Showing 1,741 - 1,760 results of 2,509 for search '(soft OR shift) algorithm', query time: 0.14s Refine Results
  1. 1741

    Wavelets, approximation, and comperssion by Sarkout Abdi, Aram Azizi, Mahmoud Shafiei, Jamshid Saeidian

    Published 2024-11-01
    “…The basis functions are eigenfunctions of linear shift invariant systems or, in other words, Fourier series diagonalize linear, shift invariant operators.…”
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    Article
  2. 1742

    Encryption & Hiding Information in Internet Files HTML & XML by Dujan Taha, Ahmed Nori, Najla Ibraheem

    Published 2010-06-01
    “…Hiding in HTML files was done by first encrypting the message using Linear Feedback Shift Register (LFSR) and embed the encryption key into the HTML tags. …”
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  3. 1743

    Developing and validating a machine learning-based model for predicting in-hospital mortality among ICU-admitted heart failure patients: A study utilizing the MIMIC-III database by De Su, Jie Zheng, Yue-kai Shao, Jun-ya Liu, Xin-xin Liu, Kun Yu, Bang-hai Feng, Hong Mei, Song Qin

    Published 2025-04-01
    “…Results In five-fold cross-validation, the soft voting ensemble learning model demonstrated the best overall performance, with accuracy and AUC values both at 0.86. …”
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    Article
  4. 1744

    An Effective Ensemble Approach for Preventing and Detecting Phishing Attacks in Textual Form by Zaher Salah, Hamza Abu Owida, Esraa Abu Elsoud, Esraa Alhenawi, Suhaila Abuowaida, Nawaf Alshdaifat

    Published 2024-11-01
    “…Our empirical experiments demonstrates that using ensemble learning to merge attributes in the evolution of phishing emails showcases the competitive performance of ensemble learning over other machine learning algorithms. This superiority is underscored by achieving an F1-score of 0.90 in the weighted ensemble method and 0.85 in the soft voting method, showcasing the effectiveness of this approach.…”
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  5. 1745

    COMPARATIVE EVALUATION OF INDICATORS OF STRUCTURAL AND MECHANICAL PROPERTIES OF WHEAT GRAIN by P. V. Medvedev, V. A. Fedotov, E. S. Lukyanova

    Published 2020-11-01
    “…The following hard and soft wheat varieties of different districts of the Orenburg region harvest of the last 5 years were studied: 10 Orenburgskaya, 200 Bezenchukskaya, 21 Orenburgskaya, Bezenchuksky amber, 3 Kharkovskaya, 3 Step, 42 Saratovskaya, Uchitel, 13 Orenburgskaya, 3 Yugo-vostochnaya, Varyag, Prokhorovka, L-503.The virtuosity of grain was determined in the traditional way, the hardness of the grain – using the developed fractographic analysis, using computer (technical) vision algorithms to describe the geometric characteristics of the size and shape of the particles of ground grain.The article presents the results of a comparative assessment of the virtuosity and hardness of grain of hard and soft wheat varieties. …”
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  6. 1746

    TAL-SRX: an intelligent typing evaluation method for KASP primers based on multi-model fusion by Xiaojing Chen, Xiaojing Chen, Jingchao Fan, Jingchao Fan, Shen Yan, Longyu Huang, Longyu Huang, Longyu Huang, Guomin Zhou, Guomin Zhou, Jianhua Zhang, Jianhua Zhang

    Published 2025-02-01
    “…Finally, the two machine learning algorithms are fused through a soft voting integration strategy to output the KASP marker typing effect scores. …”
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    Article
  7. 1747

    Study on the inversion and spatiotemporal variation mechanism of soil salinization at multiple depths in typical oases in arid areas: A case study of Wei-Ku Oasis by Jinming Zhang, Jianli Ding, Zihan Zhang, Jinjie Wang, Xu Zeng, Xiangyu Ge

    Published 2025-06-01
    “…Taking the Wei-Ku Oasis, a typical arid region oasis, as an example, this study uses Landsat remote sensing imagery as the data source, incorporating soil salinity field measurements over a decade, employing the Bootstrap Soft Shrinkage(BOSS) algorithm to select feature variables, and building soil salinity inversion models at various depths through a Convolutional Neural Networks and Long Short-Term Memory networks (CNN-LSTM) framework. …”
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  8. 1748
  9. 1749

    Relationship of transforming growth factor β1 with diabetic retinopathy in type 2 diabetes by A.S. Hudz, V.A. Serhiyenko, I.V. Kudryl, V.G. Guryanov, M.I. Kovtun, S.V. Ziablitsev

    Published 2025-03-01
    “…Using the genetic selection algorithm, 3 features were identified that were associated with DR: diabetes compensation and TGF-β1 content in blood and IOF. …”
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    Article
  10. 1750

    Are Electromyography Data a Fingerprint for Patients with Cerebral Palsy (CP)? by Mehrdad Davoudi, Firooz Salami, Robert Reisig, Dimitrios A. Patikas, Nicholas A. Beckmann, Katharina S. Gather, Sebastian I. Wolf

    Published 2025-01-01
    “…The patients underwent at least one soft tissue surgery on their shank and foot muscles. …”
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  11. 1751

    Proposing a New Classification for Managing Prostaglandin-Induced Enophthalmos in Glaucoma Patients by Ferraro V, Gaeta A, Barone G, Confalonieri F, Tredici C, Vinciguerra P, Di Maria A

    Published 2025-07-01
    “…The underlying mechanism is believed to involve adipocyte apoptosis, altered lipid metabolism, and changes in soft tissue dynamics. Currently, there is no standardized grading for enophthalmos, complicating its management. …”
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  12. 1752

    FPGA Implementation for 24.576-Gbit/s Optical PAM4 Signal Transmission with MLP-Based Digital Pre-Distortion by Sheng Hu, Tianqi Zheng, Chengzhen Bian, Xiongwei Yang, Xinda Sun, Zonghui Zhu, Yumeng Gou, Yuanxiao Meng, Jie Zhang, Jingtao Ge, Yichen Li, Kaihui Wang

    Published 2024-12-01
    “…Lookup table (LUT) algorithms are commonly employed for pre-distortion in intensity modulation and direct detection (IM/DD) systems. …”
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  13. 1753

    Geoinformatics and Machine Learning for Shoreline Change Monitoring: A 35-Year Analysis of Coastal Erosion in the Upper Gulf of Thailand by Chakrit Chawalit, Wuttichai Boonpook, Asamaporn Sitthi, Kritanai Torsri, Daroonwan Kamthonkiat, Yumin Tan, Apised Suwansaard, Attawut Nardkulpat

    Published 2025-02-01
    “…This study analyzes 35 years (1988–2023) of shoreline changes using geoinformatics, machine learning algorithms (Random Forest, Support Vector Machine, Maximum Likelihood, Minimum Distance), and the Digital Shoreline Analysis System (DSAS). …”
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  14. 1754

    LR-FHSS Transceiver for Direct-to-Satellite IoT Communications: Design, Implementation, and Verification by Sooyeob Jung, Seongah Jeong, Jinkyu Kang, Gyeongrae Im, Sangjae Lee, Mi-Kyung Oh, Joon Gyu Ryu, Joonhyuk Kang

    Published 2025-01-01
    “…Moreover, we apply a robust synchronization scheme against the Doppler effect and co-channel interference (CCI) caused by LEO satellite channel environments, including signal detection for the simultaneous reception of numerous frequency hopping signals and an enhanced soft-output-Viterbi-algorithm (SOVA) for the header and payload receptions. …”
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  15. 1755

    Comparison of the effectiveness of various conservative treatment options for trophic ulcers and varicose eczema by E. V. Ivanov, E. P. Burleva

    Published 2021-11-01
    “…Based on the obtained data, therapeutic algorithms were proposed for the management of patients with venous TU and VE in outpatient settings.Conclusions. …”
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  16. 1756

    Two Power Allocation and Beamforming Strategies for Active IRS-aided Wireless Network via Machine Learning by Q. Cheng, J. Bai, X. Wang, B. Shi, W. Gao, F. Shu

    Published 2024-12-01
    “…BS beamforming vector and IRS phase shift matrix are obtained by Dinkelbach's transform and successive convex approximation methods. …”
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  17. 1757

    An Electrochemical Impedance Spectrum-Based State of Health Differential Indicator with Reduced Sensitivity to Measurement Errors for Lithium–Ion Batteries by Jaber Abu Qahouq

    Published 2024-10-01
    “…This supports the future development of more accurate and faster online and offline SOH estimation algorithms and systems that have a higher immunity to impedance measurement shift/offset (error). …”
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  18. 1758

    Estimation of Cement Asphalt Mortar Disengagement Degree Using Vehicle Dynamic Response by Hui Shi, Liqiang Zhu, Hongmei Shi, Zujun Yu

    Published 2019-01-01
    “…An improved genetic algorithm with a shifting window is employed for the parameter optimization, which is split into a number of phases and whose initial values are given in terms of a priori probabilities. …”
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  19. 1759

    Easy to Snack—Hard to Digest? Strategies of Dis/Array in Streaming, Social Media, and Television by Kim Carina Hebben, Christine Piepiorka

    Published 2025-04-01
    “…As a result, not only is there a shift in how content is viewed, but there is also a shift in how content is produced. …”
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  20. 1760

    Deployment of real-time particle detection monitoring system in operating theatres for airborne contamination assessments: a methodological evaluation by Frans Stålfelt, Johan Tenghamn, Henrik Malchau, Karin Svensson Malchau

    Published 2025-04-01
    “…Future research should focus on integrating predictive algorithms and machine-learning to enhance clinical utility and drive improvements in surgical safety. …”
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    Article