Interleaved Landsman Converter with Class Topper Optimized PI Control in Sensorless BLDC Motor Drive for Electric Vehicle by Suresh V., Jahnavi V.G., Manjula D., Lokesh M.

“…In order to achieve the set goals, the following tasks were accomplished: The scientific novelty of this work lies in the design of a novel interleaved Landsman converter along with Class Topper Optimization (CTO) algorithm. …”
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Capturing Spatial-Temporal Traffic Patterns: A Dynamic Partitioning Strategy for Heterogeneous Traffic Networks by Xianyue Peng, Hao Wang

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Impact of a Novel Electronic Medical Record–Integrated Electronic Form (Provider Asthma Assessment Form) and Severe Asthma Algorithm in Primary Care: Single-Center, Pre- and Postob... by Matheson L McFarlane, Alison Morra, Delanya Podgers, David Barber, M Diane Lougheed

“…Retrospective baseline data were collected for 2 years prior to PAAF implementation from January 2018 to December 2019. …”
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A combination of urinary biomarker panel and PancRISK score for earlier detection of pancreatic cancer: A case-control study. by Silvana Debernardi, Harrison O'Brien, Asma S Algahmdi, Nuria Malats, Grant D Stewart, Marija Plješa-Ercegovac, Eithne Costello, William Greenhalf, Amina Saad, Rhiannon Roberts, Alexander Ney, Stephen P Pereira, Hemant M Kocher, Stephen Duffy, Oleg Blyuss, Tatjana Crnogorac-Jurcevic

“…Here, we aimed to establish the accuracy of an improved panel, including REG1B instead of REG1A, and an algorithm for data interpretation, the PancRISK score, in additional retrospectively collected urine specimens. …”
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The Use of Neural Networks in Distance Education Technologies for the Identification of Students by O. A. Kozlova, A. A. Protasova

“…The identification procedure must be repeated several times during a session to ensure that the identity of the authorized user is verified.Conclusion. Realizing the set goal to study the problematics of learning technologies of modern artificial neural networks for carrying out the procedure of unambiguous authentication of students according to a pre-formed reference base of digital biometric characteristics of authorized users in the field of distance learning technologies, and relying on the results obtained in the course of generalization and analysis of existing experience and our own studies, the authors identified two independent stages in the algorithm for the implementation of the task of identifying the student’s personality: the formation of a reference base of digital biometric characteristics of authorized users and user authentication according to the previously formed reference base, and also revealed that when training a neural network, it is necessary to take into account a sufficiently large number of different attributes affecting it. …”
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A Corn Point Cloud Stem-Leaf Segmentation Method Based on Octree Voxelization and Region Growing by Qinzhe Zhu, Ming Yu

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Genome-wide association studies are enriched for interacting genes by Peter T. Nguyen, Simon G. Coetzee, Irina Silacheva, Dennis J. Hazelett

“…Results We used genetic algorithms to measure fitness of gene-cell set proposals against a series of objective functions that capture data and annotations. …”
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Real-Time Motor Control Using a Raspberry Pi, ROS, and CANopen over EtherCAT, with Application to a Semi-Active Prosthetic Ankle by Kieran M. Nichols, Rebecca A. Roembke, Peter G. Adamczyk

“…CANopen over EtherCAT was implemented directly on the Raspberry Pi to synchronize real-time communication between it and the motor controllers. Kinematic algorithms for setting ankle angles of zero to ten degrees in any combination of sagittal and frontal angles were implemented. …”
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Performance Predictions of Solar-Assisted Heat Pumps: Methodological Approach and Comparison Between Various Artificial Intelligence Methods by Minghui Ma, Oguzhan Pektezel, Vincenzo Ballerini, Paolo Valdiserri, Eugenia Rossi di Schio

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Deep Learning Unravels Differences Between Kinematic and Kinetic Gait Cycle Time Series from Two Control Samples of Healthy Children Assessed in Two Different Gait Laboratories by Alfonso de Gorostegui, Damien Kiernan, Juan-Andrés Martín-Gonzalo, Javier López-López, Irene Pulido-Valdeolivas, Estrella Rausell, Massimiliano Zanin, David Gómez-Andrés

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A large-scale prospective nested case-control study: developing a comprehensive risk prediction model for early detection of pancreatic cancer in the community-based ESPRIT-AI coho... by Chaoliang Zhong, Penghao Li, Jia Zhao, Xue Han, Beilei Wang, Gang Jin

“…Findings: The cohort was divided into training (n=39,929, including 45 cases and 900 nested controls) and test (n=11,561, including 15 cases and 11,546 controls) sets. …”
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Quantitative Comparison of Geographical Color of Traditional Village Architectural Heritage Based on K-Means Color Clustering—A Case Study of Southeastern Hubei Province, China by Li Dong, Meiqi Kang

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"Non-destructive and rapid determination of bound styrene content of styrene-butadiene rubber latex using near-infrared spectroscopy" by LI Yan, ZHONG Ming-li, ZHU Shi-yong, CUI Jia-min, ZHANG Jian-ping, CHEN Shi-long

“…A non-destructive and rapid determination of bound styrene content in styrene-butadiene rubber latex was studied using near-infrared spectroscopy diffuse transmission method combined with chemometrics, bound styrene content in styrene-butadiene rubber latex was determined by refractive index method, near-infrared spectral data of styrene-butadiene rubber latex were collected using Fourier transform near-infrared spectrometer, Kennard-Stone algorithm was used to divide the calibration set and validation set, partial least squares regression quantitative analysis model was established by combining the spectral preprocessing methods, such as multiple scattering correction method, second-order derivatives and Norris smoothing, etc, and the influence of screening spectral feature variables by interval partial least squares algorithm on the quantitative ana-lysis model was finally investigated. …”
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Effectiveness of biomarker-guided duration of antibiotic treatment in children hospitalised with confirmed or suspected bacterial infection: the BATCH RCT by Cherry-Ann Waldron, Philip Pallmann, Simon Schoenbuchner, Debbie Harris, Lucy Brookes-Howell, Céu Mateus, Jolanta Bernatoniene, Katrina Cathie, Saul N Faust, Josie Henley, Lucy Hinds, Kerry Hood, Chao Huang, Sarah Jones, Sarah Kotecha, Sarah Milosevic, Helen Nabwera, Sanjay Patel, Stéphane Paulus, Colin VE Powell, Jenny Preston, Huasheng Xiang, Emma Thomas-Jones, Enitan D Carrol

“…Setting Paediatric wards or paediatric intensive care units within children’s hospitals (n = 6) and district general hospitals (n = 9) in the United Kingdom. …”
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Digital augmentation of aftercare for patients with anorexia nervosa: the TRIANGLE RCT and economic evaluation by Janet Treasure, Katie Rowlands, Valentina Cardi, Suman Ambwani, David McDaid, Jodie Lord, Danielle Clark Bryan, Pamela Macdonald, Eva Bonin, Ulrike Schmidt, Jon Arcelus, Amy Harrison, Sabine Landau

“…Design Transition Care In Anorexia Nervosa through Guidance Online from Peer and Carer Expertise was a multicentre, parallel-group, superiority randomised controlled trial. ECHOMANTRA augmented treatment as usual was compared with treatment as usual. …”
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Integration of bulk RNA-seq and scRNA-seq reveals transcriptomic signatures associated with deep vein thrombosis by Bao-ze Pan, Ming-jun Jiang, Li-ming Deng, Jie Chen, Xian-peng Dai, Zi-xuan Wu, Zhi-he Deng, Dong-yang Luo, Yang-yi-jing Wang, Dan Ning, Guo-zuo Xiong, Guo-shan Bi

“…Based on the same methodology as the internal test set, 12 DVT patients and six control groups were collected to construct an external test set and validated using machine learning (ML) algorithms and immunofluorescence (IF). …”
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Combined Prediction of Dust Concentration in Opencast Mine Based on RF-GA-LSSVM by Shuangshuang Xiao, Jin Liu, Yajie Ma, Yonggui Zhang

“…Next, the data are split into a training set and a test set at a 7:3 ratio, and the genetic algorithm (GA) is applied to optimize the least squares support vector machine (LSSVM) model for predicting dust concentration in opencast mines. …”
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A diagnostic model for polycystic ovary syndrome based on machine learning by Cheng Tong, Yue Wu, Zhenchao Zhuang, Ying Yu

“…The data of 10 case groups and 10 control groups were randomly selected as validation set data, and the rest of the data were included in the model construction. …”
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Hard-coded backdoor detection method based on semantic conflict by Anxiang HU, Da XIAO, Shichen GUO, Shengli LIU

“…The current router security issues focus on the mining and utilization of memory-type vulnerabilities, but there is low interest in detecting backdoors.Hard-coded backdoor is one of the most common backdoors, which is simple and convenient to set up and can be implemented with only a small amount of code.However, it is difficult to be discovered and often causes serious safety hazard and economic loss.The triggering process of hard-coded backdoor is inseparable from string comparison functions.Therefore, the detection of hard-coded backdoors relies on string comparison functions, which are mainly divided into static analysis method and symbolic execution method.The former has a high degree of automation, but has a high false positive rate and poor detection results.The latter has a high accuracy rate, but cannot automate large-scale detection of firmware, and faces the problem of path explosion or even unable to constrain solution.Aiming at the above problems, a hard-coded backdoor detection algorithm based on string text semantic conflict (Stect) was proposed since static analysis and the think of stain analysis.Stect started from the commonly used string comparison functions, combined with the characteristics of MIPS and ARM architectures, and extracted a set of paths with the same start and end nodes using function call relationships, control flow graphs, and branching selection dependent strings.If the strings in the successfully verified set of paths have semantic conflict, it means that there is a hard-coded backdoor in the router firmware.In order to evaluate the detection effect of Stect, 1 074 collected device images were tested and compared with other backdoor detection methods.Experimental results show that Stect has a better detection effect compared with existing backdoor detection methods including Costin and Stringer: 8 hard-coded backdoor images detected from image data set, and the recall rate reached 88.89%.…”
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Research on dust identification and concentration detection method based on machine vision by Luyang TU, Qinghua CHEN, Yingsong CHENG, Bingyou JIANG

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