Research on Speed and Position Detection Technology for Train Operation Control System Based on Multi-Source Information Fusion by YANG Chongfu

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Tools to improve discharge equity: Protocol for the pilot TIDE trial by Kirsten Austad, Cecilia Thai, Alegna Zavatti, Nhi Nguyen, Diana Bautista-Hurtado, Patrick Kenney, Noelia Lugo, Joo H. Lee, Howard Lanney, Ziming Xuan, Erika G. Cordova-Ramos, Mari-Lynn Drainoni, Brian Jack

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Comparative analysis of frequency characteristics for constructing digital models options of components of electrical complexes aperiodic units by Alexander S. Glazyrin, Evgeniy I. Popov, Semen S. Popov, Vladimir A. Kopyrin, Sergey N. Kladiev, Andrey P. Leonov, Nataliya A. Voronina, Vladimir Z. Kovalev

“…As a result, the aim of the paper is to determine the limits of applicability in the frequency domain of existing methods of transition to the Z-region using the analog prototype method by conducting a comparative analysis of the integral error in approximating the frequency characteristics of the analog prototype with digital models of the aperiodic link for each of the methods. …”
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Perturbative gravitational wave predictions for the real-scalar extended Standard Model by Oliver Gould, Paul M. Saffin

“…Abstract We perform a state-of-the-art study of the cosmological phase transitions of the real-scalar extended Standard Model. …”
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60-GHz Millimeter-Wave Propagation Inside Bus: Measurement, Modeling, Simulation, and Performance Analysis by Aniruddha Chandra, Aniq Ur Rahman, Ushasi Ghosh, Jose A. Garcia-Naya, Ales Prokes, Jiri Blumenstein, Christoph F. Mecklenbrauker

“…Finally, a tapped-delay-line (TDL) channel model is formulated from the proposed PDP model, and the TDL model is used to study the bit error rate (BER) performance of the mmWave link inside bus under varying data rates and link lengths.…”
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MOTION PRECISION ANALYSIS OF PERMANENT MAGNET SYBCHRONOUS GRINDING MOTORIZED SPINDLE by GAO Feng, CHENG MingKe, LI Yan, HE PingPing, JIA WeiTao

“…The results show that when the speed increases to the maximum speed,the radial error and the axial error increase,the centrifugal force has a more obvious effect on the spindle accuracy; when there is the spindle eccentricity,the radial error motion trajectory gradually transitions from the approximate circle to the petal state. …”
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Advancing amorphous solid dispersions through empirical and hybrid modeling of drug–polymer solubility and miscibility: A case study using Ibuprofen by Matheus de Castro, Ana Sara Cordeiro, Mingzhong Li, Christian Lübbert, Catherine McColl, Jatin Khurana, Mark Evans, Walkiria S. Schlindwein

“…HPMCAS also exhibited consistently prediction errors across all Tg models, (AARD ∼4.5 %), indicating poorer agreement with experimental data. …”
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A prediction model of massive 5G network users’ revisit behavior based on telecom big data by Yudi SUN

“…Users in 5G networks will generate a large amount of access data, which makes it difficult to accurately predict users’ revisit behavior.Therefore, a prediction model of massive 5G network users’ revisit behavior based on telecom big data was proposed.The user’s historical online behavior characteristic data was extracted from the telecom big data to build a data set.Multi order weighted Markov chain model was introduced.The model weight value was obtained by calculating the autocorrelation coefficient of each order, and the statistics of the model were calculated.After analysis, the one-step transition probability matrix of Markov chain with each step size was obtained, so as to accurately predict the revisit behavior of massive users in 5G network.The experimental results show that the proposed model has the lowest mean error and standard deviation, as well as the highest accuracy, recall, precision and F1 indicators, which can prove that the proposed method has a very obvious advantage in predicting users’ revisit behavior.…”
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A prediction model of massive 5G network users’ revisit behavior based on telecom big data by Yudi SUN

“…Users in 5G networks will generate a large amount of access data, which makes it difficult to accurately predict users’ revisit behavior.Therefore, a prediction model of massive 5G network users’ revisit behavior based on telecom big data was proposed.The user’s historical online behavior characteristic data was extracted from the telecom big data to build a data set.Multi order weighted Markov chain model was introduced.The model weight value was obtained by calculating the autocorrelation coefficient of each order, and the statistics of the model were calculated.After analysis, the one-step transition probability matrix of Markov chain with each step size was obtained, so as to accurately predict the revisit behavior of massive users in 5G network.The experimental results show that the proposed model has the lowest mean error and standard deviation, as well as the highest accuracy, recall, precision and F1 indicators, which can prove that the proposed method has a very obvious advantage in predicting users’ revisit behavior.…”
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Renewable energy and its impact on agricultural and economic development in the Netherlands and South Africa by Saul Ngarava, Alois Aldridge Mugadza

“…Moreover, in the Netherlands, the adjustment speed was –1.46 for renewable energy consumption with an error correction of 0.68 a (8.22 months). In South Africa, the adjustment speed was –1.28 for renewable energy consumption with an error correction of 0.78 a (9.38 months). …”
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Detection Technology for Catenary Stagger Value Based on Acceleration Signals by CHEN Hongming, ZHOU Ning, LU Wenwei, YANG Zixian, CHENG Yao, WANG Dong, ZHANG Weihua

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Design of Network Control System for Automatic Train Operation with High-Precision Synchronization and High-Reliability Redundancy by WANG Xianbing, LI Cheng, WU Wenhui, TANG Zhilong, MO Yun, WEN Fa

“…The advent of automatic train operation (ATO) technologies for rail transit vehicles has increasingly elevated the corresponding safety and reliability standards of network control systems in this sector. …”
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Machine learning based method for forecasting short-term passenger flow in urban rail stations by HU Mingwei, SHI Xiaolong, WU Wenlin, HE Guoqing

“…Urban rail transit features much strength, such as large capacity, safety and environment-friendliness, and it becomes a preferred choice for most passengers. …”
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Thrust Resistance Calculation Method in Diaphragm Wall Grab Trenching Considering Soil Accumulation and Slurry Pressure by CAO Yu, MENG Hongfeng, WANG Qian, WANG Xiaohui, LI Jie, CHEN Fudan

“…[Objective] With the rapid development of urban rail transit in China, the excavation depth of station foundation pit diaphragm wall is increasing continuously, and the soil layers that are excavated through is becoming more complex. …”
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Blood Pressure and Heart Rate Measurements Using Fiber Bragg Grating Sensor with Optical Power Detection Scheme by Yu-Jie Wang, Likarn Wang

“…The results demonstrate that the errors between the calculated values and reference values of SBP and DBP for all of the 29 subjects both range from −4 to 5 mmHg with mean errors of 0.72 mmHg and 0.83 mmHg, respectively. …”
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A Hybrid Strategy-Improved SSA-CNN-LSTM Model for Metro Passenger Flow Forecasting by Jing Liu, Qingling He, Zhikun Yue, Yulong Pei

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An improved multi-step prediction control algorithm for urban rail hybrid energy storage system by YANG Fengping, ZHOU Mingzhi, CHENG Quan, ZHANG Yin

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Impact of frailty in older people on health care demand: simulation modelling of population dynamics to inform service planning by Bronagh Walsh, Carole Fogg, Tracey England, Sally Brailsford, Paul Roderick, Scott Harris, Simon Fraser, Andrew Clegg, Simon de Lusignan, Shihua Zhu, Francesca Lambert, Abigail Barkham, Harnish Patel, Vivienne Windle

“…The average age of transition from fit to mild was 69 years, fit/mild to moderate was 77 years and any category to severe was 81 years. …”
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Quantum Hardware Devices (QHDs): Opportunities and Challenges by Aziz Oukaira

“…Despite their transformative potential, QHDs face critical hurdles, such as decoherence, Quantum Error Correction (QEC), scalability, and seamless integration with classical computing systems. …”
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Accelerated Prediction of Terahertz Performance Metrics in GaN IMPATT Sources via Artificial Neural Networks by Santu Mondal, Sneha Ray, Aritra Acharyya, Rudra Sankar Dhar, Arindam Biswas, Hiroaki Satoh, Gurudas Mandal, Vitaliy Maksimenko, Victor Krishtop

“…This work investigates the application of artificial neural network (ANN)-based regression models to predict the static and dynamic characteristics of GaN impact avalanche transit time (IMPATT) sources in the terahertz (THz) frequency regime. …”
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