scholarly journals Placement Prediction System

2021 ◽  
Vol 9 (VIII) ◽  
pp. 700-702
Author(s):  
Mr. Sreenivasa M
Keyword(s):  
Machine Learning ◽  
User Satisfaction ◽  
Educational Institution ◽  
Personality Testing ◽  
Prediction System ◽  
Project Implementation ◽  
Student Records ◽  
Machine Learning Methods ◽  
Use Of Time ◽  
Improved Model

Placement prediction system is a useful software for managers and students. An educational institution contains student records which is a wealth of information but is very large one person analyzes complete student records. To find out the placement status of each student at institution is a tedious task. Therefore, the limit of the system includes the use of time, which is minimal efficient and with little user satisfaction. The project implementation prediction plan predicts the reader placement using a variety of machine learning methods such as merging methods, regression strategies, decision solution etc. Based on student schools with the ability to measure, English skill, logical ability, technical personality testing. Improved model used predict the placement of students in the training and placement office (TPO)

scholarly journals Combining Radar and Optical Sensor Data to Measure Player Value in Baseball

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 64
Author(s):  
Glenn Healey
Keyword(s):  
Machine Learning ◽  
Optical Sensors ◽  
Optical Sensor ◽  
Doppler Radar ◽  
Major League Baseball ◽  
Three Dimensional ◽  
Sensor Data ◽  
Running Speed ◽  
Machine Learning Methods ◽  
Improved Model

Evaluating a player’s talent level based on batted balls is one of the most important and difficult tasks facing baseball analysts. An array of sensors has been installed in Major League Baseball stadiums that capture seven terabytes of data during each game. These data increase interest among spectators, but also can be used to quantify the performances of players on the field. The weighted on base average cube model has been used to generate reliable estimates of batter performance using measured batted-ball parameters, but research has shown that running speed is also a determinant of batted-ball performance. In this work, we used machine learning methods to combine a three-dimensional batted-ball vector measured by Doppler radar with running speed measurements generated by stereoscopic optical sensors. We show that this process leads to an improved model for the batted-ball performances of players.

Utilizing Blockchain Technology in Social Media Bot Identification

2020 ◽  
Author(s):  
Shreya Reddy ◽  
Lisa Ewen ◽  
Pankti Patel ◽  
Prerak Patel ◽  
Ankit Kundal ◽  
...  
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
Gold Standard ◽  
The Internet ◽  
Learning Models ◽  
Current Time ◽  
Machine Learning Methods ◽  
Blockchain Technology ◽  
Modern Age ◽  
Machine Learning Models

<p>As bots become more prevalent and smarter in the modern age of the internet, it becomes ever more important that they be identified and removed. Recent research has dictated that machine learning methods are accurate and the gold standard of bot identification on social media. Unfortunately, machine learning models do not come without their negative aspects such as lengthy training times, difficult feature selection, and overwhelming pre-processing tasks. To overcome these difficulties, we are proposing a blockchain framework for bot identification. At the current time, it is unknown how this method will perform, but it serves to prove the existence of an overwhelming gap of research under this area.<i></i></p>

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