Advancements in Predictive Microbiology: Integrating New Technologies for Efficient Food Safety Models by Oluseyi Rotimi Taiwo, Helen Onyeaka, Elijah K. Oladipo, Julius Kola Oloke, Deborah C. Chukwugozie

“…Due to their ability to predict the microbial risk, these tools are also integrated into hazard analysis critical control point (HACCP) protocols. …”
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Understanding Precipitation Moisture Sources and Their Dominant Factors During Droughts in the Vietnamese Mekong Delta by Keke Zhou, Xiaogang Shi

“…The local atmospheric conditions may also have a causal effect on moisture recycling. …”
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Classical machine learning and artificial neural network (ANN) to predict rejection in weaving industry by Toufique Ahmed

“…The optimal hyperparameters for these best-performing algorithms were also selected using RandomizedSearchCV. …”
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“I exist because I adapt”: Evolving technology HR themes, HR roles with STARA competencies for performance by Vinit Ghosh, Gaurav Kabra

“…Similarly, new tech-based HR roles and future-oriented STARA competencies have also been highlighted. The findings are novel in identifying the barriers and enablers to technology HRM systems in organizations. …”
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Diagnosis of Coronary Heart Diseases Using Gene Expression Profiling; Stable Coronary Artery Disease, Cardiac Ischemia with and without Myocardial Necrosis. by Nabila Kazmi, Tom R Gaunt

“…Three different feature optimisation algorithms were devised which identified two discriminating sets of genes, one using MI and normal controls (total genes = 6) and another one using MI and unstable angina patients (total genes = 7). …”
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BharatSim: An agent-based modelling framework for India. by Philip Cherian, Jayanta Kshirsagar, Bhavesh Neekhra, Gaurav Deshkar, Harshal Hayatnagarkar, Kshitij Kapoor, Chandrakant Kaski, Ganesh Kathar, Swapnil Khandekar, Saurabh Mookherjee, Praveen Ninawe, Riz Fernando Noronha, Pranjal Ranka, Vaibhhav Sinha, Tina Vinod, Chhaya Yadav, Debayan Gupta, Gautam I Menon

“…BharatSim uses a synthetic population created by applying statistical methods and machine learning algorithms to survey data from multiple sources, including the Census of India, the India Human Development Survey, the National Sample Survey, and the Gridded Population of the World. …”
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Random Natural Gradient by Ioannis Kolotouros, Petros Wallden

“…Hybrid quantum-classical algorithms appear to be the most promising approach for near-term quantum applications. …”
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Influence of Clinician-Related Factors on Adherence to the American Heart Association Guidelines for Acute Coronary Syndrome among Clinicians at Kenya Ports Authority clinics in Mo... by Mary Kavinya Mailu, Nilufa Jivraj Shariff, Ruth Mbugua

“…The study recommends enhancing resource allocation for ACS management, ensuring availability of essential medications and equipment, and developing simplified clinical algorithms to support guideline adherence. Regular audits and continuous professional development are also advised to sustain adherence and improve patient care quality.…”
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Instagram and #Wellness: Uncovering Gender and Body Patterns by Ana Marta M. Flores, Rita Sepúlveda

“…Not only do these platforms serve as spaces for the public expression of wellness-related topics, but they also influence public perceptions. This becomes particularly meaningful when these expressions are linked to gender. …”
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A model of thalamo-cortical interaction for incremental binding in mental contour-tracing. by Daniel Schmid, Heiko Neumann

“…They utilize Gestalt properties and eventually show growth-cone characteristics labeling perceptual items by delayed activity enhancement of neuronal firing rates. We discuss the algorithmic process underlying incremental binding and relate it to our model computations. …”
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Privacy-Preserving Machine Learning for IoT-Integrated Smart Grids: Recent Advances, Opportunities, and Challenges by Mazhar Ali, Moharana Suchismita, Syed Saqib Ali, Bong Jun Choi

“…Recent studies have provided valuable insights into the potential of machine learning algorithms in SGs, covering areas such as generation, distribution, microgrids, consumer energy market, and cyber security. …”
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From 3D reality-based models to volumes for structural analysis: some critical issues by Sara Gonizzi Barsanti, Juergen Juergen Frick

“…Noise not only deforms the unstructured geometry of the point clouds, but also adds useless information and reduces the geometric accuracy of the mesh model obtained and, consequently, the results of any analysis performed on it. …”
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SETI@home: Data Analysis and Findings by David P. Anderson, Eric J. Korpela, Dan Werthimer, Jeff Cobb, Bruce Allen

“…This approach also allowed us to estimate the sensitivity of our detection system to these signals.…”
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AIR-POLSAR-CR1.0: A Benchmark Dataset for Cloud Removal in High-Resolution Optical Remote Sensing Images with Fully Polarized SAR by Yuxi Wang, Wenjuan Zhang, Jie Pan, Wen Jiang, Fangyan Yuan, Bo Zhang, Xijuan Yue, Bing Zhang

“…The results of the ablation experiment also demonstrate the effectiveness of the PolSAR data. …”
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Transfer Learning-Empowered Physical Layer Security in Aerial Reconfigurable Intelligent Surfaces-Based Mobile Networks by Yosefine Triwidyastuti, Tri Nhu Do, Ridho Hendra Yoga Perdana, Kyusung Shim, Beongku An

“…To address these challenges, we develop robust algorithms for optimizing the phase-shift configurations of RIS. …”
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Comparative study of IoT- and AI-based computing disease detection approaches by Wasiur Rhmann, Jalaluddin Khan, Ghufran Ahmad Khan, Zubair Ashraf, Babita Pandey, Mohammad Ahmar Khan, Ashraf Ali, Amaan Ishrat, Abdulrahman Abdullah Alghamdi, Bilal Ahamad, Mohammad Khaja Shaik

“…This study evaluated different machine learning and deep learning algorithms and their hybrid and optimized algorithms for IoT-based disease detection, using the most recent papers on IoT-based disease detection systems that include computing approaches, such as cloud, edge, and fog. …”
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Analysis and quality control of weighing lysimeter water storage data by Steven R. Evett, Paul D. Colaizzi, Gary W. Marek, Karen S. Copeland, Brice B. Ruthardt

“…Other algorithms act upon these flags to correct and adjust the original raw relative storage values so that the adjusted relative storage reflects only ET. …”
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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

“…Experimental verification of real data shows that compared with existing algorithms, the DSOP method is not only more consistent with the manual line selection effect (improved by more than 3%), but also has a high success rate. …”
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De Olho na Mata: monitoring Atlantic Forests with drones and few-shot learning by A. A. Pedro, F. Dadrass Javan, S. Georgievska, E. H. P. Barreto, O. Ku, F. de Oliveira, P. D. P. Oliveira, C. Gevaert

“…It describes best practices on how to conduct drone flights to map the forests, exponentially expanding the range of identification and efficiency in invasive tree species management. It also presents an AI workflow that uses few-shot learning and Explainable AI techniques (to guarantee transparency and understanding of the decisions made by the algorithms). …”
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Accelerating Ray Tracing-Based Wireless Channels Generation for Real-Time Network Digital Twins by Claudio Modesto, Lucas Mozart, Pedro Batista, Andre Cavalcante, Aldebaro Klautau

“…It also proposes a post-processing method that augments a set of RT results to achieve an improved time resolution. …”
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