• The Journal of Bigdata
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• v.8 no.2
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• pp.149-163
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• 2023

Due to the continuous growth of the E-commerce market, the volume of orders that fulfillment centers have to process has increased, and various customer requirements have increased the complexity of order processing. Along with this trend, the operational efficiency of fulfillment centers due to increased labor costs is becoming more important from a corporate management perspective. Using historical performance data as training data, this study focused on real-time box recommendations applicable to packaging areas during fulfillment center shipping. Four types of data, such as product information, order information, packaging information, and delivery information, were applied to the machine learning model through pre-processing and feature-engineering processes. As an input vector, three characteristics were used as product specification information: width, length, and height, the characteristics of the input vector were extracted through a feature engineering process that converts product information from real numbers to an integer system for each section. As a result of comparing the performance of each model, it was confirmed that when the Gradient Boosting model was applied, the prediction was performed with the highest accuracy at 95.2% when the product specification information was converted into integers in 21 sections. This study proposes a machine learning model as a way to reduce the increase in costs and inefficiency of box packaging time caused by incorrect box selection in the fulfillment center, and also proposes a feature engineering method to effectively extract the characteristics of product specification information.

• International Journal of Human Ecology
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• v.10 no.2
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• pp.25-37
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• 2009

This study investigated differences in related factors affecting life satisfaction with the elderly in or above middle class experiencing successful ageing. In the study, the respondents were 206 elderly people whose occupation (professional career) placed them in the middle and upper class range residing in metropolitan Seoul. Major results are summarized as follows: (1) In order to test gender differences, results of t-test show that there are 13 variables with seven of those being statistically significant and the rest being insignificant. (2) Needs fulfillment and physical functioning are significant factors for Korean male elders to be satisfied with their later lives. Needs fulfillment, physical functioning, group activity, and learning activity are significant factors for Korean female elders to be satisfied with their later lives.

• The Journal of Society for e-Business Studies
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• v.26 no.1
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• pp.67-78
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• 2021

The number of domestic e-commerce transactions has been breaking its own record by an annual average growth rate of over 20% based on volume for the past 5 years. Due to the rapid increase in e-commerce market, retail companies that have difficulty meeting consumers in person are in fierce competition to take the lead in the last mile service, which is the only point of contact with customers. Especially in the delivery area, where competition is most intense, the role of the fulfillment center is very important for service differentiation. It must be capable of fast product preparation ordered by consumers in accordance with the delivery service level. This study focuses on the order picking system for rapid order processing in the fulfillment center as an alternative for companies to gain competitive advantage in the e-commerce market. A mixed integer programming model was developed and implemented to optimize the stock replenishment in order picking facilities. The effectiveness was scientifically and objectively verified by simulation using the actual operation process and data.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.9
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• pp.281-288
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• 2022

AGVs are often used in industrial applications to transport heavy materials around a large industrial building, such as factories or warehouses. In particular, in fulfillment centers their usefulness is maximized for automation. To increase productivity in warehouses such as fulfillment centers, sophisticated path planning of AGVs is required. We propose a scheme that can be applied to QMIX, a popular cooperative MARL algorithm. The performance was measured with three metrics in several fulfillment center layouts, and the results are presented through comparison with the performance of the existing QMIX. Additionally, we visualize the transport paths of trained AGVs for a visible analysis of the behavior patterns of the AGVs as heat maps.

• Journal of Families and Better Life
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• v.29 no.3
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• pp.1-12
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• 2011

The study aimed to improve the injury belief, injury prevention behavior, and safety fulfillment confidence of teachers of infants and toddlers in childcare centers. The study subjects were 376 teachers who were assigned to either the intervention group or the control group. The intervention group participated in an Injury Prevention Program for infants and toddlers for 100 minutes once a week for a total of 5 sessions, while the control group did not. The collected data were statistically analyzed through the independent t-test and paired t-test. The injury belief and injury prevention behavior test scores of the teachers in the intervention group were significantly increased compared to those in the control group after the completion of the five-week program.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.12
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• pp.287-297
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• 2019

Responding to the rapid delivery demands and variety of small-volume products through human resource-dependent logistics operations in online markets is difficult. Logistics robots in fulfillment centers are expected to increase due to difficulties in hiring workers and rising labor costs. Amazon operates more than 100,000 robots in its Fulfillment centers. Alibaba, DHL, and UPS are also introducing robot technology to improve the logistics efficiency. Logistics robots are being used actively in the fierce online market competition of the global distribution industry. On the other hand, Korea is relatively sluggish. To revitalize the introduction of logistics robots in Korea, it is necessary to examine the factors that influence acceptance. The description of acceptability was based on an expanded technology acceptance model that has been verified through various studies. Studies have shown that both the ease and usefulness of purchasing have significant effects, and that ease has the greatest effect. The more experience involved, the more innovative, the more positive. The usefulness was shown to be positive as the perceived risks are low, price efficiency is good, and social impact is greater. This study provides theoretical and practical implications for logistics robot development and marketing.

• The Journal of Bigdata
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• v.6 no.2
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• pp.17-28
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• 2021

Current development of technologies related to 4^th industrial revolution and the pandemic of COVID-19 lead the rapid expansion of e-marketplace. The level of competition among several companies gets increased by introducing different strategies. To cope with the current change in the market and satisfy the customers who request the better delivery service, the new concept, fulfillment, has been introduced. It makes the leadtime of process from order picking to delivery reduced and the efficiency improved. Still, the efficiency of operation in fulfillment centers constrains the service level of the entire delivery process. In order to solve this problem, several different approaches for demand forecasting and coordinating supplies using Bigdata, IoT and AI, which there exists the trivial limitations. Because it requires the most lead time for operation and leads the inefficiency the process from picking to packing the ordered items, the logistics service providers should try to automate this procedure. In this research, it has been proposed to develop the efficient plans to automate the process to move the ordered items from the location where it stores to stage for packing using AGV and AMR. The efficiency of automated devices depends on the number of items and total number of devices based on the demand. Therefore, the result of simulation based on several different scenarios has been analyzed. From the result of simulation, it is possible to identify the several factors which should be concerned for introducing the automated devices in the fulfillment centers. Also, it can be referred to make the optimal decisions based on the efficiency metrics.

• Journal of Korea Port Economic Association
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• v.40 no.1
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• pp.71-85
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• 2024

Due to the impact of COVID-19 in 2020, online growth is increasing more rapidly, and the need for MFCs has become important to strengthen the Last Mile service, especially in Gangnam and Seocho, where population density is high. This study analyzed MFC operation case studies using Arc GIS (Geographic Information System), and in the case of Seoul, delivery to four MFC bases is not possible within 30 minutes, and for delivery within 30 minutes, it is necessary to secure MFC bases in areas with many consumers. As a result of the analysis, it was confirmed that two to three MFC operating bases are needed for each region based on Seoul Metropolitan Government and at least one base for each administrative district depending on the delivery service after ordering.

• Journal of the Korean Professional Engineers Association
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• v.41 no.5
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• pp.59-64
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• 2008

Having regarded space technology as one of national strategic technologies for its national development, the Korean Government legislated "Space Development Promotion Act" in 2005. Based on it, the Korean government established "National Space Committee" and set up "Long-Term Plan for Korea's Space Development". For the fulfillment of those national policies, related organizations including Korea Aerospace Research Institute are developing various satellites, space launch vehicle(KSLV-1), and Naro-space center. etc.

• Economic and Environmental Geology
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• v.31 no.6
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• pp.557-567
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• 1998

In order to utilize the data obtained during the deep-sea resources exploration program, the analysis of data structure and database were conducted to develop an appropriate data operating system called Deep-sea Database System. The Relation Data Base Management System, RDBMS, was chosen as a data managing system and the MS Access$^{TM}$ as a DB engine, and the MapInfo$^{TM}$ software as GIS tools. Problems in networking and security were detected and solved during the operation test. Accordingly, development of standardized operative procedure was proposed in obtaining raw data. This proposal will also be reflected in the subsequent phase of the deep-sea program. The Deep-sea Database System could be applied to the selection of potential mining sites and the estimation of economical efficiency over th KODOS (Korea Deep Ocean Study) region. It is also expected that this system might improve the efficiency of detail survey and help in the relinquishment process as a fulfillment of the obligation as a pioneer investor.