• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.1
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• pp.219-232
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• 2023

Mobility services need to change according to the regional characteristics of the target service area. Accordingly, analysis of mobility patterns and characteristics based on Origin-Destination (OD) data that reflect travel behaviors in the target service area is required. However, since conventional methods construct the OD data obtained from the administrative district-based zone system, it is hard to ensure spatial homogeneity. Hence, there are limitations in analyzing the inherent travel patterns of each mobility service, particularly for new mobility service like Demand Responsive Transit (DRT). Unlike the conventional approach, this study applies a data-driven clustering technique to conduct spatial analyses on OD travel patterns of regional mobility services based on reconstructed OD data derived from re-aggregation for original OD distributions. Based on the reconstructed OD data that contains information on the inherent feature vectors of the original OD data, the proposed method enables analysis of the spatial characteristics of regional mobility services, including public transit bus, taxi and DRT.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.3
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• pp.62-72
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• 2023

Recently, the importance of monitoring and management measures for bicycle road related facilities has been increasing. However, research on the monitoring and evaluation of users' safety and convenience in walking spaces including bicycle path is insufficient. In this study, we would like to construct health monitoring data for cylists-pedestrians mixed road using a mobile mapping system, and propose a plan to calculate the level of service of the mixed roads from the perspective of pedestrians and cyclists using artificial intelligence based object detection techniques. The monitoring and level of service calculation method of cylists-pedestrians mixed roads proposed in this study is expected to be used as basic information for planning and management such as maintenance and reconstruction of walking spaces in preparation for the increase of electric bicycles and personal mobility in the future.

• Convergence Security Journal
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• v.22 no.1
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• pp.39-54
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• 2022

Recently, the importance of collecting, analyzing, and real-time sharing of various cybersecurity data has emerged in order to effectively respond to intelligent and advanced cyber threats. To cope with this situation, Korea is making efforts to expand its cybersecurity data sharing system, but many private companies are unable to participate in the cybersecurity data sharing system due to a lack of budget and professionals to collect cybersecurity data. In order to solve such problems, this paper analyzes the research and development trends of existing domestic and foreign cyber security data sharing systems, and based on that, propose a cybersecurity data sharing system model with a hierarchical structure that considers the size of the organization and a step-by-step security policy that can be applied to the model. In the case of applying the model proposed in this paper, it is expected that various private companies can expand their participation in cybersecurity data sharing systems and use them to prepare a response system to respond quickly to intelligent security threats.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.5
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• pp.137-147
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• 2023

LiDAR is used in autonomous driving and various industrial fields to measure the size and distance of an object. In addition, the sensor also provides intensity images based on the amount of reflected light. This has a positive effect on sensor data processing by providing information on the shape of the object. LiDAR guarantees higher performance as the resolution increases but at an increased cost. These conditions also apply to LiDAR intensity images. Expensive equipment is essential to acquire high-resolution LiDAR intensity images. This study developed artificial intelligence to improve low-resolution LiDAR intensity images into high-resolution ones. Therefore, this study performed parameter analysis for the optimal super-resolution neural network model. The super-resolution algorithm was trained and verified using 2,500 LiDAR intensity images. As a result, the resolution of the intensity images were improved. These results can be applied to the autonomous driving field and help improve driving environment recognition and obstacle detection performance

• Journal of Korean Society of Rural Planning
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• v.29 no.4
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• pp.27-34
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• 2023

Recently, worldwide to respond to climate change and secure sustainability. Korea aimed to increase water use efficiency by implementing integrated management according to the water management unification policy. Therefore, the necessity of establishing and operating governance is expanding to ensure the sustainability of agricultural water. In this study aims to evaluate the importance of agricultural water governance components and provide essential data for the participation of stakeholders in the efficient use of agricultural water in Korea. For this study, a total of 19 respondents to the ANP survey for this study were composed of experts in agricultural water and governance in Korea. As a result, the ranking for the main components was in the order of law, policy, and systems(0.222), core subjects(0.191), information sharing and communication(0.180), budget support(0.178), mutual learning(0.124), and external experts(0.105). The most important components for the operation of agricultural water governance are laws, policies, and systems. Since Korea's agricultural water management is a public management system, national standards are considered the first priority. This study, which is the purpose of the agricultural water governance model, evaluated the importance of the constituent components for participating in demand management with a sense of responsibility. Moreover, if agricultural water governance is expanded nationwide by reflecting agricultural and water resource policies in the future, it is believed that positive effects can be achieved in increasing utilization efficiency and securing sustainability through agricultural water saving.

• Journal of Korean Society of Rural Planning
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• v.29 no.4
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• pp.211-219
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• 2023

In this study, the importance of each design element was analyzed by surveying experts in the development of Agro-Healing Virtual Reality Therapy System. It was found that the results of experts content importance were consistent with the results of consumer preferences in previous studies, such as psychological and emotional stability as the main effect the importance of sight and hearing, a relatively short time of 30 minutes or less, a low price of 5,000 won or less, technical factors that can satisfy the five senses, and various contents. When the spatial elements of the Agro-Healing Virtual Reality Therapy System were categorized into three major categories: elements and equipment, lines and paths, and sites and spaces, 'flowers', 'playgrounds', 'paths', 'sidewalks', 'rest areas' and 'gardens' were found to be highly important. Among the components of Agro-Healing Virtual Reality Therapy System, the usability was divided into eight major categories, including searchability, attractiveness, cognition, error handling, control, consistency, convenience, and feedback, and the importance was analyzed for each component. The significance of this study is that it suggests the design direction of virtual healing farm systems and provides effective information that can be used in the development of related systems in the future.

• Journal of Internet of Things and Convergence
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• v.10 no.2
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• pp.109-114
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• 2024

Enterprise storage systems that require high data reliability are applying RAID (Redundant Array of Independent Disks) systems to recover from data loss and failure. In particular, RAID 5 ensures space efficiency and reliability by distributing parity across multiple storage devices. However, when storage devices have different capacities, RAID is built based on the smallest capacity storage device, resulting in wasted storage space. Therefore, research is needed to solve this resource management problem. In this paper, we propose a method for RAID grouping of each independent NAND flash memory block in a RAID consisting of SSD (Solid State Disk) with external SSDs as well as internal SSDs. This method is divided into a policy for delivering block information inside SSDs to the RAID system and a policy for RAID grouping of physical addresses delivered from the RAID system. This method allows us to maintain a RAID that does not waste resources when SSDs of different capacities are grouped into RAID5. Finally, we demonstrate the effectiveness of the proposed method through experiments.

• Journal of The Korean Society of Agricultural Engineers
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• v.66 no.4
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• pp.1-15
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• 2024

In recent years, climate change has been responsible for unusual weather patterns on a global scale. Droughts, natural disasters triggered by insufficient rainfall, can inflict significant social and economic consequences on the entire agricultural sector due to their widespread occurrence and the challenge in accurately predicting their onset. The frequency of drought occurrences in South Korea has been rapidly increasing since 2000, with notably severe droughts hitting regions such as Incheon, Gyeonggi, Gangwon, Chungbuk, and Gyeongbuk in 2015, resulting in significant agricultural and social damage. To prepare for future drought occurrences resulting from climate change, it is essential to develop long-term drought predictions and implement corresponding measures for areas prone to drought. The Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report outlines a climate change scenario under the Shared Socioeconomic Pathways (SSPs), which integrates projected future socio-economic changes and climate change mitigation efforts derived from the Coupled Model Intercomparison Project 6 (CMIP6). SSPs encompass a range of factors including demographics, economic development, ecosystems, institutions, technological advancements, and policy frameworks. In this study, various drought indices were calculated using SSP scenarios derived from 18 CMIP6 global climate models. The SSP5-8.5 scenario was employed as the climate change scenario, and meteorological drought indices such as the Standardized Precipitation Index (SPI), Self-Calibrating Effective Drought Index (scEDI), and Standardized Precipitation Evapotranspiration Index (SPEI) were utilized to analyze the prediction and variability of future drought occurrences in South Korea.

• Industry Promotion Research
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• v.9 no.1
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• pp.57-64
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• 2024

In 2015, the paradigm of hazardous chemical substance management in Korea shifted from the workplace to the regional level due to the complete revision of the Chemicals Control Act. Although regional chemical accident response plans were established in 2020, there were slight differences in the scope and criteria of each local government. Therefore, this study compared and analyzed chemical accident response plans established in four different regions to provide insights into effective chemical accident response plans. Based on publicly available information, the current status of accident preparedness, chemical accident response systems, and resident evacuation response and education/training were compared and analyzed. The results showed that there were not significant differences in the accident preparedness and response systems between the regions. However, there was a lack of discussion on the preparedness system linked to the characteristics of each workplace in each region. Additionally, there were differences in education and training for residents between regions. In the future, each local government needs to establish a response organization that fits the characteristics of their region and develop strategies for agile and effective accident response through cooperation with relevant agencies.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.6
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• pp.17-31
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• 2023

An activity-based model requires detailed population information to model individual travel behavior in a disaggregated manner. The recent innovative approach developed deep generative models with novel regularization terms that improves fidelity and diversity for population synthesis. Since the method relies on measuring the distance between distribution boundaries of the sample data and the generated sample, it is crucial to obtain well-defined continuous representation from the discretized dataset. Therefore, we propose an improved entity embedding models to enhance the performance of the regularization terms, which indirectly supports the synthesis in terms of feasible and diverse populations. Our results show a 28.87% improvement in the F1 score compared to the baseline method.