To increase the utilization of the intelligent methodology of smart farm management, estimation modeling techniques are required to assess prior examination of crops and environment changes in realtime. A mandatory environmental factor such as CO2 is challenging to establish a reliable estimation model in time domain accounted for indoor agricultural facilities where various correlated variables are highly coupled. Thus, this study was conducted to develop an artificial neural network for reducing time complexity by using environmental information distributed in adjacent areas from a time perspective as input and output variables as CO2. The environmental factors in the smart farm were continuously measured using measuring devices that integrated sensors through experiments. Modeling 1 predicted by the mean data of the experiment period and modeling 2 predicted by the day-to-day data were constructed to predict the correlation of CO2. Modeling 2 predicted by the previous day's data learning performed better than Modeling 1 predicted by the 60-day average value. Until 30 days, most of them showed a coefficient of determination between 0.70 and 0.88, and Model 2 was about 0.05 higher. However, after 30 days, the modeling coefficients of both models showed low values below 0.50. According to the modeling approach, comparing and analyzing the values of the determinants showed that data from adjacent time zones were relatively high performance at points requiring prediction rather than a fixed neural network model.
The purpose of this study is to investigate the effectiveness of two teaching methods of word problems, one based on mathematical modeling learning(ML) and the other on traditional learning(TL). Additionally, the influence of mathematical modeling learning in word problem solving behavior, application ability of real world experiences in word problem solving and the beliefs of word problem solving will be examined. The results of this study were as follows: First, as to word problem solving behavior, there was a significant difference between the two groups. This mean that the ML was effective for word problem solving behavior. Second, all of the students in the ML group and the TL group had a strong tendency to exclude real world knowledge and sense-making when solving word problems during the pre-test. but A significant difference appeared between the two groups during post-test. classroom culture improvement efforts. Third, mathematical modeling learning(ML) was effective for improvement of traditional beliefs about word problems. Fourth, mathematical modeling learning(ML) exerted more influence on mathematically strong and average students and a positive effect to mathematically weak students. High and average-level students tended to benefit from mathematical modeling learning(ML) more than their low-level peers. This difference was caused by less involvement from low-level students in group assignments and whole-class discussions. While using the mathematical modeling learning method, elementary students were able to build various models about problem situations, justify, and elaborate models by discussions and comparisons from each other. This proves that elementary students could participate in mathematical modeling activities via word problems, it results form the use of more authentic tasks, small group activities and whole-class discussions, exclusion of teacher's direct intervention, and classroom culture improvement efforts. The conclusions drawn from the results obtained in this study are as follows: First, mathematical modeling learning(ML) can become an effective method, guiding word problem solving behavior from the direct translation approach(DTA) based on numbers and key words without understanding about problem situations to the meaningful based approach(MBA) building rich models for problem situations. Second, mathematical modeling learning(ML) will contribute attitudes considering real world situations in solving word problems. Mathematical modeling activities for word problems can help elementary students to understand relations between word problems and the real world. It will be also help them to develop the ability to look at the real world mathematically. Third, mathematical modeling learning(ML) will contribute to the development of positive beliefs for mathematics and word problem solving. Word problem teaching focused on just mathematical operations can't develop proper beliefs for mathematics and word problem solving. Mathematical modeling learning(ML) for word problems provide elementary students the opportunity to understand the real world mathematically, and it increases students' modeling abilities. Futhermore, it is a very useful method of reforming the current problems of word problem teaching and learning. Therefore, word problems in school mathematics should be replaced by more authentic ones and modeling activities should be introduced early in elementary school eduction, which would help change the perceptions about word problem teaching.
Objective: The purpose of this study is to present the basic guidelines for preventing human error by measuring and analyzing the risk of collision perceived by the ship operator in the collision risk situation by using Korea Coast Guard patrol ships. Background: In the last 5 years, 97.5% of the causes of ship collision occurred at the sea was caused by human factors. However, the rate of marine accidents due to human error has not been reduced yet. Experiments and researches on the ship operators using the ships in actual operation are rarely performed. Method: Using two K.C.G Ships on the sea, the ship measured by 30 persons who are the subject of the ship (ship operator) when both ships approach and the relative distance gradually decreases in four encounter situations, perceived ship collision risk (PSCR) data were analyzed by statistical analysis. Results: The age and boarding career of the ship operator in the situation of ship collision risks encountered a negative impact on perceived collision risk in all four opposing encounter situations S1 ($000^{\circ}$), S2 ($045^{\circ}$), S3 ($090^{\circ}$) and S4 ($135^{\circ}$) respectively. That is, the higher the age of the ship operator, the lower the perceived risk of collision and the lower the age, the higher the risk of collision. Also, there was a difference between the average of group A (20~30 years) and group B (40~50 years) according to age of the ship operators at $000^{\circ}$, $045^{\circ}$ and $090^{\circ}$ and there was no difference at $135^{\circ}$. The mean difference of the experience of boarding career was also significantly different between group A (less than 4 years) and group B (more than 5 years), but there was no significant difference at $135^{\circ}$. Conclusion: The results showed that age and boarding career of the ship operators had negative impact on perceived collision risk and there was a difference in perceived risk of collision according to age and abundance of boarding career. As a result, by focusing on the ship operators who are in the age group of 20~30 years old and have less than 4 years of experience in boarding the ship. It is expected that the effect of prevention of marine accidents can be expected by avoiding collision avoidance. Application: The results of this study can be used as policy data of related organizations to prevent human error of ship operators and as training data of training institutes.
Journal of the Korean Association of Geographic Information Studies
/
v.17
no.2
/
pp.121-135
/
2014
Object-based classification methods provide a valid alternative to traditional pixel-based methods. This study reports the results of an object-based classification to examine land cover in the demilitarized zones(DMZs) of Inje-gun. We used land cover classes(7 classes for main category and 13 classes for sub-category) selected from the criteria by Korea Ministry of Environment. The average and standard deviation of the spectrum values, and homogeneity of GLCM were chosen to map land cover types in an hierarchical approach using the nearest neighborhood method. We then identified the distributional characteristics of land cover by considering 3 topographic characteristics (altitude, slope gradient, distance from the Southern Limited Line(SLL)) within the DMZs. The results showed that scale 72, shape 0.2, color 0.8, compactness 0.5 and smoothness 0.5 were the optimum weight values while scale, shape and color were most influenced parameters in image segmentation. The forests (92%) were main land cover type in the DMZs; the grassland(5%), the urban area (2%) and the forests (broadleaf forest: 44%, mixed forest: 42%, coniferous forest: 6%) also occupied mostly in land cover classes for sub-category. The results also showed that facilities and roads had higher density within 2 km from the SLL, while paddy, field and bare land were distributed largely outside 6 km from the SLL. In addition, there was apparent distinction in land cover by topographic characteristics. The forest had higher density at above altitude 600m and above slope gradient $30^{\circ}$ while agriculture, bare land and grass land were distributed mainly at below altitude 600m and below slope gradient $30^{\circ}$.
This study analyzes the efficiency of 25 shipping companies in Korea over the period 2005-2009, using Data Envelopment Analysis (DEA). Among 31 companies that listed in order of decreasing sales volume for the period 2006-2010, the sample companies has been selected on the ground of data availability. This study computes the companies' efficiency, estimates their year-on-year Malmquist productivity index, and analyzes the cause leads to the changes in the productivity, In particular, this study attempts, by dividing the companies into two group, listed or not, to compare the changes in the productivity and analyze the reasons. The results from static analysis based on CCR and BCC model indicate that listed companies are higher efficient than unquoted companies. The results from tests on the productivity changes based on the Malmquist productivity index show that 19 unquoted companies increase their average productivity by 16.2 percent year after year during the period but 6 listed companies increase by 0.5% during the same period.
Background: Despite the increasing role of dry forests in climate change adaptation and mitigation, these versatile resources has got less attention in the national and regional planning, their potential to enhance the local and national economy has been overlooked, and their contribution to sustainable environmental management has not been recognized. Hence, the objective of this study was to assess the socioeconomic contribution of dry forests and forest products to climate change adaptation in the Liben Woreda, Southern Oromia region of Ethiopia. Methods: For this study, an integrated qualitative and quantitative approach was used. A total of 74 households from villages in the Bulbul, Boba, and Melka-Guba kebeles were randomly selected for the household survey. Results: Results showed that 75% of the respondents in the area indicated that climate change has become their major sources of vulnerability, where drought has been manifested in the form of crops failure and massive death of livestock particularly cattle species. The main income strategies of the study households include livestock, crop, forests such as gum and resins, firewood and charcoal and non-farm activities such as in the form of petty trade, wage and aid. The average total household income was ETB 11,209.7. Out of this, dry forest income constituted 15% of the total income. In addition to using dry forests as rangeland for livestock, the communities collect wood for construction, fodder, traditional medicine, and forest food both for subsistence and for sale. On the other hand, dry forest products could be considered as less vulnerable, rather resilient livelihood strategies to climate- and environment-related risks compared to livestock and crop production such as in the face of drought periods. More than 48.6% of the households argued that the income generated from dry forests increased substantially due to increment in the level of engagement of family members in forest based income activities. On the other hand, 35.8% of the households responded that livestock production, particularly camels and goats, have been making the livelihood strategies of the respondents more resilient indicating the shift made from grazers browsers to livestock. In general trends show that, the trends of livelihood dependency on dry forest were highly increasing indicating the importance of dry forest income in responsse to frequent droughts. Conclusions: Dry forest income has been becoming crucial livelihood staretgy in response to frequent droughts in the study area and hence, it is important to improve the management of dry forests for livelihood enhancement, while also securing their long-term ecological functions.
The purpose of the present study is to examine elementary gifted students' perceptions on bias against creativity utilizing concept mapping approach. Twelve elementary gifted students participated in the group brainstorming and produced 55 final statements. Based on these statements, the multi-dimensional scale and hierarchial cluster analysis using dissimilarity matrix were performed. Average stress value was .30 which is appropriate for a two-dimensional concept mapping study. In addition, a questionnaire survey using likert 6 points scale was carried out targeting 132 elementary gifted students to analyze the degree of sympathy on their anti-creativity bias perception. The findings are as follow: First, four categories were concluded dividing gifted students' perceptions on bias against creativity from the hierarchial cluster analysis with X-Y coordinate matrix, these were 'Contradictory attitudes to creativity', 'Low evaluation for creativity', 'Forced to predetermined rules and ideas', and 'Aversion to new things'. Second, elementary gifted students were sympathetic to the order 'Forced to predetermined rules and ideas'(M=4.16), 'Aversion to new things'(M=3.68), 'Contradictory attitudes to creativity'(M=3.55) and 'Low evaluation for creativity'(M=3.30). This study aims to examine, analyze and categorize various relevant factors related to elementary gifted students' perceptions on bias against creativity. Implications of the study related to the present and future creative education were discussed in depth.
The objective of study was to evaluate ecological health from seven sampling locations of Yoogu Stream, one of the tributaries of Guem River, July and September 2005. The research approach was based on the Index of Biological Integrity (IBI) using fish assemblage and Qualitative Habitat Evaluation Index (QHEI) using fish assemblage. The models of IBI and QHEI were modified as 10 metric model and 11 metric model, respectively, for the regional applications. In Yoogu Stream, value of IBI were averaged 29.5 (n=7) which is judged as a 'fair condition'. The IBI model scores, at the site 3 and 7, were estimated as 23 and 24, indicating a 'poor${\sim}$fair condition' while, site 5 was estimated as 28, 'fair condition'. The remaining sites were between 31 and 34, indicating 'fair${\sim}$good condition'. According to the analysis of QHEI, the average was estimated as 136, 'fair${\sim}$good condition'. Spatial variation the QHEI were evident; site 1 and site 4 were 186 and 120 respectively, indicating an 'excellent and fair${\sim}$good conditions'. Site 3 was 69, fair condition while the other sites were 128${\sim}$156, good condition.
The global mean surface temperature has already increased by $0.6{\pm}0.2^{\circ}C$ over the last century, and warming in Korea is approximately twice as large as the global average. The Intergovernmental Panel on Climate Change (IPCC) has concluded that the majority of warming over the past 50 years could be attributed to human activities (IPCC, 2001a). In addition, the global surface temperature is expected to increase by 1.4 to $5.8^{\circ}C$ depending on the greenhouse gas emission scenarios during the $21^{st}$ century.Climate change resulting from increased greenhouse gas concentrations has the potential to harm societies and ecosystems. Reductions in emissions of greenhouse gases and their concentration in the atmosphere will reduce the degree and likelihood of significant adverse conditions due to the anticipated climate change. Mitigation policy has generally been the primary focus of public attention and policy efforts on climate change. However, some degree of climate change is inevitable due to the combination of continued increases in emissions and the inertia of the global climate system. Adaptation actions and strategies are needed for a complementary approach to mitigation. The United Nations Framework Convention on Climate Change (UNFCCC) currently addresses vulnerability and adaptation in the context of climate change negotiations and in future adaptation may be an important element of work under the Kyoto Protocol. There are several on-going programs to develop effective adaptation strategies and their implementation. But in general, many other countries are still on an initiating stage. The climate change science programs of the United States, Japan, England, and Germany are initiated to understand the current status of climate change science and adaptation researches in the developed countries. In this study, we propose the improvement on systems in policy and research aspects to effectively perform the necessary functions for development of nation-wide adaptation measures and their implementation. In policy aspect, the Korean Panel on Climate Change (KPCC) is introduced as a coordinating mechanism between government organizations related with climate change science, impact assessment and adaptation. Also in research aspect, there is a strong consensus on the need for construction of a national network on climate change research as trans-disciplinary research network.
The purpose of this study was to examine the association between metabolic syndrome and its components and health-related quality of life in Korean adults. Metabolic syndrome defined in accordance with NCEP-ATP III, and HRQOL was evaluated using EQ-5D. Data on 16,657 adult, extracted from Korean National Health and Nutrition Examination Surveys in 2016-2018, were analyzed and showed that 34.3% of subjects were metabolic syndrome, with males higher than females. The average score of HRQOL was 96.7 for men and 94.5 for women. Multiple logistic regression analysis was results, The OR of impaired HRQOL in women who metabolic syndrome was 1.27(95% CI: 1.09-1.46) compared to who women without metabolic syndrome. Among the components of metabolic syndrome, abdominal obesity (OR=1.72, 95% CI: 1.50-1.97) and high blood pressure (OR=1.26, 95% CI: 1.06-1.50) were associated to impaired HRQOL. But, there were no significant in men. In conclusion, In order to improve women's HRQOL, it suggests that an approach strategy is necessary to reduce the risk factors of metabolic syndrome, which take into account women's characteristics.
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