• Journal of the Korean Society of Environmental Restoration Technology
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• v.26 no.5
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• pp.19-32
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• 2023

The fragmentation of habitats resulting from human activities leads to the isolation of wildlife and it also causes wildlife-vehicle collisions (i.e. Road-kill). In that sense, it is important to predict potential habitats of specific wildlife that causes wildlife-vehicle collisions by considering geographic, environmental and transportation variables. Road-kill, especially by large mammals, threatens human safety as well as financial losses. Therefore, we conducted this study on roe deer (Capreolus pygargus tianschanicus), a large mammal that causes frequently Road-kill in Jeju Island. So, to predict potential wildlife habitats by considering geographic, environmental, and transportation variables for a specific species this study was conducted to identify high-priority restoration sites with both characteristics of potential habitats and road-kill hotspot. we identified high-priority restoration sites that is likely to be potential habitats, and also identified the known location of a Road-kill records. For this purpose, first, we defined the environmental variables and collect the occurrence records of roe deer. After that, the potential habitat map was generated by using Random Forest model. Second, to analyze roadkill hotspots, a kernel density estimation was used to generate a hotspot map. Third, to define high-priority restoration sites, each map was normalized and overlaid. As a result, three northern regions roads and two southern regions roads of Jeju Island were defined as high-priority restoration sites. Regarding Random Forest modeling, in the case of environmental variables, The importace was found to be a lot in the order of distance from the Oreum, elevation, distance from forest edge(outside) and distance from waterbody. The AUC(Area under the curve) value, which means discrimination capacity, was found to be 0.973 and support the statistical accuracy of prediction result. As a result of predicting the habitat of C. pygargus, it was found to be mainly distributed in forests, agricultural lands, and grasslands, indicating that it supported the results of previous studies.

• Journal of Soil and Groundwater Environment
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• v.28 no.6
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• pp.71-89
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• 2023

A groundwater potential map (GPM) was built for the Nakdonggang River Basin based on ten variables, including hydrogeologic unit, fault-line density, depth to groundwater, distance to surface water, lineament density, slope, stream drainage density, soil drainage, land cover, and annual rainfall. To integrate the thematic layers for GPM, the criteria were first weighted using the Analytic Hierarchical Process (AHP) and then overlaid using the Technique for Ordering Preferences by Similarity to Ideal Solution (TOPSIS) model. Finally, the groundwater potential was categorized into five classes (very high (VH), high (H), moderate (M), low (L), very low (VL)) and verified by examining the specific capacity of individual wells on each class. The wells in the area categorized as VH showed the highest median specific capacity (5.2 m³/day/m), while the wells with specific capacity < 1.39 m³/day/m were distributed in the areas categorized as L or VL. The accuracy of GPM generated in the work looked acceptable, although the specific capacity data were not enough to verify GPM in the studied large watershed. To create GPMs for the determination of high-yield well locations, the resolution and reliability of thematic maps should be improved. Criterion values for groundwater potential should be established when machine learning or statistical models are used in the GPM evaluation process.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.5
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• pp.200-215
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• 2023

With the rapid advance of autonomous driving technology, the related vehicle market is experiencing explosive growth, and it is anticipated that the era of fully autonomous vehicles will arrive in the near future. However, along with the development of autonomous driving technology, questions regarding its safety and reliability continue to be raised. Concerns among technology adopters are increasing due to media reports of accidents involving autonomous vehicles. To promote the improvement of the safety of autonomous vehicles, it is essential to analyze previous accident cases and identify their causes. Therefore, in this study, we aimed to analyze the factors influencing the severity of autonomous vehicle accidents using previous accident cases and related data. The data used for this research primarily comprised autonomous vehicle accident reports collected and distributed by the California Department of Motor Vehicles (CA DMV). Spatial information on accident locations and additional traffic data were also collected and utilized. Given that the primary data used in this study were accident reports, a Poisson regression analysis was conducted to model the expected number of accidents. The research results indicated that the severity of autonomous vehicle accidents increases in areas with low lighting, the presence of bicycle or bus-exclusive lanes, and a history of pedestrian and bicycle accidents. These findings are expected to serve as foundational data for the development of algorithms to enhance the safety of autonomous vehicles and promote the installation of related transportation infrastructure.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.6
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• pp.653-658
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• 2023

In systems like the combat management system of a naval ship or smart city of civilians, where many sensors and actuators are connected, the middle-ware DDS (Data Distribution Service) is mainly used to transmit large amounts of data. It is scalable and can effectively respond to the increase in sensors or equipment connected to the system in the future. The engineering control system (ECS), which plays an important role similar to the combat management system of a naval ship, still uses Server-Client model with industrial protocols such as Modbus and CAN (Controller Area Network) bus, to transmit data, which is unfavorable in terms of scalability. However, as automation and unmanned systems advance, more sensors and actuators are expected to be added, necessitating substantial program modification. DDS can effectively address such situations. The purpose of this study is to confirm the development possibility of an integrated monitoring and control system of a ship by using OpenDDS, which follows the OMG (Object Management Group) standard among the middle-ware DDS used in the combat management system. To achieve this goal, field equipment simulators and an ECS server were configured to perform field equipment data input/output and simulation using DDS was performed. The ECS prototype successfully handled data transmission, confirming that DDS is capable of serving as the middle-ware for the ECS of a ship.

• Korean journal of applied entomology
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• v.62 no.4
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• pp.385-388
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• 2023

Gypsy moth (Lymantria dispar), a polyphagous insect pest belonging to the family Lymantriidae, is widely distributed in Korea, Japan, Siberia, Europe, and North America. They pose a threat to various host plants including pear trees, apple trees, and blueberries. Traditionally considered a forest pest, the increasing incursion of gypsy moths into agricultural land near forested areas has intensified damage to crops lacking effective control methods. This study aimed to investigate the temperature-dependent development of gypsy moths to enhance outbreak prediction and advance technology development. The effects of temperature on development of each life stage were investigated under constant temperature conditions of 18, 21, 24, 27, 30, and 33℃ (14L:10D, RH 60±5%) utilizing egg masses collected in Jeollanam-do Jangheung-gun in 2021. The results revealed that higher temperatures accelerated the development rate of the gypsy moth larvae with optimal development occurring at 30℃. However, the survival rate was lowest at 33℃. At the favorable temperature of 30℃, the total development period was 43.8 days for females and 42.5 days for males. The developmental threshold temperature were 13.1℃ for females and 12.5℃ for males, with effective accumulated temperature of 641.1 DD and 657.8 DD, respectively.

• Journal of Applied Biological Chemistry
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• v.66
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• pp.467-476
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• 2023

Schisandra chinensis (S. chinensis) is a deciduous broad-leaved cave plant belonging to the Schisandraceae family and is widely distributed in East Asia including Korea, Japan, China, and Taiwan. It has been reported that the main components contained in S. chinensis include lignan compounds and triterpenoid compounds. To distinguish the characteristics of S. chinensis by production region of Korea, a discriminant was established by performing metabolite profiling and principal component analysis, a multivariate statistical analysis technique. As a result, 16 types of triterpenoids, 9 types of lignan, and 1 type each of flavonoid, phenylpropanoid, and fatty acid were identified. In addition, through multivariate statistical analysis, it was confirmed that the four groups in Danyang, Moongyeong, Geochang, and Pyeongchang were divided, by applying the s-plot model of orthogonal partial least squares discriminant analysis. Biomarkers were identified: lanostane, cycloartane, schiartane triterpenoid, and dibenzocyclo-octadiene lignan were identified as chemical markers, respectively.

• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.579-591
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• 2024

Recently, church organizations are experiencing various problems, including a sharp decline in the number of members. This study focused on the problem of lack of communication, that is, organizational silence, which is commonly pointed out in previous studies as a problem of church organizations, and empirically analyzed the relationship between organizational silence, organizational cynicism, and organizational commitment within church organizations. For this purpose, a questionnaire was distributed to 210 members of churches and related organizations from May to June 2023, of which 202 copies were used as analysis data. SPSS 23.0 and AMOS 23.0 were used to perform frequency analysis, confirmatory factor analysis, descriptive statistical analysis, correlation analysis, structural equation model analysis, and bootstrapping to verify mediation effects. As a result of the study, organizational silence had a negative effect on organizational cynicism, and organizational cynicism had a negative effect on organizational commitment. Although organizational silence did not have a direct negative effect on organizational commitment, it was found to have a negative effect mediated by organizational cynicism. This study expanded the scope of the study by applying variables from organizational theory to church organizations, and presented practical implications through the research results to church organizations.

• Steel and Composite Structures
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• v.50 no.6
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• pp.705-720
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• 2024

Analyzing the collapse behavior of thin-walled steel structures holds significant importance in ensuring their safety and longevity. Geometric imperfections present on the surface of metal materials can diminish both the durability and mechanical integrity of steel shells. These imperfections, encompassing local geometric irregularities and deformations such as holes, cavities, notches, and cracks localized in specific regions of the shell surface, play a pivotal role in the assessment. They can induce stress concentration within the structure, thereby influencing its susceptibility to buckling. The intricate relationship between the buckling behavior of these structures and such imperfections is multifaceted, contingent upon a variety of factors. The buckling analysis of thin-walled steel shell structures, similar to other steel structures, commonly involves the determination of crucial material properties, including elastic modulus, shear modulus, tensile strength, and fracture toughness. An established method involves the emulation of distributed geometric imperfections, utilizing real test specimen data as a basis. This approach allows for the accurate representation and assessment of the diversity and distribution of imperfections encountered in real-world scenarios. Utilizing defect data obtained from actual test samples enhances the model's realism and applicability. The sizes and configurations of these defects are employed as inputs in the modeling process, aiding in the prediction of structural behavior. It's worth noting that there is a dearth of experimental studies addressing the influence of geometric defects on the buckling behavior of cylindrical steel shells. In this particular study, samples featuring geometric imperfections were subjected to experimental buckling tests. These same samples were also modeled using Finite Element Analysis (FEM), with results corroborating the experimental findings. Furthermore, the initial geometrical imperfections were measured using digital image correlation (DIC) techniques. In this way, the response of the test specimens can be estimated accurately by applying the initial imperfections to FE models. After validation of the test results with FEA, a numerical parametric study was conducted to develop more generalized design recommendations for the stainless-steel shell structures with the initial geometric imperfection. While the load-carrying capacity of samples with perfect surfaces was up to 140 kN, the load-carrying capacity of samples with 4 mm defects was around 130 kN. Likewise, while the load carrying capacity of samples with 10 mm defects was around 125 kN, the load carrying capacity of samples with 14 mm defects was measured around 120 kN.

• Journal of Korean Society of Forest Science
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• v.113 no.2
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• pp.170-186
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• 2024

This study was conducted to identify the usage characteristics of the DMZ Punchbowl Trail (DPT) as a national forest trail (NFT) and to estimate its ripple effects on the local economy. The objective of this study is to provide policy implications for sustainable operational management. Out of the 500 questionnaires distributed, 215 respondents provided their complete travel itineraries and expenditures. The respondents, mainly aged 50 and above and residing in the Seoul Metropolitan Area, spend 3.5 hours of travel time to the DPT. Together with their families, the respondents typically spend approximately 4 hours for leisurely activities, primarily appreciation of scenic views and relaxation by visiting the "O-yubatgil." Furthermore, they extend their travels to other parts of Gangwon Province, where the DPT is situated. Within Gangwon Province, Yanggu County is the most visited destination. The respondents reported a notably higher average expenditure per visitor compared with the typical local walking tourists. Estimates show that the DPT generates an annual average of KRW 2.1 billion in direct expenditure (based on an average of 10,000 visitors for over five years), KRW 2.8 billion in production, and KRW 1.3 billion in added value, and it has created 40 jobs in Gangwon Province. The results of this study lies in empirically determining the specific economic scale and ripple effects of DPT as an NFT in the major sector, which occupies a significant portion of the Gangwon Province's local economy. The results will be instrumental in validating NFT policies and informing policy making for sustainable forest utilization.

• Journal of Distribution Research
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• v.16 no.2
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• pp.57-94
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• 2011

Nowadays, it is common that most consumers are purchasing goods in e-stores. The e-stores eager to attract, revisit, retain, and finally convert them into loyal customers. The e-store marketers have planned and executed numerous marketing efforts. As one of the marketing activities, e-store managers attempt to build web sites that meet customers' functional and psychological needs. A wide array of studies has been done to identify factors that could affect customers' response of web sites. Majority of studies were conducted to verify technology-related and functional variables of the website which facilitate transactions and enhance customer responses such as purchase intention and website loyalty. However, there has been little research on the external cues of website and psychological variables of consumer that could have positive influences on customer response. The purpose of this study is to investigate the influence of e-store personality on e-store loyalty through mediating variables such as e-store identification, e-store trust, and e-store engagement. The authors of this study develop the model and set up the six main hypotheses and a set of sub-hypotheses based on a literature review, shown in