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Found 6278 publications

Production process modeling and planning wih simulation method, mounting process optimisation

No authors available

Publication Name: International Workshop on Modeling and Applied Simulation, MAS 2009, Held at the International Mediterranean and Latin American Modeling Multiconference, I3M 2009

Publication Date: 2009-01-01

Volume:

Issue:

Page Range: 240-245

Description:

The paper focuses on the establishment of the production program using simulation technology in a structure, where several products and high amount of variants per product are produced. The topic of the paper addresses the discrete event simulation technology which is used to model the material flow and the manufacturing processes in the production area. This paper would like to show and describe the modelling steps of a complex production system with a lot of products and three different line parts, which are connected with buffers.

Open Access: No

DOI: DOI not available

Optical torque sensor development

A. Nagy P. Horváth

Publication Name: Recent Advances in Mechatronics 2008 2009

Publication Date: 2009-01-01

Volume: Unknown

Issue: Unknown

Page Range: 91-96

Description:

The purpose of this study is to develop a contactless torque sensor in the mNm range. The applied optical method is based on the birefringe effect of photoelastic materials. The novelty of the modified reflective photoelastic method is the application of a photoelastic tube as a coupling and measuring element between shafts. Change in intensity of polarized light is proportional to the torque to be measured. Basics of operational principle and practical considerations are also discussed.

Open Access: Yes

DOI: 10.1007/978-3-642-05022-0_16

Production process modeling and planning wih simulation method, mounting process optimisation

János Jósvai

Publication Name: International Workshop on Modeling and Applied Simulation Mas 2009 Held at the International Mediterranean and Latin American Modeling Multiconference I3m 2009

Publication Date: 2009-01-01

Volume: Unknown

Issue: Unknown

Page Range: 240-245

Description:

The paper focuses on the establishment of the production program using simulation technology in a structure, where several products and high amount of variants per product are produced. The topic of the paper addresses the discrete event simulation technology which is used to model the material flow and the manufacturing processes in the production area. This paper would like to show and describe the modelling steps of a complex production system with a lot of products and three different line parts, which are connected with buffers.

Open Access: Yes

DOI: DOI not available

Scalable collaborative filtering approaches for large reeommender systems

Bottyan Nemeth Istvan Pilaszy Gabor Takacs Domonkos Tikk

Publication Name: Journal of Machine Learning Research

Publication Date: 2009-01-01

Volume: 10

Issue: Unknown

Page Range: 623-656

Description:

The collaborative filtering (CF) using known user ratings of items has proved to be effective for predicting user preferences in item selection. This thriving subfield of machine learning became popular in the late 1990s with the spread of online services that use recommender systems, such as Amazon, Yahoo! Music, and Netflix. CF approaches are usually designed to work on very large data sets. Therefore the scalability of the methods is crucial. In this work, we propose various scalable solutions that are validated against the Netflix Prize data set, currently the largest publicly available collection. First, we propose various matrix factorization (MF) based techniques. Second, a neighbor correction method for MF is outlined, which alloys the global perspective of MF and the localized property of neighbor based approaches efficiently. In the experimentation section, we first report on some implementation issues, and we suggest on how parameter optimization can be performed efficiently for MFs. We then show that the proposed scalable approaches compare favorably with existing ones in terms of prediction accuracy and/or required training time. Finally, we report on some experiments performed on MovieLens and Jester data sets.

Open Access: Yes

DOI: DOI not available

A unified approach of factor models and neighbor based methods for large recommender systems

Bottyan Nemeth Istvan Pilaszy Gabor Takacs Domonkos Tikk

Publication Name: 1st International Conference on the Applications of Digital Information and Web Technologies Icadiwt 2008

Publication Date: 2008-12-30

Volume: Unknown

Issue: Unknown

Page Range: 186-191

Description:

Matrix factorization (MF) based approaches have proven to be efficient for rating-based recommendation systems. In this paper, we propose a hybrid approach that alloys an improved MF and the so-called NSVD1 approach, resulting in a very accurate factor model. After that, we propose a unification of factor models and neighbor based approaches, which further improves the performance. The approaches are evaluated on the Netflix Prize dataset, and they provide very low RMSE, and favorable running time. Our best solution presented here with Quiz RMSE 0.8851 outperforms all published single methods in the literature. ©2008 IEEE.

Open Access: Yes

DOI: 10.1109/ICADIWT.2008.4664342

Improvement the energy storage with ultracapacitor in metro railcar by modeling and simulation

I. Szenasy

Publication Name: 2008 IEEE Vehicle Power and Propulsion Conference Vppc 2008

Publication Date: 2008-12-29

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

This paper focuses on the use of modeling and simulation for the renewable energy. An energy storage system for improving performance of electric vehicles is presented. The supercapacitor contributes to the rapid energy recovery associated with regenerative braking in electric vehicles. This power system allows the acceleration and deceleration of the vehicle with minimal loss of energy. Short-distance passenger traffic on electrified lines is a domain where brake energy recuperation might reduce the total energy consumption significantly. In this paper the results of simulation model by Matlab-Simulink for an urbanmetro railcar and the method for reduce the need value of capacitance are presented. © 2008 IEEE.

Open Access: Yes

DOI: 10.1109/VPPC.2008.4677664

Desirable versus desired: Different insulations from observability: An evolutionary step in value theory (?)

Károly Varga

Publication Name: Journal of Human Values

Publication Date: 2008-12-01

Volume: 14

Issue: 2

Page Range: 129-140

Description:

The subject of this study, the step forward-which the author felt to be 'of evolutionary value' - was occasioned by a Delphi discussion. The debate was opened by Varga's (2003, 2006a) contrastive exposition of diagnoses of present history with respect to Hungary's accession to the European Union, offered by some leading Hungarian sociologists (Henrik Kreutz, Kálmán Kulcsár, Iván Szelényi, Iván Vitányi), in which he tried to place the views of these authors in a value sociological system by Charles Morris (1956, 1964) and Geert Hofstede (1991). In Morris' case, this involved recourse to his combination of two systems: one semiotic, the other axiological; in Hofstede's, to his system of 'software of the mind' embracing axiology and organizational psychology. This synthesis was opposed by Kreutz (2006a) who offered a new ordering principle which he advanced as truer to life. The present confrontation between the value sociological synthesis advanced by Kreutz, on the one hand, and the trends hallmarked by the names of Morris and Hofstede, on the other hand, provided the author with an opportunity to find a resolution of the tension between desired and desirable, for which he has gained some side light from Robert K. Merton's (1957) theory of the different degrees of insulation of role-activities from observability by members of the role-set (and which has derived further refinement from Jean-Paul Sartre's conception of 'glance and shame').

Open Access: Yes

DOI: 10.1177/097168580801400204

Comparison of fuzzy rule-based learning and inference systems

János Botzheim Krisztián Balázs László T. Kóczy

Publication Name: 9th International Symposium of Hungarian Researchers on Computational Intelligence and Informatics Cinti 2008

Publication Date: 2008-12-01

Volume: Unknown

Issue: Unknown

Page Range: 61-75

Description:

In our work we have compared various fuzzy rule based learning and inference systems. The base of the investigations was a modular system that we have implemented in C language. It contains several alternative versions of the two key elements of rule based learning - namely, the optimization algorithm and the inference method - which can be found in the literature. We obtained very different properties when combining these alternatives (changing the modules and connecting them) in all possible ways. The investigations determined the values of the quality measures (complexity and accuracy) of the obtained alternatives both analitically and experimentally where it was possible. Based on these quality measures the combinations have been ordered according to different aspects.

Open Access: Yes

DOI: DOI not available

Investigation of various matrix factorization methods for large recommender systems

Bottyan Nemeth Istvan Pilaszy Gabor Takacs Domonkos Tikk

Publication Name: Proceedings of the 2nd Kdd Workshop on Large Scale Recommender Systems and the Netflix Prize Competition Netflix 08

Publication Date: 2008-12-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

Matrix Factorization (MF) based approaches have proven to be efficient for rating-based recommendation systems. In this work, we propose several matrix factorization approaches with improved prediction accuracy. We introduce a novel and fast (semi)-positive MF approach that approximates the features by using positive values for either users or items. We describe a momentum-based MF approach. A transductive version of MF is also introduced, which uses information from test instances (namely the ratings users have given for certain items) to improve prediction accuracy. We describe an incremental variant of MF that efficiently handles new users/ratings, which is crucial in a real-life recommender system. A hybrid MF - neighbor-based method is also discussed that further improves the performance of MF. The proposed methods are evaluated on the Netflix Prize dataset, and we show that they can achieve very favorable Quiz RMSE (best single method: 0.8904, combination: 0.8841) and running time. Copyright 2008 ACM.

Open Access: Yes

DOI: 10.1145/1722149.1722155