Revisiting reproducibility in transportation simulation studies by Kevin Riehl, Anastasios Kouvelas, Michail A. Makridis

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Comprehensive data of 10 fruit leaf classes captured for agricultural AI applicationsMendeley Data by Minhajul Abedin, Sujon Islam, Naznin Sultana

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Real-Time Stringing Detection for Additive Manufacturing by Oumaima Charia, Hayat Rajani, Inés Ferrer Real, Miquel Domingo-Espin, Nuno Gracias

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Fast, Robust, and Laser-Free Universal Entangling Gates for Trapped-Ion Quantum Computing by Markus Nünnerich, Daniel Cohen, Patrick Barthel, Patrick H. Huber, Dorna Niroomand, Alex Retzker, Christof Wunderlich

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COMPARATIVE ANALYSIS OF THE COMPUTER VISION SYNDROME BETWEEN THE DEVELOPED EU COUNTRIES AND REPUBLIC OF SERBIA by Dejan VIDUKA, Ana BAŠIĆ, Petra BALABAN

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Visual information perception system of coal mine comprehensive excavation working face for edge computing terminal by Dongyang Zhao, Guoyong Su, Pengyu Wang

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Monthly Rainfall Estimation Using Data-Mining Process by Özlem Terzi

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PSI-Toolkit: A Natural Language Processing Pipeline by Filip Graliński, Krzysztof Jassem, Marcin Junczys-Dowmunt

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A Multilingual Integrated Framework for Processing Lexical Collocations by Violeta Seretan

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Syntactic Processing Using the Generalized Perceptron and Beam Search by Yue Zhang, Stephen Clark

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Language Processing with Perl and Prolog: Theories, Implemetation, and Application by Wei Lu

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Context Aware Task Orchestration With Deep Reinforcement Learning in Real Time Fog Computing Simulation Environment by Alp Gokhan Hossucu, Suat Ozdemir

“…In the ever-evolving landscape of cloud computing, fog and edge computing have become more prominent because of their natural property of proximity to demanding parts. …”
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Minimizing Delay and Power Consumption at the Edge by Erol Gelenbe

“…These results are obtained with a mathematical model of a multiple-server edge system that is managed by a task distribution platform, whose equations are derived and solved using methods from stochastic processes. This approach has low computational cost and provides simple linear complexity formulas to compute the fraction of tasks that should be assigned to the different servers to achieve minimum latency and minimum energy consumption.…”
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Split Edge-Cloud Neural Networks for Better Adversarial Robustness by Salmane Douch, Mohamed Riduan Abid, Khalid Zine-Dine, Driss Bouzidi, Driss Benhaddou

“…SNNs feature a neural network architecture with multiple early exit points, allowing the model to make confident decisions at earlier layers without processing the entire network. This not only reduces memory and computational demands but it also makes SNNs well-suited for edge computing applications. …”
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Fault-tolerant and mobility-aware loading via Markov chain in mobile cloud computing by Ning Wang, Ya Li, Yuanbang Li, Huanxin Nie

“…As an alternate, mobile cloud computing (MCC) makes good use of cloud resources to boost mobile devices’ storage and processing capabilities. …”
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Dynamic multi-criteria scheduling algorithm for smart home tasks in fog-cloud IoT systems by Ruchika Bhakhar, Rajender Singh Chhillar

“…DMCS dynamically allocates tasks based on criteria such as computational complexity, urgency, and data size, ensuring that time-sensitive tasks are processed swiftly on fog nodes while resource-intensive computations are handled by cloud data centers. …”
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Optical neuromorphic computing via temporal up-sampling and trainable encoding on a telecom device platform by Manuylovich Egor, Stoliarov Dmitrii, Saad David, Turitsyn Sergei K.

“…Mapping input signals to a high-dimensional space is a critical concept in various neuromorphic computing paradigms, including models such as reservoir computing (RC) and extreme learning machines (ELM). …”
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Improved salp swarm algorithm based optimization of mobile task offloading by Aishwarya R., Mathivanan G.

“…Background The realization of computation-intensive applications such as real-time video processing, virtual/augmented reality, and face recognition becomes possible for mobile devices with the latest advances in communication technologies. …”
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A hybrid fog-edge computing architecture for real-time health monitoring in IoMT systems with optimized latency and threat resilience by Umar Islam, Mohammed Naif Alatawi, Ali Alqazzaz, Sulaiman Alamro, Babar Shah, Fernando Moreira

“…Fog computing enables processing of time-critical data closer to the data source, reducing response time and relieving cloud system overload. …”
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A Feasibility Study on Indoor Localization and Multiperson Tracking Using Sparsely Distributed Camera Network With Edge Computing by Hyeokhyen Kwon, Chaitra Hegde, Yashar Kiarashi, Venkata Siva Krishna Madala, Ratan Singh, ArjunSinh Nakum, Robert Tweedy, Leandro Miletto Tonetto, Craig M. Zimring, Matthew Doiron, Amy D. Rodriguez, Allan I. Levey, Gari D. Clifford

“…Our pipeline consists of 39 edge computing camera systems equipped with tensor processing units (TPUs) placed in the indoor space's ceiling. …”
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