• Journal of the Korea Convergence Society
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• v.13 no.2
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• pp.249-255
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• 2022

This study proposed an analysis framework for real-time prediction of CNC processing defects using machine learning-based models that are recently attracting attention as processing defect prediction methods, and applied it to CNC machines. Analysis shows that the XGBoost, CatBoost, and LightGBM models have the same best accuracy, precision, recall, F1 score, and AUC, of which the LightGBM model took the shortest execution time. This short run time has practical advantages such as reducing actual system deployment costs, reducing the probability of CNC machine damage due to rapid prediction of defects, and increasing overall CNC machine utilization, confirming that the LightGBM model is the most effective machine learning model for CNC machines with only basic sensors installed. In addition, it was confirmed that classification performance was maximized when an ensemble model consisting of LightGBM, ExtraTrees, k-Nearest Neighbors, and logistic regression models was applied in situations where there are no restrictions on execution time and computing power.

• Geomechanics and Engineering
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• v.31 no.6
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• pp.545-556
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• 2022

Evaluation and optimization of tunnel wall convergence (TWC) plays a vital role in preventing potential problems during tunnel construction and utilization stage. When convergence occurs at a high rate, it can lead to significant problems such as reducing the advance rate and safety, which in turn increases operating costs. In order to design an effective solution, it is important to accurately predict the degree of TWC; this can reduce the level of concern and have a positive effect on the design. With the development of soft computing methods, the use of deep learning algorithms and neural networks in tunnel construction has expanded in recent years. The current study aims to employ the long-short-term memory (LSTM) deep neural network predictor model to predict the TWC, based on 550 data points of observed parameters developed by collecting required data from different tunnelling projects. Among the data collected during the pre-construction and construction phases of the project, 80% is randomly used to train the model and the rest is used to test the model. Several loss functions including root mean square error (RMSE) and coefficient of determination (R²) were used to assess the performance and precision of the applied method. The results of the proposed models indicate an acceptable and reliable accuracy. In fact, the results show that the predicted values are in good agreement with the observed actual data. The proposed model can be considered for use in similar ground and tunneling conditions. It is important to note that this work has the potential to reduce the tunneling uncertainties significantly and make deep learning a valuable tool for planning tunnels.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.4
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• pp.121-126
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• 2023

As service utilization for IT technologies such as artificial intelligence, big data, and IOT has recently increased, cloud computing has been introduced to efficiently manage vast amounts of data and IT infrastructure resources that process them to provide stable and reliable information services while streamlining infrastructure costs. Efforts for this are ongoing. This thesis compares and analyzes the operation results before and after cloud adoption in terms of system failures for 426 systems at 360 branches nationwide in cloud systems of companies operating a total of 1,750 cloud systems. As a result of the analysis, the number of failures and failure types , service downtime, etc., the introduction of the cloud yielded significant results in securing service continuity. Through this result, it is expected to provide meaningful implications to companies expecting to secure service continuity by adopting the cloud.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.3
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• pp.93-102
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• 2023

Data processing through the cloud causes many problems, such as latency and increased communication costs in the communication process. Therefore, many researchers study edge computing in the IoT, and autonomous driving is a representative application. In indoor self-driving, unlike outdoor, GPS and traffic information cannot be used, so the surrounding environment must be recognized using sensors. An efficient autonomous driving system is required because it is a mobile environment with resource constraints. This paper proposes a machine-learning method using neural networks for autonomous driving in an indoor environment. The neural network model predicts the most appropriate driving command for the current location based on the distance data measured by the LiDAR sensor. We designed six learning models to evaluate according to the number of input data of the proposed neural networks. In addition, we made an autonomous vehicle based on Raspberry Pi for driving and learning and an indoor driving track produced for collecting data and evaluation. Finally, we compared six neural network models in terms of accuracy, response time, and battery consumption, and the effect of the number of input data on performance was confirmed.

• Journal of the Korea Society of Computer and Information
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• v.29 no.3
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• pp.75-81
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• 2024

In this paper, we proposes a method for real-time processing of inter-floor noise problems by embedding TinyML, which includes a deep learning model, into ultra-low-power systems. The reason this method is feasible is because of lightweight deep learning model technology, which allows even systems with small computing resources to perform inference autonomously. The conventional method proposed to solve inter-floor noise problems was to send data collected from sensors to a server for analysis and processing. However, this centralized processing method has issues with high costs, complexity, and difficulty in real-time processing. In this paper, we address these limitations by employing On-Sensor AI using TinyML. The method presented in this paper is simple to install, cost-effective, and capable of processing problems in real-time.

• Journal of Internet Computing and Services
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• v.21 no.2
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• pp.139-148
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• 2020

Due to change in circumstances in the 2000s such as severe birthrate decline and shortened military service period, the armed forces of the Republic of Korea is currently turning to technologies and equipments from manpower, developing it to become high-tech, high-speed, and complex, resulting in an environment in which a single mistake could cause a mass mortality crisis.It is also evident that, considering aspects such as safety training curriculums and achievements of advanced countries and private education, hands-on training is a must in preventing suicides and accidents in the military, and establishing safety training centers is crucial for systematic and effective hands-on training.Soldiers who are joining the army as of now have experienced the Internet ever since they were born and easily use both virtual and augmented reality, and the current level of science and technology has developed to the point where most of the public safety experience centers are able to be replaced by virtual and augmented reality (VR/AR). Therefore, considering the aspects such as installation space, construction costs, maintenance costs, user characteristics, and education effects, other than for those trainings where real models and objects are more effective such as first aid training, it is with a strong recommendation that establishing military safety training facilities with VR/AR (Virtual and augmented reality) is a must in the coming future. We have derived the need for hands-on training by considering the development of virtual and augmented reality (VR/AR), analysis of operation status of the public safety experience centers, characteristics of military units, installation and maintenance costs, and proposed plan to establish safety training centers where effective training performance can be achieved at a lower cost than the public safety experience center. In addition, we suggested the scale of the required safety training center and the composition of the experience rooms considering the number of trainees and the environment of each military units. Given this analysis it will contribute to the prevention of military safety and suicide by building a safety training center in the future.

• Journal of KIISE:Computing Practices and Letters
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• v.13 no.7
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• pp.508-519
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• 2007

Flash memory based storage has been used in various mobile systems and now is to be used in Laptop computers in the name of Solid State Disk. The Flash memory has not only merits in terms of weight, shock resistance, and power consumption but also limitations like erase-before-write property. To overcome these limitations, Flash memory based storage requires special address mapping software called FTL(Flash-memory Translation Layer), which often performs merge operation for block recycling. In order to reduce block recycling cost in NAND Flash memory based storage, we introduce another block recycling scheme which we call migration. As a result, the FTL can select either merge or migration depending on their costs for each block recycling. Experimental results with Postmark benchmark and embedded system workload show that this cost-based selection of migration/merge operation improves the performance of Flash memory based storage. Also, we present a solution of macroscopic optimal migration/merge sequence that minimizes a block recycling cost for each migration/merge combination period. Experimental results show that the performance of Flash memory based storage can be more improved by the macroscopic optimization than the simple cost-based selection.

• KIISE Transactions on Computing Practices
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• v.23 no.12
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• pp.651-659
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• 2017

IT(Information Technology) has focused on infrastructure-technologies in the past but now focuses on IT service. Many companies strive to save costs and improve IT services. For this reason, they strive to implement a good internalization of ITSM (IT Service Management) by developing ITSM systems based on ITIL (Information Technology Infrastructure Library) from the late 2000s. In particular, IT service operations are one of the structure elements of ITIL version 3 and are highly related to the internalization of ITSM. However, in spite-of-the successful implementation of ITSM, the efficiency of IT service management has not improved due to iterative issues. Therefore, this study developed a user-centered training system by defining the iterative issue guidelines and implementing a database. The implemented user-centered training system provided IT service users with regular training services to produce a good solution for iterative issues after connecting the operation part of the ITSM system. Based on the results of this study, we expect that the proposed ITSM system will contribute to efficiently managing IT services by improving the limitations of IT service operation in the ITSM system.

• The KIPS Transactions:PartD
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• v.15D no.3
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• pp.375-386
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• 2008

Recently, development paradigm of information system is turning into object oriented and component based, and this methodology is leading the software industry. To acclimatize aptly to this trend, users demand the assessment of software expenses to change with the appropriate model of computing costs of the environment, and some people are actually studying the concept of Object Oriented Function Point and UCP method. Especially, Object Oriented Function Point Measurement Process has good points in overcoming the bound of LOC and the existing the Function Point Measurement Process because Object Oriented Function Point Measurement Process is applicable to the early stage of development project mainly with the used cases, and valid to the life long period as the each stage of software products develops, and always understandable to communicate with users by the UML mark rules. Accordingly, this research is to measure Functional Point at ROFP and AOFP in accordance with the development project of information system by the national defense CBD methodology procedures and UML Interrelation Analysis that are recently and widely used in the developmental environment of object oriented information system. Furthermore, this study suggests the measurement method to obtain Functional Point, and identifies service function and object/class function in the correlation analysis of use case and class based on the products and UML modeling via traditional FPA model and object oriented FPA model. Above all, this study is to demonstrate the improvement of traditional Function Point Measurement Process, IFPUG-CPM and software cost basis, and reveal Function Point Measurement Process, which is appropriate to the development of object oriented information system, and suggest the evaluation results of the compatibility through case studies.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.3
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• pp.622-628
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• 2016

As the suction pad-supporting bike carrier attached to a car may be subject to an excessive dynamic load due to random vibrations and centrifugal forces during driving, its structural safety is of great concern. To examine this, the finite-element method with a fluid-structure interaction should be used because the pressure on the pad bottom is changed in real time according to the fluctuations of the force or the moment applied on the pad. This method, however, has high computing costs in terms of modeling efforts and software expense. Moreover, the accuracy of computation is not easily guaranteed. Therefore, a new method combining the experiment and computation is proposed in this paper: the bottom pressure and contact area of the pad under varying loads was measured in real time and the acquired data are then used in the nonlinear elastic finite-element calculations. The computational and experimental results obtained with the product under development showed that the safety margin of the pad under the axial loading is relatively sufficient, whereas with an excessive rotational loading, the pad is vulnerable to separation or a local surface damage; hence, the safety margin may not be secured. The predicted contact behavior under the variation of the magnitude and type of the loading were in good agreement with the one from the experiment. The proposed analysis method in this study could be used in the design of similar vacuum pad systems.