BIM and AI Integration for Dynamic Schedule Management: A Practical Framework and Case Study by Heap-Yih Chong, Xinyi Yang, Cheng Siew Goh, Yan Luo

“…The framework comprises three layers: a data layer for collecting BIM and real-time site data, an analysis layer powered by AI algorithms for predictive analytics and optimization, and an application layer for visualizing progress and supporting decision-making. …”
Get full text

Optimization of microwave components using machine learning and rapid sensitivity analysis by Slawomir Koziel, Anna Pietrenko-Dabrowska

“…Domain confinement reduces the cost of surrogate model establishment and improves its predictive power. The global optimization phase is complemented by local tuning. …”
Get full text

Planning and layout of tourism and leisure facilities based on POI big data and machine learning. by Shifeng Wu, Jiangyun Wang, Yinuo Jia, Jintian Yang, Jixiu Li

“…Thirdly, the model training indicates that facilities at various levels in Beijing exhibit a centralized layout, aligned with the city's central axis, with a higher concentration in the urban center than in peripheral regions. The predictive analysis suggests that new tourism and leisure facilities are likely to be concentrated in densely populated areas. …”
Get full text

Fault Diagnosis in a Four-Arm Delta Robot Based on Wavelet Scattering Networks and Artificial Intelligence Techniques by Claudio Urrea, Carlos Domínguez

“…This research significantly contributes to fault diagnosis in delta robots and lays the groundwork for future studies on fault tolerance control and predictive maintenance planning. Future work will focus on the physical implementation of the delta robot in laboratory settings, aiming to improve operational efficiency and reliability in industrial applications.…”
Get full text

Revolutionizing Sperm Analysis with AI: A Review of Computer-Aided Sperm Analysis Systems by Francisco J. Baldán, Diego García-Gil, Carlos Fernandez-Basso

“…These advanced systems offer significant advantages, including enhanced objectivity, improved consistency over manual methods, and the ability to detect subtle predictive patterns not discernible by human observation. …”
Get full text

Tracking Secondary Raw Material Operational Framework—DataOps Case Study by Gabriel Pestana, Marisa Almeida, Nelson Martins

“…It enhances supply chain transparency through digital traceability, promotes predictive material sourcing, and streamlines logistics via algorithmic optimization. …”
Get full text

Smart Thermostat Development and Validation on an Environmental Chamber Using Surrogate Modelling by Leonidas Zouloumis, Nikolaos Ploskas, Nikolaos Taousanidis, Giorgos Panaras

“…Although dynamic simulation tools and decision-making algorithms are core components of energy management methodologies, they are often accompanied by excessive computational cost. …”
Get full text

A comprehensive review of flood damage in mountainous regions: challenges, solutions, and advanced management technologies by Mohammad Roohi, Jila Dehghani, Maryam Irani, Paramiss Mina

“…Modern technologies, early warning systems, predictive models, and international collaboration are key to reducing flood losses and informing sustainable flood management.…”
Get full text

Climate risk and low-carbon policies: implications for sports economics and global events by Siyu Fu, Chen Kong

“…ICSF, on the other hand, leverages game theory and optimization algorithms to enhance decision-making in areas such as resource allocation, salary cap management, and sustainability-oriented strategic planning.ResultsEmpirical results from multiple datasets and experiments confirm that the integration of climate risk and low-carbon policy variables significantly improves the predictive accuracy and resilience of economic planning in the sports sector.DiscussionThis research provides theoretical advancements and practical insights for policymakers, sports managers, and investors seeking to navigate the complex interplay between sustainability and profitability in a rapidly changing global environment.…”
Get full text

Achieving Equity via Transfer Learning With Fairness Optimization by Xiaoyang Wang, Chia-Hsuan Chang, Christopher C. Yang

“…Machine learning algorithms are increasingly used in real-world decision-making systems, raising concerns about potential biases and unfairness. …”
Get full text

AI-driven energy management system based on hesitant bipolar complex fuzzy Hamacher power aggregation operators and their applications in MADM by Walid Emam, Hafiz Muhammad Waqas, Tahir Mahmood, Ubaid ur Rehman, Dragan Pamucar

“…These systems support real-time analysis of data, predictive analytics, and automatic adjustments to improve energy efficiency, reduce expenses, and lower environmental footprints. …”
Get full text

Connectivity and community structure of online and register-based social networks by Márton Menyhért, Eszter Bokányi, Rense Corten, Eelke M. Heemskerk, Yuliia Kazmina, Frank W. Takes

“…First and foremost, we find that node metrics and the connectivity of the two population-scale networks are similar, with more long-distance ties captured by the OSN, and with the OSN ties proving to be predictive of RSN ties. These results hold when correcting for population size and geographical distance, notwithstanding that these two factors appear to be the main drivers of connectivity. …”
Get full text

Bagging Vs. Boosting in Ensemble Machine Learning? An Integrated Application to Fraud Risk Analysis in the Insurance Sector by Ruixing Ming, Osama Mohamad, Nisreen Innab, Mohamed Hanafy

“…Our comprehensive analysis reveals that while not every re-sampling technique improves model performance, all feature selection methods markedly bolster predictive accuracy. Notably, the combination of the Gradient Boosting Machine (GBM) algorithm with NCR re-sampling and GBMVI feature selection emerges as the most effective configuration, offering superior fraud detection capabilities. …”
Get full text

A Framework for Real-Time Crop Monitoring and Yield Optimisation: Improving Precision Agriculture with IoT-Driven Sensor Networks and Data Analytics by Shnain Ammar H., Mohammed G., Kumar Yalla Jeevan Nagendra

“…To solve these challenges, CM-IoT-SN combines a network of IoT-enabled sensors continuously monitoring key environmental factors such as soil moisture, temperature, and nutrient levels. Advanced algorithms then utilize the realtime data acquired to provide farmers expected insights and quick advise.CM-IoT-SNs adoption across many test locations has proved its effectiveness in producing superior decision-making in crop management by means of exact, real-time monitoring and predictive analytics. …”
Get full text

Forest Fire Hazard Assessment using Remote Sensing Data and Machine Learning, Case Study of Jijel, Algeria by Matougui Zakaria, Zouidi Mohamed

“…Both models performed well (with an average area under the curve of 0.977 and 0.984, respectively), with HGB maintaining a marginal but consistent advantage over KNN, with relatively low standard deviations, suggesting stability in its predictive capability. The study offers valuable insights for wildfire management and land-use planning in Algeria, highlighting the need for tailored risk mitigation strategies.…”
Get full text

ҚАЗАҚСТАН РЕСПУБЛИКАСЫНЫҢ НАН-ТОҚАШ КӘСІПОРЫНДАРЫН ТАРАТУДЫН ЛОГИСТИКАЛЫҚ ЖҮЙЕЛЕРІН ҚҰРУ МӘСЕЛЕЛЕРІ... by D. K. Tursynbaeva, S. .. Bolatkizy, A. E. Toylybayev

Get full text

Unsupervised clustering for sepsis identification in large-scale patient data: a model development and validation study by Na Li, Kiarash Riazi, Jie Pan, Kednapa Thavorn, Jennifer Ziegler, Bram Rochwerg, Hude Quan, Hallie C. Prescott, Peter M. Dodek, Bing Li, Alain Gervais, Allan Garland

“…After preprocessing 592 variables (demographics, encounter characteristics, diagnoses, medications, laboratory tests, and clinical management) and applying data reduction, we presented 55 principal components to eight different clustering algorithms. …”
Get full text

Machine learning-based construction of Immunogenic cell death-related score for improving prognosis and personalized treatment in glioma by Guoyin Li, Yukui Zhao, Yubo He, Zhaoqiang Qian, Yiwen Liu, Xiaoyan Li, Lili Li, Zhiqiang Liu

“…The ICDS proved effective in predicting the prognosis of glioma patients in both the training and two validating cohorts. …”
Get full text

Mathematical modeling of ethanol distribution in body fluids by G. V. Nedugov

Get full text

The Role of Time in Facial Dynamics and Challenges in Automatic Emotion Recognition (2019–2024) by Williams Contreras-Higuera, Lucrezia Crescenzi-Lanna

Get full text