• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.17 no.6
• /
• pp.173-184
• /
• 2018

As the portable traffic information collection system using probe vehicles spreads, it is becoming possible to collect road hazard information such as portholes, falling objects, and road surface freezing using in-vehicle sensors in addition to existing traffic information. In this study, we developed a integration and decision algorithm that integrates time and space in real time when multiple probe vehicles detect events such as road hazard information based on GPS coordinates. The core function of the algorithm is to determine whether the road hazard information generated at a specific point is the same point from the result of detecting multiple GPS probes with different GPS coordinates, Generating the data, (3) continuously determining whether the generated event data is valid, and (4) ending the event when the road hazard situation ends. For this purpose, the road risk information collected by the probe vehicle was processed in real time to achieve the conditional probability, and the validity of the event was verified by continuously updating the road risk information collected by the probe vehicle. It is considered that the developed hybrid processing algorithm can be applied to probe-based traffic information collection and event information processing such as C-ITS and autonomous driving car in the future.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.19 no.12
• /
• pp.872-877
• /
• 2018

STEAM is an acronym for Science, Technology, Engineering, Arts, and Mathematics. It is considered important to equip students with a creative thinking ability and the core competences required in future society, helping them devise new ideas emerging from branches of study. This study is about the convergence of instructional design in private finance for the life sciences, which aims to foster talent through problem-based learning (PBL). Skills like collaboration, creativity, critical thinking, and problem solving are part of any STEAM PBL, and are needed for students to be effective. STEAM projects give students a chance to problem-solve in unique ways, because they are forced to use a variety of methods to solve problems that pop up during these types of activities. The results of this study are as follows. First is the structured process of convergence lessons. Second is the convergence lesson process. Third is the development of problems in the introduction of private finance and the life sciences for a convergence lesson at Dornod University. Learning motivation shows the following results: understanding of learning content (66.6%), effectiveness (63.3%), self-directed learning (59.9%), motivation (63.2%), and confidence (63.3%). To make an effective model, studies applying this instructional design are to be implemented.

• Science of Emotion and Sensibility
• /
• v.24 no.1
• /
• pp.59-72
• /
• 2021

Concepts and categories offer the basis for inference pertaining to unobserved features. Prior research on category-based induction that used blank properties has suggested that similarity between categories and features explains feature inference (Rips, 1975; Osherson et al., 1990). However, it was shown by later research that prior knowledge had a large influence on category-based inference and cases were reported where similarity effects completely disappeared. Thus, this study tested category-based feature inference when features are connected in a causal chain and proposed a feature inference model that predicts participants' inference ratings. Each participant learned a category with four features connected in a causal chain and then performed feature inference tasks for an unobserved feature in various exemplars of the category. The results revealed nonindependence, that is, the features not only linked directly to the target feature but also to those screened-off by other feature nodes and affected feature inference (a violation of the causal Markov condition). Feature inference model of causal model theory (Sloman, 2005) explained nonindependence by predicting the effects of directly linked features and indirectly related features. Indirect features equally affected participants' inference regardless of causal distance, and the model predicted smaller effects regarding causally distant features.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.21 no.5
• /
• pp.59-69
• /
• 2011

Since power analysis attack which uses a characteristic that power consumed by crypto device depends on processed data has been proposed, many logics that can block these correlation originally have been developed. DRP logic has been adopted by most of logics maintains power consumption balanced and reduces correlation between processed data and power consumption. However, semi-custom design is necessary because recently design circuits become more complex than before. This design method causes unbalanced design pattern that makes DRP logic consumes unbalanced power consumption which is vulnerable to power analysis attack. In this paper, we have developed new logic style which adds another discharge phase to discharge two output nodes at the same time based on DyCML to remove this unbalanced power consumption. Also, we simulated 1bit fulladder to compare proposed logic with other logics to prove improved performance. As a result, proposed logic is improved NED and NSD to 60% and power consumption reduces about 55% than any other logics.

• The Journal of the Korea Contents Association
• /
• v.22 no.6
• /
• pp.24-34
• /
• 2022

Viewing religion as contents, we analyzed the network structure by creating networks on 13 world religions. The whole network was constructed by combining 13 religions, and it showed the characteristics of a scale-free network as a general social network. The world religion network had a very small value of clustering coefficient, unlike the general social network. This seems to be the result of the diversity of terms that describe religion. The core network was constructed by applying K-core algorithm used to create the core network to the whole network. When k-3 was applied, it was too complicated but when k-4 was applied, it was too simple to obtain meaningful results. It indicates that it difficult to apply the K-core algorithm to a network containing a low clustering coefficient. Therefore, core networks were constructed according to the number of key words centered on the hub node to analyze the characteristics of world religions. In addition, meaningful information was derived by constructing the world's five major religious networks and East Asian religious networks. In this study, various information was obtained by analyzing world religions as contents. It was also presented a method of creating and analyzing a core network based on key words for networks with a low clustering coefficient.

• Journal of Convergence for Information Technology
• /
• v.11 no.5
• /
• pp.30-37
• /
• 2021

Various devices are connected to the Internet, and attacks using the Internet are occurring. Among such attacks, there are attacks that use malicious URLs to make users access to wrong phishing sites or distribute malicious viruses. Therefore, how to detect such malicious URL attacks is one of the important security issues. Among recent deep learning technologies, neural networks are showing good performance in image recognition, speech recognition, and pattern recognition. This neural network can be applied to research that analyzes and detects patterns of malicious URL characteristics. In this paper, performance analysis according to various parameters was performed on a method of detecting malicious URLs using neural networks. In this paper, malicious URL detection performance was analyzed while changing the activation function, learning rate, and neural network structure. The experimental data was crawled by Alexa top 1 million and Whois to build the data, and the machine learning library used TensorFlow. As a result of the experiment, when the number of layers is 4, the learning rate is 0.005, and the number of nodes in each layer is 100, the accuracy of 97.8% and the f1 score of 92.94% are obtained.

• Korean Journal of Psychosomatic Medicine
• /
• v.30 no.2
• /
• pp.172-178
• /
• 2022

Objectives : Although subclinical depression symptoms are associated with suicidal idea, most research have focused on clinical depression such as major depressive disorder or dysthymia. The aim of this study is to investigate network structure of depressive symptom and to reveal which symptoms are associated with suicidal ideation. Methods : We used part of data from the seventh Korea National Health and Nutrition Examination Survey. Participants were between 19 and 65 years of age (N=8,741). Network analysis with Isingfit model is used to reveal network structure of depressive symptoms and most central symptom and edges assessed by patient health questionnaire (PHQ-9). Results : The most two central symptoms were psychomotor activity and suicidal ideation. The strongest edge was psychomotor activity-suicidal ideation. Suicidal ideation also has strong association with depressive mood and worthlessness. Conclusions : These results suggest that psychomotor activity and suicidal ideation can serve as treatment target for subclinical depression and psychomotor activity, worthlessness and depressed mood may be important factor for early intervention of suicidal ideation.

• Journal of the Korea Society of Computer and Information
• /
• v.27 no.12
• /
• pp.131-139
• /
• 2022

In this paper, to verify the authenticity of UxNB that assists terrestrial base stations, the solutions for SI (System Information) security presented in 3GPP TR 33.809 are analyzed from the perspective of UxNB. According to the definition of 3GPP (Third Generation Partnership Project), UxNB is a base station mounted on a UAV (Unmanned Aerial Vehicle), is carried in the air by the UAV, and is a radio access node that provides a connection to the UE (User Equipment). Such solutions for SI security can be classified into hash based, MAC (Message Authentication Codes) based, and digital signature based, and a representative solution for each category is introduced one by one. From the perspective of verifying the authenticity of UxNB for each solution, we compare and analyze the solutions in terms of provisioning information and update, security information leakage of UxNB, and additionally required amount of computation and transmission. As a result of the analysis, the solution for verifying the authenticity of the UxNB should minimize the secret information to be stored in the UxNB, be stored in a secure place, and apply encryption when it is updated over the air. In addition, due to the properties of the low computing power of UxNB and the lack of power, it is necessary to minimize the amount of computation and transmission.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2023.05a
• /
• pp.356-356
• /
• 2023

충청북도 청주시 상당구 월오동 251-7번지와 251-15번지 2곳에 각각 50m³ 규모의 빗물저류조를 대상으로 2017년 7월 16일 호우사상을 적용하여 설치 전·후의 침수저감 효과를 분석하였다. 침수분석을 위해 지형자료는 국토정보플랫폼에 있는 1:25,000 자료를 활용하였으며, 모의 전 대상지역의 관망구축에 따른 지형자료를 구축하였고 관망은 노드 40개와 링크 39개로 구성하였다. SWMM 모형을 구동하여 유역내 유출량을 분석하기 위해 유역과 관련한 입력자료와 이외 유역간의 연결부인 관거 하도 입력자료 구축 및 하도와 하도를 연결하는 모델상의 Junction인 실제 맨홀과 관련한 입력자료를 구축하였다. 관거 입력자료로는 관거의 제원, 길이, 깊이 등의 자료를 수집하여 사용하였다. 빗물저류조 설치전·후의 침수저감효과를 분석하기 위해 빗물저류조 설치전의 침수양상을 모의 하였으며 각각 강우발생 후 30분, 50분, 70분, 90분, 110분, 130분 및 150분으로 구분하여 분석하였다. 강우발생 후 150분의 모의분석 결과, 침수심은 0.2<깊이<0.4의 면적이 600m²로 가장 넓은 침수분포를 나타내었으며, 총 침수면적은 2,225m²로 모의되었다. 이는 강우발생 후130분 보다 125m² 더 침수되었으며, 0.8<깊이<1.0의 면적은 150m²로 모의되었다. 전체적인 침수심도 커진 것으로 분석되었다. 빗물저류조 설치 후의 침수양상을 모의하였으며 각각 강우발생 후 30분, 50분, 70분, 90분, 110분, 130분 및 150분으로 분석하였다. 강우발생 후 150분의 모의분석 결과, 침수심은 0.2<깊이<0.4의 면적이 250m²로 가장 많은 침수분포가 나타났으며, 총 침수면적은 550m²으로 모의 되었다. 이는 강우발생 후 110분과 침수면적은 동일하게 모의 되었으며, 침수심 0.2<깊이<0.4의 면적은 250m²로 모의 되었다. 따라서 해당 지역에 50m³ 규모의 빗물저류조 2개를설치 할 경우 침수피해가 저감되는 것으로 분석되었다. 이러한 분석 결과를 바탕으로 향후 도시내 상습침수구역에 빗물저류조를 설치하여 기후변화에 따른 극한 강우에 대비할 수 있도록 해야 할 것이다.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.36 no.3
• /
• pp.155-163
• /
• 2023

Real-time monitoring technology is critical for ensuring the safety and reliability of nuclear power plant structures. However, the current seismic monitoring system has limited system identification capabilities such as modal parameter estimation. To obtain global behavior data and dynamic characteristics, multiple sensors must be optimally placed. Although several studies on optimal sensor placement have been conducted, they have primarily focused on civil and mechanical structures. Nuclear power plant structures require robust signals, even at low signal-to-noise ratios, and the robustness of each mode must be assessed separately. This is because the mode contributions of nuclear power plant containment buildings are concentrated in low-order modes. Therefore, this study proposes an optimal sensor placement methodology that can evaluate robustness against noise and the effects of each mode. Indicators, such as auto modal assurance criterion (MAC), cross MAC, and mode shape distribution by node were analyzed, and the suitability of the methodology was verified through numerical analysis.