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Since the last decade, gearbox systems have been requiring increasing power, and consequently, the complexity of systems has escalated. Inevitably, this complexity has resulted in the need for the troubleshooting of gearbox systems. With a growing trend of health monitoring in rotating machines, diagnostic and prognostic studies have become focused on diagnosing existing and potential failures in gearbox systems. In this context, this study develops the architecture of the cloud-based cyber-physical system (CPS) for condition monitoring of gearbox. Empirically collected vibration signals of gear wear at various time intervals are processed using empirical mode decomposition (EMD) algorithm. A Euclidian-based distance evaluation technique is applied to select the most sensitive features of car gear wear. Artificial neural network (ANN) is trained using extracted features to monitor the gearbox for the future dataset. Comparison of the performance results revealed that the ANN is superior to the other EMD methods. The present methodology was found efficient and reliable for condition monitoring of industrial gearbox.

Optimal route selection based upon Quality of Service (QoS) requirements is a challenging task in a completely dynamic environment like MANET. To enhance the quality of service in MANET, route selection plays an important role. Existing well known routing protocols like AODV, DSR, etc. does not choose path based on QoS parameters. Different applications has its own requirements for route selection like for Email and File transfer application, less retransmissions should be there while delay can have secondary importance and for video conferencing applications, bandwidth must be high and delay must be low. So, there is an uncertain environment in which same QoS parameter may have less or more importance as per the application. Fuzzy based approach plays a vital role in an uncertain environment like adhoc network in which nodes are mobile. In this paper, Fuzzy TOPSIS (multi-criteria decision making method) based approach is proposed for the selection of optimal path among N available routes from source to destination based on QoS parameters. Total four QoS parameters are considered here reliability, bandwidth jitter and delay. AOMDV routing protocol is the base protocol for the proposed system and the proposed protocol QoS-AOMDV is finally compare and analyzed with AODV, AOMDV protocol. QoS- AOMDV results in better throughput and delay as compared to AODV and AOMDV protocols.

Nowadays, the entire world is facing the problem of pandemic i e COVID-19 Hence it is a challenging task for educators to engage students during virtual classroom activity Many online tools are available to take instant feedback from students to measure their involvement levels like Quizzes, Polls, Surveys, etc Hence, in this paper, the use of two online tools like InterviewBit and Slido is being addressed These online tools are used to ask the questions during online lecture delivery that may help in measuring the overall involvement of the students The mentioned tools are described in detail along with its incorporation in teaching Data Structure and Algorithms course for second year B Tech in Computer Engineering students (around 120 Students) Also, the learning of students before and after the usage of the Tools have been compared and analysed It has been observed that there is approximately 20% improvement in the overall learning outcomes after the usage of the Tools Also, the cognitive and affective learning domains are considered to measure the overall impact © 2021, Rajarambapu Institute Of Technology All rights reserved

Distributed defects in rolling element bearing arise due to the progression of small localized pits. If not monitored on time, this leads to premature or may turn into catastrophic failure of a rotor system and thus increases the cost of maintenance of machinery in industries. This research work introduced a novel method for the diagnosis of rolling element bearings to detect distributed defects using Dimensional Analysis (DA). The rolling element bearing system is modeled using DA with Buckingham’s theorem to study the vibration characteristics theoretically. Significant geometrical and response parameters are considered for modeling the rotor-bearing system. The in-house experimental test rig is designed and fabricated to study the vibration characteristics of distributed defects experimentally. Geometrical imperfections are created intentionally on the bearings surfaces using electro-discharge machining and vibration signatures generated are studied under different operating conditions. Experimental results are compared with analytical models developed using the DA. A comparison is made between distributed and localized defects and vibrations signatures from both are correlated with healthy bearings. It is noticed that there is a good correlation between theoretical and experimental results. The present study contributes as a simple and effective diagnosis of rolling element bearings for distributed defects and useful for condition monitoring of industrial machinery.

Mobile ad hoc networks (MANETs) have inherently dynamic topologies. Due to node mobility, the links along the paths suffer frequent failure and reactivation in highly dynamic environments. A new routing paradigm, known as Opportunistic Routing (OR) has recently been proposed that finds routes in adaptive manner, based on current channel conditions in dynamic wireless environment. OR is based on the use of broadcast transmissions to expand the potential forwarders that can assist in the retransmission of the data packets. In this paper, we embark upon the basic operations of OR and a framework to support decision making for finding optimal route in the MANET. In later part we propose an adaptive algorithm to deal with OR as a Markov decision problem (MDP). Finally the comparative analysis of the proposed Markov chain based protocol with OR protocol: CORMAN has been carried out on the basis of throughput, average delay and control overhead. The proposed protocol shows the better results as compared to existing one.

After passing out 12th standard, a student has many options to choose for higher education in India. He or she can choose a career oriented course or an academic course. Choosing a career is a critical decision. Now -a- days the multi-criteria decision making methods (MCDM) are gaining importance for the selection of best suited alternative among the available alternatives. In this paper multi criteria decision making methods viz. Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) were applied to choose the best career option. Multiple options have been considered as alternatives and some specific criteria were taken into account individually to select best career option. AHP is used to derive the weights of criteria and appropriate course selection and final ranking of all courses available after 12th have been obtained from both the methods: TOPSIS and AHP. The experimental work shows that the final ranking of both the applied methods is equivalent even though the final priorities are differ in values.

The term Course Outcomes (COs) plays a vital role in Outcome-Based Education (OBE). The attainment of Program Educational Objective (PEOs) and Program Outcomes (POs) is depends on the attainment of Course Outcomes (COs). In this paper, we have measured the CO attainment for Data Structure course on the basis of two methods; one is direct method in which students' marks have been considered as an input data. While another method, indirectly measures the CO attainment by taking feedback from Course Exit Survey. A suitable weight-age is given to direct and indirect method i.e. 80% and 20% respectively. The course Data Structure is chosen for this study of CO attainment because this course is very important for students' employment i.e. placement as well as competitive exams. The attempt is made here to find out accurate attainment of COs so that corrective actions can be taken for the next batch to improve the teaching learning process and intern higher attainment of COs and intern PEOs. Finally the analysis of results obtained by both direct and indirect methods is also shown in this paper.

Roller bearings are essential parts extensively used in many industries such as automobile, sugar factories, cement industries, weaving mills, chemical industries, and other process industries. The catastrophic failure of such bearings results into unplanned shutdowns, discontinuity of manufacturing process, and heavy maintenance cost. The vibration analysis of the roller bearing is a vital factor in the rotating machines because its performance significantly affects the safety and operational life of the rotating machines and subsequently entire plant. The object of this paper is to study how to predict the vibration characteristics of the rotor-bearing system by using the mathematical model. In the present research work, a empirical model for the vibration characteristics of the roller bearing has been established using FLTθ system. The new mathematical model considers the influences of the bearing variables on the vibration of the rotor system. Furthermore, a new model on bearing system is carried out by using dimensional analysis (DA) and the defect frequencies and vibration characteristics of the bearing system are obtained. The effects of speed and load along with other variables on vibration characteristics have been studied by establishing an empirical model. Experiments were conducted to validate the developed empirical model. The method proposed in this paper is based on FLTθ method of DA. The vibration characteristics thus obtained provides a complete and systematic theory and technique in this aspect.

RIT, established in 1983 as a self-financing institute, is well known for its continuous experiments, leadership in academic practices, and excellence in engineering education. In the journey so far since 2008 with the help of IUCEE, RIT has progressed in leaps and bounds right from curriculum development to teaching-learning process and assessment. The Institutional Performance is measured on the basis of competent curriculum, achieving course learning objectives in turn achieving program educational objectives and program outcomes of all the programs. Various IUCEE Faculty Leadership Institutes (FLIs), webinars, Virtual Academy courses, and visit to US universities have helped RIT in transforming itself from a well-known institute in western Maharashtra to one of the leading private institutes at the national level. In this paper, the attempt is made to present how this transformation took place. With the help of IUCEE, RIT shifted from the old paradigm of one-way lecturing to two-way joyful learning experiences with better, advanced technical knowledge and globally adopted advanced pedagogical tools. And also it explains new practices we learned and followed and its impact on students’ result and overall students’ satisfaction index (teaching index).