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Co-Authors
- P. C. Nissimagoudar
- Venkatesh R. Mane
- Nalini C. Iyer
- M. R. Kiran
- K. M. Uma
- A. B. Raju
- Anisha W. Joseph
- K. Hemanthraj
- B. L. Desai
- Ashok Shettar
- C. D. Kerur
- Venkatesh Mane
- Sanjay Eligar
- Anil Badiger
- Anisha Joseph
- Suneel Kumar Duvvuri
- Singh Kumar Rakesh
- Patel Singh Pankaj
- Gupta Pragya
- M. Jayakameswaraiah
- R. Pinakapani
- Ravi Dandu
Journals
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Ramakrishna, S.
- A Virtual Industry Platform for Course Projects in Automotive Electronics : A Case Study
Abstract Views :298 |
PDF Views:0
Authors
P. C. Nissimagoudar
1,
Venkatesh R. Mane
1,
Nalini C. Iyer
1,
S. Ramakrishna
1,
M. R. Kiran
1,
K. M. Uma
1,
A. B. Raju
1,
Anisha W. Joseph
1,
K. Hemanthraj
1,
B. L. Desai
1,
Ashok Shettar
1
Affiliations
1 B.V. Bhoomaraddi College of Engineering and Technology, Hubli, IN
1 B.V. Bhoomaraddi College of Engineering and Technology, Hubli, IN
Source
Journal of Engineering Education Transformations, Vol 28, No 2&3 (2015), Pagination: 145-152Abstract
This paper presents the details of hands on course instruction attempted for the undergraduate programme for automotive electronics course in electrical sciences using virtual industry platform. The design of an Electronic Control Unit for an integrated engine and safety management system developed as part of course project on Automotive Electronics at the undergraduate level in Engineering in the multidisciplinary electrical sciences is proposed. The paper also proposes a course delivery mechanism model based on learn-by-doing approach to incorporate a practical hands-on on the design and validation of automotive control systems to enhance the specifi c learning outcome during the course delivery. The details of a virtual industry platform adopted for the course delivery to impart a team level project delivery and management experience to both the students and the faculty are presented.Keywords
Automotive Electronics, Course Projects, Integrated Experience, Project Managers, Requirement Document, Sub-Module Design.- An Effective Industry Institute Engagement for Curriculum Design and Delivery:A Success Story
Abstract Views :244 |
PDF Views:2
Authors
Ashok Shettar
1,
B. L. Desai
1,
Nalini C. Iyer
1,
K. M. Uma
1,
A. B. Raju
1,
C. D. Kerur
1,
P. C. Nissimagoudar
1,
Venkatesh Mane
1,
S. Ramakrishna
1,
M. R. Kiran
1,
Sanjay Eligar
1,
Anil Badiger
1,
Anisha Joseph
1
Affiliations
1 B.V. Bhoomaraddi College of Engineering and Technology, Hubli, IN
1 B.V. Bhoomaraddi College of Engineering and Technology, Hubli, IN
Source
Journal of Engineering Education Transformations, Vol 29, No 1 (2015), Pagination: 85-90Abstract
This paper presents details of an industry institute engagement evolved for effectively bridging the gaps & creating readily deployable manpower with the requisite talent and skill set for the automotive industry. The success story presented brings out the details of conceptualization, curriculum design and course delivery model for an interdisciplinary course on automotive electronics at the under graduate engineering program in electrical sciences. Issues of very strong involvement of the industry at different levels of the engagement, including the commitment of the top Management from both sides, and the dedication of the teams involved are discussed. How the faculty from the electronics background have worked together with the faculty from the automobile background to make this successful are brought out. The significant outcomes of this initiative in terms of learning takeaways, improvement in job readiness of the graduates and influence on research initiatives in various relevant domains are presented.Keywords
Industry-Institute Interaction, Automotive Electronics, Course Design, Industry-Specific Skills.- Adaptive Neuro-Fuzzy Inference System Based On-Demand Fault Tolerant Routing Protocol (ANFIS-ODFTR) for MANETs
Abstract Views :265 |
PDF Views:1
Authors
Affiliations
1 Department of Computer Science, Government College (Autonomous), Rajahmundry, Andhra Pradesh, IN
2 Department of Computer Science, S V University, Tirupati, Andhra Pradesh, IN
1 Department of Computer Science, Government College (Autonomous), Rajahmundry, Andhra Pradesh, IN
2 Department of Computer Science, S V University, Tirupati, Andhra Pradesh, IN
Source
International Journal of Computer Networks and Applications, Vol 8, No 6 (2021), Pagination: 719-729Abstract
Due to adverse characteristics such as open medium, recurrent restructuring of paths, power constraints, and high mobility of MANETs, the nodes and links failed frequently. These failures increase the control overhead because of the tedious route discovery process. Thereby the performance of the network diminished drastically. Devising an efficient on-demand routing protocol with fault tolerance is a challenging task. Detecting and removal of these faulty nodes during data transmission without affecting the communication flow is very critical because of the unavailability of path information. The research challenge of designing the effective fault tolerant routing protocol for MANET is addressed in this study. An Adaptive Neuro-Fuzzy Inference System was utilized to create a fault-tolerant routing system. The fault tolerant routing protocols based on numerical estimation are discussed. Simulation results have attested that the suggested approach considerably boosts the Packet Delivery Ratio while lowering the Routing Overhead.Keywords
MANET, Fuzzy Inference System, ANFIS, Hybrid Neural Network, ANN, Fault Tolerance, AODV, RSSI.References
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- Almazok, S.A., Bilgehan, B. A novel dynamic source routing (DSR) protocol based on minimum execution time scheduling and moth flame optimization (MET-MFO). J Wireless Com Network 2020, 219 (2020). https://doi.org/10.1186/s13638-020-01802-5
- Hussain, Salim. (2011). Effect of Mobility Model on the Performance of DSDV Protocol in MANET.
- Thakrar, Payal and Singh, Vijander and Kotecha, Ketan, Study of Routing Limitation of OLSR Protocol in Mobile Ad Hoc Networks (October 18, 2019). Proceedings of International Conference on Advancements in Computing & Management (ICACM) 2019
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- Çaydaş, Ulaş & Hasçalık, Ahmet & Ekici, Sami. (2009). An adaptive neuro-fuzzy inference system (ANFIS) model for wire-EDM. Expert Systems with Applications. 36. 6135-6139. 10.1016/j.eswa.2008.07.019.
- A. Sarfaraz Ahmed, T. Senthil Kumaran, S. Syed Abdul Syed, S. Subburam, Cross-Layer Design Approach for Power Control in Mobile Ad Hoc Networks, Egyptian Informatics Journal,Volume 16, Issue 1,2015,Pages 1-7,ISSN 1110-8665,https://doi.org/10.1016/j.eij.2014.11.001.
- H. Zhong and T. Zhou, "Research and Implementation of AOMDV Multipath Routing Protocol," 2018 Chinese Automation Congress (CAC), 2018, pp. 611-616, doi: 10.1109/CAC.2018.8623785.
- Nisha Chaudhary, Er Shiv Kumar Goel, Nitin Goel (2015). A Deep Analysis: Highly Robust Fault Tolerant Secure Optimized Energy Ad-hoc Networks Methodologies for Mobile Nodes. International Journal of Advanced Research in Computer Science and Software Engineering, 5(7), pp.540-543
- Ravichandra and Chandrasekar Reddy (2016). Fault tolerant QoS Routing Protocol for MANETs. IEEE International Conference on Advanced Computing, pp.34-45.
- Senthilnathan Palaniappan and Kalaiarasan Chellan (2015). Energy-efficient stable routing using QoS monitoring agents in MANET. EURASIP Journal on Wireless Communications and Networking, 13(1), pp.1-11.
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- M.S. Gaur, Swati Todi, Vijay Rao, Meenakshi Tripathi, Riti Kushwaha (2017). Multi-constraints Link Stable Multicast Routing Protocol in MANETs, Ad Hoc Networks, DOI: 10.1016/j.adhoc.2017.05.007.
- Gopal Singh, Deepak Saini, Rahul Rishi, Harish Rohil, “Role of Link expiration time to make reliable link between the nodes in MANETs: A Review “International Journal of Applied Engineering Research ISSN 0973- 4562 Volume 11, Number 7 2016.
- K. Sakthidasan Sankaran, N. Vasudevan, K. R. Devabalaji, T. S. Babu, H. H. Alhelou and T. Yuvaraj, "A Recurrent Reward Based Learning Technique for Secure Neighbor Selection in Mobile AD-HOC Networks," in IEEE Access, doi: 10.1109/ACCESS.2021.3055422.
- Xin Ming Zhang, Member, IEEE, En Bo Wang, Jing Jing Xia, and Dan Keun Sung, Senior Member, IEEE, “An Estimated Distance-Based Routing Protocol for Mobile Ad hoc Networks ” IEEE Transactions on Vehicular Technology, VOL. 60, NO. 7, SEPTEMBER 2011.
- B. H. Khudayer, M. Anbar, S. M. Hanshi and T. Wan, "Efficient Route Discovery and Link Failure Detection Mechanisms for Source Routing Protocol in Mobile Ad-Hoc Networks," in IEEE Access, vol. 8, pp. 24019- 24032, 2020, doi: 10.1109/ACCESS.2020.2970279.
- A. Bhardwaj and H. El-Ocla, "Multipath Routing Protocol Using Genetic Algorithm in Mobile Ad Hoc Networks," in IEEE Access, vol. 8, pp. 177534-177548, 2020, doi: 10.1109/ACCESS.2020.3027043.
- Sudip Misra et al., “A learning automata-based fault tolerant routing algorithm for mobile ad hoc networks”, Journal of Super compt(2012) 62:4–23 [20] J.S.R. Jang, and C.T. Sun, “Neuro-Fuzzy Modeling and Control,” Proc. IEEE, vol. 83, no. 3, pp. 378-406, Mar. 1995.
- A. Al-Hmouz, Jun Shen, R. Al-Hmouz and Jun Yan, "Modeling and Simulation of an Adaptive Neuro-Fuzzy Inference System (ANFIS) for Mobile Learning" in IEEE Transactions on Learning Technologies, vol. 5, no. 03, pp. 226-237, 2012.
- Arkhipov, M.; Krueger, E.; Kurtener, D. Evaluation of ecological conditions using bioindicators: Application of fuzzy modeling. In Proceedings of the International Conference on Computational Science and Its Applications, Perugia, Italy, 30 June–3 July 2008.
- E. M. Dogo, O. J. Afolabi, N. I. Nwulu, B. Twala and C. O. Aigbavboa, "A Comparative Analysis of Gradient Descent-Based Optimization Algorithms on Convolution Neural Networks," 2018 International Conference on Computational Techniques, Electronics and Mechanical Systems (CTEMS), 2018, pp. 92-99, doi: 10.1109/CTEMS.2018.8769211.
- Osama Younes, Nigel Thomas, Analysis of the Expected Number of Hops in Mobile Ad Hoc Networks with Random Waypoint Mobility, Electronic Notes in Theoretical Computer Science, Volume 275, 2011, Pages 143-158, ISSN 1571-0661, https://doi.org/10.1016 /j.entcs.2011.09.010.
- Singh, K., & Gupta, R. (2021). SO-AODV: A Secure and Optimized Ad-Hoc On-Demand Distance Vector Routing Protocol Over AODV With Quality Assurance Metrics for Disaster Response Applications. Journal of Information Technology Research (JITR), 14(3), 87-103. http://doi.org/10.4018/JITR.2021070106
- Nanodrop Spectrophotometric Method for Estimation of Ranitidine Hydrochloride in Bulk and Tablet Dosage Form
Abstract Views :173 |
PDF Views:0
Authors
Affiliations
1 College of Pharmaceutical Sciences, Mohuda, Berhampur, Orissa, IN
2 Indira Gandhi Institute of Pharmaceutical Science, Bhubaneswar, Orissa, IN
3 Biotech Park, Lucknow, Uttar Pradesh, IN
1 College of Pharmaceutical Sciences, Mohuda, Berhampur, Orissa, IN
2 Indira Gandhi Institute of Pharmaceutical Science, Bhubaneswar, Orissa, IN
3 Biotech Park, Lucknow, Uttar Pradesh, IN
Source
Asian Journal of Research in Chemistry, Vol 3, No 3 (2010), Pagination: 716-719Abstract
A novel, simple, sensitive and rapid nanodrop spectrophotometric method was developed for the estimation of Ranitidine hydrochloride in bulk and its pharmaceutical tablet dosage form. Ranitidine hydrochloride exhibiting maximum absorbance at 316 nm in distilled water and obeyed linearity in the concentration range of 5-100 ppm. The proposed method has been applied successfully for the analysis of Ranitidine hydrochloride either in bulk or pharmaceutical tablet dosage form with good accuracy and precision. The method herein described can be employed for quality control and routine analysis of Ranitidine hydrochloride in pharmaceutical tablet dosage form.Keywords
Ranitidine Hydrochloride, Nanodrop Spectrophotometry, Maximum Absorbance, Bulk.- A Novel Approach for the Assessment of Decision Stump & Upgraded Rf Classification Algorithms
Abstract Views :233 |
PDF Views:0
Authors
Affiliations
1 School of Computer Science and Applications, REVA University, Bangalore, Karnataka, IN
2 Department of Computer Science, Sri Venkateswara University, Tirupati, Andhra Pradesh,, IN
1 School of Computer Science and Applications, REVA University, Bangalore, Karnataka, IN
2 Department of Computer Science, Sri Venkateswara University, Tirupati, Andhra Pradesh,, IN
Source
International Journal of Advanced Networking and Applications, Vol 10, No SP 5 (2019), Pagination: 105-108Abstract
The classification models in data mining consists of decision tree, neural network, genetic algorithm, rough set, statistical model, etc. In this research, we have proposed and deliberated a new algorithm called Upgraded Random Forest, which is applied for the classification of sensor discrimination dataset. Here we considered for classification of multisource Sensor Discrimination data. The Upgraded RF approach becomes extreme attention for multi-source classification. The methodology which we are developed is not only a nonparametric but it also applies for the assessment and significance of the specific variables in the classification.Keywords
Data Mining, Classification, Decision Stump, Random Forest and Upgraded RF.References
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- . Dr.M.Jayakameswariah,Dr.K.Saritha,Prof.S.Ramak rishna,Prof.S.Jyothi,“Development of Data Mining System to Evaluate Performance Accuracy of J48 and Enhanced Naïve Bayes Classifiers using Car Dataset”, International Journal Computational Science, Mathematics and Engineering,SCSMB-16-March-2016,PP- 167-170,E-ISSN: 2349-8439.
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