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Institution

Vignan University

EducationGuntur, Andhra Pradesh, India
About: Vignan University is a education organization based out in Guntur, Andhra Pradesh, India. It is known for research contribution in the topics: Control theory & CMOS. The organization has 1138 authors who have published 1381 publications receiving 7798 citations.


Papers
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Journal ArticleDOI
TL;DR: The proposed method produces efficient result in sequence searching and detection and improves the hardware utilization which in terms reduces the time complexity as well.

1 citations

Journal ArticleDOI
01 Nov 2016
TL;DR: In this article, some recommendations are given on a shift of the subject teaching paradigm and its contents, which are conditioned by rather outdated common view on the role and position of this subject in the overall discipline of Mechanical Engineering, as well as in other engineering branches.
Abstract: In spite of satisfactory availability of didactical material, there exist some problems in teaching metrology that are conditioned by rather outdated common view on the role and position of this subject in the overall discipline of Mechanical Engineering, as well as in other engineering branches. In fact, in the last ten years, many changes have occurred in metrology both as a science itself and as a practical activity on measurement uniformity support. Terminology, concerning essential elements of measurement process and measurement situation, has been revised to a large extent. In the paper, certain recommendations are given on a shift of the subject teaching paradigm and its contents.

1 citations

Journal ArticleDOI
29 Dec 2020
TL;DR: Silver nanoparticles can be considered as the favourable additives to increase the surface hardness of denture base materials.
Abstract: Background: Poly (Methyl methacrylic acid) based materials are widely used for the fabrication of removable complete and partial denture prosthesis. Regular cleansing of these dentures may abrade the surface due to an inherent lack of adequate surface hardness. This roughness may adhere food to the denture surface, making it dirty and further cause stomatitis. Recently, antimicrobial activity of denture base materials incorporated with silver nanoparticles was studied, that may logically prevent microbial growth on the denture. However, the effect of these nanoparticles on the mechanical properties, which provide longevity to the prosthesis, was not substantiated. Aim: This study was designed to evaluate the effect of incorporating various concentrations of silver nanoparticles into heat-cure denture base resin materials, on their surface hardness. Materials and methods: Silver nanoparticles were incorporated at various concentrations (0.5, 1.0, 2.0 and 5.0 wt%) into three different heat-cure denture base materials. A total of 150 rectangular-shaped specimens (62 x 10 x 2.5), which comprises 50 samples from each of the three heat-cure acrylic resins were made using the compression moulding technique. Ten specimens (n=10) were allocated for each concentration such as control, 0.5wt%, 1.0wt%, 2.0wt% and 5.0wt% concentrations of silver nanoparticles. The microhardness was evaluated using the Vickers micro-hardness tester. The data were subjected to One way ANOVA and Tukey HSD tests for statistical analyses. Results: Significant differences (p=0.000) were observed between the unmodified and modified denture base materials. Conclusion: Silver nanoparticles can be considered as the favourable additives to increase the surface hardness of denture base materials.

1 citations

Journal ArticleDOI
TL;DR: In this paper, the authors distinguished the comfort properties of clothing into three categories, viz., thermo-physiological, thermal, and metabolic properties, i.e., temperature, humidity, etc.
Abstract: Comfort is an aspect and is considered as one of the important characteristics of clothing. Generally, the comfort properties can be distinguished into three categories, viz., thermo-physiological ...

1 citations

Book ChapterDOI
01 Jan 2021
TL;DR: In this paper, a QoS with optimal confederation-aware technology, i.e., QOC-RRM method, is discussed for the next-generation wireless networks.
Abstract: From the last few decades, wireless communication networks (mobile) have experienced a remarkable change to attain advancement for maintaining the systems QoS with data rate for multimedia streaming. Some extensions of these networks came to picture for a transformation into speed, technology, frequency, data capacity, latency, etc. with extreme precision levels. It gives the enhanced lifetime and network connectivity of the system. This visualization of the next-generation wireless networks is of various types of radio access technologies such as Advance LTE, WiMax, and Wi-Fi. All invention has some principles, diverse capacity, and a new technique with new features which make a distinction from the previous one. These all extended forms of wireless networks are based on the heterogeneity of the network. For achieving these said objectives, a QoS with optimal confederation-aware technology, i.e. QOC-RRM method, is discussed. Hence, this predictable expose gives an idea about an LTE network for future-generation radio resource management. Our proposed technique makes use of the QOC-RRM method. In this hybrid RDNN method, i.e. recurrent deep neural network, we present differentiate operators based on multiple constraints through priority-wise. This QOC-RRM method controls the due source through the sink or in some cases base stations. The consumer not at all practiced earlier than such high-value skill that includes the entire advancement features. This proposed work is implemented by using the Network Simulator (NS2) version 2.34 and its extension NS3 tool. The performance outcome shows that the proposed work outperforms as compared to the existing work, i.e. the conventional RRM scheme. The parameters used are the radio spectrum utilization, the utmost amount of dynamic user, and the least rate of the data required.

1 citations


Authors
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202322
202231
2021352
2020254
2019250
2018159