A Comprehensive Study Toward Women Safety Using Machine Learning Along with Android App Development

2021 ◽  
pp. 321-330
Author(s):  
Karthik Hariharan ◽  
Rishi Raj Jain ◽  
Anant Prasad ◽  
Mridhul Sharma ◽  
Prashant Yadav ◽  
...  
Keyword(s):  
Machine Learning ◽  
App Development ◽  
Android App ◽  
Comprehensive Study

Plant leaf recognition with shallow and deep learning: A comprehensive study

2020 ◽  
Vol 24 (6) ◽  
pp. 1311-1328
Author(s):  
Jozsef Suto
Keyword(s):  
Machine Learning ◽  
Plant Species ◽  
Research Area ◽  
Research Papers ◽  
Plant Leaf ◽  
Leaf Characteristics ◽  
The Past ◽  
The Earth ◽  
Test Sets ◽  
Comprehensive Study

Nowadays there are hundreds of thousands known plant species on the Earth and many are still unknown yet. The process of plant classification can be performed using different ways but the most popular approach is based on plant leaf characteristics. Most types of plants have unique leaf characteristics such as shape, color, and texture. Since machine learning and vision considerably developed in the past decade, automatic plant species (or leaf) recognition has become possible. Recently, the automated leaf classification is a standalone research area inside machine learning and several shallow and deep methods were proposed to recognize leaf types. From 2007 to present days several research papers have been published in this topic. In older studies the classifier was a shallow method while in current works many researchers applied deep networks for classification. During the overview of plant leaf classification literature, we found an interesting deficiency (lack of hyper-parameter search) and a key difference between studies (different test sets). This work gives an overall review about the efficiency of shallow and deep methods under different test conditions. It can be a basis to further research.

scholarly journals A Comprehensive Study of Artificial Intelligence and Machine Learning Approaches in Confronting the Coronavirus (COVID-19) Pandemic

2021 ◽  
pp. 002073142110174
Author(s):  
Md Mijanur Rahman ◽  
Fatema Khatun ◽  
Ashik Uzzaman ◽  
Sadia Islam Sami ◽  
Md Al-Amin Bhuiyan ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Health Care ◽  
Language Processing ◽  
Probabilistic Models ◽  
Health Care Systems ◽  
Learning Approaches ◽  
Care Systems ◽  
Novel Coronavirus ◽  
Comprehensive Study

The novel coronavirus disease (COVID-19) has spread over 219 countries of the globe as a pandemic, creating alarming impacts on health care, socioeconomic environments, and international relationships. The principal objective of the study is to provide the current technological aspects of artificial intelligence (AI) and other relevant technologies and their implications for confronting COVID-19 and preventing the pandemic’s dreadful effects. This article presents AI approaches that have significant contributions in the fields of health care, then highlights and categorizes their applications in confronting COVID-19, such as detection and diagnosis, data analysis and treatment procedures, research and drug development, social control and services, and the prediction of outbreaks. The study addresses the link between the technologies and the epidemics as well as the potential impacts of technology in health care with the introduction of machine learning and natural language processing tools. It is expected that this comprehensive study will support researchers in modeling health care systems and drive further studies in advanced technologies. Finally, we propose future directions in research and conclude that persuasive AI strategies, probabilistic models, and supervised learning are required to tackle future pandemic challenges.

scholarly journals Investigation of reliability assessement in power electronics circuits using machine learning

2021 ◽  
Vol 12 (1) ◽  
pp. 558
Author(s):  
Soumya Rani Mestha ◽  
Pinto Pius A.J
Keyword(s):  
Machine Learning ◽  
Power Electronics ◽  
New Technologies ◽  
Remaining Useful Life ◽  
Power Electronic ◽  
Electronic Components ◽  
Recent Advances ◽  
Useful Life ◽  
Comprehensive Study

<p>Recent advances in power electronics (PE) and machine learning (ML) have prompted the technologists to adapt these new technologies to improve the reliability of PE systems. During the process, a lot of investigations on the performance and reliability of PE systems is carried out. The intention of this paper is to present a comprehensive study of advances in the field of reliability of PE systems using machine learning. Recent publications in this regard are analysed and findings are tabulated. In addition to this, literatures published in the prediction of remaining useful life (RUL) of power electronic components is discussed with emphasis on its limitations.</p>

scholarly journals Android App Development: A Review

2021 ◽  
Vol 1 (2) ◽  
pp. 1-6
Author(s):  
Anmol Tewari ◽  
Keyword(s):  
Operating System ◽  
Open Source ◽  
Mobile Devices ◽  
Free Software ◽  
Support Programs ◽  
App Development ◽  
Android Platform ◽  
Android App ◽  
Native Code ◽  
Open Standards

Android is a software stack for mobile devices that includes an operating system, middleware, and key applications. Android is a software platform and operating system for mobile devices based on the Linux operating system and developed by Google and the Open Handset Alliance. It allows developers to write managed code in a Java-like language that utilizes Google-developed Java libraries but does not support programs developed in native code. The unveiling of the Android platform on 5 November 2007 was announced with the founding of the Open Handset Alliance, a consortium of 34 hard-ware, software and telecom companies devoted to advancing open standards for mobile devices. When released in 2008, most of the Android platform will be made available under the Apache free-software and open-source license.

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