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Smart Healthcare Activity Recognition Using Statistical Regression and Intelligent Learning

Computers, Materials & Continua 2024年第1期78卷 1189-1205页

作者： k.akilandeswari Nithya Rekha Sivakumar Hend khalid Alkahtani Shakila Basheer Sara Abdelwahab Ghorashi Department of Computer Sciences Government Arts College(Autonomous)Salem636007India Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia

In this present time,Human Activity Recognition(HAR)has been of considerable aid in the case of health monitoring and *** exploitation of machine learning with an intelligent agent in the area of health informatics gathered using HAR augments the decision-making quality and *** many research works conducted on Smart Healthcare Monitoring,there remain a certain number of pitfalls such as time,overhead,and falsification involved during ***,this paper proposes a Statistical Partial Regression and Support Vector Intelligent Agent Learning(SPR-SVIAL)for Smart Healthcare *** first,the Statistical Partial Regression Feature Extraction model is used for data preprocessing along with the dimensionality-reduced features extraction ***,the input dataset the continuous beat-to-beat heart data,triaxial accelerometer data,and psychological characteristics were acquired from IoT wearable *** attain highly accurate Smart Healthcare Monitoring with less time,Partial Least Square helps extract the dimensionality-reduced *** that,with these resulting features,SVIAL is proposed for Smart Healthcare Monitoring with the help of Machine Learning and Intelligent Agents to minimize both analysis falsification and *** evaluation is carried out for factors such as time,overhead,and false positive rate accuracy concerning several *** quantitatively analyzed results indicate the better performance of our proposed SPR-SVIAL method when compared with two state-of-the-art methods.

关键词： Internet of Things smart health care monitoring human activity recognition intelligent agent learning statistical partial regression support vector

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Analysis of Cognitive Radio for LTE and 5G Waveforms

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Computer Systems Science & Engineering 2022年第12期43卷 1207-1217页

作者： Ramesh Ramamoorthy Himanshu Sharma A.akilandeswari Nidhi Gour Arun kumar Mehedi Masud Centre for Artificial Intelligence Chennai Institute of TechnologyChennaiIndia Department of Computer Science and Engineering JECRC UniversityJaipur303905India Institute of ECE Saveetha School of EngineeringChennaiIndia Department of Electronics and Communication Engineering JECRC UniversityJaipur303905India Department of Computer Science College of Computers and Information TechnologyTaif University11099Saudi Arabia

Spectrum sensing is one of the major concerns in reaching an efficientQuality of service (QOS) in the advanced mobile communication system. Theadvanced engineering sciences such as 5G, device 2 device communications(D2D), Internet of things (IoT), MIMO require a large spectrum for better *** frequency division multiplexing (OFDM) is not a choice in advancedradio due to the Cyclic Prefix (CP), wastage of the spectrum, and so on. Hence, itis important to explore the spectral efficient advanced waveform techniques andcombine a cognitive radio (CR) with the 5G waveform to sense the idle spectrum,which overcomes the spectrum issue. The demand for spectrum is ever increasing;however, spectrum is limited and is an acutely scarce resource. To alleviate theissue, techniques like Cognitive Radios (CR) have been devised. However, suchtechniques are non-standardized, and many variations of CR algorithms have beentried and tested. This paper details the several spectrum sensing methods tailoredfor CR. We explain the benefits, uniqueness, and drawbacks of the various techniques to provide a comprehensive review of the scene, including all recent andnovel techniques of CR. Finally, we provided experimental results for the performance of the CR for key 5G and beyond modulation techniques to elaborate thedependency of the CR techniques for CR applications and provide a competitivereview of their performance. Experiments show that the CR integrated withNOMA shows better performance as compared with existing techniques.

关键词： CR Energy detection FBMC NOMA OFDM

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Synthesis, Growth and Characterization of Nonlinear Optical Single Crystal of Serine Succinate

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Journal of Minerals and Materials Characterization and Engineering 2021年第1期9卷 75-89页

作者： S. akilandeswari L. Jothi Department of Physics Namakkal Kavignar Ramalingam Government Arts College for Women Namakkal India Periyar University Salem Tamilnadu India

Nonlinear optical single crystal of Serine Succinate (SSA) was grown from a mixed solvent of water, ethanol and methanol. Since amino acid exhibits nonlinear optical property, it is of interest to dope them in serine. The overwhelming success of molecular engineering in controlling nonlinear optical properties in last decade has prompted better initiative in crystal engineering. In the present study single crystals of serine doped with succinic acid in different ratios have been grown by slow evaporation solution growth method. Grown serine succinate crystals were subjected to various characterization techniques. The cell parameters of the grown crystals were characterized by X-ray diffraction analysis. FT-Raman spectral studies were carried out on the SAA grown material to confirm the synthesized compound and the functional groups of serine succinate single crystal were identified from FTIR analysis. The optical transparency and upper cut off value of UV transmission spectrum of SSA crystal were recorded. Fluorescence study was also carried out for the grown materials. The mechanical hardness was estimated by Vickers’s micro hardness tester. The second harmonic generation (SHG) of the grown crystal was confirmed by kurtz powder technique. Thermal properties of serine succinate crystal were evaluated with thermogravimetric, differential thermal and differential scanning calorimetric analyses. The SEM studies were also reported.

关键词： Crystal Growth Slow Evaporation Technique Thermo Gravimetric Analysis

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Synthesis, Growth and Characterization of Nonlinear Optical Single Crystal of Serine Succinate

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Journal of Minerals and Materials Characterization and Engineering 2021年第1期

作者： S. akilandeswari L. Jothi

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