Reliable QoE Prediction in IMVCAs Using an LMM-Based Agent by Michael Sidorov, Tamir Berger, Jonathan Sterenson, Raz Birman, Ofer Hadar

“…We apply four Machine Learning (ML) algorithms and a Large Multimodal Model (LMM)-based agent, achieving mean errors of 4.61%, 5.36%, and 13.24% for three popular QoE metrics: BRISQUE, PIQE, and FPS, respectively.…”
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ecochange: An R‐package to derive ecosystem change indicators from freely available earth observation products by Wilson Lara, Maria C. Londoño, Ivan Gonzalez, Victor H. Gutierrez‐Velez

“…Abstract Spatial resources accessible for the derivation of biodiversity indicators of the class ecosystem structure are sparse and disparate, and their integration into computer algorithms for biodiversity monitoring remains problematic. …”
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Instruments for assessing healthcare professionals’ knowledge, attitudes and practices regarding deprescribing: a scoping review protocol by Luciane Cruz Lopes, Jardel Corrêa de Oliveira, Luis Phillipe Nagem Lopes, Mariana Del Grossi Moura, Ana Carolina Figueiredo Modesto, Laís Lessa Neiva Pantuzza

“…Studies focusing on deprescribing algorithms will be excluded. Studies in any healthcare setting will be included. …”
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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

“…Here, we present next-generation NFP algorithms that substantially improve prediction accuracy for individual donors and enable serologic analysis for entire cohorts. …”
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Inhibition mediated by group III metabotropic glutamate receptors regulates habenula activity and defensive behaviors by Anna Maria Ostenrath, Nicholas Faturos, Yağnur Işık Çiftci Çobanoğlu, Bram Serneels, Inyoung Jeong, Ekin Dongel Dayanc, Anja Enz, Francisca Hinrichsen, Aytac Kadir Mutlu, Ricarda Bardenhewer, Suresh Kumar Jetti, Stephan C. F. Neuhauss, Nathalie Jurisch-Yaksi, Emre Yaksi

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AI-assisted Pattern Generator for Garment Design by Michael Danner, Elena Brake, Gabriela Kosel, Yordan Kyosev, Katharina Rose, Matthias Rätsch, Holger Cebulla

“…The process uses advanced AI algorithms to facilitate the conversion of 3D scans into usable patterns. …”
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Regression Model Employing Spiking Neural Network for Bio-Signal Analysis With Hardware Integration by Choongseop Lee, Geunbo Yang, Jaewoo Baek, Yuntae Park, Mingyu Cheon, Jongkil Park, Cheolsoo Park

“…Spiking neural networks, known for mimicking the brain’s functionality resulting in efficient algorithms, are gaining attention across various problems and applications. …”
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Artificial intelligence: clinical applications and future advancement in gastrointestinal cancers by Abolfazl Akbari, Maryam Adabi, Mohsen Masoodi, Abolfazl Namazi, Abolfazl Namazi, Fatemeh Mansouri, Seidamir Pasha Tabaeian, Seidamir Pasha Tabaeian, Zahra Shokati Eshkiki

“…There are encouraging signs that the advent of artificial intelligence could enhance the treatment of gastrointestinal issues with this data. Deep learning algorithms can swiftly and effectively analyze unstructured, high-dimensional data, including texts, images, and waveforms, while advanced machine learning approaches could reveal new insights into disease risk factors and phenotypes. …”
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Pavement performance model for road maintenance and repair planning: a review of predictive techniques by Krishna Singh Basnet, Jagat Kumar Shrestha, Rabindra Nath Shrestha

“…It explores the implications of these limitations on accuracy and application, while also discussing how advanced predictive analytics can address these challenges. …”
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Advanced Brain Tumor Segmentation With a Multiscale CNN and Conditional Random Fields by Ala Guennich, Mohamed Othmani, Hela Ltifi

“…The use of high-precision automatic algorithms for segmenting brain tumors has the potential to improve disease diagnosis, treatment monitoring, and large-scale pathological studies. …”
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A Novel Method for Community Detection in Bipartite Networks by Ali Khosrozadeh, Ali Movaghar, Mohammad Mehdi Gilanian Sadeghi, Hamidreza Mahyar

“…Nevertheless, some of them need a lot of time, which restricts their use in large networks. While several low-time complexity algorithms exist, their practical value in real-world applications is limited since they are typically non-deterministic. …”
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Innovative Approaches to Sustainable Urban Planning: Analysing Current Trends by Meruyert Baidrakhmanova, Gani Karabayev, Seimur Mamedov

“…Artificial intelligence facilitates urban planning through data analysis and pattern recognition, while generative adversarial networks and transformers improve design and data processing functionalities. …”
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Stochastic Potential Game-Based Target Tracking and Encirclement Approach for Multiple Unmanned Aerial Vehicles System by Kejie Yang, Ming Zhu, Xiao Guo, Yifei Zhang, Yuting Zhou

“…Utilizing fully distributed intelligent control algorithms has enabled the gradual adoption of the multiple unmanned aerial vehicles system for executing Target Tracking and Encirclement missions in industrial and civil applications. …”
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A novel method for predicting the geochemical composition of tailings with laboratory field and hyperspectral airborne data using a regression and classification-based approach by Yaron Ogen, Michael Denk, Cornelia Glaesser, Holger Eichstaedt

“…The increasing demand for precise and dependable models has led to the development of both sensors and statistical algorithms. However, numerous studies have demonstrated that model performance is highly dependent on a range of environmental factors, such as spatio-temporal fluctuations of moisture, sensor type, sample variability, preprocessing methods, and model selection. …”
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Efficient text-to-video retrieval via multi-modal multi-tagger derived pre-screening by Yingjia Xu, Mengxia Wu, Zixin Guo, Min Cao, Mang Ye, Jorma Laaksonen

“…Extensive experimental results demonstrate that our proposed method significantly accelerates the TVR process while maintaining high retrieval accuracy on various TVR datasets.…”
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Developing a Unified Framework for PMSM Speed Regulation: Active Disturbance Rejection Control via Generalized PI Control by Huanzhi Wang, Yuefei Zuo, Chenhao Zhao, Christopher H. T. Lee

“…The results demonstrate the relationship between ADRC and generalized PI control while highlighting ADRC’s superior capabilities. …”
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Parameter Tuning for Local-Search-Based Matheuristic Methods by Guillermo Cabrera-Guerrero, Carolina Lagos, Carolina Castañeda, Franklin Johnson, Fernando Paredes, Enrique Cabrera

“…Algorithms that aim to solve optimisation problems by combining heuristics and mathematical programming have attracted researchers’ attention. …”
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Providing contexts for classification of transients in a wide-area sky survey: An application of noise-induced cluster ensemble by Tossapon Boongoen, Natthakan Iam-On, James Mullaney

“…The results with simulated data and algorithms of NB, C4.5 and KNN have shown that the proposed framework can filter out some negative samples quickly, while making classification of the rest more effective. …”
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Drunk Driver Detection Using Multiple Non-Invasive Biosignals by Sang Hyuk Kim, Hyo Won Son, Tae Mu Lee, Hyun Jae Baek

“…Using more than 10 machine learning algorithms, the classification accuracy reached 88%. …”
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An Efficient and Low-Complexity Transformer-Based Deep Learning Framework for High-Dynamic-Range Image Reconstruction by Josue Lopez-Cabrejos, Thuanne Paixão, Ana Beatriz Alvarez, Diodomiro Baldomero Luque

“…This paper proposes an HDR reconstruction architecture using a Transformer-based approach to achieve results competitive with the state of the art while reducing computational cost. The number of self-attention blocks was reduced for feature refinement. …”
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