The influence of experimental imperfections on photonic GHZ state generation by Fabian Wiesner, Helen M Chrzanowski, Gregor Pieplow, Tim Schröder, Anna Pappa, Janik Wolters

“…While the advantages of photonic quantum computing, including direct compatibility with communication, are apparent, several imperfections such as loss and distinguishability presently limit actual implementations. …”
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Electric Field‐Driven Conformational Changes in Molecular Memristor and Synaptic Behavior by Chanjin Lim, Taegil Kim, YoungJu Park, Daeho Kim, ChaeHo Shin, Suji Ha, Jin‐Liang Lin, Yuan Li, Junwoo Park

“…Abstract This paper demonstrates the use of molecular artificial synapses in neuromorphic computing systems designed for low energy consumption. …”
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Flexible Natural Language-Based Image Data Downlink Prioritization for Nanosatellites by Ezra Fielding, Akitoshi Hanazawa

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Security Protection of Electrical Intelligent Sensors and Sensor Networks by Chunyan AN, Yang LU, Di ZHAI, Xueqiong ZHU

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Neuromorphic Readout for Hadron Calorimeters by Enrico Lupi, Abhishek, Max Aehle, Muhammad Awais, Alessandro Breccia, Riccardo Carroccio, Long Chen, Abhijit Das, Andrea De Vita, Tommaso Dorigo, Nicolas Ralph Gauger, Ralf Keidel, Jan Kieseler, Anders Mikkelsen, Federico Nardi, Xuan Tung Nguyen, Fredrik Sandin, Kylian Schmidt, Pietro Vischia, Joseph Willmore

“…We simulate hadrons impinging on a homogeneous lead tungstate (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>PbWO</mi><mn>4</mn></msub></semantics></math></inline-formula>) calorimeter using GEANT4 software to investigate how the resulting light yield and its temporal structure, as detected by an array of light-sensitive sensors, can be processed by a neuromorphic computing system. Our model encodes temporal photon distributions as spike trains and employs a fully connected spiking neural network to estimate the total deposited energy, as well as the position and spatial distribution of the light emissions within the sensitive material. …”
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Cost-aware cloud workflow scheduling using DRL and simulated annealing by Yan Gu, Feng Cheng, Lijie Yang, Junhui Xu, Xiaomin Chen, Long Cheng

“…However, the existing models are limited in handling independent tasks and cannot process workflows, which are prevalent in cloud computing and consist of related subtasks. …”
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Study on coded distributed fast Hadamard transform based non-binary LDPC code decoding algorithm by Rui LIU, Yong LI

“…Despite the excellent error correction performance and burst error resistance capability of non-binary LDPC codes, the complexity of the decoding algorithms hinders their broader application.In the classic FHT-QSPA decoding, the fast Hadamard transform (FHT) and its inverse transform (IFHT) have become the main bottleneck for updating the check nodes.Therefore, a coded distributed FHT scheme based on systematic MDS codes was proposed.In the scheme, the channel probability was modeled by the master node as a matrix and it was segmented, and those sub-matrices were encoded into redundant ones.Then, all the sub-matrices were offloaded to worker nodes to perform parallel FHT and IFHT, and the results were sent back to the master node for the final decoding.By embedding redundant information, the proposed scheme resolved the straggling problem, improving the efficiency, and accelerating the entire decoding process.Comparisons with other coded matrix multiplication schemes, the proposed scheme provides lower encoding complexity, higher numerical accuracy in decoding recovery, and maintains an efficient butterfly operation, effectively reducing the computational complexity of worker nodes.The time comparison and decoding performance analysis reveal that the proposed scheme achieves up to approximately 3.8 times acceleration compared to the traditional single-node FHT scheme, significantly enhances the FHT-QSPA decoding efficiency without affecting the decoding performance.…”
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Fog-Enabled IoT Robotic System for Efficient Date Palm Monitoring in Moroccan Oases by Baghrous Mohamed, Ezzouhairi Abdellatif

“…To overcome the latency, bandwidth, and energy inefficiencies associated with cloud-based solutions, the system integrates the fog computing paradigm. Fog computing brings computational resources closer to the data source, enabling real-time processing and decision-making while reducing network congestion. …”
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Study on coded distributed fast Hadamard transform based non-binary LDPC code decoding algorithm by Rui LIU, Yong LI

“…Despite the excellent error correction performance and burst error resistance capability of non-binary LDPC codes, the complexity of the decoding algorithms hinders their broader application.In the classic FHT-QSPA decoding, the fast Hadamard transform (FHT) and its inverse transform (IFHT) have become the main bottleneck for updating the check nodes.Therefore, a coded distributed FHT scheme based on systematic MDS codes was proposed.In the scheme, the channel probability was modeled by the master node as a matrix and it was segmented, and those sub-matrices were encoded into redundant ones.Then, all the sub-matrices were offloaded to worker nodes to perform parallel FHT and IFHT, and the results were sent back to the master node for the final decoding.By embedding redundant information, the proposed scheme resolved the straggling problem, improving the efficiency, and accelerating the entire decoding process.Comparisons with other coded matrix multiplication schemes, the proposed scheme provides lower encoding complexity, higher numerical accuracy in decoding recovery, and maintains an efficient butterfly operation, effectively reducing the computational complexity of worker nodes.The time comparison and decoding performance analysis reveal that the proposed scheme achieves up to approximately 3.8 times acceleration compared to the traditional single-node FHT scheme, significantly enhances the FHT-QSPA decoding efficiency without affecting the decoding performance.…”
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Cloud Service Broker Using Ontology-Based System by Neeraj Kumar Singh, Abhishek Jain, Shruti Arya, Pawan Bhambu, Tanya Shruti, Vipin Kumar Chaudhary

“…Cloud computing offers more advantages to clients and associations regarding capital uses and working cost investment funds. …”
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Generative AI-driven edge-cloud system for intelligent road infrastructure inspection by Naveed Ejaz, A.B.M. Bodrul Alam, Salimur Choudhury

“…The rapid advancement of edge computing and artificial intelligence (AI) has transformed infrastructure inspection by enabling real-time monitoring of roads, bridges, and pipelines. …”
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A cyber physical sustainable smart city framework toward society 5.0: Explainable AI for enhanced SDGs monitoring by Ali H. Hassan, Elsadig Musa Ahmed, Jamal M. Hussien, Riza bin Sulaiman, Mansoor Abdulhak, Hasan Kahtan

“…These components use four leading technologies: blockchain for secure data handling, B5G network function virtualizations, edge-cloud computing for scalable and flexible data processing and AI to deliver insights into the model’s data. …”
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IoT-based bed and ventilator management system during the COVID-19 pandemic by Vivek Kumar Prasad, Debabrata Dansana, S. Gopal Krishna Patro, Ayodeji Olalekan Salau, Divyang Yadav, Brojo Kishore Mishra

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Low-Latency Edge-Enabled Digital Twin System for Multi-Robot Collision Avoidance and Remote Control by Daniel Poul Mtowe, Lika Long, Dong Min Kim

“…Traditional approaches, which rely on centralized cloud processing or direct sensor-to-controller communication, are inherently limited by excessive network latency, bandwidth bottlenecks, and a lack of predictive decision-making, thus constraining their effectiveness in real-time multi-agent systems. …”
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Secure edge-based smart grid communication using lightweight authentication modeling with autoencoders and real-world data by Omar Abdullah Saleh, Mesut Cevik

“…Abstract The growing use of edge computing in intelligent grids presents security issues as a result of the limited processing capabilities of edge devices and the intensifying complexities of cyberattacks. …”
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Secure K-Means Clustering Scheme for Confidential Data Based on Paillier Cryptosystem by Zhengqi Zhang, Zixin Xiong, Jun Ye

“…The protocol uses the additive homomorphism property of the Paillier cryptosystem to perform K-means clustering on the encrypted data, which ensures the confidentiality of the data during the whole calculation process. The protocol consists of three main components: secure computation distance (SCD) protocol, secure cluster assignment (SCA) protocol and secure cluster center update (SUCC) protocol. …”
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TourismNeuro xLSTM: neuro-inspired xLSTM for rural tourism planning and innovation by Jing Jiang, You Li, You Li

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CGADNet: A Lightweight, Real-Time, and Robust Crosswalk and Guide Arrow Detection Network for Complex Scenes by Guangxing Wang, Tao Lin, Xiwei Dong, Longchun Wang, Qingming Leng, Seong-Yoon Shin

“…This research provides practical methodologies for deploying crosswalk and guide arrow detection networks on edge computing devices.…”
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Optimizing quantum convolutional neural network architectures for arbitrary data dimension by Changwon Lee, Israel F. Araujo, Dongha Kim, Junghan Lee, Siheon Park, Ju-Young Ryu, Ju-Young Ryu, Daniel K. Park, Daniel K. Park

“…This optimization is not only important for minimizing computational resources, but also essential in noisy intermediate-scale quantum (NISQ) computing, as the size of the quantum circuits that can be executed reliably is limited. …”
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Edge-Assisted Label-Flipping Attack Detection in Federated Learning by Nourah S. AlOtaibi, Muhamad Felemban, Sajjad Mahmood

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