• 제목/요약/키워드: Area Setup Method

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A Development of Fixture Planning Module using Machine Learning (기계 학습을 이용한 치구 공정 계획 모듈의 개발)

  • 김선우;이수홍
    • Korean Journal of Computational Design and Engineering
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    • v.2 no.2
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    • pp.111-121
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    • 1997
  • This study intends to develop a fixture planning module as a part of the planning system for cutting. The fixture module uses machine learning method to reuse previous failure results so that the system can reduce the repeated failures. Machine learning is one of efforts to incorporate human reasoning ability into a computerized system. A human expert designs better than a novice does because he has a wide experience in a specific area. This study implements the machine learning algorithm to have a wide experience in the fixture planning area as a human expert does. When the fixture planner finds a setup failure for the suggested operations by a process planner, it makes the process planner store its attributes and other information for the failed setup. Then the process planner applies the learned knowledge when it meets a similar case so that the planner can reduce possibility of setup failure. Also the system can teach a novice user by showing a failed setup with a modified setup.

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Location-based Area Setup Method and Optimization Technique for Deviation Detection (위치기반 영역 설정 방법 및 이탈 검출의 최적화 기법)

  • Choi, Jae-Hyun;Lim, Yang-Won;Lim, Han-Kyu
    • The Journal of the Korea Contents Association
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    • v.14 no.4
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    • pp.19-28
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    • 2014
  • Recent advancements in the IT industry have made daily life more convenient than ever before. In particular, studies have focused on the position detection of individuals using the GPS in smartphones, and this application has been utilized actively in emergency rescue organizations. However, existing methods send the location information of a user to a predetermined guardian set by the user or to a control center when the user enters into or deviates from a predetermined space. Such spaces are created by an arbitrary radius, thereby making it difficult to set a detailed area by using an existing radius-area creation method in an unstructured space and path with a specific road, such as for trekking, amusement parks, or mountaineering. This study proposes a novel method for setting up an area by connecting multiple radii to improve the existing radius-area creation method in order to easily set a detailed area in smart devices or on the Internet. In addition, an optimization method for resource use is proposed by comparing the operation results in which a user's location is detected by using the proposed location-based area setup method and deviation detection.

Five-Axis Machining with Three-Axis CNC Machine (3 축 CNC 를 이용한 5 축 자유곡면 가공)

  • Lee, Jung-Jae;Suh, Suk-Hwan
    • Journal of Korean Institute of Industrial Engineers
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    • v.21 no.2
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    • pp.217-237
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    • 1995
  • One of the most distinguished advantages of five-axis machining is that complex free surfaces(such as impeller) can be machined by one setup. Five-axis CNC machine, however, is very expensive so that its usage is restricted to a few large companies. As an economical approach to five-axis machining, this paper presents a method for machining the five-axis free surfaces(using ball-end mill) on a three-axis CNC machine with an index table. The method developed consists of: a) determining the minimum number of part setups and their interference-free and collision-free potential machining area, b) calculating actual machining area for each setup, and c) generating 3-axis cutter path for each part setup. The method has been successfully tested via computer simulations for several complex surfaces including impeller.

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Detection of PCB Components Using Deep Neural Nets (심층신경망을 이용한 PCB 부품의 검지 및 인식)

  • Cho, Tai-Hoon
    • Journal of the Semiconductor & Display Technology
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    • v.19 no.2
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    • pp.11-15
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    • 2020
  • In a typical initial setup of a PCB component inspection system, operators should manually input various information such as category, position, and inspection area for each component to be inspected, thus causing much inconvenience and longer setup time. Although there are many deep learning based object detectors, RetinaNet is regarded as one of best object detectors currently available. In this paper, a method using an extended RetinaNet is proposed that automatically detects its component category and position for each component mounted on PCBs from a high-resolution color input image. We extended the basic RetinaNet feature pyramid network by adding a feature pyramid layer having higher spatial resolution to the basic feature pyramid. It was demonstrated by experiments that the extended RetinaNet can detect successfully very small components that could be missed by the basic RetinaNet. Using the proposed method could enable automatic generation of inspection areas, thus considerably reducing the setup time of PCB component inspection systems.

Experimental Setup for Autonomous Navigation of Robotic Vehicle for University Campus (대학 캠퍼스용 로봇차량의 자율주행을 위한 실험환경 구축)

  • Cho, Sung Taek;Park, Young Jun;Jung, Seul
    • Journal of the Korean Institute of Intelligent Systems
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    • v.26 no.2
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    • pp.105-112
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    • 2016
  • This paper presents the experimental setup for autonomous navigation of a robotic vehicle for touring university campus. The robotic vehicle is developed for navigation of specific areas such as university campus or play parks. The robotic vehicle can carry two passengers to travel short distances. For the robotic vehicle to navigate autonomously the specific distance from the main gate to the administrative building in the university, the experimental setup for SLAM is presented. As an initial step, a simple method of following the line detected by a single camera is implemented for the partial area. The central line on the pavement colored with two kinds, red and yellow, is detected by image processing, and the robotic vehicle is commanded to follow the line. Experimental studies are conducted to demonstrate the performance of navigation as a possible touring vehicle.

Cluster Head Selection Protocol Using Modified Setup Phase (변형된 셋업 단계를 이용한 클러스터 헤드 선출 프로토콜)

  • Kim, Jin-Su;Choi, Seong-Yong;Han, Seung-Jin;Choi, Jun-Hyeog;Rim, Kee-Wook;Lee, Jung-Hyun
    • The Journal of the Korea Contents Association
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    • v.9 no.1
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    • pp.167-176
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    • 2009
  • Traditional cluster-based routing method is a representative method for increasing the energy efficiencies. In these cluster-based routing methods, the selected cluster head collect/aggregate the information and send the aggregated information to the base station. But they have to solve the unnecessary energy dissipation of frequent information exchange between the cluster head and whole member nodes in cluster. In this paper, we minimize the frequency of the information exchange for reducing the unnecessary transmit/receive frequencies as calculate the overlapped area or number of overlapped member nodes between the selected cluster head and previous cluster head in the setup phase. So, we propose the modified cluster selection protocol method that optimizes the energy dissipation in the setup phase and reuses the saved energy in the steady-state phase efficiently that prolongs the whole wireless sensor network lifetime by uniformly selecting the cluster head.

The Method to Setup the Path Loss Model by the Partial Interval Analysis in the Cellular Band

  • Park, Kyung-Tae;Bae, Sung-Hyuk
    • Journal of the Institute of Convergence Signal Processing
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    • v.14 no.2
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    • pp.105-109
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    • 2013
  • There are the free space model, the direct-path and ground reflected model, Egli model, Okumura-Hata model in the representative propagational models. The measured results at the area of PNG area were used as the experimental data in this paper. The new proposed partial interval analysis method is applied on the measured propagation data in the cellular band. The interval for the analysis is divided from the entire 30 Km distance to 5 Km, and next to 1 Km. The best-fit propagation models are chosen on all partial intervals. The means and standard deviations are calculated for the differences between the measured data and all partial interval models. By using the 5 Km- or 1 Km- partial interval analysis, the standard deviation between the measured data and the partial propagation models was improved more than 1.7 dB.

Bayesian test of homogenity in small areas: A discretization approach

  • Kim, Min Sup;Nandram, Balgobin;Kim, Dal Ho
    • Journal of the Korean Data and Information Science Society
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    • v.28 no.6
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    • pp.1547-1555
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    • 2017
  • This paper studies Bayesian test of homogeneity in contingency tables made by discretizing a continuous variable. Sometimes when we are considering events of interest in small area setup, we can think of discretization approaches about the continuous variable. If we properly discretize the continuous variable, we can find invisible relationships between areas (groups) and a continuous variable of interest. The proper discretization of the continuous variable can support the alternative hypothesis of the homogeneity test in contingency tables even if the null hypothesis was not rejected through k-sample tests involving one-way ANOVA. In other words, the proportions of variables with a particular level can vary from group to group by the discretization. If we discretize the the continuous variable, it can be treated as an analysis of the contingency table. In this case, the chi-squared test is the most commonly employed method. However, further discretization gives rise to more cells in the table. As a result, the count in the cells becomes smaller and the accuracy of the test becomes lower. To prevent this, we can consider the Bayesian approach and apply it to the setup of the homogeneity test.

Bayes tests of independence for contingency tables from small areas

  • Jo, Aejung;Kim, Dal Ho
    • Journal of the Korean Data and Information Science Society
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    • v.28 no.1
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    • pp.207-215
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    • 2017
  • In this paper we study pooling effects in Bayesian testing procedures of independence for contingency tables from small areas. In small area estimation setup, we typically use a hierarchical Bayesian model for borrowing strength across small areas. This techniques of borrowing strength in small area estimation is used to construct a Bayes test of independence for contingency tables from small areas. In specific, we consider the methods of direct or indirect pooling in multinomial models through Dirichlet priors. We use the Bayes factor (or equivalently the ratio of the marginal likelihoods) to construct the Bayes test, and the marginal density is obtained by integrating the joint density function over all parameters. The Bayes test is computed by performing a Monte Carlo integration based on the method proposed by Nandram and Kim (2002).

A Study on the Effect of the Difference at Design Pattern on the Characteristics of Observation (디자인유형의 차이가 주시특성에 끼치는 영향에 관한 연구)

  • Kim, Jong-Ha;Park, Sun-Myung
    • Korean Institute of Interior Design Journal
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    • v.22 no.1
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    • pp.174-182
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    • 2013
  • This study divided the observation area in an indoor space for area setup to analyse the effect of the difference of design types on the characteristics of observation with the observed time of each area as objects. Though it is thought that the difference of design patterns may be influenced by the factors and material composing the space, no existing approaches have had any quantitatively measuring method. Eye-tracking could be efficiently utilized for observation analysis from the viewpoint of dating observation behavior. The followings are the results of analysing the observation characteristics depending on design pattern. First, 5 observing areas were set up according to concentration of observation time in order for the concentration by area to be examined and the factors of design having effect on the difference of observation patterns by design type could be analysed. Second, as a whole, the observation of modern types showed high observation characteristics. When the difference of observation characteristics by pattern was examined by difference at observation frequency, the observation frequency defined to be more than 50% was seen to be almost same from Area I to III and to get higher from Area IV, and that defined to be 30% was high at Areas III and IV. In Area V, it was very high at natural. Third, that of Area II is no more than 8.2% but had the most observation time. As for observation characteristics, the horizontal observation of the central part was the highest and had more observation frequency at modern type that at natural one. These observation characteristics by area enabled to analyse the observation tendency depending on design characters at relevant area. Fourth, the design factors composing natural type were found to bring more attention when the area showed higher concentration at natural type than at modern one. And the analysis of design factors could make it to be confirmed that the quality of material and background factors in addition to design factors in the area had more effect on sight concentration.