The Future Is Organic: A Deep Dive into Techniques and Applications for Real-Time Condition Monitoring in SASO Systems—A Systematic Review by Tim Nolte, Sven Tomforde

“…Most approaches (69.09%) use Machine Learning (ML), while only 18.42% apply Deep Learning (DL). …”
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AOAFS: A Malware Detection System Using an Improved Arithmetic Optimization Algorithm by Rafat Alshorman, Bilal H. Abed-alguni, Yaqeen E. Alqudah

“…This issue diminishes the efficacy of Machine Learning models used for malware detection. Feature Selection (FS) is an approach commonly used to reduce the number of features in a malware detection dataset to a smaller set of features to facilitate the ease of the Machine Learning process. …”
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Tracking green space along streets of world cities by Giacomo Falchetta, Ahmed T Hammad

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Highlighting the Advanced Capabilities and the Computational Efficiency of DeepLabV3+ in Medical Image Segmentation: An Ablation Study by Ioannis Prokopiou, Panagiota Spyridonos

“…This study aims to present flexible and computationally efficient architecture that leverages transfer learning and delivers highly accurate results across various medical imaging problems. …”
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Autoencoder imputation of missing heterogeneous data for Alzheimer's disease classification by Namitha Thalekkara Haridas, Jose M. Sanchez‐Bornot, Paula L. McClean, KongFatt Wong‐Lin, Alzheimer's Disease Neuroimaging Initiative (ADNI)

“…Previous studies have explored various data imputation approaches on AD data, but the systematic evaluation of deep learning algorithms for imputing heterogeneous and comprehensive AD data is limited. …”
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Key Vital Signs Monitor Based on MIMO Radar by Michael Gottinger, Nicola Notari, Samuel Dutler, Samuel Kranz, Robin Vetsch, Tindaro Pittorino, Christoph Würsch, Guido Piai

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Enhanced aquila optimizer for global optimization and data clustering by Laith Abualigah, Saleh Ali Alomari, Mohammad H. Almomani, Raed Abu Zitar, Hazem Migdady, Kashif Saleem, Aseel Smerat, Vaclav Snasel, Amir H. Gandomi

“…Comprehensive experiments on benchmark test functions and data clustering problems demonstrate the efficacy of LOBLAO. …”
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Artificial Olfactory System Enabled by Ultralow Chemical Sensing Variations of 1D SnO2 Nanoarchitectures by Yun‐Haeng Cho, Dong‐Su Kim, Jung Hwan Seo, Jae Han Chung, Zion Park, Ki Chang Kwon, Jae‐Kwon Ko, Tae Won Ha, Jeong‐O Lee, Gyu‐Li Kim, Seong‐Jun Ro, Hyojung Kim, Chil‐Hyoung Lee, Kwangjae Lee, Young‐Seok Shim, Donghwi Cho

“…This study addresses these challenges by developing a highly reliable sensor platform to standardize gas sensing for deep learning applications. Specifically, 1D SnO2 nanonetworks functionalized with Au and Pd nanocatalysts are fabricated via a systematic deposition process, enhancing gas diffusion and reaction kinetics. …”
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Multimodal prediction of the need of clozapine in treatment resistant schizophrenia; a pilot study in first-episode psychosis by Jonatan M. Panula, Athanasios Gotsopoulos, Jussi Alho, Jaana Suvisaari, Maija Lindgren, Tuula Kieseppä, Tuukka T. Raij

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NetStart 2.0: prediction of eukaryotic translation initiation sites using a protein language model by Line Sandvad Nielsen, Anders Gorm Pedersen, Ole Winther, Henrik Nielsen

“…Abstract Background Accurate identification of translation initiation sites is essential for the proper translation of mRNA into functional proteins. In eukaryotes, the choice of the translation initiation site is influenced by multiple factors, including its proximity to the 5 $$^\prime $$ end and the local start codon context. …”
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Multi-strategy collaborative optimization of gravitational search algorithm by Zhonghua Yang, Yuanli Cai, Ge Li, Peng Wang, Yu Chen

“…Finally, the lens-imaging opposition-based learning strategy generates opposite solutions for particles at different stages, increasing population diversity, expanding the search range, and enhancing the global search performance of the algorithm. …”
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An efficient enhanced exponential distribution optimizer: applications in global, engineering, and combinatorial optimization problems by Marwa M. Emam, Mohammed R. Saad, Mina Younan, Essam H. Houssein

“…Abstract This paper introduces an enhanced exponential distribution optimizer (EDO), termed the exponential distribution optimizer with Levy flight orthogonal learning (EDO-LFOL). EDO-LFOL enhances EDO by integrating the Levy flight (LF) strategy during the intensification phase and utilizing the orthogonal learning (OL) approach after the end of the optimization cycle. …”
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PTK6 mediated immune signatures revealed by single cell transcriptomic and multi omics big data analysis in cervical cancer by Fen Zhao, Huanxin Zhong, Lifang You, Yi Du, Changchang Huang

“…Single-cell analysis confirmed PTK6 expression across multiple cell types. Functional validation demonstrated that PTK6 knockdown reduced HeLa cell proliferation, confirming its oncogenic role. …”
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Incremental Weak Subgradient Methods for Non-Smooth Non-Convex Optimization Problems by Narges Araboljadidi, Valentina De Simone

“…Non-smooth, non-convex optimization problems frequently arise in modern machine learning applications, yet solving them efficiently remains a challenge. …”
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A hybrid YOLO-UNet3D framework for automated protein particle annotation in Cryo-ET images by Ziyang Liu, Chunhong Yuan, Zixin Zhang, Xiang Zhou, Xiangyu Li, Zhen Tian, Yuting Pei, Zuowen Jiang, Zhikui Tian

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CCT: A Cyclic Co-Teaching Approach to Train Deep Neural Networks With Noisy Labels by Jorge K. S. Kamassury, Henrique Pickler, Filipe R. Cordeiro, Danilo Silva

“…Strategies from the LNL literature to address this typically include the use of disagreement techniques and alternative loss functions. In this paper, we propose the Cyclic Co-Teaching (CCT) method, which employs cyclic variations in the learning rate and sample retention rate at the mini-batch level, along with a checkpoint mechanism that ensures that training in subsequent cycles always resumes from the best models obtained so far. …”
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Harnessing artificial intelligence of things for cardiac sensing: current advances and network-based perspectives by Hao Ren, Hao Ren, Hao Ren, Fengshi Jing, Yongcong Ma, Ruining Wang, Chaocheng He, Yufan Wang, Jiandong Zhou, Yu Sun

“…A total of 2,128 papers were included in the analysis.ConclusionFrom our perspective, current advancements in AI-powered IoT cardiac sensors primarily focus on optimizing AI algorithms, such as deep learning techniques, and enhancing the functionality of smart wearable devices for precision medicine. …”
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Dynamic Optimization of Recurrent Networks for Wind Speed Prediction on Edge Devices by Laeeq Aslam, Runmin Zou, Ebrahim Shahzad Awan, Sayyed Shahid Hussain, Muhammad Asim, Samia Allaoua Chelloug, Mohammed A. ELAffendi

“…Server-dependent machine learning models, commonly deployed in wind farms, prove infeasible for domestic systems due to high costs and energy demands. …”
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Achievement motivation and attitude of medical laboratory assistants to continuing education by K. S. Kichukova, T. G. Taneva

“…The applicability of the results is very clearly visible in the formulated thesis of the necessary change in the educational policy in the country through new forms of continuous education of medical laboratory assistants which would update their achievement motivation and would result in increase in the efficiency of their professional functioning.…”
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Optimized ANN Model for Predicting Buckling Strength of Metallic Aerospace Panels Under Compressive Loading by Shahrukh Khan, Saiaf Bin Rayhan, Md Mazedur Rahman, Jakiya Sultana, Gyula Varga

“…The ANN model was systematically fine-tuned by testing various batch sizes, learning rates, optimizers, dense layer configurations, and activation functions. …”
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