Auswahl der wissenschaftlichen Literatur zum Thema „MIIC algorithm“
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Zeitschriftenartikel zum Thema "MIIC algorithm"
Weyerer, Veronika, Pamela L. Strissel, Reiner Strick, Danijel Sikic, Carol I. Geppert, Simone Bertz, Fabienne Lange et al. „Integration of Spatial PD-L1 Expression with the Tumor Immune Microenvironment Outperforms Standard PD-L1 Scoring in Outcome Prediction of Urothelial Cancer Patients“. Cancers 13, Nr. 10 (12.05.2021): 2327. http://dx.doi.org/10.3390/cancers13102327.
Der volle Inhalt der QuelleTinnathi, Sreenivasu, und G. Sudhavani. „Copy-Move Forgery Detection Using Superpixel Clustering Algorithm and Enhanced GWO Based AlexNet Model“. Cybernetics and Information Technologies 22, Nr. 4 (01.11.2022): 91–110. http://dx.doi.org/10.2478/cait-2022-0041.
Der volle Inhalt der QuellePourkashani, Ava, Asadollah Shahbahrami und Alireza Akoushideh. „Copy-move forgery detection using convolutional neural network and K-mean clustering“. International Journal of Electrical and Computer Engineering (IJECE) 11, Nr. 3 (01.06.2021): 2604. http://dx.doi.org/10.11591/ijece.v11i3.pp2604-2612.
Der volle Inhalt der QuelleZheng, Qingyuan, Zhengyu Jiang, Xinmiao Ni, Song Yang, Panpan Jiao, Jiejun Wu, Lin Xiong et al. „Machine Learning Quantified Tumor-Stroma Ratio Is an Independent Prognosticator in Muscle-Invasive Bladder Cancer“. International Journal of Molecular Sciences 24, Nr. 3 (01.02.2023): 2746. http://dx.doi.org/10.3390/ijms24032746.
Der volle Inhalt der QuelleYe, Qing, Ruochen Wang, Chi Zhang und Yingfeng Cai. „Research on Intelligent Vehicle Path Tracking with Subsystems Based on Multimodel Intelligent Hierarchical Control Theory“. Mathematical Problems in Engineering 2021 (09.06.2021): 1–15. http://dx.doi.org/10.1155/2021/7448517.
Der volle Inhalt der QuelleAmiri, Ehsan, Ahmad Mosallanejad und Amir Sheikhahmadi. „Copy-Move Forgery Detection Using an Equilibrium Optimization Algorithm (CMFDEOA)“. Statistics, Optimization & Information Computing 11, Nr. 3 (20.04.2023): 677–84. http://dx.doi.org/10.19139/soic-2310-5070-1511.
Der volle Inhalt der QuelleElaskily, Mohamed A., Monagi H. Alkinani, Ahmed Sedik und Mohamed M. Dessouky. „Deep learning based algorithm (ConvLSTM) for Copy Move Forgery Detection“. Journal of Intelligent & Fuzzy Systems 40, Nr. 3 (02.03.2021): 4385–405. http://dx.doi.org/10.3233/jifs-201192.
Der volle Inhalt der QuelleRajamani, Sripriya, Aaron Bieringer, Stephanie Wallerius, Daniel Jensen, Tamara Winden und Miriam Halstead Muscoplat. „Direct and Electronic Health Record Access to the Clinical Decision Support for Immunizations in the Minnesota Immunization Information System“. Biomedical Informatics Insights 8s2 (Januar 2016): BII.S40208. http://dx.doi.org/10.4137/bii.s40208.
Der volle Inhalt der QuelleLi, Qianmu, Shunmei Meng, Xiaonan Sang, Hanrui Zhang, Shoujin Wang, Ali Kashif Bashir, Keping Yu und Usman Tariq. „Dynamic Scheduling Algorithm in Cyber Mimic Defense Architecture of Volunteer Computing“. ACM Transactions on Internet Technology 21, Nr. 3 (09.06.2021): 1–33. http://dx.doi.org/10.1145/3408291.
Der volle Inhalt der QuelleJue Fu, Ying Zhang,. „Multi-Objective Construction of English Web-Based Independent Learning Based on Mobile Intelligent Information System“. Journal of Electrical Systems 20, Nr. 3s (04.04.2024): 574–86. http://dx.doi.org/10.52783/jes.1332.
Der volle Inhalt der QuelleDissertationen zum Thema "MIIC algorithm"
Li, Honghao. „Interpretable biological network reconstruction from observational data“. Electronic Thesis or Diss., Université Paris Cité, 2021. http://www.theses.fr/2021UNIP5207.
Der volle Inhalt der QuelleThis thesis is focused on constraint-based methods, one of the basic types of causal structure learning algorithm. We use PC algorithm as a representative, for which we propose a simple and general modification that is applicable to any PC-derived methods. The modification ensures that all separating sets used during the skeleton reconstruction step to remove edges between conditionally independent variables remain consistent with respect to the final graph. It consists in iterating the structure learning algorithm while restricting the search of separating sets to those that are consistent with respect to the graph obtained at the end of the previous iteration. The restriction can be achieved with limited computational complexity with the help of block-cut tree decomposition of the graph skeleton. The enforcement of separating set consistency is found to increase the recall of constraint-based methods at the cost of precision, while keeping similar or better overall performance. It also improves the interpretability and explainability of the obtained graphical model. We then introduce the recently developed constraint-based method MIIC, which adopts ideas from the maximum likelihood framework to improve the robustness and overall performance of the obtained graph. We discuss the characteristics and the limitations of MIIC, and propose several modifications that emphasize the interpretability of the obtained graph and the scalability of the algorithm. In particular, we implement the iterative approach to enforce separating set consistency, and opt for a conservative rule of orientation, and exploit the orientation probability feature of MIIC to extend the edge notation in the final graph to illustrate different causal implications. The MIIC algorithm is applied to a dataset of about 400 000 breast cancer records from the SEER database, as a large-scale real-life benchmark
Vojtíšek, Jindřich. „Analýza šifrovacích algoritmů ve standardu 802.11“. Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2014. http://www.nusl.cz/ntk/nusl-220648.
Der volle Inhalt der QuelleYe, Fan. „Nouveaux algorithmes numériques pour l’utilisation efficace des architectures multi-cœurs et hétérogènes“. Thesis, Lille 1, 2015. http://www.theses.fr/2015LIL10169/document.
Der volle Inhalt der QuelleThis study is driven by the real computational needs coming from different fields of reactor physics, such as neutronics or thermal hydraulics, where the eigenvalue problem and resolution of linear system are the key challenges that consume substantial computing resources. In this context, our objective is to design and improve the parallel computing techniques, including proposing efficient linear algebraic kernels and parallel numerical methods. In a shared-memory environment such as the Intel Many Integrated Core (MIC) system, the parallelization of an algorithm is achieved in terms of fine-grained task parallelism and data parallelism. For scheduling the tasks, two main policies, the work-sharing and work-stealing was studied. For the purpose of generality and reusability, we use common parallel programming interfaces, such as OpenMP, Cilk/Cilk+, and TBB. For vectorizing the task, the available tools include Cilk+ array notation, SIMD pragmas, and intrinsic functions. We evaluated these techniques and propose an efficient dense matrix-vector multiplication kernel. In order to tackle a more complicated situation, we propose to use hybrid MPI/OpenMP model for implementing sparse matrix-vector multiplication. We also designed a performance model for characterizing performance issues on MIC and guiding the optimization. As for solving the linear system, we derived a scalable parallel solver from the Monte Carlo method. Such method exhibits inherently abundant parallelism, which is a good fit for many-core architecture. To address some of the fundamental bottlenecks of this solver, we propose a task-based execution model that completely fixes the problems
Zgheib, Rawad. „Algorithmes adaptatifs d'identification et de reconstruction de processus AR à échantillons manquants“. Phd thesis, Université Paris Sud - Paris XI, 2007. http://tel.archives-ouvertes.fr/tel-00273585.
Der volle Inhalt der QuelleErmolenko, Evgenii. „Algorithm-aided Information Design: Hybrid Design approach on the edge of associative methodologies in AEC“. Master's thesis, 2020. http://hdl.handle.net/1822/74793.
Der volle Inhalt der QuelleLast three decades have brought colossal progress to design methodologies within the common pursuit toward a seamless fusion between digital and physical worlds and augmenting it with the of computation power and network coverage. For this historically short period, two generations of methodologies and tools have emerged: Additive generation and parametric Associative generation of CAD. Currently, designers worldwide engaged in new forms of design exploration. From this race, two prominent methodologies have developed from Associative Design approach – Object-Oriented Design (OOD) and Algorithm-Aided Design (AAD). The primary research objective is to investigate, examine, and push boundaries between OOD and AAD for new design space determination, where advantages of both design methods are fused to produce a new generation methodology which is called in the present study AID (Algorithm-aided Information Design). The study methodology is structured into two flows. In the first flow, existing CAD methodologies are investigated, and the conceptual framework is extracted based on the state of art analysis, then analysed data is synthesized into the subject proposal. In the second flow, tools and workflows are elaborated and examined on practice to confirm the subject proposal. In compliance, the content of the research consists of two theoretical and practical parts. In the first theoretical part, a literature review is conducted, and assumptions are made to speculate about AID methodology, its tools, possible advantages and drawbacks. Next, case studies are performed according to sequential stages of digital design through the lens of practical AID methodology implementation. Case studies are covering such design aspects as model & documentation generation, design automation, interoperability, manufacturing control, performance analysis and optimization. Ultimately, a set of test projects is developed with the AID methodology applied. After the practical part, research returns to the theory where analytical information is gathered based on the literature review, conceptual framework, and experimental practice reports. In summary, the study synthesizes AID methodology as part of Hybrid Design, which enables creative use of tools and elaborating of agile design systems integrating additive and associative methodologies of Digital Design. In general, the study is based on agile methods and cyclic research development mixed between practice and theory to achieve a comprehensive vision of the subject.
Last three decades have brought colossal progress to design methodologies within the common pursuit toward a seamless fusion between digital and physical worlds and augmenting it with the of computation power and network coverage. For this historically short period, two generations of methodologies and tools have emerged: Additive generation and parametric Associative generation of CAD. Currently, designers worldwide engaged in new forms of design exploration. From this race, two prominent methodologies have developed from Associative Design approach – Object-Oriented Design (OOD) and Algorithm-Aided Design (AAD). The primary research objective is to investigate, examine, and push boundaries between OOD and AAD for new design space determination, where advantages of both design methods are fused to produce a new generation methodology which is called in the present study AID (Algorithm-aided Information Design). The study methodology is structured into two flows. In the first flow, existing CAD methodologies are investigated, and the conceptual framework is extracted based on the state of art analysis, then analysed data is synthesized into the subject proposal. In the second flow, tools and workflows are elaborated and examined on practice to confirm the subject proposal. In compliance, the content of the research consists of two theoretical and practical parts. In the first theoretical part, a literature review is conducted, and assumptions are made to speculate about AID methodology, its tools, possible advantages and drawbacks. Next, case studies are performed according to sequential stages of digital design through the lens of practical AID methodology implementation. Case studies are covering such design aspects as model & documentation generation, design automation, interoperability, manufacturing control, performance analysis and optimization. Ultimately, a set of test projects is developed with the AID methodology applied. After the practical part, research returns to the theory where analytical information is gathered based on the literature review, conceptual framework, and experimental practice reports. In summary, the study synthesizes AID methodology as part of Hybrid Design, which enables creative use of tools and elaborating of agile design systems integrating additive and associative methodologies of Digital Design. In general, the study is based on agile methods and cyclic research development mixed between practice and theory to achieve a comprehensive vision of the subject.
Bücher zum Thema "MIIC algorithm"
Coolen, A. C. C., A. Annibale und E. S. Roberts. Network growth algorithms. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198709893.003.0008.
Der volle Inhalt der QuelleKolm, Petter N., und Lee Maclin. Algorithmic Trading, Optimal Execution, and Dyna Mic Port Folios. Oxford University Press, 2011. http://dx.doi.org/10.1093/oxfordhb/9780199553433.013.0017.
Der volle Inhalt der QuelleAmine, Abdelmalek, Salim Chikhi, Allaoua Chaoui, Mohamed Khireddine Kholladi und Djamel Eddine Saidouni. Modelling and Implementation of Complex Systems: Proceedings of the 6th International Symposium, MISC 2020, Batna, Algeria, October 24‐26, 2020. Springer, 2020.
Den vollen Inhalt der Quelle findenAmine, Abdelmalek, Salim Chikhi, Allaoua Chaoui und Djamel Eddine Saidouni. Modelling and Implementation of Complex Systems: Proceedings of the 5th International Symposium, MISC 2018, December 16-18, 2018, Laghouat, Algeria. Springer, 2018.
Den vollen Inhalt der Quelle findenAmine, Abdelmalek, Salim Chikhi, Allaoua Chaoui, Mohamed Khireddine Kholladi und Djamel Eddine Saidouni. Modelling and Implementation of Complex Systems: Proceedings of the 4th International Symposium, MISC 2016, Constantine, Algeria, May 7-8, 2016, ... Springer, 2016.
Den vollen Inhalt der Quelle findenDiaz-Descalzo, Gregorio, Abdelmalek Amine, Salim Chikhi, Allaoua Chaoui und Djamel Eddine Saidouni. Modelling and Implementation of Complex Systems: Proceedings of the 7th International Symposium, MISC 2022, Mostaganem, Algeria, October 30‐31 2022. Springer International Publishing AG, 2022.
Den vollen Inhalt der Quelle findenAmine, Abdelmalek, Salim Chikhi, Allaoua Chaoui, Mohamed Khireddine Kholladi und Djamel Eddine Saidouni. Modelling and Implementation of Complex Systems: Proceedings of the 4th International Symposium, MISC 2016, Constantine, Algeria, May 7-8, 2016, Constantine, Algeria. Springer London, Limited, 2016.
Den vollen Inhalt der Quelle findenGoleman, Travis. Machine Learning and Artificial Intelligence 2 Manuscripts In 1: The Essential Guide to Understand Artificial Intelligence, Machine Learning, Mimic Human Behavior, NLP Algorithms and Deep Learning. Independently Published, 2019.
Den vollen Inhalt der Quelle findenGoleman, Travis. Artificial Intelligence for Beginners: All You Have to Know about the Potential of AI in the Future, Techniques to Mimic Human Behavior, Deep Learning and NLP Algorithms. Independently Published, 2019.
Den vollen Inhalt der Quelle findenShroff, Gautam. The Intelligent Web. Oxford University Press, 2013. http://dx.doi.org/10.1093/oso/9780199646715.001.0001.
Der volle Inhalt der QuelleBuchteile zum Thema "MIIC algorithm"
Liu, Yang, und Liang Deng. „Acceleration of CFD Engineering Software on GPU and MIC“. In Algorithms and Architectures for Parallel Processing, 835–48. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-27161-3_77.
Der volle Inhalt der QuelleJu, Tao, Zhengdong Zhu, Yinfeng Wang, Liang Li und Xiaoshe Dong. „Thread Mapping and Parallel Optimization for MIC Heterogeneous Parallel Systems“. In Algorithms and Architectures for Parallel Processing, 300–311. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-11194-0_23.
Der volle Inhalt der QuelleHuang, Kun, und Yifeng Chen. „Improving Performance of Floating Point Division on GPU and MIC“. In Algorithms and Architectures for Parallel Processing, 691–703. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-27122-4_48.
Der volle Inhalt der QuelleLiang, Weihao, Hong An, Feng Li und Yichao Cheng. „Optimization of Binomial Option Pricing on Intel MIC Heterogeneous System“. In Algorithms and Architectures for Parallel Processing, 17–29. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-27137-8_2.
Der volle Inhalt der QuelleChen, Cheng, Yunfei Du, Zhen Xu und Canqun Yang. „FT-Offload: A Scalable Fault-Tolerance Programing Model on MIC Cluster“. In Algorithms and Architectures for Parallel Processing, 3–17. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-27140-8_1.
Der volle Inhalt der QuelleSzustak, Lukasz, Kamil Halbiniak, Adam Kulawik, Roman Wyrzykowski, Piotr Uminski und Marcin Sasinowski. „Using hStreams Programming Library for Accelerating a Real-Life Application on Intel MIC“. In Algorithms and Architectures for Parallel Processing, 373–82. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-49956-7_30.
Der volle Inhalt der QuelleWang, Ruping, Hui Li, Mei Chen, Zhenyu Dai und Ming Zhu. „MIC-KMeans: A Maximum Information Coefficient Based High-Dimensional Clustering Algorithm“. In Advances in Intelligent Systems and Computing, 208–18. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-91189-2_21.
Der volle Inhalt der QuelleLirkov, Ivan, Yavor Vutov, Marcin Paprzycki und Maria Ganzha. „Parallel Performance Evaluation of MIC(0) Preconditioning Algorithm for Voxel μFE Simulation“. In Parallel Processing and Applied Mathematics, 135–44. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-14403-5_15.
Der volle Inhalt der QuelleArslantas, Mustafa Kemal, Tunc Asuroglu, Reyhan Arslantas, Emin Pashazade, Pelin Corman Dincer, Gulbin Tore Altun und Alper Kararmaz. „Using Machine Learning Methods to Predict the Lactate Trend of Sepsis Patients in the ICU“. In Communications in Computer and Information Science, 3–16. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-59091-7_1.
Der volle Inhalt der QuelleSun, Wei, Shaoxiong Ji, Erik Cambria und Pekka Marttinen. „Multitask Recalibrated Aggregation Network for Medical Code Prediction“. In Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track, 367–83. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-86514-6_23.
Der volle Inhalt der QuelleKonferenzberichte zum Thema "MIIC algorithm"
Lu, Dau-Tsuong, Ramamohan Paturi, Sadik Esener und Sing H. Lee. „Parallel algorithms with irregular interconnections and optical technology“. In OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1989. http://dx.doi.org/10.1364/oam.1989.mii3.
Der volle Inhalt der QuelleNavaz, K., S. Yazhinian, N. Muthuvairavan Pillai, Neelamegam Devarasu und M. Sankar. „MXDD Scheduling Algorithm for MIBC Switches“. In 2023 International Conference on System, Computation, Automation and Networking (ICSCAN). IEEE, 2023. http://dx.doi.org/10.1109/icscan58655.2023.10395457.
Der volle Inhalt der QuelleKo, Ching Yun, Rui Lin, Shu Li und Ngai Wong. „MiSC: Mixed Strategies Crowdsourcing“. In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/193.
Der volle Inhalt der QuelleKumar, Shivesh, Marc Simnofske, Bertold Bongardt, Andreas Müller und Frank Kirchner. „Integrating Mimic Joints into Dynamics Algorithms“. In the Advances in Robotics. New York, New York, USA: ACM Press, 2017. http://dx.doi.org/10.1145/3132446.3134891.
Der volle Inhalt der QuelleTuncel, Mehmet, Ahmet Duran, M. Serdar Celebi, Bora Akaydin und Figen O. Topkaya. „A comparison of SuperLU solvers on the intel MIC architecture“. In NUMERICAL COMPUTATIONS: THEORY AND ALGORITHMS (NUMTA–2016): Proceedings of the 2nd International Conference “Numerical Computations: Theory and Algorithms”. Author(s), 2016. http://dx.doi.org/10.1063/1.4965394.
Der volle Inhalt der QuelleJunling Li, Bohu Liang und Xiaodong Su. „Research on ECG signal filtering algorithm based on the fusion of multiple algorithms“. In 2012 International Conference on Measurement, Information and Control (MIC). IEEE, 2012. http://dx.doi.org/10.1109/mic.2012.6273273.
Der volle Inhalt der QuelleNeupane, Aadesh, und Michael Goodrich. „Learning Swarm Behaviors using Grammatical Evolution and Behavior Trees“. In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/73.
Der volle Inhalt der QuelleJu, Tao, Xiaoshe Dong, Endong Wang, Liang Li und Zhengdong Zhu. „Parallel Optimization Strategies for MIC Heterogeneous Parallel Systems“. In 2014 Sixth International Symposium on Parallel Architectures, Algorithms and Programming (PAAP). IEEE, 2014. http://dx.doi.org/10.1109/paap.2014.39.
Der volle Inhalt der QuelleChangfei, Zhou, Lu Kai, Chi Wanqing, Wang Xiaoping und Xiong Zhenhai. „MIC Acceleration of Saliency Detection Algorithm“. In 1st International Workshop on Cloud Computing and Information Security. Paris, France: Atlantis Press, 2013. http://dx.doi.org/10.2991/ccis-13.2013.73.
Der volle Inhalt der QuelleWu, Zhaoqi, und Jin Wei. „Heterogeneous Executors Scheduling Algorithm for Mimic Defense Systems“. In 2019 IEEE 2nd International Conference on Computer and Communication Engineering Technology (CCET). IEEE, 2019. http://dx.doi.org/10.1109/ccet48361.2019.8989231.
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