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Research Paper

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

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Review Paper

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

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Research Paper

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

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Research Paper

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

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Research Paper

Design and optimization of Aluminium alloy wheel used in automobiles

Wheels are the main component of the car. The wheels with the tyre provide the better cushioning effect to the car without an engine car may be towed but without wheels, the car cannot be towed. The main requirement of the vehicle is it must be perfect to perform its all function. Reverse engineering is not a method to redesign the old component. The wheels have to pass the different test for best performance like static and vibration analysis etc. design is an important manufacturing activity which provides the quality of the product the 3-D model of alloy wheel design using the technology reverse engineering and CATIA V5 software and further, it was imported to ANSYS. The static fatigue and dynamic analysis were performed. This was constrained in all degrees of freedom at the bolt. Similarly based on the weight, the thickness of the rim and spoke are varied to attain different mos. Also changing the number of spoke wheel models is prepared and analysis is done. From the analysis done in the project, it can be concluded that the wheel made of magnesium alloy is better as compared to Al alloy1 wheels. As the stresses developed in the magnesium wheel are less as well1 as the S-N1 curve of the Mg wheel is better under load condition.

Published by: Lakhan Suryawanshi, Gaikwad S. M., Kulkarni P. D.

Author: Lakhan Suryawanshi

Paper ID: V7I3-1374

Paper Status: published

Published: May 19, 2021

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Research Paper

Mechanical Characterization of Al 8011 Aluminium alloy reinforced with Silicon carbide and fly ash

Aluminium metal matrix composites are gaining widespread acceptance for automobile, aerospace, agriculture farm machinery, defence sector and many other industrial applications because of their essential properties such as high strength, low density, good wear resistance, ease of production and adaptability to modification compared to any other metal. The present study deals with the addition of reinforcements such as fly ash, silicon carbide to the Aluminium matrix in various proportions. Each reinforced material has an individual property which when added improves the properties of the base alloy. An effort has been made to review the different combinations of the composites and how they affect the properties of the different alloys of aluminium. Comprehensive knowledge of the properties is provided in order to have an overall study of the composites and the best results can be employed for the further development of the Aluminium reinforced composed. The investigation shows that Al metal matrix composites can be replaced with other conventional metals for better performance and longer life

Published by: Devanathan G., Dineshkumar G., Ganesan R., Hariharan A., Dr. S. Thirunanam

Author: Devanathan G.

Paper ID: V7I3-1373

Paper Status: published

Published: May 19, 2021

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