed and subsequently analyzed. As a result of the study, the Xception transfer learning model, which demonstrated the best performance, was selected as the urban park user activity image classification model and evaluated through several evaluation indicators. This study is meaningful in that it has built AI as an index that can evaluate the characteristics of urban parks by using user-shared photos on social media. The classification model using Deep Learning mitigates the limitations of manual classification, and it can efficiently classify large amounts of urban park photos. So, it can be said to be a useful method that can be used for the monitoring and management of city parks in the future.

• The Journal of the Convergence on Culture Technology
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• v.9 no.1
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• pp.427-436
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• 2023

Je Baek-seok, who is well versed in poetry, calligraphy, painting, and sculpture, has established himself as the most outstanding painter and pavilion in the history of modern and contemporary Chinese art. During the Ming and Qing Dynasties, the art of the pavilion was developed greatly during the enlightenment period, with the emergence of many masters of the pavilion, including Jeonggyeong, Hwanghwangseokyeo, Oyangji, Jo Ji-gyeom, Hwang Mok-bo, and Oh Chang-seok. Je Baek-seok formed an original ritual under this social background. Je Baek-seok's tactics were formed by imitating works from the Hanwi period, and he harmonized Jin Kwon, Sopan, and Janggunin while using the penmanship of the Cheonbal Shinchambi based on the "Sasam Gongsanbi." In addition, by boldly using the Danipdo method, it is possible to use the human face as much as possible while fully exhibiting the artistry of calligraphy and adding to the atmosphere of gold stone. This paper mainly analyzed and reviewed the process of Je Baek-seok's transcription transformation and humanities practice from two aspects. First, it is planned to summarize the process of Je Baek-seok's transformation into a Jeonseo. Second, Je Baek-seok's humanities practice was analyzed. This paper will further understand Je Baek-seok's humanistic ideas and practical search by clarifying the originality of Je Baek-seok's engraving art with examples of Je Baek-seok's works, and it is believed that this will provide future scholars with learning paths and rich experiences.

• Journal of Korea Water Resources Association
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• v.55 no.spc1
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• pp.1261-1270
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• 2022

The purpose of this study is to collect and analyze information related to water leaks that cannot be easily accessed, and utilized by using the news search results that people can easily access. We applied a web crawling technique for extracting big data news on water leakage accidents in the water supply system and presented an algorithm in a procedural way to obtain accurate leak accident news. In addition, a data analysis technique suitable for water leakage accident information analysis was developed so that additional information such as the date and time of occurrence, cause of occurrence, location of occurrence, damaged facilities, damage effect. The primary goal of value extraction through big data-based leak analysis proposed in this study is to extract a meaningful value through comparison with the existing waterworks statistical results. In addition, the proposed method can be used to effectively respond to consumers or determine the service level of water supply networks. In other words, the presentation of such analysis results suggests the need to inform the public of information such as accidents a little more, and can be used in conjunction to prepare a radio wave and response system that can quickly respond in case of an accident.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.3
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• pp.111-118
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• 2023

Cyber attacks are increasing worldwide, and attacks on personal privacy such as CCTV and IP camera hacking are also increasing. If you search for IP camera hacking methods in spaces such as YouTube, SNS, and the dark web, you can easily get data and hacking programs are also on sale. If you use an IP camera that has vulnerabilities used by hacking programs, you easily get hacked even if you change your password regularly or use a complex password including special characters, uppercase and lowercase letters, and numbers. Although news and media have raised concerns about the security of IP cameras and suggested measures to prevent damage, hacking incidents continue to occur. In order to prevent such hacking damage, it is necessary to identify the cause of the hacking incident and take concrete measures. First, we analyzed weak account settings and web server vulnerabilities of IP cameras, which are the causes of IP camera hacking, and suggested solutions. In addition, as a specific countermeasure against hacking, it is proposed to add a function to receive a notification when an IP camera is connected and a function to save the connection history. If there is such a function, the fact of damage can be recognized immediately, and important data can be left in arresting criminals. Therefore, in this paper, we propose a method to increase the safety from hacking by using the connection notification function and logging function of the IP camera.