Multiclass aerial image recognition using improved Black Widow Optimization with deep learning on unmanned aerial networks imaging by Mahmoud Ragab, Bandar M. Alghamdi, Sami Saeed Binyamin, Sultan Algarni, Roobaea Alroobaea, Abdullah M. Baqasah, Majed Alsafyani

“…To attain this, the MAIR-IBWODL method utilizes the SE-DenseNet method for learning complex feature patterns from RS images. Furthermore, the MAIR-IBWODL method employs the IBWO method for the hyperparameter range of the SE-DenseNet model. …”
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Genome-Wide Identification and Expression Analysis of the G-Protein Gene Family in Barley Under Abiotic Stresses by Ailing Han, Zhengyuan Xu, Zhenyu Cai, Yuling Zheng, Mingjiong Chen, Liyuan Wu, Qiufang Shen

“…Heterotrimeric G-proteins are fundamental signal transducers highly conserved in plant species, which play crucial roles in regulating plant growth, development, and responses to abiotic stresses. Identification of G-protein members and their expression patterns in plants are essential for improving crop resilience against environmental stresses. …”
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Assessing the Level of Consumption by Children in Households by K. V. Kuznetsov

“…At the same time, it is necessary to take into account possible cross-country features of consumption financing: the availability and development of medicine and education. …”
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Modelling district heating demand: A synthetic dataset for two residential neighbourhoodsZenodo by Katia Ritosa, Ina De Jaeger, Dirk Saelens, Staf Roels

“…The extensive artificial datasets developed in this study capture the energy demands of two districts and, with reasonable constraints, emulate monitoring campaigns typically conducted on-site in inhabited houses. …”
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Whole genome resequencing reveals genetic diversity, population structure, and selection signatures in local duck breeds by Pengwei Ren, Yongdong Peng, Liu Yang, Muhammad Zahoor Khan, Yadi Jing, Chao Qi, Zhansheng Liu, Shuer Zhang, Nenzhu Zheng, Meixia Zhang, Xiang Liu, Zhiming Zhu, Mingxia Zhu

“…Notice that HO values larger than HE values for all three species are associated with random mating patterns, reduced selection pressure, or recovery from historical bottleneck events. …”
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Real‐Climatic Microcontroller‐in‐the‐Loop (RCMIL) Framework: A Novel, Rapid, and Cost‐Effective Approach for Verifying Photovoltaic Control Systems by Ambe Harrison, Idriss Dagal, Wulfran Fendzi Mbasso, Fritz Nguemo Kemdoum, Reagan Jean Jacques Molu, Hamid Belghiti, Pradeep Jangir

“…Among the essential study topics, the development of control techniques, such as maximum power point tracking (MPPT), is a thriving and quickly growing discipline. …”
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Introducing HeliEns: A Novel Hybrid Ensemble Learning Algorithm for Early Diagnosis of <i>Helicobacter pylori</i> Infection by Sultan Noman Qasem

“…HeliEns combines the strengths of multiple quantum machine learning models, specifically Quantum K-Nearest Neighbors (QKNN), Quantum Naive Bayes (QNB), and Quantum Logistic Regression (QLR), to enhance diagnostic accuracy and reliability. The development of HeliEns involved rigorous data preprocessing steps, including data cleaning, encoding of categorical variables, and feature scaling, to ensure the dataset’s suitability for quantum machine learning algorithms. …”
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Assessment of the Impact of Investments in Fixed Capital on the Economic Growth of the Northern Regions of the Russian Federation by A. Ts. Dolgunova

“…At the same time, northern regions are a special object of management: the specificity of the North breaks the usual ideas and patterns, making standard approaches to managing economic growth unacceptable or less effective. …”
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Anatomical characterization of Semi-arid Bignoniaceae using light and scanning electron microscopy by Romisha Sonia, Shabnum Shaheen, Muhammad Waheed, Sana Imran, Shiekh Marifatul Haq, Murad Muhammad, Abeer Hashem, Samiha Al Shehri, Elsayed Fathi Abd-Allah

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Early detection of emerging SARS-CoV-2 Variants from wastewater through genome sequencing and machine learning by Xiaowei Zhuang, Van Vo, Michael A. Moshi, Ketan Dhede, Nabih Ghani, Shahraiz Akbar, Ching-Lan Chang, Angelia K. Young, Erin Buttery, William Bendik, Hong Zhang, Salman Afzal, Duane Moser, Dietmar Cordes, Cassius Lockett, Daniel Gerrity, Horng-Yuan Kan, Edwin C. Oh

“…Here, we present an unsupervised learning approach that clusters co-varying and time-evolving mutation patterns to identify SARS-CoV-2 variants. To build our model, we sequence 3659 wastewater samples collected over two years from urban and rural locations in Southern Nevada. …”
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A non-electrical pneumatic hybrid oscillator for high-frequency multimodal robotic locomotion by Genliang Chen, Yongzhou Long, Siyue Yao, Shujie Tang, Junjie Luo, Hao Wang, Zhuang Zhang, Hanqing Jiang

“…Leveraging the characteristic capabilities of the oscillator, three distinct robots are developed, including a bionic jumping robot with high motion speed, a crawling robot with a pre-programmed logic gait, and a swimming robot with adjustable motion patterns. …”
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Optimized Ensemble Deep Learning for Real-Time Intrusion Detection on Resource-Constrained Raspberry Pi Devices by Muhammad Bisri Musthafa, Samsul Huda, Tuy Tan Nguyen, Yuta Kodera, Yasuyuki Nogami

“…Building upon our previously developed stacked Long Short-Term Memory (LSTM) model integrated with ANOVA feature selection, we optimize it by integrating dual-stage model compression: pruning and quantization to create a lightweight model suitable for real-time inference on Raspberry Pi devices. …”
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Assistive Devices Analysis for Visually Impaired Persons: A Review on Taxonomy by Sadia Zafar, Muhammad Asif, Maaz Bin Ahmad, Taher M. Ghazal, Tauqeer Faiz, Munir Ahmad, Muhammad Adnan Khan

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Randomization-Driven Hybrid Deep Learning for Diabetic Retinopathy Detection by A. M. Mutawa, G. R. Hemalakshmi, N. B. Prakash, M. Murugappan

“…This study pioneers an innovative framework, using Multi-Scale Discriminative Robust Local Binary Pattern (MS-DRLBP) features, combined with a hybrid Convolutional Neural Network-Radial Basis Function (CNN-RBF) classifier, to enhance the detection of DR. …”
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A deep learning-based detection model and illumination-adaptive behavioral analysis for soldier crabs in the intertidal zone by Liangjun Li, Zhihao Ren, Cheng Tang, Shengning Lu, Yong Liang

“…However, due to their small size and tidal-driven activity patterns, conventional behavior detection methods suffer from low efficiency and considerable observer bias, particularly under dark conditions where detection errors and omissions are prevalent. …”
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Trajectory Prediction and Intention Recognition Based on CNN-GRU by Jinghao Du, Dongdong Lu, Fei Li, Ke Liu, Xiaolan Qiu

“…Accurate trajectory prediction and intention recognition are essential for effective decision-making, as different intents manifest in distinct trajectory patterns. This study focuses on trajectory prediction and intention recognition for airborne moving targets by proposing an integrated approach that leverages trajectory data for both tasks. …”
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The Delaware General Corporation Law: Business Corporations Merger (consolidation) Transactions by Stanislav E. Kuzmin

“…The study and analysis of U.S. law on mergers and acquisitions of companies (corporations) from the standpoint of comparative legal studies allow more accurately and deeper to represent the state of the modern foreign legislation in the sphere of corporate regulation, to identify the features of such regulation, to provide an analysis of its development prospects and opportunities of influence on the Russian economic agents. …”
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Prediction of antibiotic resistance from antibiotic susceptibility testing results from surveillance data using machine learning by Swetha Valavarasu, Yasaswini Sangu, Tanmaya Mahapatra

“…Abstract Antimicrobial resistance is a growing global health threat, and artificial intelligence offers a promising avenue for developing advanced tools to address this challenge. …”
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lexible sensors for food monitoring. Part II: Applications by D. Luo, M. A. Nikitina, X. Xiao

“…We also highlight the benefits and the technical challenges along with the appropriate solutions provided by the presented flexible sensors, and we also consider the potential strategies that allow overcoming limitations in power consumption, quantitatively assess the trade-offs in maintaining the quality and marketability, to optimize wireless communication and explore new sensing patterns.…”
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Addressing Sensor Data Heterogeneity and Sample Imbalance: A Transformer-Based Approach for Battery Degradation Prediction in Electric Vehicles by Bi Wu, Shi Qiu, Wenhe Liu

“…To tackle data heterogeneity, we developed a multimodal feature fusion strategy that effectively integrates battery sensor data from different sources and formats, including time-series charge-discharge sensor data and spectral impedance sensor measurements. …”
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