• Journal of the Korea Society of Computer and Information
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• v.28 no.10
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• pp.171-178
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• 2023

In this paper, we propose a smart automated warehouse to maximize space utilization. Previous elevator-type automatic warehouses were designed with a maximum payload of 100kg on trays, which has the problem of extremely limiting the number of pallets that can be loaded within the space. In this paper, we design a smart warehouse that can maximize space utilization with a maximum vertical stiffness of 300kg. As a result of the performance evaluation of the implemented warehouse, the maximum payload was 500.6kg, which satisfied the original design and requirements, the lifting speed was 0.5m/s, the operating noise of the device was 67.1dB, the receiving and forwarding time of the pallet was 36.92sec, the deflection amount was 4mm, and excellent performance was confirmed in all evaluation items. In addition, the PLC control method, which designs the control UI and control panel separately, was integrated into the PC system to improve interoperability and maintainability with various process management systems. In the future, we plan to develop it into a fully automatic smart warehouse by linking IoT sensor-based logistics robots.

• Journal of Drive and Control
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• v.20 no.4
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• pp.1-8
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• 2023

In recent years, robots have been utilized in various industries to reduce workload and enhance work efficiency. The following mobility offers users convenience by autonomously tracking specific locations and targets without the need for additional equipment such as forklifts or carts. In this paper, deep learning techniques were employed to recognize individuals and assign each of them a unique identifier to enable the recognition of a specific person even among multiple individuals. To achieve this, the distance and angle between the robot and the targeted individual are transmitted to respective controllers. Furthermore, this study explored the control methodology for mobility that tracks a specific person, utilizing Simultaneous Localization and Mapping (SLAM) and Proportional-Integral-Derivative (PID) control techniques. In the PID control method, a genetic algorithm is employed to extract the optimal gain value, subsequently evaluating PID performance through simulation. The SLAM method involves generating a map by synchronizing data from a 2D LiDAR and a depth camera using Real-Time Appearance-Based Mapping (RTAB-MAP). Experiments are conducted to compare and analyze the performance of the two control methods, visualizing the paths of both the human and the following mobility.

• Information Systems Review
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• v.20 no.4
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• pp.25-41
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• 2018

Applying predictive analytics to enterprise processes is an effective way to reduce operation costs and enhance productivity. Accordingly, the ability to predict business processes and performance indicators are regarded as a core capability. Recently, several works have predicted processes using deep learning in the form of recurrent neural networks (RNN). In particular, the approach of predicting the next step of activity using static or dynamic RNN has excellent results. However, few studies have given attention to applying deep learning in the form of dynamic RNN to predictions of process performance indicators. To fill this knowledge gap, the study developed an approach to using process mining and dynamic RNN. By utilizing actual data from a large domestic company, it has applied the suggested approach in estimating timely stocking in purchasing process, which is an important indicator of the process. The analytic methods and results of this study were presented and some implications and limitations are also discussed.

• International Commerce and Information Review
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• v.19 no.2
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• pp.213-236
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• 2017

World trade has entered a stagnant state, protection trade measures are spread due to delayed economic recovery in developed countries, sluggish investment in emerging economies such as China, economic recession in resource exporting countries, and geopolitical and political uncertainties along with the election period in the US and other major industrialized countries. Thus, in the economic structure of our country with a focus on export, for small and medium enterprises to grow, efforts for having various markets are necessary. The importance of the trade insurance system, which can support the risk management of enterprises, is emphasized by the fact that the majority of SME exporters have a risk management level and a lack of corporate capacity to enter the global market. This study was surveyed with 87 small and medium export companies in South Korea. The purpose of this study is to verify the effect relationship how service quality of trade insurance and utilization of trade insurance impact on the risk management of trade payment and export performance. The research hypothesis and model was derived from the basis of existing theory and empirical research, and obtained the following results. Firstly, Service Quality of Trade Insurance showed positive (+) effect on Export Performance. Secondly, Utilization of Trade Insurance showed positive (+) effect on Risk Management of Trade Payment. Thirdly, Risk Management of Trade Payment showed positive (+) effect on Export Performance. This study is differentiated from previous research information by empirically evaluating the relationship between the risk management of trade payment and export performance through utilization of trade insurance. This study contributed to academic by examining the research on the risk management of trade insurance and also practically suggested the direction how small and medium export company is to take the advantage of the trade insurance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.2
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• pp.263-268
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• 2016

A rapid increase of data amount, used in ship-to-ship transmission of safety and logistics information, ships in the inland sea have trouble transmitting real-time information transmission due to an increase in traffic load caused by data transmitted by land station and offshore ships. In this study, therefore, communication is carried out by adaptively controlling the detailed beam width based on the distribution of offshore ships in land station durable in marine environment. Then after the adaptive sector system enabling real-time communication support between ships concentrated in an inland sea and land station is applied, the performance verification is conducted based on the respective Call Blocking Rates of an omnidirectional antenna, fisted sector system, and adaptive sector system. The performance verification result shows that adaptive sector system has better performance than the fixed sector system as the density of ship, q value, increases, and that the smaller the beam width is, the better performance of adaptive sector system will be.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.203-213
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• 2021

A vehicle crash occurs due to various factors such as the geometry of the road section, traffic, and driver characteristics. A safety performance function has been used in many studies to estimate the relationship between vehicle crash and road factors statistically. And depends on the purpose of the analysis, various characteristic variables have been used. And various characteristic variables have been used in the studies depending on the purpose of analysis. The existing domestic studies generally reflect the average characteristics of the sections by quantifying the traffic volume in macro aggregate units such as the ADT, but this has a limitation that it cannot reflect the real-time changing traffic characteristics. Therefore, the need for research on effective aggregation units that can flexibly reflect the characteristics of the traffic environment arises. In this paper, we develop a safety performance function that can reflect the traffic characteristics in detail with an aggregate unit for one hour in addition to the daily model used in the previous studies. As part of the present study, we also perform a comparison and evaluation between models. The safety performance function for daily and hourly units is developed using a negative binomial regression model with the number of accidents as a dependent variable. In addition, the optimal negative binomial regression model for each of the hourly and daily models was selected, and their prediction performances were compared. The model and evaluation results presented in this paper can be used to determine the risk factors for accidents in the highway section considering the dynamic characteristics. In addition, the model and evaluation results can also be used as the basis for evaluating the availability and transferability of the hourly model.

• Journal of the Korea Society of Computer and Information
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• v.27 no.11
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• pp.147-155
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• 2022

In this study, we developed a system to dynamically balance a daily stock portfolio and performed trading simulations using gradient boosting and genetic algorithms. We collected various stock market data from stocks listed on the KOSPI and KOSDAQ markets, including investor-specific transaction data. Subsequently, we indexed the data as a preprocessing step, and used feature engineering to modify and generate variables for training. First, we experimentally compared the performance of three popular gradient boosting algorithms in terms of accuracy, precision, recall, and F1-score, including XGBoost, LightGBM, and CatBoost. Based on the results, in a second experiment, we used a LightGBM model trained on the collected data along with genetic algorithms to predict and select stocks with a high daily probability of profit. We also conducted simulations of trading during the period of the testing data to analyze the performance of the proposed approach compared with the KOSPI and KOSDAQ indices in terms of the CAGR (Compound Annual Growth Rate), MDD (Maximum Draw Down), Sharpe ratio, and volatility. The results showed that the proposed strategies outperformed those employed by the Korean stock market in terms of all performance metrics. Moreover, our proposed LightGBM model with a genetic algorithm exhibited competitive performance in predicting stock price movements.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.6
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• pp.121-130
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• 2018

The purpose of this study is to analyze the effect of partnership type (pre-competitive, competitive, pro - competitive, non - competitive partnership) and national cultural characteristics on partnership performance. In order to analyze this, we conducted questionnaires on companies that have conducted international management and affiliated companies. A total of 223 questionnaires were sent. A total of 121 inquiries were collected from 224 survey requests. Based on this, a structured questionnaire was sent back to the staff members listed in the survey request, and a total of 98 samples were collected. The results of the empirical analysis through the questionnaire showed that the difference between the affiliation type and the national culture had a significant effect on the partnership performance. The results showed that the difference between the affiliation type and the national culture had a significant effect on the partnership performance. This could be a very meaningful implication for companies that are able to achieve successful alliances in a way that enables them to achieve successful alliances.

• Journal of Korean Society of Transportation
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• v.33 no.3
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• pp.256-267
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• 2015

The intelligent transportation systems allow us to have valuable opportunities for collecting wide-area coverage traffic data. The significant efforts have been made in many countries to provide the reliable traffic conditions information such as travel time. This study analyzes the impacts of the fog weather conditions on the traffic stream. Also, a strategy for predicting the long-term traffic speeds is developed under foggy weather conditions. The results show that the average of speed reductions are 2.92kph and 5.36kph under the slight and heavy fog respectively. The best prediction performance is achieved when the previous 45 pattern cases data is used, and the 14.11% of mean absolute percentage error(MAPE) is obtained. The outcomes of this study support the development of more reliable traffic information for providing advanced traffic information service.

• Journal of the Korean Society of Marine Environment & Safety
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• v.26 no.5
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• pp.437-444
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• 2020

This study was focused on the stabilization of surge motions of a moored vessel under irregular head seas. A two-point moored vessel shows strong non-linearity even in regular sea, owing to its inherent non-linear restoring force. A long-crested irregular wave is subjected to the vessel system, resulting in more complex nonlinear behavior of the displacement and velocities than in the case of regular waves. Sliding mode control (SMC) is implemented in the moored vessel to control both surge displacement and surge velocity. The SMC can provide a closed-loop system with performance and robustness against parameter uncertainties and disturbances; however, chattering is the main drawback for implementing SMC. The goal of minimizing the chattering and state convergence with accuracy is achieved using a quasi-sliding mode that approximates the discontinuous function via a continuous sigmoid function. Numerical simulations were conducted to validate the effectiveness of the proposed control algorithm.