Relevant bibliographies by topics / Distributed Artificial Intelligence {Computing Methodologies}

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Distributed Artificial Intelligence {Computing Methodologies}'

Author: Grafiati
Published: 4 June 2021
Last updated: 3 February 2022

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Journal articles on the topic "Distributed Artificial Intelligence {Computing Methodologies}"

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Bhargavi, K., B. Sathish Babu, and Jeremy Pitt. "Performance Modeling of Load Balancing Techniques in Cloud: Some of the Recent Competitive Swarm Artificial Intelligence-based." Journal of Intelligent Systems 30, no. 1 (2020): 40–58. http://dx.doi.org/10.1515/jisys-2019-0084.

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Abstract Cloud computing deals with voluminous heterogeneous data, and there is a need to effectively distribute the load across clusters of nodes to achieve optimal performance in terms of resource usage, throughput, response time, reliability, fault tolerance, and so on. The swarm intelligence methodologies use artificial intelligence to solve computationally challenging problems like load balancing, scheduling, and resource allocation at finite time intervals. In literature, sufficient works are being carried out to address load balancing problem in the cloud using traditional swarm intelli
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Hirota, Toshio Fukudand Kaoru. "Message from Editors-in-Chief." Journal of Advanced Computational Intelligence and Intelligent Informatics 1, no. 1 (1997): 0. http://dx.doi.org/10.20965/jaciii.1997.p0000.

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We are very pleased and honored to have an opportunity to publish a new journal the "International Journal of Advanced Computational Intelligence" (JACI). The JACI is a new, bimonthly journal covering the field of computer science. This journal focuses on advanced computational intelligence, including the synergetic integration of neural networks, fuzzy logic and evolutionary computations, in order to assist in fostering the application of intelligent systems to industry. This new field is called computational intelligence or soft computing. It has already been studied by many researchers, but
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Rudas, Imre J. "Intelligent Engineering Systems." Journal of Advanced Computational Intelligence and Intelligent Informatics 2, no. 3 (1998): 69–71. http://dx.doi.org/10.20965/jaciii.1998.p0069.

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Building intelligent systems has been one of the great challenges since the early days of human culture. From the second half of the 18th century, two revolutionary changes played the key role in technical development, hence in creating engineering and intelligent engineering systems. The industrial revolution was made possible through technical advances, and muscle power was replaced by machine power. The information revolution of our time, in turn, canbe characterized as the replacement of brain power by machine intelligence. The technique used to build engineering systems and replace muscle
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Eduardo, Luis, and Castillo Hern. "On distributed artificial intelligence." Knowledge Engineering Review 3, no. 1 (1988): 21–57. http://dx.doi.org/10.1017/s0269888900004367.

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AbstractDistributed Artificial Intelligence has been loosely defined in terms of computation by distributed, intelligent agents. Although a variety of projects employing widely ranging methodologies have been reported, work in the field has matured enough to reveal some consensus about its main characteristics and principles. A number of prominent projects are described in detail, and two general frameworks, theSystem conceptual modeland theagent conceptual model, are used to compare the different approaches. The paper concludes by reviewing approaches to formalizing some of the more critical
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Corchado, Juan M., Li Weigang, Javier Bajo, Fei Wu, and Tian-cheng Li. "Special issue on distributed computing and artificial intelligence." Frontiers of Information Technology & Electronic Engineering 17, no. 4 (2016): 281–82. http://dx.doi.org/10.1631/fitee.dcai2015.

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Bajo, Javier, and Juan M. Corchado. "Neural Systems in Distributed Computing and Artificial Intelligence." Neurocomputing 231 (March 2017): 1–2. http://dx.doi.org/10.1016/j.neucom.2016.08.096.

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Bajo, Javier, and Juan M. Corchado. "Neural networks in distributed computing and artificial intelligence." Neurocomputing 272 (January 2018): 1–2. http://dx.doi.org/10.1016/j.neucom.2017.06.022.

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Dzitac, Ioan, and Boldur E. Bărbat. "Artificial Intelligence + Distributed Systems = Agents." International Journal of Computers Communications & Control 4, no. 1 (2009): 17. http://dx.doi.org/10.15837/ijccc.2009.1.2410.

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The connection with Wirth’s book goes beyond the title, albeit confining the area to modern Artificial Intelligence (AI). Whereas thirty years ago, to devise effective programs, it became necessary to enhance the classical algorithmic framework with approaches applied to limited and focused subdomains, in the context of broad-band technology and semantic web, applications - running in open, heterogeneous, dynamic and uncertain environments-current paradigms are not enough, because of the shift from programs to processes. Beside the structure as position paper, to give more weight to some basic
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Bajo, Javier, and Juan M. Corchado. "Special issue on distributed computing and artificial intelligence systems." Neurocomputing 172 (January 2016): 382–84. http://dx.doi.org/10.1016/j.neucom.2015.05.114.

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Kathidjiotis, Yiannis, Kostas Kolomvatsos, and Christos Anagnostopoulos. "Predictive intelligence of reliable analytics in distributed computing environments." Applied Intelligence 50, no. 10 (2020): 3219–38. http://dx.doi.org/10.1007/s10489-020-01712-5.

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Abstract Lack of knowledge in the underlying data distribution in distributed large-scale data can be an obstacle when issuing analytics & predictive modelling queries. Analysts find themselves having a hard time finding analytics/exploration queries that satisfy their needs. In this paper, we study how exploration query results can be predicted in order to avoid the execution of ‘bad’/non-informative queries that waste network, storage, financial resources, and time in a distributed computing environment. The proposed methodology involves clustering of a training set of exploration querie
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Dissertations / Theses on the topic "Distributed Artificial Intelligence {Computing Methodologies}"

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Wagy, Mark David. "Enabling Machine Science through Distributed Human Computing." ScholarWorks @ UVM, 2016. http://scholarworks.uvm.edu/graddis/618.

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Distributed human computing techniques have been shown to be effective ways of accessing the problem-solving capabilities of a large group of anonymous individuals over the World Wide Web. They have been successfully applied to such diverse domains as computer security, biology and astronomy. The success of distributed human computing in various domains suggests that it can be utilized for complex collaborative problem solving. Thus it could be used for "machine science": utilizing machines to facilitate the vetting of disparate human hypotheses for solving scientific and engineering problems.
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Malheiro, Maria Benedita Campos Neves. "Methodologies for Belief Revision in Multi-agent Systems." Phd thesis, Instituições portuguesas -- UP-Universidade do Porto -- -Faculdade de Engenharia -- -Departamento de Engenharia Electrotécnica e de Computadores, 1999. http://dited.bn.pt:80/29534.

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The goal of this thesis is twofold: first, we want to present the distributed belief accommodation and revision model for multi-agent systems that has been developed and, second, we wish to show its applicability to an appropriate domain. The Distributed Belief Accommodation & Revision model, called DeBAteR model, was developed for co-operative heterogeneous multi-agent systems used to model inherently dynamic distributed problems. In these systems, although the agents are able to detect changes both in the environment and in the problem specifications, each agent has only a partial view of th
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Gao, Zhenning. "Parallel and Distributed Implementation of A Multilayer Perceptron Neural Network on A Wireless Sensor Network." University of Toledo / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1383764269.

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Huhtinen, J. (Jouni). "Utilization of neural network and agent technology combination for distributed intelligent applications and services." Doctoral thesis, University of Oulu, 2005. http://urn.fi/urn:isbn:9514278550.

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Abstract The use of agent systems has increased enormously, especially in the field of mobile services. Intelligent services have also increased rapidly in the web. In this thesis, the utilization of software agent technology in mobile services and decentralized intelligent services in the multimedia business is introduced and described. Both Genie Agent Architecture (GAA) and Decentralized International and Intelligent Software Architecture (DIISA) are described. The common problems in decentralized software systems are lack of intelligence, communication of software modules and system learn
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Gonzalez, Lopez Jorge. "Distributed multi-label learning on Apache Spark." VCU Scholars Compass, 2019. https://scholarscompass.vcu.edu/etd/5775.

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This thesis proposes a series of multi-label learning algorithms for classification and feature selection implemented on the Apache Spark distributed computing model. Five approaches for determining the optimal architecture to speed up multi-label learning methods are presented. These approaches range from local parallelization using threads to distributed computing using independent or shared memory spaces. It is shown that the optimal approach performs hundreds of times faster than the baseline method. Three distributed multi-label k nearest neighbors methods built on top of the Spark ar
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Kumar, Saurabh. "Real-Time Road Traffic Events Detection and Geo-Parsing." Thesis, Purdue University, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10842958.

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<p> In the 21<sup>st</sup> century, there is an increasing number of vehicles on the road as well as a limited road infrastructure. These aspects culminate in daily challenges for the average commuter due to congestion and slow moving traffic. In the United States alone, it costs an average US driver $1200 every year in the form of fuel and time. Some positive steps, including (a) introduction of the push notification system and (b) deploying more law enforcement troops, have been taken for better traffic management. However, these methods have limitations and require extensive planning. Anoth
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Sinha, Arnab. "Self-describing objects with tangible data structures." Phd thesis, Université Rennes 1, 2014. http://tel.archives-ouvertes.fr/tel-01062441.

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Pervasive computing or ambient computing aims to integrate information systems into the environment, in a manner as transparent as possible to the users. It allows the information systems to be tightly coupled with the physical activities within the environment. Everyday used objects, along with their environment, are made smarter with the use of embedded computing, sensors etc. and also have the ability to communicate among themselves. In pervasive computing, it is necessary to sense the real physical world and to perceive its "context" ; a high level representation of the physical situation.
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Hamraz, Hamid. "AUTOMATED TREE-LEVEL FOREST QUANTIFICATION USING AIRBORNE LIDAR." UKnowledge, 2018. https://uknowledge.uky.edu/cs_etds/69.

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Traditional forest management relies on a small field sample and interpretation of aerial photography that not only are costly to execute but also yield inaccurate estimates of the entire forest in question. Airborne light detection and ranging (LiDAR) is a remote sensing technology that records point clouds representing the 3D structure of a forest canopy and the terrain underneath. We present a method for segmenting individual trees from the LiDAR point clouds without making prior assumptions about tree crown shapes and sizes. We then present a method that vertically stratifies the point clo
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Jankee, Christopher. "Optimisation par métaheuristique adaptative distribuée en environnement de calcul parallèle." Thesis, Littoral, 2018. http://www.theses.fr/2018DUNK0480/document.

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Pour résoudre des problèmes d'optimisation discret de type boîte noire, de nombreux algorithmes stochastiques tels que les algorithmes évolutionnaires ou les métaheuristiques existent et se révèlent particulièrement efficaces selon le problème à résoudre. En fonction des propriétés observées du problème, choisir l'algorithme le plus pertinent est un problème difficile. Dans le cadre original des environnements de calcul parallèle et distribué, nous proposons et analysons différentes stratégies adaptative de sélection d'algorithme d'optimisation. Ces stratégies de sélection reposent sur des mét
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Terrier, Véronique. "Reconnaissance de langages par automates cellulaires." Habilitation à diriger des recherches, Université de Caen, 2011. http://tel.archives-ouvertes.fr/tel-01070916.

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Les automates cellulaires ont été introduits il y a une soixantaine d'années par von Neumann et Ulam qui cherchaient à définir les caractéristiques d'un système formel apte au calcul universel et à l'auto-reproduction. Leur utilité a été rapidement reconnue dans des domaines variés comme la physique et la biologie, pour modéliser des phénomènes complexes. En informatique, ils offrent un cadre privilégié pour l'étude du parallélisme massif. Leur description est simple et bien formalisée. Ils ont a la même puissance de calcul que les machines de Turing et de plus la richesse algorithmique propre
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Books on the topic "Distributed Artificial Intelligence {Computing Methodologies}"

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Omatu, Sigeru, José Neves, Juan M. Corchado Rodriguez, Juan F. Paz Santana, and Sara Rodríguez Gonzalez, eds. Distributed Computing and Artificial Intelligence. Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-00551-5.

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Omatu, Sigeru, Juan F. De Paz Santana, Sara Rodríguez González, Jose M. Molina, Ana M. Bernardos, and Juan M. Corchado Rodríguez, eds. Distributed Computing and Artificial Intelligence. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-28765-7.

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de Leon F. de Carvalho, Andre Ponce, Sara Rodríguez-González, Juan F. De Paz Santana, and Juan M. Corchado Rodríguez, eds. Distributed Computing and Artificial Intelligence. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-14883-5.

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Omatu, Sigeru. Distributed Computing and Artificial Intelligence: 9th International Conference. Springer Berlin Heidelberg, 2012.

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Omatu, Sigeru. Distributed Computing and Artificial Intelligence: 10th International Conference. Springer International Publishing, 2013.

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André Carlos Ponce de Leon Ferreira Carvalho. Distributed Computing and Artificial Intelligence: 7th International Symposium. Springer Berlin Heidelberg, 2010.

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Abraham, Ajith. International Symposium on Distributed Computing and Artificial Intelligence. Springer Berlin Heidelberg, 2011.

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Omatu, Sigeru, Sara Rodríguez, Gabriel Villarrubia, Pedro Faria, Paweł Sitek, and Javier Prieto, eds. Distributed Computing and Artificial Intelligence, 14th International Conference. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-62410-5.

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De La Prieta, Fernando, Sigeru Omatu, and Antonio Fernández-Caballero, eds. Distributed Computing and Artificial Intelligence, 15th International Conference. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-94649-8.

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Dong, Yucheng, Enrique Herrera-Viedma, Kenji Matsui, Shigeru Omatsu, Alfonso González Briones, and Sara Rodríguez González, eds. Distributed Computing and Artificial Intelligence, 17th International Conference. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-53036-5.

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Book chapters on the topic "Distributed Artificial Intelligence {Computing Methodologies}"

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Duan, Jun-Hua, Tao Meng, Qing-Da Chen, and Quan-Ke Pan. "An Effective Artificial Bee Colony for Distributed Lot-Streaming Flowshop Scheduling Problem." In Intelligent Computing Methodologies. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-95957-3_84.

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Moreno, Mailyn, Juan Pavón, and Alejandro Rosete. "Testing in Agent Oriented Methodologies." In Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02481-8_20.

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Zhao, Jingjing, Xingtong Liu, Afeng Yang, and Chun Du. "Foundry Material Design with Artificial Intelligence." In Intelligent Computing Methodologies. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-09339-0_45.

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Rawat, Dhruv, Amit Kumar, and Suresh Kumar. "A Secure Electronic Voting System Using Decentralized Computing." In Distributed Artificial Intelligence. CRC Press, 2020. http://dx.doi.org/10.1201/9781003038467-14.

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Fränti, Pasi, and Sami Sieranoja. "Dimensionally Distributed Density Estimation." In Artificial Intelligence and Soft Computing. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-91262-2_31.

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da Silva, André Rodrigo, Leonardo M. Rodrigues, Luciana de Oliveira Rech, and Aldelir Fernando Luiz. "RDFM: Resilient Distributed Factorization Machines." In Artificial Intelligence and Soft Computing. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-20915-5_52.

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Wall, Friederike. "Comparing Basic Design Options for Management Accounting Systems with an Agent-Based Simulation." In Distributed Computing and Artificial Intelligence. Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-00551-5_50.

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Mahmoud, Moamin A., Aida Mustapha, Mohd Sharifuddin Ahmad, Azhana Ahmad, Mohd Zaliman M. Yusoff, and Nurzeatul Hamimah Abdul Hamid. "Potential Norms Detection in Social Agent Societies." In Distributed Computing and Artificial Intelligence. Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-00551-5_51.

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Soriano, Angel, Enrique J. Bernabeu, Angel Valera, and Marina Vallés. "Collision Avoidance of Mobile Robots Using Multi-Agent Systems." In Distributed Computing and Artificial Intelligence. Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-00551-5_52.

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Lavendelis, Egons. "Multi-agent Architecture for Intelligent Insurance Systems." In Distributed Computing and Artificial Intelligence. Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-00551-5_53.

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Conference papers on the topic "Distributed Artificial Intelligence {Computing Methodologies}"

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B.S., Sagar, Niranjan S., Nithin Kashyap, and Sachin D.N. "Providing Cyber Security using Artificial Intelligence – A survey." In 2019 3rd International Conference on Computing Methodologies and Communication (ICCMC). IEEE, 2019. http://dx.doi.org/10.1109/iccmc.2019.8819719.

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Tiwari, Satyam Prasad, Ashutosh Upadhyay, and Karthikeyan S. "Artificial Intelligence based Comparative Study of Mortality Prediction." In 2020 Fourth International Conference on Computing Methodologies and Communication (ICCMC). IEEE, 2020. http://dx.doi.org/10.1109/iccmc48092.2020.iccmc-000168.

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khan, Ufaq Jeelani, Ashish oberoi, and Jasmeen Gill. "Hybrid Classfication for Heart Disease Prediction using Artificial Intelligence." In 2021 5th International Conference on Computing Methodologies and Communication (ICCMC). IEEE, 2021. http://dx.doi.org/10.1109/iccmc51019.2021.9418345.

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Wang, Danjing, and Jingkui Li. "Artificial Intelligence Aided Prediction of Building Structure Anti-seismic." In 2021 5th International Conference on Computing Methodologies and Communication (ICCMC). IEEE, 2021. http://dx.doi.org/10.1109/iccmc51019.2021.9418404.

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Lobo, Vivian Brian, Jetso Analin, Ronald Melwin Laban, and Shraddha S. More. "Convergence of Blockchain and Artificial Intelligence to Decentralize Healthcare Systems." In 2020 Fourth International Conference on Computing Methodologies and Communication (ICCMC). IEEE, 2020. http://dx.doi.org/10.1109/iccmc48092.2020.iccmc-000171.

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Ganesh, R. Senthil, K. J. Jausmin, Jenega Srilatha, R. Indumathy, Mohd Naved, and M. Ashok. "Artificial Intelligence Based Smart Facial Expression Recognition Remote Control System." In 2021 5th International Conference on Computing Methodologies and Communication (ICCMC). IEEE, 2021. http://dx.doi.org/10.1109/iccmc51019.2021.9418031.

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Yang, Yanfei. "Numerical simulation of high-temperature superconductivity and artificial intelligence-assisted visual analysis." In 2021 5th International Conference on Computing Methodologies and Communication (ICCMC). IEEE, 2021. http://dx.doi.org/10.1109/iccmc51019.2021.9418390.

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Jain, Akshat, and Shamik Tiwari. "Prediction and Visualisation of Viral Genome Antigen Using Deep Learning & Artificial Intelligence." In 2021 5th International Conference on Computing Methodologies and Communication (ICCMC). IEEE, 2021. http://dx.doi.org/10.1109/iccmc51019.2021.9418356.

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Schmidt, Rainer, Alfred Zimmermann, Barbara Keller, and Michael Mohring. "Towards Engineering Artificial Intelligence-based Applications." In 2020 IEEE 24th International Enterprise Distributed Object Computing Workshop (EDOCW). IEEE, 2020. http://dx.doi.org/10.1109/edocw49879.2020.00020.

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Huang, Zhiyuan. "Application of Artificial Intelligence System in Smart Education in Cloud Environment with Optimization Models." In 2021 5th International Conference on Computing Methodologies and Communication (ICCMC). IEEE, 2021. http://dx.doi.org/10.1109/iccmc51019.2021.9418460.

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