• Computers and Concrete
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• v.12 no.6
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• pp.785-802
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• 2013

Ready-mixed soil material, known as a kind of controlled low-strength material, is a new way of soil cement combination. It can be used as backfill materials. In this paper, artificial neural network and nonlinear regression approach were applied to predict the compressive strength of ready-mixed soil material containing Portland cement, slag, sand, and soil in mixture. The data used for analyzing were obtained from our testing program. In the experiment, we carried out a mix design with three proportions of sand to soil (e.g., 6:4, 5:5, and 4:6). In addition, blast furnace slag partially replaced cement to improve workability, whereas the water-to-binder ratio was fixed. Testing was conducted on samples to estimate its engineering properties as per ASTM such as flowability, strength, and pulse velocity. Based on testing data, the empirical pulse velocity-strength correlation was established by regression method. Next, three topologies of neural network were developed to predict the strength, namely ANN-I, ANN-II, and ANN-III. The first two models are back-propagation feed-forward networks, and the other one is radial basis neural network. The results show that the compressive strength of ready-mixed soil material can be well-predicted from neural networks. Among all currently proposed neural network models, the ANN-I gives the best prediction because it is closest to the actual strength. Moreover, considering combination of pulse velocity and other factors, viz. curing time, and material contents in mixture, the proposed neural networks offer better evaluation than interpolated from pulse velocity only.

• Journal of the Korean Society for Nondestructive Testing
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• v.22 no.2
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• pp.177-186
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• 2002

This paper describes the magnetic flux leakage(MFL) type non-destructive testing(NDT) system to detect the 3D defects in underground gas pipe. Magnetic systems with permanent magnets and yokes are analyzed by 3D non-lineal finite element method(FEM) with optimum design. In case of under-saturation of gas pipe, sensing signals are too weak to detect. In case of over-saturation, the changes of the sensing signals are too low to detect the defects sensitively. So, the operating points of the magnetic system are optimized to increase the changes of the MFL signals. The effects of the depth and size of the defects on the sensing signals are analyzed to define the range and resolution of the MFL sensors. To increase the sensor's sensitivity, the back-yoke sensors are introduced and tested.

• Journal of the Korean Society for Nondestructive Testing
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• v.14 no.3
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• pp.172-176
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• 1994

Interpreted is the geometric signal in the angle beam ultrasonic testing for the pin-finger type of turbine blade roots. The geometry of the blade roots is described and the reflection conditions for appearance of the geometric signal are proposed. The general equation for its beam path is derived and verified. As the results, it is found that the geometric signal is the back reflection front the ligament edge, and its position and amplitude can be determined from the dimension of blade root and the beam directivity of transducer.

• Journal of the Korean Society of Physical Medicine
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• v.18 no.2
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• pp.49-59
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• 2023

PURPOSE: This study examined the relationship between lumbar instability and shortening of the iliopsoas muscles in patients with chronic low back pain. METHODS: Forty-nine patients with chronic low back pain participated in this study. The modified Thomas test was used to examine the shortening state of the iliopsoas muscle. The length of the iliopsoas muscle was measured using the hip flexion angle, and those with a flexion angle of 10° or more were classified as positive. Five subtests were used for the lumbar instability test: testing for prone lumbar instability, passive lumbar extension, anterior-posterior mobility, passive straight leg raise, and age. Those who tested positive for at least three of these tests were classified as positive for the lumbar segment instability test. RESULTS: There was a significant association between the results of the lumbar instability test and the shortening of the iliopsoas test (p < .05). After analyzing the association between the iliopsoas length test and the five lumbar instability subtests, the results of the prone lumbar instability test (p < .001) and the anterior-posterior mobility test (p < .05) showed a significant association with the iliopsoas length test. CONCLUSION: The association between lumbar instability and shortening of the iliopsoas muscles was examined in 49 patients with chronic low back pain. Patients with shortened iliopsoas muscles tested positive in the lumbar instability tests more often. Hence, the length test of the iliopsoas muscle can be used to determine lumbar instability in patients with chronic low back pain.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.5
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• pp.1191-1204
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• 2012

As attackers try to paralyze information security systems, many researchers have investigated security testing to analyze vulnerabilities of information security products. Penetration testing, a critical step in the development of any secure product, is the practice of testing a computer systems to find vulnerabilities that an attacker could exploit. Security testing like penetration testing includes gathering information about the target before the test, identifying possible entry points, attempting to break in and reporting back the findings. Therefore, to obtain maximum generality, re-usability and efficiency is very useful for efficient security testing and vulnerability hunting activities. In this paper, we propose a threat analysis based software security testing technique for evaluating that the security functionality of target products provides the properties of self-protection and non-bypassability in order to respond to attacks to incapacitate or bypass the security features of the target products. We conduct a security threat analysis to identify vulnerabilities and establish a testing strategy according to software modules and security features/functions of the target products after threat analysis to improve re-usability and efficiency of software security testing. The proposed technique consists of threat analysis and classification, selection of right strategy for security testing, and security testing. We demonstrate our technique can systematically evaluate the strength of security systems by analyzing case studies and performing security tests.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.5B no.2
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• pp.142-145
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• 2005

The life expectancy of a transformer largely depends on the temperature-rise it experiences. If the temperature-rise exceeds limits specified in the design standards, the aging of insulating materials is accelerated and the capability of the cooling medium is deteriorated. Consequently, applicable limits for the temperature-rise are essential in designing the transformer and the coolers, demanding the estimation of the transformer's thermal behavior. In order to analyze the temperature characteristics of the transformer, numerical analysis by way of the commercial CFD code has been carried out, and temperature-rise testing to verify computed results was performed. The results obtained in this study show that there is a good agreement between computed outcomes and experimental outcomes.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2005.04a
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• pp.538-547
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• 2005

This paper presents the shaking table testing method, only using building specimen as an experimental part taking into account the dynamic soil-structure interaction based on the substructure method. The Parmelee's soil stiffness is used as an assumed soil model in here. The proposed methodologies are summarized as: (1) Acceleration feedback method is the one that the shaking table is driven by the motion, corresponding to the acceleration at foundation of the total SSI system. This is found by observing the fed-back accelerations of superstructure and using the interaction force based on the acceleration formulation. (2) Velocity feedback method is the one that the shaking table is driven by the motion, corresponding to the velocity at foundation of the total SSI system. This is found by observing the fed-back accelerations of superstructure and using the interaction force based on the velocity formulation. The applicability of the proposed methodologies to the shaking table test is investigated and experimentally verified in this paper.

• Journal of the Korean Mathematical Society
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• v.47 no.2
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• pp.385-407
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• 2010

To study the relationship between the levels of chemical pollutants and the number of daily total hospital admissions for respiratory diseases and to find the effect of temperature/relative humidity on the admission number, Wong et al. [17] introduced the varying-coefficient single-index model (VCSIM). As pointed out, it is a popular multivariate nonparametric fitting technique. However, the tests of the model have not been very well developed. In this paper, based on the estimators obtained by the local linear technique, the average method and the one-step back-fitting technique in the VCSIM, the generalized likelihood ratio (GLR) tests for varying-coefficient parts on the VCSIM are established. Under the null hypotheses the new proposed GLR tests follow the $\chi^2$-distribution asymptotically with scale constant and degree of freedom independent of the nuisance parameters, known as Wilks phenomenon. Simulations are conducted to evaluate the test procedure empirically. A real example is used to illustrate the performance of the testing approach.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2001.10a
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• pp.59-64
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• 2001

The objectives of the thesis are to propose a pattern classification method for remote sensing data using artificial neural network. First, we apply the error back propagation algorithm to classify the remote sensing data. In this case, the classification performance depends on a training data set. Using the training data set and the error back propagation algorithm, a layered neural network is trained such that the training pattern are classified with a specified accuracy. After training the neural network, some pixels are deleted from the original training data set if they are incorrectly classified and a new training data set is built up. Once training is complete, a testing data set is classified by using the trained neural network. The classification results of Landsat TM data show that this approach produces excellent results which are more realistic and noiseless compared with a conventional Bayesian method.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.2
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• pp.278-285
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• 1994

Aging test was done by loading back method for 20kVA amorphous core transformers manufactured by Hyosung Industries Co. and korea Electric Power Corporation. Iron losses, copper losses and insulation oil temperatures of the transfromers was measured for all the testing period. Expected life of amorphous core transformers on the basis of the degradation of the insulators was 46 years at 100% load, and 2.4 years at 130% load. Average temperature rising of transformer oil of amorphous core transformers was higher than that of silicon steel core transformers. Hence lowering the oil temperature by optimized design is needed for improving the expected life of the amorphous transformers.