• Coupled systems mechanics
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• v.13 no.3
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• pp.219-229
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• 2024

By introducing optimization algorithms into the machining process, product quality can be improved, time saved, and costs reduced. The cutting speed and feed can be handled by the turning machine. The approach of optimizing is used to manage pyrotechnics, Lawler's, greedy, bacterial colony, elephant herding, ant lion, spiral, auction, and pattern search for these ten odd ways. Ten artificial optimization methodologies were used to investigate the time and cost of a turning machine. It has been discovered how to create the optimal turning machine procedure. The best solution approach for the turning machine process problem is found, and the results are verified using ANSYS.

• The Journal of Information Systems
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• v.33 no.1
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• pp.31-44
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• 2024

Purpose The purpose of this study is to use climate data to find the algorithm with the highest Hallabong production prediction ability and to predict future Hallabong production in areas where Hallabong cultivation is expected to be possible. Design/methodology/approach The research is conducted in two stages. In the first step, find the algorithm with the highest predictive power among XGBoost, Random Forest, SVM, and LSTM methodologies. In the second stage, the algorithm found in the first stage is applied to predict future Hallabong production in three regions where Hallabong production is expected to be possible. Findings As with many prediction studies, we found that XGBoost showed the highest prediction power. Even in areas where Hallabong production is expected to be possible, Hallabong production was predicted to be highest in Hongcheon, Gangwon-do, which has the highest latitude.

• Asia-Pacific Journal of Business
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• v.15 no.1
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• pp.145-157
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• 2024

Purpose - In this study, we propose an empirical model for predicting seasoned equity offering (SEO here after) using machine learning methods. Design/methodology/approach - The models utilize the random forest method based on decision trees that considers non-linear relationships, as well as the gradient boosting tree model. SEOs incur significant direct and indirect costs. Therefore, CEOs' decisions of seasoned equity issuances are made only when the benefits outweigh the costs, which leads to a non-linear relationship between SEOs and a determinant of them. Particularly, a variable related to market timing effectively exhibit such non-linear relations. Findings - To account for these non-linear relationships, we hypothesize that decision tree-based random forest and gradient boosting tree models are more suitable than the linear methodologies due to the non-linear relations. The results of this study support this hypothesis. Research implications or Originality - We expect that our findings can provide meaningful information to investors and policy makers by classifying companies to undergo SEOs.

• Advances in materials Research
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• v.13 no.4
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• pp.321-334
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• 2024

The paper is a study on the biothermoelastic analysis in viscoelastic biological tissues in the presence of thermal relaxation times. Using Laplace transforms and related methodologies, we explore how living tissue responds to an exponentially decaying pulse of heat flux at the boundary. The Laplace transformations are reversed using the numerical method. The Tzuo technique was used to measure the reversal. Temperature, displacement, and stress distributions are affected by single-phase and delay relaxation coefficients as well as volume rheological factors, are provided with numerical findings and graphically depicted. In addition, we carry out a parametric analysis to provide assistance in choosing the design variables that are the most successful, which finally results in an improvement in the accuracy of hyperthermia treatments.

• International Journal of Control, Automation, and Systems
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• v.1 no.3
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• pp.321-331
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• 2003

Experimental software datasets describing software projects in terms of their complexity and development time have been the subject of intensive modeling. A number of various modeling methodologies and modeling designs have been proposed including such approaches as neural networks, fuzzy, and fuzzy neural network models. In this study, we introduce the concept of the Rule-based fuzzy polynomial neural networks (RFPNN) as a hybrid modeling architecture and discuss its comprehensive design methodology. The development of the RFPNN dwells on the technologies of Computational Intelligence (CI), namely fuzzy sets, neural networks, and genetic algorithms. The architecture of the RFPNN results from a synergistic usage of RFNN and PNN. RFNN contribute to the formation of the premise part of the rule-based structure of the RFPNN. The consequence part of the RFPNN is designed using PNN. We discuss two kinds of RFPNN architectures and propose a comprehensive learning algorithm. In particular, it is shown that this network exhibits a dynamic structure. The experimental results include well-known software data such as the NASA dataset concerning software cost estimation and the one describing software modules of the Medical Imaging System (MIS).

• Korean Institute of Interior Design Journal
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• no.16
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• pp.135-141
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• 1998

The objective of this study is to examine the specific progress in modern architecture with a premise that structure-oriented paradigm, as a primary factor, exerts a strong impacts on 18th and 19th centuries architecture. For this purpose, the concept and meaning backgrounds of structure-oriented paradigm have been checked also intrinsic thought s and critical aspects of modern architecture with the light of structure-oriented paradigm have been studied, This study summarized as follows: 1) The concept of structure-oriented paradigm in accordance with ideologies and technologies is framework of through which is shared as collective consciousness. 2) The backdrops of this consciousness are scientific methodologies stemmed from Renaissance and Enlightenment spiritual absoluteness claimed by German Idealists developed structural engineering with newly introduced material like iron steel and reinforced concrete. 3) The intrinsic through in architectural theories are rational and technological idelolgies which is derived from the backdrops of structure-oriented paradigm. 4)The critical sapects of modern architecture in structure-oriented paradigm point of view are $\circled1$ material alteration and directive imitation of vocabularies in classical architecture with simply using newly introduced building material and structure systems $\circled2$ morphological substitution with abstractly interpreted materials and structure systems $\circled3$ revolutionary conversion into engineering architecture through maximum consideration in compliance with tectonics capabilities

• Spatial Information Research
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• v.8 no.2
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• pp.213-232
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• 2000

It is important to scrutinize spatial patterns in crime analysis since crime data has geographical attribute in itself. We focus on the development of ¨Crime Analysis GIS¨ prototype which can discover spatial patterns in crime data by integrating mapping functions of GIS and spatial analysis techniques. The structure of this system involves integration of DBMS and GIS, and the major functions of the system include (i) exploring spatial distribution of point data, (ii) mapping hot-spot, (iii) clustering analysis of crime occurrence, and (iv) analyzing aggregated areal data. The process of design and implementation of this system is based on object-oriented methodologies. A web-based extension of the prototype using 3-tier architecture is currently under development.

• Bulletin of the Korean Chemical Society
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• v.34 no.9
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• pp.2680-2684
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• 2013

Protein kinases (PKs) are an important source of drug targets, especially in oncology. With 500 or more kinases in the human genome and only few kinase inhibitors approved, kinase inhibitor discovery is becoming more and more valuable. Because the discovery of kinase inhibitors with an increased selectivity is an important therapeutic concept, many researchers have been trying to address this issue with various methodologies. Although many attempts to predict the activity and selectivity of kinase inhibitors have been made, the issue of selectivity has not yet been resolved. Here, we studied kinase selectivity by generating predictive models and analyzing their descriptors by using kinase-profiling data. The 5-fold cross-validation accuracies for the 51 models were between 72.4% and 93.7% and the ROC values for all the 51 models were over 0.7. The phylogenetic tree based on the descriptor distance is quite different from that generated on the basis of sequence alignment.

• Korean Journal of Computational Design and Engineering
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• v.16 no.6
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• pp.424-436
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• 2011

In this paper, we propose a methodology of generating a parametric segment model for human body using the Korean anthropometric data. The model is defined as an articulated body model consisted with 19 ellipsoid primitives. The primitives are joined at locations representing the physical joints of human body. A lot of previous researches have suggested methodologies of generating body models using the European or American anthropometric data, so that these models were inappropriate for engineering analyses and simulations in case of the Koreans. We defined a set of 35 body dimensions representing our segment model based on the anthropometric data of Koreans. Also we defined four key parameters of age, height, weight and waist circumference, and then we applied regression equations to associate the parameters to the aforementioned dimensions. As the results, we obtained the parametric human body segment models according to the various body types and the subject-specific models for a specific individual. The models in the various industries can be used as the base models for static and dynamic analysis considering the Koreans.

• Journal of Power Electronics
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• v.15 no.5
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• pp.1149-1157
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• 2015

As a key part in the wind turbine system, the power electronic converter is proven to have high failure rates. At the same time, the failure of the wind power converter is becoming more unacceptable because of the quick growth in capacity, remote locations to reach, and strong impact to the power grid. As a result, the correct assessment of reliable performance for power electronics is a crucial and emerging need; the assessment is essential for design improvement, as well as for the extension of converter lifetime and reduction of energy cost. Unfortunately, there still exists a lack of suitable physic-of-failure based evaluation tools for a reliability assessment in power electronics. In this paper, an advanced tool structure which can acquire various reliability metrics of wind power converter is proposed. The tool is based on failure mechanisms in critical components of the system and mission profiles in wind turbines. Potential methodologies, challenges, and technology trends involved in this tool structure are also discussed. Finally, a simplified version of the tool is demonstrated on a wind power converter based on Double Fed Induction Generator system. With the proposed tool structure, more detailed information of reliability performances in a wind power converter can be obtained before the converter can actually fail in the field and many potential research topics can also be initiated.