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RISS 인기검색어
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- 저자 : V. RAJESWARI (검색결과 4 건)
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Diagnosis of Non-invasive Glucose Monitoring by Integrating IoT and Machine Learning
V. K. R. Rajeswari Satuluri,Vijayakumar Ponnusamy 대한전자공학회 2022 IEIE Transactions on Smart Processing & Computing Vol.11 No.6
Diabetes Mellitus (DM) is a term collectively used for all types of diabetes. DM increases the risk factor for health complications if not treated early. The Internet of Things (IoT) and artificial intelligence (AI) in healthcare have become a huge benefit for managing DM. The selfsupervision of healthcare has become convenient because of IoT-enabled devices. This paper reviews the management of diabetes, such as invasive, non-invasive, and minimally invasive methods. Justification for the need for non-invasive monitoring of glucose is discussed. Different AI and IoT-enabled management for non-invasive diabetes are also briefed. This review aims at the type of machine learning algorithms applied to non-invasive glucose monitoring. The following are to be considered to achieve an effective non-invasive method of monitoring glucose: Near Infrared spectroscopy (NIR) and Machine learning algorithms(ML). IoT in glucose monitoring has empowered doctors and caretakers to deliver outstanding care. Self-care by every person has become essential, which can be achieved by handheld or wearable IoT devices. Using current technologies, the possibility of making a wearable to monitor the glucose level is becoming closer to reality and has enormous potential.
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V. RAJESWARI,T. NITHIYA The Korean Society for Computational and Applied M 2023 Journal of applied mathematics & informatics Vol.41 No.4
Nonlinear network creates complex homotopy structural communication in wireless network medium because of complex distribution approach. Due to this multicast topological connection structure, the queuing probability was non regular principles to create routing structures. To resolve this problem, we propose a Co-cluster homotopy queuing model (Co-CHQT) for Nonlinear Algebraic Topological Structure (NLTS-) for improving poison distribution network communication. Initially this collects the routing propagation based on Nonlinear Distance Theory (NLDT) to estimate the nearest neighbor network nodes undernon linear at x<sub>(a,b)</sub>→ax<sup>2</sup>+bx<sup>2</sup> = c. Then Quillen Network Decomposition Theorem (QNDT) was applied to sustain the non-regular routing propagation to create cluster path. Each cluster be form with co variance structure based on Two unicast 2(n+1)-Z2(n+1)-Z network. Based on the poison distribution theory X<sub>(a,b)</sub> ≠ µ(C), at number of distribution routing strategies weights are estimated based on node response rate. Deriving shorte;'l/st path from behavioral of the node response, Hilbert -Krylov subspace clustering estimates the Cluster Head (CH) to the routing head. This solves the approximation routing strategy from the nonlinear communication depending on Max- equivalence theory (Max-T). This proposed system improves communication to construction topological cluster based on optimized level to produce better performance in distance theory, throughput latency in non-variation delay tolerant.
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Nano-engineered concrete using recycled aggregates and nano-silica: Taguchi approach
Prusty, Rajeswari,Mukharjee, Bibhuti B.,Barai, Sudhirkumar V. Techno-Press 2015 Advances in concrete construction Vol.3 No.4
This paper investigates the influence of various mix design parameters on the characteristics of concrete containing recycled coarse aggregates and Nano-Silica using Taguchi method. The present study adopts Water-cement ratio, Recycled Coarse Aggregate (%), Maximum cement content and Nano-Silica (%) as factors with each one having three different levels. Using the above mentioned control parameters with levels an Orthogonal Array (OA) matrix experiments of L9 (34) has selected and nine number of concrete mixes has been prepared. Compressive Strength, Split Tensile Strength, Flexural Tensile Strength, Modulus of Elasticity and Non-Destructive parameters are selected as responses. Experimental results are analyzed and the optimum level for each response is predicted. Analysis of 28 days CS depicts that NS (%) is the most significant factor among all factors. Analysis of the tensile strength results indicates that the effect of control factor W/C ratio is ranked one and then NS (%) is ranked two which suggests that W/C ratio and NS (%) have more influence as compared to other two factors. However, the factor that affects the modulus of elasticity most is found to be RCA (%). Finally, validation experiments have been carried out with the optimal mixture of concrete with Nano-Silica for the desired engineering properties of recycled aggregate concrete. Moreover, the comparative study of the predicted and experimental results concludes that errors between both experimental and predicted values are within the permissible limits. This present study highlights the application of Taguchi method as an efficient tool in determining the effects of constituent materials in mix proportioning of concrete.
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