Manori Gamage

E-learning is a form of providing education by using electronic devices. Lack of proper mechanisms for encouraging and assisting students are key issues faced by many students in an e-learning environment. The ‘Vidu Mithuru’ is a question-based e-learning application which has been developed as a solution to overcome these problems. This mobile application will auto generate and categorize the questions, evaluate the answers and track the performance while providing motivational quotes by detecting the emotions of the student. This mobile application is based on Neural Networks, Natural Language Processing and Machine Learning concepts. In order to developing this application, the information provided by the primary education professionals was used to comply with the standards. The core objective of the proposed solution is to track the performance level and assist the students to improve in their studies while keeping them motivated. The trained Machine Learning models have achieved the accuracy of 75%, 78%, 99% and 86% for question categorization model, speech emotion detection model, facial emotion detection model and model to evaluate answers as respectively. We have received favorable responses as the results after testing the developed ‘Vidu Mithuru’ mobile application among students in 3rd, 4th and 5th grades in school.

Motorcycles are an important part of daily transportation. They are specially used to avoid traffic congestions downtown and most of the individuals tend to use a motorcycle because it takes less time to get to the destination. The rapid increase of motorcycle usage has led to a significant increase in the number of motorcycle-related accidents and fatalities. The reasons for accidents which were considered are speeding, collision with objects, lack of focus or drowsiness where only the rider's head is protected but not the body. And accidents may lead to death when help is not called immediately. By considering these, author introduces a Motorcyclists Safety Assistant Application (MSAA). This research tries to address four major factors that caused most road accidents and fatalities in Sri Lanka. They are excess speed, 360-degree threat detection, motorcyclist safety balloons, and emergency alert system. Here, MSAA can detect the vehicle's real-time speed and inform the user when a certain speed limit has been exceeded. Also, it has proposed a system which automatically detects threats that occur in each collision and alerts the rider via visual and audio cues. Moreover, the next system will be focusing on safeguarding the rider's body by inflating an airbag which will be connected to the rider's jacket. An automatic alert system is also introduced where the main objective is to mitigate the consequences of accidents by sending a message to the registered mobile using wireless communication techniques and checks whether an accident has occurred using vibration frequency limits. Location will be sent through the tracking system to cover the geographical coordinates over the area. The proposed domain successfully contributes to a drastic reduction in road accidents. The ultimate objective is to create a better future for everybody through road safety. The survey conducted to test the user satisfactory level, demonstrated high user satisfaction.

E-learning is a form of providing education by using electronic devices. Lack of proper mechanisms for encouraging and assisting students are key issues faced by many students in an e-learning environment. The 'Vidu Mithuru' is a question-based e-learning application which has been developed as a solution to overcome these problems. This mobile application will auto generate and categorize the questions, evaluate the answers and track the performance while providing motivational quotes by detecting the emotions of the student. This mobile application is based on Neural Networks, Natural Language Processing and Machine Learning concepts. In order to developing this application, the information provided by the primary education professionals was used to comply with the standards. The core objective of the proposed solution is to track the performance level and assist the students to improve in their studies while keeping them motivated. The trained Machine Learning models have achieved the accuracy of 75%, 78%, 99% and 86% for question categorization model, speech emotion detection model, facial emotion detection model and model to evaluate answers as respectively. We have received favorable responses as the results after testing the developed 'Vidu Mithuru' mobile application among students in 3 rd , 4 th and 5 th grades in school.

The scarce use of tangible periodicals led to a consistently soaring popularity of online classified advertising. Nevertheless, existing platforms retain complications. Most recommendation systems are built with conventional technologies that are less scalable, less accurate, and having high latency processes. Moreover, customers find it tiring when clarifying a reliable, precise price value for items they are trying to sell through the classified advertising system. Additionally, strict validation techniques to identify and prevent fraudulent content or images from being published in the advertising portals have been neglected. Therefore, authors have inaugurated a superior classified advertising system, Tievs, as a solution, by appraising said predicaments. It wields a flexible, process-simplifying, concurrency-induced recommendation breakthrough implemented from Universal Sentence Encoding incurred Natural Language Processing and Deep Learning routines. Furthermore, an innovative price prediction system having a supervised regression-based ensemble model forged ensuing a comparative study, having excellent accuracy in proactively predicting item prices as to cater hassles faced by customers, was satisfied. Light Gradient Boosting classifier-driven fake description analysis and a Convolution Neural Network powered figure deception recognition system were introduced, which gained prodigious precision with moral clarity in fraud detection and prevention. Hence, the proposed solution's objective of surpassing former classified advertising systems in delivering customers' necessities, using the most lucrative, time-saving, human-centric, and error-preventive approaches, was accomplished. It was affirmative by the positively responded questionnaire regulated among prospective users by the authors.