• 제목/요약/키워드: Industry classification

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Land Suitability Classification for Rational Land Use Planning in County(Gun) Area( I ) - Methodological Considemtion of Land Suitability Classification - (군단위지역 토지이용계획의 합리적 책정을 위한 토지적성구분( I ) - 토지적성구분의 방법론적 고찰 -)

  • Hwang, Han-Cheol;Choe, Su-Myeong;Han, Gyeong-Su
    • Journal of Korean Society of Rural Planning
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    • v.1 no.1
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    • pp.65-74
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    • 1995
  • As a initial methodological approach to rational land use planning in the county-level area, three types of land suitability classification techniques were examined from the viewpoint of their practical applicability through the case study of Seungju-gun area, Chonnam-province, Korea : major factors' criteria(method I ), principal component analysis( I ), and local monitoring( R( ). Each method has its strong and weak points as shown in Tab.-5. Therefore, when its practical application, there seem to be wide-range methodological selectivities from exclusive use of the best one to intermethodological combination of related ones In the beginning stage, intermethodological combination of all three types were tried to formulate the best solution possible. However, because of reliability problem of method R accrued from non- uniformity of evaluators'quality, only two methods( 1 , E ) were combined into a new evaluation method The applied results of the new combined method to case study area are shown in Fig.-2, 3 and 4.

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Development of Representative Curves for Classified Demand Patterns of the Electricity Customer

  • Yu, In-Hyeob;Lee, Jin-Ki;Ko, Jong-Min;Kim, Sun-Ic
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.1379-1383
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    • 2005
  • Introducing the market into the electricity industry lets the multiple participants get into new competition. These multiple participants of the market need new business strategies for providing value added services to customer. Therefore they need the accurate customer information about the electricity demand. Demand characteristic is the most important one for analyzing customer information. In this study load profile data, which can be collected through the Automatic Meter Reading System, are analyzed for getting demand patterns of customer. The load profile data include electricity demand in 15 minutes interval. An algorithm for clustering similar demand patterns is developed using the load profile data. As results of classification, customers are separated into several groups. And the representative curves for the groups are generated. The number of groups is automatically generated. And it depends on the threshold value for distance to separate groups. The demand characteristics of the groups are discussed. Also, the compositions of demand contracts and standard industrial classification in each group are presented. It is expected that the classified curves will be used for tariff design, load forecasting, load management and so on. Also it will be a good infrastructure for making a value added service related to electricity.

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Quality Control of Two Dimensions Using Digital Image Processing and Neural Networks (디지털 영상처리와 신경망을 이용한 2차원 평면 물체 품질 제어)

  • Kim, Jin-Hwan;Seo, Bo-Hyeok;Park, Seong-Wook
    • Proceedings of the KIEE Conference
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    • 2004.07d
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    • pp.2580-2582
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    • 2004
  • In this paper, a Neural Network(NN) based approach for classification of two dimensions images. The proposed algorithm is able to apply in the actual industry. The described diagnostic algorithm is presented to defect surface failures on tiles. A way to get data for a digital image process is several kinds of it. The tiles are scanned and the digital images are preprocessed and classified using neural networks. It is important to reduce the amount of input data with problem specific preprocessing. The auto-associative neural network is used for feature generation and selection while the probabilistic neural network is used for classification. The proposed algorithm is evaluated experimentally using one hundred of the real tile images. Sample image data to preprocess have histogram. The histogram is used as input value of probabilistic neural network. Auto-associative neural network compress input data and compressed data is classified using probabilistic neural network. Classified sample images are determined by human state. So it is intervened human subjectivity. But digital image processing and neural network are better than human classification ability. Therefore it is very useful of quality control improvement.

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Research of Quantitative Modeling that Classify Personal Color Skin Tone (퍼스널 컬러 스킨 톤 유형 분류의 정량적 평가 모델 구축에 대한 연구)

  • Kim, Yong Hyeon;Oh, Yu Seok;Lee, Jung Hoon
    • Journal of the Korean Society of Clothing and Textiles
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    • v.42 no.1
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    • pp.121-132
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    • 2018
  • Recent beauty trends focus on suitability to individual features. A personal color system is a recent aesthetic concept that influences color make up and coordination. However, a personal color concept has several weaknesses. For example, type classification is qualitative and not quantitative because its measuring system is a sensory test with no industry standard of personal color system. A quantitative personal color type classification model is the purpose of this study, which can be a solution to above problems. This model is a kind of mapping system in a 3D Cartesian coordinate system which has own axes, Value, Saturation, and Yellowness. The cheek color of the individual sample is also independent variable and personal color type is a dependent variable. In order to construct the model, this study conducted a colorimetric survey on a 993 sampling frequency of Korean women in their 20s and 30s. The significance of this study is as follows. First, through this study, personal color system is established on quantitative color space; in addition, the model has flexibility and scalability because it consisted of independent axis that allows for the inclusion of any other critical variable in the form of variable axis.

A Review of Postural Classification Schemes for Evaluating Postural Load - Focused on the Observational Methods (작업 자세 부하 평가를 위한 자세 분류 체계의 연구 현황 - 관측법을 중심으로)

  • 기도형
    • Journal of the Korean Society of Safety
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    • v.15 no.4
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    • pp.139-149
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    • 2000
  • This study aims to review and assess the existing postural classification schemes used for evaluating postural loads in industry. The schemes can be classified into three categories: self-report, observational and instrument-based techniques depending upon how to record working postures. Of the three techniques, this study was mainly focused on the observational methods. The observational technique is most widely used in the industrial sites because it does not interfere with work, and is easy and simple to use and cost-effective without requiring the use of expensive equipment for estimating the angular deviation of a body segment from the neutral position. In spite of the usefulness and applicability, the techniques have some problems: 1) The existing observational techniques lack the consistency in the class limits of the motion categories in each body segment; 2) Most of them do not provide the post-analysis criteria needed to judge whether or not any posture is acceptable in view point of the postural load; and 3) They can not precisely evaluate the postural load for a given posture because the external loads and dynamic factors including acceleration, moment and force were not taken into consideration.

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EFFECTS OF RANDOMIZING PATTERNS AND TRAINING UNEQUALLY REPRESENTED CLASSES FOR ARTIFICIAL NEURAL NETWORKS

  • Kim, Young-Sup;Coleman Tommy L.
    • 한국공간정보시스템학회:학술대회논문집
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    • 2002.03a
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    • pp.45-52
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    • 2002
  • Artificial neural networks (ANN) have been successfully used for classifying remotely sensed imagery. However, ANN still is not the preferable choice for classification over the conventional classification methodology such as the maximum likelihood classifier commonly used in the industry production environment. This can be attributed to the ANN characteristic built-in stochastic process that creates difficulties in dealing with unequally represented training classes, and its training performance speed. In this paper we examined some practical aspects of training classes when using a back propagation neural network model for remotely sensed imagery. During the classification process of remotely sensed imagery, representative training patterns for each class are collected by polygons or by using a region-growing methodology over the imagery. The number of collected training patterns for each class may vary from several pixels to thousands. This unequally populated training data may cause the significant problems some neural network empirical models such as back-propagation have experienced. We investigate the effects of training over- or under- represented training patterns in classes and propose the pattern repopulation algorithm, and an adaptive alpha adjustment (AAA) algorithm to handle unequally represented classes. We also show the performance improvement when input patterns are presented in random fashion during the back-propagation training.

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A Study of Knowledge Classification Structure Improvement through Adopting BPM (BPM 도입을 통한 지식분류체계 개선에 관한 연구)

  • Hwang, Jin-Won;Choi, Hyung-Won;Choi, Yoon-Ki
    • Proceedings of the Korean Institute Of Construction Engineering and Management
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    • 2008.11a
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    • pp.720-724
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    • 2008
  • Concentration about value of invisible asset has increased in the condition of rapid business circumstance change. As one of these concentration, many company adopted knowledge management, and construction industry also tried to adopt knowledge management. However, it is difficult for construction company to get expected effects because of knowledge management system in no relation with business process. To solve this problems, this study adopted BPM that has many functions, such as business process design, operation, monitoring, sustainable improvement, to knowledge classification structure.

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Classification of Factors for Intangible Asset Valuation of Construction Engineering Consulting Firm (건설 엔지니어링 기업의 무형자산 가치측정을 위한 요소분류체계 개발)

  • Phi, Seung Woo;Hur, Young Ran;Seo, Jong Won
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.33 no.2
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    • pp.757-769
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    • 2013
  • Intangible assets for construction engineering consulting firms are very important for their valuation, because engineering consulting is typical knowledge-based business which creates value based on technical expertise and human resources. This paper presents the intangible asset classification model based on the concept of value creation in construction engineering consulting firm and proposes intangible asset valuation methodology using System Dynamics and survey data. Utilization of the valuation methodology presented in this paper would increase the public awareness of intangible assets in construction engineering consulting firm and, thus, contribute to the growth of the engineering consulting industry by realistic and accurate valuation of intangible assets.

A study on the Improvement of Work Environment System of interior Architecture (실내건축 업역의 업무환경 제도 개선에 관한 연구)

  • 오인욱
    • Korean Institute of Interior Design Journal
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    • no.37
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    • pp.3-11
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    • 2003
  • The study Is Intended to investigate and analyze the system and practice that have been applied to Interior Architecture, comparing with a number of similar foreign cases, in an attempt to seek the way toward its development as well as to come up with the solution for enhancing the competitiveness, thereby making a recommendation on how to create the desirable work environment of Interior Architecture down the road. The conclusion and recommendation we have made is highlighted as follow. Among the practical or procedural challenges in the process of improving work environment of Interior Architecture, development of current national technical qualification system in a way of further detailing the categories of Ki-sul-sa(highest engineer grade) or Ki-neung-jang(highest technician grade) as part of measures aimed at gradual approaching for improvement of design fees and rates or supervision fees will be very crucial, that calls for close coordination with the Ministry of Labor and Human Resources Development Service of Korea. In a bid to upgrade the Interior Architecture to become the part of knowledge-based industry, amendment to Korean Standard Industrial Classification along with Standard Classification of Occupations and Academic Classification will be essential, and moreover with the attitude of reflection and self-improvement, the endeavors to be able to deal with the revision of existing laws and regulations in a consistent way and manner, by forming a joint committee among the three Interior Architecture-related organizations(KOSID, ICC, KlID), will be more than important.

E2GSM: Energy Effective Gear-Shifting Mechanism in Cloud Storage System

  • You, Xindong;Han, GuangJie;Zhu, Chuan;Dong, Chi;Shen, Jian
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.10
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    • pp.4681-4702
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    • 2016
  • Recently, Massive energy consumption in Cloud Storage System has attracted great attention both in industry and research community. However, most of the solutions utilize single method to reduce the energy consumption only in one aspect. This paper proposed an energy effective gear-shifting mechanism (E2GSM) in Cloud Storage System to save energy consumption from multi-aspects. E2GSM is established on data classification mechanism and data replication management strategy. Data is classified according to its properties and then be placed into the corresponding zones through the data classification mechanism. Data replication management strategies determine the minimum replica number through a mathematical model and make decision on replica placement. Based on the above data classification mechanism and replica management strategies, the energy effective gear-shifting mechanism (E2GSM) can automatically gear-shifting among the nodes. Mathematical analytical model certificates our proposed E2GSM is energy effective. Simulation experiments based on Gridsim show that the proposed gear-shifting mechanism is cost effective. Compared to the other energy-saved mechanism, our E2GSM can save energy consumption substantially at the slight expense of performance loss while meeting the QoS of user.