• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.212-212
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• 2015

So far, geomorphologic dispersion due to the heterogeneity characteristics of flow paths in a basin has been demonstrated as a major factor affecting to the hydrologic response function of a catchment. This effect has considered by many previous studies taking into account flow path length factors, especially in the application of width function. Based upon the analysis of topographic index, another important geomorphologic factor extracted from DEM data, this work presents a new factor named saturation to evaluate its effects to the formation of the well-known instantaneous unit hydrograph (IUH) in Nash model and drainage structure in a river basin. First, the geomorphologic parameters corresponding to different saturation conditions are computed from DEM data with the support of GIS software. Then, in the combination of hydrologic and geomorphologic data, effective rainfall in each saturation degree and the Nash parameters are calculated using excel. Finally, the verification process with direct runoff data is conducted using Fortran programming. This process is applied to five sub-watersheds in Bocheong catchment ($485.21km^2$) in Korea where the necessary data are available and believable. The results from this approach will improve researchers and students'understandings about the relationship between rainfall and runoff and its relation with drainage structure within a catchment.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.176-176
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• 2018

This study presents a regional, probabilistic framework for estimating streamflow via spatial scaling in the Great Lakes basin, which is the largest lake system in the world. The framework follows a two-fold strategy including (1) a quadratic-programming based optimization model a priori to explore the model structure, and (2) a time-varying hierarchical Bayesian model based on insights found in the optimization model. The proposed model is developed to explore three innovations in hierarchical modeling for reconstructing historical streamflow at ungaged sites: (1) information of physical characteristics is utilized in spatial scaling, (2) a time-varying approach is introduced based on climate information, and (3) heteroscedasticity in residual errors is considered to improve streamflow predictive distributions. The proposed model is developed and calibrated in a hierarchical Bayesian framework to pool regional information across sites and enhance regionalization skill. The model is validated in a cross-validation framework along with four simpler nested formulations and the optimization model to confirm specific hypotheses embedded in the full model structure. The nested models assume a similar hierarchical Bayesian structure to our proposed model with their own set of simplifications and omissions. Results suggest that each of three innovations improve historical out-of-sample streamflow reconstructions although these improvements vary corrsponding to each innovation. Finally, we conclude with a discussion of possible model improvements considered by additional model structure and covariates.

• ETRI Journal
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• v.43 no.5
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• pp.825-834
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• 2021

Based on its simplicity and user-friendly characteristics, OpenMP has become the standard model for programming on shared-memory architectures. Checkpointing-aided parallel execution (CAPE) is an approach that utilizes the discontinuous incremental checkpointing technique (DICKPT) to translate and execute OpenMP programs on distributed-memory architectures automatically. Currently, CAPE implements the OpenMP execution model by utilizing the DICKPT to distribute parallel jobs and their data to slave machines, and then collects the results after executing these distributed jobs. Although this model has been proven to be effective in terms of performance and compatibility with OpenMP on distributed-memory systems, it cannot fully exploit the capabilities of multicore processors. This paper presents a novel execution model for CAPE that utilizes two levels of parallelism. In the proposed model, we add another level of parallelism in the form of multithreaded processes on slave machines with the goal of better exploiting their multicore CPUs. Initial experimental results presented near the end of this paper demonstrate that this model provides significantly enhanced CAPE performance.

• Wind and Structures
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• v.29 no.1
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• pp.65-75
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• 2019

A heated square cylinder (with height $A^*$) is kept parallel to the cold wall at a fixed gap height $0.5A^*$ from the wall. Another adiabatic rectangular cylinder (of same height $A^*$ and width $0.5A^*$) is placed upstream in an inline tandem arrangement. The spacing between the two cylinders is fixed at $3.0A^*$. The inlet flow is taken as Couette-Poiseuille flow based non-linear velocity profile. The conventional fluid (also known as base fluid) is chosen as water (W) whereas the nanoparticle material is selected as $Al_2O_3$. Numerical simulations are performed by using SIMPLE algorithm based Finite Volume approach with staggered grid arrangement. The dependencies of hydrodynamic and heat transfer characteristics of the cylinder on non-dimensional parameters governing the nanofluids and the fluid flow are explored here. A critical discussion is made on the mechanism of improvement/reduction (due to the presence of the upstream cylinder) of heat transfer and drag coefficient, in comparison to those of an isolated cylinder. It is observed that the heat transfer increases with the increase in the non-linearity in the incident velocity profile at the inlet. For the present range studied, particle concentration has a negligible effect on heat transfer.

• Journal of IKEEE
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• v.23 no.3
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• pp.1068-1076
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• 2019

Most of the electronics we use today have built-in microcontrollers, which are called embedded systems. In such a small environment, responsiveness is very important for the microcontroller. In this paper, the basic input/output control, timer/counter interrupt operation principle, and understanding of the microcontroller are described. Program logic is proposed to improve throughput and latency by controlling characteristics of service routine and program execution order. The hardware simulations in this paper were verified using ATmega128 and PIC16F877A from Atmel and Microchip.

• Nuclear Engineering and Technology
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• v.53 no.4
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• pp.1079-1087
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• 2021

NTP-ERSN is a package developed for solving the multigroup form of the discrete ordinates, characteristics and collision probability of the Boltzmann transport equation in one-dimensional cartesian geometry, by combining pin cells. In this work, C5G7 MOX benchmark is used to verify the accuracy and efficiency of NTP-ERSN package, by treating reactor core problems without spatial homogenization. This benchmark requires solutions in the form of normalized pin powers as well as the vectors and the eigenvalue. All NTP-ERSN simulations are carried out with appropriate spatial and angular approximations. A good agreement between NTP-ERSN results with those obtained with OpenMC calculation code for seven energy groups. In addition, our studies about angular and mesh refinements are carried out to produce better quality solution. Moreover, NTP-ERSN GUI has also been updated and adapted to python 3 programming language.

• Journal of IKEEE
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• v.25 no.4
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• pp.770-773
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• 2021

In this paper, the retention characteristics of 3D NAND flash memory applied with tapering and ferroelectric (HfO₂) structure were analyzed after programming operation. Electrons trapped in nitride are affected by lateral charge migration over time. It was confirmed that more lateral charge migration occurred in the channel thickened by tapering of the trapped electrons. In addition, the Oxide-Nitride-Ferroelectric (ONF) structure has better lateral charge migration due to polarization, so the change in threshold voltage (V_th) is reduced compared to the Oxide-Nitride-Oxide (ONO) structure.

• International Journal of Computer Science & Network Security
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• v.22 no.10
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• pp.1-10
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• 2022

Nowadays software defect prediction (SDP) is most active research going on in software engineering. Early detection of defects lowers the cost of the software and also improves reliability. Machine learning techniques are widely used to create SDP models based on programming measures. The majority of defect prediction models in the literature have problems with class imbalance and high dimensionality. In this paper, we proposed Centroid and Nearest Neighbor based Class Imbalance Reduction (CNNCIR) technique that considers dataset distribution characteristics to generate symmetry between defective and non-defective records in imbalanced datasets. The proposed approach is compared with SMOTE (Synthetic Minority Oversampling Technique). The high-dimensionality problem is addressed using Ant Colony Optimization (ACO) technique by choosing relevant features. We used nine different classifiers to analyze six open-source software defect datasets from the PROMISE repository and seven performance measures are used to evaluate them. The results of the proposed CNNCIR method with ACO based feature selection reveals that it outperforms SMOTE in the majority of cases.

• Wind and Structures
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• v.37 no.3
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• pp.245-254
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• 2023

In this paper, the wind-induced response of Jiayuguan wooden building (world cultural heritage) in Northwest China was studied. ANSYS finite element software was used to establish four kinds of building models under different working conditions and carry out modal analysis. The simulation results were compared with the field dynamic test results, obtaining the model which reflects the real vibration characteristics of the wooden tower. Time history data of fluctuating wind speed was obtained by MATLAB programming. Time domain method and ANSYS were used to analyze the wind-induced vibration response time history of Jiayuguan wooden building, obtaining the displacement time history curve of the structure. It was suggested that the wind-induced vibration coefficient of Jiayuguan wooden building is 1.76. Through analysis of the performance of the building under equivalent static wind load, the maximum displacement occurs in the three-story wall, gold column and the whole roof area, and the maximum displacement of the building is 5.39 cm. The ratio of the maximum stress value to the allowable value of wood tensile strength is 45 %. The research results can provide reference for the wind resistant design and protection of ancient buildings with similar structure to Jiayuguan wooden tower.

• East Asian mathematical journal
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• v.39 no.2
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• pp.93-117
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• 2023

The aim of this study is to explore the pre-service math teachers' characteristics of education to develop their AI literacy and SW competency, and to derive some implications. We conducted a 14-hours AI and SW education program for pre-service teachers with theory and practice, and an analysis on class observation data, video frames of classes and interview, Python programming assignments and papers. The results of this case study for 3 pre-service teachers are as follows. First, two students understood artificial neural network and deep learning system accurately, furthermore, all students conducted a couple of explorations related with performance improvement of deep learning system with interest. Second, coding and exploration activities using Python improved students' computational thinking as well as SW competency, which help them give convergence education in the future. Third, they responded positively to the necessity of AI literacy and SW competency development, and to applying coding to math class. Lastly, it's necessary to endeavor to give a coding education to the student's eye level according to his or her prerequisite and to ease the burden of student's studying AI technology.