SIBILA: Automated Machine-Learning-Based Development of Interpretable Machine-Learning Models on High-Performance Computing Platforms by Antonio Jesús Banegas-Luna, Horacio Pérez-Sánchez

“…Its integration of interpretability constraints alongside automated model development processes marks a substantial step forward in bridging the gap between computational efficiency and model transparency in ML applications. …”
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Smart phosphor with neuromorphic behaviors enabling full-photoluminescent Write and Read for all-optical physical reservoir computing by Yifei Zhao, Man Li, Man Chung Wong, Xun Han, Feng Guo, Yuan Liu, Xinyue Lao, Zhaoying Dang, Sin-Yi Pang, Zehan Wu, Shi Ye, Jianhua Hao

“…This work explores all-optical information processing based on photoluminescence functions using smart phosphor. …”
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A multi-user multi-operator computing pricing method for Internet of things based on bi-level optimization by Wei Jiang, Huiqiang Wang, Bingyang Li, Haibin Lv, Qingchuan Meng

“…These applications typically consume large amounts of computing and energy resources. However, due to the physical size limitations of Internet of things terminals, their computing capacity and power are limited, where users’ needs for application processing delay and power consumption cannot be met. …”
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WiCNNAct: Wi-Fi-Based Human Activity Recognition Utilizing Deep Learning on the Edge Computing Devices by Venkata Raghava Shashank Viswanathuni, Rakesh Reddy Yakkati, Sreenivasa Reddy Yeduri, Linga Reddy Cenkeramaddi

“…The model is deployed on various edge computing devices, including Raspberry Pi, to assess real-time deployment feasibility. …”
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Direct laser writing of graphene oxide for ultra-low power consumption memristors in reservoir computing for digital recognition by Chen Min, Wan Zhengfen, Dong Hao, Chen Qinyu, Gu Min, Zhang Qiming

“…A memristor is a promising candidate of new electronic synaptic devices for neuromorphic computing. However, conventional memristors often exhibit complex device structures, cumbersome manufacturing processes, and high energy consumption. …”
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Reducing time and computing costs in EC-Earth: an automatic load-balancing approach for coupled Earth system models by S. Palomas, M. C. Acosta, G. Utrera, E. Tourigny

“…However, this task traditionally involves manual testing of multiple process allocations by trial and error, requiring significant time investment from researchers and making the process more error-prone, often resulting in a loss of application performance due to the complexity of the task. …”
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Versatile parallel signal processing with a scalable silicon photonic chip by Shihan Hong, Jiachen Wu, Yiwei Xie, Xiyuan Ke, Huan Li, Linyan Lyv, Yingying Peng, Qingrui Yao, Yaocheng Shi, Ke Wang, Leimeng Zhuang, Pan Wang, Daoxin Dai

“…Abstract Silicon photonic signal processors promise a new generation of signal processing hardware with significant advancements in processing bandwidth, low power consumption, and minimal latency. …”
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Embankment Breach Simulation and Inundation Mapping Leveraging High-Performance Computing for Enhanced Flood Risk Prediction and Assessment by U. Dutta, Y. K. Singh, T. S. M. Prabhu, G. Yendargaye, R. Kale, M. K. Khare, B. Kumar, R. Panchang

“…Our findings reveal that simulations conducted on multicore processors offer superior performance compared to single-core setups, yielding enhanced result accuracy and providing administrators with increased lead time. …”
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Trust Verification Method for Leveraging Secure Task Completion in Mobile Crowd Outsourcing Processes by Abdullah Alharthi

“…This highness represents the trust observed from the previous task completion intervals. In this trust computing and verification process two distinct phases of Q-learning are utilized; the transitions between false data injection and task completion are independently validated for highness value derivations. …”
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VR-based avatar videos as an effective tool for process training in the context of digitalization? by Sarah Depenbusch, Niclas Schaper, Mirko Schürmann, Jan-Philip Schumacher

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Resolving Contrast and Detail Trade-Offs in Image Processing with Multi-Objective Optimization by Daniel Molina-Pérez, Alam Gabriel Rojas-López

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Confirmation bias in human reinforcement learning: Evidence from counterfactual feedback processing. by Stefano Palminteri, Germain Lefebvre, Emma J Kilford, Sarah-Jayne Blakemore

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Big data processing and analysis platform based on deep neural network model by Sheng Huang

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Tunnel Traffic Enforcement Using Visual Computing and Field-Programmable Gate Array-Based Vehicle Detection and Tracking by Yi-Chen Lin, Rey-Sern Lin

“…We accelerated image processing using xfOpenCV on the PYNQ-Z2 and FPGA Xilinx platforms. …”
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Autoencoder neural network-based abnormal data detection in edge computing enabled large-scale IoT systems by Tianqi YU, Yongxu ZHU, Xianbin WANG

“…Given the advantages of low cost and easy deployment,large-scale Internet of things (IoT) has been deployed for environment monitoring pervasively.Within such systems,cloud platform is typically utilized as a remote data and control center.However,tremendous amount of data uploading and processing induce huge challenges on bandwidth load and real-time data gathering.In order to overcome these challenges,edge computing enabled IoT system architecture was proposed for environmental monitoring.As the intermediate layer,local processing could be supported for end devices with low latency and assist with preliminary analysis to offload computational tasks from cloud and the amount of data uploading could be reduced.Based on this system architecture,an autoencoder neural network-based abnormal data detection scheme was developed newly.Performance evaluation has been conducted based on the practical oceanic atmospheric data.Simulation results indicate that the proposed scheme can accurately detect the abnormal data by fully exploiting the spatial data correlation.…”
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«Okun-2» software-computing complex for calculating the mutational profile of samples of the sequenced whole genomes of mycobacteria tuberculosis by M. V. Sprindzuk, L. P. Titov, V. V. Slizen, A. E. Skryahin, E. M. Skryahina, O. M. Zalutskaya, A. P. Konchits

“…Authors describe a new software and computer complex designed and developed for the processing of the data of the whole genomes of mycobacterium tuberculosis with the purpose of obtaining information about the profile of tuberculosis resistance and virulence.…”
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Edge Computing for AI-Based Brain MRI Applications: A Critical Evaluation of Real-Time Classification and Segmentation by Khuhed Memon, Norashikin Yahya, Mohd Zuki Yusoff, Rabani Remli, Aida-Widure Mustapha Mohd Mustapha, Hilwati Hashim, Syed Saad Azhar Ali, Shahabuddin Siddiqui

“…Edge computing devices and handheld gadgets can serve as useful tools to process medical data in remote areas with limited network and computational resources. …”
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PDAI: A green pesticide molecule design technology platform driven by high-performance computing and artificial intelligence by Ziling Zhu, Mengzhu Jia, Hao Zhou, Fan Wang

“…Despite the notable advancements in Computer Aided Drug Design (CADD) and Artificial Intelligence Drug Discovery (AIDD) in pharmaceuticals, their application in the pesticide sector remains underutilized. …”
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Phase Change Memory: A Review on Electrical Behavior and Use in Analog In‐Memory‐Computing (A‐IMC) Applications by Mattia Boniardi, Matteo Baldo, Mario Allegra, Andrea Redaelli

“…In Analog In‐Memory Computing (A‐IMC) the typical properties of resistance‐based memory technologies are used to both store and compute information. …”
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Towards a Granular Computing Framework for Multiple Aspect Trajectory Representation and Privacy Preservation: Research Challenges and Opportunities by Zaineb Chelly Dagdia, Vania Bogorny

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