• 제목/요약/키워드: Class number

검색결과 2,047건 처리시간 0.029초

시계열 분석을 통한 보육교사 수급 전망 (Forecasting Demand of Childcare Teachers using Time Series Analysis)

  • 이미화;박진아;강은진
    • 한국보육지원학회지
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    • 제12권6호
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    • pp.123-137
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    • 2016
  • The purpose of this study was to forecast demand of childcare teachers based ion four different scenarios. In order to, the demand for childcare teachers from 2015 to 2024 were forecasted using time series techniques with data on the number of childcare teachers from 2003 to 2014. Results were as followings. Firstly, the demand for childcare teachers was expected to increase until 2019, but after 2020 steadily decreased in terms of scenario 1(child teacher ratio regulation). According to scenario 2(child teacher ratio based on 17 cities and provinces), the demand for childcare teachers was expected to need 440 teachers more until 2016. Then, according to scenario 3(two teachers each class), Scenario 4-1(one teacher and one staff each 2 toddler class and 3 older class) and scenario 4-2(one teacher and one staff each class), the demand of childcare teachers and staffs were estimated. These results implicated that childcare teachers and staffs supply policy would be established according to forecast demand.

Performance and parameter region for real time use in IEEE 802.4 token bus network

  • Park, Hong-Seong;Kim, Deok-Woo;Kwon, Wook-Hyun
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 22-24 Oct. 1991
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    • pp.1805-1810
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    • 1991
  • This paper derives the upper and the lower bound of the mean cycle time and the mean service time of the class 6 and the class 4, within which the minimum utilization constrain of the class 4 is guaranteed. Also, derived are conditions under which the token bus network is stable or unstable. These bounds and stable conditions are represented in terms of the high priority token hold time, the token rotation time and the arrival rate and the total station number etc. This paper suggest a parameter tuning algorithm in a partially symmetric token bus network with two classes, which maximizes the token rotation time for a suitable high priority token hold time and at the same time meets the stability condition of the network, the real time constraint and the minimum utilization constraint of the class 4.

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잠재계층분석기법(Latent Class Analysis)을 활용한 영화 소비자 세분화에 관한 연구 (Segmentation of Movie Consumption : An Application of Latent Class Analysis to Korean Film Industry)

  • 구교령;이장혁
    • 한국경영과학회지
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    • 제36권4호
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    • pp.161-184
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    • 2011
  • As movie demands become more and more diversified, it is necessary for movie related firms to segment a whole heterogeneous market into a number of small homogeneous markets in order to identify the specific needs of consumer groups. Relevant market segmentation helps them to develop valuable offer to target segments through effective marketing planning. In this article, we introduce various segmentation methods and compare their advantages and disadvantages. In particular, we analyze "2009~2010 consumer survey data of Korean Film Industry" by using Latent Class Analysis(LCA), a statistical segmentation method which identifies exclusive set of latent classes based on consumers' responses to an observed categorical and numerical variables. It is applied PROC LCA, a new SAS procedure for conducting LCA and finally get the result of 11 distinctive clusters showing unique characteristics on their buying behaviors.

MMPP,M/G/1 retrial queue with two classes of customers

  • Han, Dong-Hwan;Lee, Yong-Wan
    • 대한수학회논문집
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    • 제11권2호
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    • pp.481-493
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    • 1996
  • We consider a retrial queue with two classes of customers where arrivals of class 1(resp. class 2) customers are MMPP and Poisson process, respectively. In the case taht arriving customers are blocked due to the channel being busy, the class 1 customers are queued in priority group and are served as soon as the channel is free, whereas the class 2 customers enter the retrial group in order to try service again after a random amount of time. We consider the following retrial rate control policy, which reduces their retrial rate as more customers join the retrial group; their retrial times are inversely proportional to the number of customers in the retrial group. We find the joint generating function of the numbers of custormers in the two groups by the supplementary variable method.

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Electromagnetic design of 10 MW class superconducting wind turbine using 2G HTS wire

  • Kim, J.H.;Kim, H.M.
    • 한국초전도ㆍ저온공학회논문지
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    • 제15권3호
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    • pp.29-34
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    • 2013
  • This paper introduces design processes of 10 MW class superconducting generator for wind Turbine. Superconducting generator can produce 5 times stronger magnetic field than permanent magnet at least, which enables large scale wind turbine to function as a lighter, smaller and more highly efficient system. These processes are targeted for higher efficiency and shorter high temperature superconductor (HTS) wires to fabricate 10 MW class superconducting generator. Three different approaches will be described in these design processes. First design process focuses on the number of rotor poles. Secondly, 270 and 360 A operating current of superconducting field coil can be adapted as a design parameter in this process. Lastly, 3 and 6 kV line to line voltage of stator coil will be used to design 10 MW class superconducting generator.

국제 선급의 선박 품질등급화 최근동향: 차음성능 (Recent trends of classification of ships by shipping class:)

  • 강현주;김재승;김봉기
    • 한국마린엔지니어링학회:학술대회논문집
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    • 한국마린엔지니어링학회 2002년도 춘계학술대회논문집
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    • pp.209-212
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    • 2002
  • This article introduce Comfort Class V released by Dnv The Class has an objective of classifying ships by noise and vibration levees. It is apparent that noise criteria listed in the Class can not be satisfied without special efforts to enhance sound insulation performance in cabins. Accordingly, panel makers should develope panels which have very high sound insulation performance enough to satisfy the criteria. Also, due to large difference of sound insulation performance between cabin and laboratory, it is necessary that ship yards should improve the method for installing cabins.

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미적분학 수업에 그룹게임을 적용한 협동학습 사례 (A Case Study of Cooperative Learning: Applying Group Game to Calculus Class)

  • 조영;김미라
    • 공학교육연구
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    • 제24권4호
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    • pp.41-51
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    • 2021
  • This paper is to study whether cooperative learning applying group games becomes a teaching method that can increase interest and participation in class in calculus and the effect of the number of students. To increase interest and participation in class, the researcher conducted cooperative learning by applying smartphones and various game tools to group games. The consequences of the study confirmed that students' interest and participation in the class increased regardless of their mathematics basics. Therefore, it is expected that the calculus which is difficult for students to understand will be more easily approached by cooperative learning applying group games in the future.

The classified method for overlapping data

  • Kruatrachue, Boontee;Warunsin, Kulwarun;Siriboon, Kritawan
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2004년도 ICCAS
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    • pp.2037-2040
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    • 2004
  • In this paper we introduce a new prototype based classifiers for overlapping data, where training pattern can be overlap on the feature space. The proposed classifier is based on the prototype from neural network classifier (NNC)[1] for overlap data. The method automatically chooses the initial center and two radiuses for each class. The center is used as a mean representative of training data for each class. The unclassified pattern is classified by measure distance from the class center. If the distance is in the lower (shorter radius) the unknown pattern has the high percentage of being in this class. If the distance is between the lower and upper (further radius), the pattern has the probability of being in this class or others. But if the distance is outside the upper, the pattern is not in this class. We borrow the words upper and lower from the rough set to represent the region of certainty [3]. The training algorithm to find number of cluster and their parameters (center, lower, upper) is presented. The clustering result is tested using patterns from Thai handwritten letter and the clustering result is very similar to human eyes clustering.

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Delay-Margin based Traffic Engineering for MPLS-DiffServ Networks

  • Ashour, Mohamed;Le-Ngoc, Tho
    • Journal of Communications and Networks
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    • 제10권3호
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    • pp.351-361
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    • 2008
  • This paper presents a delay-margin based traffic engineering (TE) approach to provide end-to-end quality of service (QoS) in multi-protocol label switching (MPLS) networks using differentiated services (DiffServ) at the link level. The TE, including delay, class, and route assignments, is formulated as a nonlinear optimization problem reflecting the inter-class and inter-link dependency introduced by DiffServ and end-to-end QoS requirements. Three algorithms are used to provide a solution to the problem: The first two, centralized offline route configuration and link-class delay assignment, operate in the convex areas of the feasible region to consecutively reduce the objective function using a per-link per-class decomposition of the objective function gradient. The third one is a heuristic that promotes/demotes connections at different links in order to deal with concave areas that may be produced by a trunk route usage of more than one class on a given link. Approximations of the three algorithms suitable for on-line distributed TE operation are also derived. Simulation is used to show that proposed approach can increase the number of users while maintaining end-to-end QoS requirements.

Noisy label based discriminative least squares regression and its kernel extension for object identification

  • Liu, Zhonghua;Liu, Gang;Pu, Jiexin;Liu, Shigang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제11권5호
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    • pp.2523-2538
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    • 2017
  • In most of the existing literature, the definition of the class label has the following characteristics. First, the class label of the samples from the same object has an absolutely fixed value. Second, the difference between class labels of the samples from different objects should be maximized. However, the appearance of a face varies greatly due to the variations of the illumination, pose, and expression. Therefore, the previous definition of class label is not quite reasonable. Inspired by discriminative least squares regression algorithm (DLSR), a noisy label based discriminative least squares regression algorithm (NLDLSR) is presented in this paper. In our algorithm, the maximization difference between the class labels of the samples from different objects should be satisfied. Meanwhile, the class label of the different samples from the same object is allowed to have small difference, which is consistent with the fact that the different samples from the same object have some differences. In addition, the proposed NLDLSR is expanded to the kernel space, and we further propose a novel kernel noisy label based discriminative least squares regression algorithm (KNLDLSR). A large number of experiments show that our proposed algorithms can achieve very good performance.