• Journal of the Korea Society of Computer and Information
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• v.24 no.1
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• pp.257-263
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• 2019

This paper is a study on mathematical aspects that can be basic for understanding and applying the contents of machine learning. If you are familiar with mathematics in the field of computer science, you can create algorithms that can diversify researches and implement them faster, so you can implement many real-life ideas. There is no curriculum standard for mathematics in the field of machine learning, and there are many absolutely lacking mathematical contents that are taught in the curriculum presented at existing universities. Machine learning now includes speech recognition systems, search engines, automatic driving systems, process automation, object recognition, and more. Many applications that you want to implement combine a large amount of data with many variables into the components that the programmer generates. In this course, the mathematical areas required for computer engineer (CS) practitioners and computer engineering educators have become diverse and complex. It is important to analyze the mathematical content required by engineers and educators and the mathematics required in the field. This paper attempts to present an effective range design for the essential processes from the basic education content to the deepening education content for the development of many researches.

• East Asian Journal of Business Economics (EAJBE)
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• v.9 no.3
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• pp.71-82
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• 2021

Purpose - The purpose of this study is to examine the intermediary role of job satisfaction between job autonomy and job performance and whether the process was adjusted based on the work context. Research design, data, and methodology - This study was conducted by sample survey method on 334 supervising engineers. Data analysis methods were frequency analysis, confirmatory factor analysis, reliability analysis, correlation analysis, and structural equation model analysis. Result - The results of this study suggest that: (1) after controlling for age, position, and working years, job autonomy had a significant positive impact on job performance, (2) job autonomy can not only directly affect job performance but also indirectly affect performance through job satisfaction, (3) job satisfaction has an intermediary effect on job autonomy and job performance, and (4) the relationship between job autonomy and job satisfaction is moderated by the work context, and the result showed a negative moderating effect. Conclusion - This study suggests that job autonomy significantly improves job performance, and the higher job autonomy a supervising engineer has, the more satisfied they are with their work, thus enriching the precursor research on dynamic changes in job performance. When the working environment is poor, supervisors are more sensitive to the perception of job autonomy and have a stronger impact on job satisfaction and performance.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.6
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• pp.617-625
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• 2021

The problems associated with the continuous method of a domestically improved prestressed concrete (PSC) girder and the bending moment of a continuous tendon were studied. Based on the results, a continuous tendon model was proposed that can resist the negative bending moment of an intergirder. This model lowers the anchorage of the continuous tendon as far as possible under the girder, and extends the tendon section arranged under the girder. This method reduces the PS's bending moment in the middle of the span, but maximizes it in the intergirder. This continuous tendon model can offer a suitable method for continuity before manufacturing a composite, which requires a higher design bending moment in the intergirder than in the middle of the span.

• Corrosion Science and Technology
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• v.21 no.5
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• pp.390-411
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• 2022

Any design engineer or coating formulator's primary objective is to protect metals. Large investments in terms of money, time, labour, and other resources are necessary for constructing large-scale machinery and structures. In terms of economy, the structure's lifespan should be as long as feasible to create revenue. It is becoming essential to protect metal substrates from corrosion to prolong the lifespan of such huge structures. One of the most exciting, durable, useful, and effective methods to protect metals from corrosion is the application of corrosion-resistant coating. Graphene is a novel material with a wide range of applications because of its extraordinary features. The use of graphene in coating creates an obstacle and complicates the path for corrosive medium to reach the metal. As the path to the metal elongates, the corrosion medium takes longer to reach the metal. Thus, metal corrosion can be avoided. In this paper, the importance of graphene in coating formulation is discussed, including chemical modifications of graphene, the effect of graphene concentration on corrosion inhibition, and the contact angle of coating. This review also highlights the significance of water-based corrosion-resistant coating for preventing environmental damage.

• Design & Manufacturing
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• v.16 no.3
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• pp.50-57
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• 2022

The qualities of the products produced by injection molding are strongly influenced by the process variables of the injection molding machine set by the engineer. It is very difficult to predict the qualities of the injection molded product considering the stochastic nature of the manufacturing process, since the processing conditions have a complex impact on the quality of the injection molded product. It is recognized that the artificial neural network(ANN) is capable of mapping the intricate relationship between the input and output variables very accurately, therefore, many studies are being conducted to predict the relationship between the results of the product and the process variables using ANN. However in the condition of a small number of data sets, the predicting performance and robustness of the ANN model could be reduced due to too many input variables. In the present study, the ANN model that predicts the length of the injection molded product for multiple combinations of process variables was developed. And the accuracy of each ANN model was compared for 8 process variables and 4 important process inputs that were determined by the feature selection. Based on the comparison, it was verified that the performance of the ANN model increased when only 4 important variables were applied.

• Advances in Computational Design
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• v.7 no.1
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• pp.1-17
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• 2022

In this study, a new strategy is presented to transmit the fundamental elastic beam problem into the modern optimization platform and solve it by using artificial intelligence (AI) tools. As a practical example, deflection of Euler-Bernoulli beam is mathematically formulated by 2nd-order ordinary differential equations (ODEs) in accordance to the classical beam theory. This fundamental engineer problem is then transmitted from classic formulation to its artificial-intelligence presentation where the behavior of the beam is simulated by using neural networks (NNs). The supervised training strategy is employed in the developed NNs implemented in the heuristic optimization algorithms as the fitness function. Different evolutionary optimization tools such as genetic algorithm (GA) and particle swarm optimization (PSO) are used to solve this non-linear optimization problem. The step-by-step procedure of the proposed method is presented in the form of a practical flowchart. The results indicate that the proposed method of using AI toolsin solving beam ODEs can efficiently lead to accurate solutions with low computational costs, and should prove useful to solve more complex practical applications.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.2
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• pp.486-503
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• 2023

Logs play an important role in mastering the health of the system, experienced operation and maintenance engineer can judge which part of the system has a problem by checking the logs. In recent years, many system architectures have changed from single application to distributed application, which leads to a very huge number of logs in the system and manually check the logs to find system errors impractically. To solve the above problems, we propose a method based on Message Middleware and ATT-GRU (Attention Gate Recurrent Unit) to detect the logs anomaly of distributed systems. The works of this paper mainly include two aspects: (1) We design a high-performance distributed logs collection architecture to complete the logs collection of the distributed system. (2)We improve the existing GRU by introducing the attention mechanism to weight the key parts of the logs sequence, which can improve the training efficiency and recognition accuracy of the model to a certain extent. The results of experiments show that our method has better superiority and reliability.

• Advances in aircraft and spacecraft science
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• v.10 no.2
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• pp.141-158
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• 2023

In current research work, the aerodynamics performance of a newly designed large flying V aircraft is numerically investigated. Three Flying V configurations, with V-angles of 50°, 70° and 90° that represent the minimum, moderate, and maximum configurations respectively, were designed and modeled to assess their aerodynamic performance at cruise flight conditions. The unstructured mesh was developed using ICEM CFD and Ansys-Fluent was used as an aerodynamic solver. The developed models were numerically simulated at cruise flight conditions with a Mach number equal to 0.15. K-ω SST turbulence model was chosen to account for flow turbulence.The authors performed steady flow simulations.The results obtained from the experimentation reveal that the maximum main angle configuration of 90° had the highest C_Lmax value of 0.46 compared to other configurations. While the drag coefficient remained the same for all three configurations, the 50° V-angle configuration achieved the maximum stall angle of 35°. With limited stall delay benefits, the flying V possesses no sufficient stability, due to the flow separation detected at whole elevon and winglet suction side areas at AoA equal and higher than 30°.

• The Journal of Information Systems
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• v.33 no.1
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• pp.207-226
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• 2024

Purpose This study aims to develop a job model for data convergent talents to meet the rapidly changing demands of the data industry. To create a job model, we first define and categorize data convergent talents with balanced competencies in data technology and domain knowledge, and then develop a job model by investigating job areas, scope, activities, and competencies. Design/methodology/approach The research is conducted using the following procedures and methodology. First, we conduct a current status survey on data talent demand, data talent policies, data talent programs, and curricula at home and abroad; second, we collect opinions on the jobs and competencies required for data convergent talents and curricula for talent development through in-depth interview with experts; and third, we present the job areas and job activities of data convergent talents derived from the previous status survey and expert opinions based on the National Competency Standards(NCS). Findings The research findings indicate that there are total of six job roles for data convergent talents, including data scientist, data planner, data architect, data developer, data engineer, and data analyst. It was observed that each of these roles requires the development of common competencies within their respective fields, followed by a need for further specialization into specific competencies within each professional domain.

• Geomechanics and Engineering
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• v.37 no.1
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• pp.31-48
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• 2024

To stabilize the excavations in urban area, soil anchorage is among the very common methods in geotechnical engineering. A more efficient deformation analysis can potentially lead to cost-effective and safer designs. To this end, a total of 116 three-dimensional (3D) finite element (FE) models of a deep excavation supported by tie-back wall system were analyzed in this study. An initial validation was conducted through examination of the results against the Texas A&M excavation cases. After the validation step, an extensive parametric study was carried out to cover significant design parameters of tie-back wall system in deep excavations. The numerical results indicated that the maximum horizontal displacement values of the wall (δ_hm) and maximum surface settlement (δ_vm) increase by an increase in the value of ground anchors inclination relative to the horizon. Additionally, a change in the wall embedment depth was found to be contributing more to δ_vm than to δ_hm. Based on the 3D FE analysis results, two simple equations are proposed to estimate excavation deformations for different scenarios in which the geometric configuration parameters are taken into account. The model proposed in this study can help the engineers to have a better understanding of the behavior of such systems.