Bapuji Institute of Engineering and Technology

Davangere, India

Bapuji Institute of Engineering and Technology

Davangere, India
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Prakash K.M.,Bapuji Institute of Engineering and Technology | Sunitha G.S.,Bapuji Institute of Engineering and Technology
2016 IEEE International Conference on Recent Trends in Electronics, Information and Communication Technology, RTEICT 2016 - Proceedings | Year: 2016

Polar coding has received a lot of consideration due to its nature of capacity achieving under various condition of coding. Low complexity is introduced by using successive cancelation decoding method. By using this large-error correction capacity is achieved for finite length of this work we propose a new approach for polar codes to achieve the better performance. Reduction of complexity is performed by reducing the number of XOR operations and the performance of the system is enhanced by using systematic polar codes. XOR operations are discarded by using path searching method, in this approach only desired path is considered others are discarded with the help of a posteriori probability. The proposed approach is implemented using MATLAB tool and the performance is achieved and compared in terms of bit error rate and frame error rate. © 2016 IEEE.

Anjaneya L.H.,Bapuji Institute of Engineering and Technology
2016 IEEE International Conference on Recent Trends in Electronics, Information and Communication Technology, RTEICT 2016 - Proceedings | Year: 2016

since last decade,the diabetes risks are increasing in children and adults. Various approaches have been proposed for early detection of the diabetes and prevention on it. Some methods use EMG signals for diabetes classification, due to motion artifacts in the EMG signals during acquisition of signal, these approaches are not able to classify the signal efficiently. To overcome this we propose anew method by considering time domain and frequency domain features of the EMG signals and to perform the classification we use neural network. This method is executed using MATLAB tool and simulation study shows the accuracy of proposed approach is 97.05%. © 2016 IEEE.

Raju G.U.,Alagappa Chettiar College of Engineering And Technology | Kumarappa S.,Bapuji Institute of Engineering and Technology
Journal of Materials and Environmental Science | Year: 2012

Increasing concern about global warming, primarily due to deforestation has led development of new materials substitute to wood, which enhances optimal utilization of natural resources. Natural fibers such as jute, flax, sisal, etc., belong to this category and are locally available in abundance. All these natural fibers have excellent physical and mechanical properties and can be utilized more effectively in the development of composite materials for various applications. This paper investigates the properties of groundnut shell particles reinforced polymer composite (GSPC). Composite samples were prepared with different weight percentages of particles in polymer matrix. These samples were tested for some physical and mechanical properties. From the results of the experiments, it has been observed that the sample A (with 20 wt% of reinforcement) has maximum MOR of 40.57MPa and sample E (60 wt% of reinforcement) has maximum MOE of 8.204 GPa. The tensile test shows sample C (40 wt %) has maximum tensile strength and young's modulus of 28.09 MPa and 8204MPa respectively. The impact test results show a steady increase in impact strength upto 50 wt % of filler addition. Moisture content of GSPC varies from 1.92 to 4.96% and water absorption was only 1.51-8.82% for 15 days.

Jayadevappa B.M.,Bapuji Institute of Engineering and Technology | Holi M.S.,Visvesvaraya Technological University
International Journal of Bioinformatics Research and Applications | Year: 2016

In the present work a simple, non-invasive and portable electrooptical based wireless real-time PPG monitoring system has been developed. The system can be used for monitoring of patient's health status specially those of disabled and suffering from cardiovascular diseases. It records variations in the volume of blood with each heart beat resulting in the form of signal called photoplethysmogram (PPG). System consists of light source and photo-detector packed in the form of probe, fitted to patient's index finger. For remote monitoring of PPG signals, a ZigBee wireless technology is used. The PPG contain rich information about cardiovascular and respiratory systems. From PPG, parameters like pulse rate (PR), average pulse rate (APR), pulse rate variability (PRV) and frequency spectrum were determined for diagnostic purpose. System monitors the patient's health conditions without restricting their movements, hence can be extended beyond hospital limits. Thus, physician can monitor the patient's health status remotely. Copyright © 2016 Inderscience Enterprises Ltd.

Jagannatha N.,SJM Institute of Technology | Hiremath S.S.,Indian Institute of Technology Madras | Sadashivappa K.,Bapuji Institute of Engineering and Technology
International Journal of Mechanical and Materials Engineering | Year: 2012

Carrier media plays a major role in removal of material in Abrasive Jet Machining (AJM). In this paper, an attempt has been made to use hot air as carrier media in AJM. Modified Taguchi robust design analysis is employed to determine optimal combination of process parameters. The Analysis Of Variance (ANOVA) is also applied to identify the most significant factor. It can be found that the air temperature is the most significant factor on Material Removal Rate (MRR) and Roughness of machined surface (Ra). It has been observed that there is good agreement between the predicted values and experimental values of optimization. The influence of temperature on MRR and Ra has been discussed. It can be found that at high temperature, there is a sufficient evidence of more plastic deformation accompanied by brittle fracture failure which results in increase of MRR and reduction of roughness.

Naik V.K.,Muscat College | Manjapp S.,Bapuji Institute of Engineering and Technology
International Journal of Environmental Research | Year: 2010

Water quality aspect with regard to dissolved oxygen was studied for a 24 kilometer stretch of Malaprabha River in Karnataka State, India. Main objective of the research was to simulate the predicted dissolved oxygen depletion due to the waste load allocation in the river with the ambient observed values of dissolved oxygen, and to ascertain the application of mathematical modeling for predicting the dissolved oxygen in a mixing zone. The entire river stretch selected for the study was divided in to four stations and water samples were collected from each station, and analyzed for different parameters. Station S1 was purely the upstream of the sewage discharge point and hence reflected the water quality of the river without pollution. Station S2 and downstream stations were the part of mixing zone where the discharged sewage at S2 kept spreading. Dissolved oxygen levels at these four stations were calculated through mathematical modeling, considering all variables that affect dissolved oxygen variation. Further, this predicted dissolved oxygen found with the application of mathematical modeling was then simulated with the actual observed values of dissolved oxygen in these four stations. The results were highly encouraging, with the predicted values almost agreeing witii the observed values. Thus the application of such mathematical modeling may be useful for a river stretch where water pollution due to the discharge of effluents is expected, and will help the engineers in arriving at a proper waste-load allocation for the river.

Raju G.U.,Alagappa Chettiar College of Engineering And Technology | Kumarappa S.,Bapuji Institute of Engineering and Technology
Journal of Reinforced Plastics and Composites | Year: 2011

In recent years, there is a growing interest in the use of bio-fibers as reinforcements for thermoplastics and thermosets. A lot of research work has been performed all over the world on the use of natural fibers such as flax, bamboo, sisal, hemp, and jute as reinforcing materials for the preparation of various types of composites. In this study, the agricultural residue such as groundnut shell particles were chemically modified and added to the polymer to form novel bio-based composites. Composite boards were fabricated by randomly distributed groundnut shell particles of different grain sizes and epoxy resin with volume percentages of 70:30, 65:35, and 60:40. The composites prepared were characterized for some mechanical properties according to ASTM standards. The highest tensile strength, tensile modulus, MOR, and impact strength were observed for the sample having groundnut shell particles and epoxy resin proportion 60:40 and 0.5 mm particle size. However, the sample with 60:40 particles and resin proportion and 1 mm particle size has maximum MOE. Moisture absorption test reveals that water absorption decreases with increase in epoxy content. The results of this study showed that composite could be successfully developed using groundnut shell particles and epoxy which would be a substitute for wood-based material in many applications. © The Author(s) 2011.

Swamy M.N.,Presidency College | Hanumanthappa M.,Bangalore University | Jyothi N.M.,Bapuji Institute of Engineering and Technology
Proceedings - 2014 International Conference on Intelligent Computing Applications, ICICA 2014 | Year: 2014

In the Constitution of India, a provision is made for each of the Indian states to choose their own official language for communicating at the state level for official purpose. The availability of constantly increasing amount of textual data of various Indian regional languages in electronic form has accelerated. So the Classification of text documents based on languages is essential. The objective of the work is the representation and categorization of Indian language text documents using text mining techniques. Several text mining techniques such as naive Bayes classifier, k-Nearest-Neighbor classifier and decision tree for text categorization have been used. © 2014 IEEE.

Uma Rani K.,Bapuji Institute of Engineering and Technology | Holi M.S.,Bapuji Institute of Engineering and Technology
IEEE EMBS Special Topic Conference on Point-of-Care (POC) Healthcare Technologies: Synergy Towards Better Global Healthcare, PHT 2013 | Year: 2013

Acoustical voice analyses and measurement methods might provide useful biomarkers for the diagnosis of neurological disordered voices. This paper presents a method for automatic detection of neurological disordered voices like Parkinson's disease, cerebellar demyelination and stroke using the Mel-frequency cepstral coefficient (MFCC) features. The features extracted were given to a multilayer neural network and trained to classify whether the voice was neurological disordered or normal subject. There are no risks involved in capturing and analysis of voice signals as it is noninvasive by nature and in carefully controlled circumstances, it can provide a large amount of meaningful data. The data collected in the present work consist of 137 sustained vowel phonations (/ah/), among them 73 phonations are from patients suffering from different neurological diseases and 64 phonations from controlled subjects including both male and female subjects. Thirteen MFCC features are used as input to the optimally designed artificial neural network (ANN) for classification. 112 phonations were used to train the network and 25 phonations for testing. The best classification accuracy achieved was 92%. © 2013 IEEE.

Swamy M.S.M.,Bapuji Institute of Engineering and Technology | Holi M.S.,Bapuji Institute of Engineering and Technology
Lecture Notes in Electrical Engineering | Year: 2013

Knee is a complex and highly stressed joint of the human body. Articular cartilage is a smooth hyaline spongy material between the tibia and femur bones of knee joint. The change in cartilage morphology is an important biomarker to study the progression of osteoarthritis (OA). Magnetic resonance imaging (MRI) is the modality widely used to image the knee joint because of its non ionization effect and soft tissue contrast. In the present work a semiautomatic algorithm is developed for segmentation of articular cartilage from knee MR images. Segmented cartilage is visualized in 2D and 3D. Cartilage thickness is measured in different regions of femur and total volume of the cartilage is computed from the sequence of MR images. The cartilage thickness measurement and visualization is of diagnostic use for early detection and assessment of progression of the disease in case of OA affected patients. © 2013 Springer.

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