Enhancing Incentive Schemes in Edge Computing through Hierarchical Reinforcement Learning by Gowtham R, Vatsala Anand, Yadati Vijaya Suresh, Kasetty Lakshmi Narasimha, R. Anil Kumar, V. Saraswathi

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A near-threshold memristive computing-in-memory engine for edge intelligence by Linfang Wang, Weizeng Li, Zhidao Zhou, Junjie An, Wang Ye, Zhi Li, Hanghang Gao, Hongyang Hu, Jing Liu, Xiaoming Chen, Ling Li, Qi Liu, Mingoo Seok, Chunmeng Dou, Ming Liu

“…However, their scalability faces challenges, primarily due to process variation. Here, we report a 1-Mb, 16-macro near-threshold memristive computing-in-memory engine. …”
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Optimizing Decision Making on Business Processes Using a Combination of Process Mining, Job Shop, and Multivariate Resource Clustering by Hanung Nindito Prasetyo, Riyanarto Sarno, Dedy Rahman Wijaya, Raden Budiraharjo, Indra Waspada, Kelly Rossa Sungkono, Abdullah Faqih Septiyanto

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Interval models of nonequilibrium physicochemical processes by Alexander Yu. Morozov, Dmitry L. Reviznikov, Vladimir Yu. Gidaspov

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STT-HDC: An Efficient Time-Domain In-Memory Hyper-Dimensional Computing Design Based on STT-MRAM by Thi-Nhan Pham, Quang-Kien Trinh, Thanh-Dat Nguyen, Ik-Joon Chang

“…This paper presents an efficient in-memory hyperdimensional computing (HDC) design based on spin transfer-torque magnetoresistive RAM (STT-MRAM), named STT-HDC. …”
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Modelling flame-to-fuel heat transfer by deep learning and fire images by Caiyi Xiong, Zilong Wang, Xinyan Huang

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Simulation Model as an Element of Sustainable Autonomous Mobile Robot Fleet Management by Magdalena Dobrzańska, Paweł Dobrzański

Subjects: “…process modelling…”
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DIGITAL TECHNOLOGIES AS A MEANS OF ADAPTIVE LEARNING FOR HIGHER EDUCATION INFORMATICS AND MATHEMATICS by Олена Косовець, Олена Соя, Ярослав Крупський, Любов Тютюн

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Advanced tooth profile roughing system (Innovating gear skiving with diamond-shaped edge tools) by Hiroki YONEZAWA, Jun’ichi KANEKO, Takeyuki ABE, Akihiro NAKAZATO

Subjects: “…gear skiving process…”
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Software analysis of scientific texts: comparative study of distributed computing frameworks by Serik Altynbek, Gabit Shuitenov, Madi Muratbekov, Alibek Barlybayev

“…This study aims to conduct a study of popular distributed computing frameworks for scientific text processing. …”
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Fog computing based radio access networks：architecture，principles and challenges by Bonan YIN, Yuan AI, Mugen PENG

“…To reduce the burden of fronthaul link，avoid large-scale wireless signal processing in centralized baseband unit（BBU）pool，and take full advantage of processing and storage capabilities in edge devices，a fog computing based radio access network（F-RAN）was presented as an evolution form of heterogeneous cloud radio access networks.The core idea of F-RAN was to take full advantage of processing and storage capabilities in edge devices which could achieve the local distributed content delivery，the local distributed collaboration radio signal processing and the local distributed cooperative radio resource management functions.System architectures of F-RAN，promising key techniques，and researching open issues of F-RAN were discussed in detail.…”
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Multiobjective Offloading Optimization in Fog Computing Using Deep Reinforcement Learning by Hojjat Mashal, Mohammad Hossein Rezvani

“…Edge computing allows IoT tasks to be processed by devices with passive processing capacity at the network’s edge and near IoT devices instead of being sent to cloud servers. …”
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Edge Computing for Real-Time Climate Data Analysis in Smart Farming by Shnain Ammar Hameed, Abed Z., Annapoorna Errabelli

“…In smart farming, real-time insight is scheduled for the informed decision taking but the traditional ways of data collection and processing does not support such fast and accurate measurements. …”
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AUTOMATED THERMOGRAMM CALCULATION OF SAUSAGE COOKING BASED ON COMPUTER MODELS by A.B. LISITSYN, A.M. CHERNUKHA, A.V. BORODIN

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Federated learning based intelligent edge computing technique for video surveillance by Yu ZHAO, Jie YANG, Miao LIU, Jinlong SUN, Guan GUI

“…With the explosion of global data,centralized cloud computing cannot provide low-latency,high-efficiency video surveillance services.A distributed edge computing model was proposed,which directly processed video data at the edge node to reduce the transmission pressure of the network,eased the computational burden of the central cloud server,and reduced the processing delay of the video surveillance system.Combined with the federated learning algorithm,a lightweight neural network was used,which trained in different scenarios and deployed on edge devices with limited computing power.Experimental results show that,compared with the general neural network model,the detection accuracy of the proposed method is improved by 18%,and the model training time is reduced.…”
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Comparative analysis of computing platforms for onboard micromodule of provisional image recognition by V. A. Kovalev, D. A. Paulenka, E. V. Snezhko, V. A. Liauchuk, A. A. Kalinovski

“…The information provided in this paper could be useful for engineers and researchers who are developing compact budget mobile systems for processing, analyzing and recognition of images.…”
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Real-Time Threat Mitigation in Financial IT Infrastructures Using Quantum Computing by Jean Marie Vianney Sindayigaya

“…Quantum computing promises an unmatched level of scalable parallel processing with increased accuracy, speed, and timely response to realtime threats. …”
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Parallel cache-efficient code for computing the McCaskill partition functions by Marek Pałkowski, Włodzimierz Bielecki

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End-to-end switchless architecture for fault-tolerant photonic quantum computing by Paul Renault, Patrick Yard, Raphael C. Pooser, Miller Eaton, Hussain Asim Zaidi

“…Photonics represents one of the most promising approaches to large-scale quantum computation with millions of qubits and billions of gates, owing to the potential for room-temperature operation, high clock speeds, miniaturization of photonic circuits, and repeatable fabrication processes in commercial photonic foundries. …”
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Performance Analysis and Application of Mobile Blockchain in Mobile Edge Computing Architecture by Thiago Sandes, Admilson Lima, Edward Moreno

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