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Kongu Engineering College

About: Kongu Engineering College is a based out in . It is known for research contribution in the topics: Cluster analysis & Control theory. The organization has 2001 authors who have published 1978 publications receiving 16923 citations.


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Journal ArticleDOI
TL;DR: In this paper, a simple and exhaustive search procedure for the synthesis and analysis of CMOS common gate (CG) and Inductively Degenerated Common Source (CS) LNA circuits is presented.
Abstract: The Low Noise Amplifier (LNA) is the first stage in RF CMOS receivers. The Common Gate (CG) LNA and Inductively Degenerated Common Source (CS) LNA are one of the widely used topologies for realizing RF CMOS receivers. The present work emphasizes a simple and exhaustive search procedure for the synthesis and analysis of CMOS CG and Inductively Degenerated CS LNA circuits. The width (W), gate source voltage ( $$ V_{gs} $$ ) and drain source voltage ( $$ V_{ds} $$ ) of the transistors constitute the design space in the circuit design. The design first involves the use of a circuit simulator (HSPICE) to obtain the small signal parameters of the circuit for various W, $$ V_{gs}$$ , and $$ V_{ds} $$ of the transistors and then to generate a Look-Up Table (LUT) for all design points using the obtained values. This LUT is used to meet the target performance specifications along with appropriate analytical expressions derived from the circuit in a numerical simulator (MATLAB). This will enable one to explore the whole design space quickly and fastly for arriving at the optimal values for the device dimensions, bias voltages and bias currents of the two LNA circuits. The design methodology is demonstrated by designing CG and Inductively Degenerated CS LNA circuits using 90 nm CMOS technology library in which Inductively Degenerated CS LNA gets high gain and low noise figure than CG LNA.

8 citations

Journal ArticleDOI
TL;DR: In this paper, the authors tried an effort to correlate drilling induced damage with drilling parameters during drilling on the Sisalglass/vinyl ester hybrid composites and found that the delamination can be effectively reduced in drilling of sisal-glass fiber composite materials by applying the lower feed rate values.
Abstract: Drilling of holes in the assembly of structural frames of automobile and aircrafts are inevitable in order to make joining of parts. The drilling induced damage imparts reduced life and efficiency of parts. The present study attempts an effort to correlate drilling induced damage with drilling parameters during drilling on the Sisal-glass/vinyl ester hybrid composites. Diameter of drill, speed and feed rate were considered as significant factors and they control or minimise the drilling induced damages. Experiments were conducted under various cutting conditions as per design of experiments. Mathematical models for thrust force, torque and delamination factor were developed using non-linear regression equations. Optimisations of controlling parameters were done using Nelder-Mead simplex search method and central composite face centred design (CCFD). Analysis of variance (ANOVA) was used to study the effect of process parameters on drilling responses. The results revealed that the delamination can be effectively reduced in drilling of sisal-glass fibre composite materials by applying the lower feed rate values.

8 citations

Journal ArticleDOI
01 Jan 2012
TL;DR: This paper detects online hotspot forums by computing sentiment analysis for text data available in each forum by combining K-means clustering and Support Vector Machine (SVM) classification algorithm that can be used to group the forums into two clusters forming hotspot Forums and non-hotspot forums within the current time span.
Abstract: The user generated content on the web grows rapidly in this emergent information age. The evolutionary changes in technology make use of such information to capture only the user’s essence and finally the useful information are exposed to information seekers. Most of the existing research on text information processing, focuses in the factual domain rather than the opinion domain. Text mining plays a vital role in online forum opinion mining. But opinion mining from online forum is much more difficult than pure text process due to their semi structured characteristics. In this paper we detect online hotspot forums by computing sentiment analysis for text data available in each forum. This approach analyzes the forum text data and computes value for each piece of text. The proposed approach combines K-means clustering and Support Vector Machine (SVM) classification algorithm that can be used to group the forums into two clusters forming hotspot forums and non-hotspot forums within the current time span. The experiment helps to identify that K-means and SVM together achieve highly consistent results. The prediction result of SVM is also compared with other classifiers such as Naïve Bayes, Decision tree and among them SVM performs the best.

8 citations

Proceedings ArticleDOI
08 Jul 2014
TL;DR: In this article, the main objective of the study was to identify alternative source of good quality fine aggregates which is depleting very fast due to the fast pace of construction activities in India.
Abstract: The main objective of this study was to identify alternative source of good quality fine aggregates which is depleting very fast due to the fast pace of construction activities in India. Use of slag sand is a waste material of copper production and fly ash is a waste material of power plants provides great opportunity to utilize it as an alternative to normally available aggregates and cement. For this research work, M35 grade concrete was used and tests were conducted for various proportions of copper slag replacement with sand of 0 to 100% and fly ash replacement with cement of 0 to 30 % . The fine aggregate was replaced with copper slag as proportions of 0 % , 10%, 20%, 30%, 40%, 50%, 60%, 80%, and 100% and cement was replaced with fly ash as proportions of 30% in OPC 53 grade cement. Concrete mixtures are evaluated for workability, Ultrasonic pulse velocity test and water absorption test. The obtained result was compared with those of control concrete made with Ordinary Portland Cement (OPC).

8 citations

DOI
01 Mar 2022
TL;DR: In this paper, the use of nano-silica and polypropylene fiber in problematic clay-ey soil to enhance the shear strength and compaction characteristics was investigated, and it was observed that the diameter of nanoparticles used in this study was in the range of 10-20nm.
Abstract: The current study presents the laboratory investigation on the use of nano-silica (0.2, 0.4, 0.8 and 1.0%) and polypropylene fiber (0.25, 0.50, 0.75 and 1.0%) in problematic clayey soil to enhance the shear strength and compaction characteristics. From the Transmission electron microscopy (TEM) analysis, it is observed that the diameter of nano-particles used in this study was in the range of 10–20 nm. The nano-particles have a spherical shape and amorphous in nature. Extensive laboratory tests such as the standard Proctor compaction test and unconfined compressive strength test have been conducted on untreated and polypropylene fiber along with nano-silica treated clayey soil. The outcomes showed that the addition of polypropylene fiber in poor soil, increase the maximum dry density and reduce the optimum moisture content of the soil. Whereas, the addition of nano-silica to the clay soil results in reduced maximum dry density and increased optimum moisture content. Unconfined compressive strength of clay soil is increased with the addition of polypropylene fiber and nano-silica to the clay soil. The optimum dosage of polypropylene fiber and nano-silica added to the poor soil was 0.75% and 0.8%, respectively. The Young’s modulus of clay soil was increased with the addition of polypropylene fiber and nano-silica. The microscopic analysis confirmed that C–S–H gel was the main cementitious product, and the inclusion of nano-silica can contribute to a denser packing of soil particles.

8 citations


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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202221
2021572
2020234
2019121
2018143
2017136