• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1995년도 추계학술대회 논문집
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• pp.1022-1027
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• 1995

We present a framework of an intelligent design support system for embodiment design of machine tools which can support efficiently and systematically the machine design by utilizing design knowledge such as objects(part), know-how, public, evaluation, and procedures. The design knowledge of machining center has been accumulated through interview with design experts of machine tool companies. The processes of embodiment design of machining center are established. We also introduce a hybrid knowledge representation so that the systm can easily deal with various and complicated design knowledge. The intelligent design system is being developed on the basis of object-oriented programming, and all parts of a design object, machining center, are also classified by the object-oriented modeling. For the demonstration of effectiveness of the suggested system, a structural design system for machine tools is implemented.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2006년도 추계학술대회 논문집
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• pp.315-316
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• 2006

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 하계학술대회 논문집 A
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• pp.406-408
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• 1996

This paper describes the BLDC motor which is applicated for a top front loading domestic washing machine. This motor is adopted direct drive washing machine without gear-belt-pulley system. Because gear box is removed, machine volume and noise are reduced. Moreover mechanical troubles in gear box are removed. Realization of variable speed region through of PWM control and high speed is able to efficient washing and spinning.

• 한국정밀공학회지
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• 제28권8호
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• pp.878-885
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• 2011

A kinematically-hybrid 5-axis machine tool is analyzed from the perspective of machine tool design. Its kinematic characteristics are pointed out, which should be considered during the conceptual design process. A result of the structural analysis of the machine is presented, which is performed during the detailed design process. It is also presented how we improve the thermal characteristics of the machine tool by changing the installation position of the actuators.

• International Journal of Computer Science & Network Security
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• 제24권7호
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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.

• 한국산업융합학회 논문집
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• 제27권2_2호
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• pp.415-424
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• 2024

This study analyzes trends and characteristics of the machine tool remanufacturing industry and proposes a standard process that considers environmental impact assessment during the remanufacturing process. First, trends in remanufacturing and environmental regulations are reviewed. And the current status of the machine tool remanufacturing industry and cases of national R&D projects related to machine tools are analyzed. Machine tool remanufacturing has a high resource saving effect, and remanufacturing is carried out as a finished product rather than as a part. And the scope of remanufacturing work is very wide due to the performance improvement of the machine and the addition of features. In order for the machine tool remanufacturing industry to be competitive, it is necessary to create products with high added value. In addition, in order to respond to international environmental regulations, it is necessary to secure related data by conducting an environmental impact assessment together during remanufacturing.

• Journal of Magnetics
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• 제22권1호
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• pp.69-77
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• 2017

To empower safe, economical and eco-friendly sustainable solution for enhancing oil and gas productivity from deep water reservoirs, new downhole technologies are recommended. Since electric machine plays leading role in the downhole application, it is a squeezing requirement for researchers to design and develop advanced electric machine. The Recent improvement in technology and uses of high-temperature magnets, permanent magnet flux switching machine (PMFSM) has become one of the appropriate contenders for offshore drilling but fewer designed for downhole due to ambient temperature. Therefore this comprehensive study deals with the design optimization and performance analysis of outer rotor PMFSM for the downhole application. Preliminary, the basic design parameters needed for machine design are calculated mathematically. Then the design refinement technique is implemented through deterministic method. Finally, initial and optimized performance of the machine is compared and as a result the output torque is increase from 16.39 Nm to 33.57 Nm while diminishing the cogging torque and PM weight up to 1.77 Nm and 0.79 kg, respectively. Therefore, it is concluded that purposed optimized design is suitable for the downhole application.

• 한국분말야금학회:학술대회논문집
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• 한국분말야금학회 2006년도 Extended Abstracts of 2006 POWDER METALLURGY World Congress Part2
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• pp.953-954
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• 2006

Ti-Cu-Ni-Sn quaternary amorphous alloys of $Ti_{50}Cu_{32}Ni_{15}Sn_3$, $Ti_{50}Cu_{25}Ni_{20}Sn_5$, and $Ti_{50}Cu_{23}Ni_{20}Sn_7$ composition were prepared by mechanical alloying in a planetary high-energy ball-mill (AGO-2). The amorphization of all three alloys was found to set in after milling at 300rpm speed for 2h. A complete amorphization was observed for $Ti_{50}Cu_{32}Ni_{15}Sn_3$ and $Ti_{50}Cu_{25}Ni_{20}Sn_5$ after 30h and 20h of milling, respectively. Differential scanning calorimetry analyses revealed that the thermal stability increased in the order of $Ti_{50}Cu_{32}Ni_{15}Sn_3$, $Ti_{50}Cu_{25}Ni_{20}Sn_5$, and $Ti_{50}Cu_{23}Ni_{20}Sn_7$.

• 한국분말재료학회지
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• 제17권1호
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• pp.7-12
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• 2010

In this work, effect of various process-control agents (PCAs) on the mechanical alloying of amorphous alloy of $Al_{85}Y_8Ni_5Co_2$ has been investigated. The dependence of the particle shape, size and crystallization behavior of the amorphous alloy powders on the type of PCAs and their concentrations was investigated by using X-ray diffraction, field-emission scanning electron microscopy and differential scanning calorimetry. It was found that the additive of toluene could affect positively the amorphization and thermally induced crystallization processes, as well as the size refinement, morphology and particle-size distribution of as-milled powders in comparison with alloy obtained without PCA.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2006년도 추계학술대회 논문집
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• pp.145-146
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• 2006