A novel framework to intercept GPS-denied, bomb-carrying, non-military, kamikaze drones: Towards protecting critical infrastructures by Athanasios N. Skraparlis, Klimis S. Ntalianis, Nicolas Tsapatsoulis

“…This paper, focuses on the aforementioned under-researched field, where the G-B-KD is confronted by two defensive drones. …”
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Global Maximum Power Point Tracking of Photovoltaic Systems Using Artificial Intelligence by Rukhsar, Aidha Muhammad Ajmal, Yongheng Yang

“…Traditional maximum power point tracking (MPPT) algorithms have several drawbacks on tracking the global maximum power point (GMPP) under partial shading conditions (PSCs). …”
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Silent speech recognition using visual cascading fusion of tongue-lip movements based on pre-trained and fine-tuned model by Chongchong Yu, Xuening Wang, Zhaopeng Qian

“…Different from traditional approaches, we proposed to fuse the tongue-lip visual information by a cascading fusion algorithm to achieve “visual co-occurrence” of the tongue and lip frame by frame. …”
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Machine Learning Accurately Predicts Need for Critical Care Support in Patients Admitted to Hospital for Community-Acquired Pneumonia by George S. Chen, BSc, Terry Lee, PhD, Jennifer L.Y. Tsang, MD, Alexandra Binnie, MD, Anne McCarthy, MD, Juthaporn Cowan, MD, Patrick Archambault, MD, Francois Lellouche, MD, Alexis F. Turgeon, MD, MSc, Jennifer Yoon, MD, Francois Lamontagne, MD, Allison McGeer, MD, Josh Douglas, MD, Peter Daley, MD, Robert Fowler, MD, David M. Maslove, MD, Brent W. Winston, MD, Todd C. Lee, MD, Karen C. Tran, MD, Matthew P. Cheng, MD, Donald C. Vinh, MD, John H. Boyd, MD, Keith R. Walley, MD, Joel Singer, PhD, John C. Marshall, MD, James A. Russell, MD, for the Community-Acquired Pneumonia: Toward InnoVAtive Treatment (CAPTIVATE) Investigators

“…This study aimed to develop a machine learning (ML) model that predicts the need for such interventions and compare its accuracy to that of logistic regression (LR). …”
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Identifying the Combined Impacts of Sensor Quantity and Location Distribution on Source Inversion Optimization by Shushuai Mao, Jianlei Lang, Feng Hu, Xiaoqi Wang, Kai Wang, Guiqin Zhang, Feiyong Chen, Tian Chen, Shuiyuan Cheng

“…In our study, the optimization inversion method is established based on the Gaussian plume model and the generation algorithm. A research strategy combining random sampling and coefficient of variation methods was proposed to simultaneously quantify their combined impacts in the case of a single emission source. …”
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Efficient Deep Learning Models Revolutionize Doctor’s Training for Point-of-Care Ultrasound by Hsin-Hung Chou, Yi-Chung Chang, Wan-Ching Lien, Lung-Chun Lin, Xing-Zheng Lin, Ting-En Hsu, Yueh-Ping Liu, Li Liu, Yen-Ting Chan, Feng-Sen Kuan

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A Novel Technique for Secure Data Cryptosystem Based on Chaotic Key Image Generation by Mustafa Dhiaa Al-Hassani

“…So, one of the main challenges is to keep these information safe against attacks. Many researchers and institutions realized the importance and benefits of cryptography in achieving the efficiency and effectiveness of various aspects of secure communication.This work adopts a novel technique for secure data cryptosystem based on chaos theory. …”
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ADeepWeeD: An adaptive deep learning framework for weed species classification by Md Geaur Rahman, Md Anisur Rahman, Mohammad Zavid Parvez, Md Anwarul Kaium Patwary, Tofael Ahamed, David A. Fleming-Muñoz, Saad Aloteibi, Mohammad Ali Moni, PhD

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Balanced Multi-Class Network Intrusion Detection Using Machine Learning by Faraz Ahmad Khan, Asghar Ali Shah, Nizal Alshammry, Saifullah Saif, Wasim Khan, Muhammad Osama Malik, Zahid Ullah

“…We have also found that binary classification performs better when it takes more time to train each classifier than multiclass classification. This research study incorporates proper validation of the models and achieves high accuracy and exact results compared to the literature. …”
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Multiparametric MRI-based radiomics for preoperative prediction of parametrial invasion in early-stage cervical cancer by Chongshuang Yang, Man Li, Xin Yi, Lin Wang, Guangxian Kuang, Chunfang Zhang, Benyong Yao, Zhihong Qin, Tianliang Shi, Qiang Jiang

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Automatic segmentation model and machine learning model grounded in ultrasound radiomics for distinguishing between low malignant risk and intermediate-high malignant risk of adnex... by Lu Liu, Wenjun Cai, Feibo Zheng, Hongyan Tian, Yanping Li, Ting Wang, Xiaonan Chen, Wenjing Zhu

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Predicting forest above-ground biomass using SAR imagery and GEDI data through machine learning in GEE cloud by Chiranjit Singha, Kishore Chandra Swain, Satiprasad Sahoo, Ayad M. Fadhil Al-Quraishi, Joseph Omeiza Alao, Hussein Almohamad, Mohamed Fatahalla Mohamed Ahmed, Hazem Ghassan Abdo

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Adopting Land Cover Standards for Sustainable Development in Ghana: Challenges and Opportunities by Elisha Njomaba, Fatima Mushtaq, Raymond Kwame Nagbija, Silas Yakalim, Ben Emunah Aikins, Peter Surovy

“…This study examines the challenges associated with integrating existing datasets, including variations in land cover class definitions, classification methodologies, limited interoperability, and reduced comparability across scales. Focusing on Ghana as a case study, this research aims to develop a land cover legend and land cover map aligned with International Organization for Standardization (ISO) 19144-2 standards, evaluate the effectiveness of improving land cover classification and accuracy of data, and finally, assess the challenges and opportunities for the adoption of land cover standards. …”
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Visual outcomes and treatment adherence of patients with macular pathology using a mobile hyperacuity home-monitoring app: a matched-pair analysis by Livia Faes, Lucas M Bachmann, Martin K Schmid, Dawn A Sim, Michael A Thiel, Meriam Islam, Nico Gross, Andrew Schimel

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Aerodynamic Optimization and Wind Field Characterization of a Quadrotor Fruit-Picking Drone Based on LBM-LES by Zhengqi Zhou, Yonghong Tan, Yongda Lin, Zhili Pan, Linhui Wang, Zhizhuang Liu, Yu Yang, Lizhi Chen, Xuxiang Peng

“…To address the aforementioned issues, this paper constructs a drone and wind field testing platform and employs the Lattice Boltzmann Method and Large Eddy Simulation (LBM-LES) algorithm to solve the high-dynamic, rapidly changing airflow field during the transient picking process of the drone. …”
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Machine learning-based prediction of antimicrobial resistance and identification of AMR-related SNPs in Mycobacterium tuberculosis by Yi Xu, Ying Mao, Xiaoting Hua, Yan Jiang, Yi Zou, Zhichao Wang, Zubi Liu, Hongrui Zhang, Lingling Lu, Yunsong Yu

“…By constructing training and test datasets on all SNPs, intersected SNPs, and randomly generated SNPs, we developed a Machine learning (ML) framework using twelve different algorithms. Then, we compared the performances of the various ML models and used the SHapley Additive exPlanations (SHAP) framework to decipher why and how decisions are made within the optimal algorithm. …”
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Cross-talk of m6A methylation modification and the tumor microenvironment composition in esophageal cancer by Pan Song, Jinmao Ye, Haiyang Zhang, Yishu Li, Ruizhi Cao, Yang Feng, Lei Zhang, Min Sun, Min Sun

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Factors influencing the effectiveness of SM-VCE method in solving 3D surface deformation by Xupeng Liu, Guangyu Xu, Mingkai Chen, Tengxu Zhang

“…However, when 441 points were selected, the vertical residuals increased by 22% compared to 81 points. Integration of the SM-VCE algorithm with robust estimation techniques effectively minimizes far-field deformation errors in data, thereby marginally enhancing the near-field deformation solution.…”
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Modeling the cooling effect of urban green infrastructures with an ecosystem services approach ( case study: Tehran metropolis) by S. Malekzadeh, H.R. Jafari, R. Nazari, T. Blaschke, A. Hof, M. Karimi

“…We use advanced methodologies to estimate regulating ecosystem services.METHODS: This research employed a multi-stage methodology utilizing satellite data and in-situ measurements. …”
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Accuracy Assessment of the Antarctic Digital Elevation Model Based on the ICESat-2 Elevation Data by Jie WANG, Zhiyu ZHANG, Yang JIANG, Pufan ZHAO, Songhua WU

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