OALib Journal
  OALib Journal is an all-in-one open access journal (ISSN Print: 2333-9705, ISSN Online: 2333-9721). It accepts a manuscript for the peer-review processing, typesetting, publication and then allocated to one of the 322 subject areas. The article processing charge for publishing in OALib journal is Only $99. For more details, please contact service@oalib.com. Submit now
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Sep 23, 2020Open    AccessArticle

Parallel Self-Timed Adder with Lookahead-Carry Generator

Mohammad Ashfak Habib
Parallel self-timed adder (PASTA) is a newly introduced asynchronous adder. It shows appreciable average-case performance without any special speedup circuitry or look-ahead schema, but its worst-case performance is almost similar to that of ripple carry adder. It is therefore an important research issue to find a technique to improve its worst-case performance without any significant compromise in its other performances. This paper investigates the possibility of such performance improvement of...
Open Access Library J. Vol.7, 2020
Doi:10.4236/oalib.1106799


Sep 01, 2020Open    AccessArticle

A Smart Robot Training Data Acquisition and Learning Process Recording System Based on Blockchain

Kun Wang, Chen Yang, Tao Wang
The Internet of Things and artificial intelligence have developed rapidly in recent decades, and intelligent robots have been used in various fields of production and life. There are many requirements for the functions, performance and intelligence of smart robots. Many researchers are committed to how intelligent robots can learn more efficiently and develop new functions. How to obtain the learning data while protecting the privacy of users and how to record the learning process are two major ...
Open Access Library J. Vol.7, 2020
Doi:10.4236/oalib.1106711


Aug 25, 2020Open    AccessArticle

Applications of Artificial Intelligence in Combating Covid-19: A Systematic Review

Akpofure A. Enughwure, Isaac C. Febaide
Artificial Intelligence (AI), which has become widely accepted in the medical field over the years, have proven to be valuable in dealing with sicknesses of varying degrees. Following the spread of COVID-19, so many researches have been developed suggesting ways and models to combat the virus by exploring possible diagnosis, treatment, prevention and cure using AI. This research conducted a systematic literature review to unravel the applications of Artificial Intelligence (AI) to tackle the COV...
Open Access Library J. Vol.7, 2020
Doi:10.4236/oalib.1106628


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 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 16, 2020Open    AccessArticle

An Expert System for Diagnosis and Treatment of Mental Ailment

Stanley Ikechukwu Oguoma, Kizito Kanayo Uka, Chekwube Alphonsus Chukwu, Emeka Christian Nwaoha
The stigmatization and the accompanying problems with mentally challenged persons in the third world countries like Nigeria in getting good medication are better imagined than experienced. This paper presents the design, implementation of expert system for the diagnosis and treatment of mental ailment on interactive platform for remote consultation and monitoring of mental health patients within and outside the hospital. The study of the existing system was carried out using Structural System An...
Open Access Library J. Vol.7, 2020
Doi:10.4236/oalib.1106166


Mar 25, 2020Open    AccessArticle

Recurrent Neural Networks and Deep Neural Networks Based on Intrusion Detection System

Rabeb Zarai, Mnaouer Kachout, Mohamed A. G. Hazber, Mohammed A. Mahdi
The computer security has become a major challenge. Tools and mechanisms have been developed to ensure a level of compliance. These include the Intrusion De-tection Systems (IDS). The principle of conventional IDS is to detect attempts to attack a network and to identify abnormal activities and behaviors. The reasons, including the uncertainty in searching for types of attacks and the increasing com-plexity of advanced cyber-attacks, IDS calls for the need for integration of meth-ods such as Dee...
Open Access Library J. Vol.7, 2020
Doi:10.4236/oalib.1106151


Mar 13, 2020Open    AccessArticle

Contribution of Deep Learning Algorithm to Improve Channel Estimation Performance

Lassaad Smirani
In this article, we applied Deep Learning on LTE-A uplink channel estimation system. The work involved creating of two SC-FDMA databases for training and for test, based on three types of channel propagation models. The first section of this work consists of applying an Artificial Neural Network to estimate the channel of SC-FDMA link. Neural Network training is an iterative process which consists on adapting the values of its parameters: weights and bias. After training, the Neural Network was ...
Open Access Library J. Vol.7, 2020
Doi:10.4236/oalib.1106150


Nov 23, 2018Open    AccessArticle

An Investigative Analysis on Mapping X-Ray to Live Using Convolution Neural Networks for Detection of Genu Valgum

Satyake Bakshi
Introduction: Bow Legs and Knock Knees are quite common in growing children, which usually affect the lower portions of the body, however such disorders usually do not have any pathological significance. In this paper, we investigate a method using deep learning to correctly draw a boundary between a physiologically normal knee and a genu valgum. Objective
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Open Access Library J. Vol.5, 2018
Doi:10.4236/oalib.1105009


Sep 30, 2018Open    AccessArticle

Design and Development of High School Artificial Intelligence Textbook Based on Computational Thinking

Yanfang Yu, Yuan Chen
Big data and deep learning technology have once again set off a boom in artificial intelligence. Artificial intelligence has been a major development strategy in many countries. The Chinese government has also written this into the “13th Five-Year Plan”, and the Ministry of Education has also launched with the reform measures for artificial intelligence education, the deep integration of “artificial intelligence education” has b
...
Open Access Library J. Vol.5, 2018
Doi:10.4236/oalib.1104898


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