• 한국공작기계학회논문집
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• 제16권5호
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• pp.101-107
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• 2007

Assembly is mentioned as important process saving time and cost where we produce the machine with many parts relationships. In this study, parts assembly relationship is analysed for assembly information of micro milling machine which have been developing for research. Liaison diagram, datum flow chain and assembly tree are applied to discuss assembly characteristics of micro milling machine model. We can find out the characteristics of micro machine assembly and discuss about facility of assembly. Some analysis in this paper about micro milling machine will give a useful tools for assembly. We knew that the predicted results from analysis in this study are alignment and clearance among the parts. The 3D model of micro machine which is studied in this paper is not a complete model. Main parts of a micro milling machine are used and presented.

• 펄프종이기술
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• 제34권5호
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• pp.86-92
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• 2002

The benefits of high performance retention systems have been long recognized by the paper maker. The inter-relation between chemical retention and drainage and their effect on paper production efficiency and paper quality is significant. The subject of this paper is a summary of recent studies comparing three microparticle programs made under highly controlled pilot and commercial paper machine conditions. The results presented in this paper suggest that, in addition to improvements in machine operation, the retention, drainage and formation program can have a marked influence on the paper quality. Improvement of the topographical characteristics of the base paper was observed when the microparticle was a colloidal borosilicate inorganic oxide.

• 현장농수산연구지
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• 제11권1호
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• pp.79-94
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• 2009

본 연구는 우리나라 식용포도 재배농가의 보호봉지 결속작업이 주로 고령의 부녀자에 의존하고 있어 향후 이들 노동력을 대체하기 위하여 기계적인 포도보호봉지 결속장치를 개발하여 생산비를 절감하고자 얻어진 결과 는 다음과 같다. 1. 포도 보호봉지 및 포장봉지 결속기 개발 가. 자동결속기 설계는 CATIA V12/AUTOCAD 2000으로 하였다. 나. 자동결속기는 포도보호봉지를 기계적으로 묶어주는 장치로 소형, 경량이어야 하며 작업 시간, 노동량을 줄어 젊은층에서부터 고령자까지 작업할 수 있도록 설계하였다. 다. 자동결속기의 총 무게는 350g이하 초경량으로 제작될 수 있도록 하였다. 라. 결속성공률은 99%이상이 되도록 하였다. 마. 자동결속기의 결속롤과 커터, 배터리, 모터 등의 구조를 스테플러와 같은 가트리지형태로 개발하였다. 바. 카트리지 핀은 C-ring 28mm형으로써 길이는 500mm정도로 포도보호봉지 및 제과·제빵포장봉지를 결속할 수 있도록 제작하였다. 사. 작업시 포도나무 포도넝쿨 등 장애물의 영향을 받지 않도록 디자인을 설계, 제작하였다. 2. 포도보호봉지 결속작업시스템 포장실증시험 가. 자동결속기 시작기를 이용한 포도 보호 봉지결속으로 시기별 과병장, 과식품질이 무처리에 비하여 현저히 높았다. 나. 포도보호봉지 결속작업은 숙련자의 경우 1일 3,000개내외 씌우는 반면 초보자는 1,200개(37%)정도로 크게 떨어졌다. 다. 포도 보호봉지 자동결속기를 이용한 작업효율성은 102%로써 숙련자의 노동력을 대체할 수 있을 것으로 판단되었다. ∘ 1단계 : 232.5%(앞치마에서 보호봉지를 꺼내어 포도에 씌움) ∘ 2단계 : 60.7%(씌운 보호봉지 주름을 잡음) ∘ 3단계 : 104.7%(주름이 잡힌 상태에서 결속) ∘ 4단계 : 102% 라. 포도 보호봉지 결속부위의 둘레(크기)를 조사한 바 관행보호봉지결속작업(수작업)에서는 손으로 철사핀을 감기 때문에 평균 4.6cm이었으며 자동결속기의 결속롤(핀)은 5.3cm가 되어 다소 줄이는 것이 정밀성이 높을 것으로 판단되었다. 마. 수확시 과실 품질(과중, 과방크기-과장, 과폭, 가용성고형물, 산함량)을 조사한 결과 처리한 차이가 인정되지 않았다. 바. 자동결속기를 이용한 포도보호봉지 결속작업처리에서 포도의 열과(터진포도)와 이병율 차이에는 관행방법과 차이가 없었다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 하계종합학술대회 논문집(3)
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• pp.193-196
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• 2002

Nowadays, many users use internet and many set-top box needs browser for Internet. so we need to develop a Java Virtual Machine to improve browser's performance. This paper has been studied a Java Virtual Machine based on Real-Time 05 Vxwroks. Java Virtual Machine handles Java byte-code quickly in Browser So, this paper has designed module and interfaces for Embedded Browser and Implemented them.

• Nuclear Engineering and Technology
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• 제52권7호
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• pp.1436-1442
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• 2020

Nuclear infrastructure systems play an important role in national security. The functions and missions of nuclear infrastructure systems are vital to government, businesses, society and citizen's lives. It is crucial to design nuclear infrastructure for scalability, reliability and robustness. To do this, we can use machine learning, which is a state of the art technology used in various fields ranging from voice recognition, Internet of Things (IoT) device management and autonomous vehicles. In this paper, we propose to design and develop a machine learning algorithm to perform predictive maintenance of nuclear infrastructure. Support vector machine and logistic regression algorithms will be used to perform the prediction. These machine learning techniques have been used to explore and compare rare events that could occur in nuclear infrastructure. As per our literature review, support vector machines provide better performance metrics. In this paper, we have performed parameter optimization for both algorithms mentioned. Existing research has been done in conditions with a great volume of data, but this paper presents a novel approach to correlate nuclear infrastructure data samples where the density of probability is very low. This paper also identifies the respective motivations and distinguishes between benefits and drawbacks of the selected machine learning algorithms.

• Industrial Engineering and Management Systems
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• 제15권1호
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• pp.32-40
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• 2016

This paper considers a special case of a three machine flow shop scheduling problem in which operation processing time of each job is ordered such that machine 1 has the longest processing time, whereas machine 3, the shortest processing time. The objective of the problem is the minimization of the total completion time. Although the problem is simple, its complexity is yet to be established to our best knowledge. This paper first introduces the problem and presents some optimal properties of the problem. Then, it establishes several special cases in which a polynomial-time optimal solution procedure can be found. In addition, the paper proves that the recognition version of the problem is at least binary NP-complete. The complexity of the problem has been open despite its simple structure and this paper finally establishes its complexity. Finally, a simple and intuitive heuristic is developed and the tight worst case bound on relative error of 6/5 is established.

• 한국항행학회논문지
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• 제18권1호
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• pp.74-77
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• 2014

본 논문은 사물 지능 통신 환경에서 미디어 다중 채널을 위한 오류 제어에 대해서 제안하였다. 이 시스템은 사물 지능 통신 환경 멀티미디어 컴퓨터 협력 작업을 위한 소프트웨어 복구에 적합하다. 이것은 세션의 진행 과정 중 세션의 미디어 서비스 인스턴스가 비정상적으로 종료되는 경우에 세션의 진행을 중단할 수 있지만 허용하는 한 미디어 서비스 인스턴스를 재 활성화 시켜 사용자에 대한 보호를 하는 경우에 필요하다. 본 논문은 규칙-기반 DEVS 모델링과 시뮬레이션 기법을 사용하면서 사물 지능 통신 기반 컴퓨팅 공동 환경의 오류 복구 시스템의 성능 분석을 설명한다.

• 한국정밀공학회지
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• 제23권10호
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• pp.113-120
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• 2006

A cam profile CNC grinding machine is developed for manufacture of high precision contoured cams. The developed machine is composed of the high precision spindle using boll bearings, the high stiffness box layer type bed and the three axis CNC controller with the high resolution AC servo motor. In this paper, structural and modal analysis for the developed machine is carried out to check the design criteria of the machine. The analysis is carried out by FEM simulation using the commercial software, CATIA V5. The machine is modeled by placing proper shell and solid finite elements. And also, this paper presents the measurement system and experimental investigation on the modal analysis of a grinding machine. The weak part of the machine is found by the experimental evaluation. The results provide structure modification data for good dynamic behaviors. And safety of the machine was confirmed by the modal analysis of modified machine design. Finally, the cam profile grinding machine was successfully developed.

• International Journal of Advanced Culture Technology
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• 제8권2호
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• pp.297-304
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• 2020

Recently, open source automatic machine learning solutions have been applied in many fields. To apply open source automated machine learning to real world problems, you need to write code with expertise in machine learning. Writing code without machine learning knowledge is challenging. To solve this problem, the automatic machine learning solutions provided by startups are made easy to use with a clean user interface. In this paper, we review automatic machine learning solutions of startups.

• International Journal of Computer Science & Network Security
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• 제23권8호
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• pp.190-198
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• 2023

To enhance customer satisfaction for higher profits, an e-commerce sector can establish a continuous relationship and acquire new customers. Utilize machine-learning models to analyse their customer's behavioural evidence to produce their competitive advantage to the e-commerce platform by helping to improve overall satisfaction. These models will forecast customers who will churn and churn causes. Forecasts are used to build unique business strategies and services offers. This work is intended to develop a machine-learning model that can accurately forecast retainable customers of the entire e-commerce customer data. Developing predictive models classifying different imbalanced data effectively is a major challenge in collected data and machine learning algorithms. Build a machine learning model for solving class imbalance and forecast customers. The satisfaction accuracy is used for this research as evaluation metrics. This paper aims to enable to evaluate the use of different machine learning models utilized to forecast satisfaction. For this research paper are selected three analytical methods come from various classifications of learning. Classifier Selection, the efficiency of various classifiers like Random Forest, Logistic Regression, SVM, and Gradient Boosting Algorithm. Models have been used for a dataset of 8000 records of e-commerce websites and apps. Results indicate the best accuracy in determining satisfaction class with both gradient-boosting algorithm classifications. The results showed maximum accuracy compared to other algorithms, including Gradient Boosting Algorithm, Support Vector Machine Algorithm, Random Forest Algorithm, and logistic regression Algorithm. The best model developed for this paper to forecast satisfaction customers and accuracy achieve 88 %.