• Korean Journal of Plant Resources
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• v.34 no.5
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• pp.491-501
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• 2021

This study was carried out to investigate the occurrence of seedlings of Korean fir (Abies koreana) in Korean fir forest located on the eastern slope of Mt. Halla National Park. Between June and August in 2016, the systematic sampling method was applied to 125 plots of 5 m × 5 m quadrats and field survey was came out to measure the characteristics of sites and understory vegetation. Correlation analysis was applied to the variables quantified from the data collected. Total number of flora found at the study site is 31 in families, 44 in genera, and 56 in species. The main lower layer vegetation was investigated such as Jeju dwarf bamboo, Toothed club moss (Lycopodium serratum), Pacific fir moss (Lycopodium chinense), Climbing hydrangea (Hydrangea petiolaris) etc. Among these plant species, the vegetation which had a high positive correlation with the frequency and the coverage of seedlings of Korean fir were Jeju dwarf bamboo, Toothed club moss and Pacific fir moss.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.3
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• pp.73-86
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• 2021

The primary purpose of this paper is to explore the advanced models that predict entrepreneurial innovativeness most accurately. For the first time in the field of entrepreneurship research, it presents a model that predicts entrepreneurial innovativeness based on machine learning corresponding to data scientific approaches. It uses 22,099 the Global Entrepreneurship Monitor (GEM) data from 62 countries to build predictive models. Based on the data set consisting of 27 explanatory variables, it builds predictive models that are traditional statistical methods such as multiple regression analysis and machine learning models such as regression tree, random forest, XG boost, and artificial neural networks. Then, it compares the performance of each model. It uses indicators such as root mean square error (RMSE), mean analysis error (MAE) and correlation to evaluate the performance of the model. The analysis of result is that all five machine learning models perform better than traditional methods, while the best predictive performance model was XG boost. In predicting it through XG boost, the variables with high contribution are entrepreneurial opportunities and cross-term variables of market expansion, which indicates that the type of entrepreneur who wants to acquire opportunities in new markets exhibits high innovativeness.

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1277-1290
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• 2020

Water resources which is formed of surface and groundwater, are considered as one of the pivotal natural resources worldwide. Since last century, the rapid population growth as well as accelerated industrialization and explosive urbanization lead to boost demand for groundwater for domestic, industrial and agricultural use. In fact, better management of groundwater can play crucial role in sustainable development; therefore, determining accurate location of groundwater based groundwater potential mapping is indispensable. In recent years, integration of machine learning techniques, Geographical Information System (GIS) and Remote Sensing (RS) are popular and effective methods employed for groundwater potential mapping. For determining the status of the integrated approach, a systematic review of 94 directly relevant papers were carried out over the six previous years (2015-2020). According to the literature review, the number of studies published annually increased rapidly over time. The total study area spanned 15 countries, and 85.1% of studies focused on Iran, India, China, South Korea, and Iraq. 20 variables were found to be frequently involved in groundwater potential investigations, of which 9 factors are almost always present namely slope, lithology (geology), land use/land cover (LU/LC), drainage/river density, altitude (elevation), topographic wetness index (TWI), distance from river, rainfall, and aspect. The data integration was carried random forest, support vector machine and boost regression tree among the machine learning techniques. Our study shows that for optimal results, groundwater mapping must be used as a tool to complement field work, rather than a low-cost substitute. Consequently, more study should be conducted to enhance the generalization and precision of groundwater potential map.

• The Journal of Engineering Geology
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• v.31 no.2
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• pp.187-197
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• 2021

Clay mineral content of weathered zone is a key parameter for landslide studies. Electrical resistivity tomography is usually performed to delineate the geometry of complex landslides and to identify the sliding surface. In clay-bearing weathered zone, parallel resistivity Archie equation is employed to investigate the effect of conductivity added (resistivity reduced) by clay minerals of kaolinite and montmorillonite, which is dependent on their specific surface area and cation exchange capacities (CEC). A decrease of overall resistivity and apparent formation factor is observed with increasing pore-water resistivity, significantly in montmorillonite. Formation factor is found decreased with increasing porosity and decreasing cementation factor. Parallel Archie equation was applied to the electrical resistivity data from the test area (Sinjindo-ri, Taean-gun, Chungcheongnam-do, Korea) which experienced land creeping in the year of 2014. A panel test with varying clay-mineral contents provides the best fit section when the theoretical section constructed with the assumed contents approaches the field section, from which the clay-mineral content of the weathered zone is estimated to be approximately 10%. Resistivity interpretation schemes including the clay mineral contents for land creeping studies explored in this paper can be challenged more when porosity, saturation, and pore-water resistivity are provided and they are included in the numerical resistivity modeling.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.177-177
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• 2020

새만금 간척지는 1989년 '새만금간척사업'이 발표된 이래 1991년에 방조제 공사를 시작으로 2006년 물막기 공사를 완료하였고, 2009년 이후 방조제를 완공하여 현재는 40,100ha의 간척지가 조성되었다. 하지만 간척지는 장기적으로 환경에 악영향을 미치며 특히 간척으로 인한 해안경관의 가치 상실, 생태계 파괴 및 교란에 따른 변화가 크기 때문에 이에 대한 대책이 필요하다. 적극적인 식생의 도입이 그 대책의 하나가 될 수 있는데 이는 자연적으로 식물천이를 유도하고 동물들을 유인하여 생태적으로 건강한 환경을 조성하는데 기여할 수 있다. 따라서 본 연구에서는 새만금간척지의 대표적인 수목생육 제한 요인으로 판단되는 염분, 배수 및 통기성에 대한 시험연구를 진행하고자 '09~'11까지 초기에 김제광활에서 2ha의 시험포를 운영하였고, '12부터는 군산옥구에서 2ha의 시험포를 운영하고 있다. 수목을 심을 포지를 구획하기 전에 토양의 염분값을 낮추기 위해서 군산옥구의 경우, 2ha의 시험포를 포함한 전체 묘목장 부지(100ha) 중에서 일부구간(38ha)을 '09 부터 자연강우 담수제염을 통해서 제염을 진행하였다. 이를 통해 초기 염분 값이 18ds/m~20ds/m에서 8ds/m~10ds/m로 낮아졌다. 이렇게 수목이 자랄 수 있는 정도의 제염이 이루어진 이후에는 배수 및 통기성 부분에 초점을 맞추어 포지를 구획하였다. 단지1의 경우, 사전제염작업을 하지 않고, 5M간격의 암거를 설치하였고, 단지2의 경우, 사전강우제염을 진행하고, 10M간격의 암거를 설치하였다. 단지3의 경우, 사전강우제염을 진행하고 그 위에 0.4M의 준설토를 성토하여 포지를 조성하고 일부구간에 5M, 10M암거를 설치하였다. 2년 간의 수목 생존률 및 생장 모니터링을 통해서 각 단지에서의 수목생장의 적합성의 정도를 간접적으로 판단할 수 있었다. 단지3이 암거설치 간격 및 설치유무에 관계없이 수목이 자라는데 가장 적합했다. 다음으로 단지2, 단지1 순으로 나타났다. 염분 값을 낮추기 위한 자연강우 담수제염의 경우에는 문제가 되지 않지만 배수 및 통기성 개선을 위한 암거설치의 경우는 새만금 전체 식재구역에 적용하기에는 경제성이 떨어지므로 배수 및 통기성을 위한 별도의 방안이 요구된다. 또한 각 단지에서의 수목 생장모니터링을 지속적으로 시행하여 보다 장기적인 측면에서의 식재기반 조성기법을 고려할 필요가 있다.

• Journal of the Korea Society of Computer and Information
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• v.28 no.11
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• pp.1-11
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• 2023

Breast cancer is the disease that affects women the most worldwide. Due to the development of computer technology, the efficiency of machine learning has increased, and thus plays an important role in cancer detection and diagnosis. Deep learning is a field of machine learning technology based on an artificial neural network, and its performance has been rapidly improved in recent years, and its application range is expanding. In this paper, we propose a DNN-SVM hybrid model that combines the structure of a deep neural network (DNN) based on transfer learning and a support vector machine (SVM) for breast cancer classification. The transfer learning-based proposed model is effective for small training data, has a fast learning speed, and can improve model performance by combining all the advantages of a single model, that is, DNN and SVM. To evaluate the performance of the proposed DNN-SVM Hybrid model, the performance test results with WOBC and WDBC breast cancer data provided by the UCI machine learning repository showed that the proposed model is superior to single models such as logistic regression, DNN, and SVM, and ensemble models such as random forest in various performance measures.

• Journal of the Korean Wood Science and Technology
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• v.52 no.3
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• pp.262-275
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• 2024

In Indonesia, Coptotermes curvignathus Holmgren and Cryptotermes cyanocephalus Light termite attacks can damage wood and causing losses of 8.7 trillion rupiah per year. Wood treatment and soil barrier are very important to protect structures and their components from termite infestation. The application of synthetic chemicals that pose risks to the environment and human health. The growing movement to replace these chemicals with new termiticides that are safe for the environment in place of persistent organic pollutants. Efficacy performance in entomopathogenic fungi spores such as that produce decanoic acid, hexadecanoic acid, palmitic acid, and octadecadienoic acid are potential compounds that provide for ecofriendly termite control. Entomopathogenic fungal spores from Metarhizium anisopliae, Trichoderma harzianum, and Beauveria bassiana, as the active ingredient were formulated with nanocellulose was added as an inert ingredient to which helped to deliver the active ingredients on controlling the target pest, and enhance the utility ability of the product fungi to control termites. The mortality of these termites successively entomopathogenic fungi was the main cause of death. The higher concentrations being associated with of nanocellulose used affect increased the number of termites mortality. M. anisopliae paired with 60% nanocellulose concentrate was the best percentage for yielded the greatest C. curvignathus and C. cynocephalus termite control. In the field testing, M. anisopliae provided better, it showed the finest result of termite control rather than B. bassiana and T. harzianum. The results of the research indicate that entomopathogenic fungi can be used for Pest Control Management as the subterranean termite and drywood termite control.

• The Journal of Engineering Geology
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• v.34 no.2
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• pp.249-262
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• 2024

Retaining walls are widely used in the construction of underground structures. This study reviews the stability of the high-strength joint buried pile method at a site in Korea. [Consider giving details of the location.] The method is assessed by considering the amount of ground settlement, as calculated by finite element analysis and measured at the site. Comparison of the measured and numerical results confirmed the method's stability and field applicability. Settlement of 13.42~13.65 mm was calculated for seven cross-sections [The Abstract should be comprehensible without reference to the main text. The labels A-A' to G-G' should not be introduced here without explanation.] using numerical analysis, and the measured settlement reached a maximum of 2.00 mm. The observed differences and variations [Please state what differed/varied.] did not exceed the design expectations in any section. Instruments installed at the back of the excavation area were used to assess the conditions. An underground gradient meter recorded a cumulative horizontal displacement of between -0.40 and 0.60 mm, and an underground water meter recorded slight displacements of between -0.21 and 0.28 m compared with the initial measurements. A surface settlement meter observed very little movement, with a maximum of -2.00 mm compared with the initial measurement, thereby confirming the establishment of a stable state within the management criteria.

• Journal of Ginseng Culture
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• v.6
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• pp.105-115
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• 2024

Wild ginseng, grown in undisturbed forest environments, has been maintained for centuriesthrough human intervention and knowledge, leading to the development of current ginseng agriculture. The practice of ginseng farming has long been established in various regions of Korea. However, the ginseng farming specifically in Geumsan was recognized as a Globally Important Agricultural Heritage System (GIAHS) by the Food and Agriculture Organization of the United Nations (FAO) in 2018. This designation was granted after a thorough evaluation, which confirmed that Geumsan's ginseng farming met the necessary criteria, including historical importance, traditional knowledge system, agrobiodiversity, and agricultural landscape. Traditional ginseng farming in Geumsan practices the 'rotating agriculture system', a sustainable land use approach that has been developed over several cycles of long duration (10-15 years). It contains the knowledge to choose locations for cultivation that prioritize the direction of sunlight and wind circulation. Furthermore, it received significant recognition for its agricultural heritage value based on its maintenance of several traditional knowledge systems, including ancestral wisdom and knowledge regarding pre-planting field management techniques. As of December 2023, there are currently 86 locations in 26 nations that have been designated as GIAHS. Among these sites, Geumsan stands out as the first and only site in the world specifically recognized for the cultivation of ginseng crops. This historical record serves as a significant reminder of Korea's prominent position as a major producer of ginseng on a global level. This article first provides an overview of the concept of agricultural heritage, the designation criteria, and the status of the designation. It then identifies, among the GIAHS designation criteria, the agricultural heritage value of traditional ginseng farming in the Geumsan region from the perspective of local traditional knowledge systems.

• Economic and Environmental Geology
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• v.57 no.4
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• pp.353-362
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• 2024

This study examined the spectral characteristics of sediments according to moisture content using an unmanned aerial vehicle (UAV)-based hyperspectral sensor and evaluated the efficiency of moisture content detection at different flight altitudes. For this purpose, hyperspectral images in the 400-1000nm wavelength range were acquired and analyzed at altitudes of 40m and 80m for sediment samples with various moisture contents. The reflectance of the sediments generally showed a decreasing trend as the moisture content increased. Correlation analysis between moisture content and reflectance showed a strong negative correlation (r < -0.8) across the entire 400-900nm range. The moisture content detection model constructed using the Random Forest technique showed detection accuracies of RMSE 2.6%, R² 0.92 at 40m altitude and RMSE 2.2%, R² 0.95 at 80m altitude, confirming that the difference in accuracy between altitudes was minimal. Variable importance analysis revealed that the 600-700nm band played a crucial role in moisture content detection. This study is expected to be utilized in efficient sediment moisture management and natural disaster prediction in the field of environmental monitoring in the future.