Highly adaptive Lasso for estimation of heterogeneous treatment effects and treatment recommendation by Nizam Sohail, Codi Allison, Rogawski McQuade Elizabeth, Benkeser David

“…However, few of these methods are interpretable, while those that do emphasize interpretability often suffer in terms of performance. …”
Get full text

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. …”
Get full text

Scheduling Approach for the Simulation of a Sustainable Resource Supply Chain by Henning Strubelt, Sebastian Trojahn, Sebastian Lang, Abdulrahman Nahhas

“…The process sequence is determined by means of a priority index. Genetic algorithms are then applied to improve the priority index to further increase performance. …”
Get full text

Method for designing specialized computing systems on the basis of hardware and software cooptimization by I. E. Tarasov, P. N. Sovietov, D. V. Lulyava, N. A. Duksin

“…This is due to the specifics of the algorithms for placing and routing components of digital devices, which are not capable of optimizing solutions in a strict mathematical sense in an acceptable time. …”
Get full text

Design Improvement of Permanent Magnet Motor Using Single- and Multi-Objective Approaches by Cvetkovski Goga, Petkovska Lidija

“…In this case, optimising the efficiency of the motor, reducing cogging torque, and minimising the total weight of active materials are defined as possible objective functions. Genetic algorithms are nature based algorithms that are commonly used in engineering to find optimal solutions to complex problems, including those with multiple objectives. …”
Get full text

Artificial intelligence in educational technology and transformative approaches to English language using fuzzy framework with CRITIC-TOPSIS method by Jingdan Liu, Xujie Bao, Liji Chen

“…Abstract Artificial intelligence (AI) is transforming educational technology by enabling personalized, adaptive, and data-driven learning experiences. Machine learning algorithms analyze student performance to tailor content delivery, while natural language processing facilitates interactive learning through voice assistants and essay evaluation. …”
Get full text

Hybrid machine learning and physics-based model for estimating lettuce (Lactuca sativa) growth and resource consumption in aeroponic systems by Benedetta Fasciolo, Nicolò Grasso, Giulia Bruno, Paolo Chiabert

“…Abstract As the global population is expected to reach 10.3 billion by the mid-2080s, optimizing agricultural production and resource management is crucial. …”
Get full text

Smart extrusion via data-driven prediction of grain size and peripheral coarse grain defect formation by Marco Negozio, Lorenzo Donati, Adrian H. A. Lutey

“…Abstract Optimization of the mechanical and crash properties of extruded AA6XXX automotive profiles requires detailed understanding of grain size evolution and formation of the peripheral coarse grain (PCG) defect. …”
Get full text

AHA: Design and Evaluation of Compute-Intensive Hardware Accelerators for AMD-Xilinx Zynq SoCs Using HLS IP Flow by David Berrazueta-Mena, Byron Navas

“…Our performance evaluation across various configurations highlights performance–resource trade-offs and demonstrates that ANN and BPNN achieve significant parallelism, while AES optimization increases resource utilization the most. …”
Get full text

Task-Driven Real-World Super-Resolution of Document Scans by Maciej Zyrek, Tomasz Tarasiewicz, Jakub Sadel, Aleksandra Krzywon, Michal Kawulok

Get full text

The role of precision tool positioning in enhancing machining accuracy by Tuyboyov Oybek, Baydullayev Azamat, Jeltuxin Andrey, Muxiddinov Zayniddin

“…Hybrid optimization techniques, including genetic algorithms, effectively balanced the trade-off between precision and productivity, achieving a 10% reduction in production time without sacrificing accuracy. …”
Get full text

Channel and Power Allocation for Multi-Cell NOMA Using Multi-Agent Deep Reinforcement Learning and Unsupervised Learning by Ming Sun, Yihe Zhong, Xiaoou He, Jie Zhang

“…To address these challenges, this paper proposes a framework of MDRL-UL that integrates the multi-agent deep reinforcement learning with the unsupervised learning to allocate the channel and power resources in a near-optimal manner. In the framework, a multi-agent deep reinforcement learning neural network (MDRLNN) is proposed for channel allocation, while an attention-based unsupervised learning neural network (ULNN) is proposed for power allocation. …”
Get full text

Linking Animal Feed Formulation to Milk Quantity, Quality, and Animal Health Through Data-Driven Decision-Making by Oreofeoluwa A. Akintan, Kifle G. Gebremedhin, Daniel Dooyum Uyeh

“…This review connects data-driven decision-making in optimizing feed formulation to enhance milk quantity and quality while addressing animal health implications. …”
Get full text

A new temporal locality-based workload prediction approach for SaaS services in a cloud environment by Wiem Matoussi, Tarek Hamrouni

“…The method will be implemented in order to simultaneously achieve a twofold benefit: obtain precise forecast results while optimizing response time. In this regard, we have chosen to control the computation time by dynamizing the size of the sliding window associated to the recent history to be analyzed, since the larger the size of the entry in the prediction model, the more the algorithmic complexity increases. …”
Get full text

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.…”
Get full text

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. …”
Get full text

Dimension Reduction Using Quantum Wavelet Transform on a High-Performance Reconfigurable Computer by Naveed Mahmud, Esam El-Araby

“…The quantum wavelet transform takes advantage of the principles of quantum mechanics to achieve reductions in computation time while processing exponentially larger amount of information. …”
Get full text

Exploration and Construction of Personalized Customization Mode in Modern Fashion Design by Sun Huaiqun

“…The article focuses on constructing a personalized customization implementation path based on big data analysis, artificial intelligence algorithms, and online interaction platforms, covering key links such as demand analysis, virtual fitting, and on-demand production. …”
Get full text

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. …”
Get full text

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 …”
Get full text