Sambhram Institute of Technology

Bangalore, India

Sambhram Institute of Technology

Bangalore, India
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Phanibhushana M.V.,Amrita University | Chandrappa C.N.,Acharya Institute of Technology | Niranjan H.B.,Sambhram Institute of Technology
Materials Today: Proceedings | Year: 2017

Metal Matrix Composites (MMCs) are used in aerospace, transport, automotive, marine engineering due to their light weight with improved strength, stiffness and wear resistance. Wear is one of the reasons for the failure of the machine components. It is difficult to accurately predict the life of components due to wear, because, generally the wear rates are largely scattered. An attempt is made to study the Wear characteristics of Hematite (Fe2O3) reinforced Aluminum 6061 Metal Matrix Composites. The reinforcement is added in particulate form of 40-45 μm with an increment of 2% from 0% to 8% (by weight). Composites are fabricated by liquid metallurgy technique. The Microstructural study on as cast Al6061-Fe2O3 compositesreveals uniform distribution of reinforcement particles. The wear test was conducted on the specimens by varying speed from 200 - 400 rpm & load from 50 - 100 N. The wear rate was measured by the weight loss of the specimen. The results show that there is an increase in the wear resistance with increase in percentage of reinforcement. The wear factor has decreased 30 - 40% at 8% of reinforcement as compared to base matrix material. © 2017 Elsevier Ltd. All rights reserved.


Phanibhushana M.V.,Mrita Vishwa Vidyapeetham | Chandrappa C.N.,Acharya Institute of Technology | Niranjan H.B.,Sambhram Institute of Technology
Materials Today: Proceedings | Year: 2017

Metal Matrix Composites (MMCs) are used in aerospace, transport, automotive, marine engineering due to their light weight with improved strength, stiffness and wear resistance. Wear is one of the reasons for the failure of the machine components. It is difficult to accurately predict the life of components due to wear, because, generally the wear rates are largely scattered. An attempt is made to study the Wear characteristics of Hematite (Fe2O3) reinforced Aluminum 6061 Metal Matrix Composites. The reinforcement is added in particulate form of 40-45 μm with an increment of 2% from 0% to 8% (by weight). Composites are fabricated by liquid metallurgy technique. The Microstructural study on as cast Al6061-Fe2O3 compositesreveals uniform distribution of reinforcement particles. The wear test was conducted on the specimens by varying speed from 200 - 400 rpm & load from 50 - 100 N. The wear rate was measured by the weight loss of the specimen. The results show that there is an increase in the wear resistance with increase in percentage of reinforcement. The wear factor has decreased 30 - 40% at 8% of reinforcement as compared to base matrix material. © 2017 Elsevier Ltd. All rights reserved.


Shidaganti G.I.,Sambhram Institute of Technology
Proceedings of the 2013 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2013 | Year: 2013

Various prominent feature points of human faces play a critical role for designing a system that can perform facial recognition. Involvement of facial expression as precision parameter exponentially increases the challenges in developing a face recognition system. There exist abundant volume of studies in the area of face recognition, but majority of the techniques are either computationally not viable or uses complex algorithms. Hence, the prime aim of this paper is to introduce a very simple and cost effective solution for face recognition system from facial expressions by using two techniques i.e. Singular Value Decomposition (SVD) and Rational Value Sequence based Singular Value Decomposition (RSVD). Results were evaluated for both the cases to find RSVD approach as a better alternative to SVD approach for face recognition in terms of preciseness and computational effectiveness. © 2013 IEEE.


Arumugam M.,Sambhram Institute of Technology | Sangaiah A.K.,Vellore Institute of Technology
IIOAB Journal | Year: 2015

The first and foremost step in the analysis of ECG for various cardiac disease is the extraction of ECG and classification of ECG based on feature extraction. The prediction of any cardiac disease will come correctly if the feature extraction and classification of ECG are correct. It is very difficult for any expert physicians to predict exactly the cardiac arrhythmia as the volume of data is huge. The monitoring of ECG signals for a long period of time is needed as the changes in ECG may occur at any fraction of time. The computer aided approach helps significantly for monitoring ECG signals for long period of time. Many methods like wavelet transform, Independent Component analysis (ICA), Permanent Component analysis (PCA), Time Domain, Wavelet Transform, Power Spectral Density and Fuzzy logic with Neural network techniques are used either separately or in combination by the Researchers for extracting features from ECG signal. It is found from this survey that among many classifiers, most of the research works uses SVM classifier as it gives high classification accuracy. It is also found from this survey that most of research work uses the ECG data from MIT-BIH database or from Physionet. The parameters which determines the suitable technique for feature extraction and classification are found to be classification accuracy, sensitivity and specificity. This paper presents a survey of various approaches used in the feature extraction and classification of ECG signals. © 2015, Institute of Integrative Omics and Applied Biotechnology. All rights reserved.


Basu R.,Sambhram Institute of Technology | Padage S.,Sambhram Institute of Technology
Materials Today: Proceedings | Year: 2017

Economy of motion in robots assembly lines, microelectronics, medical and space applications has not received much attention. It is however, as challenging and important as efficiency and ergonomics is to human beings in the factory workplace. Production lines with humans are prone to human fatigue. Hence robotic units are replacing human sorters for production line work. Mechanised operations are usually limited to batch processes with identical items taken from a conveyor belt and placed in a bin or stack. A further extension is to use AI programs to enable discrimination of objects and sorting into separate bins or stacks. In the present study a 5 d.o.f. arm kit was assembled by students and used to understand simple robotic concepts like degree of freedom, gripper action, pick and place, palletisation and other topics in a lab syllabus together with online simulators where factory robots are simulated. Basic algorithms are explored by testing with the 5 dof Puma arm. The addition of tactile and visual interfaces for pick and sort are discussed. Sample outputs are illustrated. © 2017 Elsevier Ltd.


Ghosh D.,Indian Institute of Technology Roorkee | Dube T.,Indian Institute of Management Ahmedabad | Shivaprasad A.,Sambhram Institute of Technology
IEEE Transactions on Pattern Analysis and Machine Intelligence | Year: 2010

A variety of different scripts are used in writing languages throughout the world. In a multiscript, multilingual environment, it is essential to know the script used in writing a document before an appropriate character recognition and document analysis algorithm can be chosen. In view of this, several methods for automatic script identification have been developed so far. They mainly belong to two broad categoriesstructure-based and visual-appearance-based techniques. This survey report gives an overview of the different script identification methodologies under each of these categories. Methods for script identification in online data and video-texts are also presented. It is noted that the research in this field is relatively thin and still more research is to be done, particularly in the case of handwritten documents. © 2010 IEEE.


Arakeri M.P.,M.S. Ramaiah Institute of Technology | Lakshmana,Sambhram Institute of Technology
Procedia Computer Science | Year: 2016

Agriculture sector plays a key role in the economic development of India. The task of fruit grading is vital in the agricultural industry because there is a great demand for high quality fruits in the market. However, fruit grading by human is inefficient, labor intensive and prone to error. The automated grading system not only speeds up the time of processing, but also minimizes error. There is a great demand for tomatoes in both local and foreign markets. The tomato fruit is very delicate and hence careful handling of this fruit is required during grading. Thus, this paper proposes an automatic and effective tomato fruit grading system based on computer vision techniques. The proposed quality evaluation method consists of two phases: development of hardware and software. The hardware is developed to capture the image of the tomato and move the fruit to the appropriate bins without manual intervention. The software is developed using image processing techniques to analyze the fruit for defects and ripeness. Experiments were carried out on several images of the tomato fruit. It was observed that the proposed method was successful with 96.47% accuracy in evaluating the quality of the tomato. © 2016 The Authors.


Manjunatha B.,Acharya Institute of Technology | Niranjan H.B.,Sambhram Institute of Technology | Satyanarayana K.G.,Poornaprajna Institute of Scientific Research PPISR
Materials Science and Engineering A | Year: 2015

Metal Matrix Composites (MMC) considered as one of the 'advanced materials' have evoked growing interest during the last three decades due to their high performance and applications in strategic sectors. These composites exhibit unique and attractive properties over the monolithic alloys, but suffer from low ductility, which makes them not so attractive for some of the applications where high toughness is one of the design criteria. This limitation of MMCs has been overcome by resorting to various treatments such as mechanical and thermal loading. Considering very limited reports available on Al alloy reinforced with boron carbide (B4C) particles, this paper presents (i) preparation of Al-6061 alloy reinforced with 1.5-10wt% B4C, (ii) subjecting them to mechanical and thermal treatments and (iii) characterization of all the above samples. Specific ultimate tensile strength and hardness of all the composites were higher than those of matrix. Also, these values increased with increasing amount of particles, with composites containing 8wt% B4C showing the maximum values in all the three conditions. These observations are supported by the uniform distribution of particles in the matrix as observed in their microstructure. © 2015 Elsevier B.V.


Prabhakar M.,Sambhram Institute of Technology | Singh J.N.,Sambhram Institute of Technology | Mahadevan G.,Amc Engg College
2013 International Conference on Computer Communication and Informatics, ICCCI 2013 | Year: 2013

The communications in VANET consists of roadside units (RSUs) linked to each other or even to the Internet. In the recent vehicular approach, VANETs security properties have received more attention in research community. We improve the game theoretic approaches for the application cases having scenarios with few known opponents and others with opponent uncertainty. In this work, we plan to introduce a defensive mechanism for the VANET security with heuristic based ant colony optimization. The heuristic based ant model, worked with known opponents and unknown opponents based on the density of pheromone deposited in the road network path with new road path exploration with traversal of ants. Then the Nash equilibrium is applied with the game theoretic framework to identify the stability state of the players involved in it. Optimal exploitation of traffic organizes and security framework is investigated both in the static (e.g., preset roadside units) and active cases (e.g., mobile law enforcement units). An experimental evaluation is carried out to evaluate the performance of the proposed defensive mechanism in game theoretic approach using heuristic based ant colony optimization [DMGTA] for VANET security. © 2013 IEEE.


Maheswari A.,Sambhram Institute of Technology | Sangaiah A.K.,Vellore Institute of Technology
Advances in Intelligent Systems and Computing | Year: 2015

Premature death and disability from sudden cardiac arrest continue to be a serious public health burden. Electrocardiography (ECG) is a ubiquitous vital sign health monitoring method used in the healthcare systems. The early detection of abnormality in ECG signal for cardiac disease leads to timely diagnosis and prevents the person from death. Normally the surgeons have to study a large amount of ECG data to search for abnormal beat in ECG. If the surgeons fail to note the abnormal cycles that are very less in number, it leads to fatigue. In the proposed research work, an intelligent ECG digital system is designed to interpret these abnormal signals which reduce the tedious work of interpreting ECG. The proposed work monitors the heart beat continuously in a convenient manner and with maximum accuracy for diagnosing. The ECG signals are acquired in real time and amplified through an Instrumentation amplifier. The resulting signals are processed for the cancellation of noise through a low pass filter and notch filter. Further processing of these signals in the microcontroller detects the abnormalities of cardiac arrest. The result is communicated through GSM which reduces the burden of the doctors to a greater extent. These signals are stored in the Secure Data (SD) card to have a complete history of the signals before and after the occurrence of the cardiac event. The proposed research work combines the capabilities of real-time monitoring of ECG signals and the abnormal symptom-reporting systems. © Springer International Publishing Switzerland 2015.

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