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Journal articles on the topic 'Computing tool'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

Kumpanya, Danupon, and Sattarpoom Thaiparnat. "Real Time Electrical Energy Computing Tool." International Journal of Advanced Culture Technology 3, no. 1 (June 30, 2015): 113–19. http://dx.doi.org/10.17703/ijact.2015.3.1.113.

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2

Mirchandani, Chandru. "Cloud Computing as a Debug Tool." Procedia Computer Science 36 (2014): 359–66. http://dx.doi.org/10.1016/j.procs.2014.09.006.

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3

Jimeno, A., and S. Cuenca. "Reconfigurable Computing for Tool-Path Computation." International Journal of Advanced Manufacturing Technology 21, no. 12 (September 1, 2003): 945–51. http://dx.doi.org/10.1007/s00170-002-1415-y.

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4

Bąk, Sławomir, Marcin Krystek, Krzysztof Kurowski, Ariel Oleksiak, Wojciech Piątek, and Jan Wąglarz. "GSSIM – A Tool for Distributed Computing Experiments." Scientific Programming 19, no. 4 (2011): 231–51. http://dx.doi.org/10.1155/2011/925395.

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In this paper we present the Grid Scheduling Simulator (GSSIM), a comprehensive and advanced simulation tool for distributed computing problems. Based on a classification of simulator features proposed in the paper, we define problems that can be simulated using GSSIM and compare it to other simulation tools. We focus on an extension of our previous works including advanced workload generation methods, simulation of a network with advance reservation features, handling specific application performance models and energy efficiency modeling. Some important features of GSSIM are demonstrated by three diverse experiments conducted with the use of the tool. We also present an advanced web tool for the remote management and execution of simulation experiments, which makes GSSIM the comprehensive distributed computing simulator available on the Web.

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Younes, Ahmed, and Moheb R. Girgis. "A tool for computing computer network reliability." International Journal of Computer Mathematics 82, no. 12 (December 2005): 1455–65. http://dx.doi.org/10.1080/0020716031000103385.

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6

Morales-A., Pedro. "Parallel computing: a tool for image evaluation." Optical Engineering 37, no. 6 (June 1, 1998): 1852. http://dx.doi.org/10.1117/1.601715.

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7

Maller, V. A. J. "Personal computing—the tool of the mind." Computing & Control Engineering Journal 1, no. 4 (1990): 146. http://dx.doi.org/10.1049/cce:19900042.

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8

Doherty, W. J., and W. G. Pope. "Computing as a tool for human augmentation." IBM Systems Journal 25, no. 3.4 (1986): 306–20. http://dx.doi.org/10.1147/sj.253.0306.

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9

Hausknotz, Ch. "Anwendungen mit dem Soft Computing Tool ECANSE." e & i Elektrotechnik und Informationstechnik 118, no. 7-8 (July 2001): 345–48. http://dx.doi.org/10.1007/bf03157837.

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10

Wišniewski, Michał. "Cloud Computing as a Tool for Improving Business Competitiveness." Foundations of Management 5, no. 3 (August 21, 2014): 75–88. http://dx.doi.org/10.2478/fman-2014-0021.

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AbstractThis article organizes knowledge on cloud computing presenting the classification of deployment models, characteristics and service models. The author, looking at the problem from the entrepreneur’s perspective, draws attention to the differences in the benefits depending on the cloud computing deployment models and considers an effective way of selection of cloud computing services according to the specificity of organization. Within this work, a thesis statement was considered that in economic terms the cloud computing is not always the best solution for your organization. This raises the question, “What kind of tools should be used to estimate the usefulness of the model cloud computing services in the enterprise?”

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Yang, Shengju. "One Implementation Method of Trust Evaluation Tool Used on Cloud Computing Service." Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering) 12, no. 3 (June 10, 2019): 223–31. http://dx.doi.org/10.2174/2352096511666180528075030.

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In order to solve the trust problems between users and cloud computing service providers in cloud computing services, the existing trust evaluation technology and access control technology in the cloud computing service are analyzed. And the evaluation index of cloud computing is also analyzed. Users can calculate the relevant indicators of cloud computing service according to their own business goals, and choose the appropriate cloud computing services according to their own trust need. In addition, the reliability assessment method of users based on the service process is proposed. Cloud computing access control system can be used for user credibility evaluation, and it can handle user access requests according to user's creditability. In the study, a cloud computing service trust evaluation tool is designed, and the modeling and architecture designs of trust evaluation are also given. The effectiveness of the method is verified by experiments on cloud computing service evaluation methods.

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12

Martin-Nielsen, Janet. "Computing the Climate." Historical Studies in the Natural Sciences 48, no. 2 (April 1, 2018): 223–45. http://dx.doi.org/10.1525/hsns.2018.48.2.223.

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This paper traces the development of numerical climate models in the United Kingdom from 1963, when the U.K.’s Meteorological Office first took up climate modelling, to the mid-to-late 1970s, when climate change became politicized in the United Kingdom. The central question posed is how U.K. climate modellers developed rhetoric, managed expectations, and weighed their professional and political responsibilities in the face of growing political interest in climate change. Whilst the modellers were reluctant to allow the modelling results to be used for political ends, U.K. civil servants saw climate modelling as a modern tool for a new problem. As scientific and political agendas diverged, the director of the Meteorological Office, John Mason, found himself caught between his position as a government employee in a service organization and his responsibility as a gatekeeper between climate models and their potential uses. Ultimately, as Mason and his modellers were forced to admit, their climate models became cultural and political as well as scientific objects.

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SarmaVittapu, Mani, Venkateswarlu Sunkari, and AtoYoseph Abate. "Synchronous CR-OLAP Tool for Efficient Parallel Computing." International Journal of Computer Applications 115, no. 17 (April 22, 2015): 1–13. http://dx.doi.org/10.5120/20240-2593.

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14

Joldeş, Iulian, Bazil Pârv, Ilie Parpucea, and Vasile Lupşe. "PyBNEq - A Tool for Computing Bayes-Nash Equilibria." International Journal of Computers Communications & Control 8, no. 4 (August 1, 2013): 571. http://dx.doi.org/10.15837/ijccc.2013.4.578.

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15

Christou, Ioannis T., Sofoklis Efremidis, and Aikaterini Roukounaki. "A CASE Tool for Java Mobile Computing Applications." International Journal of Mobile Computing and Multimedia Communications 2, no. 2 (April 2010): 34–48. http://dx.doi.org/10.4018/jmcmc.2010040103.

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The market for applications developed for mobile devices is growing as the hardware capabilities increase while costs drop. At the same time, the inability to write code once becomes a noticeable problem resulting in the time consuming task of porting an application to a variety of mobile devices, which is true for languages like Java that have been designed to be portable across a range of hardware platforms. As a result, porting a Java application written for one device to another is often a tedious and time-consuming task for developers. This paper presents an intelligent CASE tool that assists the porting of Java mobile applications by automatically generating Java code fragments for the target SDK. SeqFinder automatically generates all minimal method invocation sequences that lead to an object of a specific type, thus relieving the programmer of manually searching the manufacturer-provided SDK Java archives. However, this tool is not applicable only to the Java ME platform and has been used as a fast type-browser for J2SE/J2EE applications.

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Wu, Y., G. Graham, X. Lu, A. Afaq, B. J. Kim, and I. Fisk. "Configuration monitoring tool for large-scale distributed computing." Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 534, no. 1-2 (November 2004): 66–69. http://dx.doi.org/10.1016/j.nima.2004.07.060.

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Finch, Ralph, and Shao‐Kong Kao. "Coarse‐Grain Parallel Computing Using ISIS Tool Kit." Journal of Computing in Civil Engineering 6, no. 2 (April 1992): 233–44. http://dx.doi.org/10.1061/(asce)0887-3801(1992)6:2(233).

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18

Rui, Yong. "Deep Neural Networks: Another Tool for Multimedia Computing." IEEE MultiMedia 21, no. 4 (October 2014): 2–3. http://dx.doi.org/10.1109/mmul.2014.59.

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19

McNamara, Amelia. "Key Attributes of a Modern Statistical Computing Tool." American Statistician 73, no. 4 (September 5, 2018): 375–84. http://dx.doi.org/10.1080/00031305.2018.1482784.

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20

Attaran, Mohsen, and Sharmin Attaran. "Collaborative computing technology: the hot new managing tool." Journal of Management Development 21, no. 8 (October 2002): 598–609. http://dx.doi.org/10.1108/02621710210437572.

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Zhou, Zude, Jianmin Hu, Quan Liu, Ping Lou, Junwei Yan, and Wenfeng Li. "Fog Computing-Based Cyber-Physical Machine Tool System." IEEE Access 6 (2018): 44580–90. http://dx.doi.org/10.1109/access.2018.2863258.

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22

Arbenz, Peter, Christoph Sprenger, Hans Peter Luthi, and Stefan Vogel. "SCIDDLE: A tool for large scale distributed computing." Concurrency: Practice and Experience 7, no. 2 (April 1995): 121–46. http://dx.doi.org/10.1002/cpe.4330070203.

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23

Narayana Rao, T. Venkat, and Budati Naveen Kumar. "GNU Privacy Guard- A Tool for Safe Computing." International Journal on Recent and Innovation Trends in Computing and Communication 7, no. 4 (April 26, 2019): 12–15. http://dx.doi.org/10.17762/ijritcc.v7i4.5282.

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In the modern era, digital communications play a vital role. For an elementary security, encryption is preventing a huge number of problems. When a data is passed through many number of nodes, we don’t know what vulnerability is present at each node. Our data may be affected. GPG encryption is a tool for encrypting emails, digital materials. It uses the concept of key pairs like public key, private key. The public keys are exchanged between the sender and the receiver. The private key is kept as a secret by user. This paper focus on new GNU privacy guard which is a tool to ensure security in huge users traffic and reliable data transmission .

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24

Coe, R. D. "The Stochastic Spreadsheet: A New Statistical Computing Tool." Statistician 38, no. 2 (1989): 117. http://dx.doi.org/10.2307/2348309.

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25

Stamatakis, A., A. J. Aberer, C. Goll, S. A. Smith, S. A. Berger, and F. Izquierdo-Carrasco. "RAxML-Light: a tool for computing terabyte phylogenies." Bioinformatics 28, no. 15 (May 24, 2012): 2064–66. http://dx.doi.org/10.1093/bioinformatics/bts309.

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26

Yung, Chung, and Yu Tang Lin. "Implementing TOAST, a Tool for Agile Software Project Management in Cloud Computing Environments." Journal of Software 10, no. 11 (November 2015): 1310–18. http://dx.doi.org/10.17706//jsw.10.11.1310-131.

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27

Thomas, P. Y. "Cloud computing." Electronic Library 29, no. 2 (April 12, 2011): 214–24. http://dx.doi.org/10.1108/02640471111125177.

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PurposeThis paper aims to explore the educational potential of “cloud computing” (CC), and how it could be exploited in enhancing engagement among educational researchers and educators to better understand and improve their practice, in increasing the quality of their students' learning outcomes, and, thus, in advancing the scholarship of teaching and learning (SoTL) in a higher education context.Design/methodology/approachAdoption of the ideals of SoTL is considered an important approach for salvaging the higher education landscape around the world that is currently in a state of flux and evolution as a result of rapid advances in information and communications technology, and the subsequent changing needs of the digital natives. The study is based on ideas conceptualised from reading several editorials and articles on server virtualisation technology and cloud computing in several journals, with the eSchool News as the most important one. The paper identifies two cloud computing tools, their salient features and describes how cloud computing can be used to achieve the ideals of SoTL.FindingsThe study reports that the cloud as a ubiquitous computing tool and a powerful platform can enable educators to practise the ideals of SoTL. Two of the most useful free “cloud computing” applications are the Google Apps for Education which is a free online suite of tools that includes Gmail for e‐mail and Google Docs for documents, spreadsheets, and presentations, and Microsoft's cloud service (Live@edu) including the SkyDrive. Using the cloud approach, everybody can work on the same document at the same time to make corrections as well as improve it dynamically in a collaborative manner.Practical implicationsCloud computing has a significant place in higher education in that the appropriate use of cloud computing tools can enhance engagement among students, educators, and researchers in a cost effective manner. There are security concerns but they do not overshadow the benefits.Originality/valueThe paper provides insights into the possibility of using cloud computing delivery for originating a new instructional paradigm that makes a shift possible from the traditional practice of teaching as a private affair to a peer‐reviewed transparent process, and makes it known how student learning can be improved generally, not only in one's own classroom but also beyond it.

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28

Ichino, Kentaro. "Machine tool and method for computing attachment position of balancer in machine tool." Journal of the Acoustical Society of America 122, no. 3 (2007): 1314. http://dx.doi.org/10.1121/1.2781418.

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29

PupeikienÄ—, Lina, and Mindaugas Rybokas. "Research into a timetable forming tool for final classes." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 9, no. 2 (July 15, 2013): 1012–19. http://dx.doi.org/10.24297/ijct.v9i2.4165.

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In this paper a high-school timetable forming tool is described. Commercial products and software for this problem solving are compared. The problems of timetable forming are analyzed. A decision for initial data computing is described. A new tool for computing problems solution is described. The results of this tool are analyzed.

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30

Getov, Vladimir, Paul Gray, Sava Mintchev, and Vaidy Sunderam. "Multi-Language Programming Environments for High Performance Java Computing." Scientific Programming 7, no. 2 (1999): 139–46. http://dx.doi.org/10.1155/1999/975837.

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Recent developments in processor capabilities, software tools, programming languages and programming paradigms have brought about new approaches to high performance computing. A steadfast component of this dynamic evolution has been the scientific community’s reliance on established scientific packages. As a consequence, programmers of high‐performance applications are reluctant to embrace evolving languages such as Java. This paper describes the Java‐to‐C Interface (JCI) tool which provides application programmers wishing to use Java with immediate accessibility to existing scientific packages. The JCI tool also facilitates rapid development and reuse of existing code. These benefits are provided at minimal cost to the programmer. While beneficial to the programmer, the additional advantages of mixed‐language programming in terms of application performance and portability are addressed in detail within the context of this paper. In addition, we discuss how the JCI tool is complementing other ongoing projects such as IBM’s High‐Performance Compiler for Java (HPCJ) and IceT’s metacomputing environment.

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31

Gokulachandran, Jaganathan, and K. Mohandas. "Prediction of cutting tool life based on Taguchi approach with fuzzy logic and support vector regression techniques." International Journal of Quality & Reliability Management 32, no. 3 (March 2, 2015): 270–90. http://dx.doi.org/10.1108/ijqrm-06-2012-0084.

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Purpose – The accurate assessment of tool life of any given tool is a great significance in any manufacturing industry. The purpose of this paper is to predict the life of a cutting tool, in order to help decision making of the next scheduled replacement of tool and improve productivity. Design/methodology/approach – This paper reports the use of two soft computing techniques, namely, neuro-fuzzy logic and support vector regression (SVR) techniques for the assessment of cutting tools. In this work, experiments are conducted based on Taguchi approach and tool life values are obtained. Findings – The analysis is carried out using the two soft computing techniques. Tool life values are predicted using aforesaid techniques and these values are compared. Practical implications – The proposed approaches are relatively simple and can be implemented easily by using software like MATLAB and Weka. Originality/value – The proposed methodology compares neuro – fuzzy logic and SVR techniques.

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32

Pare, Vikas, Geeta Agnihotri, and Chimata Murali Krishna. "Optimization of Cutting Conditions in Milling Process to Minimize Tool Wear Using Selected Soft Computing Techniques: A Comparative Study." Journal of Advanced Manufacturing Systems 13, no. 01 (March 2014): 55–72. http://dx.doi.org/10.1142/s0219686714500048.

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The life of a tool is very significant in metal cutting because production time is a waste whenever a tool is replaced or reset. Because of prolonged use, cutting tools blunt and their effectiveness decreases over time. It is necessary to replace, index or resharpen, and reset the tool after certain time. Tool life is a measure of the length of time a tool will cut effectively. The life of a cutting tool is mostly affected by many factors, such as, the tool wear, material removal rate, microstructure of the material being cut, setup rigidity, and cutting fluid quality. In this paper, up-milling and down-milling are compared with respect to different input parameters mainly cutting speed, feed, and number of teeth, rake angle, and helix angle. A relationship between tool wear and these input parameters is established by using regression analysis and soft computing techniques are applied to minimize the tool wear. Five selected soft computing techniques viz. (i) Genetic Algorithm (GA), (ii) Simulated Annealing (SA), (iii) Hybrid GA with Pattern Search (PS), (iv) Particle Swarm Optimization (PSO), and (v) Threshold Acceptance Algorithm (TAA), are used for optimization of tool wear. The results obtained from each of them are also analyzed. The effect of input parameters on tool wear, the way it is different for up-milling and down-milling is addressed for each case with the help of five selected soft computing techniques. The results indicate that the tool wear is least in case of down-milling when compared to up-milling and hybrid GA gave the best results.

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Ludwig, T., M. Lindermeier, A. Stamatakis, and G. Rackl. "Tool environments in CORBA-based medical high-performance computing." Future Generation Computer Systems 18, no. 6 (May 2002): 841–47. http://dx.doi.org/10.1016/s0167-739x(02)00056-0.

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34

Muniyandi. "Membrane Computing as a Modeling Tool for Discrete Systems." Journal of Computer Science 7, no. 11 (November 1, 2011): 1667–73. http://dx.doi.org/10.3844/jcssp.2011.1667.1673.

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35

Garrad, A. D., and D. C. Quarton. "Symbolic computing as a tool in wind turbine dynamics." Journal of Sound and Vibration 109, no. 1 (August 1986): 65–78. http://dx.doi.org/10.1016/s0022-460x(86)80022-0.

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36

Gottschalk, Ingrid, and Stefan Kirn. "Cloud Computing As a Tool for Enhancing Ecological Goals?" Business & Information Systems Engineering 5, no. 5 (August 27, 2013): 299–313. http://dx.doi.org/10.1007/s12599-013-0284-2.

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37

Walker, A. M., R. P. Bruin, M. T. Dove, T. O. H. White, K. Kleese van Dam, and R. P. Tyer. "Integrating computing, data and collaboration grids: the RMCS tool." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 367, no. 1890 (December 16, 2008): 1047–50. http://dx.doi.org/10.1098/rsta.2008.0159.

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We describe RMCS as one of the first tools for grid computing that integrates data and metadata management into a single job submission system. The system is easy to use, with client tools that are easy to install. Although the RMCS system was developed as a prototype, it is now in production use and a number of scientific studies have been completed using it.

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Pecharsky, V. K. "PC - a crystallographic computing tool for experts and novices." Acta Crystallographica Section A Foundations of Crystallography 49, s1 (August 21, 1993): c51. http://dx.doi.org/10.1107/s0108767378098529.

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39

Stallworth, Clarke. "Computing, Editing on Big TV Makes Good Teaching Tool." Journalism Educator 42, no. 1 (March 1987): 46–48. http://dx.doi.org/10.1177/107769588704200115.

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Crawford, Walt. "It‘s just a tool: fifteen years of personal computing." Library Hi Tech 16, no. 2 (August 1998): 103–12. http://dx.doi.org/10.1108/07378839810303956.

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Fahringer, Thomas, Alexandru Jugravu, Sabri Pllana, Radu Prodan, Clovis Seragiotto, and Hong-Linh Truong. "ASKALON: a tool set for cluster and Grid computing." Concurrency and Computation: Practice and Experience 17, no. 2-4 (2005): 143–69. http://dx.doi.org/10.1002/cpe.929.

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Peters, J. F., S. E. Howington, J. P. Holland, F. T. Tracy, and R. S. Maier. "High performance computing as a tool for groundwater cleanup." Journal of Hydraulic Research 36, no. 6 (November 1998): 897–912. http://dx.doi.org/10.1080/00221689809498592.

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Yuan, J., G. Rochau, and G. A. Moses. "A Graphical Tool for Computing Opacities for ICF Applications." International Journal of Modelling and Simulation 23, no. 4 (January 2003): 218–25. http://dx.doi.org/10.1080/02286203.2003.11442275.

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Calin-Jageman, Robert J., and Paul S. Katz. "A Distributed Computing Tool for Generating Neural Simulation Databases." Neural Computation 18, no. 12 (December 2006): 2923–27. http://dx.doi.org/10.1162/neco.2006.18.12.2923.

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After developing a model neuron or network, it is important to systematically explore its behavior across a wide range of parameter values or experimental conditions, or both. However, compiling a very large set of simulation runs is challenging because it typically requires both access to and expertise with high-performance computing facilities. To lower the barrier for large-scale model analysis, we have developed NeuronPM, a client/server application that creates a “screen-saver” cluster for running simulations in NEURON (Hines & Carnevale, 1997). NeuronPM provides a user-friendly way to use existing computing resources to catalog the performance of a neural simulation across a wide range of parameter values and experimental conditions. The NeuronPM client is a Windows-based screen saver, and the NeuronPM server can be hosted on any Apache/PHP/MySQL server. During idle time, the client retrieves model files and work assignments from the server, invokes NEURON to run the simulation, and returns results to the server. Administrative panels make it simple to upload model files, define the parameters and conditions to vary, and then monitor client status and work progress. NeuronPM is open-source freeware and is available for download at http://neuronpm.homeip.net . It is a useful entry-level tool for systematically analyzing complex neuron and network simulations.

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Grégoire, Éric, and Jean-Marie Lagniez. "RCL: An A. I. Tool for Computing Maximal Consensuses." International Journal on Artificial Intelligence Tools 25, no. 04 (August 2016): 1650026. http://dx.doi.org/10.1142/s0218213016500263.

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RCL is an original Artificial Intelligence tool for computing maximal consensuses among conflicting agents in the Boolean logic framework. It extracts one maximal set of information that does not conflict with any of the agents, taking all possible deductions into account. This form of consensus can go far beyond what is actually shared by all agents. It might be endorsed by every agent since it does not conflict with any of them. Several types of preference criteria can be selected and iterated in order to orient the computation towards some preferred consensuses. From a computational point of view RCL relies on an internal transformation of the maximal consensus-finding problem into one single instance of the Weighted Partial Max-SAT problem.

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Pease, D., A. Ghafoor, I. Ahmad, D. L. Andrews, K. Foudil-Bey, T. E. Karpinski, M. A. Mikki, and M. Zerrouki. "PAWS: a performance evaluation tool for parallel computing systems." Computer 24, no. 1 (January 1991): 18–29. http://dx.doi.org/10.1109/2.67190.

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47

Chaney, E. L., J. S. Thom, G. Tracton, T. Cullip, J. G. Rosenman, and J. E. Tepper. "A portable software tool for computing digitally reconstructed radiographs." International Journal of Radiation Oncology*Biology*Physics 27 (1993): 180–81. http://dx.doi.org/10.1016/0360-3016(93)90717-a.

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Chaney, Edward L., Jesse S. Thorn, Gregg Tracton, Timothy Cullip, Julian G. Rosenman, and Joel E. Tepper. "A portable software tool for computing digitally reconstructed radiographs." International Journal of Radiation Oncology*Biology*Physics 32, no. 2 (May 1995): 491–97. http://dx.doi.org/10.1016/0360-3016(94)00470-6.

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Silva, Francisco Airton, Paulo Maciel, and Rubens Matos. "SmartRank: a smart scheduling tool for mobile cloud computing." Journal of Supercomputing 71, no. 8 (April 17, 2015): 2985–3008. http://dx.doi.org/10.1007/s11227-015-1423-y.

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Topol, Brad, John T. Stasko, and Vaidy Sunderam. "PVaniM: a tool for visualization in network computing environments." Concurrency: Practice and Experience 10, no. 14 (December 10, 1998): 1197–222. http://dx.doi.org/10.1002/(sici)1096-9128(19981210)10:14<1197::aid-cpe364>3.0.co;2-o.

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