Advancing Stability in Robot Manipulators: A Review of Recent Progress and Parameters by Shabnom Mustary, Mohammod Abul Kashem, Jannatul Mawya Sony, Nayem Hossain, Mohammad Asaduzzaman Chowdhury

“…ABSTRACT In this review, we present an overview of the current state‐of‐the‐art in robotics while emphasizing stability and control aspects with pragmatic consideration over robotic manipulators. …”
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Regional Logistics Network Design in Mitigating Truck Flow-Caused Congestion Problems by Mi Gan, Xinyuan Li, Fadong Zhang, Zhenggang He

“…The models determine not only the facility location, initial distribution planning, roadway construction, and expansion decisions but also offer an optimal solution to the logistics network service level and truck-type selections. …”
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Analyzing the dynamics between crude oil spot prices and futures prices by maturity terms: Deep learning approaches to futures-based forecasting by Jeonghoe Lee, Bingjiang Xia

“…In addition, this research incorporates extensive hyperparameter tuning to enhance the interpretability of the machine learning models when forecasting spot prices using futures prices, thereby contributing to the field of Explainable Artificial Intelligence (XAI) with an optimal set of hyperparameters. In summary, this research systematically shows results demonstrating predictive power in terms of XAI between spot prices and futures prices with different maturities, and machine learning algorithms.…”
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Comparative Analysis of Hybrid Model Performance Using Stacking and Blending Techniques for Student Drop Out Prediction In MOOC by Muhammad Ricky Perdana Putra, Ema Utami

“…The algorithms used in the base model are KNN, Decision Tree, and Naïve Bayes, while the meta-model uses XGBoost. …”
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Scalable earthquake magnitude prediction using spatio-temporal data and model versioning by Rahul Singh, Bholanath Roy

“…The results reveal that Gradient Boosting performs optimally on smaller datasets, while LightGBM demonstrates superior accuracy with larger datasets, showcasing the pipeline’s flexibility and scalability. …”
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A Comprehensive Survey on Machine and Deep Learning for Optical Communications by Mohammad Ali Amirabadi, S. Alireza Nezamalhosseini, Mohammad Hossein Kahaei, Lawrence R. Chen

“…Specific emphasis is placed on identifying how these algorithms enhance system performance and optimization. …”
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Treatment Strategies and Prognostic Outcomes in Acute Limb Ischemia: A Systematic Review and Meta-Analysis Comparing Thrombolytic Therapy and Open Surgical Interventions by Mircea Cătălin Coșarcă, Nicolae Alexandru Lazăr, Suzana Vasilica Șincaru, Bogdan Corneliu Bandici, Eduard Costin Argatu, Cosmin Carașca, Ráduly Gergő, Dorin Constantin Dorobanțu, Cristian Trâmbițaș, Adrian Vasile Mureșan

“…Future research should focus on refining treatment algorithms, investigating novel thrombolytic agents, and expanding the role of minimally invasive techniques to improve long-term outcomes while mitigating complications such as bleeding and reperfusion injuries.…”
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Highly adaptive Lasso for estimation of heterogeneous treatment effects and treatment recommendation by Nizam Sohail, Codi Allison, Rogawski McQuade Elizabeth, Benkeser David

“…We also describe new methods for the estimation of optimal treatment policies (OTPs), an area where interpretable, auditable treatment decision rules are often desirable. …”
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Design and Implementation of an Ultra-Low-Power Hazardous Gas Monitoring System by Hongyu Liu, Yuchen Wang, Jiankang Yu, Shuqing Wang, Huijuan Chen

“…In addition, the system optimizes data acquisition and processing algorithms to segment gases of different concentrations. …”
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Scheduling Approach for the Simulation of a Sustainable Resource Supply Chain by Henning Strubelt, Sebastian Trojahn, Sebastian Lang, Abdulrahman Nahhas

“…This paper deals with the optimization of logistics processes at an underground waste storage site by means of solving scheduling issues and reducing setup times, with the help of a simulation model. …”
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Disjunctive and conjunctive decompositions of incompletely defined Boolean functions in a Binary Decision Diagram by P. N. Bibilo

“…The application of the proposed algorithms and already known algorithms for minimizing multilevel BDD representations of partial function systems allows us to obtain the best results of technologically independent logical optimization, the initial stage of logic circuit synthesis.…”
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A PSO weighted ensemble framework with SMOTE balancing for student dropout prediction in smart education systems by Achin Jain, Arun Kumar Dubey, Shakir Khan, Arvind Panwar, Mohammad Alkhatib, Abdulaziz M Alshahrani

“…Furthermore, PSO offers computational efficiency advantages over Firefly and Ant Colony Optimization, reducing hyperparameter tuning time while improving ensemble performance. …”
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Improved YOLO for long range detection of small drones by Sicheng Zhou, Lei Yang, Huiting Liu, Chongqin Zhou, Jiacheng Liu, Yang Wang, Shuai Zhao, Keyi Wang

“…The neck structure is enhanced with a collaborative attention mechanism and multi-scale fusion, improving feature representation. An optimized loss function refines bounding box matching for small targets, while a pruning strategy removes redundant filters, boosting computational efficiency. …”
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Future horizons in diabetes: integrating AI and personalized care by Kaiqi Zhang, Yun Qi, Wenjun Wang, Xinyi Tian, Jiahui Wang, Lili Xu, Xu Zhai

“…Future horizons in diabetes care must focus on overcoming challenges in data privacy, algorithmic bias, device interoperability, and equity in AI-driven care while integrating these innovations into healthcare systems to improve patient outcomes and quality of life.…”
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Industrial-scale prediction of cement clinker phases using machine learning by Sheikh Junaid Fayaz, Néstor Montiel-Bohórquez, Shashank Bishnoi, Matteo Romano, Manuele Gatti, N. M. Anoop Krishnan

“…The framework can potentially enable real-time optimization of cement production, thereby providing a route toward reducing material waste and ensuring quality while reducing the associated emissions under real-world conditions.…”
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Rolling Cargo Management Using a Deep Reinforcement Learning Approach by Rachid Oucheikh, Tuwe Löfström, Ernst Ahlberg, Lars Carlsson

“…In this paper, we apply state-of-the-art deep reinforcement learning algorithms to automate these operations in a complex and real environment. …”
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Dimension Reduction Using Quantum Wavelet Transform on a High-Performance Reconfigurable Computer by Naveed Mahmud, Esam El-Araby

“…We develop simpler and optimized emulation architectures than what has been previously reported, to perform quantum wavelet transform on high-resolution data. …”
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Exploration and Construction of Personalized Customization Mode in Modern Fashion Design by Sun Huaiqun

“…By analyzing the advantages of this model in meeting personalized consumer needs, improving production efficiency, and promoting green design and sustainable development, this article further proposes specific suggestions for technology optimization, process simplification, and user experience improvement. …”
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Cooperative Graph-Based Predictive Collision Avoidance (CGPCA): A Decentralized Framework for Safe Drone Traffic Management by Fariborz Rasoulie

“…Cooperative Graph-based Predictive Collision Avoidance (CGPCA) is a novel, decentralized approach designed to manage and control drone traffic while preventing collisions with both other drones and surrounding obstacles. …”
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A Novel Active RFID and TinyML based system for livestock Localization in Pakistan by Syed Atir Raza Shirazi, Maham Fatima, Abdul Wahab, Sadaf Ali

“…To realize the full potential of this unique Active RFID and TinyML-based livestock localization system in Pakistan, further research should focus on optimizing localization algorithms, enhancing TinyML models, and exploring interaction with upcoming technologies …”
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