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The Linkout Plugin for JBrowse 2
JBrowse 2 is a next-generation genome browser that can be run as a web or desktop application. We present a plugin, the Linkout Plugin, that enables users to link features to external databases based on their IDs and the remote URLs on JBrowse 2 desktop or web.
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Image Predictions In Insect Databases Using Single Nucleotide Polymorphism
To the best of our knowledge, no research has utilized machine learning (ML) to study the relationship between genomics and phenotypic imaging. This project explores the potential of ML techniques to predict images of bee wings using single nucleotide polymorphism data.
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Secure Medical Data Management Based on Homomorphic Encryption and Secret Sharing
We propose a cloud storage system that utilizes homomorphic encryption and secret sharing. Our approach enables secure cloud storage of medical data and allows secure data sharing without harming patients’ privacy. A proof-of-concept implementation demonstrates the feasibility of the storage system.
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Taylor Polynomial Enhancer using Genetic Programming for Symbolic Regression
We propose using genetic programming as a Taylor polynomial enhancer, namely TPE-GP, to combine the advantages from TP and GP. Specifically, TPE-GP utilizes infinite-order operators to compensate the power of TP with finite order.
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Programmer Hunter for Game-based e-Learning
Programmer Hunter uses the concept of Monopoly to integrate introductory programming syntax for beginners. It considers elements of uncertainty, control, achievement, cognitive load, and flow in the context of Game-based e-Learning.
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Genetic Programming-based Symbolic Regression for Electric Motor Temperature
We take the temperature of an electric motor as the target parameter and obtain the relationship function by using genetic programming.
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Earthquakes Cluster Applied Ricci Curvature
It’s important to observe earthquake distribution and source properties. In this project, Ricci curvature was used to record and classify earthquakes to know the regional properties. Based on the comparative analysis, the result using Ricci curvature is better than that of Kmeans clustering.
| GitHub
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Learning Model based on Limited Data
I enhenced semi-supervised learning model’s accuracy from 77.4% to 81.2% on MIT-BIH arrhythmia database by integrating data augmentation techniques including feature space and instance space augmentation.
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Evolution algorithms combined with GMM and CMAES for optimization problems
We developed evolution algorithms combined with the gaussian mixture model (GMM) and covariance matrix adaptation evolution strategy (CMAES) on sphere and Rosenbrock problems.
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Membership system
I utilized MySQL, Flask, Python, HTML, and CSS to implement a membership system that allows the company to establish member registration information for performing user-defined data analysis.
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Effects of different fatty liver degrees on health status
We analyzed the effects of different degrees of fatty liver on health status by using canonical correlation analysis, cluster analysis, discriminant analysis, principal components analysis, factor analysis, and regression analysis.
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