Simultaneous OPEX and carbon footprint reduction with hydrogen enhancement in autothermal reforming: a machine learning–based surrogate modeling and optimization framework by Sahar Shahriari, Davood Iranshahi

“…In this study, a Surrogate-assisted Multi-Objective Reinforcement Learning (S-MORL) framework is developed to achieve the simultaneous minimization of OPEX and CO₂ emissions while enhancing hydrogen production within the ATR process. The approach integrates tabular Q-learning with a random forest-based surrogate model to accelerate objective evaluations during policy training, significantly improving sample efficiency and reducing dependence on computationally expensive reactor simulations. …”
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A pursuit-evasion game robot controller design based on a neural network with an improved optimization algorithm by Mustafa Wassef Hasan, Luay G. Ibrahim

“…The ISCACT has been used in two cases, the first case arises when ISCACT is used in the follower robot’s learning process. In the second case, the ISCACT has been used in the leader robot’s learning process. …”
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Application of the Double Approximation Method for Constructing Stiffness Matrices of Volumetric Finite Elements by P. P. Gaidzhurov, N. A. Saveleva

“…Software development and computational experiments were carried out using the Microsoft Visual Studio 2013 64-bit computing platform and the Intel ® Parallel Studio XE 2019 compiler with the integrated Intel ® Visual Fortran Composer XE 2019 text editor. …”
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Predicting viral host codon fitness and path shifting through tree-based learning on codon usage biases and genomic characteristics by Shuquan Su, Zhongran Ni, Tian Lan, Pengyao Ping, Jinling Tang, Zuguo Yu, Gyorgy Hutvagner, Jinyan Li

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A novel lightweight YOLOv8-PSS model for obstacle detection on the path of unmanned agricultural vehicles by Zhijian Chen, Yijun Fang, Jianjun Yin, Shiyu Lv, Farhan Sheikh Muhammad, Lu Liu

“…Firstly, this work integrates partial convolution (PConv) into the C2f module of the backbone network to improve inference performance and minimize computing load. PConv significantly reduces processing load during convolution operations, enhancing the model's real-time detection performance. …”
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Chiller power consumption forecasting for commercial building based on hybrid convolution neural networks-long short-term memory model with barnacles mating optimizer by Mohd Herwan Sulaiman, Zuriani Mustaffa

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Justifying the selection of a neural network linguistic classifier by Олеся Барковська, Ксенія Воропаєва, Олександр Руських

“… The subject matter of this article revolves around the exploration of neural network architectures to enhance the accuracy of text classification, particularly within the realm of natural language processing. The significance of text classification has grown notably in recent years due to its pivotal role in various applications like sentiment analysis, content filtering, and information categorization. …”
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Ensemble design for seasonal climate predictions: studying extreme Arctic sea ice lows with a rare event algorithm by J. Sauer, F. Massonnet, G. Zappa, F. Ragone

“…However, the significant computational burden of complex climate models makes it challenging to quantitatively investigate extreme events with probabilities below a few percent. …”
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TTE scheduling method based on adaptive dual redundancy and performance analysis by WANG Qing, TENG Li-ping, CUI Xin, WANG Kuo, WANG Xian, LI Wen-jian

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Comparative Analysis of Trophic Status Assessment Using Different Sensors and Atmospheric Correction Methods in Greece’s WFD Lake Network by Vassiliki Markogianni, Dionissios P. Kalivas, George P. Petropoulos, Rigas Giovos, Elias Dimitriou

“…Today, open-source Cloud Computing platforms are valuable for geospatial image analysis while the combination of the Google Earth Engine (GEE) platform and new satellite launches greatly facilitate the monitoring of national-scale lake Water Quality (WQ). …”
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Monitoring of urinary microbiota and uropathogens' antibiotic resistance in one urological hospital by Yu. L. Naboka, A. K. Alkina, M. I. Kogan, I. A. Gudima, Kh. S. Ibishev, K. T. Jalagoniya, M. L. Chernitskaya

“…Statistical analysis was performed in the statistical processing and data visualization environment «R ver 3.2» («R Foundation for Statistical Computing», Vienna, Austria).Results. …”
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An ODE based neural network approach for PM2.5 forecasting by Md Khalid Hossen, Yan-Tsung Peng, Asher Shao, Meng Chang Chen

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Cross-validation for training and testing co-occurrence network inference algorithms by Daniel Agyapong, Jeffrey Ryan Propster, Jane Marks, Toby Dylan Hocking

“…While some microorganisms cause diseases, most of them help in biological processes such as decomposition, fermentation and nutrient cycling. …”
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An enhanced denoising system for mammogram images using deep transformer model with fusion of local and global features by A. Robert Singh, Suganya Athisayamani, Faten Khalid Karim, Ahmed Zohair Ibrahim, Sameer Alshetewi, Samih M. Mostafa

“…Abstract Image denoising is a critical problem in low-level computer vision, where the aim is to reconstruct a clean, noise-free image from a noisy input, such as a mammogram image. …”
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A Novel Method for 3D Lung Tumor Reconstruction Using Generative Models by Hamidreza Najafi, Kimia Savoji, Marzieh Mirzaeibonehkhater, Seyed Vahid Moravvej, Roohallah Alizadehsani, Siamak Pedrammehr

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A Community Effort to Develop Common Data Elements for Pre-Clinical Spinal Cord Injury Research by Britt A. Fedor, Abel Torres-Espin, Romana Vavrek, Maryann E. Martone, John L. Bixby, John C. Gensel, Vance Lemmon, Jeffrey S. Grethe, J. Russel Huie, Adam R. Ferguson, Karim Fouad, Collaboration group, Collaboration group

“…For nearly 350 years, the process of disseminating scientific knowledge has remained largely unchanged. …”
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Medical VR Simulator for Pediatric Strabismus Treatment by Artem Obukhov, Elena Kutimova, Julia Matrosova, Daniil Teselkin, Maxim Shilcin

“…Existing computer programs and medical equipment should be supplemented with more modern tools and approaches based on virtual reality (VR) technologies, ensuring the full immersion of children in the treatment process. …”
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Performance Evaluation of Extended EWMA Chart for AR Model with Exogenous Variables by Totsaporn Muangngam, Yupaporn Areepong, Saowanit Sukparungsee

“…The extended exponentially weighted moving average (Extended EWMA) control chart is an effective statistical process control method for monitoring and identifying shifts in process mean, particularly when dealing with autocorrelated data. …”
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Role of additive manufacturing in developing functionally graded materials for nuclear applications by Amal Sasi, Madhulika Srivastava, K. Dash

“…A comparative analysis of the manufacturing capabilities of the additive manufacturing techniques, along with the usage of advanced computational techniques such as AI in optimising process parameters for desirable strength and low defect generation, is also presented. …”
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Two-stage deep reinforcement learning method for agile optical satellite scheduling problem by Zheng Liu, Wei Xiong, Zhuoya Jia, Chi Han

“…Next, a decomposition strategy decomposes the executable task sequence into multiple sub-sequences in the observation scheduling stage, and the observation scheduling process of these sub-sequences is modeled as a concatenated Markov decision process. …”
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