Control and System Graduate Research Colloquium 

About: Control and System Graduate Research Colloquium is an academic conference. The conference publishes majorly in the area(s): Control theory & PID controller. Over the lifetime, 605 publications have been published by the conference receiving 3372 citations.

A rainfall prediction model using artificial neural network

Abstract: The multilayered artificial neural network with learning by back-propagation algorithm configuration is the most common in use, due to of its ease in training. It is estimated that over 80% of all the neural network projects in development use back-propagation. In back-propagation algorithm, there are two phases in its learning cycle, one to propagate the input patterns through the network and other to adapt the output by changing the weights in the network. The back-propagation-feed forward neural network can be used in many applications such as character recognition, weather and financial prediction, face detection etc. The paper implements one of these applications by building training and testing data sets and finding the number of hidden neurons in these layers for the best performance. In the present research, possibility of predicting average rainfall over Udupi district of Karnataka has been analyzed through artificial neural network models. In formulating artificial neural network based predictive models three layered network has been constructed. The models under study are different in the number of hidden neurons.

Overview of use of decision tree algorithms in machine learning

Abstract: A decision tree is a tree whose internal nodes can be taken as tests (on input data patterns) and whose leaf nodes can be taken as categories (of these patterns). These tests are filtered down through the tree to get the right output to the input pattern. Decision Tree algorithms can be applied and used in various different fields. It can be used as a replacement for statistical procedures to find data, to extract text, to find missing data in a class, to improve search engines and it also finds various applications in medical fields. Many Decision tree algorithms have been formulated. They have different accuracy and cost effectiveness. It is also very important for us to know which algorithm is best to use. The ID3 is one of the oldest Decision tree algorithms. It is very useful while making simple decision trees but as the complications increases its accuracy to make good Decision trees decreases. Hence IDA (intelligent decision tree algorithm) and C4.5 algorithms have been formulated.

Real-Time Facemask Recognition with Alarm System using Deep Learning

Abstract: In the background of the COVID-19 pandemic, institutions such as the academy suffer a great deal from practically closed globally if the current situation is not going to change. COVID-19 also known as Serious Acute Respiratory Syndrome Corona virus-2 is an infectious disease that is released from an infected sick person who speaks, sneezes, or coughs by respiratory droplets. This spreads quickly through close contact with anyone infected, or by touching objects or surfaces affected with a virus. There's still currently no vaccine available to protect against COVID-19 and preventing exposure to the virus seems to be the only method to safeguard ourselves. Wearing a facemask that covers the nose and mouth in a public setting and often washing hands or the use of at least 70% alcohol-based sanitizers is one way to avoid being exposed to the virus. Amid the advancement of technology, Deep Learning has proven its effectiveness in recognition and classification through image processing. The research study uses deep learning techniques in distinguishing facial recognition and recognize if the person is wearing a facemask or not. The dataset collected contains 25,000 images using 224x224 pixel resolution and achieved an accuracy rate of 96% as to the performance of the trained model. The system develops a Raspberry Pi-based real-time facemask recognition that alarms and captures the facial image if the person detected is not wearing a facemask. This study is beneficial in combating the spread of the virus and avoiding contact with the virus.

Web-based student attendance system using RFID technology

Abstract: This paper describes the development of a student attendance system based on Radio Frequency Identification (RFID) technology. The existing conventional attendance system requires students to manually sign the attendance sheet every time they attend a class. As common as it seems, such system lacks of automation, where a number of problems may arise. This include the time unnecessarily consumed by the students to find and sign their name on the attendance sheet, some students may mistakenly or purposely signed another student's name and the attendance sheet may got lost. Having a system that can automatically capture student's attendance by flashing their student card at the RFID reader can really save all the mentioned troubles. This is the main motive of our system and in addition having an online system accessible anywhere and anytime can greatly help the lecturers to keep track of their students' attendance. Looking at a bigger picture, deploying the system throughout the academic faculty will benefit the academic management as students' attendance to classes is one of the key factor in improving the quality of teaching and monitoring their students' performance. Besides, this system provides valuable online facilities for easy record maintenance offered not only to lecturers but also to related academic management staffs especially for the purpose of students' progress monitoring.

A review of single-phase single stage inverter topologies for photovoltaic system

Abstract: This paper discussed the latest development of single-phase single stage current source inverters for grid connected photovoltaic system. In general, the single-phase single stage inverters are categorized into four types of topologies: 1) H-Bridge, 2) buck-boost, 3) flyback type chopper and 4) Z-Source inverter. The inverters are compared and evaluated on switching technique, switching frequency, efficiency, output power, MPPT method, power factor and THD.