• International Journal of Computer Science & Network Security
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• v.24 no.7
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• pp.108-117
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• 2024

The selection and recommendation of a suitable job applicant from the pool of thousands of applications are often daunting jobs for an employer. The recommendation and selection process significantly increases the workload of the concerned department of an employer. Thus, Resume Classification System using the Natural Language Processing (NLP) and Machine Learning (ML) techniques could automate this tedious process and ease the job of an employer. Moreover, the automation of this process can significantly expedite and transparent the applicants' selection process with mere human involvement. Nevertheless, various Machine Learning approaches have been proposed to develop Resume Classification Systems. However, this study presents an automated NLP and ML-based system that classifies the Resumes according to job categories with performance guarantees. This study employs various ML algorithms and NLP techniques to measure the accuracy of Resume Classification Systems and proposes a solution with better accuracy and reliability in different settings. To demonstrate the significance of NLP & ML techniques for processing & classification of Resumes, the extracted features were tested on nine machine learning models Support Vector Machine - SVM (Linear, SGD, SVC & NuSVC), Naïve Bayes (Bernoulli, Multinomial & Gaussian), K-Nearest Neighbor (KNN) and Logistic Regression (LR). The Term-Frequency Inverse Document (TF-IDF) feature representation scheme proven suitable for Resume Classification Task. The developed models were evaluated using F-Score_M, Recall_M, Precission_M, and overall Accuracy. The experimental results indicate that using the One-Vs-Rest-Classification strategy for this multi-class Resume Classification task, the SVM class of Machine Learning algorithms performed better on the study dataset with over 96% overall accuracy. The promising results suggest that NLP & ML techniques employed in this study could be used for the Resume Classification task.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.9
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• pp.189-196
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• 2020

Recently, GPU cloud computing technology applying GPU(Graphics Processing Unit) devices to virtual machines is widely used in the cloud environment. In a cloud environment, GPU devices assigned to virtual machines can perform operations faster than CPUs through massively parallel processing, which can provide many benefits when operating high-performance computing services in a variety of fields in a cloud environment. In a cloud environment, a GPU device can help improve the performance of a virtual machine, but the virtual machine scheduler, which is based on the CPU usage time of a virtual machine, does not take into account GPU device usage time, affecting the performance of other virtual machines. In this paper, we test and analyze the performance degradation of other virtual machines due to the virtual machine that performs GPGPU(General-Purpose computing on Graphics Processing Units) task in the direct path based GPU virtualization environment, which is often used when assigning GPUs to virtual machines in cloud environments. Then to solve this problem, we propose a GPGPU task management method for a virtual machine.

• Korean Management Science Review
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• v.30 no.3
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• pp.81-97
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• 2013

This paper considers a parallel-machine scheduling problem with dedicated and common processing machines. Non-identical setup and processing times are assumed for each machine. A genetic algorithm is proposed to minimize the makespan objective measure. In this paper, a lowerbound and some heuristic algorithms are derived and tested through computational experiments.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.04a
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• pp.340-345
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• 2001

In this paper, We have studied on the critical vibration limits of spindle unit for the high speed ball pen tip processing machine. The vibration of bearing can be measured by FFT, and the influence of vibration amplitude due to the Unbalance, bearing deflect, bite and timing belts tension are analyzed. So, the critical vibration limits of spindle is determined by the X, Z directional vibration of spindle Unit.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.16 no.28
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• pp.203-209
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• 1993

In Factory Automation environments such as FMS, the formation of machine-part based on GT should be considered. The purpose of this study is to develop a economic heuristic algorithm which considers various elements such as unit processing time, subcontract cost, and functional operation cost, machine processing capacity etc. When this proposed approach is applied to the real situation expected benefits are as follows: the reduction of production lead time work in process, labor force, tooling, rework and scrap, setup time, order time delivery, and paper work, etc.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.04a
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• pp.770-771
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• 2009

리눅스 커널을 VMM(Virtual Machine Monitor)로 만들어 주는 KVM의 메모리 관리 기법을 분석한다. Xen과의 차이점과 KVM의 구조를 알아보고 KVM에서의 메모리 관리 기법에 대해 분석하였다. 또한 CPU의 가상화 기능인 Intel VT-x가 어떻게 적용되었는지 분석한다.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.1
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• pp.65-73
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• 2015

This paper considers a parallel-machine scheduling problem with dedicated and common processing machines using GA (Genetic Algorithm). Non-identical setup times, processing times and order lot size are assumed for each machine. The GA is proposed to minimize the total-tardiness objective measure. In this paper, heuristic algorithms including EDD (Earliest Due-Date), SPT (Shortest Processing Time) and LPT (Longest Processing Time) are compared with GA. The effectiveness and suitability of the GA are derived and tested through computational experiments.

• Design & Manufacturing
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• v.10 no.2
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• pp.1-5
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• 2016

High-speed and high-torque performance is required in the ultra-high speed electric injection molding machine field. To implement this performance, the big-size inverter is needed and the corresponding converter should be used. In this case, the whole cost for configuring the system will be increased. In this paper, we introduce a method which is able to reduce the energy and the cost for configuring the system using the energy regeneration. The energy regeneration method is based on reusing the regeneration power generated at the electric motor during decelerating the injection motion. In this paper, we demonstrate the effectiveness of the method by using the ultra-high speed injection motion.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.138-140
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• 2004

In this study, we develop a remocon inspection automatic system using machine vision technique. By our proposed inspection system, the inspection accuracy and processing time was considerably improved.

• Proceedings of the Korean Nuclear Society Conference
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• 2005.05a
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• pp.1293-1294
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• 2005