MIT-World Peace University (MIT-WPU) is a top educational institute located in Pune, India. It is recognized within&nbsp;UGC under Government of Maharashtra Act No. XXXV 2017.&nbsp;

It is part of the MIT group of institutions (established in 1983) which covers 10+ campuses across India and has more than 50,000+ students enrolled across various disciplines at a given point of time. The institute houses 15 schools ranging from Engineering &amp; Technology, Design, Pharmacy, Commerce, Governance among others. It offers undergraduate, postgraduate and PhD programs among different disciplines.&nbsp;

&nbsp;

MIT World Peace University

This article proposes active learning strategies for delivering engineering courses to the students in order to make learning more engaging, interesting, accomplishing, and joyful. The education system was impacted by the unprecedented situations generated by the Coronavirus pandemic from the last two academic years. The student community is also going through difficult situations on many levels. The primary challenge for teachers was to engage the students passionately in learning while maintaining a stress-free, healthy and fruitful environment in the online classes. For a stress-free teaching-learning process, adopting a variability in course content delivery methods would be a smart choice for teachers. This paper discusses the most effective active learning strategies in higher education. The work also highlights examples of implementation and an analysis of the effectiveness of active learning methodologies in terms of learners understanding, competency, satisfaction and knowledge gain. The findings indicate that the active learning strategy has assisted students in being more comfortable and engaged in effective learning in the online mode. © 2022, Rajarambapu Institute Of Technology. All rights reserved.

School of Electronics & Communication Engineering

Engineering and Technology

Journal of Engineering Education Transformations

Active Learning Techniques for Effective Online Teaching and Learning in Higher Education

World University root node

Lecture Notes in Electrical Engineering

Machine Learning-Based Approach for Depression Detection Using PHQ-9 and Twitter Dataset

Traffic congestion has become a major issue nowadays. Not only in metro cities even in small cities this traffic congestion is a big problem. Therefore, we have required an intelligent traffic control system that can decrease traffic. Our current traffic control system is not flexible and adaptable, and it is time-based and is unaffected by heavy traffic. Because of its static nature, it is unreliable, unpredictable, and noisy. The proposed system is the approach for traffic control. In the proposed system the image processing and IR sensors are used. IR sensors are installed at the roadside from where they detect vehicles and send results to Arduino UNO. On the other side, image processing is used to count vehicles by using camera surveillance and sends the result to the microcontroller through a serial port. Arduino UNO then analysis both the results and update green path time according to the traffic density on the road. Using technologies separately may have its disadvantages which can be overcome by considering a combination of both results for a better result. This method increases the accuracy and productivity of the system. Apart from this, the project gives prioritization to the emergency vehicles like fire trucks, ambulances. Also, this project saves basic information about vehicles, i.e. speed, vehicle colour, type, etc. This information can be used for further analysis, and as a result, it can forecast traffic congestion and road condition at various times. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Traffic Management System Using AI and IoT

Navigation is how everything moves around globally, and electronics have provided better solutions for appliances to work seamlessly. There are two broad navigation options for finding your location. One is a Global Positioning System (GPS) system, and the other one is by using the Inertial Measurement Unit (IMU). The IMU is nothing but a combination of accelerometers and gyroscopes. This paper puts light on the Inertial Navigation System (INS), which uses GPS and IMU to get navigation data. GPS and INS give us real-time velocity and position data required for navigation. However, GPS has a slow update rate, up to 1-10Hz, while IMU performs far better at gaining navigation data with an update rate up to 1KHz. IMU accumulates errors and drifts over time while GPS has a low update rate. These drawbacks make both systems unreliable when used alone. The proposed work talks more about the use of both sensors, and Raspberry Pi Zero using a sensor fusion technology. Removing drawbacks of both the sensors and the use of the Kalman Filter are discussed in the paper. © 2022 IEEE.

2022 6th International Conference on Computing, Communication, Control and Automation, ICCUBEA 2022

SENSOR FUSION: An Advance Inertial Navigation System using GPS and IMU

In 5G cellular communications, Non-Orthogonal Multiple Access (NOMA) is the advanced radio access technique. Compared to other Orthogonal Multiple Access (OMA) schemes, NOMA is more efficient and supports a large number of users. However, as the number of users increases, OMA based schemes may not meet the emerging requirements such as very high spectral efficiency, very low latency, and massive device connectivity. NOMA allows access to several users in the same resource block, such as a time slot, subcarrier, or spreading code. This work mainly emphases on the power domain NOMA with Multiple Input Multiple Output (MIMO), which combines many users in the power domain and uses channel gain difference between multiple users. Various user signals can also spread over the channel at the transmitter side. Due to the availability of multi-users, the SIC on the receiver side cannot be able to perform the sequential decoding of the users. Whale Rank Successive Interference Cancellation (WRSIC) overcome the limitation in the existing SIC by ranking the user for successive cancellation of interference in the system. A WRSIC based Multi-User Detection (MUD) algorithm is used on the receiver side to identify the signal required. Thus, the novel WRSIC-MIMO NOMA method maximizes the channel capacity and eliminate the interference. Simulation results show the performance of the proposed scheme with different parameters and the comparison with the other schemes. © 2021 Taylor's University. All rights reserved.

Journal of Engineering Science and Technology

Noma multiuser detection with mimo for maximizing the system capacity and eliminate interference

In multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) systems, multi-user detection (MUD) algorithms play an important role in reducing the effect of multi-access interference (MAI). A combination of the estimation of channel and multi-user detection is proposed for eliminating various interferences and reduce the bit error rate (BER). First, a novel sparse based k-nearest neighbor classifier is proposed to estimate the unknown activity factor at a high data rate. The active users are continuously detected and their data are decoded at the base station (BS) receiver. The activity detection considers both the pilot and data symbols. Second, an optimal pilot allocation method is suggested to select the minimum mutual coherence in the measurement matrix for optimal pilot placement. The suggested algorithm for designing pilot patterns significantly improves the results in terms of mean square error (MSE), symbol error rate (SER) and bit error rate for channel detection. An optimal pilot placement reduces the computational complexity and maximizes the accuracy of the system. The performance of the channel estimation (CE) and MUD for the proposed scheme was good as it provided significant results, which were validated through simulations.

Fulltext

Technologies

Channel Estimation and Data Detection Using Machine Learning for MIMO 5G Communication Systems in Fading Channel

Fish keeping is a popular trend. Fish keeping is itself an industry which comes in agriculture. Fish keeping is not an easy job; we always need an aquarium or a pond for that. The hobby of fish keeping is broadly divided into three- freshwater, brackish, and marine. Among all these three, freshwater is considered to be the most popular hobby of keeping fish because it is easy to handle freshwater fish and aquariums. It requires a lot of manual work to take care of the aquarium for instance timely change of water, regular feeding of the fishes, maintaining the turbidity level and the temperature of the water in the aquarium. Hence to reduce the manual work, the research is based on the project, IOT and ARDUINO based Fish Aquarium that has been designed to save labor time through making the system automated. It is a prototype functioned to feed the fishes on a regular time intervals, keeps the temperature and the turbidity level under control. The Wi-Fi Module attached to it sends the status of the aquarium like temperature level, turbidity level, feeding etc on your respective device like cell phones.

International Journal of Innovative Research in Technology

IOT and ARDUINO Based Fish Aquarium

Nowadays, Multicarrier Direct sequence code division multiple access (MC DS-CDMA) systems are used in mobile communication. Performance of these systems are limited by multiple access interference (MAI) created by spread-spectrum users in the channel as well as background channel noise. This paper proposes an incremental gradient descent (IGD) multi-user detection (MUD) for MC DS-CDMA system that can achieve near-optimum performance while the number of users is linear in its implementation complexity. The IGD algorithm make an effort to perform optimum MUD by updating one user's bit decision each iteration in the best way. This algorithm accelerates the gradient algorithm convergence by averaging. When a minimum mean square error (MMSE) MUD is employed to initialize the proposed algorithm, in all cases tested the gradient search converges to a solution with optimum performance. Further, the iterative tests denote that the proposed IGD algorithm provides significant performance for cases where other suboptimum algorithms perform poorly. Simulation compares the proposed IGD algorithm with the conventional detectors.

International Journal of Engineering and Technology

Incremental gradient algorithm for multiuser detection in multi-carrier DS-CDMA system under modulation schemes

The aim of this paper is to design a wearable air pollution mapping system for an individual. For this itincludes interfacing some pollution related sensors (CO2, CO and dust sensor) to the user’s body which will constantlymonitor the surrounding air pollution levels and calculate the exact amount of toxic gases inhaled by the userdepending upon the breathing rate of the user. Depending upon these values, the user will be alerted in real time byshowing warnings where pollution level has surpassed the permissible limits. The data will be preserved and lateranalyzed using graphs and diagrams prepared in Excel using Visual Basic. The data analysis will provide the user withhealth prediction i.e. probability of immediate or long term health effects of various poisonous gases or pollutants.

International Journal of Advanced Research in Computer and Communication Engineering

Personal Pollution Exposure Estimates using Pollution Sensors and Health Prediction

Adaptive Filters are generally implemented in the time domain which works well in most scenarios however in many applications the impulse response becomes too long, increasing the complexity of the filter beyond a level where it can no longer be implemented efficiently in the time domain. An example of where this can happen would be in acoustic echo cancellation applications in hands free telephony. However there exists an alternative solution and that is to implement the filters in the frequency domain. The Discrete Fourier Transform or more specifically the Fast Fourier Transform (FFT) allows the conversion of signals from the time domain to the frequency domain in an efficient manner. Acoustic echo cancellation of the frequency domain adaptive filter is compared with time domain adaptive filter. Again results are compared for both frequency domain and time domain adaptive filters with different step sizes. © 2010 IEEE.