scholarly journals Autistic Savants and Mathematical sequence prediction.

2021 ◽  
Author(s):  
Anil Kumar Bheemaiah
Keyword(s):  
Data Mining ◽  
Mental Arithmetic ◽  
Branch Prediction ◽  
Sequence Prediction ◽  
The Third ◽  
Prediction Algorithms ◽  
Mental Exercise

In the third paper in a series of papers on autism savants, detection of giftedness and the use of mental arithmetic as an intervention in autism and a practice of metal wellness, we describe the use of python scripts towards primality detection exercises, of both small primes and arbitrary sized numbers and several other exercises including sequence prediction, inspired by branch prediction architectures. Sequence prediction as a mental exercise, is used as infotainment and as a wellness exercise, and a possible intervention in ASD. Several prediction mechanisms inspired by data and prediction algorithms are described. Keywords: ASD, Autism Savants, Education For The Gifted, primality detection, data mining, basket of associations, sequences, branch prediction, plotting graphs.

Calculators and the slack channel as a Math-Code Gym

2020 ◽  
Author(s):  
Anil Kumar Bheemaiah
Keyword(s):  
Data Mining ◽  
Number Theory ◽  
Prime Number ◽  
Mental Arithmetic ◽  
Branch Prediction ◽  
Sequence Prediction

The Numworks/TI-84 python calculator, which encapsulates, functionality ranging from a python shell, to built in and customisable support for statistics, functions, regression, sequences and data mining, is directly amenable to a functionality as a math and code gym towards mental arithmetic and several number theory based therapies, such as prime number therapy. Similar functionality is achieved on the slack channel, with the Wolfram Alpha API.In this paper we describe the use of python scripts towards primality detection exercises, of both small primes and arbitrary sized numbers and several other exercises including sequence prediction, inspired by branch prediction architectures, plotting functions and exercises in data mining, in spotting patterns and forming a basket of associations.Keywords: Numworks, Math and code gym, primality detection, data mining, basket of associations, sequences, branch prediction, plotting graphs.

scholarly journals Toward improved branch prediction through data mining.

2009 ◽  
Author(s):  
K. Scott Hemmert ◽  
D. Eric Johnson
Keyword(s):  
Data Mining ◽  
Branch Prediction

scholarly journals Application of Text Message Held in Image Using Combination of Least Significant Bit Method and One Time Pad

2019 ◽  
Vol 13 (4) ◽  
pp. 323
Author(s):  
Eferoni Ndruru ◽  
Taronisokhi Zebua
Keyword(s):  
Data Mining ◽  
Association Rules ◽  
Data Hiding ◽  
Text Message ◽  
Third Party ◽  
Least Significant Bit ◽  
Market Basket Analysis ◽  
Market Basket ◽  
Sales Data ◽  
The Third

Stenography and security are one of the techniques to develop art in securing data. Stenography has the most important aspect is the level of security in data hiding, which makes the third party unable to detect some information that has been secured. Usually used to hide textinformationThe (LSB) algorithm is one of the basic algorithms proposed by Arawak and Giant in 1994 to determine the frequent item set for Boolean association rules. A priory algorithm includes the type of association rules in data mining. The rule that states associations between attributes are often called affinity analysis or market basket analysis. OTP can be widely used in business. With the knowledge of text message, concealment techniques will make it easier for companies to know the number of frequencies of sales data, making it easier for companies to take an appropriate transaction action. The results of this study, hide the text message on the image (image) by using a combination of LSB and Otp methods.

A new approach for predicting crop yield prediction using data mining techniques

2019 ◽  
Author(s):  
Surya A. Venkaiah ◽  
Surya A. Venkaiah ◽  
Kondajji Swati Sunitha
Keyword(s):  
Data Mining ◽  
Climatic Conditions ◽  
Random Forest Algorithm ◽  
New Approach ◽  
Agriculture Sector ◽  
Prediction Algorithms ◽  
Indian Agriculture ◽  
Using Data ◽  
Prediction Techniques ◽  
Day By Day

Agriculture is the most important sector of Indian Economy. Indian agriculture sector accounts for 18 per cent of India's gross domestic product (GDP) and provides employment to 50% of the countries workforce. We all know agriculture is the most important factor which influence the economy of India and it also offers employment to 50% population of India. People of India are practicing agriculture for many years and the result were never satisfying due to many factors that affect the crop. Day by day environment is changing and is not stable at various places. It is very important for the farmer to cultivate their farm in good climatic conditions, under such conditions they need technology that predict the environment. In such cases data mining is the apt technology for prediction. Data mining contains various prediction algorithms like id3, cart, c4.5, random forest algorithm. In this Project we are using Id3 and cart algorithms as a prediction techniques and it is possible obtain the information from the prediction algorithms which helps farmers to cultivate the appropriate crop. Available online at https://int-scientific-journals.com

How to Achieve Fuzzy Relational Databases Managing Fuzzy Data and Metadata

2011 ◽  
pp. 351-380 ◽  
Author(s):  
Mohamed Ali Ben Hassine ◽  
Amel Grissa Touzi ◽  
José Galindo ◽  
Habib Ounelli
Keyword(s):  
Data Mining ◽  
Relational Databases ◽  
Fuzzy Data ◽  
Imprecise Data ◽  
The Third ◽  
Fuzzy Database ◽  
Existing Data ◽  
Flexible Querying ◽  
Mining Tools ◽  
Total Migration

Fuzzy relational databases have been introduced to deal with uncertain or incomplete information demonstrating the efficiency of processing fuzzy queries. For these reasons, many organizations aim to integrate flexible querying to handle imprecise data or to use fuzzy data mining tools, minimizing the transformation costs. The best solution is to offer a smooth migration towards this technology. This chapter presents a migration approach from relational databases towards fuzzy relational databases. This migration is divided into three strategies. The first one, named “partial migration,” is useful basically to include fuzzy queries in classic databases without changing existing data. It needs some definitions (fuzzy metaknowledge) in order to treat fuzzy queries written in FSQL language (Fuzzy SQL). The second one, named “total migration,” offers in addition to the flexible querying, a real fuzzy database, with the possibility to store imprecise data. This strategy requires a modification of schemas, data, and eventually programs. The third strategy is a mixture of the previous strategies, generally as a temporary step, easier and faster than the total migration.

Sentiment Evolution Analysis and Association Rule Mining for COVID-19 Tweets

2021 ◽  
Vol 2 (2) ◽  
pp. 3-21
Author(s):  
Yassine Drias ◽  
Habiba Drias
Keyword(s):  
Data Mining ◽  
Social Media ◽  
Sentiment Analysis ◽  
Association Rule ◽  
Association Rule Mining ◽  
Early Stage ◽  
Rule Mining ◽  
Virus Propagation ◽  
The Third ◽  
Evolution Analysis

This article presents a data mining study carried out on social media users in the context of COVID-19 and offers four main contributions. The first one consists in the construction of a COVID-19 dataset composed of tweets posted by users during the first stages of the virus propagation. The second contribution offers a sample of the interactions between users on topics related to the pandemic. The third contribution is a sentiment analysis, which explores the evolution of emotions throughout time, while the fourth one is an association rule mining task. The indicators determined by statistics and the results obtained from sentiment analysis and association rule mining are eloquent. For instance, signs of an upcoming worldwide economic crisis were clearly detected at an early stage in this study. Overall results are promising and can be exploited in the prediction of the aftermath of COVID-19 and similar crisis in the future.

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