Literatura académica sobre el tema "Optimization-based Integration Platform"
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Artículos de revistas sobre el tema "Optimization-based Integration Platform"
Li, Ang y Chun Jie Wang. "Construction of Lander Multidisciplinary Optimization Platform". Key Engineering Materials 407-408 (febrero de 2009): 180–84. http://dx.doi.org/10.4028/www.scientific.net/kem.407-408.180.
Texto completoGuo, Ruijie, Shengbo Ye y Yicai Ji. "Optimization Acceleration Integral Method Based on Power Spectrum Estimation". MATEC Web of Conferences 176 (2018): 03012. http://dx.doi.org/10.1051/matecconf/201817603012.
Texto completoZsiros, Attila, Attila Fülöp y Gábor Jeney. "Joint Optimization in UMTS-Based Video Transmission". Advances in Multimedia 2007 (2007): 1–14. http://dx.doi.org/10.1155/2007/28340.
Texto completoTan, Hongyun y Yiping Li. "News Information Platform Optimization Based on the Internet of Things". Wireless Communications and Mobile Computing 2021 (28 de mayo de 2021): 1–11. http://dx.doi.org/10.1155/2021/9403874.
Texto completoLi, Yu, Tai Yong Wang y Yin Ming Ge. "Adaptable Dynamic Design Platform Based on CAX/PDM System". Advanced Materials Research 694-697 (mayo de 2013): 168–71. http://dx.doi.org/10.4028/www.scientific.net/amr.694-697.168.
Texto completoZhou, Wei, Qing Min Liao y Fei Zhou. "A Design of Infrared Spots Tracking Platform Based on the Camera". Applied Mechanics and Materials 336-338 (julio de 2013): 392–96. http://dx.doi.org/10.4028/www.scientific.net/amm.336-338.392.
Texto completoChang, Bao Rong, Yun-Da Lee y Po-Hao Liao. "Development of Multiple Big Data Analytics Platforms with Rapid Response". Scientific Programming 2017 (2017): 1–13. http://dx.doi.org/10.1155/2017/6972461.
Texto completoKushwaha, Arvinda y Mohd Amjad. "A Particle Swarm Optimization Based Load Scheduling Algorithm in Cloud Platform for Wireless Sensor Networks". Scalable Computing: Practice and Experience 20, n.º 1 (9 de marzo de 2019): 71–82. http://dx.doi.org/10.12694/scpe.v20i1.1464.
Texto completoDing, Ke, Qi Yuan He y Gang Chen. "Research of Information Integration for the Grid Panoramic Information Platform Based on SOA". Applied Mechanics and Materials 667 (octubre de 2014): 50–54. http://dx.doi.org/10.4028/www.scientific.net/amm.667.50.
Texto completoYan, Yan, Liyan Zhang, Yuhan Li, Xiangyu Xu, Zhencheng Jiang y Feiyu Cheng. "Research on solar water heating system based on TRNSYS simulation optimization". Journal of Mines, Metals and Fuels 69, n.º 4 (13 de mayo de 2021): 132. http://dx.doi.org/10.18311/jmmf/2021/27801.
Texto completoTesis sobre el tema "Optimization-based Integration Platform"
Dai, Lei. "An Open Platform of Parameterized Shape Optimization based-on CAD/CAE Integration Technique". Reims, 2006. http://theses.univ-reims.fr/exl-doc/GED00000752.pdf.
Texto completoDai, Lei Guo Ying Qiao. "An Open Platform of Parameterized Shape Optimization based-on CAD/CAE Integration Technique". Reims : S.C.D. de l'Université, 2006. http://scdurca.univ-reims.fr/exl-doc/GED00000752.pdf.
Texto completoJuvert, Sández Joan. "Development and optimization of silicon based light sources for integration into a sensor platform". Doctoral thesis, Universitat de Barcelona, 2014. http://hdl.handle.net/10803/275940.
Texto completoAquesta tesi presenta un estudi de les propietats òptiques de capes d'òxid de silici enriquit en silici (SRO) i nitrur de silici enriquit en silici (SRN) que han sofert un procés tèrmic d'alta temperatura. Aquest procés indueix la creació de nanoaglomerats de silici en la matriu dielèctrica. Aquestes nanoestructures de silici presenten una superior eficiència en l'emissió respecte al silici en bloc, i a més a més emeten en el visible en comptes de l'infraroig. Això és interessant per a l'obtenció de dispositius fotònics integrats basats en silici que poden ser fabricats monolíticament en un procés compatible amb la tecnologia CMOS que domina la indústria microelectrònica. A més a més, hem estudiat les propietats òptiques i elèctriques de dispositius metall-aïllant-semiconductor en les quals l'aïllant és una capa d'SRO o SRN amb nanoaglomerats de silici. N'hem mesurat paràmetres d'interès com ara l'eficiència de conversió d'energia elèctrica-òptica o la potència òptica, i n'hem estudiat els mecanismes d'injecció que hi tenen lloc. S'han identificat tres tipus diferents d'emissió: per punts, per la vora del dispositiu, i emissió homogènia, i hem determinat que l'emissió homogènia és la més adecuada pel que fa a l'eficiència dels dispositius. Hem desenvolupat un programa que permet el càlcul de les interferències òptiques que tenen lloc als sistemes multicapa que conformen els dispositius estudiats, i que distorsionen l'espectre observat respecte al que les capes realment emeten. L'habilitat de poder calcular aquests efectes ens permet, en molts casos, eliminar l'efecte de les interferències i determinar l'autèntic espectre d'emissió de les capes i per tant estar en millors condicions d'assignar l'emissió als mecanismes correctes. Finalment, hem proposat un prototip per a un transceptor en el qual l'emissor, la guia d'ones i el detector estan integrats monolíticament en un procés CMOS. Hem fabricat el dispositiu i l'hem caracteritzat. Tot i que no hem aconseguit acoblament òptic entre l'emissor i el detector, creiem que el disseny bàsic queda validat, ja que els principals obstacles en l'obtenció del dispositiu han sigut superats amb èxit.
LIAO, PO-HAO y 廖柏豪. "Deep Learning Based Integration and Optimization of Big Data Analytics Platforms". Thesis, 2018. http://ndltd.ncl.edu.tw/handle/349jtp.
Texto completo國立高雄大學
資訊工程學系碩士班
106
This study focused on big data analysis job scheduling mechanism, predicting the time for big data analysis based on deep learning DNN (Deep Neural Network), and shortening the average waiting time of overall work by intelligent scheduling optimization. The proposed mechanism is expected to enhance the execution efficiency of big data analysis platform greatly. A multi-platform big data processing system, characterized by high efficiency, high availability and high expandability, is integrated with Hadoop and Spark to make the platform support R command-based data analysis capability. The time complexity, priority and data size of working program can influence the efficiency of overall execution work and the average waiting time for fulfilling the work, especially in the environment of big data, the average waiting time for fulfilling the work is prolonged. This problems can be solved only by designing optimal scheduling to enhance system effectiveness. This study uses DNN to predict the execution time for R program, and implements intelligent scheduling according to Shortest Job First, the optimal program execution platform is selected, so as to shorten the average waiting time for fulfilling the work to optimize the multiple big data platforms.
LEE, YUN-DA y 李昀達. "Deep Learning Based Integration and Optimization of Rapid Data Retrieval in Big Data Platforms". Thesis, 2018. http://ndltd.ncl.edu.tw/handle/96k95v.
Texto completo國立高雄大學
資訊工程學系碩士班
106
The purpose of this study is to focus on the data pre-processing mechanism and to use Deep Autoencoder and Solr to group data intelligently and reduce the scope of search required by Query. It is expected that the proposed mechanism will greatly improve the efficiency of system query. A set of multiple big data processing platform with high efficiency and high availability was adopted, and the integration of Apache Hive, Cloudera Impala and Apache SparkSQL enabled the platform to support the big data retrieval capability of SQL commands. Through the above platform and mechanism, the overall performance can be significantly improved. Data tables often need to be searched completely when data is retrieved. In order to solve the serious problem that the system I/O takes longer and longer time when the amount of data becomes larger and larger, the effect of intelligent clustering practiced by deep learning method is considered, as it is superior to the efficiency of traditional neural network. Therefore, a deep model was designed to improve the overall efficiency of the system.
Capítulos de libros sobre el tema "Optimization-based Integration Platform"
Dral, Pavlo O., Fuchun Ge, Bao Xin Xue, Yi-Fan Hou, Max Pinheiro, Jianxing Huang y Mario Barbatti. "MLatom 2: An Integrative Platform for Atomistic Machine Learning". En Topics in Current Chemistry Collections, 13–53. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-07658-9_2.
Texto completoKümpel, Michaela, Christian A. Mueller y Michael Beetz. "Semantic Digital Twins for Retail Logistics". En Dynamics in Logistics, 129–53. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-88662-2_7.
Texto completoHe, Yan. "Study on Secure Dynamic Covering Algorithm for E-Logistics Information in a Cloud Computing Platform". En Research Anthology on Architectures, Frameworks, and Integration Strategies for Distributed and Cloud Computing, 1097–111. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-5339-8.ch051.
Texto completoBiswas, Rathindra Nath, Anurup Saha, Swarup Kumar Mitra y Mrinal Kanti Naskar. "PSO-Based Antenna Pattern Synthesis". En Nature-Inspired Algorithms for Big Data Frameworks, 218–45. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-5852-1.ch009.
Texto completoLezak, Emil, Enrico Ferrera, Rosaria Rossini, Zofia Masluszczak, Malgorzata Fialkowska-Filipek, Gunnar Große Hovest, Alexander Schneider et al. "Towards Industry 4.0". En Research Anthology on Cross-Industry Challenges of Industry 4.0, 411–35. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-8548-1.ch022.
Texto completoLezak, Emil, Enrico Ferrera, Rosaria Rossini, Zofia Masluszczak, Malgorzata Fialkowska-Filipek, Gunnar Große Hovest, Alexander Schneider et al. "Towards Industry 4.0". En Technological Developments in Industry 4.0 for Business Applications, 199–223. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-4936-9.ch009.
Texto completoBrahmane, Anilkumar V. y B. Chaitanya Krishna. "DSAE – Deep Stack Auto Encoder and RCBO – Rider Chaotic Biogeography Optimization Algorithm for Big Data Classification". En Recent Trends in Intensive Computing. IOS Press, 2021. http://dx.doi.org/10.3233/apc210198.
Texto completoWu, Lei, Ming Wei y Xiang Chen. "Optimization Model of Unmanned Aerial Vehicle Distribution Path with Integrated Loading and Unloading". En Frontiers in Artificial Intelligence and Applications. IOS Press, 2021. http://dx.doi.org/10.3233/faia210205.
Texto completoAijaz, Fahad. "Mobile Web Services for P2P Computing". En Developing Advanced Web Services through P2P Computing and Autonomous Agents, 133–57. IGI Global, 2010. http://dx.doi.org/10.4018/978-1-61520-973-6.ch008.
Texto completoGebremeskel, Gebeyehu Belay, Zhongshi He y Xuan Jing. "Semantic Integrating for Intelligent Cloud Data Mining Platform and Cloud Based Business Intelligence for Optimization of Mobile Social Networks". En Data Mining in Dynamic Social Networks and Fuzzy Systems, 173–211. IGI Global, 2013. http://dx.doi.org/10.4018/978-1-4666-4213-3.ch009.
Texto completoActas de conferencias sobre el tema "Optimization-based Integration Platform"
Alsaeedi, Ayesha Ahmed Abdulla Salem, Manar Maher Mohamed Elabrashy, Mohamed Ali Alzeyoudi, Mohamed Mubarak Albadi, Sandeep Soni, Jose Isambertt, Deepak Tripathi y Melvin Hidalgo. "Leveraging Business Intelligence and Data Analytics in an Integrated Digital Production Platform to Unlock Optimization Potentials". En Abu Dhabi International Petroleum Exhibition & Conference. SPE, 2021. http://dx.doi.org/10.2118/208209-ms.
Texto completoLi, Yunpeng y Utpal Roy. "Challenges in Developing a Computational Platform to Integrate Data Analytics With Simulation-Based Optimization". En ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/detc2015-46410.
Texto completo"NAS-wide Simulation-Based Evaluation Platform for Validation of a Traffic Flow Management Optimization Tool". En 12th AIAA Aviation Technology, Integration, and Operations (ATIO) Conference and 14th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2012. http://dx.doi.org/10.2514/6.2012-5471.
Texto completoChen, Cheng, Noman Mithani, Tiffany Jin y Allen Guo. "Liquid Cooling Practice on Meta’s AI Training Platform". En ASME 2022 International Technical Conference and Exhibition on Packaging and Integration of Electronic and Photonic Microsystems. American Society of Mechanical Engineers, 2022. http://dx.doi.org/10.1115/ipack2022-96972.
Texto completoShetty, Devdas, Naresh Poudel y Esther Ososanya. "Design of Robust Mechatronics Embedded Systems by Integration of Virtual Simulation and Mechatronics Platform". En ASME 2015 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/imece2015-52784.
Texto completoNtonas, Konstantinos, Nikolaos Aretakis, Ioannis Roumeliotis y Konstantinos Mathioudakis. "A Marine Turbocharger Retrofitting Platform". En ASME Turbo Expo 2020: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/gt2020-14643.
Texto completoKopczynski, Jerry A., Bill Dickson y Gerhard J. Weiss. "Common Electronic Platform for the Steam Turbine and Generator Controls: Upgrade Installed at the Mt. Poso Cogeneration Power Station — A Case Study". En ASME 2004 Power Conference. ASMEDC, 2004. http://dx.doi.org/10.1115/power2004-52159.
Texto completoAlsaeedi, Ayesha, Mohamed Mubarak Albadi, Fahad Alharthi, Manar Elabrashy, Mohamed Alzeyoudi, Ammar Al-Ameri, Eissa Al Mheiri et al. "Improved Field Production Planning and Cost Optimization Using Predictive Analytical Choke Performance Model and Intelligent Alarms in an Integrated Platform". En ADIPEC. SPE, 2022. http://dx.doi.org/10.2118/211314-ms.
Texto completoZhao, Xin, Smruti Sahoo, Konstantinos Kyprianidis, Sharmila Sumsurooah, Giorgio Valente, Mohamed Rashed, Gaurang Vakil et al. "A Framework for Optimization of Hybrid Aircraft". En ASME Turbo Expo 2019: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/gt2019-91335.
Texto completoArroyos, Marina Roche, Javier Arturo Corea Araujo, Didac Sabria, Vinayak Padmaji, Pablo Cano y Patrice Garmier. "Model based component co-optimization and scalability of virtual testing for electric drivetrain vehicle". En FISITA World Congress 2021. FISITA, 2021. http://dx.doi.org/10.46720/f2021-dgt-045.
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