Hybrid deep learning architecture for scalable and high-quality image compression by Mustafa Al-Khafaji, Nehad T. A. Ramaha

“…A custom loss function that combines Mean Squared Error (MSE) and Structural Similarity Index (SSIM) ensures high perceptual quality and compression efficiency. …”
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Air Quality Prediction Model for Monitoring AQI by Das Aritra, Gupta Himanshu

“…Experimental findings suggest that the hybrid model outperforms standalone deep learning or ensemble methods, resulting in higher R² scores and lower error metrics. The study also discusses real-time applications, integration with additional data sources, and future research directions in AQI forecasting, aiming to support dynamic and accurate environmental monitoring systems.…”
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A Consistent Differential Privacy Dynamic Trajectory Flow Prediction Method by Hongzhi Pan

“…ABSTRACT Ensuring privacy while maintaining accuracy in trajectory prediction is a crucial challenge in privacy‐sensitive applications such as smart transportation and mobility analytics. …”
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Determining respiratory rate from photoplethysmogram and electrocardiogram signals using respiratory quality indices and neural networks. by Stephanie Baker, Wei Xiang, Ian Atkinson

“…We determine that calculating RQIs for modulation-extracted RRs decreased the mean absolute error (MAE) of our NNs by up to 38.17%. When trained and tested using 60-sec waveform segments, the proposed scheme achieved an MAE of 0.638 breaths per minute. …”
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MODEL PREDICTIVE CONTROL FOR PHOTOVOLTAIC STATION MAXIMUM POWER POINT TRACKING SYSTEM by I. Elzein, Yu. N. Petrenko

“…The system under consideration consists of a solar array with nonlinear time-varying characteristics, a step-up converter with appropriate filter.The proposed algorithm has the advantages of maximizing the efficiency of the power utilization, can be integrated to other MPPT algorithms without affecting the PVM performance, is excellent for Real-Time applications and is a robust analytical method, different from the traditional MPPT algorithms which are more based on trial and error, or comparisons between present and past states. …”
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A parametric bootstrap control chart for Lindley Geometric percentiles. by Muthanna Ali Hussein Al-Lami, Hossein Jabbari Khamnei, Ali Akbar Heydari

“…We conducted extensive simulations to assess the proposed control chart's effectiveness, considering various distribution parameters, percentile values, Type I error rates, and sample sizes. Our findings highlight how subgroup size, percentiles, and significance levels affect control limits, stressing the need for careful parameter selection in monitoring processes. …”
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TSHD: Topic Segmentation Based on Headings Detection (Case Study: Resumes) by Majd E. Tannous, Wassim H. Ramadan, Mohanad A. Rajab

“…Evaluation results show a very high F1 score (about 96%) and a very low segmentation error (about 2%). The algorithm can be easily adapted to deal with other textual domains that contain headings in their segments.…”
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Approximation and Generalization Capacities of Parametrized Quantum Circuits for Functions in Sobolev Spaces by Alberto Manzano, David Dechant, Jordi Tura, Vedran Dunjko

“…They are used to learn various types of data, with an underlying expectation that if the PQC is made sufficiently deep, and the data plentiful, the generalization error will vanish, and the model will capture the essential features of the distribution. …”
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Step-by-step classification detection algorithm of SPPM based on K-means clustering by Huiqin WANG, Wenbin HOU, Qingbin PENG, Minghua CAO, Rui HUANG, Ling LIU

“…In view of the high computational complexity in spatial pulse position modulation systems when using maximum likelihood detection algorithm, a step-by-step classification detection algorithm based on K-means clustering was proposed according to the characteristics of signal matrix with spatial pulse position modulation.The signal vector detection algorithm was utilized to detect the index of light source in the training samples.The on K-means clustering algorithm was utilized to acquire the mapping rule between centroid of samples and modulated symbol by offline training.Subsequently, online detection of modulated symbols was achieved based on the mapping rule, and then the index of light sources was detected by exhaustive search.In addition, Monte Carlo method was used to investigate the effects of key parameters such as the number of clusters and initialization times on the system bit error rate (BER) performance.Simulation results demonstrate that the proposed algorithm can achieve an approximate BER performance as the maximum likelihood algorithm on the basis of greatly reducing the computational complexity.Compared with the linear decoding algorithms, the proposed algorithm is also applicable to scenarios where the number of detectors is less than the number of light sources.…”
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Hybrid Transient-Machine Learning Methodology for Leak Detection in Water Transmission Mains by Caterina Capponi, Andrea Menapace, Silvia Meniconi, Daniele Dalla Torre, Maurizio Tavelli, Maurizio Righetti, Bruno Brunone

“…The accuracy of leak localization is demonstrated using three different degrees of noise in terms of mean absolute error, ranging between 0.54 m and 2.1 m. This proposed hybrid approach shows prospects for in-field applications.…”
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Downscaling GRACE total water storage data using random forest: a three-round validation approach under drought conditions by Youssef Hamou-Ali, Nourlhouda Karmouda, Ismail Mohsine, Tarik Bouramtane, Ilias Kacimi, Sarah Tweed, Sarah Tweed, Mounia Tahiri, Nadia Kassou, Ali El Bilali, Omar Chafki, Mohamed Abdellah Ezzaouini, Siham Laraichi, Abdelaaziz Zerouali, Marc Leblanc, Marc Leblanc, Marc Leblanc

“…The application of GRACE satellite-derived Total Water Storage (TWS) data for local water management is constrained by its coarse spatial resolution (100-300 km). …”
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Multispectral Land Surface Reflectance Reconstruction Based on Non-Negative Matrix Factorization: Bridging Spectral Resolution Gaps for GRASP TROPOMI BRDF Product in Visible by Weizhen Hou, Xiong Liu, Jun Wang, Cheng Chen, Xiaoguang Xu

“…The comprehensive test results show that this method is particularly effective in supplementing surface reflectance information for specific wavelengths where gas absorption is strong or atmospheric correction errors are significant, demonstrating its applicability not only within the 400–800 nm range but also across the broader spectral range of 400–2400 nm. …”
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Phenomenological Modeling on the Nonideal Factors of Memristor Based on Single-Crystalline LiNbO₃ Thin Film by Yi Wang, Xinqiang Pan, Qin Xie, Junde Tong, Yao Shuai, Wenbo Luo, Chuangui Wu, Wanli Zhang

“…However, the nonideal factors of memristors, such as conductance drift and programming errors, limit their performance in practical applications. …”
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Therapeutic Efficacy of Moxibustion with Seed-Sized Moxa-Cone at Jing Acupoint on Limb Spasticity after Stroke： A Meta-Analysis by ZHANG Jinfei, JIANG Jiahui, TANG Jiqin

“…Measurement data were expressed by mean difference (MD) and standardized mean difference (SMD) with 95% confidence interval (CI), and enumeration data were expressed by odds ratio (OR); SAS studio software was used to calculate the effect size (logrr) and standard error (selogrr) of ordinal data based on the cumulative odds model. …”
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Prediction of Hydrogen Production from Solid Oxide Electrolytic Cells Based on ANN and SVM Machine Learning Methods by Ke Chen, Youran Li, Jie Chen, Minyang Li, Qing Song, Yushui Huang, Xiaolong Wu, Yuanwu Xu, Xi Li

“…In recent years, the application of machine learning methods has become increasingly common in atmospheric science, particularly in modeling and predicting processes that impact air quality. …”
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Validation of CRU TS v4.08, ERA5-Land, IMERG v07B, and MSWEP v2.8 Precipitation Estimates Against Observed Values over Pakistan by Haider Abbas, Wenlong Song, Yicheng Wang, Kaizheng Xiang, Long Chen, Tianshi Feng, Shaobo Linghu, Muneer Alam

“…The monthly and seasonal precipitation estimations of each product were validated against in situ observations using statistical matrices, including the correlation coefficient (CC), root mean square error (RMSE), percent of bias (PBias), and Kling–Gupta efficiency (KGE). …”
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Replacement of fetal calf serum by human serum as supplementation for human fibroblast culture Substituição de soro bovino fetal por soro humano como suplemento para cultura de fib... by César Isaac, Cristiana Nicoli de Mattos, Francinni Mambrine Pires do Rêgo, Larissa Nocchi Cardim, Silvana Cereijido Altran, André Oliveira Paggiaro, Rafael Mamoru Carneiro Tutihashi, Mônica Beatriz Mathor, Marcus Castro Ferreira

“…Cell counts were obtained between 24 and 264 hours of cultivation; results were expressed as the mean number of cells ± standard error of the mean to create cell proliferation curves. …”
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Algoritma Jaro-Winkler Distance: Fitur Autocorrect dan Spelling Suggestion pada Penulisan Naskah Bahasa Indonesia di BMS TV by Agung Prasetyo, Wiga Maulana Baihaqi, Iqbaluddin Syam Had

“…Nowadays autocorrect feature is often encountered in various devices dan applications, like on the smartphone keyboard dan Microsoft Word application. …”
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Development, validation, and demonstration of the rotary parlor model by Ryan Prendergast, John Upton, Fergal Buckley, Michael D. Murphy

“…Model validation produced mean absolute percentage error values of 3.3%, 3.5%, and 2.9% for MPT, cows/h, and L/h metrics, respectively. …”
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A benchmark dataset for global evapotranspiration estimation based on FLUXNET2015 from 2000 to 2022 by W. Li, W. Li, Z. Yao, Z. Yao, Y. Qu, Y. Qu, H. Yang, Y. Song, L. Song, L. Wu, Y. Cui, Y. Cui

“…After analysis, the framework using the novel bias-corrected RF algorithm achieves excellent performance in both hourly gap-filling and daily prolongation, with mean root mean square error values of 33.86 and 16.58 <span class="inline-formula">W m⁻²</span>, respectively. …”
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