• Asian Journal of Turfgrass Science
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• v.21 no.2
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• pp.147-154
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• 2007

In March of 2004, gray snow mold (Typhula blight) caused by Typhula spp. occurred on perennial ryegrass (Lolium perenne L.) and Kentucky bluegrass (Poo pratensis L.) at MuJu golf courses in Jeonbuk Province. Leaves in the affected areas were matted together and frequently covered with white to grayish mycelia. Sclerotia were formed on the leaf blade, leaf sheath, or crown regions. The fungus isolated from the diseased leaf formed whitish mycelium, clamp connections, and light pink to brown, irregular-shaped small sclerotia of less than 1.4 mm in diameter, which are characteristic to Typhula incarnata. Optimum temperature ranges for mycelial growth were $5^{\circ}C$ to $15^{\circ}C$. The causal organism was confirmed to be T. incarnata as the partial sequence of its ribosomal RNA ITS1 (internal transcribed spacer) region was 91% homologous to those of T. incarnata in GenBank database. Out of the 14 fungicides tested fur antifungal activity in vitro, 10 fungicides including iprodione, tebuconazole, polyoxin D, flutolanil, hexaconazole, tolclofos-methyl, fosetyl-Al, mepronil, pencycuron+tebuconazole, and fenarimol completely inhibited fungal growth at their recommended concentrations. In the field test, these fungicides and others such as thifluzamide and thiram effectively controlled the gray snow mold of turfgrass with some variable degrees of control efficacies.

• Journal of the Korea Society of Computer and Information
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• v.11 no.3
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• pp.117-124
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• 2006

In this paper, we propose the optimal migration path searching method including path adjustment and reassignment techniques for an efficient migration of mobile agent which has an autonomous ability for some task processing. In traditional agent system, if the various and large quantify of task processing were required from the users, it could be derive excessive network traffic and overload due to increasing the size of agent. And also, if an agent migrates from node to node according to routing schedules specified by the user at which the most of network traffic occurs, it could not actively cope with particular situations such as communication loss and node obstacles and required much cost for node traversal Therefore. this paper presents the migration method of agent which can try to adjust and reassign path to the destination automatically through the optimal path search using by network traffic perception in stead of the passive routing schedule by the user. An optimal migration path searching and adjustment methods ensure the migration reliability on distributed nodes and reduce the traversal task processing time of mobile agent by avoiding network traffic paths and node obstacles.

• Korean Journal of Soil Science and Fertilizer
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• v.40 no.2
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• pp.131-135
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• 2007

This study was performed as an effort to reduce soil loss by investigating the phase of water flow according to soil texture and rainfall pattern and by determining the canopy cover subfactor in the RUSLE (revised universal soil loss equation). Red pepper was planted at the 15% sloped lysimeter of $2m{\times}5m{\times}0.5m$ ($width{\times}length{\times}depth$) with three different textured soils (loam, clay loam and sandy loam) and the relationship between amount and intensity of rainfall; soil loss and the amount of runoff; and amount of rainfall and runoff at different soil texture were measured at the experiment station of the National Institute of Agricultural Science and Technology (NIAST) during May to October of 2005. The amount of runoff increased with increasing amount of rainfall, showing difference in the relative increase rate of runoff at different soil texture. The increase rate of runoff with unit increase of rainfall for the lysimeter with red pepper was 0.44, 0.41 and 0.13 for loam, clayey loam and sandy loam, respectively. The minimum amount of rainfall for runoff was 23.53 mm for sandy loam, 10.35 mm for loam and 5.46 mm for clayey loam, respectively. The canopy cover subfactors of red pepper were 0.425, 0.459, and 0.478 for sandy loam, loam and clayey loam, respectively.

• The Korean Journal of Franchise Management
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• v.12 no.4
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• pp.41-54
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• 2021

Purpose: Delivery food orders are on the rise due to the COVID 19 pandemic. Many customers are ordering food through delivery apps rather than visiting restaurants to eat out. Delivery application platforms are growing due to the development of O2O. Most of the people who provide gig worker for delivery applications are rider. Rider provides labor on their own terms and have more work flexibility and autonomy than ordinary workers. Trust can be transferred from a well-known entity to an unknown entity. From the customer's point of view of using the delivery application, trust can be seen through the third-party trust of the delivery application platform-rider-customer. Therefore, this study intends to investigate the effect on delivery application trust and rider trust through the well-known characteristics of delivery applications. Research design, data, and methodology: This study was conducted on Korean consumers over 20 years of age who have ordered food through a delivery application for the past month. After educating 5 investigators about the purpose of this study, 60 copies of the survey were conducted per person. During the investigation period, from September 2 to September 26, 2021, 322 copies were collected over 25 days. Among the collected questionnaires, 37 were excluded from insincere or partially unanswered, and 285 were used for analysis. In addition, the collected data were analyzed using SPSS 25.0 and AMOS 25.0. Result: As a result of the study, convenience, price, and variety of restaurants were found to have a significant positive (+) effect on app trust, but design did not have a significant effect on app trust. Also, it was found that convenience had a significant positive (+) effect on trust in rider, but design, price, and variety of restaurants did not have a significant effect. App trust was found to have a significant positive (+) effect on rider trust and intention to use, and it was found to have a significant positive (+) effect on rider trust and intention to use. Conclusions: First, this study established a structural framework between delivery application characteristics-delivery-app trust-rider trust-intention to use. Second, in this study, it was found that customer trust in well-known delivery applications was transferred to less-known rider trust. Third, the delivery application should increase the convenience of use. Fourth, delivery application should set the delivery fee appropriately. Fifth, delivery application must continuously train the rider.

• Journal of the Korean earth science society
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• v.42 no.5
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• pp.504-513
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• 2021

Different physical processes, according to the atmospheric boundary layer types, were used in the Local Data Assimilation and Prediction System (LDAPS) of the Unified Model (UM) used by the Korea Meteorological Administration (KMA). Therefore, it is important to verify the atmospheric boundary layer types in the numerical model to improve the accuracy of the models performance. In this study, the atmospheric boundary layer types were verified using observational data. To classify the atmospheric boundary layer types, summer intensive observation data from radiosonde, flux observation instruments, Doppler wind Light Detection and Ranging(LIDAR) and ceilometer were used. A total number of 201 observation data points were analyzed over the course 61 days from June 18 to August 17, 2019. The most frequent types of differences between LDAPS and observed data were type 1 in LDAPS and type 2 in observed(each 53 times). And type 3 difference was observed in LDAPS and type 5 and 6 were observed 24 and 15 times, respectively. It was because of the simulation performance of the Cloud Physics such as that associated with the simulation of decoupled stratocumulus and cumulus cloud. Therefore, to improve the numerical model, cloud physics aspects should be considered in the atmospheric boundary layer type classification.

• Convergence Security Journal
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• v.21 no.2
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• pp.57-66
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• 2021

Deep neural networks (DNNs) provide excellent performance for image, speech, and pattern recognition. However, DNNs sometimes misrecognize certain adversarial examples. An adversarial example is a sample that adds optimized noise to the original data, which makes the DNN erroneously misclassified, although there is nothing wrong with the human eye. Therefore studies on defense against adversarial example attacks are required. In this paper, we have experimentally analyzed the success rate of detection for adversarial examples by adjusting various parameters. The performance of the ensemble defense method was analyzed using fast gradient sign method, DeepFool method, Carlini & Wanger method, which are adversarial example attack methods. Moreover, we used MNIST as experimental data and Tensorflow as a machine learning library. As an experimental method, we carried out performance analysis based on three adversarial example attack methods, threshold, number of models, and random noise. As a result, when there were 7 models and a threshold of 1, the detection rate for adversarial example is 98.3%, and the accuracy of 99.2% of the original sample is maintained.

• Journal of Internet Computing and Services
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• v.22 no.5
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• pp.47-55
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• 2021

Analysis of research trends in specific subject areas is performed by examining related topics and subject changes by using topic modeling techniques through keyword extraction for most of the literature information (paper, patents, etc.). Unlike existing research methods, this paper extracts topics related to the research topic using the LDA topic modeling technique for the project information of national R&D projects provided by the National Science and Technology Knowledge Information Service (NTIS) in the field of artificial intelligence. By analyzing these topics, this study aims to analyze research topics and investment directions for national R&D projects. NTIS provides a vast amount of national R&D information, from information on tasks carried out through national R&D projects to research results (thesis, patents, etc.) generated through research. In this paper, the search results were confirmed by performing artificial intelligence keywords and related classification searches in NTIS integrated search, and basic data was constructed by downloading the latest three-year project information. Using the LDA topic modeling library provided by Python, related topics and keywords were extracted and analyzed for basic data (research goals, research content, expected effects, keywords, etc.) to derive insights on the direction of research investment.

• Convergence Security Journal
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• v.21 no.1
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• pp.191-200
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• 2021

Artificial intelligence technology is developing in an environment where a lot of data is produced due to the development of computing technology, a cloud environment that can store data, and the spread of personal mobile phones. Among these artificial intelligence technologies, the deep neural network provides excellent performance in image recognition and image classification. There have been many studies on image detection for forest fires and fire prevention using such a deep neural network, but studies on detection of cigarette smoking were insufficient. Meanwhile, military units are establishing surveillance systems for various facilities through CCTV, and it is necessary to detect smoking near ammunition stores or non-smoking areas to prevent fires and explosions. In this paper, by reflecting experimentally optimized numerical values such as activation function and learning rate, we did the detection of smoking pictures and non-smoking pictures in two cases. As experimental data, data was constructed by crawling using pictures of smoking and non-smoking published on the Internet, and a machine learning library was used. As a result of the experiment, when the learning rate is 0.004 and the optimization algorithm Adam is used, it can be seen that the accuracy of 93% and F1-score of 94% are obtained.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.9 no.10
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• pp.763-774
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• 2019

A collaborative system supports collaboration among participants by providing functions such as group composition and management of data shared for collaboration. In recent years, research on collaborative services based on the blockchain technology has been done to guarantee the reliability of collaboration processes and outcomes. The diversity of the application domains in which collaborations are performed and the various characteristics of the participants in the collaboration group naturally leads to various forms of collaborative processes. In order for these processes to produce the desired outcome of the collaborative efforts, it is desirable to specify the appropriate collaborative process in advance, so that the participants can understand and agree on the process, carrying out the collaboration. In this paper, we propose a method to control flexible collaborative processes according to workflow specifications in the Ethereum-based collaborative service environment. The specification of the workflow for the designated task is stored in the Ethereum smart contract and the process of performing the task is controlled according to the stored workflow specification. For this, we introduce JSFlow which is a simple workflow specification method using JSON and an Ethereum library to utilize it.

• Journal of Digital Convergence
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• v.19 no.12
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• pp.495-504
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• 2021

This review aims to identify the virtual reality (VR)-based home modification programs and provide basic data for the future development and application of domestic VR-based home modification programs. We collected the studies of academic publication or conference, symposium addressed VR-based home modification from January 2011 to June 2021 using hand searching and databases such as Medline, Embase, and Scopus. A total of 7 studies were selected through selection criteria, and the studies were quantitative and qualitative studies on the development of VR prototype for home modification and the acceptability and usability of the programs. VR-based home modification have been developed and applied for various purposes for stakeholders involved in home modification. It can be used as the tools for fostering experts in home modification, evaluating the home environment remotely, and facilitating communication and collaboration with the stakeholders in the modification process. In the future, studies on development and feasibility of VR-based home modification program reflecting the characteristics of domestic housing should be conducted, and it is expected to be utilized as a tool to support the home modification process.