• Journal of Korean Society for Quality Management
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• v.49 no.2
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• pp.213-231
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• 2021

Purpose: This study intends to provide decision-making information to improve efficiency by analyzing the management efficiency of smart greenhouse business entities and identifying factors that affect the efficiency based on input and output. Methods: The subjects of analysis were business entities for cultivating strawberries in smart greenhouses in Jeolla region (northern and southern Jeolla provinces), and the analysis focused on the management performance of the 2019-2020 crop period (year). Data Envelopment Analysis(DEA) was applied as an analysis method for efficiency analysis, Quantile Regression(QR) analysis was applied as a factor affecting the efficiency. Results: The reason for the efficiency gap between business entities was that there were many business entities that did not minimize the input cost at the current level of output, and the area where the variance among business entities was large was the fixed cost per 10a. In the results of the affecting factor analysis, it was found that the seed-seedlings cost, fertilizer cost, other material cost, and employment and labor cost had a negative (-) effect on the efficiency, and that the repair and maintenance cost had a positive (+) effect. Conclusion: Therefore, to achieve the efficiency of scale, it is necessary to reduce the input scale to an appropriate level. In the case of business entities with low efficiency by quartile, the seed-seedlings, fertilizer, and other material costs reduce expenditures, and repair maintenance costs can improve efficiency by increasing expenditures.

• The Plant Pathology Journal
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• v.38 no.4
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• pp.345-354
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• 2022

NADPH oxidase (Nox) complexes are known to play essential roles in differentiation and proliferation of many filamentous fungi. However, the functions of Noxs have not been elucidated in Colletotrichum species. Therefore, we set out to characterize the roles of Nox enzymes and their regulators in Colletotrichum scovillei, which causes serious anthracnose disease on pepper fruits in temperate and subtropical and temperate region. In this study, we generated targeted deletion mutants for CsNox1, CsNox2, CsNoxR, and CsNoxD via homologous recombination. All deletion mutants were normal in mycelial growth, conidiation, conidial germination, and appressorium formation, suggesting that CsNox1, CsNox2, CsNoxR, and CsNoxD are not involved in those developmental processes. Notably, conidia of 𝜟Csnox2 and 𝜟Csnoxr, other than 𝜟Csnox1 and 𝜟Csnoxd, failed to cause anthracnose on intact pepper fruits. However, they still caused normal disease on wounded pepper fruits, suggesting that Csnox2 and CsnoxR are essential for penetration-related morphogenesis in C. scovillei. Further observation proved that 𝜟Csnox2 and 𝜟Csnoxr were unable to form penetration peg, while they fully developed appressoria, revealing that defect of anthracnose development by 𝜟Csnox2 and 𝜟Csnoxr resulted from failure in penetration peg formation. Our results suggest that CsNox2 and CsNoxR are critical for appressorium-mediated penetration in C. scovillei-pepper fruit pathosystem, which provides insight into understanding roles of Nox genes in anthracnose disease development.

• Smart Media Journal
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• v.6 no.4
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• pp.58-64
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• 2017

Modern society is characterized by rapid increase in world population, aging of the rural population, decrease of cultivation area due to industrialization. The food problem is becoming an important issue with the farmers and becomes rural. Recently, the researches about the field of the smart farm are actively carried out to increase the profit of the rural area. The existing smart farm researches mainly monitor the cultivation environment of the crops in the greenhouse, another way like in the case of poor quality t is being studied that the system to control cultivation environmental factors is automatically activated to keep the cultivation environment of crops in optimum conditions. The researches focus on the crops cultivated indoors, and there are not many studies applied to the cultivation environment of crops grown outside. In this paper, we propose a method to improve the harvestability of poor areas by monitoring the areas with bad harvests by using big data analysis, by precisely predicting the harvest timing of fruit trees growing in orchards. Factors besides for harvesting include fruit color information and fruit weight information We suggest that a harvest correlation factor data collected in real time. It is analyzed using the Apache Spark engine. The Apache Spark engine has excellent performance in real-time data analysis as well as high capacity batch data analysis. User device receiving service supports PC user and smartphone users. A sensing data receiving device purpose Arduino, because it requires only simple processing to receive a sensed data and transmit it to the server. It regulates a harvest time of fruit which produces a good quality fruit, it is needful to determine a poor harvest area or concentrate a bad area. In this paper, we also present an architectural model to determine the bad areas of fruit harvest using strong data analysis.

• Journal of the Economic Geographical Society of Korea
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• v.27 no.1
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• pp.38-52
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• 2024

Digital transformation industry contributes to the improvement of productivity in overall industrial production, the smart green industry for carbon neutrality and sustainable growth is growing as a future industry. The purpose of this paper is to explore the status and role of the industry in the future industry innovation ecosystem through the analysis of the growth drivers and location pattern changes of the smart green industry. The industry is on the rise in both metropolitan and non-metropolitan areas, and the growth of the industry can be seen in non-metropolitan and non-urban areas. In particular, due to the smart green industrial complex pilot project, the creation of Gwangju Jeonnam Innovation City, and the promotion of new and renewable energy policies, the emergence of core aggregation areas (HH type) in the coastal areas of Honam and Chungcheongnam-do, and the formation of isolated centers (HL type) in the Gyeongsang region, new and renewable energy production companies are being accumulated in non-metropolitan areas. Therefore, the smart green industry is expected to promote the formation of various specialized spokes in non-urban areas in the future industrial innovation ecosystem that forms a multipolar hub-spoke network structure, where policy factors are the triggers for growth.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.1
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• pp.82-89
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• 2015

The researches of image recognition have been processed traditionally. Especially, face recognition technology has been received attractions with advance and applied to various areas according as camera sensor embedded into many devices such as smart phone. In this study, we design and develop a feature vector generation technique of face for making animation caricatures using methods for face detection which are previous stage of face recognition. At first, we detect both face region and detailed eye region of component element by Viola&Johns's realtime detection method which are called as ROI(Region Of Interest). And then, we generate feature vectors of eye region by utilizing factors as opposed to the periphery and by using appearance information of eye. At this point, we focus on the embedded information in many color spaces to overcome the problems which can be occurred by using one color space. We propose a feature vector generation method using information from many color spaces. Finally, we experiment the test of feature vector generation by the proposed method with enough quantity of sample picture data and evaluate the proposed method for factors of estimating performance such as error rate, accuracy and generation time.

• The Journal of the Korea Contents Association
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• v.22 no.10
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• pp.703-722
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• 2022

The concentration of local businesses in the capital region promotes a decrease in the local population and polarization between the capital region and non-capital regions. It affects the competitiveness of local industries and creates a vicious cycle throughout the local economy, society and culture. Therefore, this study classified the companies in the capital region and non-capital regions by group and examined the effect of the innovation capability factors of companies on the creation of business performance. We analyzed the effects of R&D capabilities, which are elements of innovation capability, and open innovation and convergence capabilities on business performance. Smart PLS 3.0 was used for analysis including direct and indirect mediating and moderating effects, multi-group analysis, and structural equation model analysis. As a result, R&D capability did not have a significant effect on business performance, but it has a positive influence towards business performance through convergence capability and open innovation. However, the effectiveness of open innovation in non-capital regions and convergence capabilities in capital region were not statistically significant. In particular, in terms of open innovation, as the difference between groups is statistically clear, follow-up measures are suggested especially in non-capital regions.

• Smart Media Journal
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• v.13 no.5
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• pp.33-44
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• 2024

Chungbuk has various regional characteristics in terms of population composition by region, industrial facilities, and distribution of emergency medical institutions. However, there are no studies yet that have analyzed regional characteristic factors related to the occurrence characteristics of cardiac arrest patients. Therefore, this study provided basic data to establish a response system for OHCA patients suitable for the characteristics of the Chungcheongbuk-do region by analyzing the characteristics of OHCA patients and the transfer status of 119 paramedics in Chungcheongbuk-do. This study is a retrospective study that analyzed 1,188 cardiac arrest patients transferred by ambulance based on raw data from the survey on acute cardiac arrest in Chungbuk (2020). There are a total of 11 emergency medical institutions in Chungbuk-do, which are concentrated in city-level areas, so the transfer time of patients to hospitals in county-level areas was delayed. In the county-level area, the frequency of dispatch of special paramedics was relatively small, and the frequency of administration of cardiac arrest drugs to help resuscitate cardiac arrest patients was also low. In conclusion, efforts should be made to improve accessibility of emergency medical services (deployment of emergency vehicles in marginal areas, proper placement of emergency medical institutions, etc.), to promote prevention of traumatic cardiac arrest patients, and to expand the scope of work to strengthen the first aid expertise of paramedics.

• Journal of the Korea Society of Computer and Information
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• v.17 no.12
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• pp.137-148
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• 2012

In this paper, we proposed the location-aware coordinate routing algorithm for improving the performance of routing algorithm by using ZigBee in Smart Grid environment. A distributed address allocation scheme used an existing algorithm that has wasted in address space. The x, y and z coordinate axes from divided address space of 16 bit to solve this problems. However, coordinate routing does not take account of wireless link condition. If wiress link condition is not considered, when the routing table is updated, the nodes with bad link conditions are updated in the routing table and can be chosen as the next hop. This brings out the retransmissions because of received packet's errors. Also, because of these retransmissions, additional power is consumed. In this paper, we propose the location-aware coordinate routing algorithm considering wiress link condition, where reliable data transmission is made and the consumed enegy is minimize. and we compared and connected region and transition region of ZigBee location based routing in the aspect of average number of multi hops, subordinate packet delivery ratio, delay time, and energy consumption of proposed algorithm. It turned out that there were improvements in performances of each items.

• Smart Media Journal
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• v.10 no.2
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• pp.70-75
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• 2021

Grouping and classifying similar designs in design increase efficiency in terms of management and provide convenience in terms of use. Using artificial intelligence algorithms, this study attempted to classify textile designs into four categories: dots, flower patterns, stripes, and geometry. In particular, we explored whether it is possible to find and explain the regions of interest underlying classification from the perspective of artificial intelligence. We randomly extracted a total of 4,536 designs at a ratio of 8:2, comprising 3,629 for training and 907 for testing. The models used in the classification were VGG-16 and ResNet-34, both of which showed excellent classification performance with precision on flower pattern designs of 0.79%, 0.89% and recall of 0.95% and 0.38%. Analysis using the Local Interpretable Model-agnostic Explanation (LIME) technique has shown that geometry and flower-patterned designs derived shapes and petals from the region of interest on which classification was based.

• Korean Journal of Remote Sensing
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• v.36 no.6_2
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• pp.1551-1565
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• 2020

On April 4, 2019, a forest fire started in Goseong County and lasted for three days, burning the neighboring areas of Sokcho. The strong winds moved the blaze from one region to another region and declared the worst wildfire in South Korea in years. More than 1,880 facilities, including 400 homes, were burnt down. The fire burned a total area of 529 hectares (1,307 acres), which involved 13,000 rescuers and 16,500 military troops to control the fire occurrence. Thousands of people were evacuated, and two people are dead. This study generated post-wildfire maps to provide necessary data for evacuation and mitigation planning to respond to this destructive wildfire, also prevent further damage and restore the area affected by the wildfire. This study used KOMPSAT-3A and Sentinel-2 imagery to map the post-wildfire condition. The SVM showed higher accuracy (overall accuracy 95.29%) compared with ANN (overall accuracy of 94.61%) for the KOMPSAT-3A. Moreover, for Sentinel-2, the SVM attained a higher accuracy (overall accuracy of 91.52%) than the ANN algorithm (overall accuracy 90.11%). In total, four post-wildfire burned area maps were generated; these results can be used to assess the area affected by the Sokcho wildfire and wildfire mitigation planning in the future.