Interpretable Chinese Fake News Detection With Chain-of-Thought and In-Context Learning by Bingyi Liu, Anqi Wang, Chengqian Xia

“…The spread of fake news through on-line platforms poses a significant threat to public trust and social stability, especially in resource-constrained Chinese domains. Existing Fake News Detection (FND) models often lack transparency, functioning as “black boxes” that limit their practical utility. …”
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TEDVIL: Leveraging Transformer-Based Embeddings for Vulnerability Detection in Lifted Code by Gary A. McCully, John D. Hastings, Shengjie Xu

“…Notably, these results are achieved when the embedding model is trained with a dataset of just 48,000 functions, demonstrating effectiveness in resource-constrained settings. …”
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Vulnerability detection method for blockchain smart contracts based on metamorphic testing by Jinfu CHEN, Zhenxin WANG, Saihua CAI, Qiaowei FENG, Yuhao CHEN, Rongtian XU, KwakuKudjo Patrick

“…Aimed at the defects of existing test methods, a vulnerability detection method for blockchain smart contracts based on metamorphic testing was proposed, which could generate test cases for specific functions in blockchain smart contracts to detect possible vulnerabilities.According to the possible security vulnerabilities, different metamorphosis relationships were designed and then metamorphic testing was performed.Through verifying whether the metamorphic relationship between the source test case and the subsequent test case was satisfied, whether the smart contract had related security vulnerabilities was judged.The experimental results show that the proposed method can effectively detect the security vulnerabilities in the smart contracts.…”
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Detecting Vegetation Stress in Mixed Forest Ecosystems Through the Joint Use of Tree‐Water Monitoring and Land Surface Modeling by C. D. Jiménez‐Rodríguez, G. Fabiani, R. Schoppach, K. Mallick, S. J. Schymanski, M. Sulis

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Developing a Machine Vision System to Detect Weeds from Potato Plant by Yousef Abbaspour Gılandeh, Hossein Javadıkıa, Sajad Sabzı

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An Efficient Algorithm for Small Livestock Object Detection in Unmanned Aerial Vehicle Imagery by Wenbo Chen, Dongliang Wang, Xiaowei Xie

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Highly Efficient Biphoton Generation from Thin Dense Atomic Ensemble by Heewoo Kim, Hansol Jeong, Han Seb Moon

“…Strongly correlated bright biphotons are generated via spontaneous four‐wave mixing from a dense atomic ensemble based on the 6S1/2–6P3/2–6D5/2 transition of 133Cs. Biphoton source achieves a detected biphoton count rate of 100 kilo‐counts per second, a heralding efficiency of 15%, and a maximum normalized crosscorrelation function value of 100 between the signal and idler photons, despite the low detector efficiency of a silicon avalanche photodetector being less than 25% at 917 nm. …”
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Failure Law of Sandstone and Identification of Premonitory Deterioration Information Based on Digital Image Correlation–Acoustic Emission Multi-Source Information Fusion by Zhaohui Chong, Guanzhong Qiu, Xuehua Li, Qiangling Yao

“…Additionally, by introducing the derivative functions of the multi-source information function for quantitative analysis, a comprehensive evaluation method was proposed based on the multi-source information fusion monitoring to forewarn red sandstone failure by levels during loading. …”
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Ti3C2Tx@Pt nanocomposite based colorimetric and electrochemical dual-mode platform for glucose detection by Xuming Sun, Mingyan Zhang, Jinlong Chang, Linyan Xie, Qiongqiong Ren, Wenshuai Jiang, Zhen Jin, Shiqi Pan, Xiuli Yang, Wu Ren

“…Glucose is the main source of energy in cellular metabolism and is essential for normal cellular function and growth. …”
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An enhanced lightweight model for apple leaf disease detection in complex orchard environments by Ge Wang, Wenjie Sang, Fangqian Xu, Yuteng Gao, Yue Han, Qiang Liu

“…However, in complex natural environments, factors such as light variations, shading from branches and leaves, and overlapping disease spots often result in reduced accuracy in detecting apple diseases. To address the challenges of detecting small-target diseases on apple leaves in complex backgrounds and difficulty in mobile deployment, we propose an enhanced lightweight model, ELM-YOLOv8n.To mitigate the high consumption of computational resources in real-time deployment of existing models, we integrate the Fasternet Block into the C2f of the backbone network and neck network, effectively reducing the parameter count and the computational load of the model. …”
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Object detection with afordable robustness for UAV aerial imagery: model and providing method by Viacheslav Moskalenko, Artem Korobov, Yuriy Moskalenko

“…The model and method for ensuring the robustness of resource-constrained neural network systems for object detection in aerial video surveillance. …”
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A Hybrid and Modular Integration Concept for Anomaly Detection in Industrial Control Systems by Christian Goetz, Bernhard G. Humm

“…Therefore, in this paper, we present a modular and hybrid concept that enables the integration of efficient and effective anomaly detection while optimising the use of available resources under consideration of industrial requirements. …”
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Application of metal nanoparticle-loaded nanocomposites for extraction, removal, and detection of mycotoxins in foods by Mehdi Maham, Reza Abedi-Firoozjah, Mohammad Hadi Moradiyan, Maryam Azizi Lalabadi, Elham Assadpour, Hamed Ahari, Seid Mahdi Jafari

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Real time wire rope detection method based on Rockchip RK3588 by Mengpeng Qian, Yong Wang, Shaoqing Liu, Zhanghou Xu, Zhenshan Ji, Ming Chen, Hailong Wu, Zuchao Zhang

“…To enhance non-destructive wire rope inspection, a Mini-YOLO model was developed by integrating MobileNetV3, the Coordinate Attention (CA) mechanism, and a novel loss function, Inner-IoU, into the YOLOv8 framework. This paper’s innovation lies not in creating algorithmic components from scratch, but in their synergistic integration and targeted optimization to solve the specific challenges of real-time defect detection on resource-constrained edge devices. …”
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SGSNet: a lightweight deep learning model for strawberry growth stage detection by Zhiyu Li, Jianping Wang, Guohong Gao, Yufeng Lei, Chenping Zhao, Yan Wang, Haofan Bai, Yuqing Liu, Xiaojuan Guo, Qian Li

“…Finally, the Inner-IoU optimization loss function is applied to accelerate model convergence and enhance detection accuracy.ResultsTesting results indicate that SGSNet performs exceptionally well across key metrics, achieving 98.83% precision, 99.45% recall, 99.14% F1 score, 99.50% mAP@0.5, and a loss value of 0.3534. …”
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ChiMSource improves the accuracy of studies on novel amino acid sequences by predicting alternative sources of mass spectrometry-derived peptides by Umut Çakır, Noujoud Gabed, Ali Yurtseven, Igor Kryvoruchko

“…Here, we present a highly flexible program that predicts alternative chimeric and non-chimeric sources of peptides detected by MS proteomics.…”
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A Feature-Selective Independent Component Analysis Method for Functional MRI by Yi-Ou Li, Tülay Adali, Vince D. Calhoun

“…In this work, we propose a simple and effective scheme to incorporate prior knowledge about the sources of interest (SOIs) in independent component analysis (ICA) and apply the method to estimate brain activations from functional magnetic resonance imaging (fMRI) data. …”
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An optimization method of multiscale storage tank target detection introducing an attention mechanism by Wenjia Sun, Chunchun Hu, Nianxue Luo, Qiansheng Zhao

“…As containers for chemical storage, storage tanks are potential sources of hazards. Conducting target detection for hazard risk analysis is essential. …”
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Application of Open-Source, Low-Code Machine-Learning Library in Python to Diagnose Parkinson's Disease Using Voice Signal Features by Daniel Hilário da Silva, Caio Tonus Ribeiro, Leandro Rodrigues da Silva Souza, Adriano Alves Pereira

“…Seventeen ML algorithms were applied to a dataset of voice recordings from Healthy Control and PD individuals, sourced from a publicly available repository. We leveraged the PyCaret Python library's ML algorithms and functions, which were introduced in this article, to demonstrate their simplicity and effectiveness in dealing with real-world data. …”
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Securing Electric Vehicle Performance: Machine Learning-Driven Fault Detection and Classification by Mahbub Ul Islam Khan, Md. Ilius Hasan Pathan, Mohammad Mominur Rahman, Md. Maidul Islam, Mohammed Arfat Raihan Chowdhury, Md. Shamim Anower, Md. Masud Rana, Md. Shafiul Alam, Mahmudul Hasan, Md. Shohanur Islam Sobuj, Md. Babul Islam, Veerpratap Meena, Francesco Benedetto

“…Electric vehicles (EVs) are commonly recognized as environmentally friendly modes of transportation. They function by converting electrical energy into mechanical energy using different types of motors, which aligns with the sustainable principles embraced by smart cities. …”
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