• Journal of Environmental Impact Assessment
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• v.30 no.2
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• pp.105-116
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• 2021

In the city of high population density crowded with buildings, Urban Heat Island (UHI) is intensified, and the city is vulnerable to thermal comfort. The maintenance of vacant land in downtown is treated as a factor that undermines the residential environment, spoils the urban landscape, and decreases the economic vitality of the whole region. Therefore, this study compared the effects on microclimate in the surrounding area according to the development scenarios targeting the vacant land in Songhyeon-dong, Jongno-gu, Seoul. The status quo, green oriented, building oriented and green-building mediation scenarios were established and ENVI-met was used to compare and analyze the impact of changes in wind speed, air temperature and mean radiant temperature (MRT) within 1 km of the target and the target site. The result of inside and 1 km radius the targeted area showed that the seasonal average temperature decreased and the wind speed increased when the green oriented scenario was compared with the current state one. It was expected that the temperature lowered to -0.73 ℃ or increased to 1.5 ℃ in summer, and the wind speed was affected up to 210 meters depending on the scenario. And it was revealed that green area inside the site generally affects inside area, but the layout and size of the buildings affect either internal and external area. This study is expected to help as a decision-making support tool for developing Songhyeon-dong area and to be used to reflect the part related to microclimate on the future environmental effects evaluation system.

• Research in Plant Disease
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• v.28 no.3
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• pp.113-121
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• 2022

Rice blast is a major plant disease that occurs worldwide and significantly reduces rice yields. Rice blast disease occurs periodically in Korea, causing significant socio-economic damage due to the unique status of rice as a major staple crop. A disease outbreak prediction system is required for preventing rice blast disease. Epidemiological investigations of disease outbreaks can aid in decision-making for plant disease management. Currently, plant disease prediction and epidemiological investigations are mainly based on quantitatively measurable, structured data such as crop growth and damage, weather, and other environmental factors. On the other hand, text data related to the occurrence of plant diseases are accumulated along with the structured data. However, epidemiological investigations using these unstructured data have not been conducted. The useful information extracted using unstructured data can be used for more effective plant disease management. This study analyzed news articles related to the rice blast disease through text mining to investigate the years and provinces where rice blast disease occurred most in Korea. Moreover, the average temperature, total precipitation, sunshine hours, and supplied rice varieties in the regions were also analyzed. Through these data, it was estimated that the primary causes of the nationwide outbreak in 2020 and the major outbreak in Jeonbuk region in 2021 were meteorological factors. These results obtained through text mining can be combined with deep learning technology to be used as a tool to investigate the epidemiology of rice blast disease in the future.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.1
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• pp.56-71
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• 2023

Citizens' needs for urban green spaces are on the rise due to improved quality of life and increased interest in environments. The garden is noteworthy because it is small in size, making it less controversial to create in the city, and it is adjacent to the residential area, improving citizens' daily environment. Moreover, recently gardens is attracting attention as a tool for urban regeneration, such as being created in declining areas as part of a government project. Therefore, it is time to study the role and value of urban gardens in deteriorated areas in terms of space welfare. However, there are few studies that quantitatively evaluate the effects of gardens, and many prior studies are limited to focusing the green space larger than a certain size (e.g., parks and forests). Therefore, the aim of this study is to examine the effect of garden and gardening quantitatively, paying attention to social aspects such as life satisfaction and community of inhabitants. The study was conducted in an old row housing complex in Gojan1-dong, Ansan-si, Gyeonggi-do. In there, some of the dwellers voluntarily created outdoor gardens and engaged in gardening for a long time. In addition, after the 2017 Gyeonggi-do Garden Fair, several gardens have been maintained and used by residents there. For the first step, the field trip was done to research the status of the garden in the area, and then, a survey was conducted on whether or not gardening has an impact on the life satisfaction and community of residents. The results were analyzed by t-test and ANOVA. As a result, residents who are engaged in gardening are more active in the "neighborhood exchange" and "resident participation" than those who are not engaged in gardening. In addition, if residents voluntarily create a garden, the level of "satisfaction of life" is higher than those staying in the garden which is constructed by the government. And a resident who is gardening in the complex shows higher life satisfaction than those who garden outside of the complex. These results confirmed that the garden has positive effects promoting "exchanges with neighbors", "participation in the community", and "life satisfaction" of residents. It shows that it is important to ensure the right of residents to participate in the garden-making process as much as possible, and the garden's location should be paid attention to maximize the positive effect of gardens.

• (The) Research of the performance art and culture
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• no.39
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• pp.69-96
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• 2019

North Korea has conserved operas in a selective manner. The subject matters of operas recorded in the history of North Korea can be divided into classical tales, translated foreign works, Korean War and war against Japan. Operas that adapted folk classics of the 1950s are considered valuable materials to verify the changes of genres posterior to division of regime between North and South Korea. The officially confirmed works include "Kumgangsan Palseonnyeo (Gyeonwoo Jiknyeo)," "Chunhyangjeon." "Kongjwi Patjwi (Kotsin)," "Ondal," and "Geumnaneui Dal." These works had gone through recreation in terms of realistic situation setting, abolition of class difference, adjustment of social rank and punishment of evil while the base lies in the original folk classics. People emphasized in adapted folk operas are described as those who are hard-working souls without giving importance of difference of social rank, content with the currently living space, devoted to their parents and full of patriotic spirit, and members of community who participate in organized fights against unfair exploitation. This was the fruit of encouragement of work creation supporting union between labor and individual life, destruction of old things and fight promoting this destruction. Folk operas of South and North Korea posterior to Korean War have similarities in that both deal with a love story transcending social ranks and the concomitant conflicts and they focus on the audience who enjoy the operas. Nonetheless, they are different in that this love in North Korea became a tool of educating people wished by the regime, while it became an object of securing the audience by adding the tragic element to love in South Korea. North Korean operas of the initial stage are characterized by playwriting method emphasizing difficult life and compensation of common people, realistic stage expression, accentuation of melody and agreement between notes and lyrics. This was efforts designed to continuously lead senses concentrated from the theater to everyday life of people. In effect, this is in line with the playwriting method of revolutionary operas. Adapted folk operas were subject matters ideal for easily approaching the audience and leaving them good memories at the same time. To realize socialist realism, they went through an experiment of reviewing "people" through the classic folk operas. The possibility of continuation of a work was determined by thorough evaluation after carrying out an experiment in terms of subject matters, theme, music and operation plans from the moment of which the work was on the stage. The sign consisted in the possibility of visit of "Kim Il-sung" to appreciate the work and presentation of directionality. By proposing the clear directionality of which hard-working people who deny social status system can be duly compensated, it encouraged the audience who saw the opera to voluntarily put this in practice. Thus, operas established the directionality through selective processes for creating public communion even before revolutionary operas.

• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.163-169
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• 2024

India is a developing nation and has come with comprehensive way in modernizing its reducing poverty, economy and rising living standards for an outsized fragment of its residents. The STEM (Science, Technology, Engineering, and Mathematics) education plays an important role in it. STEM is an educational curriculum that emphasis on the subjects of "science, technology, engineering, and mathematics". In traditional education scenario, these subjects are taught independently, but according to the educational philosophy of STEM that teaches these subjects together in project-based lessons. STEM helps the students in his holistic development. Youth unemployment is the biggest concern due to lack of adequate skills. There is a huge skill gap behind jobless engineers and the question arises how we can prepare engineers for a better tomorrow? Now a day's Industry 4.0 is a new fourth industrial revolution which is an intelligent networking of machines and processes for industry through ICT. It is based upon the usage of cyber-physical systems and Internet of Things (IoT). Industrial revolution does not influence only production but also educational system as well. IoT in academics is a new revolution to the Internet technology, which introduced "Smartness" in the entire IT infrastructure. To improve socio-economic status of the India students must equipped with 21st century digital skills and Universities, colleges must provide individual learning kits to their students which can help them in enhancing their productivity and learning outcomes. The major goal of this paper is to present a low cost, effective learning mechanism for STEM implementation using Raspberry Pi 3+ model (Single board computer) and Node Red open source visual programming tool which is developed by IBM for wiring hardware devices together. These tools are broadly used to provide hands on experience on IoT fundamentals during teaching and learning. This paper elaborates the appropriateness and the practicality of these concepts via an example by implementing a user interface (UI) and Dashboard in Node-RED where dashboard palette is used for demonstration with switch, slider, gauge and Raspberry pi palette is used to connect with GPIO pins present on Raspberry pi board. An LED light is connected with a GPIO pin as an output pin. In this experiment, it is shown that the Node-Red dashboard is accessing on Raspberry pi and via Smartphone as well. In the final step results are shown in an elaborate manner. Conversely, inadequate Programming skills in students are the biggest challenge because without good programming skills there would be no pioneers in engineering, robotics and other areas. Coding plays an important role to increase the level of knowledge on a wide scale and to encourage the interest of students in coding. Today Python language which is Open source and most demanding languages in the industry in order to know data science and algorithms, understanding computer science would not be possible without science, technology, engineering and math. In this paper a small experiment is also done with an LED light via writing source code in python. These tiny experiments are really helpful to encourage the students and give play way to learn these advance technologies. The cost estimation is presented in tabular form for per learning kit provided to the students for Hands on experiments. Some Popular In addition, some Open source tools for experimenting with IoT Technology are described. Students can enrich their knowledge by doing lots of experiments with these freely available software's and this low cost hardware in labs or learning kits provided to them.

• Journal of Bio-Environment Control
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• v.32 no.4
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• pp.434-441
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• 2023

Determining the size or area of a plant's leaves is an important factor in predicting plant growth and improving the productivity of indoor farms. In this study, we developed a convolutional neural network (CNN)-based model to accurately predict the length and width of lettuce leaves using photographs of the leaves. A callback function was applied to overcome data limitations and overfitting problems, and K-fold cross-validation was used to improve the generalization ability of the model. In addition, ImageDataGenerator function was used to increase the diversity of training data through data augmentation. To compare model performance, we evaluated pre-trained models such as VGG16, Resnet152, and NASNetMobile. As a result, NASNetMobile showed the highest performance, especially in width prediction, with an R_squared value of 0.9436, and RMSE of 0.5659. In length prediction, the R_squared value was 0.9537, and RMSE of 0.8713. The optimized model adopted the NASNetMobile architecture, the RMSprop optimization tool, the MSE loss functions, and the ELU activation functions. The training time of the model averaged 73 minutes per Epoch, and it took the model an average of 0.29 seconds to process a single lettuce leaf photo. In this study, we developed a CNN-based model to predict the leaf length and leaf width of plants in indoor farms, which is expected to enable rapid and accurate assessment of plant growth status by simply taking images. It is also expected to contribute to increasing the productivity and resource efficiency of farms by taking appropriate agricultural measures such as adjusting nutrient solution in real time.

• Tuberculosis and Respiratory Diseases
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• v.54 no.1
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• pp.71-79
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• 2003

Background : A bronchoalveolar lavage(BAL) is useful in diagnosing the etiology of bilateral pulmonary infiltrations, but may worsen the oxygenation and clinical status in severely hypoxemic patients. This study assessed the safety and efficacy of the continuous positive airway pressure(CPAP) using a conventional mechanical ventilator via a face mask as a tool for maintaining the oxygenation level during BAL. Methods : Seven consecutive patients with the bilateral pulmonary infiltrates and severe hypoxemia ($PaO_2/FIO_2$ ratio ${\leq}200$ on oxygen 10 L/min via mask with reservoir bag) were enrolled. The CPAP 5-6 $cmH_2O(F_IO_2\;1.0)$ was delivered through an inflatable face mask using a conventional mechanical ventilator. The CPAP began 10 min before starting the BAL and continued for 30 min after the procedure was completed. A bronchoscope was passed through a T-adapter and advanced through the mouth. BAL was performed using the conventional method. The vital signs, pulse oxymetry values, and arterial blood gases were monitored during the study. Results : (1) Median age was 56 years(male:female=4:3). (2) The baseline $PaO_2$ was $78{\pm}16mmHg$, which increased significantly to $269{\pm}116mmHg$(p=0.018) with CPAP. After the BAL, the $PaO_2$ did not decrease significantly but returned to the baseline level after the CPAP was discontinued. The $SpO_2$ showed a similar trend with the $PaO_2$ and did not decrease to below 90 % during the duration of the study. (3) The $PaCO_2$ increased and the pH decreased significantly after the BAL but returned to the baseline level within 30 min after the BAL. (5) No complications directly related to the BAL procedure were encountered. However, intubation was necessary in 3 patients(43 %) due to the progression of the underlying diseases. Conclusion : In severe hypoxemic patients, CPAP using a face mask and conventional mechanical ventilator during a BAL might allow minimal alterations in oxygenation and prevent subsequent respiratory failure.

• Tuberculosis and Respiratory Diseases
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• v.43 no.6
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• pp.882-893
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• 1996

Background : Over one-third of solitary pulmonary nodules are malignant, but most malignant SPNs are in the early stages at diagnosis and can be cured by surgical removal. Therefore, early diagnosis of malignant SPN is essential for the lifesaving of the patient. The incidence of pulmonary tuberculosis in Korea is somewhat higher than those of other countries and a large number of SPNs are found to be tuberculoma. Most primary physicians tend to regard newly detected solitary pulmonary nodule as tuberculoma with only noninvasive imaging such as CT and they prefer clinical observation if the findings suggest benignancy without further invasive procedures. Many kinds of noninvasive procedures for confirmatory diagnosis have been introduced to differentiate malignant SPNs from benign ones, but none of them has been satisfactory. FOG-PET is a unique tool for imaging and quantifying the status of glucose metabolism. On the basis that glucose metabolism is increased in the malignant transfomled cells compared with normal cells, FDG-PET is considered to be the satisfactory noninvasive procedure which can differentiate malignant SPNs from benign SPNs. So we performed FOG-PET in patients with solitary pulmonary nodule and evaluated the diagnostic accuracy in the diagnosis of malignant SPNs. Method : 34 patients with a solitary pulmonary nodule less than 6 cm of irs diameter who visited Samsung Medical Center from Semptember, 1994 to Semptember, 1995 were evaluated prospectively. Simple chest roentgenography, chest computer tomography, FOG-PET scan were performed for all patients. The results of FOG-PET were evaluated comparing with the results of final diagnosis confirmed by sputum study, PCNA, fiberoptic bronchoscopy, or thoracotomy. Results : (I) There was no significant difference in nodule size between malignant (3.1 1.5cm) and benign nodule(2.81.0cm)(p>0.05). (2) Peal SUV(standardized uptake value) of malignant nodules (6.93.7) was significantly higher than peak SUV of benign nodules(2.71.7) and time-activity curves showed continuous increase in malignant nodules. (3) Three false negative cases were found among eighteen malignant nodule by the FDG-PET imaging study and all three cases were nonmucinous bronchioloalveolar carcinoma less than 2 em diameter. (4) FOG-PET imaging resulted in 83% sensitivity, 100% specificity, 100% positive predictive value and 84% negative predictive value. Conclusion: FOG-PET imaging is a new noninvasive diagnostic method of solitary pulmonary nodule thai has a high accuracy of differential diagnosis between malignant and benign nodule. FDG-PET imaging could be used for the differential diagnosis of SPN which is not properly diagnosed with conventional methods before thoracotomy. Considering the high accuracy of FDG-PET imaging, this procedure may play an important role in making the dicision to perform thoracotomy in diffcult cases.

• Strategy21
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• s.46
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• pp.239-276
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• 2020

The failure of early economic sanctions aimed at hurting the overall economies of targeted states called for a more sophisticated design of economic sanctions. This paved way for the advent of 'smart sanctions,' which target the supporters of the regime instead of the public mass. Despite controversies over the effectiveness of economic sanctions as a coercive tool to change the behavior of a targeted state, the transformation from 'comprehensive sanctions' to 'smart sanctions' is gaining the status of a legitimate method to impose punishment on states that do not conform to international norms, the nonproliferation of weapons of mass destruction in this particular context of the paper. The five permanent members of the United Nations Security Council proved that it can come to an accord on imposing economic sanctions over adopting resolutions on waging military war with targeted states. The North Korean nuclear issue has been the biggest security threat to countries in the region, even for China out of fear that further developments of nuclear weapons in North Korea might lead to a 'domino-effect,' leading to nuclear proliferation in the Northeast Asia region. Economic sanctions had been adopted by the UNSC as early as 2006 after the first North Korean nuclear test and has continually strengthened sanctions measures at each stage of North Korean weapons development. While dubious of the effectiveness of early sanctions on North Korea, recent sanctions that limit North Korea's exports of coal and imports of oil seem to have an impact on the regime, inducing Kim Jong-un to commit to peaceful talks since 2018. The purpose of this paper is to add a variable to the factors determining the success of economic sanctions on North Korea: preventing North Korea's evasion efforts by conducting illegal transshipments at sea. I first analyze the cause of recent success in the economic sanctions that led Kim Jong-un to engage in talks and add the maritime element to the argument. There are three conditions for the success of the sanctions regime, and they are: (1) smart sanctions, targeting commodities and support groups (elites) vital to regime survival., (2) China's faithful participation in the sanctions regime, and finally, (3) preventing North Korea's maritime evasion efforts.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.77-97
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• 2010

Market timing is an investment strategy which is used for obtaining excessive return from financial market. In general, detection of market timing means determining when to buy and sell to get excess return from trading. In many market timing systems, trading rules have been used as an engine to generate signals for trade. On the other hand, some researchers proposed the rough set analysis as a proper tool for market timing because it does not generate a signal for trade when the pattern of the market is uncertain by using the control function. The data for the rough set analysis should be discretized of numeric value because the rough set only accepts categorical data for analysis. Discretization searches for proper "cuts" for numeric data that determine intervals. All values that lie within each interval are transformed into same value. In general, there are four methods for data discretization in rough set analysis including equal frequency scaling, expert's knowledge-based discretization, minimum entropy scaling, and na$\ddot{i}$ve and Boolean reasoning-based discretization. Equal frequency scaling fixes a number of intervals and examines the histogram of each variable, then determines cuts so that approximately the same number of samples fall into each of the intervals. Expert's knowledge-based discretization determines cuts according to knowledge of domain experts through literature review or interview with experts. Minimum entropy scaling implements the algorithm based on recursively partitioning the value set of each variable so that a local measure of entropy is optimized. Na$\ddot{i}$ve and Booleanreasoning-based discretization searches categorical values by using Na$\ddot{i}$ve scaling the data, then finds the optimized dicretization thresholds through Boolean reasoning. Although the rough set analysis is promising for market timing, there is little research on the impact of the various data discretization methods on performance from trading using the rough set analysis. In this study, we compare stock market timing models using rough set analysis with various data discretization methods. The research data used in this study are the KOSPI 200 from May 1996 to October 1998. KOSPI 200 is the underlying index of the KOSPI 200 futures which is the first derivative instrument in the Korean stock market. The KOSPI 200 is a market value weighted index which consists of 200 stocks selected by criteria on liquidity and their status in corresponding industry including manufacturing, construction, communication, electricity and gas, distribution and services, and financing. The total number of samples is 660 trading days. In addition, this study uses popular technical indicators as independent variables. The experimental results show that the most profitable method for the training sample is the na$\ddot{i}$ve and Boolean reasoning but the expert's knowledge-based discretization is the most profitable method for the validation sample. In addition, the expert's knowledge-based discretization produced robust performance for both of training and validation sample. We also compared rough set analysis and decision tree. This study experimented C4.5 for the comparison purpose. The results show that rough set analysis with expert's knowledge-based discretization produced more profitable rules than C4.5.