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RISS 인기검색어
- 검색키워드
- 저자 : Bharath S. Kumar (검색결과 5 건)
- 무료
- 기관 내 무료
- 유료
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Study on the effect of ties in the intermediate length Cold Formed Steel (CFS) columns
Anbarasu, M.,Kumar, S. Bharath,Sukumar, S. Techno-Press 2013 Structural Engineering and Mechanics, An Int'l Jou Vol.46 No.3
This work aims to study the effect of stiffener ties in the behavior of intermediate length open section Cold-Formed Steel (CFS) Columns under axial compression. A comparative study on the behaviour and strength of Cold Formed Steel Columns by changing the direction of projection of lips (i.e., inwards or outwards) are also done. In this work two types of sections were considered Type-I section with lip projecting outwards (hat) and Type-II section with lip projecting inwards (channel). The length of the columns is predicted by performing elastic buckling analysis using CUFSM software. The theoretical analysis is performed using DSM - S100;2007, AS/NZ: 4600-2005 and IS: 801-1975. The compression tests are carried out in a 400 kN loading frame with hinged-hinged end condition. The non-linear numerical analysis is performed using Finite Element software ANSYS 12.0 to simulate the experimental results. Extensive parametric study is carried out by varying the width and spacing of the stiffener ties. The results are compared; the effects of stiffener ties on behaviour and load carrying capacity on both types of columns are discussed.
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Study on the effect of ties in the intermediate length Cold Formed Steel (CFS) columns
M. Anbarasu,S. Bharath Kumar,S. Sukumar 국제구조공학회 2013 Structural Engineering and Mechanics, An Int'l Jou Vol.46 No.3
This work aims to study the effect of stiffener ties in the behavior of intermediate length open section Cold-Formed Steel (CFS) Columns under axial compression. A comparative study on the behaviour and strength of Cold Formed Steel Columns by changing the direction of projection of lips (i.e., inwards or outwards) are also done. In this work two types of sections were considered Type-I section with lip projecting outwards (hat) and Type-II section with lip projecting inwards (channel). The length of the columns is predicted by performing elastic buckling analysis using CUFSM software. The theoretical analysis is performed using DSM - S100;2007, AS/NZ: 4600-2005 and IS: 801-1975. The compression tests are carried out in a 400 kN loading frame with hinged-hinged end condition. The non-linear numerical analysis is performed using Finite Element software ANSYS 12.0 to simulate the experimental results. Extensive parametric study is carried out by varying the width and spacing of the stiffener ties. The results are compared; the effects of stiffener ties on behaviour and load carrying capacity on both types of columns are discussed.
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Advances and Applications of Mass Spectrometry Imaging in Neuroscience: An Overview
Bharath S. Kumar 사단법인 한국질량분석학회 2023 Mass spectrometry letters Vol.14 No.3
Understanding the chemical composition of the brain helps researchers comprehend various neurological processes effectively. Understanding of the fundamental pathological processes that underpin many neurodegenerative disorders has recently advanced thanks to the advent of innovative bioanalytical techniques that allow high sensitivity and specificity with chemical imaging at high resolution in tissues and cells. Mass spectrometry imaging [MSI] has become more common in bio- medical research to map the spatial distribution of biomolecules in situ. The technique enables complete and untargeted delinea- tion of the in-situ distribution characteristics of proteins, metabolites, lipids, and peptides. MSI's superior molecular specificity gives it a significant edge over traditional histochemical methods. Recent years have seen a significant increase in MSI, which is capable of simultaneously mapping the distribution of thousands of biomolecules in the tissue specimen at a high resolution and is otherwise beyond the scope of other molecular imaging techniques. This review aims to acquaint the reader with the MSI experimental workflow, significant recent advancements, and implementations of MSI techniques in visualizing the anatomical distribution of neurochemicals in the human brain in relation to various neurogenerative diseases.
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Analysis of Tree-shaped slotted Impedance Matching antenna for 60GHz femtocell applications
T. Shanmuganantham,K. Bharath Kumar,S. Ashok Kumar 한국통신학회 2021 ICT Express Vol.7 No.4
Femtocell access point gives an efficient solution to furnish peak data rates in indoor wireless access systems. Propagation of the signal will get up-shot because of few considerations in advanced communication appliances. The maximum simulation reflection coefficient(S) of proposed antenna is 45.12 dB, directivity is 6.54 dBi with the efficiency of 60 % and at 60 GHz, and the measurement value of 36.35 is observed which covers the complete RADAR applications which have an unlicensed bandwidth. The proposed tree-shaped unequal slotted antenna is well suited for millimeter-wave applications because of its good bandwidth and less dimension.
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Safa M.,Pandian A.,Mohammad Gouse Baig,Reddy Sadda Bharath,Kumar K. Satish,Banu A. S. Gousia,Srihari K.,Chandragandhi S. 대한전기학회 2024 Journal of Electrical Engineering & Technology Vol.19 No.4
Cardiac disease analysis in big data is an emerging factor for human health protection against heart attacks. Most cardiovascular diseases lead to heart failure due to an imbalance of immunity and attention in health conditions. Hence, immunity-based feature analysis of patients’ records is essential to predict accurate results. The machine learning methods make predictions depending on the extended-lasting features to analyze the health data. But the marginal features expose non-relational feature observation to reduce the classifi cation prediction accuracy. We propose a Deep Spectral Time-Variant Feature Analytic Model (DSTV-FAM) using SoftMax Recurrent Neural Network (SMRNN) in a wireless sensor network to improve cardiac disease prediction accuracy. Initially, the IoT sensor devices collect the data from patient observation to validate the data transmission in route propagation. The collected data is organized as features in the collective dataset. The parts are initially preprocessed into the redundant dataset and estimate the Cardiac Immunity Infl uence Rate (CIIR) depending on the time-variant feature selection model. The estimated weights are marginalized as spectral features trained into the classifi ers. Further, Soft-Max Activation Function (SMAF) creates a logical function depending on the Cardiac Aff ection Rate (CAR). Then the trained, rational neurons are constructed into a Recurrent Neural Network (RNN) Feed-forward feature values using a classifi er and Rate of Disease Aff ection (RDA) by Class Type. The proposed structure yields high prescient exactness concerning order, accuracy, and review to help early treatment for early cardiovascular gamble expectation.
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