Artificial Intelligence Approaches to Energy Management in HVAC Systems: A Systematic Review by Seyed Abolfazl Aghili, Amin Haji Mohammad Rezaei, Mohammadsoroush Tafazzoli, Mostafa Khanzadi, Morteza Rahbar

“…This paper provides a systematic review of state-of-the-art practices (2018 and later) using AI algorithms like machine learning (ML), deep learning (DL), and other computation-based techniques that have been deployed to boost HVAC system performance. …”
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Analysis of State-of-Charge Estimation Methods for Li-Ion Batteries Considering Wide Temperature Range by Yu Miao, Yang Gao, Xinyue Liu, Yuan Liang, Lin Liu

“…However, it requires high-quality data and substantial computational resources. Future research should focus on developing high-precision, temperature-adaptive models and lightweight real-time algorithms. …”
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The synergy of neuromarketing and artificial intelligence: A comprehensive literature review in the last decade by Ahmed H. Alsharif, Junhai Wang, Salmi Mohd Isa, Nor Zafir Md Salleh, Husam Azzawi Dawas, Mohammed H. Alsharif

“…Emotion, attention, and memory have become vital in NM and AI studies. AI algorithms analyze vast neural and physiological datasets, offering marketers insights into the emotional impact of campaigns, granular insights into consumer focus, and optimizing content for maximum impact. …”
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Novel method for prioritizing protein binding sites using pocket analysis and MD simulations by Akash Deep Biswas, Emanuela Sabato, Serena Vittorio, Parisa Aletayeb, Alessandro Pedretti, Angelica Mazzolari, Carmen Gratteri, Andrea R. Beccari, Carmine Talarico, Giulio Vistoli

“…We introduce a novel algorithm COMPASS: COMputational Pocket Analysis and Scoring System includes the calculation of Pocket Frequency Score, which assesses pocket relevance based on the frequency of key residues, was introduced to refine pocket selection. …”
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A Novel Separable Model and Decomposition Method for Sensor Locational Decision Problem by Linfeng Yang, Jie Li, Jin Ye, Zhigang Zhao

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On the Synergy of IoMT Devices and Ceiling-Mounted Systems for Advanced Medical Data Analytics by Andreas Andreou, Constandinos X. Mavromoustakis, Evangelos K. Markakis, Athina Bourdena, George Mastorakis

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Opportunities and Challenges of Brain-on-a-Chip Interfaces by Wenwei Shao, Weiwei Meng, Jiachen Zuo, Xiaohong Li, Dong Ming

“…Functionally, BoCIs offer a novel framework for hybrid intelligence, merging the cognitive capabilities of biological systems (e.g., learning and memory) with the computational efficiency of machines. However, critical challenges span 4 domains: optimizing neural maturation and functional regionalization, engineering high-fidelity bioelectronic interfaces for robust signal transduction, enhancing adaptive neuroplasticity mechanisms in lab-grown brains, and achieving biophysically coherent integration with artificial intelligence architectures. …”
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Design and performance analysis of wear-resistant micro-groove cutting tool: Numerical simulation and experimental study by Feilong Du, Fukuan Chen, Tao Zhou, Hongfei Yao, Xuefeng Zhao, Dongwei Zhu, Lin He

“…This investigation establishes a novel computational framework integrating finite element modeling (FEM), machine learning (ML)-based predictive analysis, and multi-objective genetic algorithm (GA) optimization for micro-groove tool design. …”
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Ground-Truth-Free 3D Seismic Denoising Based on Diffusion Models: Achieving Effective Constraints Through Embedded Self-Supervised Noise Modeling by Zhonghan Zhang, Guihe Qin, Yanhua Liang, Minghui Sun, Yingqing Wang, Jiaru Song

“…Subsequently, spatial structural information of 3D seismic data is leveraged to improve the accuracy of noise distribution estimation. Furthermore, the algorithm integrates the noise distribution estimation network into the diffusion model to further guide and refine the sampling process, thereby optimizing computational complexity and improving detail representation. …”
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Two-Way Feature Extraction Using Sequential and Multimodal Approach for Hateful Meme Classification by Apeksha Aggarwal, Vibhav Sharma, Anshul Trivedi, Mayank Yadav, Chirag Agrawal, Dilbag Singh, Vipul Mishra, Hassène Gritli

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A novel hybrid deep learning approach for super-resolution and objects detection in remote sensing by Muhammad Asif, Mohammad Abrar, Faizan Ullah, Abdu Salam, Farhan Amin, Isabel de la Torre, Mónica Gracia Villar, Helena Garay, Gyu Sang Choi

“…Future work may focus on optimizing computational efficiency and expanding the framework to multimodal or dynamic object detection tasks.…”
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Low resolution remote sensing object detection with fine grained enhancement and swin transformer by Zhijing Xu, Xin Wang, Kan Huang, Ren Chen

“…Finally, we incorporate the Shape-IoU loss function to optimize bounding box regression, significantly improving small target detection accuracy while maintaining computational efficiency. …”
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Dual-Ascent-Inspired Transformer for Compressed Sensing by Rui Lin, Yue Shen, Yu Chen

“…The architecture features an innovative asymmetric primal–dual space at each iteration layer, enabling dimension-specific operations that balance reconstruction quality with computational efficiency. We also optimize the Cross Attention module through parameter sharing, effectively reducing its training complexity. …”
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Myoelectric Control in Rehabilitative and Assistive Soft Exoskeletons: A Comprehensive Review of Trends, Challenges, and Integration with Soft Robotic Devices by Alejandro Toro-Ossaba, Juan C. Tejada, Daniel Sanin-Villa

“…Additionally, we identify persistent challenges such as EMG signal variability, computational complexity, and the real-time adaptability of control algorithms, which limit clinical implementation. …”
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Orbital Analysis of a Dual Asteroid System Explorer Based on the Finite Element Method by Linli Su, Wenyu Feng, Lie Yang, Zichen Fan, Mingying Huo, Naiming Qi

“…The insights gained from the analysis of orbital characteristics can inform the design of landing trajectories for binary asteroid systems and provide data for deep learning algorithms that are aimed at optimizing such orbits. …”
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Discovery, design, and engineering of enzymes based on molecular retrobiosynthesis by Ancheng Chen, Xiangda Peng, Tao Shen, Liangzhen Zheng, Dong Wu, Sheng Wang

“…The shift from traditional experiment‐driven models to data‐driven and computationally driven intelligent models is already underway. …”
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Two-stage deep reinforcement learning method for agile optical satellite scheduling problem by Zheng Liu, Wei Xiong, Zhuoya Jia, Chi Han

“…A neural network is designed as the observation scheduling network to determine observation actions for the sequenced tasks, which is well trained by the soft actor-critic algorithm. Finally, extensive experiments show that the proposed method, along with the designed mechanisms and strategy, is superior to comparison algorithms in terms of solution quality, generalization performance, and computation efficiency.…”
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Adaptive Multi-Sensor Fusion for SLAM: A Scan Context-Driven Approach by Yijing Zhang, Jia Liu, Runxi Cao, Yunxi Zhang

“…Experimental results on multiple public benchmark datasets demonstrate that in the case of almost the same computational efficiency, the proposed algorithm effectively enhances the accuracy of positioning, the robustness of the algorithm and accuracy of mapping, improving the global consistency of the generated map.…”
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ACCURACY ANALYSIS OF GALILEO CODE POSITIONING FOR UAV by Klaudia CYBULSKA-GAC, Kamil KRASUSKI, Adam CIEĆKO

“…The main objective of this work is to present an optimal computational strategy for determining the user's position and the accuracy parameter of Galileo positioning in civil aviation. …”
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LoD2 Building Reconstruction from Stereo Satellite Imagery using Deep Learning and Model-Driven Approach by Rojgar Qarani Ismael, Haval Sadeq

“…Meanwhile, the computed root mean square error are shown to be within 0.9 m for the ridge and eave, which is essentially small. …”
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