Sentiment Analysis Using Stacking Ensemble After the 2024 Indonesian Election Results by Andy Victor Pakpahan, Fahmi Reza Ferdiansyah, Robby Gustian, Muhammad Nur Faiz, Sukma Aji

“…By leveraging the complementary strengths of each base model, stacking not only boosts accuracy but also increases model robustness, making it highly suitable for real-world sentiment analysis applications that involve noisy and informal textual data from social media.…”
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Dual-coding Contrastive Learning Based on the ConvNeXt and ViT Models for Morphological Classification of Galaxies in COSMOS-Web by Shiwei Zhu, Guanwen Fang, Chichun Zhou, Jie Song, Zesen Lin, Yao Dai, Xu Kong

“…Benefiting from its higher efficiency, this updated algorithm is well suited for application in future China Space Station Telescope missions.…”
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Maximum-likelihood Regression with Systematic Errors for Astronomy and the Physical Sciences. II. Hypothesis Testing of Nested Model Components for Poisson Data by Massimiliano Bonamente, Dale Zimmerman, Yang Chen

“…A novel model of systematic errors for the regression of Poisson data is applied to hypothesis testing of nested model components with the introduction of a generalization of the Δ C statistic that applies in the presence of systematic errors. …”
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A Novel Hybridized Cluster-Based Geographical Opportunistic Routing Protocol for Effective Data Routing in Underwater Wireless Sensor Networks by B. Ragavi, V. Baranidharan, K. Ramash Kumar

“…These networks are employed to transmit the data with enhanced quality of service (QoS). However, efficient data routing is the most challenging obstacle in many underwater applications. …”
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Harmonizing ground and UAV hyperspectral data: A novel spectral correction method for maximizing estimation models and datasets of ground hyperspectral by Zhonglin Wang, Pengxin Deng, Kairui Chen, Ying Xiong, Feng Yang, Cheng Wang, Zhixin Li, Biao Li, Yongjian Sun, Zongkui Chen, Zhiyuan Yang, Jun Ma

“…Importantly, the applicability and effectiveness of the CNC estimation models and the dataset of corrected hyperspectral were explored for hyperspectral images. …”
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An iteration-free approach for determining the average reservoir pressure and original gas in place by production data analysis: Methodology and field cases by Yang Wang, Shilong Yang, Hang Xie, Naichao Feng, Haiyang Yu

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Robust Synthetic Data Generation for Sequential Financial Models Using Hybrid Variational Autoencoder–Markov Chain Monte Carlo Architectures by Francesco Bruni Prenestino, Enrico Barbierato, Alice Gatti

“…Generating high-quality synthetic data is essential for advancing machine learning applications in financial time series, where data scarcity and privacy concerns often pose significant challenges. …”
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Transforming Quality Management with Industry 4.0 Technologies: A Meta-Analytic Review of AI, Blockchain, IoT, and Big Data by SOUAD LAHMINE, FATIMA BENNOUNA

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Enhanced large-scale building extraction evaluation: developing a two-level framework using proxy data and building matching by Shenglong Chen, Yoshiki Ogawa, Chenbo Zhao, Yoshihide Sekimoto

“…Deep learning-based building extraction methods have widespread applications in diverse fields. However, the evaluation of large-scale extraction results remains challenging, due to traditional evaluation metrics rely on manually created ground-truth samples and the lack of comprehensive reference-building data for developing countries. …”
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Enhancing image security via chaotic maps, Fibonacci, Tribonacci transformations, and DWT diffusion: a robust data encryption approach by Mohammad Mazyad Hazzazi, Mujeeb Ur Rehman, Arslan Shafique, Amer Aljaedi, Zaid Bassfar, Aminu Bello Usman

“…Abstract In recent years, numerous image encryption schemes have been developed that demonstrate different levels of effectiveness in terms of robust security and real-time applications. While a few of them outperform in terms of robust security, others perform well for real-time applications where less processing time is required. …”
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Lentil plant disease and quality assessment: A detailed dataset of high-resolution images for deep learning researchMendeley Data by Eram Mahamud, Md Assaduzzaman, Shayla Sharmin

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CSTFNet: A CNN and Dual Swin-Transformer Fusion Network for Remote Sensing Hyperspectral Data Fusion and Classification of Coastal Areas by Dekai Li, Harold Neira-Molina, Mengxing Huang, Syam M.S., Yu Zhang, Zhang Junfeng, Uzair Aslam Bhatti, Muhammad Asif, Nadia Sarhan, Emad Mahrous Awwad

“…However, due to the high dimensionality of HSI data and the complexity of spectral-spatial feature extraction, achieving accurate results in coastal areas remains challenging. …”
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A Novel Efficient Certificateless Signature Scheme for the Prevention of Content Poisoning Attack in Named Data Networking-Based Internet of Things by Saddam Hussain, Syed Sajid Ullah, Abdu Gumaei, Mabrook Al-Rakhami, Ijaz Ahmad, Syed Muhammad Arif

“…Recently, Named Data Networking (NDN) has emerged as a popular and active Internet architecture that addresses the issues of current host-centric communication. …”
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Nowcasting Solar Irradiance Components Using a Vision Transformer and Multimodal Data from All-Sky Images and Meteorological Observations by Onon Bayasgalan, Atsushi Akisawa

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Bare surface soil moisture and surface roughness estimation using multi-band multi-polarization NISAR-like SAR data by Sami Najem, Nicolas Baghdadi, Henri Bazzi, Mehrez Zribi, Dharmendra Kumar Pandey, Muddu Sekhar

“…The upcoming NISAR Earth-observation satellite will utilize dual frequencies simultaneously, providing synthetic aperture radar (SAR) remote sensing data in both the L-band and S-band. With its ability to operate single-polarization, dual-polarization, and quad-polarization modes, NISAR will offer significant capabilities for land surface observation applications, particularly for estimating surface soil moisture (SSM) and surface roughness (Hrms). …”
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Improving GOCI ocean color data under high solar-zenith angle over open oceans using neural networks by Xiaoming Liu, Menghua Wang

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Data Collection for Automatic Depression Identification in Spanish Speakers Using Deep Learning Algorithms: Protocol for a Case-Control Study by Luis F Brenes, Luis A Trejo, Jose Antonio Cantoral-Ceballos, Daniela Aguilar-De León, Fresia Paloma Hernández-Moreno

“…A minimum participation of 60 subjects was established and 2 health centers were selected to gather data. A total of 3 types of data are collected: voice recordings, depression labels (using the Patient Health Questionnaire-9), and additional data that could potentially influence speech. …”
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Scalable Hyperspectral Enhancement via Patch-Wise Sparse Residual Learning: Insights from Super-Resolved EnMAP Data by Parth Naik, Rupsa Chakraborty, Sam Thiele, Richard Gloaguen

“…A majority of hyperspectral super-resolution methods aim to enhance the spatial resolution of hyperspectral imaging data (HSI) by integrating high-resolution multispectral imaging data (MSI), leveraging rich spectral information for various geospatial applications. …”
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OliveTreeCrownsDb: A high-resolution UAV dataset for detection and segmentation in agricultural computer visionMendeley Data by Youness Hnida, Mohamed Adnane Mahraz, Ali Achebour, Ali Yahyaouy, Jamal Riffi, Hamid Tairi

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