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Jun 17, 2020Open    AccessArticle

Research Progress of Automatic Question Answering System Based on Deep Learning

Shiyao Zhao, Zhezhi Jin
With the rapid development of deep learning, a large number of machine reading comprehension models based on deep learning have emerged. Firstly, the paper points out the shortcomings of traditional search engines and explains the advantages of automatic question answering systems compared with them. Secondly, it summarizes the development process of the deep learning-based machine reading comprehension model, and expounds the overall framework and operation principle of the model, as well as th...
Open Access Library J. Vol.7, 2020
Doi:10.4236/oalib.1106046


May 13, 2020Open    AccessArticle

Enhanced Power and Ground Mesh Structure for IR-Drop Reduction

Vakhtang Janpoladov, Suren Abazyan
New enhanced power/ground mesh structure is presented for voltage drop (IR drop) reduction on power distribution network in integrated circuits (ICs). The new structure focuses on the length of the overall power/ground mesh wire pattern, reducing it by using a complex dotted line wire pattern instead of the usual mesh straps, which brings to wire length reduction on almost 40%, while via count on changed metal layer remained the same. Measurements of the voltage drop prove that with proposed mes...
Open Access Library J. Vol.7, 2020
Doi:10.4236/oalib.1106334


May 11, 2020Open    AccessArticle

Deep Learning Convolution Neural Network to Detect and Classify Tomato Plant Leaf Diseases

Thair A. Salih, Ahmed J. Ali, Mohammed N. Ahmed
The tomato crop is an important staple in the ?market and it is one of the most common crops daily ?consumed. Plant or crop diseases cause reduction of quality and quantity of the production; therefore detection and classification of these diseases are very necessary. There are many types of diseases that infect ?tomato plant like (bacterial spot, late blight, sartorial leaf ?spot, tomato mosaic and yellow curved). Early detection of plant diseases increases production and improves its quality. ...
Open Access Library J. Vol.7, 2020
Doi:10.4236/oalib.1106296


Apr 27, 2020Open    AccessArticle

Interlanguage Translation Utility with Integrated Machine Learning Algorithms

Suren Abazyan, Narek Mamikonyan, Vakhtang Janpoladov
Same program can be written in different programming languages and different ways. One programming language will have advantages and disadvantages compared to another; hence sometimes it is needed to rewrite the code into another language to support this or that functionality. This paper demonstrates an algorithm of interlanguage translator, which is using intended machine learning (ML) algorithms to ensure higher translation rate. In the scope of research, too
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Open Access Library J. Vol.7, 2020
Doi:10.4236/oalib.1106318


Apr 24, 2020Open    AccessArticle

Multi-Memory Grouping Wrapper with Top Level BIST Algorithm

Narek Mamikonyan, Suren Abazyan, Vakhtang Janpoladov
This algorithm integrates second level Built in self-test (BIST) into multiple memory grouping wrapper. Second level BIST brings additional reliability into memory system while fastening testing time. Main approach is to test whole memory modules from top level by numerous step count of which can be modified based on power consumption requirement and overheat conditions. The worst case of the algorithm can be observed by the time when number of steps is equal to the number of memory modules, oth...
Open Access Library J. Vol.7, 2020
Doi:10.4236/oalib.1106294


Apr 17, 2020Open    AccessArticle

Unsupervised Feature Selection Based on Low-Rank Regularized Self-Representation

Wenyuan Li, Lai Wei
Feature selection aims to find a set of features that are concise and have good generalization capabilities by removing redundant, uncorrelated, and noisy features. Recently, the regularized self-representation (RSR) method was proposed for unsupervised feature selection by minimizing the L2,1 norm of residual matrix and self-representation coefficient matrix. In this paper, we find that minimizing the L2,1 norm of the self-representation coefficient matrix cannot effectively extract the feature...
Open Access Library J. Vol.7, 2020
Doi:10.4236/oalib.1106274


Apr 14, 2020Open    AccessArticle

Using Cellular Agents (CA) to Prove Kurzweil’s Law of Accelerating Returns (LOAR) Wrong When Using a Series of Paradigm Shifts Trying to Maintain Exponential Growth

Luis F. Copertari
Objective: To prove LOAR wrong with a mathematical and algorithmically designed experiment. Methodology: Using changes from one to two to three to four to five and to six dimensions as paradigm shifts when CA growth occurs. Results: A series of S-curves are obtained and the actual growth of CA is shown. Limitation: The results could not be continued due to the experimental design used. Conclusion: There is evidence against a continued exponential growth even with paradigm shifts being considered...
Open Access Library J. Vol.7, 2020
Doi:10.4236/oalib.1106255


Apr 08, 2020Open    AccessArticle

Standard Cell Placement Optimization Using Quadratic Placement Algorithm

Suren Abazyan, Narek Mamikonyan, Vakhtang Janpoladov
Designs including tens of millions of standard cells in one chip are commonly used in current IC projects, so finding optimal location on a chip surface for each logic cell is a very important step in IC design. Apart from finding room for logic cell placement with minimum chip area, length of connecting wires is also playing big role and needs to be taken under control. In this paper, research and implementation of standard cell placement-optimizations’ quadratic algorithm is described. Main re...
Open Access Library J. Vol.7, 2020
Doi:10.4236/oalib.1106218


Jan 08, 2020Open    AccessArticle

Static IR Drop Estimation on the Power Network

S. S. Abazyan, N. E. Mamikonyan
This paper presents a power consumption estimation algorithm for static analysis. IR drop is being calculated for each separated node, which makes this algorithm favorable for IR drop calculation on infinite power network. The power consumption is being calculated using random walk algorithm, which includes Monte Carlo simulation method for increasing accuracy of estimation. For power mesh with 150 k power nodes, total IR drop cal
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Open Access Library J. Vol.7, 2020
Doi:10.4236/oalib.1105995


Jun 28, 2019Open    AccessArticle

Establishment of the Docker-Based Laboratory Environment

Fang Hu, Shijun Che
At present, part of the experimental environment of computer science courses and the software development environment of the school are built based on virtual machines. As the number of students rapidly increases, the demand for virtual machines goes up correspondingly. Virtual machines consume a lot of resources, and the shortage of resources becomes the bottleneck of laboratory construction. According to the current situation of
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Open Access Library J. Vol.6, 2019
Doi:10.4236/oalib.1105519


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