Relevant bibliographies by topics / Computing Devices

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Computing Devices'

Author: Grafiati
Published: 7 June 2025
Last updated: 2 August 2025

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Journal articles on the topic "Computing Devices"

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Amin, Muhammad Rizwan. "Mobile Cloud Computing-Challenges and Future Prospects." International Journal of Information Systems and Computer Technologies 2, no. 2 (2023): 44–51. http://dx.doi.org/10.58325/ijisct.002.02.0050.

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With the expanding use of portable devices in modern environments, everything, including shopping, social networking, and information collecting, is now possible via mobile devices. Mobile phone use, on the other hand, is expanding by the day. Because the use of mobile devices has increased the number of computing jobs, so has the amount of processing of these tasks. Despite all of these gains in data storage and processing, mobile devices struggle to handle massive applications such as CPUs.
 MCC enables a mobile device to do operations or analyze data in the cloud and then return result
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Sharma, Bhoj Raj, Deepika Sharma, and Ritika Ritika. "Bluetooth- Connecting Computing and Telecommunication Devices." International Journal of Scientific Research 2, no. 3 (2012): 74–76. http://dx.doi.org/10.15373/22778179/mar2013/25.

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Jha, Rashmi, Vamshi Kiran Kiran Gogi, and Siddharth Barve. "(Invited) Novel Neuromorphic Computing Paradigms Enabled By Emerging Memory Devices." ECS Meeting Abstracts MA2024-01, no. 57 (2024): 3011. http://dx.doi.org/10.1149/ma2024-01573011mtgabs.

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Implementation of Artificial Intelligence and Machine Learning algorithms on conventional Von Neumann computing architectures are crippled by the memory-wall bottleneck. To overcome these issues, novel computing architectures with high-bandwidth memories, in-memory computing, and near-memory computing capabilities are being developed. Almost all of these architectures will benefit from high-density on-chip non-volatile memories, offered by the emerging non-volatile memory devices. Additionally, emerging memory devices offer rich device physics that can be leveraged for the implementation of no
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MIHAILIDIS, ALEX, LAURA KRONES, and JENNIFER BOGER. "Assistive Computing Devices." CIN: Computers, Informatics, Nursing 24, no. 6 (2006): 328–36. http://dx.doi.org/10.1097/00024665-200611000-00007.

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Chen, An. "(Invited, Digital Presentation) Emerging Materials and Devices for Energy-Efficient Computing." ECS Meeting Abstracts MA2022-01, no. 19 (2022): 1073. http://dx.doi.org/10.1149/ma2022-01191073mtgabs.

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As the CMOS scaling driven by the Moore’s Law approaching the fundamental limits, high energy consumption and heat dissipation have been recognized as the most critical device challenges. Novel switching devices with significantly lower power based on unconventional mechanisms have been explored to replace CMOS in various research programs, e.g., Nanoelectronics Research Initiative (NRI). The major categories of these devices include steep-slope transistors, spintronic devices, ferroelectric devices, and van der Waals devices [1]. These devices are often implemented on emerging materials with
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Ali, Abid, Muhammad Munawar Iqbal, Harun Jamil, et al. "An Efficient Dynamic-Decision Based Task Scheduler for Task Offloading Optimization and Energy Management in Mobile Cloud Computing." Sensors 21, no. 13 (2021): 4527. http://dx.doi.org/10.3390/s21134527.

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Restricted abilities of mobile devices in terms of storage, computation, time, energy supply, and transmission causes issues related to energy optimization and time management while processing tasks on mobile phones. This issue pertains to multifarious mobile device-related dimensions, including mobile cloud computing, fog computing, and edge computing. On the contrary, mobile devices’ dearth of storage and processing power originates several issues for optimal energy and time management. These problems intensify the process of task retaining and offloading on mobile devices. This paper presen
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Jiang, Jiafu, Linyu Tang, Ke Gu, and WeiJia Jia. "Secure Computing Resource Allocation Framework For Open Fog Computing." Computer Journal 63, no. 4 (2020): 567–92. http://dx.doi.org/10.1093/comjnl/bxz108.

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Abstract Fog computing has become an emerging environment that provides data storage, computing and some other services on the edge of network. It not only can acquire data from terminal devices, but also can provide computing services to users by opening computing resources. Compared with cloud computing, fog devices can collaborate to provide users with powerful computing services through resource allocation. However, as many of fog devices are not monitored, there are some security problems. For example, since fog server processes and maintains user information, device information, task par
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Longo, Mathias, Matías Hirsch, Cristian Mateos, and Alejandro Zunino. "Towards Integrating Mobile Devices into Dew Computing: A Model for Hour-Wise Prediction of Energy Availability." Information 10, no. 3 (2019): 86. http://dx.doi.org/10.3390/info10030086.

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With self-provisioning of resources as premise, dew computing aims at providing computing services by minimizing the dependency over existing internetwork back-haul. Mobile devices have a huge potential to contribute to this emerging paradigm, not only due to their proximity to the end user, ever growing computing/storage features and pervasiveness, but also due to their capability to render services for several hours, even days, without being plugged to the electricity grid. Nonetheless, misusing the energy of their batteries can discourage owners to offer devices as resource providers in dew
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Singh, Anuj Kumar, and B. D. K. Patro. "Security of Low Computing Power Devices: A Survey of Requirements, Challenges & Possible Solutions." Cybernetics and Information Technologies 19, no. 1 (2019): 133–64. http://dx.doi.org/10.2478/cait-2019-0008.

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Abstract Security has been a primary concern in almost all areas of computing and for the devices that are low on computing power it becomes more important. In this paper, a new class of computing device termed as Low Computing Power Device (LCPD) has been defined conceptually. The paper brings out common attributes, security requirements and security challenges of all kinds of low computing power devices in one place so that common security solutions for these can be designed and implemented rather than doing this for each individual device type. A survey of existing recent security solutions
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Ahuja, Sanjay P., and Inan Kaddour. "Mobile Cloud Computing." International Journal of Cloud Applications and Computing 15, no. 1 (2025): 1–35. https://doi.org/10.4018/ijcac.378695.

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Currently, smart mobile devices are used for more than just calling and texting. They can run complex applications such as GPS, antivirus, and photo editor applications. Smart devices today offer mobility, flexibility, and portability, but they have limited resources and a relatively weak battery. As companies began creating mobile resource-hungry and power-hungry applications, they have realized that cloud computing was one of the solutions that they could utilize to overcome smart device constraints. Cloud computing helps decrease memory usage and improve battery life. Mobile cloud computing
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Dissertations / Theses on the topic "Computing Devices"

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Ensini, Davide. "Spatial computing per smart devices." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2014. http://amslaurea.unibo.it/7990/.

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Magic Carpet, nato come un middleware orientato a una dimostrazione sullo spatial computing, che inizialmente coinvolgeva solo smart devices ed un tappeto di tag NFC, è il punto di partenza per uno studio sulle tecnologie abilitanti in tale campo. Il prodotto finale è una toolchain per lo sviluppo e la distribuzione, su dispositivi connessi, di applicazioni di spatial computing. Essa comprende un interprete per un DSL basato su un core calculus formalizzato, Field Calculus, e un middleware che supporta l'astrazione curando, a basso livello, le comunicazioni con il vicinato e le percezioni a
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Browne, James D. "Masterless Distributed Computing Over Mobile Devices." Thesis, Monterey, California. Naval Postgraduate School, 2012. http://hdl.handle.net/10945/17328.

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Approved for public release; distribution is unlimited<br>It is obvious that information is becoming increasingly important in todays society. This can be seen by the widespread availability of high-speed Internet in homes and the ubiquity of smart phones. This new information centric paradigm is possible because of a large supporting infrastructure without which the Internet, the volumes of information, and the speed we can access them would not exist. The military has recognized the potential value of this trend because the greatest hindrance that any commander has is the fog of warthe absen
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Bridle, Robert Angus, and robert bridle@gmail com. "Adaptive User Interfaces for Mobile Computing Devices." The Australian National University. College of Engineering and Computer Sciences, 2008. http://thesis.anu.edu.au./public/adt-ANU20081117.184430.

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This thesis examines the use of adaptive user interface elements on a mobile phone and presents two adaptive user interface approaches. The approaches attempt to increase the efficiency with which a user interacts with a mobile phone, while ensuring the interface remains predictable to a user. ¶ An adaptive user interface approach is presented that predicts the menu item a user will select. When a menu is opened, the predicted menu item is highlighted instead of the top-most menu item. The aim is to maintain the layout of the menu and to save the user from performing scrolling key presses. A m
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Abeed, Md Ahsanul. "STRAINTRONIC NANOMAGNETIC DEVICES FOR NON-BOOLEAN COMPUTING." VCU Scholars Compass, 2019. https://scholarscompass.vcu.edu/etd/6020.

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Nanomagnetic devices have been projected as an alternative to transistor-based switching devices due to their non-volatility and potentially superior energy-efficiency. The energy efficiency is enhanced by the use of straintronics which involves the application of a voltage to a piezoelectric layer to generate a strain which is ultimately transferred to an elastically coupled magnetostrictive nanomaget, causing magnetization rotation. The low energy dissipation and non-volatility characteristics make straintronic nanomagnets very attractive for both Boolean and non-Boolean computing applicatio
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Bridle, Robert Angus. "Adaptive user interfaces for mobile computing devices /." View thesis entry in Australian Digital Theses Program, 2008. http://thesis.anu.edu.au/public/adt-ANU20081117.184430/index.html.

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Rosenberg, Robert. "Computing without mice and keyboards : text and graphic input devices for mobile computing." Thesis, University College London (University of London), 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.285005.

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VijayaRamachandran, Karthikeyan. "Computing with nanoscale devices -- looking at alternate models /." Full text open access at:, 2005. http://content.ohsu.edu/u?/etd,213.

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Qaddoura, Fady. "Bi-Directional Information Exchange with Computing Handheld Devices." ScholarWorks@UNO, 2007. http://scholarworks.uno.edu/td/536.

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The "Bi-Directional Information Exchange with Handheld Computing Devicesz' project introduces two new concepts: dynamic "digital receipts" and "personal data warehousing."  Dynamic digital receipts means digitalizing paper transactions generated from points of sale. Personal data warehousing means organizing and collecting data for later viewing and analysis. The consumer will be able to use a handheld device such as a cell phone or PDA to receive and store a transaction in XML format. Later on, the user can upload the receipt through a web application to a personal data warehouse for stor
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Aji, Ashwin M. "Programming High-Performance Clusters with Heterogeneous Computing Devices." Diss., Virginia Tech, 2015. http://hdl.handle.net/10919/52366.

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Today's high-performance computing (HPC) clusters are seeing an increase in the adoption of accelerators like GPUs, FPGAs and co-processors, leading to heterogeneity in the computation and memory subsystems. To program such systems, application developers typically employ a hybrid programming model of MPI across the compute nodes in the cluster and an accelerator-specific library (e.g.; CUDA, OpenCL, OpenMP, OpenACC) across the accelerator devices within each compute node. Such explicit management of disjointed computation and memory resources leads to reduced productivity and performance. Thi
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Sadaquat, Jan. "Facilitating file retrieval on resource limited devices." Thesis, Brunel University, 2011. http://bura.brunel.ac.uk/handle/2438/5451.

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The rapid development of mobile technologies has facilitated users to generate and store files on mobile devices. However, it has become a challenging issue for users to search efficiently and effectively for files of interest in a mobile environment that involves a large number of mobile nodes. In this thesis, file management and retrieval alternatives have been investigated to propose a feasible framework that can be employed on resource-limited devices without altering their operating systems. The file annotation and retrieval framework (FARM) proposed in the thesis automatically annotates
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Books on the topic "Computing Devices"

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Bhaumik, Jaydeb, Indrajit Chakrabarti, Bishnu Prasad De, Banibrata Bag, and Surajit Mukherjee, eds. Communication, Devices, and Computing. Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-8585-7.

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Library of Congress. Copyright Office., ed. Computing and measuring devices. Copyright Office, Library of Congress, 1999.

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Library of Congress. Copyright Office, ed. Computing and measuring devices. Copyright Office, Library of Congress, 1999.

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Jain, Lakhmi C., Srikanta Patnaik, and Nikhil Ichalkaranje, eds. Intelligent Computing, Communication and Devices. Springer India, 2015. http://dx.doi.org/10.1007/978-81-322-2009-1.

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Jain, Lakhmi C., Srikanta Patnaik, and Nikhil Ichalkaranje, eds. Intelligent Computing, Communication and Devices. Springer India, 2015. http://dx.doi.org/10.1007/978-81-322-2012-1.

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Aly, Mohamed M. Sabry, and Anupam Chattopadhyay, eds. Emerging Computing: From Devices to Systems. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-16-7487-7.

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Huang, Chao, ed. Robust Computing with Nano-scale Devices. Springer Netherlands, 2010. http://dx.doi.org/10.1007/978-90-481-8540-5.

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Mikkonen, Tommi. Programming Mobile Devices. John Wiley & Sons, Ltd., 2007.

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Yu, Shimeng, ed. Neuro-inspired Computing Using Resistive Synaptic Devices. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-54313-0.

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Bobyr', Maksim, Sergey Emel'yanov, Aleksandr Arhipov, Natal'ya Milostnaya, Andrey Ronzhin, and Roman Mescheryakov. Applied neuro-fuzzy computing systems and devices. INFRA-M Academic Publishing LLC., 2023. http://dx.doi.org/10.12737/1900641.

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The monograph is devoted to the analysis and development of applied neuro-fuzzy systems and devices. The issues related to the training of neuro-fuzzy inference systems are outlined. There are many examples and algorithms that explain the essence of the functioning of the developed methods.&#x0D; It is intended for students, postgraduates, researchers, engineers engaged in the development of intelligent systems and devices for controlling mechanisms.
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Book chapters on the topic "Computing Devices"

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Gammaitoni, Luca. "Computing with Devices." In The Physics of Computing. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-87108-6_1.

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Hirvensalo, Mika. "Devices for Computation." In Quantum Computing. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-662-09636-9_3.

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Hirvensalo, Mika. "Devices for Computation." In Quantum Computing. Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/978-3-662-04461-2_2.

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Smiljanic, Aleksandar. "Mobile Devices." In Geschäftsprozesse mit Mobile Computing. Vieweg+Teubner Verlag, 2002. http://dx.doi.org/10.1007/978-3-322-90275-7_2.

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Hansmann, Uwe, Lothar Merk, Martin S. Nicklous, and Thomas Stober. "Information Access Devices." In Pervasive Computing Handbook. Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/978-3-662-04318-9_2.

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Mukherjee, Manas. "Quantum Computing—An Emerging Computing Paradigm." In Emerging Computing: From Devices to Systems. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-7487-7_6.

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Alhazov, Artiom, Yurii Rogozhin, and Sergey Verlan. "Small Universal Devices." In Computing with New Resources. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-13350-8_19.

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Vollmar, Roland. "Konrad Zuse’s First Computing Devices." In Computer Aided Systems Theory – EUROCAST 2017. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-74718-7_2.

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Likharev, Konstantin K. "Superconductor Devices for Ultrafast Computing." In Applications of Superconductivity. Springer Netherlands, 2000. http://dx.doi.org/10.1007/978-94-017-0752-7_5.

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Zidan, Mohammed A., An Chen, Giacomo Indiveri, and Wei D. Lu. "Memristive Computing Devices and Applications." In Electronic Materials: Science & Technology. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-42424-4_2.

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Conference papers on the topic "Computing Devices"

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Mondal, Surojit, Bikash Debnath, Jadav Chandra Das, and Debashis De. "Homomorphic Encryption in Quantum Computing." In 2025 Devices for Integrated Circuit (DevIC). IEEE, 2025. https://doi.org/10.1109/devic63749.2025.11012553.

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Telsang, Vinayak A., Mahabaleshwar S. Kakkasageri, and Anil D. Devangavi. "Edge Computing Devices Authentication using Quantum Computing." In 2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT). IEEE, 2024. http://dx.doi.org/10.1109/icccnt61001.2024.10725671.

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Fukami, Shunsuke. "Probabilistic computing utilizing stochastic spintronic devices." In 2025 IEEE 55th International Symposium on Multiple-Valued Logic (ISMVL). IEEE, 2025. https://doi.org/10.1109/ismvl64713.2025.00009.

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Lemme, Max C., Lukas Völkel, Sofia Cruces, Jimin Lee, and Yuan Fa. "2D Materials for Neuromorphic Computing Devices." In 2025 9th IEEE Electron Devices Technology & Manufacturing Conference (EDTM). IEEE, 2025. https://doi.org/10.1109/edtm61175.2025.11041583.

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Youngblood, Nathan, Paolo Pintus, Mario Dumont, et al. "Non-reciprocal devices for in-memory photonic computing." In Frontiers in Optics. Optica Publishing Group, 2024. https://doi.org/10.1364/fio.2024.ftu1d.2.

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Non-reciprocal platforms can offer several key advantages for scalable and efficient photonic computing. In this talk, I will present our recent experimental work validating the use of non-reciprocal materials to implement high-endurance memory for photonic computing. Full-text article not available; see video presentation
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Fernando, Owen Noel Newton, Saipang Chan, Naoko Tosa, Ryohei Nakatsu, Adrian David Cheok, and Ajith P. Madurapperuma. "Personalized Cultural Information for Mobile Devices." In 2011 Second International Conference on Culture and Computing (Culture Computing). IEEE, 2011. http://dx.doi.org/10.1109/culture-computing.2011.32.

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Keyes, Robert W. "Limitations of Computing Devices." In 11th European Solid State Circuits Conference. IEEE, 1985. http://dx.doi.org/10.1109/esscirc.1985.5467754.

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Theis, Thomas N. "New devices for computing." In 2014 Silicon Nanoelectronics Workshop (SNW). IEEE, 2014. http://dx.doi.org/10.1109/snw.2014.7348525.

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Lau, K. Y., and A. Yariv. "Bistable Optoelectronic Devices in GaAs." In Optical Computing. Optica Publishing Group, 1985. http://dx.doi.org/10.1364/optcomp.1985.mc4.

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Bistable switching devices occupy a central role in the area of signal processing. Electronic switching devices (electrical in - electrical out) commonly known as Schmidt trigger are key elements in the general area of analog and digital signal processing by electronic means. It seems inevitable that optical computing and signal processing systems will eventually incorporate some form of optical bistable switching elements. Purely optical bistable devices (optical in - optical out) have, through investigations in recent years, made very substantial advances in terms of switching speed and opti
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Gaba, Siddharth, Phil Knag, Zhengya Zhang, and Wei Lu. "Memristive devices for stochastic computing." In 2014 IEEE International Symposium on Circuits and Systems (ISCAS). IEEE, 2014. http://dx.doi.org/10.1109/iscas.2014.6865703.

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Reports on the topic "Computing Devices"

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Leson, Joel L. Mobile Computing Devices. Defense Technical Information Center, 2001. http://dx.doi.org/10.21236/ada402388.

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Pirkelbauer, P., and C. Liao. Trustworthy Computing with Edge Devices. Office of Scientific and Technical Information (OSTI), 2021. http://dx.doi.org/10.2172/1825848.

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Caravelli, Francesco. Computing with memristive devices and networks. Office of Scientific and Technical Information (OSTI), 2020. http://dx.doi.org/10.2172/1726132.

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Jerzy Bernholc. Integrated Multiscale Modeling of Molecular Computing Devices. Office of Scientific and Technical Information (OSTI), 2011. http://dx.doi.org/10.2172/1004483.

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Gregory Beylkin. Integrated Multiscale Modeling of Molecular Computing Devices. Office of Scientific and Technical Information (OSTI), 2012. http://dx.doi.org/10.2172/1036976.

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Weinan E. Integrated Multiscale Modeling of Molecular Computing Devices. Office of Scientific and Technical Information (OSTI), 2012. http://dx.doi.org/10.2172/1037453.

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Leathers, Emily, Clayton Thurmer, and Kendall Niles. Encryption for edge computing applications. Engineer Research and Development Center (U.S.), 2024. http://dx.doi.org/10.21079/11681/48596.

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As smart sensors and the Internet of Things (IoT) exponentially expand, there is an increased need for effective processing solutions for sensor node data located in the operational arena where it can be leveraged for immediate decision support. Current developments reveal that edge computing, where processing and storage are performed close to data generation locations, can meet this need (Ahmed and Ahmed 2016). Edge computing imparts greater flexibility than that experienced in cloud computing architectures (Khan et al. 2019). Despite these benefits, the literature highlights open security i
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Capraro, Gerard T. Hand-Held Computing Devices and Large Knowledge Bases. Defense Technical Information Center, 1998. http://dx.doi.org/10.21236/ada358590.

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Li, Andy C. Y., Alessandro Roggero, Joseph Carlson, Rajan Gupta, and Gabriel N. Perdue. Quantum Computing for Neutrino-nucleus Scattering with NISQ Devices. Office of Scientific and Technical Information (OSTI), 2020. http://dx.doi.org/10.2172/1630713.

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Tim Schulze. Integrated Multiscale Modeling of Molecular Computing Devices. Final Report. Office of Scientific and Technical Information (OSTI), 2012. http://dx.doi.org/10.2172/1053995.

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