• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• 제14권3호
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• pp.184-192
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• 2021

Domestic agriculture is facing real problems, such as a decrease in the population in rural areas, a shortage of labor due to an aging population, and increased risks due to the deepening of climate change. Smart farming technology is being developed to solve these problems. In the development of smart agricultural technology, irrigation control plays an important role in creating an optimal growth environment and is an important issue in terms of environmental protection. This paper is about the study of collecting and analyzing the rhizosphere environmental data of domestic paprika farms for the purpose of improving the quality of crops, reducing production costs, and increasing production. Irrigation control modeling presented in this paper Control modeling is to graphically present changes in a medium weight, feed, and drainage due to regional climatic features. To derive the graph, the parameters were determined through data collection and analysis, and the suggested irrigation control modeling method was applied to the collected rhizosphere environmental data to control irrigation in 6 regions (Gangwon-do, Chungnam, Jeonbuk, Jeonnam, Gyeongbuk, and Gyeongnam). The parameters were obtained and graphs were derived from them. After that, a study was conducted to analyze the derived parameters to verify the validity of the irrigation control modeling method and to correlate them with climatic features (average temperature and precipitation).

• Journal of Korean Society of Forest Science
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• 제100권2호
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• pp.305-313
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• 2011

Fertilization is essential to seedling production in nursery culture, but excessive fertilization can contaminate surface and ground water around the nursery. The objective of this study was to find optimal fertilization practice of container seedling production for reducing soil and water contamination around the nursery without compromising seedling quality. This study was conducted to investigate growth performance, photosynthesis, chlorophyll fluorescence, and chlorophyll contents of Liriodendron tulipifera growing under three different fertilization treatments (Constant rate, Three-stage rate, and Exponential rate fertilization). Root collar diameter, height, and biomass of L. tulipifera were the highest at Constant treatment. Like growth performance, seedling quality index (SQI) were higher at Constant than at other treatments, but not significantly different among treatments. L. tulipifera showed good photosynthetic capacity at all treatments. Photochemical efficiency and chlorophyll contents were significantly lower at Exponential than at other treatments. Therefore, Exponential fertilization which is 50% fertilizer of other treatments would maximize seedling growth and minimize nutrient loss.

• Journal of the Institute of Convergence Signal Processing
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• 제21권1호
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• pp.13-20
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• 2020

In shipyards, internal materials are assembled after designing and manufacturing each ship's block. Internal material assembly means the installation of parts and equipment except ship's body. In this process, if the assembly of pipes and equipment existing in the block is not done correctly during the assembly between blocks, this causes a lot of costs. In addition, even if the assembly of the internal materials already completed, the production efficiency of the ship is reduced due to rework when problems such as space arrangement of the internal materials occurs. Therefore, this study introduces space arrangement and inspection system before and after hull outfitting work based on coexistence reality technology using 3D design drawing to solve these problems. The various coexistence reality algorithms and inspection systems developed and introduced in this study are based on AR service, which has never been introduced in Korea. So it will be widely applicable to various manufacturing industries using design drawings such as automobiles and architectures as well as ship building process.

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• 제28권3호
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• pp.183-192
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• 2022

With the growth of the packaging industry, demand on the packaging printing comes in various forms. Customers' orders are diversifying and the standards for quality are increasing. Offset printing is mainly used in the packaging printing since it is easy to print in large quantities. However, productivity of the offset printing decreases when printing various order. This is because it takes time to change colors for each printing unit. Therefore, scheduling that minimizes the color replacement time and shortens the overall makespan is required. By the existing manual method based on workers' experience or intuition, scheduling results may vary for workers and this uncertainty increase the production cost. In this study, we propose an automated scheduling method of parallel offset printing process for packaging printing. We decompose the original problem into assigning and sequencing orders, and ink arrangement for printing problems. Vehicle routing problem and assignment problem are applied to each part. Mixed integer programming is used to model the problem mathematically. But it needs a lot of computational time to solve as the size of the problem grows. So guided local search algorithm is used to solve the problem. Through actual data experiments, we reviewed our method's applicability and role in the field.

• Journal of the Korean Crystal Growth and Crystal Technology
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• 제32권6호
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• pp.239-245
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• 2022

Reduced graphene oxide (rGO) has attracted many attention and applications due to its excellent electrochemical ability. Therefore, standardization of rGO through structural and thermal analysis facilitates quality improvement and management, enabling users to increase efficiency and reduce relevant costs. For rGO and graphene-related materials, it is very important to determine the number of layers and define the resulting difference in physical properties. In this study, 3~4 layers of rGO-1 and 9~10 layers of rGO-2 were obtained from graphene oxide (GO) through a hydrazine reduction process. For the prepared rGOs, X-ray diffraction (XRD) pattern obtained a diffraction peak at 2θ≈25° related to (002) reflection was used to calculate the layer numbers by determining interlayer distance and FWHM value. To reduce the angular uncertainty, XRD data analysis was performed with angle correction using standard reference materials for X-ray powder diffraction analysis. Precise interlayer distance and number of layers were determined using OriginLab and open-source XRD diffraction analysis programs using the angle-corrected diffraction data. TG-DSC thermal analysis was performed to further standardize the physical properties of rGO samples.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• 제15권4호
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• pp.257-270
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• 2022

In this paper, we design a smart factory risk improvement system and risk improvement method using AI edge devices. The smart factory risk improvement system collects, analyzes, prevents, and promptly responds to the worker's work performance process in the smart factory using AI edge devices, and can reduce the risk that may occur during work with improving the defect rate when workers perfom jobs. In particular, based on worker image information, worker biometric information, equipment operation information, and quality information of manufactured products, it is possible to set an abnormal risk condition, and it is possible to improve the risk so that the work is efficient and for the accurate performance. In addition, all data collected from cameras and IoT sensors inside the smart factory are processed by the AI edge device instead of all data being sent to the cloud, and only necessary data can be transmitted to the cloud, so the processing speed is fast and it has the advantage that security problems are low. Additionally, the use of AI edge devices has the advantage of reducing of data communication costs and the costs of data transmission bandwidth acquisition due to decrease of the amount of data transmission to the cloud.

• Journal of the Korea Society for Simulation
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• 제19권4호
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• pp.11-19
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• 2010

ZigBee is a standard for wireless personal area networks(WPANs) based on the IEEE 802.15.4 standard. It has been developed for low cost and low power consumption. There are two alternative routing schemes that have been proposed for the ZigBee standard: Ad-hoc On-Demand Distance Vector(AODV) and tree routing. The tree routing forwards packets from sensors to a sink node based on the parent-child relationships established by the IEEE 802.15.4 MAC topology formation procedure. In order to join the network, a sensor node chooses an existing node with the strongest RSSI(Received signal strength indicator) signal as a parent node. Therefore, some nodes carry a large amount of traffic load and exhaust their energy rapidly. To overcome this problem, we introduce a new metric based on link quality and traffic load for load balancing. Instead of the strength of RSSI, the proposed scheme uses the new metric to choose a parent node during the topology formation procedure. Extensive simulation results using TOSSIM(TinyOS mote SIMulator) show that the CFR scheme outperforms well in comparison to the conventional tree routing scheme.

• KIPS Transactions on Software and Data Engineering
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• 제12권4호
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• pp.189-198
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• 2023

As crimes frequently occur on the street, the spread of CCTV is increasing. However, due to the shortcomings of passively operated CCTV, the need for intelligent CCTV is attracting attention. Due to the heavy system of such intelligent CCTV, high-performance devices are required, which has a problem in that it is expensive to replace the general CCTV. To solve this problem, an intelligent CCTV system that recognizes low-quality images and operates even on devices with low performance is required. Therefore, this paper proposes a Saying CCTV system that can detect threats in real time by using the AWS cloud platform to lighten the system and convert images into text. Based on the data extracted using YOLO v4 and OpenPose, it is implemented to determine the risk object, threat behavior, and threat situation, and calculate the risk using machine learning. Through this, the system can be operated anytime and anywhere as long as the network is connected, and the system can be used even with devices with minimal performance for video shooting and image upload. Furthermore, it is possible to quickly prevent crime by automating meaningful statistics on crime by analyzing the video and using the data stored as text.

• Korean Chemical Engineering Research
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• 제61권2호
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• pp.175-188
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• 2023

Global interest in hydrogen energy is increasing as an eco-friendly future energy that can replace fossil fuels. Accordingly, a next-generation hydrogen production technology using microorganisms, nuclear power, etc. is being developed, while a lot of time and effort are still required to overcome the cost of hydrogen production based on fossil fuels. As a way to minimize greenhouse gas emissions in the hydrocarbon-based hydrogen production process, methane direct decomposition technology has recently attracted attention. In order to improve the economic feasibility of the process, the simultaneous production of value-added carbon materials with hydrogen can be one of the most essential aspects. For that purpose, various studies on catalysis related to the quality and yield of high-value carbon materials such as carbon nanotubes (CNTs). In terms of process technology, a number of the research and development of fluidized-bed reactors capable of continuous production and improved gas-solid contact efficiency has been attempted. Recently, methane direct decomposition technology using a fluidized bed has been developed to the extent that it can produce 270 kg/day of hydrogen and 1000 kg/day of carbon. Plus, with the development of catalyst regeneration, separation and recirculation technologies, the process efficiency can be further improved. This review paper investigates the recent development of catalysts and fluidized bed reactor for methane direct pyrolysis to identify the key challenges and opportunities.

• Korean Journal of Construction Engineering and Management
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• 제24권3호
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• pp.12-19
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• 2023

In the case of the construction industry, the relationship between process and cost should be appropriately distributed so that the finished product can be delivered at the minimum fee within the construction period. At that time, it should be considered the size of the bridge, the construction method, the environment and production capacity of the factory, and the transport distance. However, due to various reasons that occur during the construction period, problems such as construction delay, construction cost increase, and quality and reliability degradation occur. Therefore, a systematic and scientific construction technique and process management technology are needed to break away from the conventional method. The prefab(Pre-Fabrication) is a representative OSC (Off-Site Construction) method manufactured in a factory and constructed onsite. This study develops a resource and process plan optimization system for the process management of the Nodular girder, a prefab bridge girder. A simulation algorithm develops to automatically test various variables in the personnel equipment mobilization plan to derive the optimal value. And, the algorithm was applied to the Paju-Pocheon Expressway Construction (Section 3) Dohwa 4 Bridge under construction, and the results compare. Based on construction work standard product calculation, actual input manpower, equipment type, and quantity were applied to the Activity Card, and the amount of work by quantity counting, resource planning, and resource requirements was reflected. In the future, we plan to improve the accuracy of the program by applying forecasting techniques including various field data.