• Korea Science and Art Forum
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• v.27
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• pp.101-114
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• 2017

Based on the relationship between urban public space, urban lighting and the sense of place, this paper aims to analyze the lighting environment types with the sense of place and their characteristics. First, with the theory study as the research foundation, it extracts six spatial factors of public space lighting design and then analyzes 12 relevant cases on the basis. Finally, it divides the 12 cases into four types, Basic types, Storytelling, Interactive and Multi-Media and analyzes the core design factor and characteristics of various types. The results show that: first, functionality, sustainability and aesthetics are the basic factors to realize the urban public space lighting places. Second, the six cases of "Storytelling" show that the theme of specific areas, namely the exploration of "story" is conducive for lighting design to form clear and definite environment recognition. Third, for "Interactive" and "Multi-Media", the intervention of new media technology and new lighting way has made the wide expansion of urban lighting design connotation and extension. The research results show that strengthening the urban location performance by the lighting design could improve the city image, which provides the basis for the development of urban public space lighting design.

• Journal of The Korean Association For Science Education
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• v.43 no.3
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• pp.237-251
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• 2023

This study explores the possibility of automated scoring for scientific graph answers by designing an automated scoring model using convolutional neural networks and applying it to students' kinematics graph answers. The researchers prepared 2,200 answers, which were divided into 2,000 training data and 200 validation data. Additionally, 202 student answers were divided into 100 training data and 102 test data. First, in the process of designing an automated scoring model and validating its performance, the automated scoring model was optimized for graph image classification using the answer dataset prepared by the researchers. Next, the automated scoring model was trained using various types of training datasets, and it was used to score the student test dataset. The performance of the automated scoring model has been improved as the amount of training data increased in amount and diversity. Finally, compared to human scoring, the accuracy was 97.06%, the kappa coefficient was 0.957, and the weighted kappa coefficient was 0.968. On the other hand, in the case of answer types that were not included in the training data, the s coring was almos t identical among human s corers however, the automated scoring model performed inaccurately.

• Industry Promotion Research
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• v.8 no.3
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• pp.181-199
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• 2023

E-commerce is gradually upgrading from traditional text and image formats to short video and livestreaming formats. Livestreaming e-commerce enriches the content and forms of information dissemination and product display, enhances the consumer's shopping experience, and gradually becomes the mainstream new consumer scene. However, there are many negative phenomena in the development of livestreaming e-commerce, such as false propaganda, counterfeit goods, and various negative events, which seriously affect the level of consumer trust in livestreaming e-commerce. Trust is the core competitive factor of livestreaming e-commerce. Based on previous research on trust theory and combined with the characteristic elements of "people, goods, and scenes" of livestreaming e-commerce, this article constructs a trust model for livestreaming e-commerce, proposes hypotheses, and proves through empirical research that factors such as store characteristics, livestream host characteristics, brand image, product information, platform reputation, livestreaming situation, and trust tendency have a significant positive impact on consumer trust. Based on the research conclusions, this article provides insights and management suggestions, such as emphasizing the construction of store characteristic indicators, creating desirable livestream host characteristics, focusing on product brand building and selection, maintaining the display of product information, selecting suitable livestreaming platforms, and creating rich content for livestreaming situations.

• The Journal of Bigdata
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• v.7 no.1
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• pp.15-27
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• 2022

In the past five years, the fatality rate of single-vehicle accidents has been 4.7 times higher than that of all accidents, so it is necessary to establish a system that can detect and respond to single-vehicle accidents immediately. The IoT(Internet of Thing)-based real-time traffic accident recognition system proposed in this study is as following. By attaching an IoT sensor which detects the impact and vehicle ingress to the guardrail, when an impact occurs to the guardrail, the image of the accident site is analyzed through artificial intelligence technology and transmitted to a rescue organization to perform quick rescue operations to damage minimization. An IoT sensor module that recognizes vehicles entering the monitoring area and detects the impact of a guardrail and an AI-based object detection module based on vehicle image data learning were implemented. In addition, a monitoring and operation module that imanages sensor information and image data in integrate was also implemented. For the validation of the system, it was confirmed that the target values were all met by measuring the shock detection transmission speed, the object detection accuracy of vehicles and people, and the sensor failure detection accuracy. In the future, we plan to apply it to actual roads to verify the validity using real data and to commercialize it. This system will contribute to improving road safety.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.3D
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• pp.205-213
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• 2010

The unsignalized intersections in a community road in the city of Seoul have 3,753 traffic accidents(9%) of total 41,702 cases in 2008, not high in the occurrence rate of traffic accidents, but seem to have a quite high potential of accidents due to the unreasonable and insufficient operation of systems and facilities in the part of traffic foundations. In particular, the un-signalized intersections in a community road have an insufficient measure for safety as compared to the crossroads with signals, and there are few analysis of traffic accidents and domestic researches on the model of affecting factors. Our country also has no concept of passing priority in operating a crossroad without signals, differently from foreign countries, so the researches and safety measures for improving the safety of a crossroad without signals in a community road are urgent. Therefore, this research has developed a safety model for a crossroad without signals in a community road based on the safety image data collected through individual interviews and questionnaires for the users of unsignalized intersections in a community road, and confirmed that legal systems, road facilities, personal factors, etc. have the biggest effect on the safety of drivers. It was confirmed that the clarity of passing methods, establishment of legal systems, etc. have the biggest effect on safety in order to raise the safety of unsignalized intersections in a community road, which drivers desire.

• Journal of Korea Entertainment Industry Association
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• v.13 no.6
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• pp.187-202
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• 2019

The main goal of this study is to investigate influence of trust in physical education (PE) teachers and immersion experience in PE classes on attitude and satisfaction during PE classes. Total 863 middle school students in Gwang-ju metropolitan area were recruited by utilizing a convenience sampling method. All data were analyzed by using SPSS statistic program ver. 25.0 (frequency analysis, exploratory factor analysis, reliability analysis, correlation analysis, multiple regression analysis). Alpha was set at 0.05. The results of this study is summarized as in the following. First, all sub-factors of trust in the PE teachers partially positively or negatively influence sub-factors of attitude during PE classes. Second, sub-factors of satisfaction during PE classes were partially positively affected to trust in the PE teachers. Third, Attitude during PE Classes were found to have partial positive influence on immersion experience in PE classes. Fourth, sub-factors of immersion experience in PE classes have partial positive effect on the sub-factors of satisfaction during PE classes. Thus, in order to the positive attitude and greater satisfaction during PE classes, it is important to establish the trust of PE teachers through maintaining interaction with students, constructing better systemic class, and creating the class conditions based on considering students' ability. In addition, in order to enhance immersion experiences of students during PE classes, it is necessary to set up learning goals and tasks based on ability of students, to study various teaching method, and to make only focusing on the performance based PE classes without grading.

• Asia Marketing Journal
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• v.9 no.2
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• pp.49-95
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• 2007

The "cause-related marketing (CRM)," generally defined as a mutually beneficial relationship between a company and a non-profit relationship or a social cause, which is perhaps the most progressive outgrowth of marketing trend. This paper contributes to, and looks at the practical issues of CRM and its effect on the brand attitude of the customer. To do so, following three broad research questions have been addressed. Which cause-related orientation is effective on customer's attitude of the brand? Which type of cause-related message provides crucial impact on customer's attitude of the brand? How product category acts upon and brings about different consequences on CRM? To address these questions, a causal model has been developed incorporating message type, product relevance, social significance, and brand attitude. The study model was tested with survey data collected from 400 career professionals and students in Seoul and statistically processed the 176 valid ones. The results of the study considerably supported the conceptual model. The analysis also revealed that the study population was not able to detect the differences in CRM strategies but tend to conceptualize them as a whole.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.6
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• pp.1099-1110
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• 2023

The recognition system of autonomous driving and robot navigation performs vision work such as object recognition, tracking, and lane detection after multi-sensor fusion to improve performance. Currently, research on a deep learning model based on the fusion of a camera and a lidar sensor is being actively conducted. However, deep learning models are vulnerable to adversarial attacks through modulation of input data. Attacks on the existing multi-sensor-based autonomous driving recognition system are focused on inducing obstacle detection by lowering the confidence score of the object recognition model.However, there is a limitation that an attack is possible only in the target model. In the case of attacks on the sensor fusion stage, errors in vision work after fusion can be cascaded, and this risk needs to be considered. In addition, an attack on LIDAR's point cloud data, which is difficult to judge visually, makes it difficult to determine whether it is an attack. In this study, image scaling-based camera-lidar We propose an attack method that reduces the accuracy of LCCNet, a fusion model (camera-LiDAR calibration model). The proposed method is to perform a scaling attack on the point of the input lidar. As a result of conducting an attack performance experiment by size with a scaling algorithm, an average of more than 77% of fusion errors were caused.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.119-125
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• 2023

Through the Ukraine-Russia war, the military importance of drones is being reassessed, and North Korea has completed actual verification through a drone provocation towards South Korea at 2022. Furthermore, North Korea is actively integrating artificial intelligence (AI) technology into drones, highlighting the increasing threat posed by drones. In response, the Republic of Korea military has established Drone Operations Command(DOC) and implemented various drone defense systems. However, there is a concern that the efforts to enhance capabilities are disproportionately focused on striking systems, making it challenging to effectively counter swarm drone attacks. Particularly, Air Force bases located adjacent to urban areas face significant limitations in the use of traditional air defense weapons due to concerns about civilian casualties. Therefore, this study proposes a new passive air defense method that aims at disrupting the object detection capabilities of AI models to enhance the survivability of friendly aircraft against the threat posed by AI based swarm drones. Using laser-based adversarial examples, the study seeks to degrade the recognition accuracy of object recognition AI installed on enemy drones. Experimental results using synthetic images and precision-reduced models confirmed that the proposed method decreased the recognition accuracy of object recognition AI, which was initially approximately 95%, to around 0-15% after the application of the proposed method, thereby validating the effectiveness of the proposed method.

• Applied Chemistry for Engineering
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• v.34 no.6
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• pp.674-678
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• 2023

The effect of Pt was investigated to the catalytic methane decomposition of CH₄ to H₂ over Pt(1)-Fe(30)/MCM-41 and Fe(30)/MCM-41 using a fixed bed flow reactor under atmosphere. The Fe₂O₃ and Pt crystal phase behavior of fresh Pt(1)-Fe(30)/MCM-41 were obtained via XRD analysis. SEM, EDS analysis, and mapping were performed to show the uniformed distribution of nano particles such as Fe, Pt, Si, O on the catalyst surface. XPS results showed O^2-, O^- species and metal ions such as Pt⁰, Pt²⁺, Pt⁴⁺, Ft⁰, Fe²⁺, Fe³⁺ etc. When 1 wt% of Pt was added to Fe(30)/MCM-41, automic percentage of Fe2p increased from 13.39% to 16.14%, and Pt4f was 1.51%. The yield of hydrogen over Pt(1)-Fe(30)/MCM-41 was 3.2 times higher than Fe(30)/MCM-41. The spillover effect of H₂ from Pt to Fe increased the reduction of Fe particles and moderate interaction of Fe, Pt and MCM-41 increased the uniform dispersion of fine nanoparticles on the catalyst surface, and improved hydrogen yield.