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Journal articles on the topic 'Computer science Machine theory'

Author: Grafiati

Published: 4 June 2021

Last updated: 10 February 2022

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1

Molina, Mario, and Filiz Garip. "Machine Learning for Sociology." Annual Review of Sociology 45, no. 1 (2019): 27–45. http://dx.doi.org/10.1146/annurev-soc-073117-041106.

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Machine learning is a field at the intersection of statistics and computer science that uses algorithms to extract information and knowledge from data. Its applications increasingly find their way into economics, political science, and sociology. We offer a brief introduction to this vast toolbox and illustrate its current uses in the social sciences, including distilling measures from new data sources, such as text and images; characterizing population heterogeneity; improving causal inference; and offering predictions to aid policy decisions and theory development. We argue that, in addition

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2

Whyman, Richard. "Physical Computational Complexity and First-order Logic." Fundamenta Informaticae 181, no. 2-3 (2021): 129–61. http://dx.doi.org/10.3233/fi-2021-2054.

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We present the concept of a theory machine, which is an atemporal computational formalism that is deployable within an arbitrary logical system. Theory machines are intended to capture computation on an arbitrary system, both physical and unphysical, including quantum computers, Blum-Shub-Smale machines, and infinite time Turing machines. We demonstrate that for finite problems, the computational power of any device characterisable by a finite first-order theory machine is equivalent to that of a Turing machine. Whereas for infinite problems, their computational power is equivalent to that of

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Chen, Yijia, Jörg Flum, and Martin Grohe. "Machine-based methods in parameterized complexity theory." Theoretical Computer Science 339, no. 2-3 (2005): 167–99. http://dx.doi.org/10.1016/j.tcs.2005.02.003.

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Blum, Manuel, and Lenore Blum. "A Theoretical Computer Science Perspective on Consciousness." Journal of Artificial Intelligence and Consciousness 08, no. 01 (2021): 1–42. http://dx.doi.org/10.1142/s2705078521500028.

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The quest to understand consciousness, once the purview of philosophers and theologians, is now actively pursued by scientists of many stripes. This paper studies consciousness from the perspective of theoretical computer science. It formalizes the Global Workspace Theory (GWT) originated by the cognitive neuroscientist Bernard Baars and further developed by him, Stanislas Dehaene, and others. Our major contribution lies in the precise formal definition of a Conscious Turing Machine (CTM), also called a Conscious AI. We define the CTM in the spirit of Alan Turing’s simple yet powerful definiti

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Galinkin, Erick. "Review of The Foundations of Computability Theory (Second Edition) by Borut Robič." ACM SIGACT News 52, no. 2 (2021): 7–9. http://dx.doi.org/10.1145/3471469.3471472.

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Computability theory forms the foundation for much of theoretical computer science. Many of our great unsolved questions stem from the need to understand what problems can even be solved. The greatest question of computer science, P vs. NP, even sidesteps this entirely, asking instead how efficiently we can find solutions for the problems that we know are solvable. For many students both at the undergraduate and graduate level, a first exposure to computability theory follows a standard sequence on data structures and algorithms and students often marvel at the first results they see on undeci

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House, Brian. "Machine Listening." A Peer-Reviewed Journal About 6, no. 1 (2017): 16–24. http://dx.doi.org/10.7146/aprja.v6i1.116008.

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Beyond the sub-field of computer science concerned with the extraction of meaningful information from audio data, that term "machine listening" invokes the knotty questions of what it is to listen, what (if anything) separates listening by machines and by humans, and how listening is entangled with the materiality of the voice. The timely emergence of WaveNet is provocative regarding each of these—it is, perhaps more than anything else, a listening machine. Furthermore, it reveals the limits of a media materialist approach to sonicity, as exemplified by Wolfgang Ernst, when it comes to media t

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Resma, KS, GS Sharvani, and Ramasubbareddy Somula. "Optimization of cloud load balancing using fitness function and duopoly theory." International Journal of Intelligent Computing and Cybernetics 14, no. 2 (2021): 198–217. http://dx.doi.org/10.1108/ijicc-11-2020-0176.

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PurposeCurrent industrial scenario is largely dependent on cloud computing paradigms. On-demand services provided by cloud data centre are paid as per use. Hence, it is very important to make use of the allocated resources to the maximum. The resource utilization is highly dependent on the allocation of resources to the incoming request. The allocation of requests is done with respect to the physical machines present in the datacenter. While allocating the tasks to these physical machines, it needs to be allocated in such a way that no physical machine is underutilized or over loaded. To make

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Sokolov, I. A. "Theory and practice in artificial intelligence." Вестник Российской академии наук 89, no. 4 (2019): 365–70. http://dx.doi.org/10.31857/s0869-5873894365-370.

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Artificial Intelligence is an interdisciplinary field, and formed about 60 years ago as an interaction between mathematical methods, computer science, psychology, and linguistics. Artificial Intelligence is an experimental science and today features a number of internally designed theoretical methods: knowledge representation, modeling of reasoning and behavior, textual analysis, and data mining. Within the framework of Artificial Intelligence, novel scientific domains have arisen: non-monotonic logic, description logic, heuristic programming, expert systems, and knowledge-based software engin

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Németh, Zoltán, and Miklós Kuczmann. "State space modeling theory of induction machines." Pollack Periodica 15, no. 1 (2020): 124–35. http://dx.doi.org/10.1556/606.2020.15.1.12.

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Abstract The paper discusses the theoretical background of the state space modeling of induction machines. The main goal is to present the necessary equations of the induction machine and the topic of the state space modeling. Although the induction machine is a highly non-linear system, LPV/qLPV model can be formulated from these equations.

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10

Grier, D. A. "The great machine theory of history." IEEE Annals of the History of Computing 25, no. 3 (2003): 96–95. http://dx.doi.org/10.1109/mahc.2003.1226668.

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11

Lim, Daniel. "Philosophy through Machine Learning." Teaching Philosophy 43, no. 1 (2020): 29–46. http://dx.doi.org/10.5840/teachphil202018116.

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In a previous article (2019), I motivated and defended the idea of teaching philosophy through computer science. In this article, I will further develop this idea and discuss how machine learning can be used for pedagogical purposes because of its tight affinity with philosophical issues surrounding induction. To this end, I will discuss three areas of significant overlap: (i) good / bad data and David Hume’s so-called Problem of Induction, (ii) validation and accommodation vs. prediction in scientific theory selection and (iii) feature engineering and Nelson Goodman’s so-called New Riddle of

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Börger, Egon, and Klaus-Dieter Schewe. "A Behavioural Theory of Recursive Algorithms." Fundamenta Informaticae 177, no. 1 (2020): 1–37. http://dx.doi.org/10.3233/fi-2020-1978.

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“What is an algorithm?” is a fundamental question of computer science. Gurevich’s behavioural theory of sequential algorithms (aka the sequential ASM thesis) gives a partial answer by defining (non-deterministic) sequential algorithms axiomatically, without referring to a particular machine model or programming language, and showing that they are captured by (nondeterministic) sequential Abstract State Machines (nd-seq ASMs). However, recursive algorithms such as mergesort are not covered by this theory, as has been pointed out by Moschovakis, who had independently developed a different framew

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Boccia Artieri, Giovanni. "Analogie e mimesi tra scienze computazionali e sociologia: l'Intelligenza Artificiale in Achille Ardigň." SALUTE E SOCIETÀ, no. 2 (September 2009): 85–98. http://dx.doi.org/10.3280/ses2009-su2005.

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- This essay is about the 80th-90th Italian sociological context when the second order cybernetic and the theory of the complexity introduced a new perspective. That context produced a convergence between social sciences and Artificial Intelligence (AI) theory. The paper focuses on 3 perspectives: 1. the sociocultural change: AI is a cultural approach that produces an imaginary about the mutation introduced by the informatic evolution. It opens people's concerns and hopes about the relation between "man" and cybernetic "machine". 2. The analogy between the theory that produces intelligence mac

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Knop, A., S. Lovett, S. McGuire, and W. Yuan. "Guest Column." ACM SIGACT News 52, no. 2 (2021): 46–70. http://dx.doi.org/10.1145/3471469.3471479.

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Communication complexity studies the amount of communication necessary to compute a function whose value depends on information distributed among several entities. Yao [Yao79] initiated the study of communication complexity more than 40 years ago, and it has since become a central eld in theoretical computer science with many applications in diverse areas such as data structures, streaming algorithms, property testing, approximation algorithms, coding theory, and machine learning. The textbooks [KN06,RY20] provide excellent overviews of the theory and its applications.

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Gordon, M. J. C. "Tactics for mechanized reasoning: a commentary on Milner (1984) ‘The use of machines to assist in rigorous proof’." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 373, no. 2039 (2015): 20140234. http://dx.doi.org/10.1098/rsta.2014.0234.

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Robin Milner's paper, ‘The use of machines to assist in rigorous proof’, introduces methods for automating mathematical reasoning that are a milestone in the development of computer-assisted theorem proving. His ideas, particularly his theory of tactics, revolutionized the architecture of proof assistants. His methodology for automating rigorous proof soundly, particularly his theory of type polymorphism in programing, led to major contributions to the theory and design of programing languages. His citation for the 1991 ACM A.M. Turing award, the most prestigious award in computer science, cre

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Liangong, Song, Wu Huixin, and Zhang Zezhong. "Support Vector Machine Prediction Model Based on Chaos Theory." International Journal of Multimedia and Ubiquitous Engineering 11, no. 2 (2016): 173–84. http://dx.doi.org/10.14257/ijmue.2016.11.2.18.

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SUN, MINGHE. "A MULTI-CLASS SUPPORT VECTOR MACHINE: THEORY AND MODEL." International Journal of Information Technology & Decision Making 12, no. 06 (2013): 1175–99. http://dx.doi.org/10.1142/s0219622013500338.

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A multi-class support vector machine (M-SVM) is developed, its dual is derived, its dual is mapped to high dimensional feature spaces using inner product kernels, and its performance is tested. The M-SVM is formulated as a quadratic programming model. Its dual, also a quadratic programming model, is very elegant and is easier to solve than the primal. The discriminant functions can be directly constructed from the dual solution. By using inner product kernels, the M-SVM can be built and nonlinear discriminant functions can be constructed in high dimensional feature spaces without carrying out

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Horsman, D. C. "Abstraction/Representation Theory for heterotic physical computing." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 373, no. 2046 (2015): 20140224. http://dx.doi.org/10.1098/rsta.2014.0224.

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We give a rigorous framework for the interaction of physical computing devices with abstract computation. Device and program are mediated by the non-logical representation relation ; we give the conditions under which representation and device theory give rise to commuting diagrams between logical and physical domains, and the conditions for computation to occur. We give the interface of this new framework with currently existing formal methods, showing in particular its close relationship to refinement theory, and the implications for questions of meaning and reference in theoretical computer

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Palade, Vasile, and J. Gerard Wolff. "A Roadmap for the Development of the ‘SP Machine’ for Artificial Intelligence." Computer Journal 62, no. 11 (2019): 1584–604. http://dx.doi.org/10.1093/comjnl/bxy126.

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AbstractThis paper describes a roadmap for the development of the SP Machine, based on the SP Theory of Intelligence and its realization in the SP Computer Model. The SP Machine will be developed initially as a software virtual machine with high levels of parallel processing, hosted on a high-performance computer. The system should help users visualize knowledge structures and processing. Research is needed into how the system may discover low-level features in speech and in images. Strengths of the SP System in the processing of natural language may be augmented, in conjunction with the furth

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Grasso, Emanuele, Marco Palmieri, Riccardo Mandriota, Francesco Cupertino, Matthias Nienhaus, and Stephan Kleen. "Analysis and Application of the Direct Flux Control Sensorless Technique to Low-Power PMSMs." Energies 13, no. 6 (2020): 1453. http://dx.doi.org/10.3390/en13061453.

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In the field of sensorless control of permanent magnet synchronous motors (PMSMs), different techniques based on machine anisotropies have been studied and implemented successfully. Nevertheless, most proposed approaches extract the rotor position information from the measured machine currents, that, when applied to low-power machines, might require high-bandwidth current sensors. An interesting alternative is given by sensorless techniques that exploit the star-point voltage of PMSMs, such as the direct flux control technique. This work aims at analyzing the conditions of applicability of suc

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Kaunang, Fergie Joanda, and Jacquline Waworundeng. "Implementation of Finite State Automata in an Amusement Park Automatic Ticket Selling Machine." Abstract Proceedings International Scholars Conference 7, no. 1 (2019): 1776–85. http://dx.doi.org/10.35974/isc.v7i1.1979.

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Introduction: Amusement Park is a place that provides various attractions for entertainment purpose. People can enjoy games, rides such as roller coaster rides, merry-go-round, etc. Over the time, technology has grown. Many things that are usually done manually by humans are now being replaced by computers. With an automated ticket selling machine, the process of buying the ticket of an amusement park becomes easier for the user. Automata theory is a theoretical branch that has not been widely known to many yet plays essential role in the field of computer science. The main concept of automata

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QUECKE, GERHARD. "ENVIRONMENTS FOR PARALLEL ARCHITECTURES." International Journal of Modern Physics C 04, no. 01 (1993): 121–25. http://dx.doi.org/10.1142/s0129183193000136.

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This paper describes the facilities of the Laboratory for Parallel Systems at Germany's national institute for computer science. It gives an overview of the parallel machines installed in the laboratory, the environment they are embedded in and their usage, especially the usage of the Connection Machine.

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Welch, Philip. "Characterisations of variant transfinite computational models: Infinite time Turing, ordinal time Turing, and Blum–Shub–Smale machines." Computability 10, no. 2 (2021): 159–80. http://dx.doi.org/10.3233/com-200301.

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We consider how changes in transfinite machine architecture can sometimes alter substantially their capabilities. We approach the subject by answering three open problems touching on: firstly differing halting time considerations for machines with multiple as opposed to single heads, secondly space requirements, and lastly limit rules. We: 1) use admissibility theory, Σ 2 -codes and Π 3 -reflection properties in the constructible hierarchy to classify the halting times of ITTMs with multiple independent heads; the same for Ordinal Turing Machines which have On length tapes; 2) determine which

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Ejaz, Farukh, Muhammad Hussain, Hamad Almohamedh, Khalid M. Alhamed, Rana Alabdan, and Sultan Almotairi. "Dominating Topological Analysis and Comparison of the Cellular Neural Network." Mathematical Problems in Engineering 2021 (April 16, 2021): 1–9. http://dx.doi.org/10.1155/2021/6613433.

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Graph theory is a discrete branch of mathematics for designing and predicting a network. Some topological invariants are mathematical tools for the analysis of connection properties of a particular network. The Cellular Neural Network (CNN) is a computer paradigm in the field of machine learning and computer science. In this article we have given a close expression to dominating invariants computed by the dominating degree for a cellular neural network. Moreover, we have also presented a 3D comparison between dominating invariants and classical degree-based indices to show that, in some cases,

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Currin, Andrew, Konstantin Korovin, Maria Ababi, et al. "Computing exponentially faster: implementing a non-deterministic universal Turing machine using DNA." Journal of The Royal Society Interface 14, no. 128 (2017): 20160990. http://dx.doi.org/10.1098/rsif.2016.0990.

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The theory of computer science is based around universal Turing machines (UTMs): abstract machines able to execute all possible algorithms. Modern digital computers are physical embodiments of classical UTMs. For the most important class of problem in computer science, non-deterministic polynomial complete problems, non-deterministic UTMs (NUTMs) are theoretically exponentially faster than both classical UTMs and quantum mechanical UTMs (QUTMs). However, no attempt has previously been made to build an NUTM, and their construction has been regarded as impossible. Here, we demonstrate the first

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TARASOV, VASILY E. "QUANTUM NANOTECHNOLOGY." International Journal of Nanoscience 08, no. 04n05 (2009): 337–44. http://dx.doi.org/10.1142/s0219581x09005517.

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Nanotechnology is based on manipulations of individual atoms and molecules to build complex atomic structures. Quantum nanotechnology is a broad concept that deals with a manipulation of individual quantum states of atoms and molecules. Quantum nanotechnology differs from nanotechnology as a quantum computer differs from a classical molecular computer. The nanotechnology deals with a manipulation of quantum states in bulk rather than individually. In this paper, we define the main notions of quantum nanotechnology. Quantum analogs of assemblers, replicators and self-reproducing machines are di

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Concolato, Claude E., and Li M. Chen. "Data Science: A New Paradigm in the Age of Big-Data Science and Analytics." New Mathematics and Natural Computation 13, no. 02 (2017): 119–43. http://dx.doi.org/10.1142/s1793005717400038.

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As an emergent field of inquiry, Data Science serves both the information technology world and the applied sciences. Data Science is a known term that tends to be synonymous with the term Big-Data; however, Data Science is the application of solutions found through mathematical and computational research while Big-Data Science describes problems concerning the analysis of data with respect to volume, variation, and velocity (3V). Even though there is not much developed in theory from a scientific perspective for Data Science, there is still great opportunity for tremendous growth. Data Science

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Sundar, S. Shyam. "Rise of Machine Agency: A Framework for Studying the Psychology of Human–AI Interaction (HAII)." Journal of Computer-Mediated Communication 25, no. 1 (2020): 74–88. http://dx.doi.org/10.1093/jcmc/zmz026.

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Abstract Advances in personalization algorithms and other applications of machine learning have vastly enhanced the ease and convenience of our media and communication experiences, but they have also raised significant concerns about privacy, transparency of technologies and human control over their operations. Going forth, reconciling such tensions between machine agency and human agency will be important in the era of artificial intelligence (AI), as machines get more agentic and media experiences become increasingly determined by algorithms. Theory and research should be geared toward a dee

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Eldakhly, Nabil Mohamed, Magdy Aboul-Ela, and Areeg Abdalla. "A Novel Approach of Weighted Support Vector Machine with Applied Chance Theory for Forecasting Air Pollution Phenomenon in Egypt." International Journal of Computational Intelligence and Applications 17, no. 01 (2018): 1850001. http://dx.doi.org/10.1142/s1469026818500013.

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The particulate matter air pollutant of diameter less than 10 micrometers (PM[Formula: see text]), a category of pollutants including solid and liquid particles, can be a health hazard for several reasons: it can harm lung tissues and throat, aggravate asthma and increase respiratory illness. Accurate prediction models of PM[Formula: see text] concentrations are essential for proper management, control, and making public warning strategies. Therefore, machine learning techniques have the capability to develop methods or tools that can be used to discover unseen patterns from given data to solv

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Grosz, Barbara. "What Question Would Turing Pose Today?" AI Magazine 33, no. 4 (2012): 73. http://dx.doi.org/10.1609/aimag.v33i4.2441.

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In 1950, when Turing proposed to replace the question "Can machines think?" with the question "Are there imaginable digital computers which would do well in the imitation game?" computer science was not yet a field of study, Shannon’s theory of information had just begun to change the way people thought about communication, and psychology was only starting to look beyond behaviorism. It is stunning that so many predictions in Turing’s 1950 Mind paper were right. In the decades since that paper appeared, with its inspiring challenges, research in computer science, neuroscience, and the behavior

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COSNARD, MICHEL, and AFONSO FERREIRA. "ON THE REAL POWER OF LOOSELY COUPLED PARALLEL ARCHITECTURES." Parallel Processing Letters 01, no. 02 (1991): 103–11. http://dx.doi.org/10.1142/s0129626491000057.

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We propose new models of SIMD distributed memory parallel computers. We define concurrent read/write access also for machines other than PRAM. Our goal is to unify the description of abstract models of parallel machines with the aim of building a complexity theory where all models can be soundly compared. As an example, we introduce the Hypercube Random Access Machine with concurrent read/write capabilities, and show that it can solve some problems faster than the PRAM.

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Hwang, Inkwon, and Massoud Pedram. "Hierarchical, Portfolio Theory-Based Virtual Machine Consolidation in a Compute Cloud." IEEE Transactions on Services Computing 11, no. 1 (2018): 63–77. http://dx.doi.org/10.1109/tsc.2016.2531672.

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Li, Jun-Qing, Quan-Ke Pan, and Sheng-Xian Xie. "A hybrid variable neighborhood search algorithm for solving multi-objective flexible job shop problems." Computer Science and Information Systems 7, no. 4 (2010): 907–30. http://dx.doi.org/10.2298/csis090608017l.

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In this paper, we propose a novel hybrid variable neighborhood search algorithm combining with the genetic algorithm (VNS+GA) for solving the multi-objective flexible job shop scheduling problems (FJSPs) to minimize the makespan, the total workload of all machines, and the workload of the busiest machine. Firstly, a mix of two machine assignment rules and two operation sequencing rules are developed to create high quality initial solutions. Secondly, two adaptive mutation rules are used in the hybrid algorithm to produce effective perturbations in machine assignment component. Thirdly, a speed

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Hoey, Jesse, Tobias Schröder, Jonathan Morgan, Kimberly B. Rogers, Deepak Rishi, and Meiyappan Nagappan. "Artificial Intelligence and Social Simulation: Studying Group Dynamics on a Massive Scale." Small Group Research 49, no. 6 (2018): 647–83. http://dx.doi.org/10.1177/1046496418802362.

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Recent advances in artificial intelligence and computer science can be used by social scientists in their study of groups and teams. Here, we explain how developments in machine learning and simulations with artificially intelligent agents can help group and team scholars to overcome two major problems they face when studying group dynamics. First, because empirical research on groups relies on manual coding, it is hard to study groups in large numbers (the scaling problem). Second, conventional statistical methods in behavioral science often fail to capture the nonlinear interaction dynamics

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Gao, Xiaochun, and Shin-Min Song. "Body Vibration of a Legged Walking Machine." Journal of Mechanical Design 115, no. 4 (1993): 856–62. http://dx.doi.org/10.1115/1.2919279.

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Unlike wheeled vehicles, compliance in walking machine systems changes due to the variation of leg geometry, as its body proceeds. This variation in compliance will cause vibration, even if external loads remain constant. A theory is thus developed to predict the body vibrations of a walking machine during walking. On the other hand, dynamic foot forces under body vibrations can be computed by application of the existing numerical methods. As an example, the body vibrations of a quadrupedal walking chair under different walking conditions are simulated in terms of the developed theory. The res

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TRIPICCIONE, RAFFAELE. "DEDICATED COMPUTERS FOR LATTICE GAUGE THEORY SIMULATIONS." International Journal of Modern Physics C 04, no. 02 (1993): 425–33. http://dx.doi.org/10.1142/s012918319300046x.

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I discuss several features of lattice gauge theory simulations that have been exploited by dedicated processors to achieve extremely high computing speed. I describe in some details APE100, one such machine, and discuss the possible use of dedicated processors in other areas of computational physics.

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PIC, MARC MICHEL, and HASSANE ESSAFI. "WAVELET TRANSFORM ON CONNECTION MACHINE AND SYMPATI 2." International Journal of Modern Physics C 04, no. 01 (1993): 97–103. http://dx.doi.org/10.1142/s0129183193000100.

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The time of computation of Wavelet Transform on classic computers limits its applications in several area of signal processing and data compression. A parallel algorithm to compute the Wavelet Transform is presented in this paper and is ported on two parallel computers: a Connection–Machine 2 and a SYMPATI 2 line–processor.

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Moslemnejad, Somaye, and Javad Hamidzadeh. "Weighted support vector machine using fuzzy rough set theory." Soft Computing 25, no. 13 (2021): 8461–81. http://dx.doi.org/10.1007/s00500-021-05773-7.

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SCHILLING, KLAUS. "THE CONNECTION MACHINE IN A UNIVERSITY ENVIRONMENT: GESAMTHOCHSCHULE WUPPERTAL." International Journal of Modern Physics C 04, no. 01 (1993): 137–41. http://dx.doi.org/10.1142/s012918319300015x.

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A short account is presented on the early history, the intentions and the development of large scale parallel computing at the University of Wuppertal. It might serve as an illustration how common activities between computational and computer science can be stimulated, in the university environment.

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Sergiyenko, Oleg, Wendy Flores-Fuentes, Julio C. Rodríguez-Quiñónez, Moisés Rivas-López, and Lars Lindner. "Control theory and signal processing in machine vision for navigation." International Journal of Advanced Robotic Systems 17, no. 4 (2020): 172988142092647. http://dx.doi.org/10.1177/1729881420926470.

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Burscher, Bjorn, Rens Vliegenthart, and Claes H. De Vreese. "Using Supervised Machine Learning to Code Policy Issues." ANNALS of the American Academy of Political and Social Science 659, no. 1 (2015): 122–31. http://dx.doi.org/10.1177/0002716215569441.

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Content analysis of political communication usually covers large amounts of material and makes the study of dynamics in issue salience a costly enterprise. In this article, we present a supervised machine learning approach for the automatic coding of policy issues, which we apply to news articles and parliamentary questions. Comparing computer-based annotations with human annotations shows that our method approaches the performance of human coders. Furthermore, we investigate the capability of an automatic coding tool, which is based on supervised machine learning, to generalize across context

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SWARZTRAUBER, PAUL N. "THE COMMUNICATION MACHINE." International Journal of High Speed Computing 12, no. 01 (2004): 69–82. http://dx.doi.org/10.1142/s0129053304000207.

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Yan, Liang, Lei Zhang, Zongxia Jiao, Hongjie Hu, Chin-Yin Chen, and I.-Ming Chen. "A tubular linear machine with dual Halbach array." Engineering Computations 31, no. 2 (2014): 177–200. http://dx.doi.org/10.1108/ec-01-2013-0022.

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Purpose – Force output is extremely important for electromagnetic linear machines. The purpose of this study is to explore new permanent magnet (PM) array and winding patterns to increase the magnetic flux density and thus to improve the force output of electromagnetic tubular linear machines. Design/methodology/approach – Based on investigations on various PM patterns, a novel dual Halbach PM array is proposed in this paper to increase the radial component of flux density in three-dimensional machine space, which in turn can increase the force output of tubular linear machine significantly. T

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FATMI, H. A., P. J. MARCER, M. JESSEL, and G. RESCONI. "THEORY OF CYBERNETIC AND INTELLIGENT MACHINE BASED ON LIE COMMUTATORS." International Journal of General Systems 16, no. 2 (1990): 123–64. http://dx.doi.org/10.1080/03081079008935070.

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Chen, Ziheng, and Hongshik Ahn. "Item Response Theory Based Ensemble in Machine Learning." International Journal of Automation and Computing 17, no. 5 (2020): 621–36. http://dx.doi.org/10.1007/s11633-020-1239-y.

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Chehaibou, Bilal, Michael Badawi, Tomáš Bučko, Timur Bazhirov, and Dario Rocca. "Computing RPA Adsorption Enthalpies by Machine Learning Thermodynamic Perturbation Theory." Journal of Chemical Theory and Computation 15, no. 11 (2019): 6333–42. http://dx.doi.org/10.1021/acs.jctc.9b00782.

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Yang, Li, and Abdallah Shami. "On hyperparameter optimization of machine learning algorithms: Theory and practice." Neurocomputing 415 (November 2020): 295–316. http://dx.doi.org/10.1016/j.neucom.2020.07.061.

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Jones, R. E., J. A. Templeton, C. M. Sanders, and J. T. Ostien. "Machine Learning Models of Plastic Flow Based on Representation Theory." Computer Modeling in Engineering & Sciences 117, no. 3 (2018): 309–42. http://dx.doi.org/10.31614/cmes.2018.04285.

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ZHANG, LI, WEIDA ZHOU, and LICHENG JIAO. "SUPPORT VECTOR MACHINES BASED ON THE ORTHOGONAL PROJECTION KERNEL OF FATHER WAVELET." International Journal of Computational Intelligence and Applications 05, no. 03 (2005): 283–303. http://dx.doi.org/10.1142/s1469026805001489.

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Recently the study on the theory of wavelets shows that the wavelets have not only the multi-resolution property both in frequency and time domain, but also the good approximation ability. SVMs based on the statistical learning theory are a kind of general and effective learning machines, and have described for us the nice application blueprint in machine learning domain. There exists a bottleneck problem, or the pre-selection of kernel parameter for SVMs. In this paper, the orthogonal projection kernels of father wavelet (OPFW kernels) are introduced into SVMs. In doing so SVMs based on the O

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Jiang, Yiwei, Zhiyi Tan, and Yong He. "Preemptive Machine Covering on Parallel Machines." Journal of Combinatorial Optimization 10, no. 4 (2005): 345–63. http://dx.doi.org/10.1007/s10878-005-4923-5.

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