Cryo-SIMPLY: A Reliable STT-MRAM-Based Smart Material Implication Architecture for In-Memory Computing by Tatiana Moposita, Esteban Garzón, Adam Teman, Marco Lanuzza

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Dynamic Split Computing Framework for Multi-Task Learning Models: A Deep Reinforcement Learning Approach by Haneul Ko, Sangwon Seo, Sangheon Pack

“…Subsequently, an IoT device makes decisions regarding the split computing of the head and tail models. To minimize the average task completion time across multiple tasks and the energy consumption of the IoT device, we formulate a Markov decision process problem. …”
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A Comprehensive Integrated Security Model with Advanced Access Control for Enhancing WSN Computing in IoT Frameworks by Navaneethan S., Arun A.

“…Wireless Sensor Network (WSN) Computing has emerged as a pivotal intermediary process addressing latency challenges inherent in Cloud-oriented Internet of Things (IoT) services. …”
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AN APPROACH PRIORITIZING THE CAUSAL FACTORS OF LARGE SCALED DATA USING SOFT COMPUTING: A CASE STUDY by Jyoti Prakash MISHRA, Zdzislaw POLKOWSKI, Sambit Kumar MISHRA

“…In such situation, it may be difficult for data acquisition and processing. In fact, this complexity can be due to constrain in operations linked to computational resources especially in distributed environments. …”
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Applications of multi-GPU computing in large-scale fully kinetic particle-in-cell simulations of space plasma by Q. Y. Xiong, S. Y. Huang, Z. G. Yuan, L. L. Kuang, B. Sharma, K. Jiang, H. H. Wu, L. Yu

“…The rapid development of an emerging computing device, the graphical processing unit (GPU), has significantly enhanced our ability to conduct full kinetic particle-in-cell (PIC) simulations in space physics. …”
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Edge Computing-Based Video Action Recognition Method and Its Application in Online Physical Education Teaching by Jinzhu Han, Jinjin Zhao, Yan Yue, Xinrui Che

“…However, traditional cloud computing-based intelligent online PE teaching systems often face various challenging issues, such as computational complexity and latency. …”
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High‐Performance Synapse Arrays for Neuromorphic Computing via Floating Gate‐Engineered IGZO Synaptic Transistors by Junhyeong Park, Yumin Yun, Sunyeol Bae, Yuseong Jang, Seungyoon Shin, Soo‐Yeon Lee

“…Abstract Neuromorphic computing emulating the human brain offers a promising alternative to the Von Neumann architecture. …”
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Enhancing Vehicle Location Prediction Accuracy with Road-Aware Rectification for Multi-Access Edge Computing Applications by Asif Mehmood, Afaq Muhammad, Faisal Mehmood, Wang-Cheol Song

“…The results demonstrate that the prediction error is approximately 0.005, while the proposed rectification process further reduces the error to 0.001, highlighting the effectiveness of the proposed approach. …”
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Transmission Line Anomaly Detection and Real-Time Monitoring System Combining Edge Computing and EfficientDet by Menghao Lin, Yang Ding, Tianle Wang, Yang Liu, Zewei Li

“…Secondly, in order to improve the speed of model detection, the convolution operation process for obtaining data features based on Ghost lightweight module is reconstructed. …”
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Stub Signature-Based Efficient Public Data Auditing System Using Dynamic Procedures in Cloud Computing by Paromita Goswami, Neetu Faujdar, Ghanshyam Singh, Kanta Prasad Sharma, Ajoy Kumar Khan, Somen Debnath

“…To address these issues, we suggest proposing a partial signature-based data auditing system so that both privacy and accuracy can be fortified while reducing the computational cost associated with auditing processes significantly. …”
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Conditional Random Field-Based Incremental Auto Scaling Algorithm to Enhance Workflow Scheduling in Cloud Computing by George Fernandez, Arunkumar Gopu, S. P. Abirami, B. Misha Chandar, T. Poongodi, B. Arunkumar

“…Thus, according to the values obtained in the experiment, it is proved that the proposed auto-scaling algorithm is effective with the identified evaluation criteria: This is the total time needed to complete all activities, the energy used in the computing process, the costs incurred, and the rate at which the activities are completed in a schedule. …”
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Integrating Tiny Machine Learning and Edge Computing for Real-Time Object Recognition in Industrial Robotic Arms by Nian-Ze Hu, Bo-An Lin, Yen-Yu Wu, Hao-Lun Huang, You-Xin Lin, Chih-Chen Lin, Po-Han Lu

“…By integrating visual recognition technology and multi-object recognition into robotic arms, the flexibility and automation of the production process were improved in this study. By applying tiny machine learning (TinyML) and machine vision algorithms, we integrated edge computing devices to control the robotic arms and identified objects precisely on the production line, with ultra-low energy consumption. …”
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Machine learning for handover decision with mobile edge computing in 6G mobile network: a survey by Soule Issa Loutfi, Ibraheem Shayea, Ufuk Tureli, Ayman A. El-Saleh, Waheeb Tashan, Ramazan Caglar

“…The case becomes more critical with the implementation of Mobile Edge Computing (MEC), which will lead to making the handover decision process more challenging due to its characterization and high requirements. …”
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Multi-user joint task offloading and resource allocation based on mobile edge computing in mining scenarios by Siqi Li, Weidong Li, Wanbo Zheng, Yunni Xia, Kunyin Guo, Qinglan Peng, Xu Li, Jiaxin Ren

“…Given the limited computational capacity of terminal devices, this paper optimizes the offloading decision-making process between terminal devices and MEC servers. …”
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Model for Prediction of Testing Time of a Computer Program for Automated Reliability Evaluation of Semiconductor Devices by V. O. Kaziuchyts, S. M. Borovikov, E. N. Shneiderov

“…The model was used for the computer program KLASS planned for development and takes into account the programming language, the amount of program code, the speed of the computer processor, and the scope of the program. …”
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Elementary integrate-and-fire process underlies pulse amplitudes in Electrodermal activity. by Sandya Subramanian, Patrick L Purdon, Riccardo Barbieri, Emery N Brown

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When less is more: non-monotonic spike sequence processing in neurons. by Hinrich Arnoldt, Shuwen Chang, Sven Jahnke, Birk Urmersbach, Holger Taschenberger, Marc Timme

“…Fundamental response properties of neurons centrally underly the computational capabilities of both individual nerve cells and neural networks. …”
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Understanding pitch perception as a hierarchical process with top-down modulation. by Emili Balaguer-Ballester, Nicholas R Clark, Martin Coath, Katrin Krumbholz, Susan L Denham

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An integrated calcium imaging processing toolbox for the analysis of neuronal population dynamics. by Sebastián A Romano, Verónica Pérez-Schuster, Adrien Jouary, Jonathan Boulanger-Weill, Alessia Candeo, Thomas Pietri, Germán Sumbre

“…We present a comprehensive computational workflow for the analysis of neuronal population calcium dynamics. …”
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Marked point process variational autoencoder with applications to unsorted spiking activities. by Ryohei Shibue, Tomoharu Iwata

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