Development of Adaptive Testing Method Based on Neurotechnologies by E. V. Chumakova, D. G. Korneev, M. S. Gasparian

“…However, it remains to answer the question of the need to improve the efficiency of an already implemented network, and, therefore, to conduct research on methods to improve the efficiency of networks, including finer tuning of parameters and learning algorithms, as well as architecture.A well-known and obvious drawback of using LSTMs is their exactingness in terms of equipment and resources, both during training (the training process takes a significant amount of time) and during startup, in our case, it is supplemented by increased requirements for the training sample and casts doubt on the advisability of further study of LSTM networks when solving this task.Conclusion. …”
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New directions in mapping the Earth’s surface with citizen science and generative AI by Linda See, Qingqing Chen, Andrew Crooks, Juan Carlos Laso Bayas, Dilek Fraisl, Steffen Fritz, Ivelina Georgieva, Gerid Hager, Martin Hofer, Myroslava Lesiv, Žiga Malek, Milutin Milenković, Inian Moorthy, Fernando Orduña-Cabrera, Katya Pérez-Guzmán, Dmitry Schepaschenko, Maria Shchepashchenko, Jan Steinhauser, Ian McCallum

“…This paper discusses how generative AI could be harnessed for land cover/land use mapping by enhancing citizen science approaches with multi-modal large language models (MLLMs), including improvements to the spatial awareness of AI.…”
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Individualized post‐operative prediction of cochlear implantation outcomes in children with prelingual deafness using functional near‐infrared spectroscopy by Zhe Chen, Xue Zhao, Haotian Liu, Yuyang Wang, Zhikai Zhang, Yuxuan Zhang, Yuhe Liu

“…Both classification and individualized regression models were constructed to predict post‐CI behavioral improvement from fNIRS data using support vector machine (SVM) learning algorithms. …”
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An enhanced pivot-based neural machine translation for low-resource languages by Danang Arbian Sulistyo, Aji Prasetya Wibawa, Didik Dwi Prasetya, Fadhli Almuíini Ahda

“…Further research is necessary to examine the integration of named entity recognition (NER) to improve accuracy and optimize the intermediate translation process. …”
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Artificial intelligence applications in pediatric ophthalmology: A comprehensive review by Anupama Janardhanan, Meenakshi Ravindran, Allapitchai Fathima, Neelam Pawar

“…The future of AI in pediatric ophthalmology appears bright, with ongoing research aimed at optimizing algorithms, personalizing treatment, and expanding telemedicine capabilities. …”
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Emerging Imaging Technologies in Forensic Medicine: A Systematic Review of Innovations, Ethical Challenges, and Future Directions by Feras Alafer

“…Emerging imaging modalities enhance diagnostic precision and facilitate non-invasive examinations, offering culturally sensitive alternatives to traditional autopsies. However, high costs, algorithmic biases, data security risks, and the lack of standardized forensic imaging protocols present significant challenges. …”
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Filter-enhanced adiabatic quantum computing on a digital quantum processor by Erenay Karacan, Conor Mc Keever, Michael Foss-Feig, David Hayes, Michael Lubasch

“…Eigenstate filters underpin near-optimal quantum algorithms for ground-state preparation. …”
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Lentil plant disease and quality assessment: A detailed dataset of high-resolution images for deep learning researchMendeley Data by Eram Mahamud, Md Assaduzzaman, Shayla Sharmin

“…The dataset aims to support the development of machine-learning models for precise disease detection and quality assessment in lentil cultivation. …”
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The Impact of a Deep Learning Self-Adaptive Colour Restoration Pipeline for Deep Underwater Images in 3D Reconstruction by M. Vlachos, D. Skarlatos, S. Demesticha

“…The findings are intended to inform future development of hybrid approaches that combine physical modelling with deep learning, aiming to optimize both visual clarity and geometric fidelity in underwater mapping and documentation. …”
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Navigating the landscape: Unveiling the reflection of AI in the sharing economy through bibliometric-based approach by Veljko Uskoković, Milica Maričić, Aleksandra Dacić-Pilčević, Veljko Jeremić

“…Furthermore, AI optimizes resource allocation and improves matching algorithms on online labour platforms, thereby boosting platform efficiency. …”
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Aspect-Based Sentiment Analysis for Afaan Oromoo Movie Reviews Using Machine Learning Techniques by Obsa Gelchu Horsa, Kula Kekeba Tune

“…The implementation result shows that the optimal values of models’ performance evaluation parameters were generated using different hyperparameter tuning settings.…”
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An FPGA-accelerated multi-level AI-integrated simulation framework for multi-time domain power systems with high penetration of power converters by Chen Liu, Peng Su, Hao Bai, Xizheng Guo, Alber Filbà Martínez, Jose Luis Dominguez Garcia

“…The framework structures systems hierarchically using energy transmission functions and unified energy information flow-based surrogate models with defined ports, ensuring compatibility with artificial intelligence algorithms. …”
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Hole Cleaning during Drilling Oil and Gas Wells: A Review for Hole-Cleaning Chemistry and Engineering Parameters by Mohammed Al-Rubaii, Mohammed Al-Shargabi, Dhafer Al-Shehri

“…The development of hole-cleaning models is important for use as hole-cleaning indicators to ensure optimized drilling efficiency. …”
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A joint three-plane physics-constrained deep learning based polynomial fitting approach for MR electrical properties tomography by Kyu-Jin Jung, Thierry G. Meerbothe, Chuanjiang Cui, Mina Park, Cornelis A.T. van den Berg, Stefano Mandija, Dong-Hyun Kim

“…For the prediction of optimal fitting coefficients, three neural networks were separately trained on simulated heterogeneous brain models to predict optimal polynomial weighting parameters in three orthogonal planes. …”
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From Code to Life: The AI‐Driven Revolution in Genome Editing by Zhidong Li, Wasi Ullah Khan, Genxiang Bai, Chao Dong, Jungang Wang, Youpeng Zhang, Chong Wang, Hongbin Zhang, Wenyi Wang, Ming Luo, Fei Chen

“…Recent advancements in artificial intelligence (AI) have significantly enhanced genome editing by improving target selection, minimizing off‐target effects, and optimizing CRISPR‐associated systems. …”
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Artificial Intelligence and Smart Technologies in Safety Management: A Comprehensive Analysis Across Multiple Industries by Jiyoung Park, Dongheon Kang

“…AI-driven solutions, such as predictive analytics, machine learning algorithms, IoT sensor integration, and digital twin models, are shown to proactively identify and mitigate potential hazards, optimize energy consumption, and enhance operational efficiency. …”
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A Novel Active RFID and TinyML based system for livestock Localization in Pakistan by Syed Atir Raza Shirazi, Maham Fatima, Abdul Wahab, Sadaf Ali

“…To realize the full potential of this unique Active RFID and TinyML-based livestock localization system in Pakistan, further research should focus on optimizing localization algorithms, enhancing TinyML models, and exploring interaction with upcoming technologies …”
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Applications, Challenges, and Future Perspectives of Artificial Intelligence in Psychopharmacology, Psychological Disorders and Physiological Psychology: A Comprehensive Review by Mohammad Hossein Salemi, Elham Foroozandeh, Molouk Khademi Ashkzari

“…However, challenges persist, including data privacy, algorithmic bias, ethical dilemmas, and regulatory hurdles, emphasizing the need for robust governance. …”
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Benefits and Challenges of AI-Based Digital Twin Integration in the Saudi Arabian Construction Industry: A Correspondence Analysis (CA) Approach by Aljawharah A. Alnaser, Haytham Elmousalami

“…However, several challenges hinder the realization of these benefits, including a lack of standardization of integrated DT and AI in construction projects, a lack of understanding of AI’s capabilities, a lack of logistics and the limited availability of IT infrastructure, and the complexity of AI algorithms. These findings underscore the transformative potential of integrating AI-driven DTs to optimize construction performance, improve decision-making, and address real-world complexities. …”
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Remote Sensing Image Segmentation Using Vision Mamba and Multi-Scale Multi-Frequency Feature Fusion by Yice Cao, Chenchen Liu, Zhenhua Wu, Lei Zhang, Lixia Yang

“…Although segmentation algorithms based on convolutional neural networks (CNNs) or Transformers have achieved significant performance improvements, the trade-off between segmentation precision and computational complexity remains a key limitation for practical applications. …”
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