• Journal of Software Assessment and Valuation
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• v.15 no.2
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• pp.43-50
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• 2019

With the development of IT technology, computer-related crimes are rapidly increasing, and in recent years, the damage to ransomware infections is increasing rapidly at home and abroad. Conventional security solutions are not sufficient to prevent ransomware infections, and to prevent threats such as malware and ransomware that are evolving, a combination of deep learning technologies is needed to detect abnormal behavior and abnormal symptoms. In this paper, a method is proposed to detect user abnormal behavior using CNN-LSTM model and various deep learning models. Among the proposed models, CNN-LSTM model detects user abnormal behavior with 99% accuracy.

• Journal of Software Assessment and Valuation
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• v.17 no.1
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• pp.31-40
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• 2021

Plagiarism refers to the act of using the original data as if it were one's own without revealing the source. The plagiarism of source code causes a variety of problems, including legal disputes. Plagiarism in software projects is usually determined by measuring similarity by comparing every pair of source code within two projects. However, blindly comparing every pair has been a huge computational burden, causing a major factor of not using tools of better accuracy. If we can only compare pairs that are probable to be clones, eliminating pairs that are impossible to be clones, we can concentrate more on improving the accuracy of detection. In this paper, we propose a method of selecting highly probable candidates of clone pairs by pre-classifying suspected source-codes using a machine-learning model called code2vec.

• Earthquakes and Structures
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• v.15 no.6
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• pp.605-616
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• 2018

In this paper, an extended Cloud analysis method is developed for seismic fragility assessment of existing highway bridges in the southeast Queensland region. This method extends the original Cloud analysis dataset by performing scaled Cloud analyses. The original and scaled Cloud datasets are then paired to generate seismic fragility curves. The seismic hazard in this region is critically reviewed, and the ground motion records are selected for the time-history analysis based on various record selection criteria. A parametric highway bridge model is developed in the OpenSees analysis software, and a sampling technique is employed to quantify the uncertainties of highway bridges ubiquitous in this region. Technical recommendations are also given for the seismic performance evaluation of highway bridges in such low-to-moderate seismic zones. Finally, a probabilistic fragility study is conducted by performing a total of 8000 time-history analyses and representative bridge fragility curves are generated. It is illustrated that the seismic fragility curves generated by the proposed extended Cloud analysis method are in close agreement with those which are obtained by the rigorous incremental dynamic analysis method. Also, it reveals that more than 50% of highway bridges existing in southeast Queensland will be damaged subject to a peak ground acceleration of 0.14 g.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.39-39
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• 2012

Data assimilation techniques have received growing attention due to their capability to improve prediction in various areas. Despite of their potentials, applicable software frameworks to probabilistic approaches and data assimilation are still limited because the most of hydrologic modelling software are based on a deterministic approach. In this study, we developed a hydrological modelling framework for sequential data assimilation, namely MPI-OHyMoS. MPI-OHyMoS allows user to develop his/her own element models and to easily build a total simulation system model for hydrological simulations. Unlike process-based modelling framework, this software framework benefits from its object-oriented feature to flexibly represent hydrological processes without any change of the main library. In this software framework, sequential data assimilation based on the particle filters is available for any hydrologic models considering various sources of uncertainty originated from input forcing, parameters and observations. The particle filters are a Bayesian learning process in which the propagation of all uncertainties is carried out by a suitable selection of randomly generated particles without any assumptions about the nature of the distributions. In MPI-OHyMoS, ensemble simulations are parallelized, which can take advantage of high performance computing (HPC) system. We applied this software framework for several catchments in Japan using a distributed hydrologic model. Uncertainty of model parameters and radar rainfall estimates is assessed simultaneously in sequential data assimilation.

• Earthquakes and Structures
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• v.7 no.1
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• pp.57-82
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• 2014

The heritage value of the mixed wood-masonry 18th century Pombalino buildings of downtown Lisbon is recognized both nationally and internationally. The present paper focuses on the seismic assessment of global response and retrofitting of a typical Pombalino building by nonlinear static analyses, performed by the research software Tremuri, which is able to model 3D configurations. The structure is modelled using nonlinear beams for masonry panels, while in case of the internal walls (frontal walls) an original formulation has been developed in order to take into account their specific seismic behaviour. Floors are modelled as orthotropic membrane finite elements: this feature allows to simulate the presence of both flexible and rigid diaphragms, being the first ones more representative of the original state while the second ones of retrofitted configurations. Seismic assessment has been evaluated by applying nonlinear static procedure and comparing the performance of different configurations (by considering various retrofitting strategies). Finally, assuming a lognormal cumulative distribution, fragility curves are obtained to be representative of Pombalino buildings: the most important application of such curves is for seismic risk and loss estimation analyses.

• Journal of the Korean Society for Geothermal and Hydrothermal Energy
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• v.18 no.4
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• pp.45-57
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• 2022

The Ministry of National Defense of the Republic of Korea is showing a lot of interest in net zero-energy buildings (NZEBs) to reduce energy consumption of military facilities and to promote green growth policy in military sector. The application of building passive technologies and renewable energies is essential to achieving NZEBs. This paper analyzed energy performance and energy cost on the conventional heating and cooling system (baseline scenario) and three different alternative scenarios (ALT 1, ALT 2 and ALT 3) applied in a hypothetical military building. A building modeling and simulation software (DesignBuilder V6.1) with EnergyPlus calculation engine was used to calculate the energy consumption for each scenario. Overall, when the GSHPs are applied to both space airconditioning and domestic hot water (DHW) production, Alt-2 and Alt-3, the amount of energy consumption for target building can be greatly reduced. In addition, when the building envelope performance is increased like Alt-3, the energy consumption can be further reduced. The annual energy cost analysis showed that the baseline was approximately 161 million KRW, while Alt-3 was approximately 33 million KRW. Therefore, it was analyzed that the initial construction cost increase could be recovered within about 6.7 years for ALT 3. The results of this study can help decision-makers to determine the optimal strategy for implementing GSHP systems in military buildings through energy performance and initial construction cost assessment.

• 한국신재생에너지학회:학술대회논문집
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• 2010.06a
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• pp.184.1-184.1
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• 2010

In order to research the way to evaluate wind resource without actual Met Mast data, this paper has been carried out on the southeastern region of Jeju island, Korea. Although wind turbine has been an economical alternative energy resource, misjudging the prediction of lifetime or payback period occurs because of the inaccurate assessment of wind resource and the location of wind turbine. Using WindPRO(Ver. 2.7), a software for wind farm design developed by EMD from Denmark, wind resources for the southeastern region of Jeju island was analyzed, and the performance of WindPRO prediction was evaluated in detail. Met Mast data in Su-san 5.5Km far from Samdal wind farm, AWS in Sung-san 4.5km far from Samdal wind farm, and Korea Wind Map data had been collected for this work.

• Smart Structures and Systems
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• v.11 no.2
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• pp.135-161
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• 2013

This work presents a test platform for the assessment and benchmarking of modern actuators which have been specifically developed for the new field and service robotics applications. This versatile platform has been designed for the comparative analysis of actuators of dissimilar technology and operating conditions. It combines a modular design to adapt to linear and rotational actuators of different sizes, shapes and functions, as well as those with different load capacities, power and displacement. This test platform emulates the kinematics of robotic joints while an adaptive antagonist-load actuator allows reproducing the variable dynamic loads that actuators used in real robotics applications will be subjected to. A data acquisition system is used for monitoring and analyzing test actuator performance. The test platform combines hardware and software in the loop to allow actuator performance characterization. The use of the proposed test platform is demonstrated through the characterization and benchmarking of three controllable impedance actuators recently being incorporated into modern robotics.

• Membrane and Water Treatment
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• v.8 no.5
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• pp.423-435
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• 2017

Settling Basins are one of the most important and popular methods for removal of suspended sediments irrigation and drainage networks or power canals taking off from an alluvial river and wastewater treatment plant. Improving the performance and so increasing sediment removal efficiency of settling basins by an alternative method is necessary. In the present work, the effect of baffle and its angle of attack with the flow (${\theta}$) on the sediment removal efficiency is investigated by conducting a series of experiments on a straight canal with 8 m length, 0.3 m width and 0.5 m height and 3 m length of basin equipped with an adjustable glass baffle. A numerical analysis has been carried out using ANSYS Fluent 3D software (a general purpose computational fluid dynamics simulation tool) for three Froude numbers from the experiments. The numerical and experimental results were found to match reasonably well.

• Journal of Environmental Health Sciences
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• v.48 no.3
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• pp.159-166
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• 2022

Background: A quantitative structure-activity relationship (QSAR) model was adopted in the Registration, Evaluation, Authorization, and Restriction of Chemicals (REACH, EU) regulations as well as the Act on Registration, Evaluation, etc. of Chemicals (AREC, Republic of Korea). It has been previously used in the registration of chemicals. Objectives: In this study, we investigated the correlation between the predicted data provided by three prediction programs using a QSAR model and actual experimental results (acute fish, daphnia magna toxicity). Through this approach, we aimed to effectively conjecture on the performance and determine the most applicable programs when designating toxic substances through the AREC. Methods: Chemicals that had been registered and evaluated in the Toxic Chemicals Control Act (TCCA, Republic of Korea) were selected for this study. Two prediction programs developed and operated by the U.S. EPA - the Ecological Structure-Activity Relationship (ECOSAR) and Toxicity Estimation Software Tool (T.E.S.T.) models - were utilized along with the TOPKAT (Toxicity Prediction by Komputer Assisted Technology) commercial program. The applicability of these three programs was evaluated according to three parameters: accuracy, sensitivity, and specificity. Results: The prediction analysis on fish and daphnia magna in the three programs showed that the TOPKAT program had better sensitivity than the others. Conclusions: Although the predictive performance of the TOPKAT program when using a single predictive program was found to perform well in toxic substance designation, using a single program involves many restrictions. It is necessary to validate the reliability of predictions by utilizing multiple methods when applying the prediction program to the regulation of chemicals.