Automated evaluation of accessibility issues of webpage content: tool and evaluation by Jinat Ara, Cecilia Sik-Lanyi

“…In order to predict a webpage’s accessibility status, we implemented three distinct algorithms to analyze web features/objects considering both semantic and non-semantic aspects. …”
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Multi-strategy enterprise development optimizer for numerical optimization and constrained problems by Xinyu Cai, Weibin Wang, Yijiang Wang

“…However, the analysis of the EDO algorithm shows that it suffers from the defects of rapidly decreasing population diversity and weak exploitation ability when dealing with complex optimization problems, while its algorithmic structure has room for further enhancement in the optimization process. …”
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A Framework for Multi-Objective Optimization in Energy Retrofit of Heritage Museums: Enhancing Preservation, Comfort, and Conservation Conditions by Camila Gea-Salim, Silvana Flores-Larsen, Marcos Hongn, Silvina Gonzalez

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Advanced Planning Systems in Production Planning Control: An Ethical and Sustainable Perspective in Fashion Sector by Martina De Giovanni, Mariangela Lazoi, Romeo Bandinelli, Virginia Fani

“…The integration of metaheuristic algorithms—especially Ant Colony Optimization (ACO) and hybrid models like GA-ACO—further improves optimization performance by offering high-quality, near-optimal solutions without requiring extensive structural modeling. …”
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A Review of Systematic Methodologies for Shipyard Facility Layout Design by Ghulam Tulus Pambudi, Gunawan Gunawan, Dimas Angga Fakhri Muzhoffar, Wanda Rulita Sari

“…Heuristic algorithms, including genetic algorithms and simulated annealing, offer flexible and rapid solutions but may not always achieve global optimization. …”
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Enhancing Manufacturing Precision: Leveraging Motor Currents Data of Computer Numerical Control Machines for Geometrical Accuracy Prediction Through Machine Learning by Lucijano Berus, Jernej Hernavs, David Potocnik, Kristijan Sket, Mirko Ficko

“…Different machine learning algorithms, such as Random Forest (RF), k-nearest neighbors (k-NN), and Decision Trees (DT), were used for predictive modeling. …”
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Adaptive Quantum-Inspired Evolution for Denoising PCG Signals in Unseen Noise Conditions by Lubna Siddiqui, Ashish Mani, Jaspal Singh

“…The filter coefficients were optimised using the proposed QiEA with Adaptive Rotation Gate Operator (ARGO). The proposed algorithm accelerates convergence towards optimal solutions based on fitness feedback, improving filter optimisation while clamping rotation angles to maintain algorithm stability. …”
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A CGAN-based adversarial attack method for data-driven state estimation by Qi Wang, Jing Zhang, Jianxiong Hu, Shutan Wu, Shiyi Hou, Yi Tang

“…With the development of data science and technology, the data-driven algorithms under the new power system architecture provide support for real-time and accurate state estimation (SE). …”
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Quantitative study of lung structure in COPD patients based on low-dose Karl iterative reconstruction by Ye Yizhai, Li Juehui, Wang Weigen, He Jianhua, Yang Qi

“…Low-dose Karl iterative reconstruction (KIR) is a commonly used technique in medical imaging. An iterative algorithm reduces the dose of X-ray radiation while ensuring image quality, making it a safer and more convenient imaging method. …”
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A Review of Advanced Deep Learning Methods of Multi-Target Segmentation for Breast Cancer WSIs by Qiaoyi Xu, Afzan Adam, Azizi Abdullah, Nurkhairul Bariyah

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A hyperspectral approach for retrieving inherent optical properties, phytoplankton pigments, and associated uncertainties from non-water absorption by Brice Grunert, Audrey Ciochetto, Audrey Ciochetto, Colleen Mouw

“…Across absorption spectra, simulated noise led to modest changes in model performance, while spectral resolution varying from 1 to 5 nm did not significantly alter model performance. …”
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Development of Self-Powered Energy-Harvesting Electronic Module and Signal-Processing Framework for Wearable Healthcare Applications by Jegan Rajendran, Nimi Wilson Sukumari, P. Subha Hency Jose, Manikandan Rajendran, Manob Jyoti Saikia

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Usability and Perceived Efficiency of an Adaptive Route Optimization Solution for Commercial Vehicles by Florian Anghelache, Nicolae Goga, Constantin Viorel Marian, Dan Alexandru Mitrea, Ionel-Bujorel Pavaloiu

“…This paper details the outcome of a European scientific research and development project, funded to prototype a commercial solution for vehicle fleets. While current route optimization solutions have data sources such as real-time road traffic and weather conditions, our solution was developed to offer companies a proposed plan with adapted optimized routes, considering critical operational requirements, local conditions, and drivers’ driving experience. …”
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Development of A Novel Discharge Routing Method Based On the Large Discharge Dataset, Muskingum Model, Optimization Methods, and Multi-Criteria Decision Making by Mahdi Valikhan Anaraki, Saeed Farzin, Iman Ahmadianfar, Amin Shams

“…Different MOAs, including a Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Firefly Algorithm (FFA), Cuckoo Search (CS), Bat Algorithm (BA), Shark Smell Optimization (SSO), Whale Optimization Algorithm (WOA), Harris Hawk''s Optimization (HHO), and hybrid of WOA and CS (WOA_CS), were developed for Muskingum calibration. …”
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Harmonized Integration of GWO and J-SLnO for Optimized Asset Management and Predictive Maintenance in Industry 4.0 by A. N. Arularasan, P. Ganeshkumar, Mohammad Alkhatib, Tahani Albalawi

“…The study encompasses the application of two different advanced optimization algorithms on asset management and predictive maintenance in Industry 4.0—Grey Wolf Optimization and Jaya-based Sea Lion Optimization (J-SLnO). …”
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Machine learning-aided hybrid technique for dynamics of rail transit stations classification: a case study by Ahad Amini Pishro, Shiquan Zhang, Alain L’Hostis, Yuetong Liu, Qixiao Hu, Farzad Hejazi, Maryam Shahpasand, Ali Rahman, Abdelbacet Oueslati, Zhengrui Zhang

“…The study employs several regression models trained on existing data to generate accurate ridership forecasts, and data clustering using mathematical algorithms reveals distinct categories of stations. …”
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Optimization of off-grid hybrid renewable energy systems for cost-effective and reliable power supply in Gaita Selassie Ethiopia by Elsabet Ferede Agajie, Takele Ferede Agajie, Isaac Amoussou, Armand Fopah-Lele, Wirnkar Basil Nsanyuy, Baseem Khan, Mohit Bajaj, Ievgen Zaitsev, Emmanuel Tanyi

“…To achieve the results, meta-heuristics such as the Multiobjective Gray wolf optimization algorithm (MOGWO) and Multiobjective Grasshopper optimization algorithm (MOGOA) were applied using MATLAB software. …”
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Effectiveness and cost-effectiveness of community-based TB screening algorithms using computer-aided detection (CAD) technology alone compared with CAD combined with point-of-care... by Fabrizio Tediosi, Klaus Reither, Bram van Ginneken, Alastair van Heerden, Tinne Gils, Lutgarde Lynen, Josephine Muhairwe, Alfred Kipyegon Keter, Aita Signorell, Rediet Fikru Gebresenbet, Irene Ayakaka, Thomas Zoller, Fiona Vanobberghen, Mashaete Kamele, Thandanani Madonsela, Shannon Bosman, Anna Verjans, Bart Karl Jacobs, Curdin Brugger, Marina Antillon, Niklaus Daniel Labhardt, Harsh Vivek Harkare, Mamatlakeng Keitseng, Johanna Kurscheid, Keelin Murphy, Bulemba Katende, Rahel Milena Erhardt, Tracy R Glass

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Enhanced Anti-Lock Braking System Performance: A Comparative Study of Adaptive Terminal Sliding Mode Control Approaches by Salma Khatory, Houcine Chafouk, El Mehdi Mellouli

“…Gain tuning, essential for optimizing system performance and reducing tracking errors, is achieved using the efficient Teaching–Learning-Based Optimization (TLBO) algorithm. This study applies TSMC, ITSMC, and ASC-based PSO to an Anti-Lock Braking System (ABS), aiming to enhance robustness, stability, and finite-time convergence while reducing chattering. …”
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Distributed Optimization Strategy for Voltage Regulation in PV-Integrated Power Systems with Limited Sensor Deployment by Xun Lu, Junlei Liu, Xinmiao Liu, Jun Liu, Lingxue Lin

“…The methodology integrates an adaptive step size algorithm within a dynamic projected primal–dual distributed optimization framework, eliminating manual parameter tuning requirements while ensuring theoretical convergence guarantees through Lyapunov stability analysis. …”
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