• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.17 no.11 s.114
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• pp.1120-1131
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• 2006

This paper describes the numerical analysis techniques using the Combined Integration/Matrix Method to calculate ground potential rise which can be occurred in the various grounding systems. Combined Integration/Matrix Method is used to reduce the error and computation time with the analytical integration equation and the proper segmentaion of earth embedded conductor. To do it, optimal segmentaion method for the buried conductors is presented through error analysis which is capable of applying the practical scaled various grounding systems. The optimum length of segmented element is much co-related with the buried depth of grounding electrode and the maximum length of buried electrode. As a result, less 3 precent errors was obtained by proposed model. The proposed model is applied to verify an effect of multi-grounding problems which was aroused much controversy with separated or common grounding between the high power grounding system and low power grounding system such as signal and telecommunication grounding.

• Genomics & Informatics
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• v.4 no.1
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• pp.40-44
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• 2006

Toxicogenomics combines transcriptome, proteome and metabolome profiling with conventional toxicology to investigate the interaction between biological molecules and toxicant or environmental stress in disease caution. Toxicogenomics faces the problems of comparison and integration across different sources of data. Cause of unusual characteristics of toxicogenomic data, researcher should be assisted by data analysis and annotation for getting meaningful information. There are already existing repositories which claim to stand for toxicogenomics database. However, those just contain limited abilities for toxicogenomic research. For supporting toxicologist who comes up against toxicogenomic data flood, now we propose novel toxicogenomics knowledgebase system, XPERANTO-TOX. XPERANTO-TOX is an integrated system for toxicogenomic data management and analysis. It is composed of three distinct but closely connected parts. Firstly, Data Storage System is for reposit many kinds of '-omics' data and conventional toxicology data. Secondly, Data Analysis System consists of analytical modules for integrated toxicogenomics data. At last, Data Annotation System is for giving extensive insight of data to researcher.

• Journal of Korean Society of Water and Wastewater
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• v.31 no.6
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• pp.511-519
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• 2017

Multi-regional water supply system, which installed for supplying multiple water demands, is characterized by large-sized, long-distance, tree-type layout. This system is vulnerable to long-standing service interruption when a pipe breaks is occurred. In this study, a numerical method is proposed to calculate drainage time that directly affects time of service interruption. To begin with, governing equations are formulated to embed the delayed drainage effect by the friction loss, and to resolve complicated connection of pipelines, which are derived from the continuity and energy equations. The nonlinear hydraulic equations are solved by using explicit time integration method and the Newton-Raphson method. The developed model is verified by comparing the result with analytical solution. Furthermore, the model's applicability is validated by the examples of pipelines in serial, in parallel, and complex layout. Finally, the model is utilized to suggest an appropriate actions to reduce the deviation of draining time in the C transmission line of the B multi-regional water supply system.

• The Korean Journal of Applied Statistics
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• v.29 no.1
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• pp.75-83
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• 2016

We propose methodology to analyze the dynamic mechanisms of financial market contagion under market integration using a biological contagion analytical approach. We employ U-statistic to measure market integration, and a dynamic model based on an error correction mechanism (single equation error correction model) and latent factor model to examine market contagion. We also use quantile regression and Wald-Wolfowitz runs test to test market contagion. This methodology is designed to effectively handle heteroscedasticity and correlated errors. Our simulation results show that the single equation error correction model fits well with the linear regression model with a stationary predictor and correlated errors.

• Journal of Communications and Networks
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• v.13 no.4
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• pp.313-318
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• 2011

When wireless channels undergo fast fading, non-coherent frequency shift keying (FSK) (de)modulation schemes may be considered for amplify-and-forward (AF) cooperative communications. In this paper, we derive the bit-error-rate performance of partial non-coherent receiver as a lower bound of the optimal non-coherent receiver for FSK modulated AF cooperative communications. From the simulation and analytical results, it is found that the derived lower bound is very closed to simulation results. This result shows that knowing partial channel state information may not improve system performance significantly. On the other hand, conventional optimal non-coherent receiver involves complicated integration operation. To address the above complexity issue, we also propose a near optimal non-coherent receiver which does not involve integration operation. Simulation results have shown that the performance gap between the proposed near optimal receiver and the optimal receiver is small.

• Journal of the Korea Safety Management & Science
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• v.7 no.5
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• pp.155-174
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• 2005

Parametric life-cycle cost(LCC) models have been integrated with traditional design tools, and used in prior work to demonstrate the rapid solution of holistic, analytical tradeoffs between detailed design variations. During early designs stages there may be competing concepts with dramatic differences. Additionally, detailed information is scarce, and decisions must be models. for a diverse range of concepts, and the lack of detailed information make the integration make the integration of traditional LCC models impractical. This paper explores an approximate method for providing preliminary life-cycle cost. Learning algorithms trained using the known characteristics of existing products be approximated quickly during conceptual design without the overhead of defining new models. Artificial neural networks are trained to generalize on product attributes and life cycle cost date from pre-existing LCC studies. The Product attribute data to quickly obtain and LCC for a new and then an application is provided. In additions, the statistical method, called regression analysis, is suggested to predict the LCC. Tests have shown it is possible to predict the life cycle cost, and the comparison results between a learning LCC model and a regression analysis is also shown

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.24 no.1
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• pp.45-53
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• 2014

For the time integration solution of the impulsive dynamic contact problem of high-speed rotating disks formulated by the finite element technique, the velocity and acceleration contact constraints as well as the displacement contact constraint are imposed for the numerical stability without spurious oscillations. The solution of the present technique is checked by the numerical simulation using the concentric high-speed rotating disks with the clearance and impulsive loading. It is shown that the almost steady state solution agrees with the corresponding analytical solution of the elasticity and that the differentiated constraints are crucial for the numerical stability of such high-speed contact problems of the disks under impulsive loading.

• The Mathematical Education
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• v.63 no.2
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• pp.233-254
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• 2024

This paper delves into the symbiotic integration of coding and mathematics education, aimed at cultivating computational thinking and enriching mathematical problem-solving proficiencies. We have identified a corpus of scholarly articles (n=38) disseminated within the preceding two decades, subsequently culling a portion thereof, ultimately engendering a contemplative analysis of the extant remnants. In a swiftly evolving society driven by the Fourth Industrial Revolution and the ascendancy of Artificial Intelligence (AI), understanding the synergy between these domains has become paramount. Mathematics education stands at the crossroads of this transformation, witnessing a profound influence of AI. This paper explores the evolving landscape of mathematical cognition propelled by AI, accentuating how AI empowers advanced analytical and problem-solving capabilities, particularly in the realm of big data-driven scenarios. Given this shifting paradigm, it becomes imperative to investigate and assess AI's impact on mathematics education, a pivotal endeavor in forging an education system aligned with the future. The symbiosis of AI and human cognition doesn't merely amplify AI-centric thinking but also fosters personalized cognitive processes by facilitating interaction with AI and encouraging critical contemplation of AI's algorithmic underpinnings. This necessitates a broader conception of educational tools, encompassing AI as a catalyst for mathematical cognition, transcending conventional linguistic and symbolic instruments.

• Mass Spectrometry Letters
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• v.15 no.2
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• pp.69 -78
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• 2024

The advancement of high-throughput omics technologies and systems biology is essential for understanding complex biological mechanisms and diseases. The integration of proteomics and metabolomics provides comprehensive insights into cellular functions and disease pathology, driven by developments in mass spectrometry (MS) technologies, including electrospray ionization (ESI). These advancements are crucial for interpreting biological systems effectively. However, integrating these technologies poses challenges. Compared to genomic, proteomics and metabolomics have limitations in throughput, and data integration. This review examines developments in MS equipped electrospray ionization (ESI), and their importance in the effective interpretation of biological mechanisms. The review also discusses developments in sample preparation, such as Simultaneous Metabolite, Protein, Lipid Extraction (SIMPLEX), analytical techniques, and data analysis, highlighting the application of these technologies in the study of cancer or Huntington's disease, underscoring the potential for personalized medicine and diagnostic accuracy. Efforts by the Clinical Proteomic Tumor Analysis Consortium (CPTAC) and integrative data analysis methods such as O2PLS and OnPLS extract statistical similarities between metabolomic and proteomic data. System modeling techniques that mathematically explain and predict system responses are also covered. This practical application also shows significant improvements in cancer research, diagnostic accuracy and therapeutic targeting for diseases like pancreatic ductal adenocarcinoma, non-small cell lung cancer, and Huntington's disease. These approaches enable researchers to develop standardized protocols, and interoperable software and databases, expanding multi-omics research application in clinical practice.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.151-156
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• 1995

This paper presents a methodology for real-time detecting and identifying the runout geometry of an end mill. Cutter runout is a common but undesirable phenomenon in multi-tooth machining such as end-milling process because it introduces variable chip loading to insert which results in a accelerated tool wear,amplification of force variation and hence enlargement vibration amplitude. Form understanding of chip load change kinematics, the analytical sutting force model was formulated as the angular domain convolution of three dynamic cutting force component functions. By virtue of the convolution integration property, the frequency domain expression of the total cutting forces can be given as the algebraic multiplication of the Fourier transforms of the local cutting forces and the chip width density of the cutter. Experimental study are presented to validata the analytical model. This study provides the in-process monitoring and compensation of dynamic cutter runout to improve machining tolerance tolerance and surface quality for industriql application.