• Title/Summary/Keyword: Rating Prediction

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Analytical Prediction of Bearing Life and Load Distribution for Plugin HEV (플러그인 HEV용 베어링 수명 및 응력분포의 분석예측)

  • Zhang, Qi;Kang, Jae-Hwa;Yun, Gi-Baek;Lyu, Sung-Ki
    • Journal of the Korean Society of Manufacturing Process Engineers
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    • v.11 no.5
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    • pp.1-7
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    • 2012
  • The transportation is almost dependent on a single fuel petroleum with transportation energy dilemma. Hybrid Electric Vehicle(HEV) technology holds more advantages on efficiency improvements for petroleum consumption at the transportation. And bearing is recognized as the important component of gearbox. Gearboxes for HEV transmission have been ensured the highest reliability over some years in withstanding high dynamic loads. At the same time, the demands of lightweight design and cost minimization are required by thought-out design, high-quality material, superior production quality and maintenance. In order to design a reliable and lightweight gearbox, it is necessary to analyze bearing rating life methods between standard and different bearing companies with calculation methods for modification factors. In this paper, the influence of life time of bearings will be pointed out. Bearing contact stress and load stress distribution of HEV gearbox are obtained and compared with Romaxdesigner and BearinX. And the unequal wear of the left bearing for the gearbox intermediate shaft is investigated between simulation and test.

Analytical Prediction of Bearing Life and Load Distribution for Plugin HEV (플러그인 HEV용 베어링 수명 및 응력분포의 분석예측)

  • Zhang, Qi;Kang, Jae-Hwa;Yun, Gi-Baek;Lyu, Sung-Ki
    • Journal of the Korean Society of Manufacturing Process Engineers
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    • v.11 no.4
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    • pp.25-30
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    • 2012
  • The transportation is almost dependent on a single fuel petroleum with transportation energy dilemma. Hybrid Electric Vehicle(HEV) technology holds more advantages on efficiency improvements for petroleum consumption at the transportation. And bearing is recognized as the important component of gearbox. Gearboxes for HEV transmission have been ensured the highest reliability over some years in withstanding high dynamic loads. At the same time, the demands of lightweight design and cost minimization are required by thought-out design, high-quality material, superior production quality and maintenance. In order to design a reliable and lightweight gearbox, it is necessary to analyze bearing rating life methods between standard and different bearing companies with calculation methods for modification factors. In this paper, the influence of life time of bearings will be pointed out. Bearing contact stress and load stress distribution of HEV gearbox are obtained and compared with Romaxdesigner and BearinX. And the unequal wear of the left bearing for the gearbox intermediate shaft is investigated between simulation and test.

Online Reviews Analysis for Prediction of Product Ratings based on Topic Modeling (토픽 모델링에 기반한 온라인 상품 평점 예측을 위한 온라인 사용 후기 분석)

  • Park, Sang Hyun;Moon, Hyun Sil;Kim, Jae Kyeong
    • Journal of Information Technology Services
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    • v.16 no.3
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    • pp.113-125
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    • 2017
  • Customers have been affected by others' opinions when they make a purchase. Thanks to the development of technologies, people are sharing their experiences such as reviews or ratings through online or social network services, However, although ratings are intuitive information for others, many reviews include only texts without ratings. Also, because of huge amount of reviews, customers and companies can't read all of them so they are hard to evaluate to a product without ratings. Therefore, in this study, we propose a methodology to predict ratings based on reviews for a product. In a methodology, we first estimate the topic-review matrix using the Latent Dirichlet Allocation technic which is widely used in topic modeling. Next, we predict ratings based on the topic-review matrix using the artificial neural network model which is based on the backpropagation algorithm. Through experiments with actual reviews, we find that our methodology can predict ratings based on customers' reviews. And our methodology performs better with reviews which include certain opinions. As a result, our study can be used for customers and companies that want to know exactly a product with ratings. Moreover, we hope that our study leads to the implementation of future studies that combine machine learning and topic modeling.

Potential Mapping of Mountainous Wetlands using Weights of Evidence Model in Yeongnam Area, Korea (Weight of Evidence 기법을 이용한 영남지역의 산지습지 가능지역 추출)

  • Baek, Seung-Gyun;Jang, Dong-Ho
    • Journal of The Geomorphological Association of Korea
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    • v.20 no.1
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    • pp.21-33
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    • 2013
  • Weight of evidence model was applied for potential mapping of mountainous wetland to reduce the range of the field survey and to increase the efficiency of operations because the surveys of mountainous wetland need a lot of time and money owing to inaccessibility and extensiveness. The relationship between mountainous wetland location and related factors is expressed as a probability by Weight of evidence model. For this, the spatial database consist of slope map, curvature map, vegetation index map, wetness index map, soil drainage rating map was constructed in Yeongnam area, Korea, and weights of evidence based on the relationship between mountainous wetland location and each factor rating were calculated. As a result of correlation analysis between mountainous wetland location and each factors rating using likelihood ratio values, the probability of mountainous wetlands were increased at condition of lower slope, lower curvature, lower vegetation index value, lower wetness value, moderate soil drainage rating. Mountainous Wetland Potential Index(MWPI) was calculated by summation of the likelihood ratio and mountainous wetland potential map was constucted from GIS integration. The mountain wetland potential map was verified by comparison with the known mountainous wetland locations. The result showed the 75.48% in prediction accuracy.

Rock Classification Prediction in Tunnel Excavation Using CNN (CNN 기법을 활용한 터널 암판정 예측기술 개발)

  • Kim, Hayoung;Cho, Laehun;Kim, Kyu-Sun
    • Journal of the Korean Geotechnical Society
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    • v.35 no.9
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    • pp.37-45
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    • 2019
  • Quick identification of the condition of tunnel face and optimized determination of support patterns during tunnel excavation in underground construction projects help engineers prevent tunnel collapse and safely excavate tunnels. This study investigates a CNN technique for quick determination of rock quality classification depending on the condition of tunnel face, and presents the procedure for rock quality classification using a deep learning technique and the improved method for accurate prediction. The VGG16 model developed by tens of thousands prestudied images was used for deep learning, and 1,469 tunnel face images were used to classify the five types of rock quality condition. In this study, the prediction accuracy using this technique was up to 83.9%. It is expected that this technique can be used for an error-minimizing rock quality classification system not depending on experienced professionals in rock quality rating.

Privacy-Preserving Two-Party Collaborative Filtering on Overlapped Ratings

  • Memis, Burak;Yakut, Ibrahim
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.8 no.8
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    • pp.2948-2966
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    • 2014
  • To promote recommendation services through prediction quality, some privacy-preserving collaborative filtering solutions are proposed to make e-commerce parties collaborate on partitioned data. It is almost probable that two parties hold ratings for the same users and items simultaneously; however, existing two-party privacy-preserving collaborative filtering solutions do not cover such overlaps. Since rating values and rated items are confidential, overlapping ratings make privacy-preservation more challenging. This study examines how to estimate predictions privately based on partitioned data with overlapped entries between two e-commerce companies. We consider both user-based and item-based collaborative filtering approaches and propose novel privacy-preserving collaborative filtering schemes in this sense. We also evaluate our schemes using real movie dataset, and the empirical outcomes show that the parties can promote collaborative services using our schemes.

A Study on Prediction and Development of Prospective Fisheries-Related Jobs in Korea (우리나라 수산업의 유망직종 예측과 개발에 관한 연구)

  • Kim, Sam-Kon
    • Journal of Fisheries and Marine Sciences Education
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    • v.20 no.1
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    • pp.36-45
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    • 2008
  • The purpose of this study was to explore new fisheries-related jobs in the future. The study is based on a thorough literature review and in-depth interviews with experts in the fisheries industry. The major findings of the study were as follows: First, new fisheries-related jobs that surpass the fitness rating of 90% and earn more than 3 on the prospect scale are expected to be found mostly in professional fishery sectors. In the production and processing sectors, fishery quality control manager, marine product cooks, and raw fish cooks looked most promising. In the fishery marketing and distribution section, on the other hand, marine tour consultants, marine product distribution consultants, underwater guides, online marine product traders, marine sports consultants, and marine safety specialists ranked high on the list.

Parameter Measurement and Dynamic Performance Estimation of Synchronous Reluctance Motor Considering Iron Loss (철손을 고려한 자기저항 동기전동기의 정수 측정 및 동특성 예측)

  • Lee, J.S.;Hong, J.P.;Hahn, S.C.;Joo, S.W.
    • Proceedings of the KIEE Conference
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    • 1999.07a
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    • pp.58-60
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    • 1999
  • This paper presents dynamic performance prediction using Matlab / simulink after parameter estimation of synchronous reluctance motor considering iron loss. Test motor is 3 phase SynRM with the segmental rotor, rating power is 0.175KW. Experiment equipment is consists of testing motor, dynamometer, vector invertor dynamocontroller, and power analyser. The stator iron loss and rotor iron loss are modelled by additional windings on three-phase winding axis. These windings are transformed into d-q axis, and are represented as equivalent eddy current windings. P-Q circle diagram method and single phase standstill method are used to measure motor parameters considering iron loss.

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Relationships between Children's Social Development and Day Care Quality, Child-care Experience and Family Characteristics (탁아기관의 질, 탁아경험 및 가족특성과 아동의 사회성발달과의 관계)

  • Yang, Yeon Suk;Cho, Bok Hee
    • Korean Journal of Child Studies
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    • v.17 no.2
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    • pp.181-193
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    • 1996
  • The purpose of this study was: (1) to examine relationships between social development and day care quality, child-care experience and family characteristics, and (2) to investigate the explainability of those related variables for social development. Subjects for this study were 252 4-year-old children and their mothers from 32 day care centers in Seoul. Harms & Clifford's Early Childhood Environment Rating Scale was used to measure the quality of day care. The main results were as follows: (1) Day care quality, child-care experience and family characteristics were significantly related to social development. (2) Child's gender, months of age, mother's child rearing attitude, the length of child-care experience, overall quality of day care, and group size significantly predicted social development. 33% of the variance of social development was explained by these variables. The relative influence of these variables to the prediction of social development was about the same.

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The Effect of Co-rating on the Recommender System of User Base

  • Lee, Hee-Choon;Lee, Seok-Jun;Chung, Young-Jun
    • Journal of the Korean Data and Information Science Society
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    • v.17 no.3
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    • pp.775-784
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    • 2006
  • This study is to investigate the effect of the number of co-rated users to the MAE. User based collaborative algorithm generally uses similarity weight to compute the relation of active user and other users. The original estimation algorithm of the GroupLens used the Pearson's correlation coefficient, soon after other researchers used various weighting. The Pearson’s correlation coefficient and Vector similarity, which is used in the field of information retrieval, are commonly used to the estimation algorithm. In prediction, we analyze the effect of the number of co-rated users on the user based recommender system.

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