• Structural Engineering and Mechanics
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• v.73 no.5
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• pp.501-513
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• 2020

In the present work, the optimization of machining parameters to achieve the desired technological parameters such as surface roughness, tool radial vibration and material removal rate have been carried out using response surface methodology (RSM). The hard turning of EN19 alloy steel with coated carbide (GC3015) cutting tools was studied. The main problem faced in manufacturer of hard and high precision components is the selection of optimum combination of cutting parameters for achieving required quality of surface finish with maximum production rate. This problem can be solved by development of mathematical model and execution of experiments by RSM. A face centred central composite design (FCCD), which comes under the RSM approach, with cutting parameters (cutting speed, feed rate and depth of cut) was used for statistical analysis. A second-order regression model were developed to correlate the cutting parameters with surface roughness, tool vibration and material removal rate. Consequently, numerical and graphical optimization were performed to obtain the most appropriate cutting parameters to produce the lowest surface roughness with minimal tool vibration and maximum material removal rate using desirability function approach. Finally, confirmation experiments were performed to verify the pertinence of the developed mathematical models.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.8
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• pp.4108-4122
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• 2019

Workflow process mining is becoming a more and more valuable activity in workflow-supported enterprises, and through which it is possible to achieve the high levels of qualitative business goals in terms of improving the effectiveness and efficiency of the workflow-supported information systems, increasing their operational performances, reducing their completion times with minimizing redundancy times, and saving their managerial costs. One of the critical challenges in the workflow process mining activity is to devise a reasonable approach to discover and recognize the bottleneck points of workflow process models from their enactment event histories. We have intuitively realized the fact that the iterative process pattern of redo-activities ought to have the high possibility of becoming a bottleneck point of a workflow process model. Hence, we, in this paper, propose an algorithmic approach and its implementation to discover the redo-activities and their performers' involvements patterns from workflow process enactment event logs. Additionally, we carry out a series of experimental analyses by applying the implemented algorithm to four datasets of workflow process enactment event logs released from the BPI Challenges. Finally, those discovered redo-activities and their performers' involvements patterns are visualized in a graphical form of information control nets as well as a tabular form of the involvement percentages, respectively.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.7
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• pp.90-99
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• 1996

In the area of assembly process of micro-chips and electronic parts on the printed circuit board, surface mounting device(SMD) is used as a fundamental tool. Generally speaking, the motion of the SMD is based on the ball screw system operated by any type of actuators. The ball screw system is a mechanical transformed which converts the mechanical rotational motion to the translational one. Also, this system could be considered as an efficient motion device against mechanical backlash and friction. Therefore a dynamic modeling and state sensitivity analysis of the ball screw system in SMD have to be done in the initial design stage. In this paper, a simple mathematical dynamic model for this system and the sensit- ivity analysis are mentioned. Especially, the bond graph approach is used for graphical modeling of the dynamic system before analysis stage. And the direct differentiation method is used for the state sensit- ivity analysis of the system. Finally, some trends for the state variables with respect to the design variables could be suggested for the better design and faster operating based on the results of dynamic and state sensitivity.

• Journal of Information Science Theory and Practice
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• v.12 no.1
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• pp.77-86
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• 2024

As the significance of knowledge convergence continues to grow, universities are making efforts to develop methods that promote multidisciplinary learning. To address this educational challenge, our paper applies network theory and text mining techniques to analyze university curricula and introduces a graphical syllabus rendering method. Visualizing the course curriculum provides a macro and structured perspective for individuals seeking alternative educational pathways within the existing system. By visualizing the relationships among courses, students can explore different combinations of courses with comprehensive search support. To illustrate our approach, we conduct a detailed demonstration using the syllabus database of Yonsei University. Through the application of our methods, we create visual course networks that reveal the underlying structure of the university curriculum. Our results yield insights into the interconnectedness of courses across various academic majors at Yonsei University. We present both macro visualizations, covering 18 academic majors, and visualizations for a few selected majors. Our analysis using Yonsei University's database not only showcases the value of our methodology but also serves as a practical example of how our approach can facilitate multidisciplinary learning.

• Journal of Convergence Society for SMB
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• v.3 no.2
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• pp.33-39
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• 2013

Recently, lots of anti-phishing schemes have been developed. Several products identify phishing sites and show the results on the address bar of the internet browser. However, they determine only by domain names or IP addresses. Although this kind of method is effective against recent DNS Pharming attacks, there is still a possibility that hidden attacks which modifies HTML codes could incapacitate those anti-phishing programs. In this paper, the cognitive approach which compares images to decide phishing or Pharming is presented by using system tray and balloon tips that are hard to fake with pop-ups or flash in order for users to compare pictures from connecting sites and system tray. It differs from an old method that a program analyzes IP or domains to judge if it is phishing or Pharming. Therefore, proposed method effective cognitive approach against phishing and Pharming attacks.

• Journal of Korean Port Research
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• v.12 no.1
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• pp.55-64
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• 1998

Directed graphic algorithm was applied to an empirical analysis of traffic occupant fatalities based on a model by Crandall. In this paper, Crandall's data on U.S. traffic fatalities for the period 1947-1981 are focused and extended to include 1982-1993. Based on the 1947-1981 annual data, the directed graph algorithms reveal that occupant traffic deaths are directly caused by income, vehicle miles, and safety devices. Vehicle mileage is caused by income and rural driving. The estimation is conducted using three stage least squares regression. Those results show a difference between the traditional regression methodology and causal graphical analysis. It is also found that forecasts from the directed graph based model outperform forecasts from the regression-based models, in terms of mean squared forecasts error. Furthermore, it is demonstrates that there exists some latent variables between all explanatory variables and occupant deaths.

• Geomechanics and Engineering
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• v.37 no.1
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• pp.65-72
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• 2024

Water ingress poses a common and intricate geological hazard with profound implications for tunnel construction's speed and safety. The project's success hinges significantly on the precision of estimating water inflow during excavation, a critical factor in early-stage decision-making during conception and design. This article introduces an optimized model employing the gene expression programming (GEP) approach to forecast tunnel water inflow. The GEP model was refined by developing an equation that best aligns with predictive outcomes. The equation's outputs were compared with measured data and assessed against practical scenarios to validate its potential applicability in calculating tunnel water input. The optimized GEP model excelled in forecasting tunnel water inflow, outperforming alternative machine learning algorithms like SVR, GPR, DT, and KNN. This positions the GEP model as a leading choice for accurate and superior predictions. A state-of-the-art machine learning-based graphical user interface (GUI) was innovatively crafted for predicting and visualizing tunnel water inflow. This cutting-edge tool leverages ML algorithms, marking a substantial advancement in tunneling prediction technologies, providing accuracy and accessibility in water inflow projections.

• Water Engineering Research
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• v.1 no.2
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• pp.137-146
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• 2000

A windows-based software package, named DREDGE, is developed for estimating sediment resuspension and contaminant release during dredging operations. DREDGE allows user to enter the necessary dredge information, site characteristics, operational data, and contaminant characteristics, then calculates an array of concentration using the given values. The program mainly consists of the near-field models, which are obtained empirically, for estimating sediment resuspension and the far-field models, which are obtained analytically, for suspended sediment transport. A linear equilibrium partitioning approach is applied to estimate particulate and dissolved contaminant concentrations. This software package which requires only a minimal amount of data consists of three components; user input, tabular output, and graphical output. Combining the near-field and far-field models into a user-friendly windows-based computer program can greatly save dredge operator's, planners', and regulators' efforts for estimating sediment transports and contaminant distribution.

• International Journal of Reliability and Applications
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• v.6 no.2
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• pp.79-85
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• 2005

We show how comparative mean residual life functions (MRL) can be used to give unique insights into strengths of materials data. Recall that Weibull's original reliability function was developed studying and fitting strengths for various materials. This creative comparing of MRL functions approach can be used for regular life data or any time to response data. We apply graphical MRL's to real data from tests of tensile strength of high quality engineered wood.

• 한국신재생에너지학회:학술대회논문집
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• 2010.06a
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• pp.106.2-106.2
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• 2010

IGCC (Integrated Gasification Combined Cycle) plants are among the most advanced and effective systems for electric energy generation. From a control perspective, IGCC plants represent a significant challenge: complex reactions, highly integrated control to simultaneously satisfy production, controllability, operability and environmental objectives. While all these requirements seem clearly to demand a multivatiable, model predictive approach, not many applications can be easily found in the literature. This paper describes the IGCC dynamic simulation that is capable of simulating plant startup, shutdown, normal, and abnormal operation and engineering studies. This high fidelity dynamic models contain the detailed process design data to produce realistic responses to process operation and upset. And the simulation is used by engineers to evaluate the transient performance and produce graphical information indicating the response of the process under study conditions.