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Journal articles on the topic 'Computing approach'

Author: Grafiati

Published: 10 December 2022

Last updated: 31 July 2025

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1

Anjaneyulu, P., and Mr S. Srinivasa Reddy. "Cloud Computing Adoption Approach towards Securing Data in Cloud Computing." International Journal of Trend in Scientific Research and Development Volume-2, Issue-4 (2018): 390–93. http://dx.doi.org/10.31142/ijtsrd12995.

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2

Panhwar, Muhammad Aamir. "Workflow-based Approach in Cloud Computing Environment." Journal of Advanced Research in Dynamical and Control Systems 12, no. 7 (2020): 815–22. http://dx.doi.org/10.5373/jardcs/v12i7/20202066.

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3

Emmert-Streib, Frank. "Biostatistics: A Computing Approach." CHANCE 26, no. 4 (2013): 59–60. http://dx.doi.org/10.1080/09332480.2013.868760.

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4

William Hughes, P. "Biostatistics: a computing approach." Journal of Applied Statistics 39, no. 10 (2012): 2306. http://dx.doi.org/10.1080/02664763.2012.692545.

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5

Baba, Toshio, Yoshi-aki Shimada, Seiichiro Kawamura, et al. "Proposal of disruptive computing (A computing-domain-oriented approach)." Japanese Journal of Applied Physics 59, no. 5 (2020): 050503. http://dx.doi.org/10.35848/1347-4065/ab8577.

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6

Mohammad Badiezadegan, Sayed. "Secure Multiparty Computing: A Decentralized Approach to GPA Calculation." International Journal of Science and Research (IJSR) 12, no. 9 (2023): 515–16. http://dx.doi.org/10.21275/sr23905191245.

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7

Negi, Adhyayan, Gautam Sharma, and Ankit Mittal. "Green Computing: An Efficient Approach." International Journal of Computer Applications 179, no. 32 (2018): 1–3. http://dx.doi.org/10.5120/ijca2018916715.

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8

Zauner, K. P., and M. Conrad. "Molecular approach to informal computing." Soft Computing 5, no. 1 (2001): 39–44. http://dx.doi.org/10.1007/s005000000064.

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9

GIORGADZE, G. "MONODROMY APPROACH TO QUANTUM COMPUTING." International Journal of Modern Physics B 16, no. 30 (2002): 4593–605. http://dx.doi.org/10.1142/s0217979202014607.

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In this work, a gauge approach to quantum computing is considered. It is assumed that there exists a classical procedure for placing certain classical system in a state described by a holomorphic vector bundle with connection with logarithmic singularities. This bundle and its connection are constructed with the aid of unitary operators realizing the given algorithm using methods of the monodromic Riemann–Hilbert problem. Universality is understood in the sense that for any collection of unitary matrices there exists a connection with logarithmic singularities whose monodromy representation in

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10

Anderson, M., S. L. Anderson, and C. Armen. "An Approach to Computing Ethics." IEEE Intelligent Systems 21, no. 4 (2006): 56–63. http://dx.doi.org/10.1109/mis.2006.64.

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11

Huang, Ching-Huei, Horn-Yong Jan, Chun-Liang Lin, and Chia-Soon Lee. "System identification: DNA computing approach." ISA Transactions 48, no. 3 (2009): 254–63. http://dx.doi.org/10.1016/j.isatra.2009.01.006.

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12

Érdi, Péter. "Neurobiological approach to computing devices." Biosystems 21, no. 2 (1988): 125–33. http://dx.doi.org/10.1016/0303-2647(88)90005-6.

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13

Mathieu, R. G. "Top-down approach to computing." Computer 35, no. 1 (2002): 138–39. http://dx.doi.org/10.1109/2.976930.

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14

Förtsch, Michael, and Tobias M. Wintermantel. "Quantum computing – the photonic approach." PhotonicsViews 19, no. 6 (2022): 35–37. http://dx.doi.org/10.1002/phvs.202200051.

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15

Joshi, Garima, and S. K. Verma. "Load Balancing Approach in Cloud Computing using Improvised Genetic Algorithm: A Soft Computing Approach." International Journal of Computer Applications 122, no. 9 (2015): 24–28. http://dx.doi.org/10.5120/21729-4894.

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16

P., Anjaneyulu, and S. Srinivasa Reddy Mr. "Cloud Computing Adoption Approach towards Securing Data in Cloud Computing." International Journal of Trend in Scientific Research and Development 2, no. 4 (2018): 390–93. https://doi.org/10.31142/ijtsrd12995.

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Present or late investigation on cloud security communicates that the security of customers data has the most astonishing need and furthermore concern. Customers store colossal measures of delicate data on a cloud. Sharing sensitive data will empower attempts to reduce the cost of giving customers redid advantages and offer some motivating force included data organizations. Regardless, secure data sharing is risky. Security is a champion among the most troublesome errand to realize in cloud computing. Assorted sorts of strikes in the application side and in the gear parts. This paper proposes

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17

Gupta, Chitvan, and M. Laxmaiah. "Green Cloud Computing: A Futuristic Approach." Journal of Futuristic Sciences and Applications 5, no. 2 (2022): 9–13. http://dx.doi.org/10.51976/jfsa.522202.

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By providing numerous services through the internet and utilizing a variety of resources, cloud computing is a solution to diverse computational difficulties. Problems with energy use and carbon emissions are constant in the IT sector. Datacenters are an essential component of cloud computing. Because of this, there is a growing desire to open more and more datacenters. The greater power consumption at data centres raises the costs on an economic and environmental level. Additionally, the greenhouse effect and carbon footprint have increased due to the increasing release of CO2 and other gases

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18

Manoj Kumar, P. K. "Analysis and Motivation for Green Computing, an Approach in India." Bonfring International Journal of Networking Technologies and Applications 3, no. 1 (2016): 01–03. http://dx.doi.org/10.9756/bijnta.7138.

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19

Narayana Samy, Ganthan, Nurazean Maarop, Doris Hooi-Ten Wong, et al. "Proposed Proactive Digital Forensic Approach for Cloud Computing Environment." International Journal of Engineering & Technology 7, no. 4.15 (2018): 12. http://dx.doi.org/10.14419/ijet.v7i4.15.21362.

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There are many challenges for the digital forensic process in the cloud computing due to the distinguished features of the cloud computing environment. Many of well-known digital forensic methods and tools are not suitable for cloud computing environment. The multi-tenancy, multi-stakeholder, Internet-based, dynamics expendability, and massive data, logs and datasets are examples of the cloud computing environment features that make conducting digital forensics in the cloud computing environment a very difficult task. Therefore, there is a need to develop an appropriate digital forensic approa

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20

Azhmy, Muhammad Fauzan, Annisha Suvero Suyar, and Arasy Ayu Setiamy. "Digital HRM with Machine Learning Approach." Jurnal Penelitian Pendidikan IPA 10, SpecialIssue (2024): 18–23. http://dx.doi.org/10.29303/jppipa.v10ispecialissue.7213.

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The purpose of this paper is to provide an overview of how modern resource management resolves conventional challenges in that area. Computing technology with all its specific application variants will help human performance in HR management in the contemporary era. The rapid advancement of technology and digitalization has presented a digital economy characterized by business and the trade transactions based on technology. This study aims to analyze the influence of the digital economy as measured by the Value of Electronic Money Transactions and the Value of E-Commerce Transactions on Indone

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21

Popa, Raluca Ada. "Confidential Computing or Cryptographic Computing?" Queue 22, no. 2 (2024): 108–32. http://dx.doi.org/10.1145/3664295.

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Secure computation via MPC/homomorphic encryption versus hardware enclaves presents tradeoffs involving deployment, security, and performance. Regarding performance, it matters a lot which workload you have in mind. For simple workloads such as simple summations, low-degree polynomials, or simple machine-learning tasks, both approaches can be ready to use in practice, but for rich computations such as complex SQL analytics or training large machine-learning models, only the hardware enclave approach is at this moment practical enough for many real-world deployment scenarios.

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22

AlNuaim, Abdullah, and Shakeel Ahmed. "Fog Computing: A Novel Approach to provide Security in Cloud Computing." Indian Journal of Science and Technology 11, no. 15 (2018): 1–6. http://dx.doi.org/10.17485/ijst/2018/v11i15/119540.

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23

White, Steve R., James E. Hanson, Ian Whalley, David M. Chess, Alla Segal, and Jeffrey O. Kephart. "Autonomic computing: Architectural approach and prototype." Integrated Computer-Aided Engineering 13, no. 2 (2006): 173–88. http://dx.doi.org/10.3233/ica-2006-13206.

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24

Marosi, Attila Csaba, and Robert Lovas. "Defining volunteer computing: a formal approach." Computer Research and Modeling 7, no. 3 (2015): 565–71. http://dx.doi.org/10.20537/2076-7633-2015-7-3-565-571.

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25

Zhou, Bing. "A Logic Approach to Granular Computing." International Journal of Cognitive Informatics and Natural Intelligence 2, no. 2 (2008): 63–79. http://dx.doi.org/10.4018/jcini.2008040104.

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26

Patel, R. B., and Manpreet Singh. "Cluster Computing: A Mobile Code Approach." Journal of Computer Science 2, no. 10 (2006): 798–806. http://dx.doi.org/10.3844/jcssp.2006.798.806.

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27

Ishikawa, Yutaka. "MPC++ approach to parallel computing environment." ACM SIGAPP Applied Computing Review 4, no. 1 (1996): 15–18. http://dx.doi.org/10.1145/240732.240738.

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28

Chafouk, Houcine, Ghaleb Hoblos, Nicolas Langlois, Serge Le Gonidec, and José Ragot. "Soft Computing Approach for Data Validation." Journal of Aerospace Computing, Information, and Communication 4, no. 1 (2007): 628–35. http://dx.doi.org/10.2514/1.20742.

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29

Petre, Luigia, Kaisa Sere, and Marina Waldén. "A Topological Approach to Distributed Computing." Electronic Notes in Theoretical Computer Science 28 (2000): 59–80. http://dx.doi.org/10.1016/s1571-0661(05)80630-9.

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30

Sands, David. "Computing With Contexts A simple approach." Electronic Notes in Theoretical Computer Science 10 (1998): 134–49. http://dx.doi.org/10.1016/s1571-0661(05)80694-2.

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31

Appavoo, Paramasiven. "The constructivist' approach to teaching computing." International Journal of Continuing Engineering Education and Life-Long Learning 20, no. 3/4/5 (2010): 407. http://dx.doi.org/10.1504/ijceell.2010.037055.

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32

Kalantari, Mohsen. "Spatial Cloud Computing: A Practical Approach." Journal of Spatial Science 60, no. 1 (2015): 197–98. http://dx.doi.org/10.1080/14498596.2015.1011588.

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33

Li, Chunshien, Jyh-Yann Huang, and Chih-Ming Chen. "Soft computing approach to feature extraction." Fuzzy Sets and Systems 147, no. 1 (2004): 119–40. http://dx.doi.org/10.1016/s0165-0114(03)00229-x.

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34

Kobayashi, Satoshi. "Enumeration approach to computing chemical equilibria." Theoretical Computer Science 499 (August 2013): 51–87. http://dx.doi.org/10.1016/j.tcs.2013.05.017.

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35

Geru, I. I. "Non-traditional Approach to Quantum Computing." Applied Magnetic Resonance 45, no. 12 (2014): 1427–39. http://dx.doi.org/10.1007/s00723-014-0594-7.

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36

Spyra, Grzegorz, William J. Buchanan, and Elias Ekonomou. "Sticky policies approach within cloud computing." Computers & Security 70 (September 2017): 366–75. http://dx.doi.org/10.1016/j.cose.2017.07.005.

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37

Karam, Nihad A. "Specific Approach for Computing Hubble's Constant." Journal of Al-Nahrain University Science 9, no. 2 (2006): 90–98. http://dx.doi.org/10.22401/jnus.9.2.14.

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38

Nguyen, Son H., Andrzej Skowron, and Jaroslaw Stepaniuk. "Granular Computing: a Rough Set Approach." Computational Intelligence 17, no. 3 (2001): 514–44. http://dx.doi.org/10.1111/0824-7935.00161.

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39

Alexander, J. "A new approach to business computing." ITNOW 47, no. 2 (2005): 20–21. http://dx.doi.org/10.1093/itnow/bwi035.

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40

Fatoorehchi, Hooman, Ivan Gutman, and Hossein Abolghasemi. "Computing graph energy: An alternative approach." Kragujevac Journal of Science, no. 36 (2014): 69–78. http://dx.doi.org/10.5937/kgjsci1436069f.

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41

Sukhwani, Bharat, Hong Min, Mathew Thoennes, et al. "Database Analytics: A Reconfigurable-Computing Approach." IEEE Micro 34, no. 1 (2014): 19–29. http://dx.doi.org/10.1109/mm.2013.107.

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42

Bastos, Ricardo M., Flávio M. de Oliveira, and José Palazzo M. de Oliveira. "Autonomic computing approach for resource allocation." Expert Systems with Applications 28, no. 1 (2005): 9–19. http://dx.doi.org/10.1016/j.eswa.2004.08.014.

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43

Turkmanovic, Haris, Ivan Popovic, Dejan Drajic, and Zoran Cica. "Green computing for iot - software approach." Facta universitatis - series: Electronics and Energetics 35, no. 4 (2022): 541–55. http://dx.doi.org/10.2298/fuee2204541t.

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More efficient usage of limited energy resources on embedded platforms, found in various IoT applications, is identified as a universal challenge in designing such devices and systems. Although many power management techniques for control and optimization of device power consumption have been introduced at the hardware and software level, only few of them are addressing device operation at the application level. In this paper, a software engineering approach for managing the operation of IoT edge devices is presented. This approach involves a set of the application-level software parameters th

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44

Yadav, Mahendra Pratap, Gaurav Raj, Harishchandra A. Akarte, and Dharmendra Kumar Yadav. "Horizontal Scaling for Containerized Application Using Hybrid Approach." Ingénierie des systèmes d information 25, no. 6 (2020): 709–18. http://dx.doi.org/10.18280/isi.250601.

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Cloud computing is a paradigm to provide services to end-users through the Internet. The availability of services to end-users is dependent on various factors such as the availability of computing resources as well as the number of users to access those services. To manage the real-time fluctuating workload cloud providers use elasticity mechanisms. Elasticity is one of the important characteristics of cloud computing that dynamically allocates computing resources to manage the fluctuating workload. The failure of allocation/de-allocation of computing resources at the right moment leads to SLA

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45

HURMAN, Ivan, Kira BOBROVNIKOVA, Leonid BEDRATYUK, and Hanna BEDRATYUK. "APPROACH FOR CODE ANALYSIS TO ESTIMATE POWER CONSUMPTION OF CUDA CORE." Herald of Khmelnytskyi National University. Technical sciences 217, no. 1 (2023): 67–73. http://dx.doi.org/10.31891/2307-5732-2023-317-1-67-73.

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The graphics processing unit is a popular computing device for achieving exascale performance in high-performance computing programs, which is used not only in graphics tasks, but also in computational tasks such as machine learning, scientific computing, and cryptography. With the help of a graphics processor, you can achieve significant speed and performance compared to the central processing unit. CUDA, Compute Unified Device Architecture, a graphics processing unit software development platform, allows developers to use the high-performance computing capabilities of graphics processing uni

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46

Raju, Y. Home Prasanna, and Nagaraju Devarakonda. "A cluster medoid approach for cloud task scheduling." International Journal of Knowledge-based and Intelligent Engineering Systems 25, no. 1 (2021): 65–73. http://dx.doi.org/10.3233/kes-210053.

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One of the familiar distributed technologies for sharing computing resources through internet is a cloud computing technology. One need not setup all computing resources on their own to design their applications. They can own as much they want by requesting computing resources through net. These resources are shared between users upon request by properly scheduling tasks in cloud. The process of scheduling tasks is to be optimized to share the resources very fast. The paper proposes a cluster medoid based task scheduling technique KMPS (K-medoid particle swarm approach) for minimizing the make

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47

Astrakhantsev, Andrii, Larysa Globa, Oleksandr Fedorov, Dmytro Degtiarov, Yevgen Romanko, and Kyrylo Romanii. "An improved approach to organising mobile edge computing in a 5G network." System research and information technologies, no. 2 (June 28, 2024): 82–92. http://dx.doi.org/10.20535/srit.2308-8893.2024.2.06.

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Mobile edge computing is an important element in ensuring the efficiency of the 5G network as a whole, as it enables data storage and computing at the network edge. Existing solutions do not fully address the issues of load distribution between computing nodes, and most solutions do not offer methods for verifying computations and controlling errors. Accordingly, this paper aims to develop an approach to the organization of mobile edge computing in a 5G mobile network that would authenticate distribution servers and computing nodes, manage the process of distributing computing nodes, have a pr

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48

Biryaltsev, Eugeniy Vasiljevich, Marat Razifovich Galimov, Denis Evgenievich Demidov, and Aleksandr Mikhailovich Elizarov. "The platform approach to research and development using high-performance computing." Program Systems: Theory and Applications 10, no. 2 (2019): 93–119. http://dx.doi.org/10.25209/2079-3316-2019-10-2-93-119.

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In this paper, we analyze the prerequisites and substantiate the relevance for creating an open Internet platform that employs big data technologies, highperformance computing, and multilateral markets in a unified way. Conceived as an ecosystem for the development and use of applied software (including in the field of design and scientific research), the platform should reduce time/costs and improve the quality of software development for solving analytical problems arising in industrial enterprises, scientific research organizations, state bodies and private individuals. The article presents

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49

Pavan Kumar, T., B. Eswar, P. Ayyappa Reddy, and D. Sindhu Bhargavi. "An efficient fog computing for comprising approach to avoid data theft attack." International Journal of Engineering & Technology 7, no. 2.8 (2018): 680. http://dx.doi.org/10.14419/ijet.v7i2.8.10556.

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Cloud computing has become a new paradigm shift in the IT world because of its revolutionary model of computing. It provides flexibility, scalability, and reliability and decreased operational and support expenses for an organization. The Enterprise edition software’s are very costly and maintaining a separate IT team and maintaining their own servers is very expensive and that’s the reason why most of the companies are opting for Cloud computing over enterprise edition of the software. However, few organization cloud customers are not willing to step to cloud computing up on a big scale becau

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50

Sebastian, Shoney, Iyyappan MIn, Sultan Ahmad, Mohammad Maqbool Waris, Hikmat A. M. Abdeljaber, and Jabeen Nazeer. "Hybrid Agent-Based Load-Balancing Approach Used in an IaaS Platform." Wireless Communications and Mobile Computing 2024 (April 26, 2024): 1–9. http://dx.doi.org/10.1155/2024/2357142.

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Cloud computing has received a resounding welcome. It was created following methodical and thorough study in web services, distributed computing, utility computing, and virtualization, and it offers several benefits, including lower costs, less space required, and easier management. These advantages bring in a significant number of new users to the cloud platform every day. In addition, because cloud computing is an Internet-based computing paradigm, it must deal with the issue of overwhelming demands through effective load-balancing. A very small number of studies only focus on load-balancing

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