• Journal of Information Processing Systems
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• v.17 no.3
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• pp.473-488
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• 2021

The enterprise resource planning (ERP) system is a standardized and advanced business process that many companies are implementing now-a-days through customization. However, it affects the efficiency of operations as these customizations are based on uniqueness. In this study, we analyzed the impact of customized modules and processing time on customer service request (CSR), by utilizing the stacked CSR data during the construction and operation of ERP, focusing on small and medium-sized enterprises (SMEs). As a result, a positive correlation was found between unit companies and the length of ERP implementation; ERP modules and the length of ERP implementation; ERP modules and unit companies; and the type of ERP implementation and ERP module. In terms of CSR, a comparison of CSR processing time of CBO (customized business object) module and STD (standard) module revealed that while the five modules did not display statistically significant differences, one module demonstrated a statistically very significant difference. In sum, the analysis indicates that the CBO-type CSR and its processing cost are higher than those of STD-type CSR. These results indicate that companies planning to implement an ERP system should consider the ERP module and their customization ratio and level. It not only gives the theoretical validity that should be considered as an indicator for decision making when ERP is constructed, but also its implications on the impact of processing time suggesting that the maintenance costs and project scheduling of ERP software must also be considered. This study is the first to present the degree of impact on the operation and maintenance of customized modules based on actual data and can provide a theoretical basis for applying SW change ratio in the cost estimation of ERP system maintenance.

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.2
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• pp.11-18
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• 2021

A community-centered smart village process model was developed through the theoretical review of the rural field forum. By analyzing the difference in technology demand according to the digital capabilities of leaders by community type, village types were classified and detailed technologies were defined. The smart village process was proposed to enable residents to operate autonomously by inducing continuous interest and participation of local residents through the conception stage, planning stage, implementation and self-reliance stage, and allowing them to cooperate together. The business model canvas was reconstructed to be used in the workshop. It was applied to the village of Yesan-gun. As a result of running a resident workshop using the business model Cambus, the lack of resident awareness and illegal garbage dumping were presented as the first problems to be solved. The value of the village was set as 'a village that is clean and clean with a sense of residents, and a good place to live', and users were expressed as 'family' and 'outsiders'. It was suggested that we meet frequently to convey the value of the village by using broadcasting and announcements as a channel to convey the value. Core activities were to cultivate residents' consciousness, such as implementing a campaign against illegal garbage dumping, and to establish and guide separate collection sites. When a garbage collection center is installed, it was estimated that around 2 million won per month for management costs, and it was investigated that it was possible to spend an hour or so twice a month to solve the problem of illegal dumping. If a method to derive village projects based on the derived business model canvas is developed in the future, it will be more practical.

• Design & Manufacturing
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• v.16 no.4
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• pp.52-59
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• 2022

Currently, Korea is an aging society and is expected to become a super-aged society in about four years. X-ray devices are widely used for early diagnosis in hospitals, and many X-ray technologies are being developed. The development of X-ray device technology is important, but it is also important to increase the reliability of the device through accurate data management. Sensor nodes such as temperature, voltage, and current of the diagnosis device may malfunction or transmit inaccurate data due to various causes such as failure or power outage. Therefore, in this study, the temperature, tube voltage, and tube current data related to each sensor and detection circuit of the diagnostic X-ray imaging device were measured and analyzed. Based on QC data, device failure prediction and diagnosis algorithms were designed and performed. The fault diagnosis algorithm can configure a simulator capable of setting user parameter values, displaying sensor output graphs, and displaying signs of sensor abnormalities, and can check the detection results when each sensor is operating normally and when the sensor is abnormal. It is judged that efficient device management and diagnosis is possible because it monitors abnormal data values (temperature, voltage, current) in real time and automatically diagnoses failures by feeding back the abnormal values detected at each stage. Although this algorithm cannot predict all failures related to temperature, voltage, and current of diagnostic X-ray imaging devices, it can detect temperature rise, bouncing values, device physical limits, input/output values, and radiation-related anomalies. exposure. If a value exceeding the maximum variation value of each data occurs, it is judged that it will be possible to check and respond in preparation for device failure. If a device's sensor fails, unexpected accidents may occur, increasing costs and risks, and regular maintenance cannot cope with all errors or failures. Therefore, since real-time maintenance through continuous data monitoring is possible, reliability improvement, maintenance cost reduction, and efficient management of equipment are expected to be possible.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.1226-1236
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• 2022

Because students majoring in construction-related fields must develop a broad repository of knowledge and skills, effective transferal of these is the primary focus of most academic programs. While inculcation of this body of knowledge is certainly critical, actual construction projects are complicated ventures that involve levels of risk and uncertainty, such as resistant neighboring communities, unforeseen weather conditions, escalating material costs, labor shortages and strikes, accidents on jobsites, challenges with emerging forms of technology, etc. Learning how to develop a level of discernment about potential ways to handle such uncertainty often takes years of costly trial-and-error in the proverbial "school of hard knocks." There is therefore a need to proactively expedite the development of a sharpened intuition when making decisions. The AGC Education and Research Foundation case study committee was formed to address this need. Since its inception in 2011, 14 freely downloadable case studies have thus far been jointly developed by an academics and industry practitioners to help educators elicit varied responses from students about potential ways to respond when facing an actual project dilemma. AGC case studies are typically designed to focus on a particular concern and topics have thus far included: ethics, site logistics planning, financial management, prefabrication and modularization, safety, lean practices, preconstruction planning, subcontractor management, collaborative teamwork, sustainable construction, mobile technology, and building information modeling (BIM). This session will include an overview of the history and intent of the AGC case study program, as well as lively interactive demonstrations and discussions on how case studies can be used both by educators within a typical academic setting, as well as by industry practitioners seeking a novel tool for their in-house training programs.

• Journal of Korean Society of Rural Planning
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• v.28 no.4
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• pp.83-91
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• 2022

The goal of this study is to promote the spread of environmentally friendly agricultural products, which have been receiving a lot of attention lately, as a way to improve food safety and quality. As a result of the increased labor input, increased production costs, and an aging population, environmentally friendly agriculture is making it more difficult for farmers to expand their enterprises. In the meantime, consumers find it difficult to spread eco-friendly agricultural products due to their high expectations for safety and quality, as well as the desire to purchase products at a reasonable price. Previous studies have revealed differences in perceptions between eco-friendly agricultural producers and consumers. In light of this, this study divided consumers based on their characteristics (such as age, purchase history, health concerns, etc.), and different policies were proposed in order to increase purchasing factors for each group based on their characteristics. In order to gather information for this study, general citizens were asked about their perceptions of eco-friendly agricultural products, future purchase intentions and awareness, reliability, necessity, purpose, and information sources. A two-step clustering analysis was conducted using nominal and continuous variables simultaneously. The paper presents the three derived group differences (senior organic interest group, middle-aged organic interest group, and indifferent young organics) as well as group differences for the purchasing/non-purchasing factor analysis and policy improvement for each group. An eco-friendly agricultural product distribution proposal was made at the end of this article.

• Journal of Korean Society of Rural Planning
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• v.29 no.4
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• pp.127-135
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• 2023

This study examined the impact of changes in agricultural production methods on society, the economy, and the environment. While traditional open-field farming relied heavily on natural conditions, modern approaches, including greenhouse and smart farming, have emerged to mitigate the effects of climate and seasonal variations. Facility horticulture has been on the rise since the 1990s, and recently, there has been a growing interest in smart farms due to reasons such as climate change adaptation and food security. We compared open-field spinach and greenhouse spinach using agricultural income survey data, and we also compared greenhouse tomato cultivation with smart farming tomato cultivation, utilizing data from the smart farm survey reports. The economic results showed that greenhouse spinach increased yield by 25.8% but experienced a 29% decrease in income due to equipment depreciation. In the case of tomato production in smart farms, both yield and income increased by 36-39% and 34-46%, respectively. In terms of environmental impact, we also compared fertilizer and energy usage. It was found that greenhouse spinach used 29% less fertilizer but 14% more energy compared to open-field spinach. Smart farming for tomatoes saw a negligible decrease in electricity and fuel costs. Regarding the social impact, greenhouse spinach reduced labor hours by 31%, and the introduction of smart farming for tomatoes led to an average 11% reduction in labor hours. This reduction is expected to have a positive effect on sustainable farming. In conclusion, the transition from open-field to greenhouse cultivation and from greenhouse cultivation to smart farming appears to yield positive effects on the economy, environment, and society. Particularly, the reduction in labor hours is beneficial and could potentially contribute to an increase in rural populations.

• Korean Journal of Construction Engineering and Management
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• v.18 no.3
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• pp.12-21
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• 2017

From 1960, the government decided to build apartment houses on a large scale in order to resolve the rising housing problems. However, the maintenance issues that have arisen from the deterioration of housing has not received adequate attention. The policy focuses only on the supply of housing. By passing new laws, the durable period during which buildings allowed reconstruction was increased, and long term maintenance plans were treated as important issues. The government was then obligated to establish certain long term maintenance plans and costs by legislating a Housing Act and requiring it be adjusted every three years. However, when planning long-term repair costs, doing so without considering the time value of money would become a problem. In addition, if differences between the planned repair costs and actual costs occur, it becomes necessary to adjust the long-term repair costs but, as of yet, the criteria to adjust such things does not exist. For these reasons, if there is lack of money to execute large-scale repair work, a building is unlikely to respond to deterioration of housing; on the other hand, an unnecessary reserve or pool of money can lead to conflict among residents. Therefore, this paper will propose estimation and adjustment models considering the time value of money for long term maintenance costs of apartment houses.

• The Journal of Fisheries Business Administration
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• v.51 no.1
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• pp.37-52
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• 2020

The production of abalone seed has grown and been specialized since the 2000s with the growth of the abalone farming industry. Despite the increase in the production of abalone seeds, the sales volume of abalone seeds remained flat and competition among producers increased. This paper will analyze the management efficiency of abalone seed production fishery to diagnose the management status and improve the abalone seed production efficiency. In addition, this study is the result of the basic research on the abalone seed industry and it is meaningful to prepare a platform for further research since the management status survey and the management efficiency survey of abalone seed production fishery have not been conducted until now. The data on the farmed fish prices of abalone seeds were collected from surveys of sample fish as part of the fish seed observation project conducted by the Fisheries Outlook Center (FOC) of Korea Maritime and Fisheries Development Institute (KMI). Management efficiency analysis utilizes DEA (Data Envelopment Analysis) model. The DEA model was analyzed by classifying into CCR (Super-CCR), BCC, and SBM (Super-SBM) models according to the assumptions taking into account the characteristics of the industry. The slack considered in the SBM model was judged as possible decreases in input variables and increase in output variables. The average efficiency from the CCR model was analyzed to be 69%. The BCC model was classified into input and output orientations, and the average efficiency was 79% and 75%, respectively. There were seven production fisheries with an SE value of 1 or more, which remained unchanged in terms of size and could be benchmarked. The average efficiency of the SBM model was 59% for CRS and 66% for VRS. Under the VRS assumptions, the variable increase/decrease efficiency analysis shows that labor costs can be reduced by 37.3%, facility capacity by 18.8%, and operating costs by 8.5%. In order to improve management efficiency, Wando needs to reduce labor and management costs. In Jindo region, sales increase as well as labor cost reduction is urgent. In other regions, reduced facilities and increased sales are recommended.

• The Journal of Society for e-Business Studies
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• v.24 no.3
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• pp.19-33
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• 2019

Recently, manufacturers have been struggling to efficiently use production equipment as their production methods become more sophisticated and complex. Typical factors hindering the efficiency of the manufacturing process include setup cost due to job change. Especially, in the process of using expensive production equipment such as semiconductor / LCD process, efficient use of equipment is very important. Balancing the tradeoff between meeting the deadline and minimizing setup cost incurred by changes of work type is crucial planning task. In this study, we developed a scheduling model to achieve the goal of minimizing the duedate and setup costs by using reinforcement learning in parallel machines with duedate and work preparation costs. The proposed model is a Deep Q-Network (DQN) scheduling model and is a reinforcement learning-based model. To validate the effectiveness of our proposed model, we compared it against the heuristic model and DNN(deep neural network) based model. It was confirmed that our proposed DQN method causes less due date violation and setup costs than the benchmark methods.

• Journal of the Korea Fashion and Costume Design Association
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• v.14 no.1
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• pp.131-150
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• 2012

The purpose of this study is to provide the characteristics of marketing strategy on the SPA(Specialty store retailor of Private label Apparel) brand. This research can be used as information for the domestic SPA brand to enhance its international competitiveness. The characteristics of marketing strategy on the SPA brand are as follows. 1. One company integrate vertically the process of planning, production, promotion and distribution. 2. As using the advanced information, productions, and logistics systems, they are carried out speedy management. 3. The production strategies are focused on providing new goods of fast cycle and very diverse styles in a season, developing products that accurately reflect the general market trend and consumer demands, extending the line of goods, outsourcing of the place to reduce production costs. For high-quality goods, they are collaborating with the famous designers and developing of new and green environment materials. 4. Generally, the SPA brand emphasizes the low price strategy against the quality. 5. The promotion strategies are focused on conducting various unique and high sensible VMDs, fashion shows, star marketing, campaigns, aggressive publicity, magazine & outdoor advertisement and various events through the internet website, etc. 6. The place (distribution) strategies of SPA brand are focused on launching into global, expanding number of stores, increasing large-sized stores and diversifying the forms of store and selling.