Advanced Intrusion Detection in MANETs: A Survey of Machine Learning and Optimization Techniques for Mitigating Black/Gray Hole Attacks by Saad M. Hassan, Mohd Murtadha Mohamad, Farkhana Binti Muchtar

“…We also discussed the potential of game theory and reinforcement learning for optimizing routing protocols and improving network resilience. The survey underscores the necessity for ongoing research into more sophisticated and adaptable detection mechanisms, urging both academic and practical communities to explore novel approaches for developing more secure, efficient MANET systems.…”
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The role of advanced machine learning in COVID-19 medical imaging: A technical review by Abdul Muiz Fayyaz, Said Jadid Abdulkadir, Shahab Ul Hassan, Safwan Mahmood Al-Selwi, Ebrahim Hamid Sumiea, Lareib Fatima Talib

“…The review also compares different ML and DL techniques, offering insights into their contributions to improving COVID-19 detection, diagnosis, and prediction. …”
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Microbiota as diagnostic biomarkers: advancing early cancer detection and personalized therapeutic approaches through microbiome profiling by Majid Eslami, Ramtin Naderian, Aisa Bahar, Ali Babaeizad, Solaleh Rezanavaz Gheshlagh, Valentyn Oksenych, Hamed Tahmasebi

“…Additionally, the influence of microbiota on the effectiveness of treatments such as immunotherapy and chemotherapy highlights its dual function in improving treatment outcomes and reducing side effects. …”
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Protecting Industrial Control Systems From Shodan Exploitation Through Advanced Traffic Analysis by Sayed Reza Ghazinour Naeini, Alireza Shameli-Sendi, Masoume Jabbarifar

“…This research introduces protocol analysis as a novel feature in network traffic analysis, significantly improving detection accuracy over models that rely solely on traditional network features. …”
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AI’s role in transforming learning environments: a review of collaborative approaches and innovations by Dwi Mariyono, Akmal Nur Alif Hd

“…Practical implications for educators and institutions include: personalized learning: AI-powered platforms can adapt to diverse student needs, improving outcomes by providing tailored learning experiences, particularly for students with disabilities or from underserved regions. …”
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RGB-based machine vision for enhanced pig disease symptoms monitoring and health management: a review by Md Nasim Reza, Kyu-Ho Lee, Eliezel Habineza, Samsuzzaman, Hyunjin Kyoung, Young Kyoung Choi, Gookhwan Kim, Sun-Ok Chung

“…Machine vision and image processing algorithms enable for the real-time detection of subtle changes in pig appearance and behavior that may signify potential health issues. …”
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Mathematical model of on-demand route formation for public transport based on individual passenger requests in low-density population area by Svetlana S. Titova, Andrey V. Ostroukh

“…The organization of public transport routes based on individual passenger requests (on-demand routes) using small-class buses in areas with low population density has become a pressing issue due to the necessity of improving the efficiency of transport systems under limited financial and material resources. …”
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AnimalMotionViz: An interactive software tool for tracking and visualizing animal motion patterns using computer vision by Angelo L. De Castro, Jin Wang, Jessica G. Bonney-King, Gota Morota, Emily K. Miller-Cushon, Haipeng Yu

“…It implements a set of background subtraction algorithms in the OpenCV package to track animal motion patterns in real time. …”
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WU Hongchun1, ZHENG Youqi1, CAO Liangzhi1, DU Xianan1, WANG Xuesong2, ZU Tiejun1, LIU Zhouyu1, HE Qingming1, CHEN Ronghua1, GE Li1, YANG Rui2, GAO Xinzhao2, WANG Shixi2... by WU Hongchun1, ZHENG Youqi1, CAO Liangzhi1, DU Xianan1, WANG Xuesong2, ZU Tiejun1, LIU Zhouyu1, HE Qingming1, CHEN Ronghua1, GE Li1, YANG Rui2, GAO Xinzhao2, WANG Shixi2, A Reai2

“…High-precision numerical analysis software of liquid-metal fast reactor is the basis for improving the research and development level of fast reactor in China. …”
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Machine-Learning Parsimonious Prediction Model for Diagnostic Screening of Severe Hematological Adverse Events in Cancer Patients Treated with PD-1/PD-L1 Inhibitors: Retrospective... by Seok Jun Park, Seungwon Yang, Suhyun Lee, Sung Hwan Joo, Taemin Park, Dong Hyun Kim, Hyeonji Kim, Soyun Park, Jung-Tae Kim, Won Gun Kwack, Sung Wook Kang, Yun-Kyoung Song, Jae Myung Cha, Sang Youl Rhee, Eun Kyoung Chung

“…<b>Background/Objectives</b>: Earlier detection of severe immune-related hematological adverse events (irHAEs) in cancer patients treated with a PD-1 or PD-L1 inhibitor is critical to improving treatment outcomes. The study aimed to develop a simple machine learning (ML) model for predicting irHAEs associated with PD-1/PD-L1 inhibitors. …”
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Diagnosis and activity prediction of SLE based on serum Raman spectroscopy combined with a two-branch Bayesian network by Qianxi Xu, Qianxi Xu, Qianxi Xu, Xue Wu, Xue Wu, Xue Wu, Xinya Chen, Ziyang Zhang, Jinrun Wang, Jinrun Wang, Zhengfang Li, Zhengfang Li, Zhengfang Li, Xiaomei Chen, Xiaomei Chen, Xiaomei Chen, Xin Lei, Xin Lei, Zhuoyu Li, Zhuoyu Li, Zhuoyu Li, Mengsi Ma, Mengsi Ma, Mengsi Ma, Chen Chen, Lijun Wu, Lijun Wu

“…It has been demonstrated that prompt diagnosis and treatment are crucial for improving patient outcomes. However, applying spectral data in the classification and activity assessment of SLE reveals a high degree of spectral overlap and significant challenges in feature extraction. …”
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Bridge Deformation Prediction Using KCC-LSTM With InSAR Time Series Data by Zechao Bai, Chang Shen, Yanping Wang, Yun Lin, Yang Li, Wenjie Shen

“…The approach initially combines two machine learning based clustering algorithms, K-Shape for better capturing shape features of time series and complete linkage hierarchical clustering combined with spatial geographic location captures the spatial characteristics of time series to derive clusters with unique spatiotemporal deformation behavior, improving clustering accuracy and spatiotemporal correlation. …”
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High-resolution surface soil moisture retrieval: A hybrid machine learning framework integrating change detection and downscaling for precision water management by Zihao Wang, Qi Gao, Michele Crosetto, Maria Jose Escorihuela

“…A novel backscatter difference variable, derived from the change detection method, improves model performance by addressing vegetation. …”
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Comparative Assessment of Data Quality Dimensions in Scientific Multimedia Indexing Process by Hamid Hassani, Azadeh Mohebi, Mohammad Javad Ershadi

“…Appropriate methods and algorithms are those that lead to the improvement of various aspects of quality in the process of organizing and retrieving information. …”
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An Investigation of Suicidal Ideation from Social Media Using Machine Learning Approach by Soumyabrata Saha, Suparna Dasgupta, Adnan Anam, Rahul Saha, Sudarshan Nath, Surajit Dutta

“…   Despite improvements in the detection and treatment of severe mental disorders, suicide remains a significant public health concern. …”
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Restoring flowcell type and basecaller configuration from FASTQ files of nanopore sequencing data by Jun Mencius, Wenjun Chen, Youqi Zheng, Tingyi An, Yongguo Yu, Kun Sun, Huijuan Feng, Zhixing Feng

“…These parameters are essential for many analysis algorithms, and their misapplication can lead to significant drops in performance. …”
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A GPU parallelization of the neXtSIM-DG dynamical core (v0.3.1) by R. Jendersie, R. Jendersie, C. Lessig, C. Lessig, T. Richter

“…<p>The cryosphere plays a crucial role in the Earth's climate system, making accurate sea-ice simulation essential for improving climate projections. To achieve higher-resolution simulations, graphics processing units (GPUs) have become increasingly appealing due to their higher floating-point peak performance compared to central processing units (CPUs). …”
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Assessment of the effectiveness of measures to preserve, strengthen, and restore mental health and psychological well-being of specialists of EMERCOM of Russia by Julia S. Shoigu, Anastasia А. Tarasova

“…An empirical study on the evaluation of psychological prevention and psychological correction programs demonstrated an improvement in the functional state of EMERCOM specialists after participating in the programs not only according to subjective assessments, but also according to psychophysiological indicators, which shows the compliance of the programs with the stated goals. …”
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Comparison of artificial intelligence approaches for estimating wind energy production: A real-world case study by Mohamed Bousla, Mohamed Belfkir, Ali Haddi, Youness El Mourabit, Badre Bossoufi

“…The precise prediction of wind power is essential not only for the smooth integration into the power grid but also for the optimization of unit commitment, maintenance scheduling, and the improvement of power traders' profitability. The present work investigates several forecasting methodologies for wind energy by employing sophisticated machine learning algorithms, including Support Vector Machines and Recurrent Neural Networks. …”
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The More, the Better? Evaluating the Role of EEG Preprocessing for Deep Learning Applications by Federico Del Pup, Andrea Zanola, Louis Fabrice Tshimanga, Alessandra Bertoldo, Manfredo Atzori

“…The last decade has witnessed a notable surge in deep learning applications for electroencephalography (EEG) data analysis, showing promising improvements over conventional statistical techniques. …”
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