BACKGROUND: The changes in the climatic conditions have brought potentially significant new challenges, most critical are likely to be its impact on local livelihoods, agriculture, biodiversity and environments. Water induced disasters such as landslides, floods, erratic rain etc., are very common in developing countries which lead to changes in biological, geophysical and socioeconomic elements. The extent of damages caused by natural disasters is more sever in least developing countries. However, disasters affect women and men differently. In most of the cases women have to carry more burden as compared to their male counterpart during the period of disasters. METHODS AND RESULTS: This study examines the impact of disasters on the local livelihood especially agriculture and income generating activities of women in three districts of Nepal. The study uses the primary data collected following an exploratory approach, based on an intensive field study. The general findings of the study revealed that women had to experience hard time as compared to their male counterpart both during and after the disaster happen. Women are responsible for caring their children, collecting firewood, fetching water, collecting grass for livestock and performing household chores. Whereas, men are mainly involved in out-migration and remained out-side home most of the time. After the disaster occurred, most of the women had to struggle to support their lives as well as had to work longer hours than men during reconstruction period. Nepal follows patriarchal system and men can afford more leisure time as compared to women. During the disaster period, some of the households lost their agricultural lands, livestock and other properties. These losses created some additional workload to women respondent, however at the same time; they learn to build confidence, self-respect, self-esteem, and self-dependency.Although Nepal is predominantly agriculture, majority of the farmers are at subsistence level. In addition, men and women have different roles which differ with the variation in agro-production systems. Moreover women are extensively involved in agricultural activities though their importances were not recognized. Denial of land ownership and denial of access to resources as well as migration of male counterparts are some of the major reasons for affecting the agricultural environments for women in Nepal. CONCLUSION: The shelter reconstruction program has definitely brought positive change in women's access to decision making. The gradual increase in number of women respondent in access to decision making in different areas is a positive change and this has also provided them with a unique opportunity to change their gendered status in society.Furthermore, the exodus out-flow of male counterparts accelerated the additional burden and workload on women.
Journal of the Korean Institute of Landscape Architecture
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v.28
no.3
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pp.39-52
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2000
The purpose of this paper is to investigate the difference in facilities of natural recreation forests developed by public and private body to answer the research that what is the difference in development of natural recreation forest between public and private developer\ulcorner After reviewing the literatures, developer's decision-making and motivation of investment, and the planning process of natural recreation forest, we had constructed th conceptual framework and have found the hypothesis of this research. Using data on development status of natural recreation forests and questionnaire surveying of 625 visitors from 9 among 72 natural recreation forests in Korea, We analyzed the data through the comparison of quantity of facilities per 1000 visitors and logistic regression method for quality of facilities. We have found that 1) the six facilities have been turned out to be statistically significant in determining the difference of public and private recreation forests. i.e., infrastructure including roads, maintenance and information and lodging and evacuation, indoor education, outdoor education, and shopping, 2) public recreation forests are well equipped such basic facility as roads, maintenance and information, lodging and evacuation while private recreation forests are well equipped such facility as indoor education, outdoor education, and shopping, and 3) the importance of such facility as roads, maintenance and information, lodging and evacuation, outdoor education, and shopping have been turned out to have 1.99, 2.26, 1.99, 3.01 and 2.24 times more important than that of indoor education, respectively. We can conclude that public recreation forest seems to be equipped with the facilities for sound recreational opportunities for general public, and private recreation forest turned out to have more facilities for pursuit of profits, installed basic facilities for user convenience and service, and special facilities for attracting user and raising revenue. Using the results of this research, we can make a guideline for a market positioning, and standards and provisions of natural recreation forests. We suggest that the relationship between user-satisfaction and recreation facility is needed to be examined in the future research.
HIV-1 coreceptor usage and phenotype mainly determined by V3 loop are associated with the disease progression of AIDS. Predicting HIV-1 coreceptor usage and phenotype facilitates the monitoring of R5-to-X4 switch and treatment decision-making. In this study, we employed random forest to predict HIV-1 biological phenotype, based on 37 random features of V3 loop. In comparison with PSSM method, our RF predictor obtained higher prediction accuracy (95.1% for coreceptor usage and 92.1% for phenotype), especially for non-B non-C HIV-l subtypes (96.6% for coreceptor usage and 95.3% for phenotype). The net charge, polarity of V3 loop and five V3 sites are seven most important features for predicting HIV-1 coreceptor usage or phenotype. Among these features, V3 polarity and four V3 sites (22, 12, 18 and 13) are first reported to have high contribution to HIV-1 biological phenotype prediction.
Purpose This study aims to analyze the relationship between consumption patterns and default risk among financially vulnerable households in a rapidly changing economic environment. Financially vulnerable households are more susceptible to economic shocks, and their consumption patterns can significantly contribute to an increased risk of default. Therefore, this study seeks to provide a systematic approach to predict and manage these risks in advance. Design/methodology/approach The study utilizes data from the Korea Welfare Panel Study (KOWEPS) to analyze the consumption patterns and default status of financially vulnerable households. To address the issue of data imbalance, sampling techniques such as SMOTE, SMOTE-ENN, and SMOTE-Tomek Links were applied. Various machine learning algorithms, including Logistic Regression, Decision Tree, Random Forest, and Support Vector Machine (SVM), were employed to develop the prediction model. The performance of the models was evaluated using Confusion Matrix and F1-score. Findings The findings reveal that when using the original imbalanced data, the prediction performance for the minority class (default) was poor. However, after applying imbalance handling techniques such as SMOTE, the predictive performance for the minority class improved significantly. In particular, the Random Forest model, when combined with the SMOTE-Tomek Links technique, showed the highest predictive performance, making it the most suitable model for default prediction. These results suggest that effectively addressing data imbalance is crucial in developing accurate default prediction models, and the appropriate use of sampling techniques can greatly enhance predictive performance.
Korean Journal of Agricultural and Forest Meteorology
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v.21
no.4
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pp.373-379
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2019
Smart-farm has been spreading across Korea to improve the labor efficiency and productivity of greenhouse crops. Although notable improvements have been made in the monitoring technologies and environmental-controlling systems in greenhouses, only a few simple decision-support systems are available for predicting the optimum environmental conditions for crop growth. In this study, a tomato growth model (GreenTom), which was developed by Seoul National University in 1997, was calibrated and validated to examine if the model can be used as a decision-supporting system. The original GreenTom model was not able to simulate artificial defoliation, which resulted in overestimation of the leaf area index in the late growth. Thus, an algorithm for simulating the artificial defoliation was developed and added to the original model. The node development, leaf growth, stem growth, fruit growth, and leaf area index were generally well simulated by the modified model indicating that the model could be used effectively in the decision-making of smart greenhouse.
The Journal of Korea Institute of Information, Electronics, and Communication Technology
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v.16
no.5
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pp.325-330
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2023
This paper proposes to apply machine learning to the process of predicting the slab thickness based on the structural analysis results or experience and subjectivity of engineers in the design of bridge data construction to enable digital-based decision-making. This study aims to build a reliable design environment by utilizing machine learning techniques to provide guide values to engineers in addition to structural analysis for slab thickness selection. Based on girder bridges, which account for the largest proportion of bridge data, a prediction model process for predicting slab thickness among superstructures was defined. Various machine learning models (Linear Regress, Decision Tree, Random Forest, and Muliti-layer Perceptron) were competed for each process to produce the prediction value for each process, and the optimal model was derived. Through this study, the applicability of machine learning techniques was confirmed in areas where slab thickness was predicted only through existing structural analysis, and an accuracy of 95.4% was also obtained. models can be utilized in a more reliable construction environment if the accuracy of the prediction model is improved by expanding the process
Korean Journal of Agricultural and Forest Meteorology
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v.3
no.1
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pp.37-43
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2001
Crop status monitoring and yield prediction at higher spatial resolution is a valuable tool in various decision making processes including agricultural policy making by the national and local governments. A prototype crop forecasting system was developed to project the size of rice crop across geographic areas nationwide, based on daily weather pattern. The system consists of crop models and the input data for 1,455 cultivation zone units (the smallest administrative unit of local government in South Korea called "Myun") making up the coterminous South Korea. CERES-rice, a rice crop growth simulation model, was tuned to have genetic characteristics pertinent to domestic cultivars. Daily maximum/minimum temperature, solar radiation, and precipitation surface on 1km by 1km grid spacing were prepared by a spatial interpolation of 63 point observations from the Korea Meteorological Administration network. Spatial mean weather data were derived for each Myun and transformed to the model input format. Soil characteristics and management information at each Myun were available from the Rural Development Administration. The system was applied to the forecasting of national rice production for the recent 3 years (1997 to 1999). The model was run with the past weather data as of September 15 each year, which is about a month earlier than the actual harvest date. Simulated yields of 1,455 Myuns were grouped into 162 counties by acreage-weighted summation to enable the validation, since the official production statistics from the Ministry of Agriculture and Forestry is on the county basis. Forecast yields were less sensitive to the changes in annual climate than the reported yields and there was a relatively weak correlation between the forecast and the reported yields. However, the projected size of rice crop at each county, which was obtained by multiplication of the mean yield with the acreage, was close to the reported production with the $r^2$ values higher than 0.97 in all three years.
Kim, Jung Teak;Kim, Jaeuk;Lee, Woo-Kyun;Jeon, Seong Woo;Kim, Joon Soon
Journal of Forest and Environmental Science
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v.31
no.3
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pp.207-213
/
2015
It is estimated that there is a total of approximately 100,000 species in Korea. However, the number is currently about 30,000 and only 16,027 species are listed in the 'Species Korea' (as of December, 2014). Of the listed species, 51 species are designated as the Endangered Species Class I while 195 species are in the Class II, totaling 246 endangered species including 20 mammals. Under the circumstances that development (e.g., roads) is increasingly threatening the persistence of endangered mammals, it is significant to identify and preserve suitable habitats for them. In this context, evaluating the values of the suitable habitat environment would serve as essential information for development decision making. This study estimated the values of endangered mammals' forest habitats through spatialization of habitat services. In doing so, a species distribution model, Maximum Entropy Model (MaxEnt) was utilized for a group of endangered mammals including, mountain goat, wildcat, marten cat, and flying squirrel. To calculate the values per unit area, a benefit transfer method was used based on the point-estimate technique with the best available values estimated previously. The range of discount rate of 3.0 to 5.5 percent was applied taking the notion of social discount rate into account. As a result, the province with the highest values for endangered mammal habitats appeared to be Gangwon, followed by Gyeongbuk and Gyeongnam. The monetary values of the endangered mammal habitats were estimated to be 330 billion to 421 billion won per year.
Kim, Eun-sook;Won, Myoungsoo;Kim, Kyoungmin;Park, Joowon;Lee, Jung Soo
Korean Journal of Remote Sensing
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v.35
no.6_2
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pp.1031-1035
/
2019
Nowadays, the utilization infrastructure of domestic satellite information is expanding rapidly. Especially, the development of agriculture and forestry satellite is expected to drastically change the utilization of satellite information in the forest sector. The launch of the satellite is expected in 2023. Therefore, NIFoS and academic experts in forest sectors have prepared "Special Issue on Forest Management Research using Optical Sensors and Remote Sensing Technologies" in order to understand new remote sensing technologies and suggest the future direction of forest research and decision-making. This special issue is focused on a variety of fields in forest remote sensing research, including forest resources survey, forest disaster detection, and forest ecosystem monitoring. The new research topics for remote sensing technologies in forest sector focuses on three points: development of new indicators and information for accurate detection of forest conditions and changes, the use of new information sources such as UAV and new satellites, and techniques for improving accuracy through the use of artificial intelligence techniques.
The purpose of this study was to provide the basic data necessary for stakeholders to establish and promote policies related to the national forest trail. Awareness analysis was conducted on 800 visitors to the national forest trail, specifically to the Jirisan trail and Daegwallyeong forest trail, as well as 1,200 members of the public. Awareness of the national forest trail was low and at a similar level for both visitors and the general public; however, compared with the general public, the visitors had a higher need for the national forest trail system and were willing to visit and recommend the trail. The most common answers in response to the purpose of visit, reason for choosing the national trail, matters of interest, problems, necessary regulation, and role expectations were similar among the visitors and general public. Based on gender and age, there was a significant difference in the matters of interest and desired activity, but "scenery" was the most crucial factor. Therefore, after a comprehensive survey on the major view points, given that "scenery" was identified as an attractor, a system should be developed to identify and provide the information desired by visitors and the general public. These results are expected to be employed as basic data for stakeholders in decision making related to the national forest trail.
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