Dynamic Foraging in Swarm Robotics: A Hybrid Approach with Modular Design and Deep Reinforcement Learning Intelligence by Ali Hammoud, Alaa Iskandar, Béla Kovács

“…This paper proposes a hybrid approach that combines intelligent algorithms and modular design to solve a foraging problem within the context of swarm robotics. …”
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Smart Farming: AI and IoT-Based Solutions for Real-Time Agriculture Monitoring by Kadao Anjali Krushna, Shivaji Ghorpade Bipin

“…There is a network of IoT sensors that work in various environments from which data is collected regarding soil moisture, temperature, and humidity among many other parameters. These data streams are analyzed by advanced AI algorithms that generate actionable insights. …”
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BFS: A blockchain-based financing scheme for logistics company in supply chain finance by Jia Fu, Bangcan Cao, Xiaoliang Wang, Pengjie Zeng, Wei Liang, Yuzhen Liu

“…At the same time, the transparency feature of blockchain is used to solve the financing dilemma of many industries in supply chain finance. On this basis, we propose a blockchain-based financing scheme (BFS) for logistics company. …”
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Unlocking autism’s complexity: the Move Initiative’s path to comprehensive motor function analysis by Ashley Priscilla Good, Elizabeth Horn

“…Despite advances in sensors, wearables, algorithms, machine learning, and agentic AI, autism research remains siloed, with many tools inaccessible to affected families and care teams. …”
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Hybrid neural network method for damage localization in structural health monitoring by Fatahlla Moreh, Yusuf Hasan, Zarghaam Haider Rizvi, Sven Tomforde, Frank Wuttke

“…Abstract The detection of cracks in large structures is of critical importance, as such damage can result not only in significant financial costs but also pose serious risks to public safety. Many existing methods for crack detection rely on deep learning algorithms or traditional approaches that typically use image data. …”
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From patterned response dependency to structured covariate dependency: Entropy based categorical-pattern-matching. by Hsieh Fushing, Shan-Yu Liu, Yin-Chen Hsieh, Brenda McCowan

“…Data generated from a system of interest typically consists of measurements on many covariate features and possibly multiple response features across all subjects in a designated ensemble. …”
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Prediction of Corona-Virus Using Deep Learning by Laith Al-Ali

“…Artificial intelligence provides many tools for data analysis, statistical analysis, and intelligent research. …”
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Computational inference of co-regulatory modules from transcription factors, MicroRNAs, and their targets using CanMod2 by Ziynet Nesibe Kesimoglu, Jubair Ibn Malik Rifat, Serdar Bozdag

“…In this work, we have introduced several algorithmic enhancements to the earlier version of CanMod2. …”
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Data analysis methods in astronomic objects classification (Sloan Digital Sky Survey DR14) by V. A. Golov, D. A. Petrusevich

“…The large quantity of statistical information leads to the demand for analytical algorithms and systems capable of making classification. …”
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Using mathematical modelling to highlight challenges in understanding trap counts obtained by a baited trap by Omar Mazen Alqubori, Daniel Bearup, Sergei Petrovskii

“…Abstract Baited traps are routinely used in many ecological and agricultural applications, in particular when information about pest insects is required. …”
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Optimization of non-smooth functions via differentiable surrogates. by Shikun Chen, Zebin Huang, Wenlong Zheng

“…Mathematical optimization is fundamental across many scientific and engineering applications. While data-driven models like gradient boosting and random forests excel at prediction tasks, they often lack mathematical regularity, being non-differentiable or even discontinuous. …”
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Graph-based two-level indicator system construction method for smart city information security risk assessment by Li Yang, Kai Zou, Yuxuan Zou

“…The rapid development of urban informatization has led to a deep integration of advanced information technology into urban life. Many decision-makers are starting to alleviate the adverse effects of this informatization process through risk assessment. …”
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Application of the Endurance Time Method in the Seismic Assessment of Moment-Resisting Reinforced Concrete Frames with Setbacks by Mehdi Izadpanah

“…Nowadays, many buildings around the world exhibit height irregularities. …”
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Modeling LTE-advanced cell capacity estimation using packet bundling and carrier aggregation by Rajiv Senapati

“…The increasing demand for mobile usage raises many challenges for service providers. Satisfying subscribers by providing a better quality of service (QoS) is one of the major concerns of an operator. …”
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Computational toolkit for predicting thickness of 2D materials using machine learning and autogenerated dataset by large language model by Chinedu E. Ekuma

“…This Python-based computational framework harnesses an autogenerated thickness database, developed using large language models, and advanced ML algorithms to facilitate the rapid and scalable estimation of material thickness, relying solely on crystallographic data. …”
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A willingness-aware user recruitment strategy based on the task attributes in mobile crowdsensing by Yang Liu, Yong Li, Wei Cheng, Weiguang Wang, Junhua Yang

“…Mobile crowdsensing has become a versatile platform for many Internet of things applications in urban scenarios. …”
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Application of Machine Learning for Real-Time Phishing Attack Detection by Akshay Shankar Agrawal, Sanketi Raut, Andrina Dsouza, Jimit Mehta, Prajwal Naik

“…The system uses machine learning algorithms to distinguish legitimate websites from phishing websites and generate a prediction to be used for the platform. …”
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Real Time Application for Automatic Object and 3D Position Detection and Sorting with Robotic Manipulator by Tichaona Jonathan Makomo, Barış Boru, Kenan Erin

“…For this work, a common industrial task in many factories of pick and place is implemented. …”
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Explainable Anomaly Detection Based on Operational Sequences in Industrial Control Systems by Ka-Kyung Kim, Joon-Seok Kim, Ieck-Chae Euom

“…Anomaly detection systems, initially implemented for detecting device faults or failures, have increasingly become the focus of research aimed at identifying attack patterns as cyberattack techniques become more sophisticated and intelligent. Many anomaly detection algorithms based on deep learning models have good performance but often involve complex neural network structures, creating a black-box issue where users cannot interpret the decisions made by the models. …”
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OWNC: Open-World Node Classification on Graphs with a Dual-Embedding Interaction Framework by Yuli Chen, Chun Wang

“…Additionally, when there are too many or too few nodes from unseen classes, classification performance typically declines. …”
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