• Korean Journal of Human Ecology
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• v.20 no.2
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• pp.427-437
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• 2011

This study was conducted to investigate the utilization, recognition, and satisfaction of environment-friendly agricultural products (EAPs) in school food services according to the type of foodservice in the Jeonbuk area. Among the 270 school food service providers evaluated, 56.3% of the schools were located in an urban area and 43.7% were in a rural area. About 80% of urban schools used the EAPs for school foodservice, and 89.8% in rural schools (p<.05). The purchase frequency of grain (p<.01), fruits (p<.05), and processed foods (e.g. Tofu) (p<.001) was significantly different between the urban and rural schools. The perception of school dietitians in urban and rural schools between the EAPs and general agricultural products was significantly different (p<.05). The most different fact was 'safety' (p<.001). Most school dietitians has a gut understanding and a lot of confidence about the system of EAPs (p<0.01). The satisfaction score with EAPs was 3.35; in the urban schools it was 3.36 and in the rural schools 3.12 (p<.01). The satisfaction with EAPs in urban and rural schools was significantly different with regard to several factors; these were 'design' (p<.05), 'color' (p<.001), 'fresh' (p<.001), and 'diversity' (p<.01). There are conflicting views between the urban and rural schools for the additional costs brought by using EAPs (p<.01). In conclusion, our central and local governments should change their roles in financially positive ways and reflect the issue to make the policy effective.

• The Journal of Industrial Distribution & Business
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• v.8 no.5
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• pp.77-85
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• 2017

Purpose - The purpose of this study is to investigate the variables that lead consumers to visit traditional markets and buy market goods. Thus, the current research examined the relationship between satisfaction and return intention as among the factors influencing loyalty. Research design, data, and methodology - This study was conducted to examine the effects of the perceived level of factors on loyalty and how it influenced consumers' visits to traditional markets in 125 adult adolescents and women living in Mok-po area. The results of the questionnaire were obtained. The statistical data of the questionnaire were verified by SPSS. Results - In this study, consumers' perception level of eight loyalty factors can be perceived by the traditional Korean market. The empirical analysis is summarized as follows. First, by selecting five representative variables influencing intention to return to traditional markets, Mok-po area consumers were affected by the intention to revisit according to the intensity of recognition level among these variables. Second, the higher the perceived level of product price, quality of access (accessibility) among the factors that consumers perceive as important factors in visiting traditional markets were heightened. Third, Mokpo residents are aware of the main important factors of visiting the market such as receiving a friendly atmosphere (image) about traditional market, market environment (hygiene and cleanliness), connection with the local economy, and customer service such as kindness, refund and return. These loyalty factors did not affect consumers' intention to revisit. In other words, image, environment, regional economic linkage, and these factors did not have a positive effect on revisit intention. Conclusions - The empirical analysis of this study suggests that factors that directly affect loyalty among the key factors that play a major role in visiting traditional markets should be identified and developed as loyalty factors. It is necessary to identify the key factors influencing the satisfaction and loyalty of traditional market users, and operate a system that systematically and comprehensively manages and evaluates them. In order to do this, the government, the local governments, and related organizations should regularly conduct loyalty and satisfaction surveys on visa recognition levels and establish strategies for dramatic improvement measures.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.5
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• pp.19-32
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• 2018

This study focuses on an M/M/1 queue with an attached continuous-type inventory. The customers arrive into the system according to the Poisson process, and are served in their arrival order; i.e., first-come-first-served. The service times are assumed to be independent and identically distributed exponential random variable. At a service completion epoch, the customer consumes a random amount of inventory. The inventory is controlled by the traditional (s, S)-inventory policy with a generally distributed lead time. A customer that arrives during a stock-out period assumed to be lost. For the number of customers and the inventory size, we derive a product-form stationary joint probability distribution and provide some numerical examples. Besides, an operational strategy for the inventory that minimizes the long-term cost will also be discussed.

• Journal of Convergence for Information Technology
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• v.10 no.4
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• pp.1-10
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• 2020

The performance of the personalized product recommendation system for offline shopping malls is poor compared with the one using online environment information since it is difficult to obtain visitors' characteristic information. In this paper, a mobile robot platform is suggested capable of recommending personalized advertisement using customers' sex and age information provided by Face API of MS Azure Cloud service. The performance of the developed robot is verified through locomotion experiments, and the performance of API used for our robot is tested using sampled images from open Asian FAce Dataset (AFAD). The developed robot could be effective in marketing by providing personalized advertisements at offline shopping malls.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.37 no.4
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• pp.106-115
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• 2014

Until now, because a new product (or facility) launched in market has been retired from one year of age, we can have had ASL by stub-curve method by Iowa curve. Recently, many innovative products with important role in market like display and solar-cell etc. are more durable and, what are better, they have the constant variance in ASL because of their good quality. Of course, there are some ones like smart mobile phone with relatively big dispersion in ASL. Estimating ASL of products like display and solar-cell etc., the new approach is needed. In this paper a new method applied traditional Iowa curve with accelerated reliability test (indoor/outdoor) etc. is proposed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.2
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• pp.394-402
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• 2010

At a recent, enterprises based on online-service are established because of rapid growth of information network. These enterprises collect personal information and do customer management. If customers use a paid service, company send billing information to customer and customer pay it. Such circulation and management of information is big issue but most companies don't care of information security. Actually, personal information that was managed by largest internal open-market was exposed. For safe customer information management, this paper proposes the method that decrease load of RSA cryptography algorithm that is commonly used for preventing from illegal attack or hacking. The method for decreasing load was designed by Binary NAF Method and it can operates modular Exponentiation rapidly. We implemented modular Exponentiation algorithm using existing Binary Method and Windows Method and compared and evaluated it.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.179-186
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• 2021

We have been developed the smart tourism app and the Instagram and YouTube contents to provide personalized tourism information and travel product information to individual tourists. In this paper, we develop a rule-based smart tourism chatbot with the khaiii (Kakao Hangul Analyzer III) morphological analyzer and Neo4J graph database. In the proposed chatbot system, we use a morpheme analyzer, a proper noun dictionary including tourist destination names, and a general noun dictionary including containing frequently used words in tourist information search to understand the intention of the user's question. The tourism knowledge base built using the Neo4J graph database provides adequate answers to tourists' questions. In this paper, the nodes of Neo4J are Area based on tourist destination address, Contents with property of tourist information, and Service including service attribute data frequently used for search. A Neo4J query is created based on the result of analyzing the intention of a tourist's question with the property of nodes and relationships in Neo4J database. An answer to the question is made by searching in the tourism knowledge base. In this paper, we create the tourism knowledge base using more than 1300 Jeju tourism information used in the smart tourism app. We plan to develop a multilingual smart tour chatbot using the named entity recognition (NER), intention classification using conditional random field(CRF), and transfer learning using the pretrained language models.

• Smart Media Journal
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• v.11 no.5
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• pp.48-55
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• 2022

Tomato crops are easy to expose to disease and spread in a short period of time, so late measures against disease are directly related to production and sales, which can cause damage. Therefore, there is a need for a service that enables early prevention by simply and accurately diagnosing tomato diseases in the field. In this paper, we construct a system that applies a deep learning-based model in which ImageNet transition is learned in advance to classify and serve nine classes of tomatoes for disease and normal cases. We use the input of MobileNet, ResNet, with a deep learning-based CNN structure that builds a lighter neural network using a composite product for the image set of leaves classifying tomato disease and normal from the Plant Village dataset. Through the learning of two proposed models, it is possible to provide fast and convenient services using MobileNet with high accuracy and learning speed.

• The Journal of Information Systems
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• v.31 no.4
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• pp.145-160
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• 2022

Purpose The purpose of this study is to develop a virtual try-on deep learning model that can efficiently learn front and back clothes images. It is expected that the application of virtual try-on clothing service in the fashion and textile industry field will be vitalization. Design/methodology/approach The data used in this study used 232,355 clothes and product images. The image data input to the model is divided into 5 categories: original clothing image and wearer image, clothing segmentation, wearer's body Densepose heatmap, wearer's clothing-agnosting. We advanced the HR-VITON model in the way of Mixed-Precison, Gradient Accumulation, and sharing model weights. Findings As a result of this study, we demonstrated that the weight-shared MP-GA HR-VITON model can efficiently learn front and back fashion images. As a result, this proposed model quantitatively improves the quality of the generated image compared to the existing technique, and natural fitting is possible in both front and back images. SSIM was 0.8385 and 0.9204 in CP-VTON and the proposed model, LPIPS 0.2133 and 0.0642, FID 74.5421 and 11.8463, and KID 0.064 and 0.006. Using the deep learning model of this study, it is possible to naturally fit one color clothes, but when there are complex pictures and logos as shown in <Figure 6>, an unnatural pattern occurred in the generated image. If it is advanced based on the transformer, this problem may also be improved.

• Atmosphere
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• v.34 no.1
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• pp.1-21
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• 2024

Private companies are increasingly required to take more substantial actions on climate change. This study introduces the principle and cases of climate (physical) risk estimation for 11 private companies in Korea. Climate risk is defined as the product of three major determinants: hazard, exposure, and vulnerability. Hazard is the intensity or frequency of weather phenomena that can cause disasters. Vulnerability can be reflected in the function that explains the relationship between past weather records and loss records. The final climate risk is calculated by multiplying the function by the exposure, which is defined as the area or value of the target area exposed to the climate. Future climate risk is estimated by applying future exposure to estimated future hazard using climate model scenarios or statistical trends based on weather data. The estimated climate risks are developed into three types according to the demand of private companies: i) climate risk for financial portfolio management, ii) climate risk for port logistics management, iii) climate risk for supply chain management. We hope that this study will contribute to the establishment of the climate risk management system in the Korean industrial sector as a whole.