Physics field super-resolution reconstruction via enhanced diffusion model and fourier neural operator by Yanan Guo, Junqiang Song, Xiaoqun Cao, Chuanfeng Zhao, Hongze Leng

“…However, traditional numerical methods often entail high computational costs, involve complex data processing, and struggle to capture fine-scale high-frequency details. …”
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Flexibly Reconfigurable Kerr Micro-Comb Based on Cascaded Si₃N₄ Micro-Ring Filters by Jieyu Yang, Guang Chen, Lidan Lu, Jianzhen Ou, Chao Mei, Yingjie Xu, Wenbo Bo, Peng Wang, Xinyi Li, Lianqing Zhu

“…Due to the significance of flexibly controlled optical sources with high-repetition rates and multiple channels for system-on-chip, our proposal has potential in photonic integrated circuit systems, such as high-density photonic computing and large-capacity optical communications, in the future.…”
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Application research and effectiveness evaluation mechanism of hybrid intelligent algorithm integrating cognitive computing and deep learning for dynamically adjusting employee per... by Zhenlin Luo, Kebin Lu

“…Abstract This study investigates the impact of a hybrid intelligent algorithm, integrating cognitive computing and deep learning, on the dynamic adjustment of employee performance evaluation in multi-scale organizational networks, through simulation experiments. …”
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Energy Optimization and Efficiency Improvement Model for Enterprise Production Process Based on Deep Learning Under the Background of Carbon Peak and Carbon Neutrality by Hui Bai, Yiyi Chen, Hua Bai, Meiling Liu, Yu Fan

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A novel trace-based sampling method for conformance checking by Heidy M. Marin-Castro, Miguel Morales-Sandoval, José Luis González-Compean, Julio Hernandez

“…Under a big data scenario, traditional conformance checking methods struggle to analyzing the instances or traces in large event logs, increasing the associated computational cost. In this article, we study and address the conformance-checking task supported by a traces selection approach that uses representative sample data of the event log and thus reduces the processing time and computational cost without losing confidence in the obtained conformance value. …”
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A Temporal Attention-Based SARIMA-BiLSTM Residual Learning Model Tuned by Grey Wolf Optimizer for Parallel Urban Traffic Forecasting by Manas Kamal Das, Christopher Columbus Chinnappan, E. Elakiya

“…Furthermore, the entire pipeline is adapted for parallel execution to improve scalability and reduce computational latency, enabling faster processing of large-scale traffic data. …”
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Development of a numerical method for solving optimization problems approximation of the function given approximately and its derivatives based on the variational approach by Igor Naats, Victoria Igorevna Naats, Elena Yartseva

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An Automated Clubbed Fingers Detection System Based on YOLOv8 and U-Net: A Tool for Early Prediction of Lung and Cardiovascular Diseases by Wen-Shin Hsu, Guan-Tsen Liu, Su-Juan Chen, Si-Yu Wei, Wei-Hsun Wang

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AIoT: a taxonomy, review and future directions by Jiyi WU, Wenjuan LI, Jian CAO, Shiyou QIAN, Qifei ZHANG, Rajkumar BUYYA

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Gait Perception via Actual and Estimated Pneumatic Physical Reservoir Output by Junyi Shen, Tetsuro Miyazaki, Swaninda Ghosh, Toshihiro Kawase, Kenji Kawashima

“…Traditional approaches to gait perception—such as estimating joint angles and walking conditions—often rely on electronic sensors and neural networks, which can compromise wearability and impose high computational demands. Physical reservoir computing (PRC), which utilizes the inherent nonlinearity of physical systems for data processing, offers a promising alternative. …”
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Quantum classical hybrid convolutional neural networks for breast cancer diagnosis by Qiuyu Xiang, Dongfen Li, Zhikang Hu, Yuhang Yuan, Yuchen Sun, Yonghao Zhu, You Fu, Yangyang Jiang, Xiaoyu Hua

“…To address these issues, this paper adds a quantum convolutional layer to the classical convolutional neural network to take advantage of quantum computing to improve learning efficiency and processing speed. …”
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Design and evaluation of clock-gating-based approximate multiplier for error-tolerant applications by Venkata Sudhakar Chowdam, Suresh Babu Potladurty, Prasad Reddy karipireddy

“…Although approximation arithmetic affects the output accuracy in multipliers, it offers a realistic avenue for constructing power-, area--, and speed-efficient digital circuits. The approximation computing technique is commonly used in error-tolerant applications such as signal, image, and video processing. …”
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Intelligent deep learning for human activity recognition in individuals with disabilities using sensor based IoT and edge cloud continuum by Mohammed Maray

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Towards edge-collaborative,lightweight and secure region proposal network by Jinbo XIONG, Renwan BI, Qianxin CHEN, Ximeng LIU

“…Aiming at the problem of image privacy leakage and computing efficiency in edge environment,a lightweight and secure region proposal network (SecRPN) was proposed.A series of secure computing protocols were designed based on the additive secret sharing scheme.Two non-collusive edge servers cooperate to perform calculation modules such as secure feature processing,secure anchor transformation,secure bounding-box correction,and secure non-maximum suppression.Theoretical analysis guarantees the correctness and security of SecRPN.The actual performance evaluation shows that SecRPN is outstanding in the computational cost and communication overhead compared with the existing works.…”
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Transforming Farming with Technology: A Smart Novel Agriculture Framework and Infrastructure. by Mushtaque Ahmed Rahu

“…It includes communication technologies, IoT, WSN, autonomous vehicles, computing, and data processing. We also analyze the disparities between traditional and smart agriculture across various parameters. …”
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Uncertain edge coalition game based EIP revenue estimation strategy by ZHAO Shuxu, XIA Xinyu, WANG Xiaolong

“…In the edge computing environment, there are risks such as communication channel risks and edge server failures, which can lead to a mismatch between the computing resources required for task processing and the resources allocated by the edge coalition. …”
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Product collaborative filtering based recommendation systems for large-scale E-commerce by Trang Trinh, Van-Ho Nguyen, Nghia Nguyen, Duy-Nghia Nguyen

“…This paper introduces a product-based collaborative filtering approach utilizing Apache Spark, a powerful parallel processing framework to address the scalability issues of recommender systems in the cloud computing environment. …”
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Application of edge-cloud collaborative intelligence technologies in power grids by Qing HAN, Kunlun GAO, Ting ZHAO, Jiangqi CHEN, Xinyu YANG, Shusen YANG

“…With the continuous development of the Internet of things on electricity (IoTE) and large-scale deployment of intelligent edge devices, an explosively increasing amount of data are being generated at the network edge.The efficient, fast and secure processing and analysis of the massive edge located data brings great challenges for the traditional cloud computing-based intelligence technologies.Instead, edge-cloud collaborative intelligence (ECCI) technologies can significantly outperform the cloud computing-based intelligence in terms of the network bandwidth saving, delay reduction and privacy protection, and therefore have shown a great potential in boosting the development of power grids.To investigate the application of ECCI in power grids, the concept and research progress of ECCI were firstly introduced.The characteristics and advantages of ECCI were summarized and its applicability in the power grids were discussed.Secondly, the key technologies of ECCI applications for power grids were discussed and the solutions based on ECCI technologies for two typical scenes were proposed respectively.Finally, a brief discussion of future work was given.…”
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Implementing Holographic Reduced Representations for Spiking Neural Networks by Vidura Sumanasena, Daswin de Silva, Evgeny Osipov, Dmitri A. Rachkovskij, Ross W. Gayler

“…In this paper, we explore the potential of VSA as an intermediary abstraction layer to advance practical neuromorphic computing applications. We introduce a novel vectorised framework that efficiently processes parallel streams of spiking data by combining and computing them through VSA for real-time downstream learning tasks, leveraging spike latency encoding. …”
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Enhancing the e-commerce shopping experience with IoT-enabled smart carts in smart stores by Jian Wang

“…These tags enable smart shopping carts equipped with RFID readers to automatically scan items, allowing seamless billing directly from the cart and eliminating the need for manual payment processes. The study compares IoT architectures implemented within cloud and fog computing frameworks to optimize smart store shopping scenarios. …”
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