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Uncovering the spatiotemporal evolution of the service industry based on geo-big-data- a case study on the bath industry in China

Bingyu Zhao, Jingzhong Li, Bing Xue • Computational Urban Science (2023)

Abstract The bath industry has multiple attributes, such as economic, health, and cultural communication. Therefore, exploring this industry's spatial pattern evolution is crucial to forming a healthy and balanced development model. Based o...

DOAJ Open Access (DOAJ) DOI: 10.1007/s43762-023-00085-y

Modular multi-fidelity simulation framework for advanced sail-driven spacecraft control and dynamics in perturbation-rich regimes

Celia Redondo-Verdú, Álvaro Belmonte-Baeza, José L. Ramón, Cristina Cachero et al. • Results in Engineering (2026)

This work presents a high-fidelity Software-in-the-Loop (SIL) simulation framework for the development and validation of control strategies for sail-driven spacecraft operating in Low Earth Orbit (LEO). The framework integrates NVIDIA Omniv...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.rineng.2026.113314

Optimal pre-train/fine-tune strategies for accurate material property predictions

Reshma Devi, Keith T. Butler, Gopalakrishnan Sai Gautam • npj Computational Materials (2024)

Abstract A pathway to overcome limited data availability in materials science is to use the framework of transfer learning, where a pre-trained (PT) machine learning model (on a larger dataset) can be fine-tuned (FT) on a target (smaller) d...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41524-024-01486-1

A Novel Construction Method of Bayesian Neural Networks Based on Multi-type Engineering Knowledge

Wenbin Ye, YanZhou Duan, Jun Yuan, Jixu Wang et al. • International Journal of Computational Intelligence Systems (2026)

Abstract In the field of engineering, the utilization of surrogate models to replace computationally intensive simulation software has become a widely adopted approach. However, when addressing complex engineering problems, the costs of sim...

DOAJ Open Access (DOAJ) DOI: 10.1007/s44196-026-01214-1

Music Genre Recommendations Based on Spectrogram Analysis Using Convolutional Neural Network Algorithm with RESNET-50 and VGG-16 Architecture

nyoman purnama • JISA (Jurnal Informatika dan Sains) (2022)

Recommendations are a very useful tool in many industries. Recommendations provide the best selection of what the user wants and provide satisfaction compared to ordinary searches. In the music industry, recommendations are used to provide ...

DOAJ Open Access (DOAJ) DOI: 10.31326/jisa.v5i1.1270

BP Neural Network–Based Kalman Filtering Method Under Multiple Cyberattacks

Zijing Li, Keting Huang, Gang Wang, Zhuowei Liang et al. • IET Signal Processing (2026)

This paper proposes a Kalman-gain-driven neural Kalman filtering (KF) defense framework, termed KFDBP, for secure state estimation in cyber–physical systems (CPSs) under denial-of-service (DoS), spoofing, and replay attacks. Unlike end-to-e...

DOAJ Open Access (DOAJ) DOI: 10.1049/sil2/3335149

Modeling a High Concentrator Photovoltaic Module Using Fuzzy Rule-Based Systems

Manuel Angel Gadeo-Martos, Antonio Jesús Yuste-Delgado, Florencia Almonacid Cruz, Jose-Angel Fernandez-Prieto et al. • Energies (2019)

Currently, there is growing interest in the modeling of high concentrator photovoltaic modules, due to the importance of achieving an accurate model, to improve the knowledge and understanding of this technology and to promote its expansion...

DOAJ Open Access (DOAJ) DOI: 10.3390/en12030567

Artificial neural network modeling of mixed convection viscoelastic hybrid nanofluid across a circular cylinder with radiation effect: Case study

Syed M. Hussain, Rahimah Mahat, Nek Muhammad Katbar, Imran Ullah et al. • Case Studies in Thermal Engineering (2023)

As a result of its use in the manufacturing and construction industries, research on the flow of nanofluid is rather well-known among academics and professionals in related fields. It is helpful for electrical equipment to utilize it for co...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.csite.2023.103487

Prognostic techniques for aeroengine health assessment and Remaining Useful Life estimation

Caricato A., Ficarella A., Chiodo L. Spada • E3S Web of Conferences (2021)

Predictive maintenance is the latest frontier in the management and maintenance of many industrial assets, including aeroengines. Made possible by last decades advances in monitoring equipment and machine learning algorithms, it permits ind...

DOAJ Open Access (DOAJ) DOI: 10.1051/e3sconf/202131211017

Explainable machine learning in materials science

Xiaoting Zhong, Brian J. Gallagher, Shusen Liu, Bhavya Kailkhura et al. • npj Computational Materials (2022)

Abstract Machine learning models are increasingly used in materials studies because of their exceptional accuracy. However, the most accurate machine learning models are usually difficult to explain. Remedies to this problem lie in explaina...

OPENALEX cc-by DOI: https://doi.org/10.1038/s41524-022-00884-7

Testing the Physical Parameter Constraining Power of HCN and HNC with Neural Networks

Erica Behrens, Jeffrey G. Mangum, Mathilde Bouvier, Cosima Eibensteiner et al. • The Astrophysical Journal (2026)

We quantify the utility of HCN and HNC to characterize gas conditions in the nearby starburst galaxy NGC 253. We use measurements from the Atacama Large Millimeter/Submillimeter Array (ALMA) Large Program ALCHEMI: the ALMA Comprehensive Hig...

DOAJ Open Access (DOAJ) DOI: 10.3847/1538-4357/ae3567

Numerical investigation of corroded middle‐high strength pipeline subjected to combined internal pressure and axial compressive loading

Linlin Lu, Lecai Liang • Energy Science & Engineering (2021)

Abstract Buried oil and gas pipelines may face the threat of geological disasters such as landslides, faults, and floods. However, long‐term buried oil and gas pipelines often have corrosion defects, which bring greater challenges to the sa...

DOAJ Open Access (DOAJ) DOI: 10.1002/ese3.830

Machine Learning–Based Prediction of Organic Solar Cell Performance Using Molecular Descriptors

Mohammed Saleh Alshaikh • International Journal of Emerging Research in Engineering, Science, and Management (2025)

The performance of Organic Solar Cells (OSCs) is intrinsically linked to the molecular, electronic, and structural properties of donor and acceptor materials. This study employs various machine learning techniques, namely the Generalized Re...

DOAJ Open Access (DOAJ) DOI: 10.58482/ijeresm.v4i4.4

Quantum Computing in Transportation Engineering: A Survey

Shriyank Somvanshi, Md Monzurul Islam, Sazzad Bin Bashar Polock, Gaurab Chhetri et al. • IEEE Transactions on Intelligent Transportation Systems (2026)

Quantum computing introduces new computational methods that address complex optimization and machine learning challenges in transportation engineering. This literature survey reviews fundamental quantum principles, including qubits, superpo...

OPENALEX Open Access DOI: https://doi.org/10.1109/tits.2026.3662626

Computing with Bees: Attacking Complex Transportation Engineering Problems

Panta Lučić, Dušan Teodorović • International Journal of Artificial Intelligence Tools (2003)

The Bee System (an artificial bee swarm) is introduced in this paper. The proposed approach is applied to the Traveling Salesman Problem. The obtained results are very promising. The potential applications of the developed Bee System in the...

OPENALEX DOI: https://doi.org/10.1142/s0218213003001289

Encyclopedic Dictionary of Applied Geophysics

Robert E. Sheriff • Society of Exploration Geophysicists eBooks (2002)

The fourth edition of SEG's best seller is a valuable, comprehensive reference that is a must for every geophysicist, geologist, explorationist, engineer, energy adviser, economist, editor, and student involved in the field. Hundreds of ter...

OPENALEX DOI: https://doi.org/10.1190/1.9781560802969