Bringing a health systems modelling approach to complex evaluations: multicountry applications in HIV, TB and malaria by Adama Faye, Stephen S Lim, Bernardo Hernandez Prado, Herbert Duber, David E Phillips, Guillermo Ambrosio, Audrey Batzel, Carmen Cerezo, Ibrahima Gaye, Bethany Huntley, Edgar Kestler, Constant Kingongo, Emily Linebarger, Jorge Matute, Godefroid Mpanya, Salva Mulongo, Caitlin O'Brien-Carelli, Erin Palmisano, Francisco Rios Casas, Roger Tine, Daniel Whitaker, Jennifer M Ross

“…As a result, it is challenging to evaluate programme implementation while reflecting real-world complexity. We present our experience in using a health systems modelling approach as part of a mixed-methods evaluation and describe applications of these models.Methods We developed a framework for how health systems translate financial inputs into health outcomes, with in-country and international experts. …”
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An Efficient Large-Scale Sensor Deployment Using a Parallel Genetic Algorithm Based on CUDA by Jae-Hyun Seo, Yourim Yoon, Yong-Hyuk Kim

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Deep learning-assisted terahertz intelligent detection and identification of cancer tissue by Xingyu Wang, Yafei Xu, Rong Wang, Nuoman Tian, Zhengpeng Zhu, Shuting Fan, Liuyang Zhang, Ruqiang Yan, Xuefeng Chen

“…By combining the THz detection technique and artificial intelligence technique, here we propose a dense and efficient channel attention network (DECANet) framework-based THz diagnosis system for cancer prescreening. …”
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PLL-VO： An Efficient and Robust Visual Odometry Integrating Point-Line Features and Neural Networks by L. Zhao, Y. Yang, D. Ma, X. Lin, W. Wang

“…To overcome the impact of complex lighting conditions, a self-supervised learning method for interest point detection and a line detection algorithm that combines line optical flow tracking with cross-constraints is presented. …”
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Insulator Defect Detection Algorithm Based on Improved YOLOv11n by Junmei Zhao, Shangxiao Miao, Rui Kang, Longkun Cao, Liping Zhang, Yifeng Ren

“…Ensuring the reliability and safety of electrical power systems requires the efficient detection of defects in high-voltage transmission line insulators, which play a critical role in electrical isolation and mechanical support. …”
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Intelligent Detection of Tomato Ripening in Natural Environments Using YOLO-DGS by Mengyuan Zhao, Beibei Cui, Yuehao Yu, Xiaoyi Zhang, Jiaxin Xu, Fengzheng Shi, Liang Zhao

“…To achieve accurate detection of tomato fruit maturity and enable automated harvesting in natural environments, this paper presents a more lightweight and efficient maturity detection algorithm, YOLO-DGS, addressing the challenges of subtle maturity differences between regular and cherry tomatoes, as well as fruit occlusion. …”
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Edge-Optimized Lightweight YOLO for Real-Time SAR Object Detection by Caiguang Zhang, Ruofeng Yu, Shuwen Wang, Fatong Zhang, Shaojia Ge, Shuangshuang Li, Xuezhou Zhao

“…Experimental results demonstrate that the proposed method achieves comparable detection performance to state-of-the-art YOLO variants while drastically reducing computational complexity (4.4 GFLOP) and parameter count (1.9 M). …”
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Contrastive Learning Algorithm for Low-Resource Cryptographic Attack Event Detection by Peng Luo, Rangjia Cai, Yuanbo Guo

“…Additionally, assigning appropriate weights to keywords of different event types and employing clustering methods for effective classification reduce reliance on manually labeled data, thereby facilitating the training of an efficient cryptographic attack event detection model. …”
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A Novel Approach to Speed Up Hampel Filter for Outlier Detection by Mario Roos-Hoefgeest Toribio, Alejandro Garnung Menéndez, Sara Roos-Hoefgeest Toribio, Ignacio Álvarez García

“…This paper proposes a novel Hampel filter variant that replaces the MAD with an original estimator (mMAD) that retains statistical robustness but is computationally more efficient. This reduces the filter’s computational complexity from <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>O</mi><mo>(</mo><mi>N</mi><mo>·</mo><mi>w</mi><mo form="prefix">log</mo><mi>w</mi><mo>)</mo></mrow></semantics></math></inline-formula> to <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>O</mi><mo>(</mo><mi>N</mi><mo>·</mo><mi>w</mi><mo>)</mo></mrow></semantics></math></inline-formula>, where <i>N</i> is the data length and <i>w</i> the window size. …”
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A Suggested Point Search Algorithm for Circle Detection in Binary Images by Sundus Ebraheem

“…The proposed algorithm was more efficient, where the average ratio of the running time for the proposed algorithm to HT method was 1:646, and the accuracy of the proposed algorithm was 100% for circles detection. …”
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Log Anomaly Detection Method Based on Transformer and Temporal Convolutional Networks by Niandong Liao, Zihan Liu

“…However, the rapid development of distributed technologies has led to the increasing scale and complexity of log data, resulting in existing methods facing difficulties in fully mining log features and information loss during parsing. …”
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Security anomaly detection for enterprise management network based on attention mechanism by Zhaohan You, Yucai Zheng

“…It is an enterprise management network security anomaly detection method based on deep learning, aiming to achieve efficient and intelligent monitoring and management of security anomaly data in enterprise management network. …”
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Adaptive Neuro-Fuzzy System for Detection of Wind Turbine Blade Defects by Lesia Dubchak, Anatoliy Sachenko, Yevgeniy Bodyanskiy, Carsten Wolff, Nadiia Vasylkiv, Ruslan Brukhanskyi, Volodymyr Kochan

“…Unmanned aerial vehicles are deployed to photograph the turbines, and these images are beamed back and processed for early defect detection. The proposed adaptive neuro-fuzzy inference system processes the data vectors with lower complexity and higher accuracy. …”
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Enhancing Cybersecurity: Hybrid Deep Learning Approaches to Smishing Attack Detection by Tanjim Mahmud, Md. Alif Hossen Prince, Md. Hasan Ali, Mohammad Shahadat Hossain, Karl Andersson

“…Experimental results demonstrate that the proposed CNN-Bi-GRU model outperforms existing approaches, achieving an overall highest accuracy of 99.82% in detecting SMS phishing messages. This study provides an empirical analysis of the effectiveness of hybrid deep learning techniques for SMS phishing detection, offering a more precise and efficient solution to enhance cybersecurity in mobile communications.…”
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TARGE: large language model-powered explainable hate speech detection by Muhammad Haseeb Hashir, Memoona, Sung Won Kim

“…The proliferation of user-generated content on social networking sites has intensified the challenge of accurately and efficiently detecting inflammatory and discriminatory speech at scale. …”
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Anomaly detection in encrypted network traffic using self-supervised learning by Sadaf Sattar, Shumaila Khan, Muhammad Ismail Khan, Ainur Akhmediyarova, Orken Mamyrbayev, Dinara Kassymova, Dina Oralbekova, Janna Alimkulova

“…ET-SSL extends the use of SSL based traffic classification in order to improve detection performance while keeping computational complexity low through the maximization of the difference between normal and anomalous traffic. …”
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Multi-defect detection and classification for aluminum alloys with enhanced YOLOv8. by Ying Han, Xingkun Li, Gongxiang Cui, Jie Song, Fengyu Zhou, Yugang Wang

“…Experimental results show that the proposed method performs effectively in target detection and classification. The number of model parameters is reduced from more than 300,000 to 160,000, significantly reducing the complexity of the model. …”
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Lightweight Pepper Disease Detection Based on Improved YOLOv8n by Yuzhu Wu, Junjie Huang, Siji Wang, Yujian Bao, Yizhe Wang, Jia Song, Wenwu Liu

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A Lightweight and Rapid Dragon Fruit Detection Method for Harvesting Robots by Fei Yuan, Jinpeng Wang, Wenqin Ding, Song Mei, Chenzhe Fang, Sunan Chen, Hongping Zhou

“…To enhance detection accuracy and satisfy the deployment constraints of edge devices, we propose YOLOv10n-CGD, a lightweight and efficient dragon fruit detection method designed for robotic harvesting applications. …”
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LNT-YOLO: A Lightweight Nighttime Traffic Light Detection Model by Syahrul Munir, Huei-Yung Lin

“…Moreover, most of the recent works only focused on daytime scenarios, often overlooking the significantly increased risk and complexity associated with nighttime driving. To address these critical issues, this paper introduces a novel approach for nighttime traffic light detection using the LNT-YOLO model, which is based on the YOLOv7-tiny framework. …”
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