InBRwSANet: Self-attention based parallel inverted residual bottleneck architecture for human action recognition in smart cities. by Yasir Khan Jadoon, Muhammad Attique Khan, Yasir Noman Khalid, Jamel Baili, Nebojsa Bacanin, MinKyung Hong, Yunyoung Nam

“…These datasets are chosen to allow for meaningful comparison with earlier research. UCF101 dataset has a wide range of activity classes, and HMDB51 has varied real-world behaviors. …”
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Intrusion Detection Using Hybrid Pearson Correlation and GS-PSO Optimized Random Forest Technique for RPL-Based IoT by Wei Yang, Xinlong Wang, Zhiming Zhang, Shaolong Chen, Chengqi Hou, Siwei Luo

“…And we develop feature extraction algorithms for dataset to extract 24 features implementing in IDS model training. …”
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Strengths and weaknesses of Global Positioning System (GPS) data-loggers and semi-structured interviews for capturing fine-scale human mobility: findings from Iquitos, Peru. by Valerie A Paz-Soldan, Robert C Reiner, Amy C Morrison, Steven T Stoddard, Uriel Kitron, Thomas W Scott, John P Elder, Eric S Halsey, Tadeusz J Kochel, Helvio Astete, Gonzalo M Vazquez-Prokopec

“…Location-aware technologies such as Global Positioning System (GPS)-enabled devices are used increasingly as a gold standard for mobility research. The main goal of this observational study was to compare and contrast the information obtained through GPS and semi-structured interviews (SSI) to assess issues affecting data quality and, ultimately, our ability to measure fine-scale human mobility. …”
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A hybrid Spatial Ant Lion optimization and utilitarian data transmission approach for intelligent optimization for energy-efficient wireless sensor networks by Malathy Sathyamoorthy, Rajesh Kumar Dhanaraj, C N Vanitha, Md Shohel Sayeed

“…Abstract Numerous researches on wireless sensor networks was conducted to design proficient algorithms not only to minimalize the exploitation of energy and delay, but also to increase the network lifetime and throughput. …”
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Fire and Smoke Detection Based on Improved YOLOV11 by Zhipeng Xue, Lingyun Kong, Haiyang Wu, Jiale Chen

“…Fire and smoke detection is an important measure to ensure the safety of people’s lives and property, as well as a crucial link in maintaining ecological balance and supporting scientific research. Traditional object detection methods rely more on manually designed features and rules. …”
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Optimization of Flavor Quality of Lactic Acid Bacteria Fermented Pomegranate Juice Based on Machine Learning by Wenhui ZOU, Fei PAN, Junjie YI, Linyan ZHOU

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Hybrid method for automatic initialization and segmentation of ventricular on large-scale cardiovascular magnetic resonance images by Ning Pan, Zhi Li, Cailu Xu, Junfeng Gao, Huaifei Hu

“…Thus, we proposed a full automatic and robust algorithm for large-scale cardiac MRI segmentation by combining the advantages of deep learning localization and 3D-ASM restriction. …”
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Beyond buzzwords: NLP reveals common threads in sustainable and circular construction discourse by Shakarim Aubakirov, Alexandr Pak, Iskander Akhmetov, Aidana Tleuken, Huseyin Atakan Varol, Assel Akzhalova, Ferhat Karaca

“…By clarifying the distinctions and overlaps between the terms “circular construction” and “sustainable construction”, our research offers enhanced understanding for policymakers, industry practitioners, and academics aiming to integrate sustainable and circular principles effectively within the construction sector.…”
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Optimized YOLOv8 for enhanced breast tumor segmentation in ultrasound imaging by Ayman Mohamed Mostafa, Alaa S. Alaerjan, Bader Aldughayfiq, Hisham Allahem, Alshimaa Abdelraof Mahmoud, Wael Said, Hosameldeen Shabana, Mohamed Ezz

“…These results highlight the advantage of specialized model training and the potential of using advanced object detection algorithms for segmentation tasks. This research underscores the significant potential of using specialized training strategies and innovative model adaptations in medical imaging segmentation, ultimately contributing to better patient outcomes.…”
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A Bi-level Stochastic-Robust Optimal Bidding Model of Wind-Storage System in Spot Markets Considering Internal and External Uncertainties by Haowen Xu, Minglei Bao, Xun Yao, Xiaocong Sun, Yi Ding, Zhenglin Yang

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MANET Routing Protocols’ Performance Assessment Under Dynamic Network Conditions by Ibrahim Mohsen Selim, Naglaa Sayed Abdelrehem, Walaa M. Alayed, Hesham M. Elbadawy, Rowayda A. Sadek

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Synergistic effect of artificial intelligence and new real-time disassembly sensors: Overcoming limitations and expanding application scope by Bozhou Li, Dajiang Ju, Xingwang Li, Yan Liu, Hongru He, Hao Wang

“…In response to the problem of difficulty in accurately achieving predictive maintenance and the severely limited application range of new real-time disassembly sensors, this article conducts research on the synergistic effect of the new real-time disassembly sensors and artificial intelligence technology. …”
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Grid connected improved sepic converter with intelligent mppt strategy for energy storage system in railway applications by Suresh vendoti, A. Hema Sekhar, A. V. Bharadwaja, Bapayya Naidu Kommula, Rayala Sateesh, S. Prabhakar, M. Arunkumar, Cui Yaping

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Uncertainty analysis of clinically relevant distances derived using photogrammetric intersection for the assessment of motor-speech-control in children by L. Boyle, P. Helmholz, R. Ward, R. Palmer, D. Lichti

“…Perceptual analysis is the current benchmark standard used by speech-language pathologists in diagnosing speech sound disorders (SSDs). Yet, related research indicates access to objective measures could improve the assessment process. …”
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Deep learning-based classification of coronary arteries and left ventricle using multimodal data for autonomous protocol selection or adjustment in angiography by Arpitha Ravi, Philipp Bernhardt, Mathis Hoffmann, Florian Kordon, Siming Bayer, Stephan Achenbach, Andreas Maier

“…These anatomydependent parameters are organized into customizable organ programs, but manual selection of the programs increases workload and complexity. Our research introduces a deep learning algorithm that autonomously detects three target anatomies:the left coronary artery (LCA), right coronary artery (RCA), and left ventricle (LV),based on singleX-ray frames without vessel structure and enables adjustment of imaging parameters by choosing the appropriate organ program. …”
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Digital image representation by atomic functions: features for computer vision and machine learning by Viktor Makarichev, Vladimir Lukin, Sergii Kryvenko, Iryna Brysina

“…The proposed method can enhance the efficiency of downstream ML and CV algorithms, especially in constrained environments where computational resources are limited. …”
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Poisson random measure noise-induced coherence in epidemiological priors informed deep neural networks to identify the intensity of virus dynamics by Saima Rashid, Ayesha Siddiqa, Fekadu Tesgera Agama, Nazeran Idrees, Mohammed Shaaf Alharthi

“…Compartmental models have estimates of parameter complications, whereas machine learning algorithms struggle to understand MPV’s progression and lack elucidation. …”
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Selection of memory clinic patients for CSF biomarker assessment can be restricted to a quarter of cases by using computerized decision support, without compromising diagnostic acc... by Hanneke F M Rhodius-Meester, Ingrid S van Maurik, Juha Koikkalainen, Antti Tolonen, Kristian S Frederiksen, Steen G Hasselbalch, Hilkka Soininen, Sanna-Kaisa Herukka, Anne M Remes, Charlotte E Teunissen, Frederik Barkhof, Yolande A L Pijnenburg, Philip Scheltens, Jyrki Lötjönen, Wiesje M van der Flier

“…We applied these simulated CSF values and combined them with demographic, neuropsychology and MRI data to initiate CSF testing (computerized decision support approach). We compared proportion of CSF measurements and patients diagnosed with sufficient confidence (probability of correct class ≥0.80) based on an algorithm with scenarios without CSF (only neuropsychology, MRI and APOE), CSF according to the appropriate use criteria (AUC) and CSF for all patients.…”
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A hybrid ultra-short-term photovoltaic power prediction framework integrating ant colony optimization for clustering with Bi-GRU by Xinyi Liu, Zitao Wang, Yang Wang, Shanke Liu, Lijun Yu

“…Compared to derivative models, this approach improves the Dunn Index by 24 % and the Silhouette Coefficient by 34 %. …”
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Enhanced Superpixel-Guided ResNet Framework with Optimized Deep-Weighted Averaging-Based Feature Fusion for Lung Cancer Detection in Histopathological Images by Karthikeyan Shanmugam, Harikumar Rajaguru

“…While biopsy is the gold standard, manual histopathological analysis is time-consuming. This research enhances lung cancer diagnosis through deep learning-based feature extraction, fusion, optimization, and classification for improved accuracy and efficiency. …”
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