• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.1B
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• pp.89-100
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• 2010

The performance evaluation of a conventional Wave Resonator at the entrance of harbors against solitary wave has been performed using 3D numerical wave flume. A wave resonator has been designed for the attenuation of the transmitted wave energy by trapping the short periodic incident waves only. In this study, however, the controlled performance of the wave resonator by its various widths has been numerically investigated for solitary waves. Source distribution method based on the Green function and the 3D one-field Model for immiscible TWO-Phase flows (TWOPM-3D) using 3D numerical wave flume were used for the short-periodic waves and the solitary waves, respectively, and these models were verified through the comparisons with the previous experimental and numerical results by other researchers. It was confirmed that the wave resonator is effective enough to control the solitary waves as well as the periodic waves when it compares with the case of no resonance system. Further, it was found that there is the optimal width of a wave resonator to attenuate the target solitary waves.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.6A
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• pp.513-523
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• 2010

For continuous I-girder bridges, a large negative bending moment is generated near pier region so that plastic hinge is first formed at this point. Then, the bending moment is redistributed when the I-girder has enough flexural ductility (or rotational capacity). However, for I-girder with high strength steel, it is known that the flexural ductility is considerably decreased by increasing the yield strength of material. Thus, it is necessary to conduct a study for guaranteeing proper flexural ductility of I-girder with high-strength steel. In this study, the evaluation of flexural ductility of negative moment region of I-girder with high strength steel where yield stress of steel is 680 MPa is presented based on the results of finite element analysis and experiment. From the results, it is found that the flexural ductility of the I-girder is significantly reduced due to the increase of elastic deformation and the decrease of plastic deformation ability of the material when the yield strength increases. In this study, the method to improve the flexural ductility of I-girder with high strength steel is proposed by an unequal installation of cross beam and an optimal position of cross beam is also suggested. Finally, the effects of the unequal installation of cross beam on the flexural ductility are discussed based on the experimental results.

• The Journal of the Acoustical Society of Korea
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• v.42 no.6
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• pp.519-528
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• 2023

The aim of this study was to enhance the flow rate and noise performance of a centrifugal pump in dishwashers by designing an optimized impeller shape through numerical and experimental investigations. To evaluate the performance of the target centrifugal pump, experiment was conducted using a pump performance tester and noise experiment was carried out in a semi-anechoic chamber with microphones and a reflecting wall behind the dishwasher. Through the use of advanced computational fluid dynamics techniques, numerical simulations were performed to analyze the flow and aeroacoustics performance of our target centrifugal pump impeller. To achieve this, numerical simulations were carried out using the Reynolds-Average Navier-Stokes equations and Ffowcs-Willliams and Hawkings equations as governing equations. In order to ensure the validity of numerical methods, a thorough comparison of numerical results with experimental results. After having confirmed the reliability of the current numerical method of this study, the optimization of the target centrifugal pump impeller was conducted. An improvement in flow rate was confirmed numerically, and a manufactured proto-type of the optimized model was used for experimental investigation. Furthermore, it was observed that by applying the fan law, we could effectively reduce noise levels without reducing the flow rate.

• Geophysics and Geophysical Exploration
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• v.26 no.4
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• pp.211-228
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• 2023

Ground-penetrating radar (GPR) surveys are commonly used to monitor embankments, which is a nondestructive geophysical method. The results of GPR surveys can be complex, depending on the situation, and data processing and interpretation are subject to expert experiences, potentially resulting in false detection. Additionally, this process is time-intensive. Consequently, various studies have been undertaken to detect cavities in GPR survey data using deep learning methods. Deep-learning-based approaches require abundant data for training, but GPR field survey data are often scarce due to cost and other factors constaining field studies. Therefore, in this study, a deep- learning-based model was developed for embankment GPR survey cavity detection using data augmentation strategies. A dataset was constructed by collecting survey data over several years from the same embankment. A you look only once (YOLO) model, commonly used in computer vision for object detection, was employed for this purpose. By comparing and analyzing various strategies, the optimal data augmentation approach was determined. After initial model development, a stepwise process was employed, including box clustering, transfer learning, self-ensemble, and model ensemble techniques, to enhance the final model performance. The model performance was evaluated, with the results demonstrating its effectiveness in detecting cavities in embankment GPR survey data.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.6
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• pp.91-98
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• 2023

The amount of power generation of a solar plant has a high correlation with weather conditions, geographical conditions, and the installation conditions of solar panels. Previous studies have found the elements which impacts the amount of power generation. Some of them found the optimal conditions for solar panels to generate the maximum amount of power. Considering the realistic constraints when installing a solar power plant, it is very difficult to satisfy the conditions for the maximum power generation. Therefore, it is necessary to know how sensitive the solar power generation amount is to factors affecting the power generation amount, so that plant owners can predict the amount of solar power generation when examining the installation of a solar power plant. In this study, we propose a polynomial regression analysis method to analyze the relationship between solar power plant's power generation and related factors such as weather, location, and installation conditions. Analysis data were collected from 10 solar power plants installed and operated in Daegu and Gyeongbuk. As a result of the analysis, it was found that the amount of power generation was affected by panel type, amount of insolation and shade. In addition, the power generation was affected by interaction of the installation angle and direction of the panel.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.5
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• pp.151-158
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• 2023

The researchers entirely focused on meta-heuristic method for generalized assignment problem(GAP) that is known as NP-hard problem because of the optimal solution within polynomial time algorithm is unknown yet. On the other hand, this paper proposes a heuristic greedy algorithm with rules for finding solutions. Firstly, this paper reduces the weight matrix of original data to w_ij ≤ b_i/l in order to n jobs(items) pack m machines(bins) with l = n/m. The maximum profit of each job was assigned to the machine for the reduced data. Secondly, the allocation was adjusted so that the sum of the weights assigned to each machine did not exceed the machine capacity. Finally, the k-opt swap optimization was performed to maximize the profit. The proposed algorithm is applied to 50 benchmarking data, and the best known solution for about 1/3 data is to solve the problem. The remaining 2/3 data showed comparable results to metaheuristic techniques. Therefore, the proposed algorithm shows the possibility that rules for finding solutions in polynomial time exist for GAP. Experiments demonstrate that it can be a P-problem from an NP-hard.

• Tunnel and Underground Space
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• v.33 no.6
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• pp.594-609
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• 2023

TBM (Tunnel Boring Machine) method is gaining popularity in urban and underwater tunneling projects due to its ability to ensure excavation face stability and minimize environmental impact. Among the prominent models for predicting disc cutter life, the NTNU model uses the Cutter Life Index(CLI) as a key parameter, but the complexity of testing procedures and rarity of equipment make measurement challenging. In this study, CLI was predicted using multiple linear regression analysis and tree-based machine learning techniques, utilizing rock properties. Through literature review, a database including rock uniaxial compressive strength, Brazilian tensile strength, equivalent quartz content, and Cerchar abrasivity index was built, and derived variables were added. The multiple linear regression analysis selected input variables based on statistical significance and multicollinearity, while the machine learning prediction model chose variables based on their importance. Dividing the data into 80% for training and 20% for testing, a comparative analysis of the predictive performance was conducted, and XGBoost was identified as the optimal model. The validity of the multiple linear regression and XGBoost models derived in this study was confirmed by comparing their predictive performance with prior research.

• Korean Journal of Culture and Social Issue
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• v.14 no.4
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• pp.103-117
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• 2008

The polygraph test administered by the Korean Prosecutors Office for crime investigations customarily uses the score of -12 as the cutoff point separating the subjects who lie from those who tell the truth. The criterion used by the KPO is different from the one (-13) suggested by Backster (1963) who invented the particular method for lie detection. Based on the signal detection theory applied to the real polygraph test data obtained from real crime suspects by the KPO, the present study identified the score of -8 as an optimal criterion resulting in the highest overall accuracy of the polygraph test. The classification of the subjects with the score of -8 as the criterion resulted in the highest accuracy (83.17%) compared with the accuracies of classifications with the Backster's criterion (76.24%) and the KPO's criterion (80.20%). However, the new criterion was also found to result in more false-positive cases. Based on the results from the present study, it was recommended to use the score of -8 as the criterion when the overall accuracy is important but the score of -12 or -13 when avoiding false-positive is more important than securing the overall accuracy.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.325-345
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• 2023

In the rapidly evolving domain of e-commerce, our study presents a cohesive approach to enhance customer satisfaction prediction from online reviews, aligning methodological innovation with practical insights. We integrate the RFE-SHAP feature selection with LDA topic modeling to streamline predictive analytics in e-commerce. This integration facilitates the identification of key features-specifically, narrowing down from an initial set of 28 to an optimal subset of 14 features for the Random Forest algorithm. Our approach strategically mitigates the common issue of overfitting in models with an excess of features, leading to an improved accuracy rate of 84% in our Random Forest model. Central to our analysis is the understanding that certain aspects in review content, such as quality, fit, and durability, play a pivotal role in influencing customer satisfaction, especially in the clothing sector. We delve into explaining how each of these selected features impacts customer satisfaction, providing a comprehensive view of the elements most appreciated by customers. Our research makes significant contributions in two key areas. First, it enhances predictive modeling within the realm of e-commerce analytics by introducing a streamlined, feature-centric approach. This refinement in methodology not only bolsters the accuracy of customer satisfaction predictions but also sets a new standard for handling feature selection in predictive models. Second, the study provides actionable insights for e-commerce platforms, especially those in the clothing sector. By highlighting which aspects of customer reviews-like quality, fit, and durability-most influence satisfaction, we offer a strategic direction for businesses to tailor their products and services.

• Journal of Mushroom
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• v.21 no.4
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• pp.261-265
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• 2023

We aimed to develop outstanding domestic varieties suitable for both columnar and cylindrical-shape substrates, aiming to replace foreign varieties. and bred a high-quality new strain named 'Charmjon', using genetic resources collected from Japan and China. The optimal cultivation temperature for Charmjon's mycelial growth was found to be 25℃, and its mycelial growth at 15℃ and 25℃ was superior to the control variety. In terms of mycelial growth characteristics based on the substrate, Charmjon exhibited excellent mycelial strength on PDA medium compared to the control variety. Through columnar and cylindrical-shape substrates cultivation, we assessed the quantity and morphological characteristics of the fruiting bodies. The results confirmed that Charmjon can be produced stably using both cultivation methods, and it showed higher yields and individual weights than the control variety. In addition, the color of the pileus was notably darker, and the shape of the pileus varied depending on the cultivation method. The test of genetic diversity revealed that Charmjon has distinct genetic characteristics compared to the control varieties.