• Journal of the Korea Computer Industry Society
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• v.3 no.1
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• pp.85-94
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• 2002

EMRCA(Explicit Max_min Rate Control Algorithm) switch, which has been proposed in the ATM(Asychronous Transfer Mode) standard, controls the ABR(Available Bit Rate) service traffic in the ATM networks. The ABR service class of ATM networks uses a feedback control mechanism to adapt to varying link capacities. The VS/VD(Virtual Source/Virtual Destination) technique offers the possibility to segment the otherwise end-to-end ABR control loop into separate loops. The improved feedback delay and the control of ABR traffic inside closed segments provide a better performance and QoS(Quality of Service) for ABR connections with respect to throughput, delay, and jitter. This paper is study of an ABR VS/VD flow control method. Linear control theory offers the means to derive correct choices of parameters and to assess performance issues, like stability of the system, during the design phase. The performance goals are a high link utilization, fair bandwidth distribution and robust operation in various environments, which are verified by discrete event simulations. The major contribution of this work is the use of linear control theory to model and design an ABR flow control method tailored for the special layout of a VS/VD switch, the simulation shows that this techniques better than conventional method.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.3
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• pp.199-204
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• 2013

An implementation method of real-time numeral recognizer based on gesture is presented in this paper for various information devices. The proposed algorithm steadily captures the motion of a hand on 3D open space with the Kinect sensor. The captured hand motion is simplified with PCA, in order to preserve the trace consistency and to minimize the trace variations due to noises and size changes. In addition, we also propose a new HMM using both the gradient and the positional features of the simplified hand stroke. As the result, the proposed algorithm has robust characteristics to the variations of the size and speed of hand motion. The recognition rate is increased up to 30%, because of this combined model. Experimental results showed that the proposed algorithm gives a high recognition rate about 98%.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.6
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• pp.741-747
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• 2012

In this paper, we propose a fast and robust framework for detecting and tracking multiple targets. The proposed system includes two modules: object detection module and object tracking module. In the detection module, we preprocess the input images frame by frame, such as gray and binarization. Next after extracting the foreground object from the input images, morphology technology is used to reduce noises in foreground images. We also use a block-based histogram analysis method to distinguish human and other objects. In the tracking module, color-based tracking algorithm and Kalman filter are used. After converting the RGB images into HSV images, the color-based tracking algorithm to track the multiple targets is used. Also, Kalman filter is proposed to track the object and to judge the occlusion of different objects. Finally, we show the effectiveness and the applicability of the proposed method through experiments.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.4
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• pp.516-521
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• 2010

In this paper, we propose a video-based intelligent unmanned fire surveillance system using fuzzy color models. In general, to detect heat or smoke, a separate device is required for a fire surveillance system, this system, however, can be implemented by using widely used CCTV, which does not need separate devices and extra cost. The systems called video-based fire surveillance systems use mainly a method extracting smoke or flame from an input image only. The smoke is difficult to extract at night because of its gray-scale color, and the flame color depends on the temperature, the inflammable, the size of flame, etc, which makes it hard to extract the flame region from the input image. This paper deals with a intelligent fire surveillance system which is robust against the variation of the flame color, especially at night. The proposed system extracts the moving object from the input image, makes a decision whether the object is the flame or not by means of the color obtained by fuzzy color model and the shape obtained by histogram, and issues a fire alarm when the flame is spread. Finally, we verify the efficiency of the proposed system through the experiment of the controlled real fire.

• Smart Structures and Systems
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• v.24 no.5
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• pp.567-585
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• 2019

In the past two decades, structural health monitoring (SHM) systems have been widely installed on various civil infrastructures for the tracking of the state of their structural health and the detection of structural damage or abnormality, through long-term monitoring of environmental conditions as well as structural loadings and responses. In an SHM system, there are plenty of sensors to acquire a huge number of monitoring data, which can factually reflect the in-service condition of the target structure. In order to bridge the gap between SHM and structural maintenance and management (SMM), it is necessary to employ advanced data processing methods to convert the original multi-source heterogeneous field monitoring data into different types of specific physical indicators in order to make effective decisions regarding inspection, maintenance and management. Conventional approaches to data analysis are confronted with challenges from environmental noise, the volume of measurement data, the complexity of computation, etc., and they severely constrain the pervasive application of SHM technology. In recent years, with the rapid progress of computing hardware and image acquisition equipment, the deep learning-based data processing approach offers a new channel for excavating the massive data from an SHM system, towards autonomous, accurate and robust processing of the monitoring data. Many researchers from the SHM community have made efforts to explore the applications of deep learning-based approaches for structural damage detection and structural condition assessment. This paper gives a review on the deep learning-based SHM of civil infrastructures with the main content, including a brief summary of the history of the development of deep learning, the applications of deep learning-based data processing approaches in the SHM of many kinds of civil infrastructures, and the key challenges and future trends of the strategy of deep learning-based SHM.

• Journal of Hydrogen and New Energy
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• v.30 no.5
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• pp.401-410
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• 2019

The operating conditions greatly impact the efficiency and performance of polymer electrolyte membrane (PEM) fuel cell systems and must be properly managed to ensure better performance and efficiency. In particular, small variations in operating conditions interact with each other and affect the performance and efficiency of PEM fuel cell systems. Thus, a systematic study is needed to understand how small changes in operating conditions affect the system performance and efficiency. In this paper, an automotive fuel cell system (including cell stack and balance of plant [BOP]) with a turbo-blower was modeled using MATLAB/Simulink platform and the sensitivity analyses of main operating parameters were performed using the developed system model. Effects of small variations in four main parameters (stack temperature, cathode air stoichiometry, cathode pressure, and cathode relative humidity) on the system efficiency were investigated. The results show that cathode pressure has the greatest potential impact on the sensitivity of fuel cell system efficiency. It is expected that this study can be used as a basic guidance to understand the importance of achieving accurate control of the fuel cell operating conditions for the robust operation of automotive PEM fuel cell systems.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2013.11a
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• pp.28-29
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• 2013

We have been measuring $CH_4$ flux in a rice paddy in Gimje using the eddy covariance method since July 2011. In order to measure the fast fluctuations of $CH_4$ concentration, an innovative LI-7700 open-path laser spectrometer is used. This high-precision, low power, light weight, low maintenance sensor enables us to operate it on a continuous and long-term basis. One particular feature, among other things, is the self-cleaning lower mirror which decreases maintenance requirements while ensuring more robust, continuous, high-quality dataset. Its cleaning is initiated at user-specified time intervals or a signal strength threshold, and its status is recorded as a diagnostic index. We have noticed that the operation of LI-7700 at Gimje site is quite challenging particularly due to its frequent mirror cleaning requirement and the associated sensitivity of the instrument. In this presentation, we present some field observation data regarding the mirror cleaning and their analysis, thereby suggesting the pertinent operation options for high-quality, maximum data retrieval in the field.

• Smart Structures and Systems
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• v.18 no.3
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• pp.501-523
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• 2016

Electromechanical impedance (EMI) based structural health monitoring is performed by measuring the variation in the impedance due to the structural local damage. The impedance signals are acquired from the piezoelectric patches that are bonded on the structural surface. The impedance variation, which is directly related to the mechanical properties of the structure, indicates the presence of local structural damage. Two traditional EMI-based damage detection methods are based on calculating the difference between the measured impedance signals in the frequency domain from the baseline and the current structures. In this paper, a new structural damage detection approach by analyzing the time domain impedance responses is proposed. The measured time domain responses from the piezoelectric transducers will be used for analysis. With the use of the Time Frequency Autoregressive Moving Average (TFARMA) model, a damage index based on Singular Value Decomposition (SVD) is defined to identify the existence of the structural local damage. Experimental studies on a space steel truss bridge model in the laboratory are conducted to verify the proposed approach. Four piezoelectric transducers are attached at different locations and excited by a sweep-frequency signal. The impedance responses at different locations are analyzed with TFARMA model to investigate the effectiveness and performance of the proposed approach. The results demonstrate that the proposed approach is very sensitive and robust in detecting the bolt damage in the gusset plates of steel truss bridges.

• International Journal of Industrial Entomology and Biomaterials
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• v.22 no.2
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• pp.65-74
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• 2011

The Scarites aterrimus (Coleoptera: Carabidae), is one of the carabid beetles dwelling exclusively on coastal sandy dunes. Habitat deterioration and equivalent activity have greatly concerned population declines in several species dwelling on the coastal sandy dunes. As a first step to establish long-term conservation strategy, we investigated the nation-wide magnitude and nature of genetic diversity of the species. As a first step, we sequenced a portion of mitochondrial COI gene, corresponding to "DNA Barcode" region (658 bp) from a total of 24 S. aterrimus individuals collected over nine sandy dunes belonging to four Korean provinces. The sequence analysis evidenced moderate to low magnitude of sequence diversity compared with other insect species distributed in Korean peninsula (0.152% to 0.912%). The presence of closely related haplotypes and relatively high gene flow estimate collectively suggest that there had been no historical barriers that bolster genetic subdivision. Population decline was postulated on the basis of several missing haplotypes that are well found in the species with a large population size. This interpretation is consistent with field observation of small population size in the coastal sandy dune habitats. The highest genetic diversity estimates were found in the coastal sand dune population of Seogwipo, Jeju Island, justifying a prior attention to the population, in order to sustain overall genetic diversity of the species. Further scrutinized study might be required for further robust conclusion.

• Journal of the Korea Society of Computer and Information
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• v.26 no.10
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• pp.101-108
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• 2021

In this paper, we analyze Shin's proposed dynamic ID-based user authentication scheme for TMIS(Telecare Medicine Information System), and Shin's authentication scheme is vulnerable to smart card loss attacks, allowing attackers to acquire user IDs, which enables user impersonation attack. In 2019, Shin's proposed authentication scheme attempted to generate a strong random number using ECC, claiming that it is safe to lose a smart card because it is impossible to calculate random number r'i due to the difficulty of the ECC algorithm without knowing random number ri. However, after analyzing Shin's authentication scheme in this paper, the use of transmission messages and smart cards makes it easy to calculate random numbers r'i, which also enables attackers to generate session keys. In addition, Shin's authentication scheme were analyzed to have significantly greater overhead than other authentication scheme, including vulnerabilities to safety analysis, the lack of a way to pass the server's ID to users, and the lack of biometric characteristics with slightly different templates.