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ieee international conference on Big data (Big data)

作者： Tewari, Naveen C. Koduvely, Hari M. Guha, Sarbendu Yadav, Arun David, Gladbin Infosys Ltd Infosys Labs Ctr Knowledge Driven Intelligent Syst Bangalore 560100 Karnataka India

ISBN: (纸本)9781479912926;9781479912933

We introduce in this paper a scalable implementation of Variational Bayesian Matrix Factorization method for collaborative filtering using the MapReduce framework. Variational Bayesian methods have the advantage of providing good approximate analytical solutions for the posterior distribution. Due to the independence assumption about the parameters in the posterior distribution, variational methods are also likely to be able to parallelize efficiently. Though Variational Bayesian Matrix Factorization method has shown to produce more accurate results in collaborative filtering, its scaling properties have not studied so far. We ran our MapReduce implementation on the CiteULike data set and show that our parallelization scheme achieves approximately linear scaling. We also compare its performance with the MapReduce implementation of a popular matrix factorization algorithm, ALSWR, from the open source machine learning library Mahout.

关键词： Variational Bayesian Matrix Factorization Probabilistic Matrix Factorization MapReduce Distributed computing Collaborative Filtering Recommendation systems

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advanced AEROSPACE COMPOSITE-MATERIAL STRUCTURAL DESIGN USING ARTIFICIAL intelligent TECHNOLOGY

ADVANCED AEROSPACE COMPOSITE-MATERIAL STRUCTURAL DESIGN USIN...

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international conference on advanced Composite Materials (ICACM) - advanced Composites 93

作者： SUN, SH HWANG, WC CHEN, JL NATL CHENG KUNG UNIV DEPT MECH ENGNTAINANTAIWAN

ISBN: (纸本)0873392515

Due to the complexity in the prediction of property and behavior, composite material has not substituted for metal widely yet, though it has high specific-strength and high specific-modulus that are more important in the aerospace industry. In this paper two artificial intelligent techniques, the expert systems and neural network technology, were introduced to the structural design of composite material. Expert System which has good ability in symbolic processing can helps us to solve problem by saving experience and knowledge. It is, therefore, a reasonable way to combine expert system technology to the composite structural design. The development of a prototype expert system to help designer during the process of composite structural design is presented. Neural network is a network similar to people's brain that can simulate the thinking way of people and has the ability of learning from the training data by adapting the weights of network. Because of the bottleneck in knowledge acquisition processes, the application of neural network and its learning ability to strength design of composite structures are presented. Some examples are in this paper to demonstrate the idea.

关键词： Composite structures

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Ontological methodology of knowledge base design in economics

Ontological methodology of knowledge base design in economic...

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ieee international Workshop on intelligent data acquisition and advanced computing systems: Technology and Applications

作者： Ihor Tkach Sergiy Rippa Tetiana Gonchar Research Institute of Intelligent Computer Systems Ternopil National Economic University Ternopil Ukraine National University of State Tax Service of Ukraine Kiev Ukraine

This article deals with the concept development methodological principles of conceptualization of the economic systems using ontological modelling. Proposed approach enables to build ontology of any economic system on micro- and macro levels, to form the set of problem situations and set of ways of their overcoming which are the basis for designing the knowledge base of the intelligence system.

关键词： Ontologies Environmental economics Power generation economics Object oriented modeling intelligent systems Knowledge management OWL conferences data acquisition Application software

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data-Driven Fault Detection and Identification in Wind Turbines Through Performance Assessment

Data-Driven Fault Detection and Identification in Wind Turbi...

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ieee international conference on intelligent data acquisition and advanced computing systems

作者： Boudy Bilal Kondo Hloindo Adjallah Alexandre Sava FST LRAER Université de Nouakchott AL Aasriya Nouakchott Mauritanie LCOMS EA7306 University of Lorraine Metz France

This paper proposes a simple data-driven method for fault detection and identification based on the assessment of performance and detection miscorrelation among the operating data of wind turbines. The operating data were collected over one year on a 30 MW wind farm in Mauritania, Nouakchott area, for parameters including the wind speed, generator output power, turbine rotating speed, generator temperature, rotor speed, gearbox bearing temperature and generator rotating speed. The method starts with identifying the distribution of the pitch angle and the temperature of the generator on each of the four identified operating phases of the wind turbine. Then the correlation faults analysis allows identifying their characteristics and explaining the performance failures.

关键词： Wind speed Generators Wind turbines Temperature measurement Temperature distribution

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Optimization of resource and qualitative limitations in management of education projects

Optimization of resource and qualitative limitations in mana...

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ieee international Workshop on intelligent data acquisition and advanced computing systems: Technology and Applications

作者： Taras Lendyuk Sergey Rippa Department of Information-Computer Systems and Control Ternopil National Economic University Ternopil Ukraine National University of State Tax Service of Ukraine Kiev Ukraine

In the paper interdependence between the basic project resources and requirements to it execution quality is described. Graphic visualization of these resources of optimal values choice is shown. Also the experimental... 详细信息

关键词： Quality management Project management Resource management Financial management Cost function Calendars Raw materials conferences data acquisition Educational technology

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Using Blockchain to Enhance and Optimize IoT-based intelligent Traffic System 6

Using Blockchain to Enhance and Optimize IoT-based Intellige...

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6th international conference on Platform Technology and Service (PlatCon)

作者： Ren, Qilei Man, Ka Lok Li, Muqing Gao, Bingjie Xian Jiaotong Liverpool Univ Suzhou Peoples R China Xian Jiaotong Liverpool Univ AI URC RIBDA Suzhou Peoples R China Xian Jiaotong Liverpool Univ Dept Comp Sci & Software Engn Suzhou Peoples R China AXA Next Lab Asia Shanghai Peoples R China Shanghai Cunjian Technol Co Ltd Shanghai Peoples R China

ISBN: (纸本)9781728112886

Smart city blueprint is constructed by increasing deployment of various Internet of Things devices. In this paper, we focus on data transmission and request for lane property right under the domain of an intelligent traffic system. IoT devices are usually deployed in a heterogeneous environment, with the natural gene of decentralization. Compared with cloud-based centralized architecture, in this paper, we introduce blockchain as a decentralized technology to let vehicles jointly collaborate without having to go through a central computing node authority. data transmission between vehicles uses a peer-to-peer network in which every node communicates directly with every other node, verified by their relevant end-point nodes;lane's acquisition right is approved by all relevant vehicle nodes, as well as with consensus agreed upon via smart contract.

关键词： Internet of Things Blockchain Decentralised system data Transmission Lane Property Right acquisition Smart contract

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Environmentally-friendly navigation

Environmentally-friendly navigation

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10th international ieee conference on intelligent Transportation systems

作者： Barth, Matthew Boriboonsomsin, Kanok Vu, Alex Univ Calif Riverside Elect Engn & CE CERT Riverside CA 92521 USA

ISBN: (纸本)9781424413959

One of the major successes in ITS technology lately has been in the area of advanced Traveler Information systems (ATIS). In particular, there are now many good navigation systems that can advise drivers on route selection within a roadway network. This type of navigation software is now available on the Internet that can be used for trip planning, as well as in on-board navigation systems that can calculate optimal routes based on current vehicle location. The primary role of these navigation systems is to help drivers find their destinations. More advanced navigation systems can now help drivers avoid congestion on the roadways based on receiving real-time roadway data information. To date, these navigation systems have embedded algorithms that attempt to minimize trip distance and/or travel time. However, many drivers are now becoming increasingly concerned with rising fuel costs and pollutant emissions. Therefore, it is desirable to create new "environmentally-friendly" navigation algorithms. Taking advantage of the latest navigation technology, we have developed new navigation techniques that focus on minimizing energy consumption and pollutant emissions. These methods combine sophisticated mobile-source energy and emission models with route minimization algorithms that are used for navigational purposes. These new methods have been applied in several Southern California case studies resulting in significant energy savings compared to standard navigation techniques.

关键词： navigation intelligent route selection telematics

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Guest Editorial Focused Section on Sensing and Perception systems for intelligent Manufacturing (SPIM)

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ieee-ASME TRANSACTIONS ON MECHATRONICS 2018年第3期23卷 983-985页

作者： Chen, X. Zhang, S. Geraedts, J. M. P. Univ Windsor Dept Elect & Comp Engn Windsor ON N9B 3P4 Canada Purdue Univ Sch Mech Engn W Lafayette IN 47907 USA Delft Univ Technol Ind Design Engn NL-2628 CE Delft Netherlands

The 11 papers in this special section focus on sensing and perception systems for intelligent manufacturing. This new industrial revolution calls for solutions to embedded intelligence, networked environment, interaction, autonomous, and high performance computing. The manufacturing industry is at the center of this wave of innovation with sensing and perception in focus. The papers included in this section examine the methodologies developed are all based on processing data generated by complex sensing devices acting on certain kind of physical fields, such as vision and temperature field, in order to render 2-D or 3-D information of fields. This kind of field sensing and perception development is the key to facilitate the intelligent operation of manufacturing systems in practices.

关键词： Special issues and sections Manufacturing processes Robot sensing systems Temperature sensors intelligent systems Industrial electronics intelligent sensors Manufacturing automation

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A Highly Reliable data Storage Method for Power data Centers with Hyper-Converged Architectures 4

A Highly Reliable Data Storage Method for Power Data Centers...

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4th ieee international conference on Power, intelligent computing and systems, ICPICS 2022

作者： Zhang, Yunhou Wang, Zhe Ren, Jiyuan Yin, Lu Song, Yang Liu, Fuyang Wang, Jing Northeast Branch of State Grid Corporation of China Shenyang China School of Computer Science and Engineering Northeastern University Shenyang China

ISBN: (数字)9781665467735

ISBN: (纸本)9781665467735

The data center suffers from poor reliability and unbalanced load. This is caused by the selection of single-round storage nodes that are too close to each other. This paper proposes a data storage method based on deep reinforcement learning, which includes two parts: the node reliability judgment module and the data placement module. Firstly, we use multiple neural networks to build a node reliability judgment module to evaluate the reliability degree of server nodes. Based on this, a distributed parallel data storage method is proposed to select server nodes. The experimental results show that the data storage method in this paper has high reliability and can achieve load balancing in the data center. © 2022 ieee.

关键词： Reliability

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Development and Validation of Lane Keeping Assist Algorithm for advanced Driver Assistance System Applications 9

Development and Validation of Lane Keeping Assist Algorithm ...

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9th international conference on Smart computing and Communications, ICSCC 2023

作者： Anand Padmanabhan, A. Khan, Jihas Prakash, Amal Nair, Arjun R. Amrita Vishwa Vidyapeetham Department of Mechanical Engineering Amritapuri India Transportation Business Unit Tata Elxsi Trivandrum India

ISBN: (纸本)9798350314090

Over the past decade, there has been a significant change in trends in the automotive industry. The number of vehicles equipped with advanced driver assistance system (ADAS) are increasing on the roads, but their level of autonomy is showing a gradual increase over time. The important part that is required to have reliable ADAS is that it must process all the data coming from different sensors efficiently. One of the most important ADAS algorithms is intended for lane keeping assist system (LKAS) and lane departure warning (LDW). This paper looks forward to employ LKAS algorithm that aids the user to have a real-world visual experience with a 3D visualization. Most of this algorithm testing are done on straight road scenes but in this paper a clothoid road structure is adapted and is visualized using the tool. © 2023 ieee.

关键词： advanced driver assistance systems

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