The Role of VADER and SentiWordNet Labeling in Naïve Bayes Accuracy for Sentiment Analysis of Rice Price Increases by Ihtiar Nur Furqon, Dewi Soyusiawaty

“…SentiWordNet performs better for positive sentiment detection, reaching 77.86% accuracy and 96.22% recall at an 80:20 split but yields a low F1-score of 32.15% for negative sentiments. …”
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A new nuclear marker for quantitative analysis of wild boar and domestic pig meat in game meat products using PLAG1 zinc finger gene by Bukola M. Adenuga, Anita Spychaj, Magdalena Montowska

“…The assay achieved satisfactory performance parameters for fraud detection, reaching a sensitivity of 0.1 ng of wild boar or pig DNA, and both detection and quantification limits (LOD and LOQ) at 0.1% for raw and 0.5% (w/w) for thermally processed samples, respectively. …”
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Weed Detection Algorithms in Rice Fields Based on Improved YOLOv10n by Yan Li, Zhonghui Guo, Yan Sun, Xiaoan Chen, Yingli Cao

“…Ablation studies revealed that YOLOv10n-FCDS achieved a 2.6% increase in mean average precision at intersection over union 50% for weed detection, reaching 87.4%. The model also improved small target detection (increasing mAP50 by 2.5%), obscured weed detection (increasing mAP50 by 2.8%), and similar weed detection (increasing mAP50 by 3.0%). …”
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Exploring Transformer-Based Learning for Negation Detection in Biomedical Texts by Ghadeer Althari, Mohammad Alsulmi

“…Our findings show the potential of transformer-based learning for negation detection, reaching an accuracy of 99% for negation identification and a PCS of 95% for negation scope recognition.…”
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Electric Field-Enhanced SERS Detection Using MoS₂-Coated Patterned Si Substrate with Micro-Pyramid Pits by Tsung-Shine Ko, Hsiang-Yu Hsieh, Chi Lee, Szu-Hung Chen, Wei-Chun Chen, Wei-Lin Wang, Yang-Wei Lin, Sean Wu

“…The SERS results demonstrated that the intensity in the pits of the few-layer MoS₂/patterned Si SERS substrate was approximately 274 times greater compared to planar Si, with a limit of detection reaching 10⁻⁵ M. The experimental results confirm that this method effectively resolves the issue of random distribution of analyte molecules during droplet evaporation, thereby enhancing detection sensitivity and stability.…”
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Optimizing Liquid Electron Ionization Interface to Boost LC-MS Instrumental Efficiency by Tommaso Grazioso, Genny Grasselli, Adriana Arigò, Giorgio Famiglini, Achille Cappiello

“…The results show that a new combination of capillaries in the interface set up significantly improves instrumental detectability, reaching LOD values almost five times lower than those of the previous setup.…”
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Quantitative and sensitive detection of alpha fetoprotein in serum by a plasmonic sensor by Xiong Yang, Hu Huatian, Zhang Tianzhu, Xu Yuhao, Gao Fei, Chen Wen, Zheng Guangchao, Zhang Shunping, Xu Hongxing

“…The uniform gaps between the nanoparticles and gold film and the alignment of the gap modes relative to the excitation electric field endow this substrate with a uniform and strong SERS enhancement. The limit of detection reaches 1.45 fM, 697 times higher than that under normal excitation and 7800 times higher than a commercial enzyme-linked immunosorbent assay kit. …”
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Multisensor Track Occupancy Detection Model Based on Chaotic Neural Networks by Ze-xi Hua, Xiang-dong Chen

“…Moreover, the accuracy of detection reaches 99.9999%, which can help to greatly reduce the labor intensity of manual confirmation.…”
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The effect of using Naive Bayes to detect spam email by Sun Zehui

“…The results and analysis of the experimental dataset demonstrate that the accuracy of Park’s Bayesian algorithm in spam detection reaches an impressive 99.193%. This high level of accuracy underscores the effectiveness of the Bayesian approach in identifying and filtering out spam, thereby enhancing the overall efficiency and security of email communication.…”
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A Route to the Colorimetric Detection of Alpha-Fetoprotein Based on a Smartphone by Junjie Liu, Qingfubo Geng, Zhaoxin Geng

“…Testing has confirmed that this system can quantitatively analyze AFP using colorimetry. The limit of detection reached 0.083 ng/mL, and the average accuracy reached 90.81%. …”
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PUE Attack Detection in CWSN Using Collaboration and Learning Behavior by Javier Blesa, Elena Romero, Alba Rozas, Alvaro Araujo, Octavio Nieto-Taladriz

“…If the 20% of the nodes collaborates, the PUE detection reaches the 98% with less than 1% of false positives.…”
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Construction of advanced persistent threat attack detection model based on provenance graph and attention mechanism by Yuancheng LI, Hao LUO, Xinyu WANG, Jiexuan YUAN

“…In response to the difficulty of existing attack detection methods in dealing with advanced persistent threat (APT) with longer durations, complex and covert attack methods, a model for APT attack detection based on attention mechanisms and provenance graphs was proposed.Firstly, provenance graphs that described system behavior based on system audit logs were constructed.Then, an optimization algorithm was designed to reduce the scale of provenance graphs without sacrificing key semantics.Afterward, a deep neural network (DNN) was utilized to convert the original attack sequence into a semantically enhanced feature vector sequence.Finally, an APT attack detection model named DAGCN was designed.An attention mechanism was applied to the traceback graph sequence.By allocating different weights to different positions in the input sequence and performing weight calculations, sequence feature information of sustained attacks could be extracted over a longer period of time, which effectively identified malicious nodes and reconstructs the attack process.The proposed model outperforms existing models in terms of recognition accuracy and other metrics.Experimental results on public APT attack datasets show that, compared with existing APT attack detection models, the accuracy of the proposed model in APT attack detection reaches 93.18%.…”
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A hybrid clustering routing protocol based on machine learning and graph theory for energy conservation and hole detection in wireless sensor network by Mohammad Z Masoud, Yousef Jaradat, Ismael Jannoud, Mustafa A Al Sibahee

“…The accuracy of detection reached 98%. Moreover, network life time has prolonged 10%. …”
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Room‐Temperature Blackbody‐Sensitive Photodetector with Visible‐To‐Long‐Wavelength‐Infrared Photoresponse and Ultrafast Speed Based on a Te/PtSe2 Heterostructure by Zhiyuan Dai, Yu Yu, Haibiao Guan, Ruowen Wang, Tao Ye, Yonghao Bu, Jie Deng, Mengdie Shi, Rui Xin, Tianxin Li, Haibo Shu, Xiaoshuang Chen, Jing Zhou

“…The peak responsivity and specific detectivity reach 196.8 A W−1, and 4.3 × 109 cm Hz1/2 W−1, respectively, at the wavelength of 3.32 µm. …”
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Low-Illumination Parking Scenario Detection Based on Image Adaptive Enhancement by Xixi Xu, Meiqi Zhang, Hao Tang, Weiye Xu, Bowen Sun, Zhu’an Zheng

“…Experiments show that the algorithm makes the image pixel value distribution more balanced in low-light scenarios, the accuracy of parking space recognition reaches 95.46%, and the mean average precision of obstacle detection reaches 90.4%, which is better than the baseline algorithms, and is of great significance for the development of automatic parking sensing technology.…”
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Research on Traffic Marking Segmentation Detection Algorithm Based on Feature Fusion by Zhonghe He, Zizheng Gan, Pengfei Gong, Min Li, Kailong Li

“…The results show that the index MIoU (Mean Intersection over Union) of traffic marking segmentation detection reaches 61.44% and 70.15%, thus achieving a more perfect road traffic marking detection and right-of-way information perception and proving the effectiveness of the integrated traffic marking detection method designed in this paper.…”
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YOLO-RGDD: A Novel Method for the Online Detection of Tomato Surface Defects by Ziheng Liang, Tingting Zhu, Guang Teng, Yajun Zhang, Zhe Gu

“…The experimental results show that the average precision, recall, and F1-score of the proposed YOLO-RGDD model for tomato defect detection reach 88.5%, 85.7%, and 87.0%, respectively, surpassing advanced object recognition detection algorithms. …”
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Real‐Time Flood Inundation Modeling With Flow Resistance Parameter Learning by Alexander Young, John D. Albertson, Giovanni Moretti, Stefano Orlandini

“…Performance metrics like critical success index and probability of detection reach values above 90% across the flood plain.…”
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Efficient Small Object Detection You Only Look Once: A Small Object Detection Algorithm for Aerial Images by Jie Luo, Zhicheng Liu, Yibo Wang, Ao Tang, Huahong Zuo, Ping Han

“…In the VisDrone2019 test set, when the input size is uniformly 640 × 640 pixels, the parameters of ESOD-YOLO are 4.46 M, and the average mean accuracy of detection reaches 29.3%, which is 3.6% higher than the baseline method YOLOv8n. …”
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Pattern transition recognition based on transfer learning for exoskeleton across different terrains by Yifan Gao, Jianbin Zheng, Yang Gao, Ziyao Chen, Jing Tang, Liping Huang

“…The accuracy of pattern transition detection reaches 97.46%, 97.62%, and 98.21% in M0, M20, and M40, respectively. …”
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