Inversion model of stress state reconstruction for geological hazard pipelines based on digital twin by Xue Luning, Tian Mingliang, Zhao Juncheng

“…The results indicate that the research model has high prediction accuracy and efficiency and can effectively handle the problem of predicting pipeline stress states under different geological disasters, providing a reliable method for evaluating pipeline stress states in geological disasters.…”
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Deep-Learning-Based Solar Flare Prediction Model: The Influence of the Magnetic Field Height by Lei Hu, Zhongqin Chen, Long Xu, Xin Huang

“…This paper investigates how different magnetic field heights affect solar flare prediction performance. …”
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Mitigating Transmission Errors: A Forward Error Correction-Based Framework for Enhancing Objective Video Quality by Muhammad Babar Imtiaz, Rabia Kamran

“…This is achieved by combining H.264/AVC syntax-based encryption and decryption algorithms with error correction during the video coding process to provide end-to-end confidentiality. …”
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Optimizing Semantic-Aware Video Compression Using Particle Swarm Optimization Technique for Automotive Applications by Vadivel Shanmugam, B. Uma Maheswari

“…This popular and fast-developing technology aims to increase vehicle safety through various sensors and advanced-level Artificial Intelligence (AI)- based algorithms. The camera is one of the vital components of AM systems, which captures real-time videos, processes, encodes, packetizes and transfers them to different processing units for further applications. …”
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Human-in-the-loop control strategy for IoT-based smart thermostats with Deep Reinforcement Learning by Payam Fatehi Karjou, Fabian Stupperich, Phillip Stoffel, Drk Müller

“…The study explores the challenges of transferring control behaviors from simulation environments to real-world settings, examining the performance across different thermal zones and evaluating the integration flexibility of the control strategy within building systems. …”
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Development of Cyber Security Platform for Experiential Learning by Abhishek Vaish, Ravindra Kumar, Samo Bobek, Simona Sternad

“…The present research proposes a comprehensive web-based platform that can be used to communicate, collaborate and practice various use cases in the domain of network intrusion detection tools using machine learning algorithms and to evaluate user experience. The proposed platform CySecLearn is a collection of various functionalities and features that ensures experiential learning, will help the learner to develop critical thinking and expertise in network security and promote digital literacy in the domain of cyber security.…”
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MIE-SPD: A New and Highly Efficient Chaos-Based Multiple Image Encryption Technique With Synchronous Permutation Diffusion by Bibhudendra Acharya, Javvadi Venkata Sravan, Durga Ram Janaki Potnuru, K. Abhimanyu Kumar Patro

“…Due to the advancement of computing technologies and the Internet of Things, there has been a notable rise in image data in different sectors. Having safety mechanisms in place is crucial to protect image data from unauthorised access. …”
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Identification of reference genes for RT-qPCR in the Antarctic moss Sanionia uncinata under abiotic stress conditions. by Mira Park, Soon Gyu Hong, Hyun Park, Byeong-Ha Lee, Hyoungseok Lee

“…In this report, 11 traditionally used and 6 novel candidate reference genes were selected from transcriptome data of S. uncinata and the expression stability of these genes was evaluated under various abiotic stress conditions using three statistical algorithms; geNorm, NormFinder, and BestKeeper. …”
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State of Charge Estimation in Li-Ion Batteries Using a Parallel LSTM-Based Approach: The Impact of Modeling Based on Operating States by Osman Ozer, Hayri Arabaci

“…To address this, deep learning algorithms such as long short-term memory (LSTM) have been focused on for SOC prediction. …”
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Research on recycling value grading and real-time perception of rock debris from TBM tunneling by Weiqi Yue, Weilin Su, Zhanfei Gu, Xiao Qu

“…Leveraging a comprehensive database that encompasses both tunnel rock debris performance indicators and TBM tunneling parameters, perception models are constructed using different machine learning algorithms. After Bayesian hyperparameter optimization, the perception models based on CART, SVM, KNN, and ANN demonstrate accuracies of 67.5%, 80.0%, 82.5%, and 83.8% respectively. …”
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Challenges of Water Resources Governance under the Impact of Climate Change and Water Transfer by Atabak Jaffari, Ahmad Sharafati, Amin reza Neshat, Seyed abbas Hosseini

“…Research Topic: The water resources management approach should be based on a water governance framework in different dimensions for optimal allocation in terms of time and space with a view to future conditions. …”
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Joint User Association and Resource Allocation for Hierarchical Federated Learning Based on Games in Satisfaction Form by Panagiotis Charatsaris, Maria Diamanti, Symeon Papavassiliou

“…Algorithms based on Reinforcement Learning (RL) and Best Response Dynamics (BRD) are, then, devised to conclude the SE and MESE points. …”
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A Federated Learning-Based Framework for Accurately Identifying Human Activity in the Environment by Nwadher Suliman Al-Blihed, Dina M. Ibrahim

“…Analysis of the data generated by HAR devices may involve deep learning models and algorithms of different kinds. These data are personal and may include some sensitive data. …”
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A comprehensive approach to Queue Waiting Time Prediction using Tree-Based Ensembles with Data Balancing and Explainable AI by Tapodhir Karmakar Taton, Bipin Saha, Md. Johirul Islam, Shaikh Khaled Mostaque

“…Principal Component Analysis (PCA), t-distributed Stochastic Neighbor Embedding (t-SNE), and Autoencoders have been evaluated to compare the effectiveness of different dimensionality reduction techniques. …”
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Rethinking Technological Investment and Cost-Benefit: A Software Requirements Dependency Extraction Case Study by Gouri Ginde, Guenther Ruhe, Chad Saunders

“…Machine Learning (ML) is widely used for different purposes within Software Engineering. It can substantially improve the efficiency and effectiveness of organizations. …”
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AI-Driven Optimization of Breakwater Design: Predicting Wave Reflection and Structural Dimensions by Mohammed Loukili, Soufiane El Moumni, Kamila Kotrasova

“…Two datasets of 32,000 data points were generated for underwater and free-surface breakwaters, with an additional 10,000 data points for validation, totaling 42,000 data points per case. Five ML algorithms—Random Forest, Support Vector Regression, Artificial Neural Network, Decision Tree, and Gaussian Process—were applied and evaluated. …”
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Optimizing deep learning for accurate blood cell classification: A study on stain normalization and fine-tuning techniques by Mohammed Tareq Mutar, Jaffar Nouri Alalsaidissa, Mustafa Majid Hameed, Ali Almothaffar

“…BACKGROUND: Deep learning’s role in blood film screening is expanding, with recent advancements including algorithms for the automated detection of sickle cell anemia, malaria, and leukemia using smartphone images. …”
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False data injection attack dataset for classification, identification, and detection for IIoT in Industry 5.0Zenodo by A K M Ahasan Habib, Mohammad Kamrul Hasan, Rosilah Hassan, Shayla Islam, Huda Saleh Abbas

“…The dataset offers an accurate characterization of IoT environments by covering many different kinds of network configurations and scenarios. …”
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Empowering Community Health Workers With Scripted Medicine: Design Science Research Study by Dario Staehelin, Damaris Schmid, Felix Gerber, Mateusz Dolata, Gerhard Schwabe

“…We first developed the medical algorithms and ThinkLets based on insights from collaboration engineering and algorithmic management literature. …”
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Automatic diagnosis of extraocular muscle palsy based on machine learning and diplopia images by Xiao-Lu Jin, Xue-Mei Li, Tie-Juan Liu, Ling-Yun Zhou

“…AIM: To develop different machine learning models to train and test diplopia images and data generated by the computerized diplopia test. …”
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