A Multi-Branch Convolution and Dynamic Weighting Method for Bearing Fault Diagnosis Based on Acoustic–Vibration Information Fusion by Xianming Sun, Yuhang Yang, Changzheng Chen, Miao Tian, Shengnan Du, Zhengqi Wang

“…Additionally, when processing acoustic signals, a depthwise separable convolutional network is used, effectively reducing computational complexity. Experimental results demonstrate that our method significantly outperforms other algorithms in terms of convergence speed and final performance. …”
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Evaluation of the Cost of Intelligent Upgrades of Transportation Infrastructure for Intelligent Connected Vehicles by Zongwei Liu, Haokun Song, Hong Tan, Han Hao, Fuquan Zhao

“…The costs of RSUs, LIDARS, and edge computing servers as well as data transmission rate of 5G are key elements affecting the costs of intelligent upgrades of transportation infrastructure.…”
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Assessing left main bifurcation anatomy and haemodynamics as a potential surrogate for disease risk in suspected coronary artery disease without stenosis by R. Gharleghi, M. Zhang, C. Shen, M. Webster, C. Ellis, S. Beier

“…This is especially powerful with the latest computing resources and may unlock clinical integration via standard imaging modalities as biomarkers without further computationally expensive simulations.…”
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SS-YOLO: A Lightweight Deep Learning Model Focused on Side-Scan Sonar Target Detection by Na Yang, Guoyu Li, Shengli Wang, Zhengrong Wei, Hu Ren, Xiaobo Zhang, Yanliang Pei

“…The lightweight design is essential for reducing computational complexity and resource consumption, allowing the model to be more efficient on edge devices with limited processing power and storage. …”
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Production of Biogas and Bio-fertilizer from Abattoir Waste as Sustainable Management, Eastern Ethiopia, 2019 by Sina Temsgen Tolera, Fekade Ketema Alemu

“…The magnitude of abattoir waste composition were computed based on Aneibo mathematical computational from the actual number of  slaughtered livestock. …”
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Preface by Susanne Ditlevsen, Petr Lansky

“…A variety of problems in computational neuroscienceaccompanied with a rich diversity of mathematical tools and approachesare presented. …”
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Accelerated Modeling of Transients in Electromagnetic Devices Based on Magnetoelectric Substitution Circuits by Sergii Tykhovod, Ihor Orlovskyi

“…The resulting dangerous current surges are best studied by computer simulation. However, the time required for computer simulation of such processes is significant for complex electromagnetic devices, which is undesirable. …”
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Signals of propaganda-Detecting and estimating political influences in information spread in social networks. by Alon Sela, Omer Neter, Václav Lohr, Petr Cihelka, Fan Wang, Moti Zwilling, John Phillip Sabou, Miloš Ulman

“…While computational propaganda influences modern society, it is hard to measure or detect it. …”
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Hybrid optimization of EDLP and high-low pricing strategies by Hamed Karimi

“…This linearization simplifies the computational process, enabling the model to scale and be applied in large retail settings. …”
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Adversarial examples defense method based on multi-dimensional feature maps knowledge distillation by Baolin QIU, Ping YI

“…The neural network approach has been commonly used in computer vision tasks.However, adversarial examples are able to make a neural network generate a false prediction.Adversarial training has been shown to be an effective approach to defend against the impact of adversarial examples.Nevertheless, it requires high computing power and long training time thus limiting its application scenarios.An adversarial examples defense method based on knowledge distillation was proposed, reusing the defense experience from the large datasets to new classification tasks.During distillation, teacher model has the same structure as student model and the feature map vector was used to transfer experience, and clean samples were used for training.Multi-dimensional feature maps were utilized to enhance the semantic information.Furthermore, an attention mechanism based on feature map was proposed, which boosted the effect of distillation by assigning weights to features according to their importance.Experiments were conducted over cifar100 and cifar10 open-source dataset.And various white-box attack algorithms such as FGSM (fast gradient sign method), PGD (project gradient descent) and C＆amp;W (Carlini-Wagner attack) were applied to test the experimental results.The accuracy of the proposed method on Cifar10 clean samples exceeds that of adversarial training and is close to the accuracy of the model trained on clean samples.Under the PGD attack of L2 distance, the efficiency of the proposed method is close to that of adversarial training, which is significantly higher than that of normal training.Moreover, the proposed method is a light-weight adversarial defense method with low learning cost.The computing power requirement is far less than that of adversarial training even if optimization schemes such as attention mechanism and multi-dimensional feature map are added.Knowledge distillation can learn the decision-making experience of normal samples and extract robust features as a neural network learning scheme.It uses a small amount of data to generate accurate and robust models, improves generalization, and reduces the cost of adversarial training.…”
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Machine learning-based prediction of hemodynamic parameters in left coronary artery bifurcation: A CFD approach by Sara Malek, Arshia Eskandari, Mahkame Sharbatdar

“…Hemodynamic parameters (TAWSS and OSI) were computed using CFD simulations and utilized for ML model training. …”
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A Massively Parallel SMC Sampler for Decision Trees by Efthyvoulos Drousiotis, Alessandro Varsi, Alexander M. Phillips, Simon Maskell, Paul G. Spirakis

“…A widely used approach to reducing an algorithm’s runtime is to employ modern multi-core computer architectures, either with shared memory (SM) or distributed memory (DM), and use parallel computing to accelerate the algorithm. …”
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Production of Biogas and Bio-fertilizer from Abattoir Waste as Sustainable Management, Eastern Ethiopia, 2019 by Sina Temsgen Tolera, Fekade Ketema Alemu

“…The magnitude of abattoir waste composition were computed based on Aneibo mathematical computational from the actual number of  slaughtered livestock. …”
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Semantic Segmentation Method for High-Resolution Tomato Seedling Point Clouds Based on Sparse Convolution by Shizhao Li, Zhichao Yan, Boxiang Ma, Shaoru Guo, Hongxia Song

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A Two-Point Association Tracking System Incorporated With YOLOv11 for Real-Time Visual Tracking of Laparoscopic Surgical Instruments by Nyi Nyi Myo, Apiwat Boonkong, Kovit Khampitak, Daranee Hormdee

“…Real-time tracking of surgical instruments allows for more accurate maneuvering, reduces the risk of accidental tissue damage, and enables the development of advanced computer-assisted surgical systems. In this context, advancements in deep learning, particularly through detection models and modern tracking algorithms, have opened new avenues for addressing the challenges posed by real-time laparoscopic instrument tracking. …”
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Model-Free Change Point Detection for Mixing Processes by Hao Chen, Abhishek Gupta, Yin Sun, Ness Shroff

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Prevalence and associated risk factors of bovine Schistosoma and Fasciola infections among cattle in South Achefer District, North West Ethiopia by Solomon Tesfaye, Mastewal Yeshambel, Amir Alelign, Tilahun Yohannes

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A Novel Air-to-Ground Communication Scheme for Advanced Big Data Collection in Smart Farming Using UAVs by Georgios A. Kakamoukas, Thomas D. Lagkas, Vasileios Argyriou, Sotirios K. Goudos, Panagiotis Radoglou-Grammatikis, Stamatia Bibi, Panagiotis G. Sarigiannidis

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Enhancing Building Evacuation Efficiency in Case of Fire Breakout by Integrating Evacuee Categorization Into an Agent-Based Simulation by Selain K. Kasereka, Noella E. Kalondji, Godwill W. K. Ilunga, Ruffin-Benoit M. Ngoie, Kyandoghere Kyamakya, Nathanael M. Kasoro

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Seasonal Variability of PM10 Chemical Composition Including 1,3,5-triphenylbenzene, Marker of Plastic Combustion and Toxicity in Wadowice, South Poland by Przemysław Furman, Katarzyna Styszko, Alicja Skiba, Damian Zięba, Mirosław Zimnoch, Magdalena Kistler, Anne Kasper-Giebl, Stefania Gilardoni

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