• Journal of Information Processing Systems
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• v.3 no.2
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• pp.43-53
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• 2007

The use of agent paradigm in today's applications is hampered by the security concerns of agents and hosts alike. The agents require the presence of a secure and trusted execution environment; while hosts aim at preventing the execution of potentially malicious code. In general, hosts support the migration of agents through the provision of an agent server and managing the activities of arriving agents on the host. Numerous studies have been conducted to address the security concerns present in the mobile agent paradigm with a strong focus on the theoretical aspect of the problem. Various proposals in Intrusion Detection Systems aim at securing hosts in traditional client-server execution environments. The use of such proposals to address the security of agent hosts is not desirable since migrating agents typically execute on hosts as a separate thread of the agent server process. Agent servers are open to the execution of virtually any migrating agent; thus the intent or tasks of such agents cannot be known a priori. It is also conceivable that migrating agents may wish to hide their intentions from agent servers. In light of these observations, this work attempts to bridge the gap from theory to practice by analyzing the security mechanisms available in Aglet. We lay the foundation for implementation of application specific protocols dotted with access control, secured communication and ability to detect tampering of agent data. As agents exists in a distributed environment, our proposal also introduces a novel security framework to address the security concerns of hosts through collaboration and pattern matching even in the presence of differing views of the system. The introduced framework has been implemented on the Aglet platform and evaluated in terms of accuracy, false positive, and false negative rates along with its performance strain on the system.

• The Journal of Korean Association of Computer Education
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• v.5 no.4
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• pp.43-52
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• 2002

A theory of binary wavelets which are performed over binary field has been recently proposed. Binary wavelet transform (BWT) of binary images can be used as an alternative to the real-valued wavelet transform of binary images in image processing applications such as compression, edge detection, and recognition. The BWT, however, requires large amount of computations for binary wavelet reconstruction since its operation is accomplished by matrix multiplication. In this paper, an efficient binary wavelet reconstruction method which utilizes filtering operation instead of matrix multiplication is presented. Experimental results show that the proposed algorithm can significantly reduce the computational complexity of the BWT. For the reconstruction of an $N{\times}N$ image, the proposed technique requires only $2MN^2$ multiplications and $2N(M-1)^2$ additions when the filter length M, while the BWT needs $2N^3$ multiplications and $2N(N-1)^2$ additions.

• Journal of Physiology & Pathology in Korean Medicine
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• v.23 no.5
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• pp.933-937
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• 2009

The purpose of this study is to develop a diagnostic screening tool for the early detection of osteoporosis in persons with a predisposition for this condition and to facilitate effective management of the disease. Data are collected using questionnaires. The subjects are 120 women in a small city OB-GY clinic in South Korea, who are 6 months or more post menopausal and who have been examined for BMD. Two items in general syndrome of kidney vacuity(Shin Hur) : hears noises like streaming water or the sound of shrill chirrups of a cicada (OR=3.34, p<0.1), feels twinges in the back and knee(OR=4.10, p<0.05), one item in kidney yin vacuity: feels thirst and gets sore throat(OR=8.5, p<0.01) were proven as statistically significant risk factors in the identification of osteoporosis (Odds Ratio). The predictability score was 86.36%, and ROC curve was 0.84. This study attempted to identify risk factors in female osteoporosis so as to develop a screening tool for the purposes of early diagnosis, the effective management of osteoporosis patients and to modify the progress of their disease. Further studies are needed to elaborate this tool's ability to identify contributing factors in osteoporosis as defined by diagnostic evidence predicted by Oriental Medicine Theory.

• Journal of the Korean Society for Nondestructive Testing
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• v.17 no.4
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• pp.262-269
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• 1997

An eddy current probe ($8{\times}1$ multiple-element, surface scan) was successfully designed and fabricated at the KEPRI using the impedance equivalent circuit theory. The probe is intended for the detection of circumferential deformations (cross-section view) of the heat exchanger tubing that can occur due to corrosion, erosion, and denting. Optimum design parameters providing the highest sensitivity and signal-to-noise ratio, such as the coil dimensions, electrical characteristics, and test frequencies, were determined based on initial laboratory experiments conducted on the test specimen (SS304 tubing: OD : 9.68mm, wall-thickness : 0.47mm) containing artificial flaws (e.g., dents and corroded surface on tube OD) using the available Zetec-made probe. Using this parameters, a new probe was made and tested on an unknown specimen. The result indicated that the new probe is capable of detecting the circumferential deformation with the error of ${\pm}0.2%$ (0.022mm) of the tube O.D.

• Smart Structures and Systems
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• v.10 no.3
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• pp.229-251
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• 2012

Guided waves have shown a great potential for structural health monitoring (SHM) applications. In contrast to traditional non-destructive testing (NDT) methodologies, a key element of SHM approaches is the high process of automation. The monitoring system should decide autonomously whether the host structure is intact or not. A basic requirement for the realization of such a system is that the sensors are permanently installed on the host structure. Thus, baseline measurements become available that can be used for diagnostic purposes, i.e., damage detection, localization, etc. This paper contributes to guided wave-based inspection in anisotropic materials for SHM purposes. Therefore, computational strategies are described for both, the solution of the complex equations for wave propagation analysis in composite materials based on exact elasticity theory and the popular global matrix method, as well as the underlying equations of two active damage localization algorithms for anisotropic structures. The result of the global matrix method is an angular and frequency dependent wave velocity characteristic that is used subsequently in the localization procedures. Numerical simulations and experimental investigations through time-delay measurements are carried out in order to validate the proposed theoretical model. An exemplary case study including the calculation of dispersion curves and damage localization is conducted on an exemplary unidirectional composite structure where the ultrasonic signals processed in the localization step are simulated with the spectral element method. The proposed study demonstrates the capabilities of the proposed algorithms for accurate damage localization in anisotropic structures.

• Journal of the Earthquake Engineering Society of Korea
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• v.11 no.2 s.54
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• pp.69-79
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• 2007

In this paper, a technique to detect structural damage and estimate its severity using peaks and zeros of frequency response functions (FRFs) is developed. The peaks in FRFs represent the natural frequencies of the structure and the zeros provide additional information. The characteristics of peaks and zeros are defined and the calculation procedure to obtain the peaks and zeros from the relationship between frequency response function and stiffness and mass matrices are clearly explained. A structural system identification theory which is utilizing the sensitivity of stiffness of a structural member to eigenvalues, i.e., peaks and zeros, is established. The proposed method can identify damage location and its severity, with natural and zero frequencies, by estimating structural stiffness of the structure in the process of making a analytical model The accuracy and feasibility is demonstrated by numerical models of a spring-mass system and a beam structure.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.1
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• pp.116-122
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• 2016

Recently, the production cycle in manufacturing process has been getting shorter and different types of product have been produced in the same process line. In this case, the control chart using coefficient of variation would be applicable to the process. The theory that random variables are located in the three times distance of the deviation from mean value is applicable to the control chart that monitor the process in the manufacturing line, when the data of process are changed by the type of normal distribution. It is possible to apply to the control chart of coefficient of variation too. ${\bar{x}}$, s estimates that taken in the coefficient of variation have just used all of the data, but the upper control limit, center line and lower control limit have been settled by the effect of abnormal values, so this control chart could be in trouble of detection ability of the assignable value. The purpose of this study was to present the robust control chart than coefficient of variation control chart in the normal process. To perform this research, the location parameter, ${\bar{x_{\alpha}}}$, $s_{\alpha}$ were used. The robust control chart was named Tim-CV control chart. The result of simulation were summarized as follows; First, P values, the probability to get away from control limit, in Trim-CV control chart were larger than CV control chart in the normal process. Second, ARL values, average run length, in Trim-CV control chart were smaller than CV control chart in the normal process. Particularly, the difference of performance of two control charts was so sure when the change of the process was getting to bigger. Therefore, the Trim-CV control chart proposed in this paper would be more efficient tool than CV control chart in small quantity batch production.

• Journal of Sensor Science and Technology
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• v.29 no.4
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• pp.249-254
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• 2020

It is difficult to control children who exhibit negative behavior in dental clinics. Various methods are used for preventing pediatric dental patients from being afraid and for eliminating the factors that cause psychological anxiety. However, when it is difficult to apply this routine behavioral control technique, sedation therapy is used to provide quality treatment. When the sleep anesthesia treatment is performed at the dentist's clinic, it is challenging to identify emergencies using the current breath detection method. When a dentist treats a patient that is under the influence of an anesthetic, the patient is unconscious and cannot immediately respond, even if the airway is blocked, which can cause unstable breathing or even death in severe cases. During emergencies, respiratory instability is not easily detected with first aid using conventional methods owing to time lag or noise from medical devices. Therefore, abnormal breathing needs to be evaluated in real-time using an intuitive method. In this paper, we propose a method for identifying abnormal breathing in real-time using an intuitive method. Respiration signals were measured using a 3M Littman electronic stethoscope when the patient's posture was supine. The characteristics of the signals were analyzed by applying the signal processing theory to distinguish abnormal breathing from normal breathing. By applying a short-time Fourier transform to the respiratory signals, the frequency range for each patient was found to be different, and the frequency of abnormal breathing was distributed across a broader range than that of normal breathing. From the wavelet transform, time-frequency information could be identified simultaneously, and the change in the amplitude with the time could also be determined. When the difference between the amplitude of normal breathing and abnormal breathing in the time domain was very large, abnormal breathing could be identified.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.4
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• pp.308-315
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• 2018

In this paper, we present the basic design results for high-resolution radar development at S-band frequency that can precisely measure the miss distance between two targets. The basic system requirement is proposed for the design of a 3.5 GHz linear frequency-modulated (LFM) radar with maximum detection distance and distance resolution of 2 km and 1 m, respectively, and the specifications of each module are determined using the radar equation. Our calculations revealed a signal-to-noise ratio ${\geq}30dB$ with a bandwidth of 150 MHz, transmission power of 43 dBm for the power amplifier, gain of 26 dBi for the antenna, noise figure of 8 dB, and radar cross-section of $1m^2$ at a target distance of 2 km from the radar. Based on the calculation results and the theory and method of LFM radar design, the hardware was designed using software defined radar technology. The results of the subsequent field test are presented that prove that the designed radar system satisfies the requirements.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.5
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• pp.412-417
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• 2013

Analytical modeling of photovoltaic power systems has been receiving significant attentions in recent years in that it is easy to apply for prediction of its dynamics and fault detection and diagnosis in advanced engineering technologies. This paper presents a novel probabilistic modeling approach for such power systems with a big data sequence. Firstly, we express input/output function of photovoltaic power systems in which solar irradiation and ambient temperature are regarded as input variable and electric power is output variable respectively. Based on this functional relationship, conditional probability for these three random variables(such as irradiation, temperature, and electric power) is mathematically defined and its estimation is accomplished from ratio of numbers of all sample data to numbers of cases related to two input variables, which is efficient in particular for a big data sequence of photovoltaic powers systems. Lastly, we predict the output values from a probabilistic model of photovoltaic power systems by using the expectation theory. Two case studies are carried out for testing reliability of the proposed modeling methodology in this paper.