• IE interfaces
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• v.13 no.1
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• pp.78-91
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• 2000

This paper presents a computerized quality forecasting system for glass manufacturing. In forecasting the molten glass quality, we are concerned with three major issues : (1) to find the reasonable time lags between a set of process conditions and the quality measurement of glass products, (2) to find the most significant process variables affecting the quality, and (3) to construct the appropriate causal forecasting models using genetic algorithms. The experimental results show the proposed model results in better forecasting than linear regression model. The suggested forecasting model was implemented successfully and is being currently used in a real manufacturing line.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2003.03a
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• pp.415-421
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• 2003

With the increasing possibility of earthquake occurrence, seismic safety of bridges has become one of the most important social issues in Korea. In this study, a nonlinear earthquake response analysis is carried out for a real bridge by incorporating soil-structure interaction and pier nonlinearity. The material nonlinearity of the bridge pier is realized by utilizing SAP2000 whereas the soil-structure interaction is analized in time domain by adapting KIESSI. The numerical results are compared to those of the models without considering the effects.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.2
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• pp.105-114
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• 2013

Expansion and growth of body information monitoring service based on WBAN technology speeds up technological evolution in bio-signal detection and measurement, real time monitoring of vital sign and telemedicine control. It is essential for taking action against such technological evolution that newest technology trend and standardization issue should be included in designing and materializing body-information monitoring system strategically to secure preceding technology and to preoccupy market. This paper investigates and analyzes technological trend & issues, and suggests task to take action technologically.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.762-766
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• 2004

This paper introduces a testbed which is suitable for the study of security issues arising in applications involving internet appliances. The testbed implements secure door locks by utilizing the intranet in the building and is composed of two main parts, namely a database server and door locks each of which equipped with a custom-made embedded system. The main objective is to provide a platform for teaching the conflict among real-time specifications, security requirements, and limited-resource constraints. After definitions of threat, vulnerability, and attack are given, we discuss how the testbed can be applied as an education tool for these concepts. Finally, the effects of sequential and multitasking operations are given as a case study.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.301-303
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• 2004

In this work, we develop on-line traffic prediction algorithm for real-time VBR traffic. There are a number of important issues: (i) The traffic prediction algorithm should exploit the stochastic characteristics of the underlying traffic and (ii) it should quickly adapt to structural changes in underlying traffic. GOP ARIMA model effectively addresses this issues and it is used as basis in our bandwidth prediction. Our prediction model deploy Kalman filter to incorporate the prediction error for the next prediction round. We examine the performance of GOP ARIMA based prediction with linear prediction with LMS and double exponential smoothing. The proposed prediction algorithm exhibits superior performam againt the rest.

• Agricultural and Biosystems Engineering
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• v.4 no.1
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• pp.22-27
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• 2003

An autonomous tractor requires not only automatic steering (automatic guidance) but also automated control of tractor functions and implement operations. Examples of tractor functions include engine throttle, transmission speed, and 3-point hitch position. Implement operations include tillage, planting, and cultivating. This article provides an overview of a map-based methodology used for the implementation of autonomous field operations of agricultural tractors. The procedure for developing autonomous field operation maps were presented, and several important issues in the implementation of map-based autonomous operations were discussed. These issues included combining field operation maps, position offset, and real-time sensing and update of field operation maps.

• Industrial Engineering and Management Systems
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• v.7 no.1
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• pp.78-89
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• 2008

The need for holistic modeling efforts for returns that capture the extended closed loop supply chain (CLSC) system at strategic as well as operational level has been clearly recognized by the industry and academia. Strategic decision-makers need comprehensive models that can guide them in efficient decision-making to increase the profitability of the entire forward and return chain. Therefore, determination of a near optimal design configuration, which includes the environmental, economical and technological capability factors, is important in strategic decision-making effort that affect the profitability of the closed loop supply chain. In this paper, we adopted an improved system dynamics methodology to tackle strategic issues that affect various performance measures, like market, time/cost, environment etc., for closed loop supply chains. After studying real life implementation issues in CLSC design, we presented guidelines for the PBM (Participative Business Modeling) methodology and presented its extension for the strategic dynamic system modeling of return chains. Finally, we demonstrated the measurement of operational performance by extending SD (system dynamic) application to closed loop supply chain management.

• International Journal of Computer Science & Network Security
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• v.23 no.4
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• pp.25-31
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• 2023

Fog computing diversifies cloud computing by using edge devices to provide computing, data storage, communication, management, and control services. As it has a decentralised infrastructure that is capable of amalgamating with cloud computing as well as providing real-time data analysis, it is an emerging method of using multidisciplinary domains for a variety of applications; such as the IoT, Big Data, and smart cities. This present study provides an overview of the security and privacy concerns of fog computing. It also examines its fundamentals and architecture as well as the current trends, challenges, and potential methods of overcoming issues in fog computing.

• International journal of advanced smart convergence
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• v.11 no.1
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• pp.19-27
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• 2022

Across the world, 'housing' comprises a significant portion of wealth and assets. For this reason, fluctuations in real estate prices are highly sensitive issues to individual households. In Korea, housing prices have steadily increased over the years, and thus many Koreans view the real estate market as an effective channel for their investments. However, if one purchases a real estate property for the purpose of investing, then there are several risks involved when prices begin to fluctuate. The purpose of this study is to design a real estate price 'return rate' prediction model to help mitigate the risks involved with real estate investments and promote reasonable real estate purchases. Various approaches are explored to develop a model capable of predicting real estate prices based on an understanding of the immovability of the real estate market. This study employs the LSTM method, which is based on artificial intelligence and deep learning, to predict real estate prices and validate the model. LSTM networks are based on recurrent neural networks (RNN) but add cell states (which act as a type of conveyer belt) to the hidden states. LSTM networks are able to obtain cell states and hidden states in a recursive manner. Data on the actual trading prices of apartments in autonomous districts between January 2006 and December 2019 are collected from the Actual Trading Price Disclosure System of the Ministry of Land, Infrastructure and Transport (MOLIT). Additionally, basic data on apartments and commercial buildings are collected from the Public Data Portal and Seoul Metropolitan Government's data portal. The collected actual trading price data are scaled to monthly average trading amounts, and each data entry is pre-processed according to address to produce 168 data entries. An LSTM model for return rate prediction is prepared based on a time series dataset where the training period is set as April 2015~August 2017 (29 months), the validation period is set as September 2017~September 2018 (13 months), and the test period is set as December 2018~December 2019 (13 months). The results of the return rate prediction study are as follows. First, the model achieved a prediction similarity level of almost 76%. After collecting time series data and preparing the final prediction model, it was confirmed that 76% of models could be achieved. All in all, the results demonstrate the reliability of the LSTM-based model for return rate prediction.

• Smart Structures and Systems
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• v.16 no.6
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• pp.1147-1167
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• 2015

Wireless smart sensors, which have become popular for monitoring applications, are an attractive option for implementing structural control systems, due to their onboard sensing, processing, and communication capabilities. However, wireless smart sensors pose inherent challenges for control, including delays from communication, acquisition hardware, and processing time. Previous research in wireless control, which focused on semi-active systems, has found that sampling rate along with time delays can significantly impact control performance. However, because semi-active systems are guaranteed stable, these issues are typically neglected in the control design. This work achieves active control with smart sensors in an experimental setting. Because active systems are not inherently stable, all the elements of the control loop must be addressed, including data acquisition hardware, processing performance, and control design at slow sampling rates. The sensing hardware is shown to have a significant impact on the control design and performance. Ultimately, the smart sensor active control system achieves comparable performance to the traditional tethered system.