EventSegNet: Direct Sparse Semantic Segmentation from Event Data by Pengju Li, Yuqiang Fang, Jiayu Qiu, Jun He, Jishun Li, Qinyu Zhu, Xia Wang, Yasheng Zhang

“…Semantic segmentation tasks encompass various applications, such as autonomous driving, medical imaging, and robotics. …”
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Apply IOT technology to practice a pandemic prevention body temperature measurement system: A case study of response measures for COVID-19 by Wei-Ling Lin, Chun-Hung Hsieh, Tung-Shou Chen, Jeanne Chen, Jian-Le Lee, Wei-Chung Chen

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Prediction of Pt, Ir, Ru, and Rh complexes light absorption in the therapeutic window for phototherapy using machine learning by V. Vigna, T. F. G. G. Cova, A. A. C. C. Pais, E. Sicilia

“…By compiling a dataset of 9775 complexes from the Reaxys database, we trained six classification models, including random forests, support vector machines, and neural networks, utilizing various molecular descriptors. Our findings indicate that the Extreme Gradient Boosting Classifier (XGBC) paired with AtomPairs2D descriptors delivers the highest predictive accuracy and robustness. …”
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Dynamic Demodulation Algorithm for Bio-radar Sensors Based on Range Tapper by Changyu LIU, Hao ZHANG, Fanglin GENG, Zhongrui BAI, Peng WANG, Zhenfeng LI, Lidong DU, Xianxiang CHEN, Zhen FANG

“…Using range Fourier transform, the heartbeat and breathing signals can be extracted from quasi-static targets across various distance intervals, thereby improving monitoring accuracy. …”
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Comparative analysis of harmonic sensitivity for stator fault diagnosis in induction motors by Allal Abderrahim, Lamouchi Zakaria, Abderrahmane Khechekhouche, Antonio Marcos de Oliveira Siqueira, Julio César Costa Campos, Kheireddine Lamamra

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Lightweight Apple Leaf Disease Detection Algorithm Based on Improved YOLOv8 by LUO Youlu, PAN Yonghao, XIA Shunxing, TAO Youzhi

“…[Results and Discussions]Compared to the original model, the improved model showed significant improvements in various performance metrics. The mAP50 and mAP50:95 achieved 88.2% and 37.0% respectively, which were 2.7% and 1.3% higher than the original model. …”
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A Study of the anthrax transmission model in herbivorous animals involving vaccination and harvesting by Anita Triska, Mona Zevika

“…Caused by the bacterium Bacillus anthracis, anthrax is a serious zoonotic disease with a mortality rate of up to 60%. …”
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The Effect of Interlayer on Water Cut Rise in a Bottom Water Reservoir by Yunpeng Hu, Xiaoling Zhang, Wei Ding, Ziyun Cheng, Liangchao Qu, Penghui Su, Chunliu Sun, Wenqi Zhang

“…At the same time, in the production process, the pressure drop generated by the formation is mainly concentrated near the wellbore, which leads to a short period of waterless oil production, fast water breakthrough, and fast water cut rise, which seriously affects the overall recovery factor and increases the risk of oil filed exploitation. …”
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Network Design and Route Analysis Using Outside Plant by Isaac Adjaye Aboagye, Nii Longdon Sowah, Wiafe Owusu-Banahene, Aryee Shaelijah, Margaret Ansah Richardson, Emmanuel Baah-Boadi

“…FAT Power (dBm) for feeder lines 1, 2, 3, and 4 and distribution lines 1, 2, 3, and 4, respectively, were all within the acceptable range. …”
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Gridless DOA Estimation with Extended Array Aperture in Automotive Radar Applications by Pengyu Jiang, Silin Gao, Jie Zhao, Zhe Zhang, Bingchen Zhang

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Correlation between Acoustic Feature and Sensory Crispness of Different Puffed Food Based on Energy Release Analysis by Chengkai ZHU, Xinnan HU, Zhili JI, Wangyang SHEN, Xiwu JIA

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Preliminary Selection of Device Materials to Locally Transform Thermal into SFR Neutron Spectrum by N. Chrysanthopoulou, P. Savva, M. Varvayanni, C. Colin, C. Huot-Marchand, N. Catsaros

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Recent breakthroughs of non-thermal cold plasma food processing: A review by Muhammad Umair, Song Xun, Saqib Jabbar, Muhammad Abid, Muhammad Shahid Riaz Rajoka, He Zhendan

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<i>Macrostomum lignano</i> as a model to study the genetics and genomics of parasitic flatworms by K. V. Ustyantsev, V. Yu. Vavilova, A. G. Blinov, E. V. Berezikov

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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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Visualization of Observational Learning and Peer Influence on Plastic Waste Diversity in the Campus Environment Using ArcGIS by Nüket Sivri, Atilla Aydoğdu, Vildan Zülal Sönmez, Ceyhun Akarsu

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You Only Attack Once: Single-Step DeepFool Algorithm by Jun Li, Yanwei Xu, Yaocun Hu, Yongyong Ma, Xin Yin

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Performance Degradation of Subsea Shield Tunnel Segment Accounting for Concrete Strength Loss and Steel Bar Corrosion by Jiaqi Guo, Weiling Yang, Chong Xu, Bo Peng, Jinhai Lin, Yuan Qian

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Acoustic interaction of submerged thin-shell structures considering seabed reflection effects by Xin Zhang, Kai Ai, Sen Yang, Sen Yang, Qingxiang Pei, Qingxiang Pei, Guang Lei, Guang Lei

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Multi-terminal flexible DC grid circuit breaker withstands multi-lightning strike analysis by Yutao Tang, Hongchun Shu, Kai He, Yue Dai, Yu Kuang, Yiming Han, Weijie Lou

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