Enhanced Detection of Intrusion Detection System in Cloud Networks Using Time-Aware and Deep Learning Techniques by Nima Terawi, Huthaifa I. Ashqar, Omar Darwish, Anas Alsobeh, Plamen Zahariev, Yahya Tashtoush

“…We generate real DoS traffic, including normal, Internet Control Message Protocol (ICMP), Smurf attack, and Transmission Control Protocol (TCP) classes, and develop nine predictive algorithms, combining traditional machine learning and advanced deep learning techniques with optimization methods, including the synthetic minority sampling technique (SMOTE) and grid search (GS). …”
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Joined Spatial and Spectral Segmentation of Hyperspectral Datasets on Historical Art Objects by Lingxi Liu, Aurore Malmert, Emeline Pouyet, Silvia Mirri, Giovanni Delnevo

“…We explore Simple Linear Iterative Clustering (SLIC) Superpixel’s potential in reducing hyperspectral data while maintaining spectral richness. By optimizing superpixel segmentation and extracting central spectra, we reduce data size significantly. …”
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HSI Reconstruction: A Spectral Transformer With Tensor Decomposition and Dynamic Convolution by Le Sun, Xihan Ma, Xinyu Wang, Qiao Chen, Zebin Wu

“…Conversely, traditional iterative optimization algorithms are built upon sound mathematical derivations. …”
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Mapping Polyclonal HIV-1 Antibody Responses via Next-Generation Neutralization Fingerprinting. by Nicole A Doria-Rose, Han R Altae-Tran, Ryan S Roark, Stephen D Schmidt, Matthew S Sutton, Mark K Louder, Gwo-Yu Chuang, Robert T Bailer, Valerie Cortez, Rui Kong, Krisha McKee, Sijy O'Dell, Felicia Wang, Salim S Abdool Karim, James M Binley, Mark Connors, Barton F Haynes, Malcolm A Martin, David C Montefiori, Lynn Morris, Julie Overbaugh, Peter D Kwong, John R Mascola, Ivelin S Georgiev

“…Specifically, we developed algorithms for: (a) selection of optimized virus neutralization panels for NFP analysis, (b) estimation of NFP prediction confidence for each serum sample, and (c) identification of sera with potentially novel epitope specificities. …”
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Overhead line path planning based on deep reinforcement learning and geographical information system by Jiahui Chen, Yi Yang, Ling Peng, Lina Yang, Yinhui Han, Xingtong Ge

“…This approach is mainly based on an assumption: the process of overhead line planning is a continuous trial-and-error process, and a relatively reasonable path can eventually be obtained through the continuous optimization of multiple objectives while meeting constraint conditions. …”
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Robust vector-weighted and matrix-weighted multi-view hard c-means clustering by Zhe Liu, Sarah Aljohani, Sijia Zhu, Tapan Senapati, Gözde Ulutagay, Salma Haque, Nabil Mlaiki

“…With the rapid advancement of information technology, multi-view data has become ubiquitous, prompting extensive attention towards multi-view clustering algorithms. Despite significant strides, several challenges persist: (1) the prevalence of noise and outliers in real-world multi-view data often compromises the efficacy of clustering; (2) most existing multi-view clustering algorithms predominantly assess the overall contribution of each view, while neglecting the intra-view contributions. …”
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Automated analysis and textual summarization of time-varying references in advanced greenhouse climate control by Ramesh Arvind Naagarajan, Kiran Kumar Sathyanarayanan, Nadja Bauer, Stefan Streif, Stefan Streif

“…The growing need for energy-efficient and sustainable crop production has made advanced control systems, such as Model Predictive Control (MPC), essential in greenhouse farming. MPC is an optimization-based control strategy that uses mathematical models and weather forecast data to regulate greenhouse climates effectively. …”
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Systematic Review on the Use of CCPM in Project Management: Empirical Applications and Trends by Adriano de Oliveira Martins, Vanderlei Giovani Benetti, Fernando Elemar Vicente dos Anjos, Débora Oliveira da Silva, Charles Jefferson Rodrigues Alves

“…Most studies used modeling and simulation, focusing on time reduction, risk mitigation, and cost optimization. A growing trend has been identified toward integrating CCPM with methodologies, such as Scrum, BIM, Lean Construction, Fuzzy FMEA, and predictive algorithms, thereby broadening its applicability in high-complexity scenarios. …”
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Improving health-promoting workplaces through interdisciplinary approaches. The example of WISEWORK-C, a cluster of five work and health projects within Horizon-Europe by Deborah De Moortel, Michelle C Turner, Ella Arensman, Alex Binh Vinh Duc Nguyen, Víctor Gonzalez

“…These shifts are giving rise to new forms of work (eg, hybrid work, gig economy jobs) and reshaping management and work organization practices (eg, through algorithmic decision-making or digital monitoring of worker performance). …”
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Artificial intelligence and machine learning in modern cardiology: Advancements in diagnosis, treatment and patient monitoring by Szymon Kopciał, Dawid Piecuch, Edyta Hańczyk, Karolina Kornatowska, Natalia Pawelec, Weronika Mazur

“… Introduction and purpose: Artificial intelligence (AI) and machine learning (ML) are impacting cardiology by enhancing diagnostic accuracy, personalizing treatment and optimizing patient care. This review examines current and emerging applications of AI and ML in cardiology, highlighting their transformative impact on clinical practice, workflow efficiency, and long-term patient outcomes. …”
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The Adversarial Robust and Generalizable Stereo Matching for Infrared Binocular Based on Deep Learning by Bowen Liu, Jiawei Ji, Cancan Tao, Jujiu Li, Yingxun Wang

“…This paper presents a novel deep-learning-based depth optimization method that obviates the need for large infrared image datasets and adapts seamlessly to any specific infrared camera. …”
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Neuromorphic principles for machine olfaction by Nik Dennler, Aaron True, André van Schaik, Michael Schmuker

“…Considering the physical characteristics of turbulent odour environments, we argue that event-driven signal processing is optimally suited to the inherent properties of olfactory signals. …”
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Research on load frequency control system attack detection method based on multi-model fusion by Feng Zheng, Weixun Li, Huifeng Li, Libo Yang, Zengjie Sun

“…A multi-model fusion attack detection framework is proposed, integrating (Long Short-Term Memory) LSTM supervised learning and autoencoder unsupervised learning algorithms, with an adaptive weight adjustment mechanism that dynamically optimizes detection strategies. …”
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PV Module Soiling Detection Using Visible Spectrum Imaging and Machine Learning by Boris I. Evstatiev, Dimitar T. Trifonov, Katerina G. Gabrovska-Evstatieva, Nikolay P. Valov, Nicola P. Mihailov

“…Some results from the application of the optimal model after specific weather events are also presented in this study. …”
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Computational Linguistics Applications in AI-Based Investment and Cost Structuring Models by Miralieva Dilafruz, Ramatov Jumaniyoz, Azimova Lola, Khusamiddinova Malika, Alimbaeva Shahlo, Omonova Laylo

“…AI-enabled linguistics modeling promotes scalable optimization and context-aware applications of financial analytics, and realizes cost transparency improvements in automated investment systems. …”
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An evaluation of multi-fidelity methods for quantifying uncertainty in projections of ice-sheet mass change by J. D. Jakeman, M. Perego, D. T. Seidl, T. A. Hartland, T. R. Hillebrand, M. J. Hoffman, S. F. Price

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Toward Greener Matrix Operations by Lossless Compressed Formats by Francesco Tosoni, Philip Bille, Valerio Brunacci, Alessio de de Angelis, Paolo Ferragina, Giovanni Manzini

“…Moreover, our experiments reveal that while data parallelism can improve execution speed and energy efficiency, optimizing both simultaneously poses interesting challenges. …”
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Advancing soil mapping and management using geostatistics and integrated machine learning and remote sensing techniques: a synoptic review by Sunshine A. De Caires, Chaney St Martin, Melissa A. Atwell, Fuat Kaya, Glorious A. Wuddivira, Mark N. Wuddivira

“…Hybrid approaches combining geostatistics with ML algorithms (e.g., RF, Boost, SVM, ANN) demonstrate promise in addressing spatial uncertainty, while RS data enhances covariate enrichment and near-real-time applications. …”
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The use of artificial intelligence in the HR processes of logistics companies by Adam Panek

“…Personalization of AI-based training improves employee engagement and productivity, while optimization of work schedules and accurate forecasting of staffing needs allow for better human resource management. …”
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Bioinformatic Analysis of Complex In Vitro Fertilization Data and Predictive Model Design Based on Machine Learning: The Age Paradox in Reproductive Health by Myrto A. Lantzi, Eleni Papakonstantinou, Dimitrios Vlachakis

“…This approach to the processing and utilization of clinical data demonstrates the potential for optimization and documentation of therapeutic procedures. …”
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