• Korean Management Science Review
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• v.31 no.1
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• pp.17-26
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• 2014

This study presents a new real estate value analysis model considering the changes in the population structure. We propose a new model that takes advantage of the binomial option model one of the techniques of real options and considers the changes in the population structure. The real estate market price data of Seoul city from year 2001 to 2012 were extracted and the correlation analysis between real estate prices and changes in the population structure was performed. The result shows that they have positive correlation with one year time lag. The coefficient between the real estate prices and demographic changes was estimated using the OLS analysis and included in the traditional binomial option model to calculate the value of the property. It is assumed for the future price prediction that real estate invested in Seoul in January, 2013 will be sold within five years. Analysis result shows that the values of real estate in September of 2013 were predicted as 583.5 million won in the new model and as 582.4 million won in the traditional model. This reflects that the new model considering the change of population change gives better realistic performance than the traditional one.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.11
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• pp.381-394
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• 2022

Recently, due to the personalization and customization of data, Internet-based services have increased requirements for real-time processing, such as real-time AI inference and data analysis, which must be handled immediately according to the user's situation or requirement. Real-time tasks have a set deadline from the start of each task to the return of the results, and the guarantee of the deadline is directly linked to the quality of the services. However, traditional container systems are limited in operating real-time tasks because they do not provide the ability to allocate and manage deadlines for tasks executed in containers. In addition, tasks such as AI inference and data analysis basically utilize graphical processing units (GPU), which typically have performance impacts on each other because performance isolation is not provided between containers. And the resource usage of the node alone cannot determine the deadline guarantee rate of each container or whether to deploy a new real-time container. In this paper, we propose a monitoring technique for tracking and managing the execution status of deadlines and real-time GPU tasks in containers to support real-time processing of GPU tasks running on containers, and a node list management technique for container placement on appropriate nodes to ensure deadlines. Furthermore, we demonstrate from experiments that the proposed technique has a very small impact on the system.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.10a
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• pp.219-226
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• 2003

In this paper, it is presented a new scheme of adaptive-neuro control system to implement real-time control of robot manipulator. Unlike the well-established theory fir the adaptive control of linear systems, there exists relatively little general theory fir the adaptive control of nonlinear systems. Adaptive control technique is essential fir providing a stable and robust performance fir application of robot control. The proposed neuro control algorithm is one of teaming a model based error back-propagation scheme using Lyapunov stability analysis method. Through simulation, the proposed adaptive-neuro control scheme is proved to be a efficient control technique f3r real-time control of robot system using DSPs.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.10a
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• pp.193-200
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• 2004

In this paper, it is presented a new scheme of adaptive-neuro control system to implement real-time control of robot manipulator. Unlike the well-established theory for the adaptive control of linear systems, there exists relatively little general theory for the adaptive control of nonlinear systems. Adaptive control technique is essential for providing a stable and robust performance for application of robot control. The proposed neuro control algorithm is one of learning a model based error back-propagation scheme using Lyapunov stability analysis method. Through simulation, the proposed adaptive-neuro control scheme is proved to be a efficient control technique for real-time control of robot system using DSPs.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.1588-1593
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• 2008

This paper describes a real-time isometric pinch force prediction algorithm from surface electromyogram (sEMG) using multilayer perceptron (MLP) for human robot interactive applications. The activities of seven muscles which are observable from surface electrodes and also related to the movements of the thumb and index finger joints were recorded during pinch force experiments. For the successful implementation of the real-time prediction algorithm, an off-line analysis was performed using the recorded activities. Four muscles were selected for the force prediction by using the Fisher linear discriminant analysis among seven muscles, and the four muscle activities provided effective information for mapping sEMG to the pinch force. The MLP structure was designed to make training efficient and to avoid both under- and over-fitting problems. The pinch force prediction algorithm was tested on five volunteers and the results were evaluated using two criteria: normalized root mean squared error (NRMSE) and correlation (CORR). The training time for the subjects was only 2 min 29 sec, but the prediction results were successful with NRMSE = 0.112 ${\pm}$ 0.082 and CORR = 0.932 ${\pm}$ 0.058. These results imply that the proposed algorithm is useful to measure the produced pinch force without force sensors in real-time. The possible applications include controlling bionic finger robot systems to overcome finger paralysis or amputation.

• Journal of Microbiology and Biotechnology
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• v.18 no.4
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• pp.648-657
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• 2008

In this study, we used functional genomic strategies, proteomics and quantitative real-time (qRT)-PCR, to advance our understanding of genes associated with fumonisin production in the fungus Fusarium verticillioides. Earlier studies have demonstrated that deletion of the FCC1 gene, which encodes a C-type cyclin, leads to a drastic reduction in fumonisin production and conidiation in the mutant strain (FT536). The premise of our research was that comparative analysis of F. verticillioides wild-type and FT536 proteomes will reveal putative proteins, and ultimately corresponding genes, that are important for fumonisin biosynthesis. We isolated proteins that were significantly upregulated in either the wild type or FT536 via two-dimensional polyacrylamide gel electrophoresis, and subsequently obtained sequences by mass spectrometry. Homologs of identified proteins, e.g., carboxypeptidase, laccase, and nitrogen metabolite repression protein, are known to have functions involved in fungal secondary metabolism and development. We also identified gene sequences corresponding to the selected proteins and investigated their transcriptional profiles via quantitative real-time (qRT)-PCR in order to identify genes that show concomitant expression patterns during fumonisin biosynthesis. These genes can be selected as targets for functional analysis to further verify their roles in $FB_1$ biosynthesis.

• Journal of Electrical Engineering and Technology
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• v.10 no.4
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• pp.1682-1691
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• 2015

In this paper, a real time implementation of selective harmonic elimination pulse width modulation (SHEPWM) using Real Coded Genetic Algorithm (RGA), Particle Swarm Optimization technique (PSO) and a new technique known as Linearization Method (LM) for Single Phase Matrix Converter (SPMC) is designed and discussed. In the proposed technique, the switching frequency is fixed and the optimum switching angles are obtained using simple mathematical calculations. A MATLAB simulation was carried out, and FFT analysis of the simulated output voltage waveform confirms the effectiveness of the proposed method. An experimental setup was also developed, and the switching angles and firing pulses are generated using Field Programmable Gate Array (FPGA) processor. The proposed method proves that it is much applicable in the industrial applications by virtue of its suitability in real time applications.

• Journal of KIISE:Software and Applications
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• v.27 no.2
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• pp.120-133
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• 2000

Major obstruction of using formal methods for hybrid real-time systems in industry is the difficulty that engineers have in understanding and applying the quantitative methods in an abstract requirements phase. While formal methods technology in safety-critical systems can help increase confidence of software, difficulty and complexity in using them can cause another hazard. In order to overcome this obstruction, we propose a framework for qualitative requirements engineering of the hybrid real-time systems. It consists of a qualitative method for requirements specification, called QFM (Qualitative Formal Method), and a safety analysis method for the requirements based on a causality information, called CRSA (Causal Requirements Safety Analysis). QFM emphasizes the idea of a causal and qualitative reasoning in formal methods to reduce the cognitive burden of designers when specifying and validating the software requirements of hybrid safety systems. CRSA can evaluate the logical contribution of the software elements to the physical hazard of systems by utilizing the causality information that is kept during specification by QFM. Using the Shutdown System 2 of Wolsong nuclear power plants as a realistic example, we demonstrate the effectiveness of our approach.

• Journal of Information Technology Services
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• v.10 no.1
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• pp.105-116
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• 2011

With recent spotlight on the, uniquitous computing technology, the need for object of indentification and location infrastructure has increased. Such GPS technolgy must utilize IEEE 802.15.4 Zigbee used for existing wireless sensor network infra as a basice element for user's context-awareness in a uniquitous environement, for effectiveness.Such real-time GPS service is provided in the internal environment where the user would actually are and most high-rise buildlings apply. Underthe assumption, the real-time GPS technology is seperated by each floor, and signals do not get transmitted to other floors, the application on one floor within the high-rise buildling was conducted. This study intends to suggest a floor detection algorithm using IEE 802.15.3/Zigbee's RSSI which supports the accuracy within a couple of meters for the user's the movement between the floors in high-rise buildings in a complex environment. It proposes an floor detection algorithm using IEEE 802.15.4/Zigbee's RSSI which provides accuracy within a radius of few meters for the users movement between the floors for real-time location tracking within high-rise building in a cmoplex environment. Furthermore, for more accurate real-time location tracking, it suggests an algorithm for real-time location tracking using IEEE 802.15.4a/Zigbee's CSS technology based on triangulation. Based on the suggested algorithm, it designs a hybrid real-time location tracking service system in a high-rise buildling and test its functions.

• Journal of Computing Science and Engineering
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• v.8 no.4
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• pp.215-227
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• 2014

In modern computer architectures, caches are widely used to shorten the gap between processor speed and memory access time. However, caches are time-unpredictable, and thus can significantly increase the complexity of worst-case execution time (WCET) analysis, which is crucial for real-time systems. This paper proposes a time-predictable two-level scratchpad-based architecture and an ILP-based static memory objects assignment algorithm to support real-time computing. Moreover, to exploit the load/store latencies that are known statically in this architecture, we study a Scratch-pad Sensitive Scheduling method to further improve the performance. Our experimental results indicate that the performance and energy consumption of the two-level scratchpad-based architecture are superior to the similar cache based architecture for most of the benchmarks we studied.