Difference between revisions of "Team:NEFU China/Software"

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  <p class="meta">
 
  <p class="meta">
 
<span class="cat"><a href="https://2018.igem.org/Team:NEFU_China/Software3">Software 1:</a></span>
 
<span class="cat"><a href="https://2018.igem.org/Team:NEFU_China/Software3">Software 1:</a></span>
−
<span class="date">Software 1's name</span>
+
<span class="date">Coding</span>
 
 
 
</p>
 
</p>
−
  <h1>This is software 1's name!</h1>
+
  <h1>Build Coding Book.</h1>
−
<h1>This is software 1's introduction!</h1>
+
<h1>By using DFS(Depth First Search) algorithm and optimization arithmetic, we find out the correspondence between letters and codons.</h1>
 
  </div>
 
  </div>
 
  </div>
 
  </div>
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  <p class="meta">
 
  <p class="meta">
 
<span class="cat"><a href="https://2018.igem.org/Team:NEFU_China/Software2">Software 2:</a></span>
 
<span class="cat"><a href="https://2018.igem.org/Team:NEFU_China/Software2">Software 2:</a></span>
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<span class="date">Software 2's name</span>
+
<span class="date">Misleading</span>
 
 
 
</p>
 
</p>
−
  <h1>This is software 2's name!</h1>
+
  <h1>Enhance password security.</h1>
−
<h1>This is software 2's introduction!</h1>
+
<h1>We added random sequences, introns, and enzymes to the codon sequences so that the intercepted codon information would not be easily decoded.</h1>
 
  </div>
 
  </div>
 
  </div>
 
  </div>
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  <p class="meta">
 
  <p class="meta">
 
<span class="cat"><a href="https://2018.igem.org/Team:NEFU_China/Software3">Software 3:</a></span>
 
<span class="cat"><a href="https://2018.igem.org/Team:NEFU_China/Software3">Software 3:</a></span>
−
<span class="date">Software 3's name</span>
+
<span class="date">English Word Segment</span>
 
 
 
</p>
 
</p>
−
  <h1>This is software 3's name!</h1>
+
  <h1>Segment English Sentences without Spaces.</h1>
−
<h1>This is software 3's introduction!</h1>
+
<h1>Firstly, we implement word graph scanning based on prefix tree structure and construct DAG(Directed Acyclic Graph) to obtain all English word segmentation results. Secondly, we use IF-IDF(Term Frequency-Inverse Document Frequency) model and maximum sharding method to obtain the optimal word segmentation results. </h1>
 
  </div>
 
  </div>
 
  </div>
 
  </div>
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<h1>Software</h1>
 
<h1>Software</h1>
 
<p>
 
<p>
−
So far, the national trends in costs for wages, salaries, and benefits have glossed over these concerns. The growth in labor costs continued to slow in the second quarter - a pattern that held true in all major regions. However, the slowdown in labor costs is due solely to sharp cutbacks in what companies, mainly large corporations, are paying for benefits, which make up about a fourth of total compensation costs nationally. Because of slower growth in health care costs, workers' compensation, and state unemployment insurance, benefits grew only 2.6% during the past year, the lowest pace on record.<br>
+
We develop the Encrypt & Decrypt software. By using DFS(Depth First Search) algorithm and optimization arithmetic, we find out the correspondence between letters and codons. The heart of our software is the Misleading module. By adding enzymes and introns to genes, we complicate the sequences and increase the security of our Coding Book. During the decryption period, we use regular expressions to match useless enzymes and introns, eliminating them and converting the rest of codons into letters. What’s more, we write the information of codons and letters into the picture as a qr code and users can scan the qr code to get this information.<br>
−
But since few have marked down their own prices in line with the metal's fall, they will be able to recoup much of the difference. Not so the producers, whose income is directly related to the fluctuating daily price on the London Metal Exchange.<br>
+
            We also develop English Word Segmentation software. Firstly, we implement word graph scanning based on prefix tree structure and construct DAG(Directed Acyclic Graph) to obtain all English word segmentation results. Secondly, we use IF-IDF(Term Frequency-Inverse Document Frequency) model and maximum sharding method to obtain the optimal word segmentation results.  
−
The Japanese have their electronics, the Germans their engineering. But when it comes to command of global markets, the U.S. owns the service sector.<br>
+
−
Meanwhile, pressure has been growing from the car companies. GM ships about 60% of its cars and trucks with Ryder, while Chrysler ships some 40%.<br>
+
−
First of all, current modest demand growth will not support any more increases that large. Second, now that manufacturers have worked to get their inventories lower, they will be cautious about adding goods in coming months.<br>
+
  
 
</p>
 
</p>
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<p class="meta">
 
<p class="meta">
 
<span class="cat"><a href="https://2018.igem.org/Team:NEFU_China/Software1">Software 1</a></span>
 
<span class="cat"><a href="https://2018.igem.org/Team:NEFU_China/Software1">Software 1</a></span>
−
<span class="date">Software 1's name</span>
+
<span class="date">Coding</span>
 
 
 
</p>
 
</p>
−
<h2><a href="https://2018.igem.org/Team:NEFU_China/Software1">Software 1's name</a></h2>
+
<h2><a href="https://2018.igem.org/Team:NEFU_China/Software1">Build Coding Book.</a></h2>
−
<p>Software 1's introduction.</p>
+
<p>By using DFS(Depth First Search) algorithm and optimization arithmetic, we find out the correspondence between letters and codons.</p>
 
</div>
 
</div>
 
</div>
 
</div>
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<p class="meta">
 
<p class="meta">
 
<span class="cat"><a href="https://2018.igem.org/Team:NEFU_China/Software2">Software 2</a></span>
 
<span class="cat"><a href="https://2018.igem.org/Team:NEFU_China/Software2">Software 2</a></span>
−
<span class="date">Software 2's name</span>
+
<span class="date">Misleading</span>
 
 
 
</p>
 
</p>
−
<h2><a href="https://2018.igem.org/Team:NEFU_China/Software2">Software 2's name</a></h2>
+
<h2><a href="https://2018.igem.org/Team:NEFU_China/Software2">Enhance password security.</a></h2>
−
<p>Software 2's introduction.</p>
+
<p>We added random sequences, introns, and enzymes to the codon sequences so that the intercepted codon information would not be easily decoded.</p>
 
</div>
 
</div>
 
</div>
 
</div>
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<p class="meta">
 
<p class="meta">
 
<span class="cat"><a href="https://2018.igem.org/Team:NEFU_China/Software3">Software 3</a></span>
 
<span class="cat"><a href="https://2018.igem.org/Team:NEFU_China/Software3">Software 3</a></span>
−
<span class="date">Software 3's name</span>
+
<span class="date">English Word Segment</span>
 
 
 
</p>
 
</p>
−
<h2><a href="https://2018.igem.org/Team:NEFU_China/Software3">Software 3's name</a></h2>
+
<h2><a href="https://2018.igem.org/Team:NEFU_China/Software3">Segment English Sentences without Spaces.</a></h2>
−
<p>Software 3's introduction.</p>
+
<p>Firstly, we implement word graph scanning based on prefix tree structure and construct DAG(Directed Acyclic Graph) to obtain all English word segmentation results. Secondly, we use IF-IDF(Term Frequency-Inverse Document Frequency) model and maximum sharding method to obtain the optimal word segmentation results. </p>
 
</div>
 
</div>
 
</div>
 
</div>

Revision as of 13:17, 15 October 2018

Software Overview

Software

We develop the Encrypt & Decrypt software. By using DFS(Depth First Search) algorithm and optimization arithmetic, we find out the correspondence between letters and codons. The heart of our software is the Misleading module. By adding enzymes and introns to genes, we complicate the sequences and increase the security of our Coding Book. During the decryption period, we use regular expressions to match useless enzymes and introns, eliminating them and converting the rest of codons into letters. What’s more, we write the information of codons and letters into the picture as a qr code and users can scan the qr code to get this information.
We also develop English Word Segmentation software. Firstly, we implement word graph scanning based on prefix tree structure and construct DAG(Directed Acyclic Graph) to obtain all English word segmentation results. Secondly, we use IF-IDF(Term Frequency-Inverse Document Frequency) model and maximum sharding method to obtain the optimal word segmentation results.

html5 bootstrap template

Software 1 Coding

Build Coding Book.

By using DFS(Depth First Search) algorithm and optimization arithmetic, we find out the correspondence between letters and codons.

html5 bootstrap template

Software 2 Misleading

Enhance password security.

We added random sequences, introns, and enzymes to the codon sequences so that the intercepted codon information would not be easily decoded.

html5 bootstrap template

Software 3 English Word Segment

Segment English Sentences without Spaces.

Firstly, we implement word graph scanning based on prefix tree structure and construct DAG(Directed Acyclic Graph) to obtain all English word segmentation results. Secondly, we use IF-IDF(Term Frequency-Inverse Document Frequency) model and maximum sharding method to obtain the optimal word segmentation results.

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Contact us

iGEM-NEFU_China2018

Email: hexinglu@nefu.edu.cn

No.26 Hexing Road, Xiangfang
District, Harbin, Heilongjiang
Province 150000