Design and Application of Six edges Robo Arm Using Arduino UNO

To provide a better life to human, A six edges Robotic arm prototype model is developed. For the movement of every part there are Motors attached with them and for controlling we used Arduino UNO, for connection there is breadboard. A Robotic arm provides a facility to pick a thing from place and put that thing to another place. This prototype is used at home for carrying small things. With the reference to this prototype model a heavy thing carrying robotic arm can be use in industries.

Machine Learning Techniques for Enhancing Student Learning Experiences

Outcome-based learning (OBL) is a tried-and-true learning technique based on a set of predetermined objectives. Program Educational Objectives (PEOs), Program Outcomes (POs), and Course Outcomes are the three components of OBL (COs). Faculty members may adopt many ML-based advised actions at the conclusion of each course to improve the quality of learning and, as a result, the overall education. Due to the huge number of courses and faculty members involved, harmful behaviors may be advocated, resulting in unwanted and incorrect choices. The education system is described in this study based on college course requirements, academic records, and course learning results evaluations is provided for anticipating appropriate actions utilizing various machine learning algorithms. Dataset translates to different problem conversion methods and adaptive methods such as one-versus-all, binary significance, naming power set, series classification and custom classification ML-KNN. The suggested recommender ML-based system is used as a case study at the Institute of Computer and Information Sciences to assist academic staff in boosting learning quality and instructional methodologies. The results suggest that the proposed recommendation system offers more measures to improve students' learning experiences.

Survey on Fake News or Truth - Rumours Detection using Machine Learning

This study is to help readers to understand detection of fake news using machine learning. The main purpose of the planned system is to build an application which identifies fake news stories from a bunch of news stories to make people aware of fake news rumours. With the help of machine learning algorithms, we can detect and separate out the fake news. Nowadays, it is become harder to identify the original source of news stories, like looking for a needle in a haystack. In the modern world, news is a kind of communication that keeps us up to date on the latest events, topics, and people in the wider globe. A society relies on news for a variety of reasons, the most important of which is informing its members about events taking on in and around them that might influence them. Oral and traditional media, as well as digital communication methods, altered videos, memes, unconfirmed marketing, and social media have all contributed to the spread of rumors. As nowadays many people use social media in many cases people get wrong and misleading information and people share those stories without verifying whether it is real or fake news stories. Spreading false information on social media has become a major problem these days. That is why we need a system that can tell us whether something is false news or not. Applications are: 1. Fake news may be detected on social media using this approach. 2. The system can be used to help news channels to broadcast only real and classified news. 3. Users can easily detect and eliminate fake articles that contain misinformation intended to mislead readers.

Ocean Waste Detection Model

The number of marine debris is excellent in understanding the diagnosis of debris from all oceans of the world and the identification of the highest levels of waste disposal that is most necessary for the removal of waste. Currently, the standard for floating waste management requires the use of a manta trawl. Techniques that require manta trawls (or similar ground-collection devices) that use the physical removal of marine debris as a first step and then analyze the collected samples as a second step. The need for pre-analysis removal is very costly and requires significant oversight - preventing the safe transfer of marine waste monitoring services to all Earth's marine bodies. Without better monitoring methods and samples, the overall impact of water pollution on the entire environment. This study revealed an unusual flow of activity that used images taken from aquatic debris as roots. Produces quantification of marine plastic or waste incorporated into photographs to perform accurate quantification and body removal. This model is trained in the ImageNet Large Visual Recognition Challenge using the 2012 data and can distinguish between many different classes such as cardboard, glass, metal, paper, and plastic. This program uses the transfer of learning from the existing model and then returns it to separate a new set of images. Workflow involves creating and processing domain-specific information, building an object acquisition model using a deep neural network.

Social Interactions for Detecting Stress Based Issues

Mental stress is showing harmfulness to human health leads abnormal stress in chronology with this may lose our mental health for proactive care. With recognizable pieces of proof of web-based media, individuals cannot share their everyday exercises and collaborate with companions via web-based media stages, making it happing to use online informal community information for stress identification. We find that users stress state is closely associated with thereupon of his/her friends in social media, which we employ a large-scale dataset from real-world social platforms to systematically study the relationship between users’ stress states and social interactions. We first define a gaggle of stress-related comments, images, and social attributes from various aspects, then proposed a plot. Research results saying that the proposed model can improve the detection performance. With the help of enumeration, we build an internet site for the users to spot their stress rate level and may check other related activities.

Political Tweets Anatomization Using Sentiment Analysis

Social Media has an impact on different aspects of our life. It has revolutionized the way people communicate and socialize on the web. It is an undeniable force in modern society. It has the power to force necessary changes. Social networking platforms such as Facebook, Twitter, Instagram allows users to interact with the world, to express their view on different topics in society. Social media influence in political campaigns has increased tremendously, it plays an important role in electoral politics, political polling, so it is necessary to perform sentiment analysis on political topics to get the public opinion. This technical paper focuses mainly on analysis of political tweets using sentiment analysis. In this paper, we performed sentiment analysis on different political topics in India and analysed the overall sentiments regarding those topics, using naive bayes machine learning algorithm and classified those tweets as positive and negative.

Quality Identification: Fruit Grading System

In India, agriculture plays a major role in the economic development. Agriculture must be able to produce fruit of better quality and grow at a faster rate. With the use of different image processing techniques, improvement in agriculture field for quality identification, sorting the fruits with different quality, irrigation becomes feasible. Major parameters considered are reduction in the time required and cost efficient, using Image processing. In this proposal, we have provided a technique to address the challenge of fruit grading using image processing techniques for smart farming.

Development of Geographic Information System based COVID-19 Dashboards using Operations Dashboard for ArcGIS

A dashboard is used to view, analyze and manage the key performance indicators of a process or business. It is a kind of information management system. The information in the dashboards can be enhanced by integrating Geographic information systems (GIS) with it. During this age of the pandemic, GIS technologies have been very useful to get a synoptic view of the whole situation and support the global fight against it. This paper reviews a process to build an interactive data driven and GIS based COVID dashboard in a short period of time and that too without any programming skills using Operations Dashboard in ArcGIS Online.