IoT based smart home security system
The research paper based on home & industrial security ,the system are already installed in various industries but they have some drawback. We are all the student of final year computer technology we are try to overcome the problem that are facing the industry in any accident or harmful damage like gas leakage & fire.
Published by: Titesh Aglawe, Sudhanshu Raut, Sunny Fofse, Atharva Hawale, Suraj Deshkar
Author: Titesh Aglawe
Paper ID: V7I3-1384
Paper Status: published
Published: May 20, 2021
Employing project work to enhance aspects of learner autonomy for tertiary EFL learners
The study aims to explore the enhancement of learner autonomy through the integration of the project work in the existing syllabus. The study was conducted with thirty-four first-year non-English majors in a university in the north of Vietnam. In the study, learner autonomy is conceptualized as a multi-faced concept with four aspects: technical, psychological, political-critical, and socio-cultural. Learner autonomy was researched based on the empirical evidence of its benefits to learners in language learning. Meanwhile, project work was argued to be potential to promote learner autonomy. As a result, eight different projects created by the students were implemented in the learning process. The study employed action research approach with three different data collection tools (questionnaires, interviews, and the teacher’s diary). Content analysis was applied for the data in the study. The findings reveal that the enhancement of learner autonomy was evident in all the four aspects. Technically, the students were found to have more access to the learning resources and used more learning strategies. Psychologically, the students were identified to exhibit highly positive attitudes and to be motivated in learning. Political-critically, the students reported that they had more choices in learning contents and methods. Socio-culturally, the students demonstrated more interaction and collaboration.
Published by: Pham Duc Thuan
Author: Pham Duc Thuan
Paper ID: V7I3-1381
Paper Status: published
Published: May 20, 2021
Real Estate Recommendation System
Technology has advanced in the field of Online Real Estate Marketing, market trends and advances in various techniques such as data science, editing and filtering algorithms, machine learning is growing rapidly These days, however, web sites for sale are paying a lot of money to get their services. Our proposal The web site overcomes this problem and provides customers with free services so that they can access the information you need and to measure future market trends and technologies in a friendly manner. Ours The website is basically an online service where the user will be able to buy / rent / sell properties as they wish Focus on building an easy-touse web application. This can help people to communicate easily with buyer / seller / employer, as this program uses the KNN process to process user queries, to identify the key words, align them with Knowledge Base and respond with real results. To make the answers more understandably, answers are made using classification techniques and produce non-textual responses to can be easily seen by users. The program also uses machine learning capabilities to process data such as price of buildings for years to come based on previous data records
Published by: Bhaumik Kesalikar, Mayank Doshi, Hardik Doshi
Author: Bhaumik Kesalikar
Paper ID: V7I3-1367
Paper Status: published
Published: May 20, 2021
Analyzing the sentiment through Twitter data
Social media is widely used for interactions among people in which they create, share, exchange information, opinions, and thoughts. Some social media websites as emerged as one the platforms to raise users’ opinions and influence the way any business is commercialized. These days, the applications of such analysis can be easily observed using public elections, movie promotions, brand endorsements, and many other fields. Opinions of people matter a lot to analyze how the propagation of information impacts the lives in a large-scale network like Twitter. In this paper, we can see different feature sets and machine learning classifiers to determine the best combination of sentimental analysis of tweets. The primary aim is to explore possible methods for analyzing sentiment scores in a noisy Twitter stream. This paper reports on the design of sentiment analysis, extracting vast twitter data such as tweets. We can also see various techniques to carry out a sentiment analysis on Twitter data in detail.
Published by: Pooja B.
Author: Pooja B.
Paper ID: V7I3-1341
Paper Status: published
Published: May 20, 2021
Speech based Emotion Recognition using CNN Classifier
Communication through voice is one of the main components of affective computing in human-computer interaction. In this type of interaction, properly comprehending the meanings of the words or the linguistic category and recognizing the emotion included in the speech is essential for enhancing the performance. In order to model the emotional state, the speech waves are utilized, which bear signals standing for emotions such as boredom, fear, joy and sadness. This project is aiming to design and develop speech based emotional reaction (SER) prediction system, where different emotions are recognized by means of Convolutional Neural Network (CNN) classifiers. Spectral features extracted is mel-frequency cepstral (MFCC). Librosa package in python language is used to develop proposed algorithm and its performance is tested on taking Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS) samples to differentiate emotions such as happiness, surprise, anger, neutral state, sadness, fear etc. Feature selection (FS) was applied in order to seek the most relevant feature subset. Results show that the maximum gain in performance is achieved by using CNN.
Published by: B. Sandeep, Dr. R. Sivaranjani, R. Mourya, J. Sai Vinay, Y. Vineela
Author: B. Sandeep
Paper ID: V7I3-1372
Paper Status: published
Published: May 20, 2021
Intelligent Electronic Toll Collection System on Highway (Android App)
In few years, the number of vehicles is getting increased day by day due to this the amount of traffic in most of the roads are increased. There are some of the highway roads, where the people need to pay the toll tax. Most of the toll plazas are manually worked which is time consuming process and increases heavy traffic, fuel wastage and other issues. To automated this process, we propose a new Toll Collection Android App which uses to pay the toll tax using them mobiles and simply scan generated QR code on toll plaza. The proposed system provides fast result as compare to traditional systems. Thus, the vehicles won’t have to stop at toll plaza to pay toll which would save the time and efforts and reduces long queues on toll plaza and traffic.
Published by: Manasi Patil, Vrushali Pawar, Priya Gunjal, Nandita Shama, Pravin Hole
Author: Manasi Patil
Paper ID: V7I3-1378
Paper Status: published
Published: May 19, 2021
