Academic literature on the topic 'Usinage intelligent'
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Journal articles on the topic "Usinage intelligent":
Kishorekumar, Mr A., Mr E. Ezhilarasan, and Mr R. Parthiban. "Intelligent Drone based Personal Assistant using Artificial Intelligence AI." International Journal of Trend in Scientific Research and Development Volume-2, Issue-3 (April 30, 2018): 1618–21. http://dx.doi.org/10.31142/ijtsrd11482.
Chinagolum, Aneke Israel, Chineke Amaechi Hyacenth, and Udeh Chukwuma Callistus W. "Intelligent Routing Algorithm Using Antnet." International Journal of Trend in Scientific Research and Development Volume-3, Issue-1 (December 31, 2018): 306–14. http://dx.doi.org/10.31142/ijtsrd18990.
A., Ponmalar. "Intelligent Crime Analysis System Using Pyspark." International Journal of Psychosocial Rehabilitation 24, no. 5 (March 31, 2020): 860–67. http://dx.doi.org/10.37200/ijpr/v24i5/pr201757.
Liu, Hong, Haijun Wei, Lidui Wei, Jingming Li, and Zhiyuan Yang. "The Segmentation of Wear Particles Images UsingJ-Segmentation Algorithm." Advances in Tribology 2016 (2016): 1–10. http://dx.doi.org/10.1155/2016/4931502.
Islam, Faraz, and Ali Faraz Syed. "PLC Based Intelligent Toll Road Traffic Control Using." International Journal of Computer Theory and Engineering 6, no. 4 (2014): 353–56. http://dx.doi.org/10.7763/ijcte.2014.v6.888.
Yadav, Kiran, and Ranjit Biswas. "Finding a Shortest Path Using an Intelligent Technique." International Journal of Engineering and Technology 1, no. 2 (2009): 139–41. http://dx.doi.org/10.7763/ijet.2009.v1.25.
GEORGIEV, Rumen, and Kolyo KOLEV. "COMPARATIVE ANALYSIS OF TUNING MISSILE AUTOPILOTS USING INTELLIGENT METHODS." SCIENTIFIC RESEARCH AND EDUCATION IN THE AIR FORCE 18, no. 1 (June 24, 2016): 251–58. http://dx.doi.org/10.19062/2247-3173.2016.18.1.34.
Chinagolum, Aneke Israel, Chineke Amaechi Hyacenth, and Udeh Chukwuma Callistus W. "Improving Robustness of Data Network Using Intelligent Modulation Technique." International Journal of Trend in Scientific Research and Development Volume-3, Issue-1 (December 31, 2018): 315–23. http://dx.doi.org/10.31142/ijtsrd18991.
Thomas, Hephzibah, and Thyla B. "Intelligent Fall Detection Using Statistical Features and Machine Learning." International Journal of Trend in Scientific Research and Development Volume-3, Issue-1 (December 31, 2018): 609–12. http://dx.doi.org/10.31142/ijtsrd19024.
COLLINĂSZY, Juraj, Marek BUNDZEL, and Iveta ZOLOTOVĂ. "IMPLEMENTATION OF INTELLIGENT SOFTWARE USING IBM WATSON AND BLUEMIX." Acta Electrotechnica et Informatica 17, no. 1 (March 1, 2017): 58–63. http://dx.doi.org/10.15546/aeei-2017-0008.
Dissertations / Theses on the topic "Usinage intelligent":
Chouhad, Hassan. "Towards online metrology for proactive quality control in smart manufacturing." Thesis, Paris, HESAM, 2022. http://www.theses.fr/2022HESAE021.
In the traditional manufacturing industry, metrology is an essential element in sanctioning quality at the end of the production line. The innovation brought by concept of smart manufacturing leads to a repositioning of metrology to be proactive at the heart of production by performing the so-called first-time-right manufacturing of parts. The goal of this thesis is therefore to propose a methodological approach for the development of a proactive system, enhanced by AI models, to control the conformity of a product to a specification during machining and to characterize its defects. For this purpose, a first study on the surface aspect was carried out by collecting high-resolution images of coated and cut copper wires that may present defects. The images, taken by a computer vision system based on chromatic confocal imaging, were used to generate different artificial intelligence models. These models can perform segmentation and classification of observed defects. When comparing the accuracy and processing time of the AI models, transfer learning using the mobile-net model showed better performance. To extend the study of surface quality assessment, surface profile measurements on machine tools were performed using non-contact chromatic confocal sensors. Two approaches were performed: i) milling aluminum without tool wear signature, and ii) milling titanium with tool wear signature. In both cutting configurations, machining parameters, surface roughness profiles, and cutting forces were measured to build a dataset for training the prediction models by machine learning. The results showed that the XGboost model presented the best prediction performance and for both scenarios i) and ii). By considering the cutting time in titanium milling, the autoregressive integrated moving average time series prediction model was applied to track the evolution of roughness with tool wear
Escriba, Christophe. "Conception, réalisation et caractérisation de capteurs infrarouges à thermopiles : application à la détection de présence passive dans l'habitat." Phd thesis, Université Paul Sabatier - Toulouse III, 2005. http://tel.archives-ouvertes.fr/tel-00088644.
Vigouroux, Jean-Louis. "Modélisation des connaissances pour l’optimisation des systèmes d’usinage intelligents." Dijon, 2008. http://www.theses.fr/2008DIJOS053.
Research on Intelligent machining systems has the potential to make production of machined parts easily adaptive to changes in the part geometry specification, and to skip the industrialization step. The work presented here fosters the realization of this potential, by using standard data models of the field and optimization under uncertainty. First a bibliography is made to keep track of previous efforts related to intelligent manufacturing systems, optimization under uncertainty, and manufacturing and optimization knowledge representation. Important concepts like Manufacturing system agility, and optimization under uncertainty were defined, and the standards STEP and UML for knowledge representation and system modeling were studied. Then an information system architecture is proposed, to link manufacturing knowledge and optimization problem knowledge, using a new data model. An evolutionary algorithm called Robust Evolutionary Algorithm (REA) is designed and added to the architecture for solving non linear optimization under uncertainty. The architecture is then applied to the process plan optimization of a turning part. Some drawbacks of the architecture are discovered during the implementation, thus leading to an evolution. Two new data models are introduced, the System Operation simulation Model (SOM) and the Optimization under Uncertainty Model (OUM). The SOM data model is a proposal for the representation of manufacturing system operational properties, and the OUM data model is a proposal for the representation of a non linear optimization problem with uncertainties. The second version of the architecture is a solid base for the software implementation of an intelligent machining system. Some further studies are necessary to capture of the dependency relations between experimental machining models and operational properties of a machining system
Bernardes, Vitor Giovani. "Urban environment perception and navigation using robotic vision : conception and implementation applied to automous vehicle." Thesis, Compiègne, 2014. http://www.theses.fr/2014COMP2155/document.
The development of autonomous vehicles capable of getting around on urban roads can provide important benefits in reducing accidents, in increasing life comfort and also in providing cost savings. Intelligent vehicles for example often base their decisions on observations obtained from various sensors such as LIDAR, GPS and Cameras. Actually, camera sensors have been receiving large attention due to they are cheap, easy to employ and provide rich data information. Inner-city environments represent an interesting but also very challenging scenario in this context,where the road layout may be very complex, the presence of objects such as trees, bicycles,cars might generate partial observations and also these observations are often noisy or even missing due to heavy occlusions. Thus, perception process by nature needs to be able to dea lwith uncertainties in the knowledge of the world around the car. While highway navigation and autonomous driving using a prior knowledge of the environment have been demonstrating successfully,understanding and navigating general inner-city scenarios with little prior knowledge remains an unsolved problem. In this thesis, this perception problem is analyzed for driving in the inner-city environments associated with the capacity to perform a safe displacement basedon decision-making process in autonomous navigation. It is designed a perception system that allows robotic-cars to drive autonomously on roads, with out the need to adapt the infrastructure,without requiring previous knowledge of the environment and considering the presenceof dynamic objects such as cars. It is proposed a novel method based on machine learning to extract the semantic context using a pair of stereo images, which is merged in an evidential grid to model the uncertainties of an unknown urban environment, applying the Dempster-Shafer theory. To make decisions in path-planning, it is applied the virtual tentacle approach to generate possible paths starting from ego-referenced car and based on it, two news strategies are proposed. First one, a new strategy to select the correct path to better avoid obstacles and tofollow the local task in the context of hybrid navigation, and second, a new closed loop control based on visual odometry and virtual tentacle is modeled to path-following execution. Finally, a complete automotive system integrating the perception, path-planning and control modules are implemented and experimentally validated in real situations using an experimental autonomous car, where the results show that the developed approach successfully performs a safe local navigation based on camera sensors
Babovic, Vladan. "Emergence, evolution, intelligence: hydroinformatics : a study of distributed and decentralised computing using intelligent agents /." Rotterdam [etc.] : Balkema, 1996. http://opac.nebis.ch/cgi-bin/showAbstract.pl?u20=905410404X.
Hall, Douglas Lee. "A Comparative Analysis of Guided vs. Query-Based Intelligent Tutoring Systems (ITS) Using a Class-Entity-Relationship-Attribute (CERA) Knowledge Base." Thesis, North Texas State University, 1987. https://digital.library.unt.edu/ark:/67531/metadc331475/.
Kostias, Aristotelis, and Georgios Tagkoulis. "Development of an Artificial Intelligent Software Agent using Artificial Intelligence and Machine Learning Techniques to play Backgammon Variants." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-251923.
Artificiell intelligens har sett enorma framsteg inom många discipliner de senare åren. Speciellt, digitaliserade brädspel kräver implementering av Artificiell intelligens då deras beslutfattande logik är väldigt komplex. Dataspelutvecklarnas syfte och mål är att skapa programvaror som är intelligenta, adaptiva och lyhörda. Dock konstruktionsoch utvecklingsprocess för att kunna skapa en sådan mjukvara är långtifrån att vara faställd, mest på grund av diversitet av naturen av varje spel. Denna avhandlingen forskar och föreslår en detaljerad procedur för att bygga en "Software Agent" för olika slags Backagammon, genom att använda AI neurala nätvärk och back-propagation metoder. Olika artificiell intelligensoch maskininlärningsalgoritmer som används i brädspel forskas och presenteras. Slutligen denna avhandling beskriver implementeringen och utvecklingen av ett mjukvaru agent för en backgammonvariant, närmare bestämt av "Svenska Tabeller" samt utvärderar dess prestanda.
Enyedy, Albert J. "Robotic Construction Using Intelligent Scaffolding." Digital WPI, 2020. https://digitalcommons.wpi.edu/etd-theses/1356.
Hiesel, Jeanne C. "An approach to the analysis and design of an intelligent tutoring systems using an object-oriented methodology /." Online version of thesis, 1993. http://hdl.handle.net/1850/11716.
Artun, F. Emre. "Reservoir characterization using intelligent seismic inversion." Morgantown, W. Va. : [West Virginia University Libraries], 2005. https://eidr.wvu.edu/etd/documentdata.eTD?documentid=4185.
Title from document title page. Document formatted into pages; contains xii, 82 p. : ill. (some col.), maps (some col.). Includes abstract. Includes bibliographical references (p. 80-82).
Books on the topic "Usinage intelligent":
Dehuri, Satchidananda, and Sung-Bae Cho. Knowledge mining using intelligent agents. London: Imperial College Press, 2011.
Babovic, Vladan. Emergence, evolution, intelligence: Hydroinformatics : a study of distributed and decentralised computing using intelligent agents. Rotterdam: A.A. Balkema, 1996.
Bigus, Joseph P. Constructing intelligent agents using JAVA. 2nd ed. New York: Wiley, 2001.
Hemanth, D. Jude, ed. Human Behaviour Analysis Using Intelligent Systems. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-35139-7.
Yan, Jun. Using fuzzy logic: Towards intelligent systems. New York: Prentice Hall, 1994.
Casillas, Jorge, and Francisco J. Martínez-López, eds. Marketing Intelligent Systems Using Soft Computing. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15606-9.
Schildt, Herbert. Artificial intelligence using C. Berkeley, Calif: Osborne McGraw-Hill, 1987.
Huddleston, Creed. Intelligent sensor design using the microchip dsPIC. Boston: Elsevier/Newnes, 2006.
Cao, Tiehua. Intelligent task planning using fuzzy Petri nets. Singapore: World Scientific, 1996.
Hafner, Christian. Post-modern electromagnetics: Using intelligent Maxwell solvers. Chichester: John Wiley, 1999.
Book chapters on the topic "Usinage intelligent":
Fonseca, Camilo Isaza, Octavio J. Salcedo Parra, and Brayan S. Reyes Daza. "Intelligent Road Design Using Artificial Intelligence Techniques." In Mobile, Secure, and Programmable Networking, 166–77. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-67807-8_13.
Laskari, Naveen Kumar, and Suresh Kumar Sanampudi. "Design Artificial Intelligence Course Contents Using Artificial Intelligent Techniques." In ICICCT 2019 – System Reliability, Quality Control, Safety, Maintenance and Management, 592–99. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-8461-5_68.
Chen, Jim X., and Harry Wechsler. "Human Computer Intelligent Interaction Using Augmented Cognition and Emotional Intelligence." In Virtual Reality, 205–14. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-73335-5_23.
Floares, Alexandru G. "Using Computational Intelligence to Develop Intelligent Clinical Decision Support Systems." In Computational Intelligence Methods for Bioinformatics and Biostatistics, 266–75. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-14571-1_20.
Babenko, Liudmila, and Ilya Pisarev. "Comprehensive Analysis of Cryptographic Protocol Implementations Using Formal Verification and Dynamic Analysis Using the PDA Language." In Artificial Intelligence in Intelligent Systems, 428–43. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-77445-5_40.
Ali, Ammar Alhaj, Bronislav Chramcov, Roman Jasek, Rasin Katta, and Said Krayem. "Classification of Plant Diseases Using Convolutional Neural Networks." In Artificial Intelligence in Intelligent Systems, 268–75. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-77445-5_24.
Kok, Vernon, Nontokozo Mpofu, and Micheal Olusanya. "Severity Estimation of Potholes in Imagery Using Convolutional Neural Networks." In Artificial Intelligence in Intelligent Systems, 658–72. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-77445-5_60.
Rafique, Imsal, Mudasir Dilawar, Amina Umer, and Muhammad Ahmad Hassan. "Classification of Cardiotocography Data for Fetal Health Using Feature Selection Techniques." In Artificial Intelligence in Intelligent Systems, 34–44. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-77445-5_4.
Ekblom, Paul. "Intelligence." In Crime Prevention, Security and Community Safety Using the 5Is Framework, 163–80. London: Palgrave Macmillan UK, 2011. http://dx.doi.org/10.1057/9780230298996_11.
Shoilekova, Kamelia. "Intelligent Data Analysis Using a Classification Method for Data Mining Knowledge Discovery Process." In Artificial Intelligence in Intelligent Systems, 153–57. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-77445-5_14.
Conference papers on the topic "Usinage intelligent":
Guerra-Zubiaga, David, Logan Block, Adam Ricketts, Jacob Faile, and Charlie Dickson. "A New Approach to Develop an Intelligent Robotic Gripper Using Virtual Tools Implementing IIoT and ML Technologies." In ASME 2021 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/imece2021-69993.
Monteiro, Juarez, Roger Granada, Rafael C. Pinto, and Rodrigo C. Barros. "Beating Bomberman with Artificial Intelligence." In XV Encontro Nacional de Inteligência Artificial e Computacional. Sociedade Brasileira de Computação - SBC, 2018. http://dx.doi.org/10.5753/eniac.2018.4430.
Shweta A.S. "Intelligent refrigerator using ARTIFICIAL INTELLIGENCE." In 2017 11th International Conference on Intelligent Systems and Control (ISCO). IEEE, 2017. http://dx.doi.org/10.1109/isco.2017.7856036.
Hosam, Osama. "Intelligent Risk Management using Artificial Intelligence." In 2022 Advances in Science and Engineering Technology International Conferences (ASET). IEEE, 2022. http://dx.doi.org/10.1109/aset53988.2022.9734861.
Westermann, Thorsten, Harald Anacker, Roman Dumitrescu, Ursula Frank, and Axel Hessenkämper. "Interdisciplinary System Architecture for Intelligent Technical Systems." In ASME 2015 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/imece2015-50579.
Fang, Sheng, and Shunhuai Chen. "Research on Intelligent Loading of Bulk Carriers." In ASME 2020 39th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/omae2020-18209.
Усамов, И. Р., А. А. Албакова, and А. А. Мустиев. "THE ROLE OF INTELLIGENT INFORMATION SYSTEMS IN THE MODERN WORLD." In «АКТУАЛЬНЫЕ ВОПРОСЫ СОВРЕМЕННОЙ НАУКИ: ТЕОРИЯ, ТЕХНОЛОГИЯ, МЕТОДОЛОГИЯ И ПРАКТИКА». Международная научно-практическая онлайн-конференция, приуроченная к 60-ти летию член-корреспондента Академии наук ЧР, доктора технических наук, профессора Сайд-Альви Юсуповича Муртазаева. Crossref, 2021. http://dx.doi.org/10.34708/gstou.conf..2021.10.35.053.
Garbenis, Simas. "Trait Emotional Intelligence of Teachers Working in Special Education Schools." In 79th International Scientific Conference of University of Latvia. University of Latvia, 2021. http://dx.doi.org/10.22364/htqe.2021.35.
Coker, L. O. Toriola, N. AYekini, H. Alaka, and A. O. Ajimo. "Artificial Intelligence Systems for Teaching and Learning in Civil Engineering: Conceptual Framework." In 9th International Conference on Artificial Intelligence and Applications (AIAP 2022). Academy and Industry Research Collaboration Center (AIRCC), 2022. http://dx.doi.org/10.5121/csit.2022.120405.
Choi, Young-Cheol, and Hyo-Sung Ahn. "The Bio-Insect and Artificial Robots Interaction Based on Multi-Agent Reinforcement Learning." In ASME 2009 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2009. http://dx.doi.org/10.1115/detc2009-86688.
Reports on the topic "Usinage intelligent":
Serhrouchni, A., and H. Labiod. TLS Authentication Using Intelligent Transport System (ITS) Certificates. Edited by M. Msahli, N. Cam-Winget, and W. Whyte. RFC Editor, September 2020. http://dx.doi.org/10.17487/rfc8902.
Anderson, John R. Using an Intelligent Tutor to Study Skill Acquisition. Fort Belvoir, VA: Defense Technical Information Center, August 1990. http://dx.doi.org/10.21236/ada225763.
Cooley, Erika J., Jaime L. McClain, Jaclyn K. Murton, Thayne L. Edwards, Komandoor E. Achyuthan, Darren W. Branch, Paul Gilbert Clem, et al. Intelligent front-end sample preparation tool using acoustic streaming. Office of Scientific and Technical Information (OSTI), September 2009. http://dx.doi.org/10.2172/993903.
Scheiber, Lane B., and Ronald A. Enlow. Warfighter's Edge: Using Intelligent Agents To Solve Warfighter Problems. Fort Belvoir, VA: Defense Technical Information Center, August 2001. http://dx.doi.org/10.21236/ada390191.
Letendre, Steven, Krishnan Gowri, Michael CW Kintner-Meyer, and Richard M. Pratt. Intelligent Vehicle Charging Benefits Assessment Using EV Project Data. Office of Scientific and Technical Information (OSTI), December 2013. http://dx.doi.org/10.2172/1118115.
Andrade, Sylvio F., Neil C. Rowe, Donald P. Gaver, and Patricia A. Jacobs. Analysis of Shipboard Firefighting-Team Efficiency Using Intelligent-Agent Simulation. Fort Belvoir, VA: Defense Technical Information Center, January 2002. http://dx.doi.org/10.21236/ada458054.
Nichols, Jonathan M., Frank Bucholtz, and Joseph V. Michalowicz. Intelligent Data Fusion Using Sparse Representations and Nonlinear Dimensionality Reduction. Fort Belvoir, VA: Defense Technical Information Center, September 2009. http://dx.doi.org/10.21236/ada507109.
Hanson, Eric N. Support of Intelligent Integration of Information Using an Asynchronous Trigger Processor. Fort Belvoir, VA: Defense Technical Information Center, June 2000. http://dx.doi.org/10.21236/ada379345.
Cao, Siyang, Yao-jan Wu, and Feng Jin. Development of Intelligent Multimodal Traffic Monitoring using Radar Sensor at Intersections. Transportation Research and Education Center (TREC), 2021. http://dx.doi.org/10.15760/trec.268.
Jenny, Hubert, Yihong Wang, Eduardo Garcia Alonso, and Roberto Minguez. Using Artificial Intelligence for Smart Water Management Systems. Asian Development Bank, July 2020. http://dx.doi.org/10.22617/brf200191-2.