• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3D
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• pp.453-459
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• 2006

This paper presents an experimental evaluation of wandering effect on asphalt concrete pavement responses. A laser-based wandering system has been developed and its performance is verified under various field conditions. The portable wandering system composed of two laser sensors with Position Sensitive Devices can allow one to measure the distance between laser sensors and tire edges of moving vehicle. Therefore, lateral position of each wheel on the pavement can be determined in a real time manner. Pavement responses due to different loading paths are investigated using a roll over test which is carried out on one of asphalt surfaced pavements in the Korea Highway Corporation test road. The pavement section (A5) consists of 5 cm thick surface course; 7 cm intermediate course; and 18 mm base course, and is heavily instrumented with strain gauges, vertical soil pressure cells and thermo-couples. From the center of wheel paths, seven equally-spaced lateral loading paths are carefully selected over an 140 cm wandering zone. Test results show that lateral horizontal strains in both surface and intermediate courses are mostly compressive right under the loading path and tensile strains start to develop as the loading offset becomes 40 cm from the wheel path. The development of the vertical stresses in the top layers of subbase and anti-frost is found to be minimal once the loading offset becomes 50 cm.

• Korean Journal of Remote Sensing
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• v.40 no.1
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• pp.33-43
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• 2024

This research assessed the applicability of the You Only Look Once (YOLO)v8 and DeepLabv3+ models for the effective detection of compost heaps, identified as a significant source of non-point source pollution. Utilizing high-resolution imagery acquired through Unmanned Aerial Vehicles(UAVs), the study conducted a comprehensive comparison and analysis of the quantitative and qualitative performances. In the quantitative evaluation, the YOLOv8 model demonstrated superior performance across various metrics, particularly in its ability to accurately distinguish the presence or absence of covers on compost heaps. These outcomes imply that the YOLOv8 model is highly effective in the precise detection and classification of compost heaps, thereby providing a novel approach for assessing the management grades of compost heaps and contributing to non-point source pollution management. This study suggests that utilizing UAVs and deep learning technologies for detecting and managing compost heaps can address the constraints linked to traditional field survey methods, thereby facilitating the establishment of accurate and effective non-point source pollution management strategies, and contributing to the safeguarding of aquatic environments.

• Journal of Environmental Impact Assessment
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• v.32 no.5
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• pp.318-337
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• 2023

This study utilizes system dynamics to examine the effects of fine dust reduction policies on PM10 concentration and health. System dynamics has the advantage of modeling the dynamic and circular relationship between PM₁₀ emission sources, reduction policies, PM₁₀ concentration, and health effect. The study created policy scenarios for Korea's representative fine dust reduction policies - industrial PM₁₀ emission control, diesel vehicle regulation, expansion of electric vehicles, and expansion of parks and green areas - and compared the results with the 2030 baseline if the current trend is maintained. The analysis showed that the policy of supporting electric vehicles reduced PM₁₀ concentration by 0.21 ㎍/m³ and reduced the number of people with circulatory diseases by 494, and the effect was evenly distributed across the country. The industrial emissions regulation scenario resulted in the highest PM₁₀ concentration reduction of 0.22 ㎍/m³, but had a lower reduction in the number of people affected (358) than the EV support strategy, which could be attributed to the fact that this policy had a particularly high PM₁₀ reduction effect in industrial areas such as Danyang-gun, Chungcheongbuk-do, and Sahagu, Busan. As a policy implication, this study suggests that it is necessary to apply fine dust policies tailored to the characteristics of local emission sources.

• Geophysics and Geophysical Exploration
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• v.26 no.4
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• pp.171-184
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• 2023

Machine learning (ML)-based cavity detection using a large amount of survey data obtained from vehicle-mounted ground penetrating radar (GPR) has been actively studied to identify underground cavities. However, only simple image processing techniques have been used for preprocessing the ML input, and many conventional seismic and GPR data processing techniques, which have been used for decades, have not been fully exploited. In this study, based on the idea that a cavity can be identified using diffraction, we applied ML-based diffraction separation to GPR data to increase the accuracy of cavity detection using the YOLO v5 model. The original ML-based seismic diffraction separation technique was modified, and the separated diffraction image was used as the input to train the cavity detection model. The performance of the proposed method was verified using public GPR data released by the Seoul Metropolitan Government. Underground cavities and objects were more accurately detected using separated diffraction images. In the future, the proposed method can be useful in various fields in which GPR surveys are used.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.5
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• pp.1-18
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• 2023

With the recent developments in big data and deep learning, a variety of traffic information is collected widely and used for traffic operations. In particular, long short-term memory (LSTM) is used in the field of traffic information prediction with time series characteristics. Since trends, seasons, and cycles differ due to the nature of time series data input for an LSTM, a trial-and-error method based on characteristics of the data is essential for prediction models based on time series data in order to find hyperparameters. If a methodology is established to find suitable hyperparameters, it is possible to reduce the time spent in constructing high-accuracy models. Therefore, in this study, a traffic information prediction model is developed based on highway vehicle detection system (VDS) data and LSTM, and an impact assessment is conducted through changes in the LSTM evaluation indicators for each hyperparameter. In addition, a methodology for finding hyperparameters suitable for predicting highway traffic information in the transportation field is presented.

• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.4
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• pp.145-160
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• 2023

The purpose of this study was to compare and analyze diurnal thermal environments using Unmanned Aerial Vehicles(UAV)-derived physical parameters(NDVI, SVF) and ENVI-met modeling. The research findings revealed significant correlations, with a significance level of 1%, between UAV-derived NDVI, SVF, and thermal environment elements such as S↑, S↓, L↓, L↑, Land Surface Temperature(LST), and Tmrt. In particular, NDVI showed a strong negative correlation with S↑, reaching a minimum of -0.52^** at 12:00, and exhibited a positive correlation of 0.53^** or higher with L↓ at all times. A significant negative correlation of -0.61^** with LST was observed at 13:00, suggesting the high relevance of NDVI to long-wavelength radiation. Regarding SVF, the results showed a strong relationship with long-wave radiative flux, depending on the SVF range. These research findings offer an integrated approach to evaluating thermal comfort and microclimates in urban areas. Furthermore, they can be applied to understand the impact of urban design and landscape characteristics on pedestrian thermal comfort.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.2
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• pp.142-156
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• 2024

The transition to electric vehicles is a crucial step toward achieving carbon neutrality in the transportation sector. Adequate charging infrastructure at residential locations is essential. In South Korea, the predominant form of housing is multifamily dwellings, necessitating the provision of public charging stations for numerous residents. Although the government mandates the availability of charging facilities and designated parking areas for electric vehicles, it bases the supply of charging stations solely on the number of parking spaces. Slow chargers, mainly 3.5kW charging outlets and 7kW slow chargers, are commonly used. While the former is advantageous for installation and use, its slower charging speed necessitates the coexistence of both types of chargers. This study presents an optimization model that allocates chargers capable of meeting charging demands based on daily driving distances. Furthermore, using the metaheuristic algorithm Tabu Search, this model satisfies the optimization requirements and minimizes the costs associated with charger supply and usage. To conduct a case study, data from personal travel surveys were used to estimate the driving distances, and a hypothetical charging scenario and environment were set up to determine the optimal supply of 22 units of 3.5kW charging outlets for the charging demands of 100 BEVs.

• The Journal of the Acoustical Society of Korea
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• v.26 no.7
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• pp.361-365
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• 2007

Aero-pulsation noise, generally caused by geometric asymmetry of a rotating device, is one of considerable sources of annoyance in passenger cars using the turbocharged diesel engine. Main source of this noise is the compressor wheel in the turbocharger system, and can be reduced by after-treatment devices such as silencers, but which may increase the manufacturing cost. More effective solution is to improve the geometric symmetry over all, or to control the quality of components by sorting out inferior ones. The latter is more simple and reasonable than the former in view of manufacturing. Thus, an appropriate discrimination method should be needed to evaluate aero-pulsation noise level at the production line. In this paper, we introduce the accurate method which can measure the noise level of aero-pulsation and also present its evaluation criteria. Besides verifying the reliability of a measurement system - a rig test system-, we analyze the correlation between the results from rig tests and those from vehicle tests. The gage R&R method is carried out to check the repeatability of measurements over 25 samples. From the result, we propose the standard specification which can discriminate inferior products from superior ones on the basis of aero-pulsation noise level.

• Journal of Trauma and Injury
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• v.37 no.1
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• pp.48-59
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• 2024

Purpose: Research on rib fracture management has exponentially increased. Predicting fracture patterns based on the mechanism of injury (MOI) and other possible correlations may improve resource allocation and injury prevention strategies. The Chest Injury International Database (CIID) is the largest prospective repository of the operative and nonoperative management of patients with severe chest wall trauma. The purpose of this study was to determine whether the MOI is associated with the resulting rib fracture patterns. We hypothesized that specific MOIs would be associated with distinct rib fracture patterns. Methods: The CIID was queried to analyze fracture patterns based on the MOI. Patients were stratified by MOI: falls, motor vehicle collisions (MVCs), motorcycle collisions (MCCs), automobile-pedestrian collisions, and bicycle collisions. Fracture locations, associated injuries, and patient-specific variables were recorded. Heat maps were created to display the fracture incidence by rib location. Results: The study cohort consisted of 1,121 patients with a median RibScore of 2 (range, 0-3) and 9,353 fractures. The average age was 57±20 years, and 64% of patients were male. By MOI, the number of patients and fractures were as follows: falls (474 patients, 3,360 fractures), MVCs (353 patients, 3,268 fractures), MCCs (165 patients, 1,505 fractures), automobile-pedestrian collisions (70 patients, 713 fractures), and bicycle collisions (59 patients, 507 fractures). The most commonly injured rib was the sixth rib, and the most common fracture location was lateral. Statistically significant differences in the location and patterns of fractures were identified comparing each MOI, except for MCCs versus bicycle collisions. Conclusions: Different mechanisms of injury result in distinct rib fracture patterns. These different patterns should be considered in the workup and management of patients with thoracic injuries. Given these significant differences, future studies should account for both fracture location and the MOI to better define what populations benefit from surgical versus nonoperative management.

• Journal of Korean Medicine for Obesity Research
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• v.24 no.1
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• pp.87-93
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• 2024

Objectives: Obesity is a globally prevalent public health issue. Hence, there is a need for the development of safer and more effective anti-obesity drugs. Lythrum salicaria, a traditional medicinal herb used for centuries, has been reported to improve lipid metabolism and fat accumulation. It also has a low toxicity profile. Therefore, its potential as a functional ingredient in health functional foods needs to be evaluated. Methods: In this randomized, double-blind, placebo-controlled clinical trial, 90 participants will be randomly assigned to either the experimental or control group. Each subject will orally receive L. salicaria extract (1,350 mg/day) (500 mg L. salicaria+850 mg lactose as vehicle) or lactose (1,350 mg/day) as a hard capsule formula for 84 days (12 weeks). The primary outcome will be body fat mass (kg), which will be assessed using dual-energy x-ray absorptiometry (DXA) (performed only at visits 2 and 4). Secondary outcomes include body mass index, body weight, waist-to-hip ratio, body fat percentage (%) measured using DXA, lean body mass (kg) measured using DXA (assessed only at visits 2 and 4), lipids (total cholesterol, triglyceride, high-density lipoprotein cholesterol, and calculated low-density lipoprotein cholesterol), free fatty acid, high sensitivity C-reactive protein, adiponectin, and leptin. Conclusions: This protocol will be implemented after approval of Institutional Review Board of Pusan National University Korean Medicine Hospital (approval number: PNUKHIRB-2022-08-002) and registration with the Korean National Clinical Research Information Service (CRIS) (CRIS-KCT0008060). The results of this trial will provide potential of L. salicaria as a new anti-obesity functional food with fat-reducing effects and low toxicity.