A Two-Criteria Weather Routing Method Based on Neural Network and A-star Algorithm by Khanh Huu Doan, Anh-Tuan Dinh

“…The HIL simulator is built from equations of the ship's 6 degrees of freedom (6-DOF), models of environmental disturbances, propulsion systems, and technical records of the real ship. In fact, operating data of the real ship is collected from noon reports, which are often incomplete in terms of environmental disturbances acting on the ship, not to mention the large sampling time (usually updated once a day). …”
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Real-time train acceleration estimation method based on least-square piecewise linear fitting by ZHU Baolin, CHEN Mingyang, LIU Yexuan, JIANG Fan, LI Tiebing, ZHOU Wenwei

“…Firstly, the median average filter algorithm was used to process the data collected by the speed sensor, and then the improved least square piecewise fitting algorithm was used to estimate the acceleration. …”
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Establishing laboratory-specific reference intervals for TSH and fT4 by use of the indirect Hoffman method. by Sylwia Płaczkowska, Małgorzata Terpińska, Agnieszka Piwowar

“…The aim of the study was the application of the indirect Hoffman method to determine RIs for TSH and fT4 based on the large data pools stored in laboratory information systems and the comparison of these RIs to generally used RIs.…”
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Carbon emission prediction method of steel plants based on long short-term memory network by Fengyun LI, Zehui DOU, Peng LI, Wei GUO

“…As the second largest carbon emitter in China, iron and steel enterprises have great potential for carbon emission reduction.In order to facilitate the supervision and control of carbon emissions by relevant departments, carbon emission prediction research is carried out.Taking a steelmaking plant as the research object, firstly, the carbon dioxide emissions in the steelmaking process were analyzed, and 10 energy substances that caused carbon emissions were determined.The basic energy data of the steelmaking plant from 2001 to 2023 were collected, and the carbon emissions were calculated from the basic energy data according to the carbon emission accounting method.Secondly, based on the long short-term memory network to predict the carbon emissions in the next 7 years, the training error and test error were close to 0.01, and the actual error was 1 323 307.46 tons of carbon dioxide.Then, the Mann-Kendall trend test was used to evaluate the overall carbon emission trend of the steelmaking plant.Finally, some reasonable suggestions were put forward for steelmaking plants in order to actively respond to the goal of low-carbon environmental protection.…”
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A novel prediction method for intracerebral hemorrhage-associated pneumonia: A single center analysis. by Ya-Ming Li, Yue Chen, Mei-Fen Yao, Guo-Jiang Wang, Yi-Ni Pan, Hui Chen, Jian-Hua Xu

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The effect of Eurasian Economic Union on trade of Kazakhstan: impact evaluation using the Synthetic Control Method by B. M. Mukhamediyev, Z. S. Temerbulatova, G. K. Ilyashova

“…For modeling data from Kazakhstan and 40 donor pool countries for 1995-2018 were collected. …”
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Classification and functional roots of the geometric patterns in the ornaments of traditional houses in Dezful based on vikor method by Ahmad Sarrafzadeh, Mohammad Didehban, Behzad Vasigh

“…The aim of this study is the documentation of geometric patterns and their underlying generative context in Dezful houses, answering research questions on the way. The research method is a combination of field studies and historical-interpretive methods, with data collected through library studies and personal observations. …”
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A Mechanism-aid Deep Learning Method for Li-ion Battery State-of-charge Estimation by Zhanghua Xiao, Cheng Ji, Fangyuan Ma, Jingde Wang, Wei Sun, Chi Zhai

“…However, existing methods that directly utilize measured data to establish the SOC estimation will suffer from low prediction accuracy due to the insufficient incorporation of mechanism information. …”
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Challenges and Benefits of Blended Learning in University EFL Reading Comprehension: A Mixed-Method Study by Dagnachew Tsegaye, Girma Gezahegn

“…The research focuses on exploring the experiences of first year university students engaged in BL-based reading comprehension. Using a mixed-method approach, data was collected from 36 participants enrolled in a noncredit reading skills course integrated with a BL platform over 16-weeks. …”
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A Short-Term Load Forecasting Method Based on CNN-BiGRU-NN Model by Youjun ZENG, Xianyong XIAO, Fangwei XU, Lin ZHENG

“…In order to fully mine the effective information contained in a large number of collected data and improve the accuracy of short-term load forecasting, a short-term load forecasting method is proposed based on a hybrid model of convolutional neural network (CNN), bidirectional gated recurrent unit (BiGRU), and fully connected neural network (NN). …”
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Evaluation of Calculation Methods used for Estimating the Ultimate Moment Resistance of Bridge Decks Reinforced with FRP Bars by Tomas Skuturna, Juozas Valivonis

“…Wilk-Shapiro test were used to determine the distribution of experimental and theoretical data. The statistical research to evaluate the calculation methods was performed by testing the statistical hypothesis on the differences between theoretical and experimental values. …”
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Highlighting the Best English Teaching Method for Katsina State Secondary Schools: Communicative Versus Traditional by Ibrahim Sani, Abdulhakim Saidu

“…In order to analyze the collected data, the researchers utilized the SPSS (IBM Statistical Processor Version 25) for precise and efficient processing, generating various necessary outputs to draw meaningful conclusions. …”
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A spatial interpolation method based on 3D-CNN for soil petroleum hydrocarbon pollution. by Sheng Miao, Guoqing Ni, Guangze Kong, Xiuhe Yuan, Chao Liu, Xiang Shen, Weijun Gao

“…By introducing Channel Attention Mechanism (CAM), the model assigns different weights to auxiliary variables, improving the prediction accuracy of soil hydrocarbon content. We collected soil pollution data and validated the spatial distribution map generated using this method based on the drilling dataset. …”
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A Method of Identifying the Characteristic Parameter of Material by Using Modal Test and Finite Element Analysis by Wang Lixin, Chen Linkai

“…At first,by using the LMS modal test system,an impact hammer test on the front housing of gearbox is performed,which is hung with rubber bands to simulate the free boundary conditions. By processing the collected data with LMS Test. Lab software,the first 8 order natural frequencies and damping ratios of the front housing of gearbox are identified. …”
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FedDDPG: A reinforcement learning method for federated learning-based vehicle trajectory prediction by Jinlong Li, Ruonan Li, Guojie Ma, Weihong Yang, Hongye Wang, Zhaoquan Gu

“…Federated Learning (FL) emerges as a promising approach to address these problems. However, trajectory data collected from roadside units often contains varying levels of noise, which poses unique challenges for traditional FL methods. …”
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Research and application of water drainage borehole design method based on three-dimensional geological model by Zhenrong WANG

“…The mine roadway model is reconstructed through the roadway centerline with three - dimensional coordinates and relevant attributes; the coal seam model is constructed by triangulating point data and boundary data, and is dynamically updated based on the cross - layer point data during borehole construction; the hydrogeological model is constructed by processing spatial data points using the Delaunay triangulation algorithm, similar to the coal seam modeling method, and is also updated according to the control point data collected during borehole construction. …”
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A Novel Denoising Algorithm of Electromagnetic Ultrasonic Detection Signal Based on Improved EEMD Method by Wenkang Gong, Qi Liu, Wenhao Du, Weichen Xu, Gang Wang

“…The results show that after processing, the noise component in the signal is less and the original information is more reserved, which prevents the signal distortion to a great extent and provides more effective data for subsequent processing. In the experiment, the crack defect data collected by the electromagnetic ultrasonic experiment system were processed by the improved EEMD method. …”
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Fault Detection Method of Low-Orbit Satellite Internet Based on Deep Uncertainty Estimation Network by Wenyu SUN, Weijia ZHANG, Limin WANG

“…Low-orbit satellite internet technology is a highly innovative direction of development with few existing cases.Low-orbit satellite internet systems are characterised by a large number of constituent satellites, frequent topology changes, and complex payload types.The fault categories of such complex systems are diffi cult to be completely mastered with methods such as expert systems or practical engineering experience.Moreover, traditional fault detection and diagnosis methods tailored for a single satellite and a single functionality are diffi cult to predict uncertain faults under sophisticated and transient environment conditions.For the above problems, a fault prediction model based on the deep uncertainty estimation network for low-orbit satellite internet was proposed, and was verifi ed used self-collected data from simulated joint satellite-ground tests.Experimental results showed that the proposed method could improved the detection accuracy of known types of faults and demonstrated particular eff ectiveness in predicting faults of unknown types.…”
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Challenge of successful KMSs implementation: exploration of effective factors on KM acceptance via mixed method by Mona Jami Pour, Mohammad Hossein Sherkat

“…Finally, in order to validating developed model, number of KM experts and specialists are asked to assess the factors and collected data were analyzed with structural equation modelling (SEM). …”
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Development of a deep learning method to identify acute ischaemic stroke lesions on brain CT by Emanuele Trucco, Joanna M Wardlaw, Wenwen Li, Grant Mair, Amos Storkey, Alessandro Fontanella, Antreas Antoniou, Eleanor Platt, Paul Armitage

“…Machine learning techniques can provide rapid automated CT assessment but are usually developed from annotated images which necessarily limits the size and representation of development data sets. We aimed to develop a deep learning (DL) method using CT brain scans that were labelled but not annotated for the presence of ischaemic lesions.Methods We designed a convolutional neural network-based DL algorithm to detect ischaemic lesions on CT. …”
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