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Статті в журналах з теми "AMP ALGORITHM"

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Kparib, Douglas Yenwon, John Awuah Addor, and Anthony Joe Turkson. "A Comprehensive Comparison of Label Setting Algorithm and Dynamic Programming Algorithm in Solving Shortest Path Problems." Journal of Mathematics Research 13, no. 5 (September 21, 2021): 14. http://dx.doi.org/10.5539/jmr.v13n5p14.

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In this paper, Label Setting Algorithm and Dynamic Programming Algorithm had been critically examined in determining the shortest path from one source to a destination. Shortest path problems are for finding a path with minimum cost from one or more origin (s) to one or more destination(s) through a connected network. A network of ten (10) cities (nodes) was employed as a numerical example to compare the performance of the two algorithms. Both algorithms arrived at the optimal distance of 11 km, which corresponds to the paths 1→4→5→8→10 ,1→3→5→8→10 , 1→2→6→9→10  and  1→4→6→9→10 . Thus, the problem has multiple shortest paths. The computational results evince the outperformance of Dynamic Programming Algorithm, in terms of time efficiency, over the Label Setting Algorithm. Therefore, to save time, it is recommended to apply Dynamic Programming Algorithm to shortest paths and other applicable problems over the Label-Setting Algorithm.
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Dahiya, Tripti, Nakul Vashishth, Deepika Garg, Avinash K. Shrivastava, and P. K. Kapur. "Novel Heuristic Algorithm & its Application for Reliability Optimization." International Journal of Mathematical, Engineering and Management Sciences 8, no. 4 (August 1, 2023): 755–68. http://dx.doi.org/10.33889/ijmems.2023.8.4.043.

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Heuristic algorithms are practical, easy to implement, and work fast to provide short-term, feasible solutions for any kind of problem within economical budgets as compared to other meta-heuristic algorithms. This paper presents a novel heuristic algorithm named the Dahiya-Garg Heuristic Algorithm (DG-Alg) to find the optimal solution for constrained reliability redundancy allocation optimization problems. The cornerstone of the novel DG-Alg is its novel selection factor, which is a mathematical formula that helps the heuristic algorithm search for optimal subsystems for reliability optimization. A novel formulated selection factor in DG-Alg has increased its effectiveness and efficiency. To analyze the performance of the proposed heuristic algorithm and the other three existing heuristic algorithms, they are applied to a problem taken from a pharmaceutical manufacturing plant named Yaris Pharmaceuticals. During the application of the heuristic algorithms, it was ensured that redundancy allocation was done within stipulated cost constraints. Further, a comparative analysis of the obtained results has been done to judge the performance of the proposed heuristic algorithm. It is deduced that the proposed heuristic algorithm gives optimized and computationally efficient results in comparison to the other existing heuristic algorithms.
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Kanagasabai, Lenin. "Two bio-inspired algorithms for solving optimal reactive power problem." International Journal of Advances in Applied Sciences 9, no. 3 (September 1, 2020): 180. http://dx.doi.org/10.11591/ijaas.v9.i3.pp180-185.

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<span>In this work two ground-breaking algorithms called; Sperm Motility (SM) algorithm &amp; Wolf Optimization (WO) algorithm is used for solving reactive power problem. In sperm motility approach spontaneous movement of the sperm is imitated &amp; species chemo attractant, sperms are enthralled in the direction of the ovum. In wolf optimization algorithm the deeds of wolf is imitated in the formulation &amp; it has a flag vector also length is equivalent to the whole sum of numbers in the dataset the optimization. Both the projected algorithms have been tested in standard IEEE 57,118, 300 bus test systems. Simulated outcomes reveal about the reduction of real power loss &amp; with variables are in the standard limits. Almost both algorithms solved the problem efficiently, yet wolf optimization has slight edge over the sperm motility algorithm in reducing the real power loss.</span>
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Gajawada, Satish, and Hassan M. H. Mustafa. "Out of the Box Artificial Intelligence (OBAI): The Beginning of a New Era in Artificial Intelligence." Computer and Information Science 15, no. 2 (February 14, 2022): 6. http://dx.doi.org/10.5539/cis.v15n2p6.

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The main purpose of writing this article is to unify all the OUT OF THE BOX ideas (under Artificial Intelligence) invented by the corresponding author of this work during the period (2013-2022) under a single umbrella titled &ldquo;Out of the BOX Artificial Intelligence Field (OBAI Field)&rdquo;. All the OUT OF THE BOX ideas which are proposed under Artificial Intelligence will come under new field titled OBAI Field which is defined in this work. A new Artificial Intelligence field titled &ldquo;Artificial Cartoon Algorithms (ACA)&rdquo; is invented in this work. ACA is a sub-field of OBAI field as it is an OUT OF THE BOX idea. Four new algorithms titled &ldquo;Artificial Cartoon Popeye Algorithm&rdquo;, &ldquo;Artificial Cartoon Chhota Bheem Algorithm&rdquo;, &ldquo;Artificial Cartoon Jerry Algorithm&rdquo; and &ldquo;Artificial Cartoon Happy Kid Algorithm&rdquo; are designed in this work.
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Roy, Shyamal Kumar. "Design and Analysis of P&O algorithm based MPPT solar system in PSIM." YMER Digital 21, no. 06 (June 30, 2022): 1188–94. http://dx.doi.org/10.37896/ymer21.06/b4.

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Conventional solar panels suffer with non-identical losses (resistive losses, diode leakage, loss of material properties etc.). To overcome these unwanted phenomena, a solar maximum power point tracking (MPPT) algorithm has been introduced. In this paper, the algorithms used for tracking the sun (or the solar maximum power point tracking algorithm) has been introduced & a brief description of the basic & easiest algorithm i.e., the P&O Algorithm using PSIM software has been provided to give a clear view about the concept & implementation of MPPT. Keywords: Photovoltaic, MPPT, P&O, PSIM
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Arıcı, FerdaNur, and Ersin Kaya. "Comparison of Meta-heuristic Algorithms on Benchmark Functions." Academic Perspective Procedia 2, no. 3 (November 22, 2019): 508–17. http://dx.doi.org/10.33793/acperpro.02.03.41.

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Optimization is a process to search the most suitable solution for a problem within an acceptable time interval. The algorithms that solve the optimization problems are called as optimization algorithms. In the literature, there are many optimization algorithms with different characteristics. The optimization algorithms can exhibit different behaviors depending on the size, characteristics and complexity of the optimization problem. In this study, six well-known population based optimization algorithms (artificial algae algorithm - AAA, artificial bee colony algorithm - ABC, differential evolution algorithm - DE, genetic algorithm - GA, gravitational search algorithm - GSA and particle swarm optimization - PSO) were used. These six algorithms were performed on the CEC&amp;rsquo;17 test functions. According to the experimental results, the algorithms were compared and performances of the algorithms were evaluated.
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Dr Asha Ambhaikar, Mr Abhishek Guru,. "AES AND RSA-BASED HYBRID ALGORITHMS FOR MESSAGE ENCRYPTION & DECRYPTION." INFORMATION TECHNOLOGY IN INDUSTRY 9, no. 1 (March 1, 2021): 273–79. http://dx.doi.org/10.17762/itii.v9i1.129.

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File encryption is an easy means of securing personal or business data protection. The RSA and AES representative encryption algorithms are not capable of satisfying the criteria of file encryption reliability and security when used separately. A hybrid encryption algorithm mixing AES and RSA algorithms is suggested in this paper to overcome the above issues in order to solve file encryption performance and security problems. The experimental results suggest that the RSA and AES hybrid encryption algorithm can not only encrypt files, but also provide the benefits of efficiency and protection of the algorithm.
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Chaibou, Amadou, Ousmane Moussa Tessa, and Oumarou Sié. "Modeling the Parallelization of the Edmonds-Karp Algorithm and Application." Computer and Information Science 12, no. 3 (July 25, 2019): 81. http://dx.doi.org/10.5539/cis.v12n3p81.

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Many optimization problems can be reduced to the maximum flow problem in a network. However, the maximum flow problem is equivalent to the problem of the minimum cut, as shown by Fulkerson and Ford (Fulkerson &amp; Ford, 1956). There are several algorithms of the graph&rsquo;s cut, such as the Ford-Fulkerson algorithm (Ford &amp; Fulkerson, 1962), the Edmonds-Karp algorithm (Edmonds &amp; Karp, 1972) or the Goldberg-Tarjan algorithm (Goldberg &amp; Tarjan, 1988). In this paper, we study the parallel computation of the Edmonds-Karp algorithm which is an optimized version of the Ford-Fulkerson algorithm. Indeed, this algorithm, when executed on large graphs, can be extremely slow, with a complexity of the order of O|V|.|E|2 (where |V| designates the number of vertices and |E| designates the number of the edges of the graph). So why we are studying its implementation on inexpensive parallel platforms such as OpenMp and GP-GPU. Our work also highlights the limits for parallel computing on this algorithm.
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HEJDUCKI, Zdzisław, and Michał PODOLSKI. "SCHEDULING OF CONSTRUCTION PROJECTS WITH APPLICATION OF METAHEURISTIC ALGORITHMS." Scientific Journal of the Military University of Land Forces 166, no. 4 (October 1, 2012): 68–79. http://dx.doi.org/10.5604/01.3001.0002.3530.

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The paper presents the authors’ research on the application of metaheuristic algorithms in Time Coupling Methods (TCM). The experimental analysis of algorithms: tabu search, genetic search, simulated annealing and B&amp;amp;B algorithm was conducted in the paper. The application of these algorithms, which are currently used to solve job scheduling problems, allows one to obtain better suboptimal solutions than with the currently used B&amp;amp;B algorithm. The main branch of the authors’ research is developing the methodology of construction works scheduling with the application of TCM 17,8,9 1013. The problems of scheduling linear construction works using time-cost optimisation are worked out.
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Javidian, Mohammad Ali, Marco Valtorta, and Pooyan Jamshidi. "AMP Chain Graphs: Minimal Separators and Structure Learning Algorithms." Journal of Artificial Intelligence Research 69 (October 7, 2020): 419–70. http://dx.doi.org/10.1613/jair.1.12101.

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This paper deals with chain graphs (CGs) under the Andersson–Madigan–Perlman (AMP) interpretation. We address the problem of finding a minimal separator in an AMP CG, namely, finding a set Z of nodes that separates a given non-adjacent pair of nodes such that no proper subset of Z separates that pair. We analyze several versions of this problem and offer polynomial time algorithms for each. These include finding a minimal separator from a restricted set of nodes, finding a minimal separator for two given disjoint sets, and testing whether a given separator is minimal. To address the problem of learning the structure of AMP CGs from data, we show that the PC-like algorithm is order dependent, in the sense that the output can depend on the order in which the variables are given. We propose several modifications of the PC-like algorithm that remove part or all of this order-dependence. We also extend the decomposition-based approach for learning Bayesian networks (BNs) to learn AMP CGs, which include BNs as a special case, under the faithfulness assumption. We prove the correctness of our extension using the minimal separator results. Using standard benchmarks and synthetically generated models and data in our experiments demonstrate the competitive performance of our decomposition-based method, called LCD-AMP, in comparison with the (modified versions of) PC-like algorithm. The LCD-AMP algorithm usually outperforms the PC-like algorithm, and our modifications of the PC-like algorithm learn structures that are more similar to the underlying ground truth graphs than the original PC-like algorithm, especially in high-dimensional settings. In particular, we empirically show that the results of both algorithms are more accurate and stabler when the sample size is reasonably large and the underlying graph is sparse
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Дисертації з теми "AMP ALGORITHM"

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Dementiev, Roman. "Algorithm engineering for large data sets : hardware, software, algorithms /." Saarbrücken : VDM-Verl. Dr. Müller, 2007. http://deposit.d-nb.de/cgi-bin/dokserv?id=3029033&prov=M&dok_var=1&dok_ext=htm.

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Nallagandla, Shilpa. "Radix 2 division algorithm /." Available to subscribers only, 2006. http://proquest.umi.com/pqdweb?did=1251871361&sid=5&Fmt=2&clientId=1509&RQT=309&VName=PQD.

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Jonas, Mario Ricardo Edward. "High performance computing and algorithm development: application of dataset development to algorithm parameterization." Thesis, University of the Western Cape, 2006. http://etd.uwc.ac.za/index.php?module=etd&amp.

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A number of technologies exist that captures data from biological systems. In addition, several computational tools, which aim to organize the data resulting from these technologies, have been created. The ability of these tools to organize the information into biologically meaningful results, however, needs to be stringently tested. The research contained herein focuses on data produced by technology that records short Expressed Sequence Tags (EST's).
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Han, Tony. "SWASAD Smith & Waterman-algorithm-specific ASIC design /." St. Lucia, Qld, 2001. http://www.library.uq.edu.au/pdfserve.php?image=thesisabs/absthe16391.pdf.

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Alweh, Mohammad. "Robust algorithm for WiFi network /." Available to subscribers only, 2006. http://proquest.umi.com/pqdweb?did=1136091901&sid=6&Fmt=2&clientId=1509&RQT=309&VName=PQD.

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Konda, Lakshmana Rao. "An empirical study of TJFast algorithm /." Available to subscribers only, 2006. http://proquest.umi.com/pqdweb?did=1240708321&sid=12&Fmt=2&clientId=1509&RQT=309&VName=PQD.

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McLoone, M. P. "Generic silicon architectures for encryption algorithm." Thesis, Queen's University Belfast, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.269123.

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Kreslins, Karlis. "A stemming algorithm for Latvian." Thesis, Loughborough University, 1996. https://dspace.lboro.ac.uk/2134/7433.

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The thesis covers construction, application and evaluation of a stemming algorithm for advanced information searching and retrieval in Latvian databases. Its aim is to examine the following two questions: Is it possible to apply for Latvian a suffix removal algorithm originally designed for English? Can stemming in Latvian produce the same or better information retrieval results than manual truncation? In order to achieve these aims, the role and importance of automatic word conflation both for document indexing and information retrieval are characterised. A review of literature, which analyzes and evaluates different types of stemming techniques and retrospective development of stemming algorithms, justifies the necessity to apply this advanced IR method also for Latvian. Comparative analysis of morphological structure both for English and Latvian language determined the selection of Porter's suffix removal algorithm as a basis for the Latvian sternmer. An extensive list of Latvian stopwords including conjunctions, particles and adverbs, was designed and added to the initial sternmer in order to eliminate insignificant words from further processing. A number of specific modifications and changes related to the Latvian language were carried out to the structure and rules of the original stemming algorithm. Analysis of word stemming based on Latvian electronic dictionary and Latvian text fragments confirmed that the suffix removal technique can be successfully applied also to Latvian language. An evaluation study of user search statements revealed that the stemming algorithm to a certain extent can improve effectiveness of information retrieval.
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Kassapakis, E. G. "Studies on a predictive control algorithm." Thesis, University of Reading, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.360726.

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Hounsinou, Sena Gladys N. "Hardware realization of speech-time warping algorithm /." Available to subscribers only, 2008. http://proquest.umi.com/pqdweb?did=1650508391&sid=1&Fmt=2&clientId=1509&RQT=309&VName=PQD.

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Книги з теми "AMP ALGORITHM"

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Kim, Jaeseok, and Hyunchul Shin, eds. Algorithm & SoC Design for Automotive Vision Systems. Dordrecht: Springer Netherlands, 2014. http://dx.doi.org/10.1007/978-94-017-9075-8.

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Troiano, Luigi, Alfredo Vaccaro, Nishtha Kesswani, Irene Díaz Rodriguez, and Imene Brigui, eds. Progresses in Artificial Intelligence & Robotics: Algorithms & Applications. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-98531-8.

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Manichev, Vladimir, Valentina Glazkova, and Кузьмина Анастасия. Numerical methods. The authentic and exact solution of the differential and algebraic equations in SAE systems of SAPR. ru: INFRA-M Academic Publishing LLC., 2016. http://dx.doi.org/10.12737/13138.

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In the manual classical numerical methods are considered and algorithms for the decision of systems of the ordinary differential equations (ODE), nonlinear and linear algebraic equations (NAU and LAU), and also ways of ensuring reliability and demanded accuracy of results of the decision. Ideas, which still not are stated are reflected in textbooks on calculus mathematics, namely: decision systems the ODE without reduction to a normal form of Cauchy resolved rather derivative, and refusal from any numerical an equivalent - nykh of transformations of the initial equations of mathematical models and is- the hodnykh of data because such transformations can change properties of models at a variation of coefficients in corresponding urav- neniyakh. It is intended for students, graduate students and teachers of higher education institutions in the direction of preparation &#34;Informatics and computer facilities&#34;. The grant will also be useful for engineers and scientists on the corresponding specialties.
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El-Habash, N. A. Final report of frontal barrier impacts of a 1985 Pontiac Grand AM 2-door coupe in support of Crash III damage algorithm reformation. [Washington, D.C.]: U.S. Dept. of Transportation, National Highway Traffic Safety Administration, 1988.

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Brown, Gavin, and Richard Whittle. Algorithms, Blockchain & Cryptocurrency: Implications for the Future of the Workplace. Emerald Publishing Limited, 2020. http://dx.doi.org/10.1108/9781838674953.

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Bag-of-Words Algorithms Can Supplement Transformer Sequence Classification & Improve Model Interpretability. RAND Corporation, 2022. http://dx.doi.org/10.7249/wra1719-1.

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Berger, Franz X., Anne Deremetz, Martin Hennig, and Alix Michell, eds. Autonomie und Verantwortung in digitalen Kulturen. Academia – ein Verlag in der Nomos Verlagsgesellschaft, 2021. http://dx.doi.org/10.5771/9783896659378.

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The increasing complexity of networked systems casts doubt on the self-determination in the digital sphere. Externally predetermined algorithms and practices of third-party data processing raise questions as to the protection of and the danger to autonomy and the freedom of expression. At the same time, the legal, political, ethical, social, and economic responsibility for the consequences of digital transformation processes for societies, collectives, and individuals remains undetermined. Precisely in this field, the present interdisciplinary volume would like to stimulate a discussion on responsibilities and impact assessments; in which regard, it researches problems in digital cultures, tackles possible solutions, and discusses conflicts of economic, political, and social systems. With contributions by Anna K. Bernzen, Barbara Büttner & Carsten Ochs, Stephan Dreyer, Hans-Christian Gräfe & Andrea Hamm, Hermann Jakobi & Elizaveta Saponchik, Thomas Krämer-Badoni & Jens Crueger, Wulf Loh, Tim Raupach & Phillip Siedenburg, Caroline Richter & Christian Lenk, Alexander Schiff, Julia Schröder, Lea Watzinger and Florian Wittner
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Michel, Bierlaire. Optimization: Principles and Algorithms. EPFL Press, 2015. http://dx.doi.org/10.55430/6116v1mb.

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Every engineer and decision scientist must have a good mastery of optimization, an essential element in their toolkit. Thus, this articulate introductory textbook will certainly be welcomed by students and practicing professionals alike. Drawing from his vast teaching experience, the author skillfully leads the reader through a rich choice of topics in a coherent, fluid and tasteful blend of models and methods anchored on the underlying mathematical notions (only prerequisites: first year calculus and linear algebra). Topics range from the classics to some of the most recent developments in smooth unconstrained and constrained optimization, like descent methods, conjugate gradients, Newton and quasi-Newton methods, linear programming and the simplex method, trust region and interior point methods. Furthermore elements of discrete and combinatorial optimization like network optimization, integer programming and heuristic local search methods are also presented. This book presents optimization as a modeling tool that beyond supporting problem formulation plus design and implementation of efficient algorithms, also is a language suited for interdisciplinary human interaction. Readers further become aware that while the roots of mathematical optimization go back to the work of giants like Newton, Lagrange, Cauchy, Euler or Gauss, it did not become a discipline on its own until World War Two. Also that its present momentum really resulted from its symbiosis with modern computers, which made it possible to routinely solve problems with millions of variables and constraints. With his witty, entertaining, yet precise style, Michel Bierlaire captivates his readers and awakens their desire to try out the presented material in a creative mode. One of the outstanding assets of this book is the unified, clear and concise rendering of the various algorithms, which makes them easily readable and translatable into any high level programming language. ''This is an addictive book that I am very pleased to recommend.'' Prof. Thomas M. Liebling
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The Monte Carlo Method in the Physical Sciences: Celebrating the 50th Anniversary of the Metropolis Algorithm (AIP Conference Proceedings). American Institute of Physics, 2003.

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Michopoulos, John G., Christiaan J. J. Paredis, David W. Rosen, and Judy M. Vance. Advances in Computers and Information in Engineering Research, Volume 2. ASME, 2021. http://dx.doi.org/10.1115/1.862025.

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Book Series Editorial Board John Michopoulos, Naval Research Laboratory David Rosen, Georgia Institute of Technology Chris Paredis, Georgia Institute of Technology Judy Vance, Iowa State University This is the second volume in this book series that aims to capture advances in computers and information in engineering research, especially by researchers and members of ASME’s Computers & Information in Engineering (CIE) Division. The series is focusing on advances in computational methods, algorithms, tools, and processes on the cutting edge of research and development as they have evolved and/or have been reported during the last three to five annual CIE conferences. The series will provide a resource for enhancing engineering practice by enabling the understanding and the application of evolving and emerging technologies that impact critical engineering issues related to the topics and themes under CIE’s technical committees areas of interest, but not limited to: Advanced Modeling and Simulation; Computer-Aided Product and Process Development; Systems Engineering, Information and Knowledge Management; Virtual Environments and Systems.
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Частини книг з теми "AMP ALGORITHM"

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Mudumbai, Raghuraman, Soura Dasgupta, and M. Muhammad Mahboob Ur Rahman. "Analysis of a Distributed Consensus Based Economic Dispatch Algorithm." In Systems & Control: Foundations & Applications, 481–500. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-04630-9_14.

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Lin, Chen-Hsuan, Rui Zhu, and Simon Lucey. "The Conditional Lucas & Kanade Algorithm." In Computer Vision – ECCV 2016, 793–808. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-46454-1_48.

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Datta, Debabrata. "Optimization Methods Using Music-Inspired Algorithm and Its Comparison with Nature-Inspired Algorithm." In Springer Proceedings in Mathematics & Statistics, 271–82. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-0597-3_19.

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Bartel, Fabian, H. Vrenken, Marcel van Herk, Michiel B. de Ruiter, Jose Belderbos, Joost Hulshof, and Jan C. de Munck. "Semi-automatic hippocampus delineation algorithm using surface fairing." In EMBEC & NBC 2017, 956–59. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-5122-7_239.

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Asadujjaman, Md, Humyun Fuad Rahman, Ripon K. Chakrabortty, and Michael J. Ryan. "Surrogate-assisted Genetic Algorithm for Multi-project Scheduling." In Intelligent Computing & Optimization, 87–97. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-19958-5_9.

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Hooshmand, F., and S. A. MirHassani. "Efficient DC Algorithm for the Index-Tracking Problem." In Intelligent Computing & Optimization, 566–76. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-93247-3_56.

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Torres-Escobar, Rafael, José Antonio Marmolejo-Saucedo, Igor Litvinchev, and Pandian Vasant. "Monkey Algorithm for Packing Circles with Binary Variables." In Intelligent Computing & Optimization, 547–59. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-00979-3_58.

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Libal, Urszula, and Zygmunt Hasiewicz. "Wavelet Algorithm for Hierarchical Pattern Recognition." In Springer Proceedings in Mathematics & Statistics, 391–98. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-13881-7_43.

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Kamiński, Bogumił, Paweł Prałat, and François Théberge. "Community Detection Algorithm Using Hypergraph Modularity." In Complex Networks & Their Applications IX, 152–63. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-65347-7_13.

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Cho, Shinil. "Metropolis–Hastings Algorithm for Ising Model." In Synthesis Lectures on Mathematics & Statistics, 93–121. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-33886-1_5.

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Тези доповідей конференцій з теми "AMP ALGORITHM"

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A. P. Wickramarathna, M. T., and Nalin Wickramaarachchi. "Transmission Network Planning Using Genetic Algorithm." In 2006 IEEE/PES Transmission & Distribution Conference & Exposition: Latin America. IEEE, 2006. http://dx.doi.org/10.1109/tdcla.2006.311550.

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Tournier, Jean-Charles, and Martin Naef. "Influences of SIMD architectures for scattered data interpolation algorithm." In amp; Software (ISPASS 2010). IEEE, 2010. http://dx.doi.org/10.1109/ispass.2010.5452056.

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E. Nunzi. "Characterization of &amp;#916;&amp;#931; Converters by Means of the Sine-fit Algorithm." In 2006 IEEE Instrumentation and Measurement Technology. IEEE, 2006. http://dx.doi.org/10.1109/imtc.2006.234873.

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Sharma, Mukta, R. B. Garg, and Surbhi Dwivedi. "Comparative analysis of NPN algorithm & DES Algorithm." In 2014 3rd International Conference on Reliability, Infocom Technologies and Optimization (ICRITO) (Trends and Future Directions). IEEE, 2014. http://dx.doi.org/10.1109/icrito.2014.7014688.

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Thombre, Ritu, and Babita Jajodia. "Experimental Analysis of Attacks on RSA & Rabin Cryptosystems using Quantum Shor’s Algorithm." In International Conference on Women Researchers in Electronics and Computing. AIJR Publisher, 2021. http://dx.doi.org/10.21467/proceedings.114.74.

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Анотація:
In this world of massive communication networks, data security and confidentiality are of crucial importance for maintaining secured private communication and protecting information against eavesdropping attacks. Existing cryptosystems provide data security and confidentiality by the use of encryption and signature algorithms for secured communication. Classical computers use cryptographic algorithms that use the product of two large prime numbers for generating public and private keys. These classical algorithms are based on the fact that integer factorization is a non-deterministic polynomial-time (NP) problem and requires super-polynomial time making it impossible for large enough integers. Shor’s algorithm is a well-known algorithm for factoring large integers in polynomial time and takes only O(b3) time and O(b) space on b-bit number inputs. Shor’s algorithm poses a potential threat to the current security system with the ongoing advancements of Quantum computers. This paper discusses how Shor’s algorithm will be able to break integer factorization-based cryptographic algorithms, for example, Rivest–Shamir–Adleman (RSA) and Rabin Algorithms. As a proof of concept, experimental analysis of Quantum Shor’s algorithm on existing public-key cryptosystems using IBM Quantum Experience is performed for factorizing integers of moderate length (seven bits) due to limitations of thirty-two qubits in present IBM quantum computers. In a nutshell, this work will demonstrate how Shor’s algorithm poses threat to confidentiality and authentication services.
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Zeng, Chuanhua, and Yu Wu. "Emergency resources scheduling model & algorithm." In 2013 Fourth Global Congress on Intelligent Systems (GCIS). IEEE, 2013. http://dx.doi.org/10.1109/gcis.2013.29.

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Shokri, M., H. R. Tizhoosh, and M. Kamel. "Opposition-Based Q(&#955;) Algorithm." In The 2006 IEEE International Joint Conference on Neural Network Proceedings. IEEE, 2006. http://dx.doi.org/10.1109/ijcnn.2006.246689.

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Verleker, Ashwin Prabhu, and Suneeta Agarwal. "D&C Fast Exponentiation Algorithm." In 2009 International Conference on Advances in Computing, Control, & Telecommunication Technologies (ACT 2009). IEEE, 2009. http://dx.doi.org/10.1109/act.2009.166.

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Bendjoudi, A., M. Chekini, M. Gharbi, M. Mehdi, K. Benatchba, F. Sitayeb-Benbouzid, and N. Melab. "Parallel B&amp;B Algorithm for Hybrid Multi-core/GPU Architectures." In 2013 IEEE International Conference on High Performance Computing and Communications (HPCC) & 2013 IEEE International Conference on Embedded and Ubiquitous Computing (EUC). IEEE, 2013. http://dx.doi.org/10.1109/hpcc.and.euc.2013.130.

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Hajihashemi, M. R., and M. El-Shenawee. "MPI parallelization of the level-set reconstruction algorithm." In amp; USNC/URSI National Radio Science Meeting. IEEE, 2009. http://dx.doi.org/10.1109/aps.2009.5172175.

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Звіти організацій з теми "AMP ALGORITHM"

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Gubaydullina, Zulian, Jan René Judek, Marco Lorenz, and Markus Spiwoks. Gestaltungswille und Algorithm Aversion – Die Auswirkungen der Einflussnahme im Prozess der algorithmischen Entscheidungsfindung auf die Algorithm Aversion. Sonderforschungsgruppe Instituionenanalyse, June 2021. http://dx.doi.org/10.46850/sofia.9783941627925.

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Анотація:
Obwohl Algorithmen in vielen Anwendungsgebieten präzisere Prognosen abgeben als Menschen, weigern sich Entscheidungsträger häufig, auf Algorithmen zurückzugreifen. In einem ökonomischen Experiment untersuchen wir, ob das Ausmaß dieses als „Algorithm Aversion“ bekannten Phänomens reduziert werden kann, indem Entscheidungsträgern eine Einflussmöglichkeit auf die Ausgestaltung des Algorithmus eingeräumt wird (Einflussmöglichkeit auf den algorithmischen Input). Zusätzlich replizieren wir die Studie von Dietvorst, Simmons & Massey (2018). Darin zeigt sich, dass die Algorithm Aversion deutlich zurückgeht, sofern die Subjekte am Ende die Ergebnisse des Algorithmus – und sei es nur um wenige Prozent – verändern können (Einflussmöglichkeit auf den algorithmischen Output). In der vorliegenden Studie bestätigt sich, dass die Algorithm Aversion bei einer Einflussmöglichkeit auf den algorithmischen Output signifikant zurückgeht. Eine Einflussmöglichkeit auf den algorithmischen Input scheint allerdings nur bedingt geeignet, die Algorithm Aversion zu reduzieren. Die begrenzte Möglichkeit zur Modifikation des algorithmischen Outputs reduziert die Algorithm Aversion effektiver als die Möglichkeit, Einfluss auf den algorithmischen Input zu nehmen.
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Bodson, D. Simulation and Evaluation of the AT&T Proposed Pattern Recognition Algorithm for Group 4 Facsimile. Fort Belvoir, VA: Defense Technical Information Center, June 1985. http://dx.doi.org/10.21236/ada160864.

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Kelma, Virginia. Numerical Algorithms & Parallel Tasking. Fort Belvoir, VA: Defense Technical Information Center, September 1985. http://dx.doi.org/10.21236/ada162221.

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Diefenthaler, Markus, J. Bernauer, D. Blyth, C. Cuevas, A. Farhat, W. Gu, G. Heyes, E. Pooser, B. Raydo, and Dmitry Romanov. Evaluation & Development of Algorithms & Techniques for Streaming Detector Readout. Office of Scientific and Technical Information (OSTI), December 2020. http://dx.doi.org/10.2172/1735849.

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Martin, Daniel, and Phillip Colella. Self-gravitating AMR algorithm specification. Office of Scientific and Technical Information (OSTI), August 2003. http://dx.doi.org/10.2172/927008.

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Han, Euihong, and George Karypis. Centroid-Based Document Classification Algorithms: Analysis & Experimental Results. Fort Belvoir, VA: Defense Technical Information Center, March 2000. http://dx.doi.org/10.21236/ada439538.

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Gunney, B., and A. Wissink. A Task-parallel Clustering Algorithm for Structured AMR. Office of Scientific and Technical Information (OSTI), November 2004. http://dx.doi.org/10.2172/15016415.

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Соловйов, Володимир Миколайович, Vladimir Saptsin, and Dmitry Chabanenko. Prediction of financial time series with the technology of high-order Markov chains. AGSOE, March 2009. http://dx.doi.org/10.31812/0564/1131.

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Анотація:
In this research the technology of complex Markov chains, i.e. Markov chains with a memory is applied to forecast the financial time-series. The high-order Markov chains can be simplified to first-order ones by generalizing the states in Markov chains. Considering the *generalized state* as the sequence of states makes a possibility to model high-order Markov chains like first-order ones. The adaptive method of defining the states is proposed, it is concerned with the statistic properties of price returns. The algorithm of prediction includes the next steps: (1) Generate the hierarchical set of time discretizations; (2) Reducing the discretiza- tion of initial data and doing prediction at the every time-level (3) Recurrent conjunction of prediction series of different discretizations in a single time-series. The hierarchy of time discretizations gives a possibility to review long-memory properties of the series without increasing the order of the Markov chains, to make prediction on the different frequencies of the series. The technology is tested on several time-series, including: EUR/USD Forex course, the World’s indices, including Dow Jones, S&P 500, RTS, PFTS and other.
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Demmel, James W. Extreme-Scale Algorithms & Software Resilience (EASIR) Architecture-Aware Algorithms for Scalable Performance and Resilience on Heterogeneous Architectures. Office of Scientific and Technical Information (OSTI), September 2017. http://dx.doi.org/10.2172/1395330.

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Bain, Rachel, David Young, Marin Kress, Katherine Chambers, and Brandan Scully. US port connectivity and ramifications for maintenance of South Atlantic Division ports. Engineer Research and Development Center (U.S.), January 2023. http://dx.doi.org/10.21079/11681/46385.

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Анотація:
This study utilized automatic identification system (AIS) data to quantify vessel traffic patterns within a predominantly US port network from 1 January 2009 to 31 December 2020, with the methods validated using independent data sets collected between 1 January 2015 and 31 December 2019. The analysis focused on South Atlantic Division (SAD) ports. AIS-derived data characterized individual ports’ traffic and port-to-port connectivity for the network. With foreign vessel entrances and clearances (E&C) data, the AIS-reported vessel characteristics enabled calculation of ships’ physical volume, which was a reasonable proxy for tonnage at many SAD ports. The PageRank algorithm was then applied to port-to-port traffic, revealing how individual ports participate in cargo movement through the network. PageRank scores also provided insight into the maritime supply chain beyond traditional traffic metrics. For example, many East Coast SAD ports ranked higher by PageRank than by raw tonnage. Because of the supply chain implications of shared vessel traffic, PageRank scores can augment tonnage metrics when prioritizing channel and infrastructure maintenance. Vessel volume, port-to-port connectivity, and PageRank scores reveal maritime supply chain resilience by identifying alternative destinations for cargo bound for disrupted ports, robustness across supply chains, and the effects of seasonality and disruptions.
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