A Low-Complexity Diversity-Preserving Universal Bit-Flipping Enhanced Hard Decision Decoder for Arbitrary Linear Codes by Praveen Sai Bere, Mohammed Zafar Ali Khan, Lajos Hanzo

“…The simulation results provided for various known codes and decoding algorithms validate the performance versus complexity benefits of the proposed decoder.…”
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Research on new energy power plant network traffic anomaly detection method based on EMD by Danni Liu, Shengda Wang, YutongLi, Ji Du, Jia Li

“…Methodology This research propose Network Quality Assessment (NQA) traffic management algorithms to prevent illegal access and data breaches, this involves strong security measures such as encryption, firewalls, and encrypted communication methods. …”
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Inductive Power Transfer Coil Misalignment Perception and Correction for Wirelessly Recharging Underground Sensors by John Sanchez, Juan Arteaga, Cody Zesiger, Paul Mitcheson, Darrin Young, Shad Roundy

“…On average, the alignment algorithms required less than four sensor measurements for localization. …”
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UAV-Multispectral Based Maize Lodging Stress Assessment with Machine and Deep Learning Methods by Minghu Zhao, Dashuai Wang, Qing Yan, Zhuolin Li, Xiaoguang Liu

“…This study aims to introduce advanced DL algorithms into the maize lodging classification task using UAV-multispectral images and investigate the advantages of DL compared with traditional ML methods. …”
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Analysis and Identification of Factors Influencing the Survival of Burn Injury Patients with an Artificial Intelligence Approach by Sara Hashemi, Shahla Faramarzi, Laya Rahmani Pirouz, Azita Yazdani

“…Conclusion: The use of machine learning algorithms in predicting the survival of burn patients is promising. …”
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A Novel Approach to Faster Convergence and Improved Accuracy in Deep Learning-Based Electrical Energy Consumption Forecast Models for Large Consumer Groups by A. Jayanth Balaji, Binoy B. Nair, D. S. Harish Ram, Kuruvachan Kalluvelil George

“…Eight deep learning algorithms trained using eleven mini-batch combinations, for two forecasting horizons resulted in 176 workflows. …”
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Context aware machine learning techniques for brain tumor classification and detection – A review by Usman Amjad, Asif Raza, Muhammad Fahad, Doaa Farid, Adnan Akhunzada, Muhammad Abubakar, Hira Beenish

“…Competitive analysis reveals that CNN and outperform others algorithms on publicly available datasets, suggesting their potential for precise tumor diagnosis and treatment planning. …”
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VHRTrees: a new benchmark dataset for tree detection in satellite imagery and performance evaluation with YOLO-based models by Şule Nur Topgül, Elif Sertel, Samet Aksoy, Cem Ünsalan, Johan E. S. Fransson

“…We implemented various object detection algorithms to evaluate the performance of different methods, propose the best experimental configurations, and generate a benchmark analysis for further studies. …”
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Perovskite Solar Cell: Chemical Composition and Bandgap Energy via Machine Learning by Filipi França dos Santos, Kelly Cristine Da Silveira, Gesiane Mendonça Ferreira, Daniella Herdi Cariello, Mônica Calixto de Andrade

“…By deploying machine learning algorithms, this work paves the way for targeted optimizations and considerable strides in the manufacturing of perovskite-based photovoltaic cells. …”
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Integrative multi-omics analysis reveals the role of toll-like receptor signaling in pancreatic cancer by Jie Peng, Jiaao Sun, Youfeng Yu, Qihang Yuan, Yong Zhang

“…Finally, we combined a series of machine learning algorithms to build a pancreatic cancer prognosis model that includes four genes (NT5E, TGFBI, ANLN, and FAM83A). …”
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ACTION: Augmentation and computation toolbox for brain network analysis with functional MRI by Yuqi Fang, Junhao Zhang, Linmin Wang, Qianqian Wang, Mingxia Liu

“…Furthermore, it enables users to design and test custom algorithms through scripting, greatly improving its utility and extensibility. …”
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Advances in Light Field Spatial Super-Resolution: A Comprehensive Literature Survey by Wenqi Lyu, Hao Sheng, Wei Ke, Xiao Ma

“…Future research should focus on enhancing the robustness, generalization, and capability of algorithms to handle complex scenarios. This review offers valuable direction for future research on light field image super-resolution and provides a solid foundation for its applications in virtual reality, augmented reality, and autonomous driving.…”
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Quick Determination of Soil Quality Using Portable Spectroscopy and Efficient Multivariate Techniques by Ernest Teye, Charles L. Y. Amuah, Kofi Atiah, Ransford Opoku Darko, Thomas Abindaw, Kwadwo Kusi Amoah, Michael Miyittah, Emmanuel Afutu, Rebecca Owusu

“…In this study, a pocket-sized shortwave NIR spectroscopy (740–1070 nm) and multivariate statistics were used to classify soil from different land-use types and simultaneously predict nitrogen (N), phosphorus (P), potassium (K), calcium (Ca2+), magnesium (Mg2+), and pH in Ghana. Different Algorithms. Linear discriminant analysis (LDA), support vector machine (SVM), and partial least squares algorithms (full-range partial least square, FrPLS; interval partial least squares, IPLS; synergy interval partial least squares, Si-PLS) were attempted for building a suitable classification and quantification model. …”
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Adaptive Cut Selection in Mixed-Integer Linear Programming by Turner, Mark, Koch, Thorsten, Serrano, Felipe, Winkler, Michael

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ERBB3-related gene PBX1 is associated with prognosis in patients with HER2-positive breast cancer by Shufen Mo, Haiming Zhong, Weiping Dai, Yuanyuan Li, Bin Qi, Taidong Li, Yongguang Cai

“…Utilizing three distinct machine learning algorithms, we identified three signature genes-PBX1, IGHM, and CXCL13-that exhibited significant diagnostic value within the diagnostic model. …”
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Mood Detection from Physical and Neurophysical Data Using Deep Learning Models by Zeynep Hilal Kilimci, Aykut Güven, Mitat Uysal, Selim Akyokus

“…Another novelty is that the emotion classification task is performed by both conventional machine learning algorithms and deep learning models. For this purpose, Feedforward Neural Network (FFNN), Convolutional Neural Network (CNN), Recurrent Neural Network (RNN), and Long Short-Term Memory (LSTM) neural network are employed as deep learning methodologies. …”
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Radiomics for differentiating adenocarcinoma and squamous cell carcinoma in non-small cell lung cancer beyond nodule morphology in chest CT by Minmini Selvam, Abjasree Sadanandan, Anupama Chandrasekharan, Sidharth Ramesh, Arunan Murali, Ganapathy Krishnamurthi

“…Lung nodules were classified using 13 machine-learning algorithms, including Linear Discriminant Analysis, Random Forest, AdaBoost, and eXtreme Gradient Boosting. …”
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Taylor Expansion of Surface Potential in MOSFET: Application to Pao-Sah Integral by Hugues Murray, Patrick Martin, Serge Bardy

“…The solution is presented analytically wherever possible, and the integration is made from simple numerical methods (Simpson, Romberg) or adaptative algorithms and can be implemented in simple C-program or in usual mathematical software. …”
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Robust H∞ Control Implementation in IFOC for High-Performance Electric Vehicle Induction Motors by Boudallaa Abdelhak, Chennani Mohammed, Belkhadir Ahmed, Rhofir Karim, Belkhayat Driss

“…Due to the nonlinear, multivariable, and highly coupled dynamics, induction motors require particularly complex control algorithms. Consequently, this method relies on accurate knowledge of the rotor position, which is directly related to the rotor time constant and, under real conditions, depends on temperature variations as well as the magnetic state of the machine. …”
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Classification of Agricultural Emissions Among OECD Countries with Unsupervised Techniques by Adam Andrzejuk

“…Two methods were used in the analysis: K-means and HDBSCAN algorithms. Both techniques are part of unsupervised learning tasks, which group data into multiple clusters. …”
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