Secure fault-tolerant code for cloud storage by Peng-xu TAN, Yue CHEN, Ju-long LAN, Hong-yong JIA

“…A secure regenerating code,called SRCS was proposed to solve the security problem during the process of the fault-tolerant of storage systems,especially the storage system in an extremely open environment such as cloud computing and cloud storage.SRCS achieves the security of the encoding matrix in the regenerating code using the threshold public-key encryption with low redundancy and high efficiency.It is proven that SRCS is secure in the semi-adaptive model using decisional BDHE assumption.…”
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Hardware implementation of a configurable and power-efficient current conveyor architecture by Ahmed Reda Mohamed, Muneer A. Al Absi

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Parallel and distributed chimp-optimized LSTM for oil well-log reconstruction in China by Zisong Wang, Zhiliang Cheng, Wenxiang Wang, Xiujian Ding, Lu Xia

“…PDCOA’s primary goal is to speed up the process of hyperparameter tuning for LSTMs by letting them work in parallel and across multiple computers, with separate groups of computers communicating with each other regularly to ensure the system is diverse and reliable. …”
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Damage toughness assessment method of power backbone communication network based on power big data by Xue HAN

“…The damage toughness assessment method of power backbone communication network based on power big data was studied, and the damage toughness assessment results were used to formulate protection strategies and improve the network survivability.The power backbone communication network and the attacker were set as the two sides of the game, and the Nash equilibrium strategy of both sides was determined by the minimax method.The damage probability of nodes was obtained by the Nash equilibrium strategy, and the node damage probability was transformed into the network damage form.According to the network damage pattern, the repair conditions contained in the power big data were obtained by cloud computing technology.According to the importance of each node, the repair resources and repair budget were allocated to the nodes in order.The performance time-history response curve of the power backbone communication network was constructed, and the dynamic evaluation results of the network damage toughness were output.The experimental results show that all operations using cloud computing technology to process massive power big data can not exceed 330 ms.When the repair budget and repair resources are the highest, the damage toughness of the power backbone communication network can reach 0.925 at most, indicating that this method can effectively evaluate the damage toughness of the power backbone communication network.…”
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Damage toughness assessment method of power backbone communication network based on power big data by Xue HAN

“…The damage toughness assessment method of power backbone communication network based on power big data was studied, and the damage toughness assessment results were used to formulate protection strategies and improve the network survivability.The power backbone communication network and the attacker were set as the two sides of the game, and the Nash equilibrium strategy of both sides was determined by the minimax method.The damage probability of nodes was obtained by the Nash equilibrium strategy, and the node damage probability was transformed into the network damage form.According to the network damage pattern, the repair conditions contained in the power big data were obtained by cloud computing technology.According to the importance of each node, the repair resources and repair budget were allocated to the nodes in order.The performance time-history response curve of the power backbone communication network was constructed, and the dynamic evaluation results of the network damage toughness were output.The experimental results show that all operations using cloud computing technology to process massive power big data can not exceed 330 ms.When the repair budget and repair resources are the highest, the damage toughness of the power backbone communication network can reach 0.925 at most, indicating that this method can effectively evaluate the damage toughness of the power backbone communication network.…”
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Federated deep reinforcement learning-based edge collaborative caching strategy in space-air-ground integrated network by LIU Liang, JING Tengxiang, DUAN Jie, MAO Wuping, YAN Hongcheng, MA Wenjie

“…To address the problem of limited network coverage in remote areas, combining space-air-ground integrated network with mobile edge computing could provide low-latency and high-reliability transmissions for user requests in these areas, as well as timely caching services. …”
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Research on Spaceborne Neural Network Accelerator and Its Fault Tolerance Design by Yingzhao Shao, Junyi Wang, Xiaodong Han, Yunsong Li, Yaolin Li, Zhanpeng Tao

“…This fault-tolerant architecture analyzes the hardware accelerator, parameter storage, and actual computation, employing data validation to reinforce model parameters and spatial and temporal TMR to reinforce accelerator computations. …”
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5G defense network using commercial gNodeB with zero trust architecture by Woocheol Kim, Sunji Oh, Chang-Gyu Lim, Kiwon Kim, Jongkuk Lee, Hea-Sook Park

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Interaction, Artificial Intelligence, and Motivation in Children’s Speech Learning and Rehabilitation Through Digital Games: A Systematic Literature Review by Chra Abdoulqadir, Fernando Loizides

“…This review of the state of the art examines the role of serious games, Artificial Intelligence (AI), and Natural Language Processing (NLP) in speech rehabilitation, with a particular focus on interaction modalities, engagement autonomy, and motivation. …”
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Wireless Sensor Networks in Environmental Monitoring Applications Challenges and Future Directions by R Suganya, P Balaramesh, S Kannadhasan, V Chandrasekhar, S R Arun Raj, R Dhilipkumar

“…Chivalry: Signal Processing for WMSNs Humanoid vertical lace up boot where the lacing up shoes are made of suede or synthetic leather. …”
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DRL-Driven Intelligent SFC Deployment in MEC Workload for Dynamic IoT Networks by Seyha Ros, Intae Ryoo, Seokhoon Kim

“…The framework introduces task offloading and a dynamic resource orchestration strategy, where task offloading to the MEC server ensures an efficient distribution of computation workloads. The dynamic resource orchestration process, Service Function Chaining (SFC) for Virtual Network Functions (VNFs) placement, and routing path determination optimize service execution across the network. …”
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ZnO-SnO2/WO3-x heterojunction artificial synapse for realization and integration of multiple biological cognitive functions by Pengfei Sun, Ruidong Li, Haotian Meng, Tao Sun, Song Gao, Yang Li

“…In current memristor-based neuromorphic computing research, several studies face the challenge of realizing only a single function at a time or having isolated functions. …”
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Rétroaction dans les processus numériques de conception by Sébastien Bourbonnais

“…The goal is to show that the knowledge embedded by the various computer programs will have led to a real overhaul of design knowledge, as part of the implementation of a new epistemology, driven by digital design processes.…”
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APPSO‐NN: An adaptive‐probability particle swarm optimization neural network for sensorineural hearing loss detection by Jingyuan Yang, Yu‐Dong Zhang

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Dataset Gambar Wajah untuk Analisis Personal Identification by Syefrida Yulina, Hoky Nawa

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Introducing KeyRing self‐timed microarchitecture and timing‐driven design flow by Mickael Fiorentino, Claude Thibeault, Yvon Savaria

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Listener Acoustic Personalization Challenge - LAP24: Head-Related Transfer Function Upsampling by Aidan O. T. Hogg, Roberto Barumerli, Rapolas Daugintis, Katarina C. Poole, Fabian Brinkmann, Lorenzo Picinali, Michele Geronazzo

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P-TAME: Explain Any Image Classifier With Trained Perturbations by Mariano V. Ntrougkas, Vasileios Mezaris, Ioannis Patras

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Max–Min semantic chunking of documents for RAG application by Csaba Kiss, Marcell Nagy, Péter Szilágyi

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Sparsity‐optimised farrow structure variable fractional delay filter for wideband array by Wenjing Zhou, Mingwei Shen, Min Xu, Guodong Han, Yudong Zhang

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