• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.2
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• pp.263-277
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• 2021

Taint analysis techniques are popularly used to detect web vulnerabilities originating from unverified user input data, such as Cross-Site Scripting (XSS) and SQL Injection, in web applications written in JavaScript. To detect such vulnerabilities, it would be necessary to trace variables affected by user-submitted inputs. However, because of the dynamic nature of JavaScript, it has been a challenging issue to identify those variables without running the web application code. Therefore, most existing taint analysis tools have been developed based on dynamic taint analysis, which requires the overhead of running the target application. In this paper, we propose a novel static taint analysis technique using symbol information obtained from the TypeScript (a superset of JavaScript) compiler to accurately track data flow and detect security vulnerabilities in TypeScript code. Our proposed technique allows developers to annotate variables that can contain unverified user input data, and uses the annotation information to trace variables and data affected by user input data. Since our proposed technique can seamlessly be incorporated into the TypeScript compiler, developers can find vulnerabilities during the development process, unlike existing analysis tools performed as a separate tool. To show the feasibility of the proposed method, we implemented a prototype and evaluated its performance with 8 web applications with known security vulnerabilities. We found that our prototype implementation could detect all known security vulnerabilities correctly.

• Journal of the Korean Institute of Gas
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• v.23 no.3
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• pp.7-19
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• 2019

In this study, a model was developed for estimating deliverability considering the pressure dependent permeability and predicting production profile with Material Balance Equation(MBE) for Coalbed Methane(CBM) fields. The estimated deliverability was compared with the conventional deliverability based on CBM well testing data with coefficient of determination($R^2$). As a result, the former was 0.76 and the latter was 0.69. It was confirmed that the deliverability which consider the pressure dependent permeability is more adoptable when representing the productivity of CBM fields. Through this process, in order to calculate pressure dependent permeability when well testing data exist, a method to infer reservoir pressure within the radius of investigation was proposed. The production profile of 31 gas wells was predicted for 15 years, using the estimated deliverability and the MBE. After that, the results was compared with simulation results of the literature. The simulation results did not account the pressure dependent permeability and the developed model results considered that. As the applied field permeability rised 1.17 times, field production rate was increased approximately 15% than the literature results. According to other researches, the permeability of CBM fields can be rise 6 ~ 25 times. For these cases, the production profiles may have significant difference with conventional gas fields.

• Earthquakes and Structures
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• v.16 no.2
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• pp.221-234
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• 2019

Today, many important concrete face rockfill dams (CFRDs) have been built on the world, and some of these important structures are located on the strong seismic regions. In this reason, examination and monitoring of these water construction's seismic behaviour is very important for the safety and future of these dams. In this study, the nonlinear seismic behaviour of Ilısu CFR dam which was built in Turkey in 2017, is investigated for various reservoir water heights taking into account 1995 Kobe near-fault and far-fault ground motions. Three dimensional (3D) finite difference model of the dam is created using the FLAC3D software that is based on the finite difference method. The most suitable mesh range for the 3D model is chosen to achieve the realistic numerical results. Mohr-Coulomb nonlinear material model is used for the rockfill materials and foundation in the seismic analyses. Moreover, Drucker-Prager nonlinear material model is considered for the concrete slab to represent the nonlinearity of the concrete. The dam body, foundation and concrete slab constantly interact during the lifetime of the CFRDs. Therefore, the special interface elements are defined between the dam body-concrete slab and dam body-foundation due to represent the interaction condition in the 3D model. Free field boundary condition that was used rarely for the nonlinear seismic analyses, is considered for the lateral boundaries of the model. In addition, quiet artificial boundary condition that is special boundary condition for the rigid foundation in the earthquake analyses, is used for the bottom of the foundation. The hysteric damping coefficients are separately calculated for all of the materials. These special damping values is defined to the FLAC3D software using the special fish functions to capture the effects of the variation of the modulus and damping ratio with the dynamic shear-strain magnitude. Total 4 different reservoir water heights are taken into account in the seismic analyses. These water heights are empty reservoir, 50 m, 100 m and 130 m (full reservoir), respectively. In the nonlinear seismic analyses, near-fault and far-fault ground motions of 1995 Kobe earthquake are used. According to the numerical analyses, horizontal displacements, vertical displacements and principal stresses for 4 various reservoir water heights are evaluated in detail. Moreover, these results are compared for the near-fault and far-faults earthquakes. The nonlinear seismic analysis results indicate that as the reservoir height increases, the nonlinear seismic behaviour of the dam clearly changes. Each water height has different seismic effects on the earthquake behaviour of Ilısu CFR dam. In addition, it is obviously seen that near-fault earthquakes and far field earthquakes create different nonlinear seismic damages on the nonlinear earthquake behaviour of the dam.

• Journal of the Microelectronics and Packaging Society
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• v.25 no.4
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• pp.149-154
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• 2018

This paper describes the fabrication and heat transfer property of 50 watts rated LED array module where multiple chips are mounted on chip-on-board type ceramic-metal hybrid substrate with high heat dissipation property for high power street and anti-explosive lighting system. The high heat transfer ceramic-metal hybrid substrate was fabricated by conformal coating of thick film glass-ceramic and silver pastes to form insulation and conductor layers, using thick film screen printing method on top of the high thermal conductivity aluminum alloy heat-spreading panel, then co-fired at $515^{\circ}C$. A comparative LED array module with the same configuration using epoxy resin based FR-4 PCB with thermalvia type was also fabricated, then the thermal properties were measured with multichannel temperature sensors and thermal resistance measuring system. As a result, the thermal resistance of the ceramic-metal hybrid substrate in the $4{\times}9$ type LEDs array module exhibited about one third to the value as that of FR-4 substrate, implying that at least triple performance of heat transfer property as that of FR-4 substrate was realized.

• Journal of the Korea Society of Computer and Information
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• v.26 no.1
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• pp.45-55
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• 2021

This paper has proposed an algorithm that detecting for dense small vehicle in large image efficiently. It is consisted of two Ensemble Deep-Learning Network algorithms based on Coarse to Fine method. The system can detect vehicle exactly on selected sub image. In the Coarse step, it can make Voting Space using the result of various Deep-Learning Network individually. To select sub-region, it makes Voting Map by to combine each Voting Space. In the Fine step, the sub-region selected in the Coarse step is transferred to final Deep-Learning Network. The sub-region can be defined by using dynamic windows. In this paper, pre-defined mapping table has used to define dynamic windows for perspective road image. Identity judgment of vehicle moving on each sub-region is determined by closest center point of bottom of the detected vehicle's box information. And it is tracked by vehicle's box information on the continuous images. The proposed algorithm has evaluated for performance of detection and cost in real time using day and night images captured by CCTV on the road.

• Journal of Biomedical Engineering Research
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• v.43 no.5
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• pp.341-352
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• 2022

Medical image segmentation is the most important task in radiation therapy. Especially, when segmenting medical images, the liver is one of the most difficult organs to segment because it has various shapes and is close to other organs. Therefore, automatic segmentation of the liver in computed tomography (CT) images is a difficult task. Since tumors also have low contrast in surrounding tissues, and the shape, location, size, and number of tumors vary from patient to patient, accurate tumor segmentation takes a long time. In this study, we propose a method algorithm for automatically segmenting the liver and tumor for this purpose. As an advantage of setting the boundaries of the tumor, the liver and tumor were automatically segmented from the CT image using the 2D CoordConv DeepLab V3+ model using the CoordConv layer. For tumors, only cropped liver images were used to improve accuracy. Additionally, to increase the segmentation accuracy, augmentation, preprocess, loss function, and hyperparameter were used to find optimal values. We compared the CoordConv DeepLab v3+ model using the CoordConv layer and the DeepLab V3+ model without the CoordConv layer to determine whether they affected the segmentation accuracy. The data sets used included 131 hepatic tumor segmentation (LiTS) challenge data sets (100 train sets, 16 validation sets, and 15 test sets). Additional learned data were tested using 15 clinical data from Seoul St. Mary's Hospital. The evaluation was compared with the study results learned with a two-dimensional deep learning-based model. Dice values without the CoordConv layer achieved 0.965 ± 0.01 for liver segmentation and 0.925 ± 0.04 for tumor segmentation using the LiTS data set. Results from the clinical data set achieved 0.927 ± 0.02 for liver division and 0.903 ± 0.05 for tumor division. The dice values using the CoordConv layer achieved 0.989 ± 0.02 for liver segmentation and 0.937 ± 0.07 for tumor segmentation using the LiTS data set. Results from the clinical data set achieved 0.944 ± 0.02 for liver division and 0.916 ± 0.18 for tumor division. The use of CoordConv layers improves the segmentation accuracy. The highest of the most recently published values were 0.960 and 0.749 for liver and tumor division, respectively. However, better performance was achieved with 0.989 and 0.937 results for liver and tumor, which would have been used with the algorithm proposed in this study. The algorithm proposed in this study can play a useful role in treatment planning by improving contouring accuracy and reducing time when segmentation evaluation of liver and tumor is performed. And accurate identification of liver anatomy in medical imaging applications, such as surgical planning, as well as radiotherapy, which can leverage the findings of this study, can help clinical evaluation of the risks and benefits of liver intervention.

• Structural Engineering and Mechanics
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• v.83 no.3
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• pp.305-326
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• 2022

To realize the recycling utilization of waste concrete and alleviate the shortage of resources, 11 specimens of steel reinforced recycled concrete (SRRC) filled circular steel tube columns were designed and manufactured in this study, and the cyclic loading tests on the specimens of columns were also carried out respectively. The hysteretic curves, skeleton curves and performance indicators of columns were obtained and analysed in detail. Besides, the finite element model of columns was established through OpenSees software, which considered the adverse effect of recycled coarse aggregate (RA) replacement rates and the constraint effect of circular steel tube on internal RAC. The numerical calculation curves of columns are in good agreement with the experimental curves, which shows that the numerical model is relatively reasonable. On this basis, a series of nonlinear parameters analysis on the hysteretic behaviors of columns were also investigated. The results are as follows: When the replacement rates of RA increases from 0 to 100%, the peak loads of columns decreases by 7.78% and the ductility decreases slightly. With the increase of axial compression ratio, the bearing capacity of columns increases first and then decreases, but the ductility of columns decreases rapidly. Increasing the wall thickness of circular steel tube is very profitable to improve the bearing capacity and ductility of columns. When the section steel ratio increases from 5.54% to 9.99%, although the bearing capacity of columns is improved, it has no obvious contribution to improve the ductility of columns. With the decrease of shear span ratio, the bearing capacity of columns increases obviously, but the ductility decreases, and the failure mode of columns develops into brittle shear failure. Therefore, in the engineering design of columns, the situation of small shear span ratio (i.e., short columns) should be avoided as far as possible. Based on this, the calculation model on the skeleton curves of columns was established by the theoretical analysis and fitting method, so as to determine the main characteristic points in the model. The effectiveness of skeleton curve model is verified by comparing with the test skeleton curves.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.2
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• pp.107-114
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• 2022

In order to classify 3D film images as right or wrong, it is necessary to detect the pattern in a 3D film image. However, if the contrast of the pixels in the 3D film image is low, it is not easy to classify as the right and wrong 3D film images because the pattern in the image might not be clear. In this paper, we propose a method of classifying 3D film images as right or wrong by comparing the width at a specific frequency of each histogram after obtaining the histogram. Since, it is classified using the width of the histogram, the analysis process is not complicated. From the experiment, the histograms of right and wrong 3D film images were distinctly different, and the proposed algorithm reflects these features, and showed that all 3D film images were accurately classified at a specific frequency of the histogram. The performance of the proposed algorithm was verified to be the best through the comparison test with the other methods such as image subtraction, otsu thresholding, canny edge detection, morphological geodesic active contour, and support vector machines, and it was shown that excellent classification accuracy could be obtained without detecting the patterns in 3D film images.

• Korean Chemical Engineering Research
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• v.61 no.2
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• pp.196-201
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• 2023

In this study, a CNT fiber flexible electrode grafted with CuO nanoparticles (CuO NPs) and polyaniline (PANI) was developed and applied to a nonenzymatic electrochemical sensor for H₂O₂ detection. CuO NPs/PANI/CNT fiber electrode was fabricated through the synthesis and deposition of PANI and CuO NPs on the CNT fiber surface using an electrochemical method. Surface morphology and elemental composition of the CuO NPs/PANI/CNT fiber electrode were characterized by scanning electron microscope with energy dispersive X-ray spectrometry. And its electrochemical characteristics were investigated by cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS) and chronoamperometry (CA). Compared with a bare CNT fiber as a control group, the CuO NPs/PANI/CNT fiber electrode showed a 4.78-fold increase in effective surface area and a 8.33-fold decrease in electron transfer resistance, which leads to excellent electrochemical properties such as a good electrical conductivity and an efficient electron transfer. These improved characteristics were due to the synergistic effect through the grafting of CNT fiber, PANI and CuO NPs. As a result, this electrode enhanced the H₂O₂ sensing performance.

• Journal of the Korea Institute of Building Construction
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• v.20 no.6
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• pp.489-495
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• 2020

Whereas the control of the hydration heat in mass concrete has been important as the concrete structures enlarge, many conventional strategies show some limitations in their effectiveness and practicality. Therefore, In this study, as a solution of controling the heat of hydration of mass concrete, a method to reduce the heat of hydration by controlling the hardening of cement was examined. The reduction of the hydration heat by the developed Phosphate Inorganic Salt was basically verified in the insulated boxes filled with binder paste or concrete mixture. That is, the effects of the Phosphate Inorganic Salt on the hydration heat, flow or slump, and compressive strength were analyzed in binary and ternary blended cement which is generally used for low heat. As a result, the internal maximum temperature rise induced by the hydration heat was decreased by 9.5~10.6% and 10.1~11.7% for binder paste and concrete mixed with the Phosphate Inorganic Salt, respectively. Besides, the delay of the time corresponding to the peak temperature was apparently observed, which is beneficial to the emission of the internal hydration heat in real structures. The Phosphate Inorganic Salt that was developed and verified by a series of the aforementioned experiments showed better performance than the existing ones in terms of the control of the hydration heat and other performance. It can be used for the purpose of hydration heat of mass concrete in the future.