Srinivas Institute of Technology

Mangalore, India

Srinivas Institute of Technology

Mangalore, India

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This paper discusses the effect of Hydnocarpus wightiana methyl ester (HWME) and its blends with diesel and kerosene on performance and combustion characteristics of a single-cylinder, four-stroke diesel engine. The engine tests were conducted with HWME (B100) and its blends with diesel in proportions of 20:80 (B20), 40:60 (B40) and 60:40 (B60), and with blends of HWME, diesel, and kerosene in proportions of 20:75:5 (B20K5), 20:70:10 (B20K10), 20:65:15 (B20K15) and 40:55:5 (B40K5) at 0, 25, 50, 75 and 100% of rated load at constant engine speed (1500 rpm). Blends B20 and B20K5 have lower brake specific fuel consumption (BSFC) than other blends but are 5% and 2.9%, respectively, greater than diesel at full load. Blends B20 and B20K5 have higher brake thermal efficiency (BTE) than other blends but are 9.6% and 9%, respectively, lower than diesel at full load. At the rated engine speed of 1500 rpm, there is an increase of 26.81% and 31.15% in peak pressure with the crank angle for the B20 and B20K5 blends, respectively, from zero load to maximum load. The peak pressure values for B20, B40 and B60 were 3.21, 3.38 and 3.59%, respectively, less than diesel at full load. © 2017 Informa UK Limited, trading as Taylor & Francis Group


Shivakumar G.S.,Srinivas Institute of Technology | Natarajan S.,PESIT
ARPN Journal of Engineering and Applied Sciences | Year: 2016

This paper introduces and implements a novel object based image classification method on remote sensing images. The novelty introduced in this implementation is the application of a Multikernel Sparse Representation method on the object based image classification. The template-matching algorithm inspired from the object tracking implementation replaces the process of segmentation usually applied in object based image classification. The Multikernel fusion sparse representation based learning and prediction method is developed for remote sensing image classification. A particle filter framework for the sample template selection with the Multikernel Fusion Sparse Representation optimization technique is used to develop the image classification algorithm. The particle filter will act as the template-matching framework for our classification algorithm and the optimization of the observation model of this framework is carried out using the Multikernel Fusion Sparse Representation. Multikernel implementation has been proved to be more accurate than the feature extraction techniques since it extracts the internal intricacies of the image vector. The Kernels consume lesser memory space and lesser computational complexity compared to the traditional feature extracting methods. Multikernel Sparse representation has been proved to be more accurate and less computationally complex while implemented in other applications like the video object tracking. Affine transform based templates are extracted from the image which have to be trained and the kernel matrix is generated which is used for comparison with the templates extracted from the test images. Kernel Coordinate Descent (KCD) algorithm is used to find the similarity measure between the database kernel and the testing kernel. The weight values updated using the observation likelihood method that would indicate whether the test template matches with the database templates. The comparison is carried out with the multikernel method using the SVM classifier. The results that are observed are kappa coefficient and overall accuracy, which measure the classification accuracy, for images with higher and lower illumination and also the images are analysed for robustness to direction change and the classification performance for two different hyperspectral images. © 2006-2016 Asian Research Publishing Network (ARPN).


Ramachandra C.G.,Srinivas Institute of Technology
IEEE-International Conference on Advances in Engineering, Science and Management, ICAESM-2012 | Year: 2012

In this information age, data has become one of the most important resources to organizations. The effective and efficient management of large quantities of data is a common problem found in many industries. An effective Management Information System (MIS) supplies accurate, relevant and timely information to the manager of an organization. Decision making is an important requirement in every organization, where in different types of information obtained from different functional area of management like finance, marketing, production, personal, planning and control etc. This paper discusses the acceptance and usage of Management Information System in 50 organizations consisting of 30 small scale and 20 medium to large scale organizations. The study is exclusively based on the primary data collected through a sample survey. Main emphasis was laid to understand MIS usage and problems which hinder its use. To achieve the objective of the study, the data was collected through a structured and pretested questionnaire. The analysis reveals that only 5 out of 30 small scale organizations and as many as 16 out of 20 medium to large scale organizations are found making use of MIS for supporting decision making process. To find out the possible reasons for inadequate MIS usage in organization, the respondents were requested to provide a feedback on various factors which could be possible causes for non-use of MIS in their respective organizations. In order to increase the usage of MIS in small scale organizations, there is a need to build up computer culture by properly disseminating information about potential computer applications and the benefits thereof. Such information dissemination is required to be made through various seminars/conferences/training programs etc. This in turn, increases the usage of MIS in organizations. © 2012 Pillay Engineering College.


Bhat S.,Srinivas Institute of Technology | Meenakshi M.,Dr. AIT
2015 International Conference on Pervasive Computing: Advance Communication Technology and Application for Society, ICPC 2015 | Year: 2015

This paper presents a novel approach for human classification based on skin colour identification technique. Next the same classifier is extended for the path planning and control of autonomous robots. The techniques for obstacle identification used in this work are Skin Colour Based (SCB), Pixel Count Based (PCB), Correlation Coefficient Based (CCB) and Histogram methods. In real- time obstacle detection, the Pixel Count Based (PCB) algorithm, Correlation Coefficient Based (CCB) and Skin Colour Based (SCB) algorithm are used. In this work CCB and PCB methods compare the similarities between two objects but SCB algorithm is to identify whether the tracked object is human or nonhuman in real time. Real time experimental results demonstrated the accuracy of CCB, PCB and SCB algorithms are 87.5% and 88.8% and 90.9% respectively and the time of CCB, PCB and SCB algorithms are 6.27sec, 6.50sec and 8.67sec respectively. © 2015 IEEE.


Chandrashekhara K.G.,Srinivas Institute of Technology | Gopalakrishna Bhat N.,Srinivas Institute of Technology | Nagaraj P.,Dr Mv Shetty Institute Of Technology
Asian Journal of Chemistry | Year: 2015

A complexometric method for the determination of palladium in the presence of other metal ions based on the selective masking ability of L-Cystine towards palladium is described. Palladium(II) is complexed with excess of EDTA and the surplus EDTA is back titrated with standard lead nitrate solution at 5 to 6 pH by using hexamine and xylenol orange as an indicator. L-Cystine (0.02 M) solution is then added to release EDTA quantitatively from Pd-EDTA complex. The EDTA released is back titrated with standard lead nitrate solution as before. The method works well in the concentration range 2 to 34 mg of Pd with relative error ≤ 0.94 % and relative standard deviation ≤ 1.21 %. The method has been successfully applied to the determination of Pd in alloy composition and complexes.


Bhat S.,Srinivas Institute of Technology | Meenakshi M.,AIT Inc
2015 International Conference on Control Instrumentation Communication and Computational Technologies, ICCICCT 2015 | Year: 2015

Presently a day's need of the robot is expanding as a result of robot's effectiveness at work. The independent robot meets expectations without human intervention. Zones like military, ATM stalls, and atomic reactors so on are utilizing robots. This paper presents a novel applications based on robot in the hotel as a waiter and in military as a baggage carrier. These robots use Infrared (IR) sensor for their pathway planning in the hotel to serve the food and also for soldiers to carry their baggage in a war field. These robots are utilizing Microcontroller based Embedded System to perform the task. © 2015 IEEE.


Chandrashekhara K.G.,Srinivas Institute of Technology | Bhat N.G.,Srinivas Institute of Technology | Nagaraj P.,Drm V Shetty Institute Of Technology
Indian Journal of Chemical Technology | Year: 2015

A sensitive and selective spectrophotometric method for the determination of trace amounts of chromium(VI) directly and chromium(III) after oxidation to chromium(VI) with bromine water has been developed. Chromium(VI) oxidises hydoxylamine using acetate buffer of pH 4 to nitrite, which then diazotises sulphanilic acid to form diazonium salt. These diazonium salts are then coupled with N, N-dimethylaniline in alkaline medium resulting azo dye methyl orange, which induces orange colour in acidic medium shows an absorption maximum at 507 nm. The method is free from the interferences of several metal ions and obeys Beer’s law in the range of 0.1 to 1.8 μg/mL in acidic medium. Molar absorptivity and Sandell’s sensitivity of the system with sulphanilic acid diazoniumchloride and N,N-dimethylaniline couple(methyl orange) in acidic medium are found to be 1.74 × 104 Lmol-1 cm-1 and 3.84 × 10-3 μg/cm2 respectively. The optimum reaction condition evaluation and interference of other ions on the determination have been described. The method is useful for the analysis of chromium in soil and pharmaceutical samples. © 2015 National Institute of Science Communication and Information Resources (NISCAIR). All rights reserved.


Dsouza K.J.,Srinivas Institute of Technology | Ansari Z.A.,P.A. College
Proceedings - 2015 IEEE International Conference on Cloud Computing in Emerging Markets, CCEM 2015 | Year: 2015

Text classification, which aims to assign a document to one or more categories based on its content, is a fundamental task for Web and/or document data mining applications. In natural language processing and information extraction fields Text classification is emerging as an important part, were we can use this approach to discover useful information from large database. These approaches allow individuals to construct classifiers that have relevance for a variety of domains. Existing algorithms such as SVM Light have less GUI support and take more time to perform classification task. In this presented work classification of multi-domain documents is performed by using weka-LibSVM classifier. Here to transform collected training set and test set documents into term-document matrix (TDM), the vector space model is used. In classifier TDM is used to generate predicted results. The results emerged from weka with its GUI support using TDM have quick response time in classifying the documents. © 2015 IEEE.


Naik P.S.,Anjuman Engineering College | Orangalu S.A.,National Institute of Technology Karnataka | Londhe N.V.,Srinivas Institute of Technology
Polymer Composites | Year: 2012

This article presents the synthesis of carbon-carbon (C/C) composites by preformed yarn (PY) method, by varying the percentage of carbon fiber weight fraction. The PY used was carbon fiber bundle surrounded by coke and pitch which was enclosed in nylon-6. Three types of samples with fiber weight fractions of 30, 40, and 50%, respectively, are fabricated and mechanical properties were studied. In each case, the PY was chopped and filled into a die of required shape and hot pressed at 500°C to get the preform composite. To obtain the carbonized and graphitic structure, the specimen was heat treated at 2500°C followed by soaking for 10 to 12 hrs. Further, two cycles pitch impregnation was done by hot isostatic pressing, to eliminate the voids and to increase the density hence to obtain good mechanical properties. The characteristics such as hardness, flexural strength, and impact strengths were studied. It is observed that, as the carbon fiber percentage increases, the properties also get improved, provided sintering is done at fairly higher temperatures such as 2700°C. The superiority of the new class of C/C composites made by the proposed PY technique over those obtained by the conventional methods is also demonstrated. Copyright © 2012 Society of Plastics Engineers.


Bhat S.,Srinivas Institute of Technology | Meenakshi M.,Dr. Ambedkar I.T
Proceedings - 2014 5th International Conference on Signal and Image Processing, ICSIP 2014 | Year: 2014

This paper presents the design, development and validation of vision based autonomous robotic system for military applications. Sum of Absolute Difference (SAD) algorithm is used for the implementation of the proposed image processing algorithm. It works on the principle of image subtraction. The developed algorithm is validated in real time by change-based moving object detection method. The novelty of this work is the application of the developed autonomous robot for the detection of mines in the war field. Developed algorithm is validated both in offline using MATLAB simulation and in real time by conducting an experiment. Once the confidence of using the algorithm is increased, developed algorithm is coded into the Microcontroller based hardware and is validated in real time. Real time experimental results match well with those of the offline simulation results. However, there is only a small mismatch in distance and accuracy of the target detection, which is due to the limitations of the hardware used for the implementation. © 2014 IEEE.

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