Perceptual responses of (sports-)clothing-body interaction simulating pre- and post-purchase experience by Julia Wilfling, George Havenith, Margherita Raccuglia, Simon Hodder

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Development of a bench-scale Kroll reactor: Experimental results and preliminary findings by T.A. Ferguson, C. Reilly, S.L. Cockcroft, D․ M․ Maijer

“…Despite its widespread industrial use, the Kroll process has received limited attention in the scientific literature, with existing studies presenting limited process data with differing interpretations. …”
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Perceptual responses of (sports-)clothing-body interaction simulating pre- and post-purchase experience by Julia Wilfling, George Havenith, Margherita Raccuglia, Simon Hodder

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Perceptual responses of (sports-)clothing-body interaction simulating pre- and post-purchase experience by Julia Wilfling, George Havenith, Margherita Raccuglia, Simon Hodder

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Perceptual responses of (sports-)clothing-body interaction simulating pre- and post-purchase experience by Julia Wilfling, George Havenith, Margherita Raccuglia, Simon Hodder

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Assessment of operational non-time-critical Sentinel-6A Michael Freilich radio occultation data: insights into tropospheric GNSS signal cut-off strategies and processor improvement... by S. Paolella, A. Von Engeln, S. Padovan, R. Notarpietro, C. Marquardt, F. Sancho, V. Rivas Boscan, N. Morew, F. Martin Alemany

“…Additionally, the analysis revealed terrestrial interference signals on the L2 frequency, confirming that they do not significantly compromise the Sentinel-6A RO data quality.</p> <p>The validation of the EUMETSAT processed Sentinel-6A RO-NTC data against the European Centre for Medium-Range Weather Forecasts (ECMWF) short-range forecasts and comparisons with Metop-B/C and EUMETSAT-processed SPIRE occultations, highlights the reduction in random error and modifications in the tropospheric bias structure, a result of the enhancements in data processing techniques. …”
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Geoinformation Monitoring of Demographic Development of Krasnodar Urban Agglomeration by N. V. Sopnev

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Impact of Chronic Kidney Disease on the Processes of Care and Long‐Term Mortality of Non–ST‐Segment–Elevation Myocardial Infarction: A Nationwide Cohort Study and Long‐Term Follow‐... by Nicholas Weight, Saadiq Moledina, Mohsin Ullah, Harindra C. Wijeysundera, Simon Davies, Nicholas W. S. Chew, Claire Lawson, Safi U. Khan, Chris P. Gale, Muhammad Rashid, Mamas A. Mamas

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Well control diagnosis model of underground gas storage in multi-cycle operation by ZHANG Siyuan, YANG Jiakun, SONG Lina, ZHOU Dongliang, HU Jun, XU Feng, SHI Yuxia, XU Hongcheng, PEI Gen, FAN Jiayi

“…The process begins with preprocessing the dynamic production data from W23 UGS, which is then inputted into RTA software along with the reservoir parameters. …”
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CHPOA-DBN Transformer Fault Diagnosis Method Considering Sample Within-Class Imbalance by Shuang WANG, Qian LUO, Bo TANG, Lan JIANG, Jin LI

“…Then, the Tent chaotic map embedded chaotic hybrid pelican optimization algorithm (CHPOA) is developed to optimize the number of hidden layer nodes and reverse fine-tuning learning rate of DBN, and the CHPOA-DBN transformer fault diagnosis model is constructed. …”
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PREDIKSI HARGA EMAS MENGGUNAKAN METODE AVERAGE BASED FUZZY TIME SERIES by Yusmet Rizal, Suci Ramadhani

“…The method used Average Based Fuzzy Time Series (ABFTS) allows processing data with irregular fluctuations, thus providing more stable and reliable results. …”
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Optimizing bioprocessing efficiency with OptFed: Dynamic nonlinear modeling improves product-to-biomass yield by Guido Schlögel, Rüdiger Lück, Stefan Kittler, Oliver Spadiut, Julian Kopp, Jürgen Zanghellini, Mathias Gotsmy

“…Process design is based on simple feed profiles (e.g., constant or exponential), operator experience, and basic statistical tools (e.g., response surface methodology), which are unable to harvest the full potential of production.To address this challenge, we propose a general modeling framework, OptFed, which utilizes experimental data from non-optimal fed-batch processes to predict an optimal one. …”
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Revisiting X-Ray Afterglows of Jetted Tidal Disruption Events with the External Reverse Shock by Chengchao Yuan, Walter Winter, B. Theodore Zhang, Kohta Murase, Bing Zhang

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Impact of SAR Image Quantization Method on Target Recognition With Neural Networks by Kangwei Li, Di Wang, Daoxiang An

“…Despite deep neural network models achieving recognition rates exceeding 99&#x0025; under standard operating conditions on the moving and stationary target acquisition and recognition dataset, the unique imaging mechanisms of SAR, its background dependency, variations in imaging parameters, and diversity in preprocessing lead to highly variable image statistical characteristics, thereby affecting the performance of deep learning models. …”
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eGFR slope as predictor of mortality in heart failure patients by Sofie Verstreken, Monika Beles, Clara L. Oeste, Ana Moya, Imke Masuy, Riet Dierckx, Ward Heggermont, Jeroen Dauw, Dries Hens, Jozef Bartunek, Marc Vanderheyden

“…Methods and results Retrospective clinical data of HF patients were processed using natural language processing. …”
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The Use of Economic and Mathematical Modeling in Assessing the Competitiveness of Tourism Industry Enterprises by S. N. Medvedeva, V. P. Pavlyuk

“…According to the results of the study, the nature of the relationship between the share of the gross value added of the tourism industry in the gross regional product and the consumer price index, the growth rate of retail turnover, the growth rate of public catering turnover, and the quantity of registered crimes was revealed. …”
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Skills Prediction for the South African Food and Beverages Manufacturing Sector by Megashnee Munsamy, Arnesh Telukdarie

“…The analysis identified four vital skills: (1) entrepreneurship inclusive of digital skills; (2) data analytics inclusive of AI, simulation, and modelling; (3) digital tools and technologies implementation, and operation; and (4) sustainable operations skills of advanced process control, and energy, water, and resource optimisation. …”
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Priority-aware task offloading for LEO satellite edge computing network: a multi-agent deep reinforcement learning-based approach by Juan Chen, Jie Zhong, Zongling Wu, Di Tian, Yujie Chen

“…This provides a new avenue for real-time data processing on a global scale. However, effectively scheduling tasks to optimize resource utilization, reduce processing delay, and ensure the timeliness of task execution has become a critical issue in SatEC. …”
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Methodological Validation of Machine Learning Models for Non-Technical Loss Detection in Electric Power Systems: A Case Study in an Ecuadorian Electricity Distributor by Carlos Arias-Marín, Antonio Barragán-Escandón, Marco Toledo-Orozco, Xavier Serrano-Guerrero

“…This study proposes a methodology based on data analytics that, through the processing of information, generates lists of suspicious metering systems for fraud. …”
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Prediction of Machining Characteristics and Machining Performance for Grade 2 Titanium Material in a Wire Electric Discharge Machine Using Group Method of Data Handling and Artific... by Sudhir Jain Prathik, Athimoolam Sundaramahalingam, Maddur Eswara Nithyashree, Addamani Rudreshi, Gonchikar Ugrasen

“…This study investigates numerous process parameters, including pulse on time, current, pulse off time, voltage, bed speed and flush rate. …”
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