• Journal of Information Processing Systems
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• v.8 no.4
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• pp.555-566
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• 2012

The cloud environment makes it possible to analyze large data sets in a scalable computing infrastructure. In the bioinformatics field, the applications are composed of the complex workflow tasks, which require huge data storage as well as a computing-intensive parallel workload. Many approaches have been introduced in distributed solutions. However, they focus on static resource provisioning with a batch-processing scheme in a local computing farm and data storage. In the case of a large-scale workflow system, it is inevitable and valuable to outsource the entire or a part of their tasks to public clouds for reducing resource costs. The problems, however, occurred at the transfer time for huge dataset as well as there being an unbalanced completion time of different problem sizes. In this paper, we propose an adaptive resource-provisioning scheme that includes run-time data distribution and collection services for hiding the data transfer time. The proposed adaptive resource-provisioning scheme optimizes the allocation ratio of computing elements to the different datasets in order to minimize the total makespan under resource constraints. We conducted the experiments with a well-known sequence alignment algorithm and the results showed that the proposed scheme is efficient for the cloud environment.

• Proceedings of the Korean Society for Quality Management Conference
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• 1998.11a
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• pp.295-300
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• 1998

Recently graphical modelling is being studied as a useful process analysis tool for exploratory causal analysis. Graphical modelling is a presentation method that uses graphs to describe statistical models of the structures of multivariate data. This paper describes an application of this graphical modeling with two cases from the automotive parts industry. One case is the unbalance problem of the pulley, an automotive generator part. There is multivariate data of the product from each of the processes which are connected in the series. By means of exploratory causal analysis between the variables using graphical modeling, the key processes which causes the variation of the final characteristics and their mechanism of the causal relationship have become clear. Another case is, also, the unbalanced problem of automotive starter parts which consists of many parts and is manufactured by complex machinery and assembling process. By means of the similar technique, the key processes are obtained easily and the results are reasonable from technical knowledge.

• Journal of the Korean Home Economics Association
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• v.35 no.1
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• pp.1-14
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• 1997

The purpose of this study is to investigate time use of married female clerical workers and their husbands. Data for 143 couples were gathered from using structured questioinaire and time dairy. The analysis of time use data was carried out two approaches. They are the amount of time spent and the distribution of time for dailly activities. And also the couples' perceptions how restricted their long time labor to their family life was analyzed. The results were shown as follows: (1) Married female clerical workers and their husbands have long labor time and their physiological and leisure time is too short. This means the patterns of their time use are very unbalanced type. (2) Wives worked longer than husbands on total labor with a large sexual difference in household works.(3) Couples perceived that wives' work more negative affection on their family life than husbands' work.

• The Korean Journal of Applied Statistics
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• v.17 no.1
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• pp.145-151
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• 2004

PROC MIXED fits a variety of mixed models to data and enables one to use these fitted models to make statistical inferences about the data. However, the simulation study in this article shows that PROC MIXED using REML estimators provides one with a confidence interval, that does not keep the stated confidence coefficients, on sums of two variance components in the simple regression model with unbalanced nested error structure which is a mixed model.

• Proceedings of the KIEE Conference
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• 2004.04a
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• pp.290-292
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• 2004

Tilting train has been developed to increase the operational speed of the trains on conventional lines which have many curves. This train are tilted at curves to compensate for unbalanced carbody centrifugal acceleration to a greater extent than compensation produced by the track cant, so that passengers do not feel centrifugal acceleration and thus trains can run at higher speed at curves. This paper developed PDM(product data management) to make a system engineering of TTX(tilting train express) with maximum operation speed 180 km/h.

• Proceedings of the KIPE Conference
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• 2001.07a
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• pp.377-380
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• 2001

The vestibular system located in the inner ear controls reflex body posture and movement. It has the semicircular canals sensing an angular acceleration and the otolith organs sensing a linear acceleration. With this organic signal, medical doctor decide if a person has disease or not. To obtain this data, a precision stimular system is considered. Robust control is needed to obtain eye signals induced by off-vertical axis rotation because of an unbalanced load produced by tilting the axis of the system upto 30 degrees. In this study, off-vertical axis rotatory system with visual stimulation system are developed. This system is consisted of head mounted display for generating horizontal, vertical, and three dimensional stimulus patterns. Furthermore wireless recording system using RF modem is considered for noiseless data transmission.

• Journal of the Korea Society of Computer and Information
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• v.12 no.3
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• pp.51-58
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• 2007

The shared-nothing multiprocessor architecture has advantages in scalability, this architecture has been adopted in many multiprocessor database system. But, if the data are not uniformly distributed across the processors, load will be unbalanced. Therefore, the whole system performance will deteriorate. This is the data skew problem, which usually occurs in processing parallel hash join. Balancing the load before performing join will resolve this problem efficiently and the whole system performance can be improved. In this paper, we will present an algorithm using merit of very large memory to reduce disk access overhead in performing load balancing and to efficiently solve the data skew problem. Also, we will present analytical model of our new algorithm and present the result of some performance study we made comparing our algorithm with the other algorithms in handling data skew.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.69-77
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• 2021

The objective of this research is to explore the inconclusive theoretical and empirical association between institutional ownership and firm performance in the context of emerging Pakistani economy. The data set consists of all the non-financial firms listed on the Pakistan Stock Exchange (PSX). Annual data set covers the period ranging from 2010 to 2015. However, the econometric analysis does not include those firms with incomplete data. Thus the final data set comprised of an unbalanced panel of sample of 276 firms with 1231 firms years observations. Data related to the institutional ownership and other variables taken for the study were extracted through the annual financial reports of the firms. The research used Tobin's Q as a proxy of market measure of firm performance and tested the endogenous relation with institutional ownership through OLS and 2SLS approach. The study also applied Durbin-Wu-Hausman test to determine the endogeneity before analyzing the 2SLS model. The Durbin-Wu-Hausman Test (DWH) conform the endogenous link between institutional ownership and performance and vice versa. The results derived from 2SLS also confirm a highly significant relationship and two way direct proportional relationships between the institutional investment and corporate performance in the studied companies.

• International Journal of Advanced Culture Technology
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• v.10 no.4
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• pp.499-510
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• 2022

This study examines the reporting factors of crime against business in Korea and proposes a corresponding predictive model using machine learning. While many previous studies focused on the individual factors of theft victims, there is a lack of evidence on the reporting factors of crime against a business that serves the public good as opposed to those that protect private property. Therefore, we proposed a crime prevention model for the willingness factor of theft reporting in businesses. This study used data collected through the 2015 Commercial Crime Damage Survey conducted by the Korea Institute for Criminal Policy. It analyzed data from 834 businesses that had experienced theft during a 2016 crime investigation. The data showed a problem with unbalanced classes. To solve this problem, we jointly applied the Synthetic Minority Over Sampling Technique and the Tomek link techniques to the training data. Two prediction models were implemented. One was a statistical model using logistic regression and elastic net. The other involved a support vector machine model, tree-based machine learning models (e.g., random forest, extreme gradient boosting), and a stacking model. As a result, the features of theft price, invasion, and remedy, which are known to have significant effects on reporting theft offences, can be predicted as determinants of such offences in companies. Finally, we verified and compared the proposed predictive models using several popular metrics. Based on our evaluation of the importance of the features used in each model, we suggest a more accurate criterion for predicting var.

• Proceedings of the Korean Vacuum Society Conference
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• 2015.08a
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• pp.231.1-231.1
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• 2015

Surface energy, being an important material parameter to control its interactions with the other surfaces plays a key role in bio-related application. Carbon films are found very promising due to their characteristics such as wear and corrosion resistant, high hardness, inert, low resistivity and biocompatibility. The present work deals with the deposition of carbon films using unbalanced facing target magnetron sputtering technique. The discharge characteristics were studied using optical emission spectroscopy and correlated with the film properties. Surface energy was investigated through contact angle measurement. The ID/IG ratio as calculated from Raman spectroscopy data increases with the increase in power density due to the higher number of sp2 clusters embedded in the amorphous matrix. The deposited films were smooth and homogeneous as observed by Atomic force microscopy having RMS roughness in the range of 1.74 to 2.25 nm. It is observed that electrical resistivity and surface energy varies in direct proportionality with operating pressure and has inverse relation with power density. The surface energy results clearly exhibited that these films can have promising applications in cell cultivation.