• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2005년도 추계학술대회논문집
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• pp.838-843
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• 2005

The nonlinear characteristics of a suspension is directly related to the ride quality of a passenger car. In this study, a dynamic experiment for a spring and a damper of a passenger car is performed to analyze the nonlinear characteristics using MTS 1-axial testing machine and a mathematical nonlinear dynamic suspension model based on experimental data is devised to estimate the ride quality using Billings' method. The devised nonlinear model is applied to the ride quality analysis using K factor and the effect of suspension parameters is examined. As a result, the friction between the cylinder and the piston of a damper is the most effective parameter for the ride quality of a passenger car.

• 국제학술발표논문집
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• The 5th International Conference on Construction Engineering and Project Management
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• pp.513-516
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• 2013

Earthmoving equipment's haul-route has a great influence on the productivity of the earth work operation. Haul-route grade is a critical factor in selecting the haul-route. The route that has low grade resistance contributes to increase machine travel speed and production. This study presents a mathematical model called "Hauling-Unit Optimal Routes Selecting system" (HUORS). The system identifies optimal path that maximize the earth-work productivity. It consists of 3 modules, i.e., (1) Module 1 which inputs site characteristic data and computes site location and elevation using GIS(Geographical Information System); (2) Module 2 which calculates haul time; (3) Module 3 which displays an optimum haul-route by considering the haul-route's gradient resistances (i.e., from the departure to the destination) and hauling time. This paper presents the system prototype in detail. A case study is presented to demonstrate the system and verifies the validity of the model.

• 한국정밀공학회지
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• 제29권8호
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• pp.863-872
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• 2012

The squareness measurement of driving axes of a machine tool is very important to evaluate the performance of the machine. Laser interferometer measurement system is one of the most reliable equipment to measure the squareness. However, squareness measurement using laser system with an optical square result in restriction of straightness optics setup and Abbe's offset. This offset combines with angular errors during the motion of an axis to cause Abbe's error. In addition, the difficulty in optical square setup causes restriction of other optics and limitation of measurable range. In this paper, mathematical approaches are presented to eliminate the Abbe's error and to estimate squareness for full range by using the best fit of straightness data measured without an optical square. Experiments for squareness measurement of 3 axis machine tool were conducted and the proposed techniques were used for squareness evaluation with elimination of Abbe's error and squareness estimation for the full travel range.

• 산업경영시스템학회지
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• 제1권1호
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• pp.37-44
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• 1978

The purpose of this study is to search for an efficient application method in solving delay-phenomenon problems which influence upon total production cost through case study. The method of this study is an experimental study based on cutting time data in lead cutting operations from "Lead Cutting Machine (Stripper)" and its service rate data from a large electronic products company which utilizes conveyor line system for the products "Car Stereo" The procedure of this experimental study is as follows; 1) Using loading(Man-Hour) analysis technique j,1 order to analyse and evaluate Production capacity, efficiency, operation and idle rate assembly charge, waiting and service cost -when its are controlled by stripper operator(server) 2) Establishing adequate waiting time model of finite population caused by the interference of 4 stripper machine which is drawn from mathematical statistics testing, that is, goodness of fit test in the waiting and service rate and to search for optimal solution by utilizing the above mentioned model The experimental result was that amount to 8,546,618won Per year was brought down, that is, by optimum point, it shows a decrease as compared with Present point. The major limitation of this experimental study is that the Queue in the Finite Population, so to speak. it comes from the interference of 4 stripper machine dealt with this case were limited only on the Car Stereo conveyor line. Further study of application of this application method to the areas such as material handling, personnel management marketing and transportation management is strong1y recommended.trong1y recommended.

• Journal of Computing Science and Engineering
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• 제7권2호
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• pp.112-121
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• 2013

The last years have seen a rise of interest in using electroencephalography-based brain computer interfacing methodology for investigating non-medical questions, beyond the purpose of communication and control. One of these novel applications is to examine how signal quality is being processed neurally, which is of particular interest for industry, besides providing neuroscientific insights. As for most behavioral experiments in the neurosciences, the assessment of a given stimulus by a subject is required. Based on an EEG study on speech quality of phonemes, we will first discuss the information contained in the neural correlate of this judgement. Typically, this is done by analyzing the data along behavioral responses/labels. However, participants in such complex experiments often guess at the threshold of perception. This leads to labels that are only partly correct, and oftentimes random, which is a problematic scenario for using supervised learning. Therefore, we propose a novel supervised-unsupervised learning scheme, which aims to differentiate true labels from random ones in a data-driven way. We show that this approach provides a more crisp view of the brain states that experimenters are looking for, besides discovering additional brain states to which the classical analysis is blind.

• 산업공학
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• 제12권3호
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• pp.395-400
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• 1999

Shipbuilding process is composed of hull construction, in which the structural body of a ship is formed, and outfitting, in which all the non-structural parts such as pipes, derricks, engines, machinery, electrical cable, etc. are manufactured, added and assembled. Hull construction can be classified into parts fabrication, block assembly and hull erection. Among them, the parts fabrication is the first manufacturing stage that produces components or zones needed for block assembly and hull construction. More specifically, the parts fabrication is performed through machining processes including marking, cutting, pressing, and/or forming. When material is entering into the parts fabrication stage, it is important for achieving the total efficiency of production to select one of production division, so-called 'bay,' as well as machine tools on which the part is fabricated. In this paper, given production quantities of parts in the fabrication stage, the problem is to optimally select machine tools and production division, such that the total flow-time is minimized as well as the workload among machines is balanced. Specifically, three mathematical models for flow-time minimization, load balance, and simultaneously considering both objectives, and a numerical example are analyzed and presented.

• Journal of Electrical Engineering and Technology
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• 제9권2호
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• pp.523-531
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• 2014

Brushless Dual-Mechanical-Port Electrical Machine (BLDMPEM) is a new type of motor designed for Hybrid Electric Vehicle (HEV), which contains two mechanical ports and two electric ports. Compared with Dual-Mechanical-Port Electrical Machine (DMPEM), the brushless structure brings higher reliability and easier maintenance. In this paper, the model of BLDMPEM is discussed. In Chapter 2, the energy flow and mathematical model of BLDMPEM are analyzed. Then a novel three-phase half-bridge controlled rectifier topology and its control strategy for cruising mode of HEV based on BLDMPEM are proposed in Chapter 3. Compared with the Field Oriented Control (FOC) strategy of BLDMPEM, the proposed method does not require accurate motor parameters, and it is much simpler and easier to be implemented. At last, simulation and experiment results show the feasibility and validity of the proposed strategy.

• 전력전자학회논문지
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• 제27권5호
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• pp.425-430
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• 2022

A pumped storage power station is an important means to solve the problem of peak load regulation and ensures the safety of power grid operation. The doubly fed variable-speed pumped storage (DFVSPS) system adopts a doubly fed induction machine (DFIM) to replace the synchronous machine used in traditional pumped storage. The stator of DFIM is connected to the power grid, and the three-phase excitation windings are symmetrically distributed on the rotor. Excitation current is supplied by the converter. The active and reactive power of the unit can be quickly adjusted by adjusting the amplitude, frequency, and phase of the rotor-side voltage or current through the converter. Compared with a conventional pumped storage hydropower station (C-PSH), DFVSPS power stations have various operating modes and frequent start-up and shutdown. This study introduces the structure and principle of the DFVSPS unit. Mathematical models of the unit, including a model of DFIM, a model of the pump-turbine, and a model of the converter and its control, are established. Fast power control strategies are proposed for the unit model. A 300 MW model of the DFVSPS unit is established in MATLAB/Simulink, and the response characteristics in generating mode are examined.

• Asia pacific journal of information systems
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• 제30권1호
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• pp.31-52
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• 2020

Stock markets are popular investment avenues to people who plan to receive premium returns compared to other financial instruments, but they are highly volatile and risky due to the complex financial dynamics and poor understanding of the market forces involved in the price determination. A system that can forecast, predict the stock prices and automatically create a portfolio of top performing stocks is of great value to individual investors who do not have sufficient knowledge to understand the complex dynamics involved in evaluating and predicting stock prices. In this paper the authors propose a Stock prediction, Portfolio Generation and Selection model based on Machine learning algorithms, Artificial neural networks (ANNs) are used for stock price prediction, Mathematical and Statistical techniques are used for Portfolio generation and Un-Supervised Machine learning based on K-Means Clustering algorithms are used for Portfolio Evaluation and Selection which take in to account the Portfolio Return and Risk in to consideration. The model presented here is limited to predicting stock prices on a long term basis as the inputs to the model are based on fundamental attributes and intrinsic value of the stock. The results of this study are quite encouraging as the stock prediction models are able predict stock prices at least a financial quarter in advance with an accuracy of around 90 percent and the portfolio selection classifiers are giving returns in excess of average market returns.

• 한국멀티미디어학회논문지
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• 제20권8호
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• pp.1299-1311
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• 2017

Sounds based machine fault diagnosis recovers all the studies that aim to detect automatically faults or damages on machines using the sounds emitted by these machines. Conventional methods that use mathematical models have been found inaccurate because of the complexity of the industry machinery systems and the obvious existence of nonlinear factors such as noises. Therefore, any fault diagnosis issue can be treated as a pattern recognition problem. We present here an automatic fault diagnosis system of hand drills using discrete wavelet transform (DWT) and pattern recognition techniques such as principal component analysis (PCA) and artificial neural networks (ANN). The diagnosis system consists of three steps. Because of the presence of many noisy patterns in our signals, we first conduct a filtering analysis based on DWT. Second, the wavelet coefficients of the filtered signals are extracted as our features for the pattern recognition part. Third, PCA is performed over the wavelet coefficients in order to reduce the dimensionality of the feature vectors. Finally, the very first principal components are used as the inputs of an ANN based classifier to detect the wear on the drills. The results show that the proposed DWT-PCA-ANN method can be used for the sounds based automated diagnosis system.