Happiness management and workplace well-being: Evolution, key insights, and future directions. A systematic review by Mario Alberto Salazar-Altamirano, Esthela Galván Vela, Rafael Ravina-Ripoll, Mónica Lorena Sánchez-Limón

“…However, limited research exists on SMEs and the gig economy, inconsistencies in measurement methods, and a lack of longitudinal studies assessing the long-term impact of workplace happiness. …”
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Advancing 1.5T MR imaging: toward achieving 3T quality through deep learning super-resolution techniques by Sk Rahatul Jannat, Kirsten Lynch, Maryam Fotouhi, Steve Cen, Steve Cen, Jeiran Choupan, Nasim Sheikh-Bahaei, Nasim Sheikh-Bahaei, Gaurav Pandey, Bino A. Varghese

“…Specifically, we employed metrics such as the Structural Similarity Index Measure (SSIM), Peak Signal-to-Noise Ratio (PSNR), Learned Perceptual Image Patch Similarity (LPIPS), and Intensity Differences in Pixels (IDP) to evaluate the similitude and visual quality of the enhanced images.ResultsAccording to our experimental results it has been exhibited that among the three evaluated deep learning-based super-resolution techniques, the Transformer Enhanced Generative Adversarial Network (TCGAN) significantly outperformed the others. …”
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Evolution of deep learning tooth segmentation from CT/CBCT images: a systematic review and meta-analysis by Wai Ying Kot, Sum Yin Au Yeung, Yin Yan Leung, Pui Hang Leung, Wei-fa Yang

“…This systematic review and meta-analysis aims to evaluate the evolution and performance of deep learning in tooth segmentation. Methods We systematically searched PubMed, Web of Science, Scopus, IEEE Xplore, arXiv.org, and ACM for studies investigating deep learning in human tooth segmentation from CT/CBCT. …”
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Predicting trajectories of coastal area vessels with a lightweight Slice-Diff self attention by Jinxu Zhang, Jin Liu, Xiliang Zhang, Lai Wei, Zhongdai Wu, Junxiang Wang

“…Existing trajectory prediction studies predominantly employ recurrent neural network (RNN) and Transformer-based methods. However, the former often encounter challenges such as gradient vanishing or exploding, and the latter tend to focus on global temporal dependencies, making it difficult to capture local irregular trajectory features in coastal maritime areas. …”
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A Multimodal Large Language Model Framework for Intelligent Perception and Decision-Making in Smart Manufacturing by Tianyu Wang, Bowen Zhang, Daqi Jiang, Dong Li

“…This approach addresses common limitations of traditional single-modal methods, such as isolated data analysis and poor integration between different data types. …”
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METHODOLOGY OF COSEISMIC DISPLACEMENTS COMBINATION OBTAINED BY DATA STEMMING FROM HETEROGENEOUS GEODETIC NETWORKS: ON THE EXAMPLE OF THE GREAT 2011 TOHOKU EARTHQUAKE, Mw 9.1 by N. V. Shestakov, М. D. Gerasimenko, А. К. Kishkina, V. G. Bykov, V. V. Pupatenko, А. S. Prytkov, N. F. Vasilenko, V. S. Zhizherin, S. V. Yakovenko

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Palmprint recognition based on principal line features by Hongxia Wang, Teng Lv

“…With the successful removal of fine lines by WLE, we propose a new Layer Visual Transformer (LViT) design paradigm. For its input, distinct blocking strategies are adopted, carefully designed to partition the data to capture different levels of spatial and feature information, using larger blocks for global structure and smaller ones for local details. …”
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A systematic narrative review of the research evidence of the impact of intersectionality on service engagement and help-seeking across different groups of women, trans women, and... by Carolin Hess, Zahra Abdulla, Lydia Finzel, Antonina Semkina, Jess Harris, Annette Boaz, Jill Manthorpe

“…Narrative methods were utilised in the synthesis and analysis of the research.…”
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A Framework for Predicting Winter Wheat Yield in Northern China with Triple Cross-Attention and Multi-Source Data Fusion by Shuyan Pan, Liqun Liu

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Instance-Level Weighted Contrast Learning for Text Classification by Xinhui Liu, Jifa Chen, Qiubo Huang

“…Contrastive learning has become a key research focus aimed at improving classification performance by learning the similarities and differences between samples using models. However, existing contrastive learning methods have notable shortcomings, primarily concerning insufficient data utilization. …”
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Approach to design of distributed multi-agent system for processing sound information of the environment by U. A. Vishniakou, B. H. Shaya

“…Two estimations of a sound situation are given: on the basis of short-term energy and average speed of change. Three different classification methods are investigated: KNearest neighbors, Gaussian mixture model and Support vector machine.Multi-agent system (M)AS characteristics are given, the classification, trends in the use of multi-agent intelligent technologies for information processing are presented. …”
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Photovoltaic Power Forecasting with Weather Conditioned Attention Mechanism by Xuetao Jiang, Yuchun Gou, Meiyu Jiang, Lihui Luo, Qingguo Zhou

“…However, the PV process is affected differently by various factors under different weather conditions, resulting in significantly different energy output curves. …”
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Kinematical Analysis of Waist Structure of Single Drive Robot by Hu Yankai, Zheng Meng, Hou Zhao, Lin Yuanbin, He Beilin

“…The kinematical principle of the structure and the selection of the relevant initial parameters are introduced and the coordinate transformation matrix of the upper body under different conditions is obtained by Denavit-Hartenberg（ D-H） method. …”
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Sustainable Material Selection in Construction using Multi Criteria Decision Analysis (MCDA) by Sudakova Anna, Lalitha Yaragudipati Sri, Reddy K. Ramakrishna, Kataria Ansh, Prakash Sunil, Sharma Gazal, Mittal Sachin, Kumar Yogesh, Almusawi Muntather

“…Sustainable material is an innovative combination of hybrid engineering methods and advanced Multi Criteria Decision that seeks to transform the properties of materials on different surfaces. …”
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Computer-Modeling System of Agronomist’s Labor Functions by I. E. Bystrenina

“…Among the main objectives of the research is the study of the essence of computer modeling as a teaching method in the works of domestic scientists, as well as the construction of models and their implementation using high-level programming languages in order to obtain an information system for the labor functions of an agronomist.Materials and methods. …”
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A Frequency-Independent Phase Shifter by Máté Csanád, Amira K. F. Val Baker, Paul Oomen

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Entropy-Guided KV Caching for Efficient LLM Inference by Heekyum Kim, Yuchul Jung

“…Instead of selecting different key–value tokens per head, our method selects a common set of important tokens per layer, based on aggregated attention scores, and caches them uniformly across all heads within the same layer. …”
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Multi-scale attention patching encoder network: a deployable model for continuous estimation of hand kinematics from surface electromyographic signals by Chuang Lin, Qiong Xiao, Penghui Zhao

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Rapid landslide detection from free optical satellite imagery using a robust change detection technique by Rosa Coluzzi, Angela Perrone, Caterina Samela, Vito Imbrenda, Salvatore Manfreda, Letizia Pace, Maria Lanfredi

“…In this study, the wide-ranging Tasseled Cap Transformation (TCT) is proposed as a not-sophisticated and rapid method able to detect different land-change features simultaneously by processing only two (pre- and post-event) Sentinel-2 images. …”
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Study of Recent Image Restoration Techniques: A Comprehensive Survey by Nikita Singhal, Anup Kadam, Pravesh Kumar, Hritik Singh, Aaryan Thakur, Pranay

“…This article provides an all-inclusive review of state-of-the-art (SOTA) methods in image restoration, covering traditional methods as well as modern techniques like deep learning and transformer-based models. …”
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