Difference between revisions of "Template:SYSU-Software/statics/html/Projects/Techniques.html"
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<div class="header1"> Projects </div> | <div class="header1"> Projects </div> | ||
| − | <div class="header2"> Techniques </div> | + | <div class="header2"> Techniques & Search Algorithm </div> |
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In consideration of the stable, robust and friendly performance of Django with Python 3, we | In consideration of the stable, robust and friendly performance of Django with Python 3, we | ||
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logic behind beautiful widgets using jQuery. Some other open-source JavaScript libraries are also used, such as | logic behind beautiful widgets using jQuery. Some other open-source JavaScript libraries are also used, such as | ||
Chart.js and echart.js for displaying chart, jsPlumb for showing the relationships in circuit in the design page, | Chart.js and echart.js for displaying chart, jsPlumb for showing the relationships in circuit in the design page, | ||
| − | etc... jQuery and CSS3 was used to build the interesting game 'Little tomato with big dreams', hope you will enjoy it! | + | etc... jQuery and CSS3 was used to build the interesting game 'Little tomato with big dreams', hope you will enjoy |
| + | it! | ||
</div> | </div> | ||
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| − | < | + | <div class="tech"> |
| − | < | + | <img src="https://static.igem.org/mediawiki/2018/4/49/T--SYSU-Software--sqlite.png"> |
| − | < | + | <img src="https://static.igem.org/mediawiki/2018/0/02/T--SYSU-Software--djangopython.png"> |
| + | <img src="https://static.igem.org/mediawiki/2018/0/08/T--SYSU-Software--tf.png"> | ||
| + | </div> | ||
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| + | <div class="header3"> Search Algorithm </div> | ||
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| + | As is known to us, the users of our software are all innovative researchers who are interested in utilizing | ||
| + | Synthetic Biology to tackle many different real-world problems. The purpose of our system is to recommend the most | ||
| + | related projects to the users based on their research interests detected by our system. | ||
| + | </div> | ||
| + | |||
| + | <div class="content"> | ||
| + | When it comes to the advanced algorithms behind our project, we mainly use Python3 to implete the Ball Tree, | ||
| + | Word2Vec, Encoder-Decoder model and so forth in Machine Learning. As for the powerful Search & Recommendation | ||
| + | system, we mainly use TensorFlow, an open source software library for high performance numerical computation, to | ||
| + | train 2 Deep Neural Networks for a great many of times. Moreover, the collaborative filtering framework enables | ||
| + | users to get accurate recommendation after offering their interest to our system, which is based on a database | ||
| + | powered by Deep Neural Network. | ||
| + | </div> | ||
| + | |||
| + | <img src="https://static.igem.org/mediawiki/2018/c/cc/T--SYSU-Software--modelTech.png"> | ||
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</div> | </div> | ||
Latest revision as of 15:24, 17 October 2018
Projects
Techniques & Search Algorithm
Techniques
In consideration of the stable, robust and friendly performance of Django with Python 3, we chose it as the back-end for CO-RAD, a web application; Sqlite3 with Django models binding gives us a lighter but still powerful database support; For front-end, we build the view with customized Semantic UI, and control the logic behind beautiful widgets using jQuery. Some other open-source JavaScript libraries are also used, such as Chart.js and echart.js for displaying chart, jsPlumb for showing the relationships in circuit in the design page, etc... jQuery and CSS3 was used to build the interesting game 'Little tomato with big dreams', hope you will enjoy it!
<img src=""> <img src="
"> <img src="
">
Search Algorithm
As is known to us, the users of our software are all innovative researchers who are interested in utilizing Synthetic Biology to tackle many different real-world problems. The purpose of our system is to recommend the most related projects to the users based on their research interests detected by our system.
When it comes to the advanced algorithms behind our project, we mainly use Python3 to implete the Ball Tree, Word2Vec, Encoder-Decoder model and so forth in Machine Learning. As for the powerful Search & Recommendation system, we mainly use TensorFlow, an open source software library for high performance numerical computation, to train 2 Deep Neural Networks for a great many of times. Moreover, the collaborative filtering framework enables users to get accurate recommendation after offering their interest to our system, which is based on a database powered by Deep Neural Network.
<img src="">