scholarly journals An Unmanned Aerial Vehicle for Parking Slot Availability

2020 ◽  
Author(s):  
Anil Mallidi ◽  
Sabah Mohammed
Keyword(s):  
Computer Vision ◽  
Unmanned Aerial Vehicle ◽  
Programming Language ◽  
Research Project ◽  
Python Programming Language ◽  
Parking Lot ◽  
Aerial Vehicle ◽  
Python Programming

This is a research project which uses computer vision techniques to find out the empty parking spaces in any given Parking lot. It uses existing functions from OpenCV library in Python programming language to extract the parking lines from an image.

scholarly journals An Unmanned Aerial Vehicle for Parking Slot Availability

2020 ◽  
Author(s):  
Anil Mallidi ◽  
Sabah Mohammed
Keyword(s):  
Computer Vision ◽  
Unmanned Aerial Vehicle ◽  
Programming Language ◽  
Research Project ◽  
Python Programming Language ◽  
Parking Lot ◽  
Aerial Vehicle ◽  
Python Programming

This is a research project which uses computer vision techniques to find out the empty parking spaces in any given Parking lot. It uses existing functions from OpenCV library in Python programming language to extract the parking lines from an image.

scholarly journals Development of Computer Vision Applications to Automate the Measurement of the Dimensions of Skin Wounds

Proceedings ◽  
2019 ◽  
Vol 19 (1) ◽  
pp. 18
Author(s):  
David Sánchez-Jiménez ◽  
Fernando Buchón-Moragues ◽  
Begoña Escutia-Muñoz ◽  
Rafael Botella-Estrada
Keyword(s):  
Computer Vision ◽  
Real Time ◽  
Programming Language ◽  
Three Dimensional ◽  
Skin Wounds ◽  
Two Dimensional ◽  
Python Programming Language ◽  
Computer Vision Applications ◽  
Python Programming

This paper shows the progress in the development of two computer vision applications for measuring skin wounds. Both applications have been written in Python programming language and make use of OpenCV and Scipy open source libraries. Their objective is to be part of a software that calculates the dimensions of skin wounds in an objective and reliable way. This could be useful in the clinical follow-up, assessing the evolution of skin wounds, as well as in research, comparing the efficacy of different treatments. Merging these two applications into a single one would allow to generate two-dimensional results in real time, and three-dimensional results after a few hours of processing.

A Python application to generate digital signals

2020 ◽  
Vol 65 (1) ◽  
pp. 96-104
Author(s):  
Tatian-Cristian Mălin
Keyword(s):  
Numerical Simulation ◽  
Programming Language ◽  
Digital Signals ◽  
Python Programming Language ◽  
Python Programming

We introduce in this paper an application developed in the Python programming language that can be used to generate digital signals with known frequencies and amplitudes. These digital signals, since have known parameters, can be used to create benchmarks for test and numerical simulation.

An Open Source Finance System for Stocks Backtesting Trade Strategies

2021 ◽  
Vol 12 (2) ◽  
pp. 52-65
Author(s):  
Eviatar Rosenberg ◽  
Dima Alberg
Keyword(s):  
User Interface ◽  
Open Source ◽  
Programming Language ◽  
Capital Market ◽  
Historical Data ◽  
Trading Strategies ◽  
Market Volatility ◽  
Finance System ◽  
Python Programming Language ◽  
Python Programming

A significant part of pension savings is in the capital market and exposed to market volatility. The COVID-19 pandemic crisis, like the previous crises, damaged the gains achieved in those funds. This paper presents a development of open-source finance system for stocks backtesting trade strategies. The development will be operated by the Python programming language and will implement application user interface. The system will import historical data of stocks from financial web and will produce charts for analysis of the trends in stocks price. Based on technical analysis, it will run trading strategies which will be defined by the user. The system will output the trade orders that should have been executed in retrospect and concluding charts to present the profit and loss that would occur to evaluate the performance of the strategy.

scholarly journals ATLaS: Assistant Software for Life Scientists to Use in Calculations of Buffer Solutions

2021 ◽  
Vol 15 (4) ◽  
pp. 541-545
Author(s):  
Ugur Comlekcioglu ◽  
Nazan Comlekcioglu
Keyword(s):  
Programming Language ◽  
Life Science ◽  
Source Code ◽  
Experimental Results ◽  
Acid Base ◽  
Buffer Solutions ◽  
Python Programming Language ◽  
Science Laboratories ◽  
Executable File ◽  
Python Programming

Many solutions such as percentage, molar and buffer solutions are used in all experiments conducted in life science laboratories. Although the preparation of the solutions is not difficult, miscalculations that can be made during intensive laboratory work negatively affect the experimental results. In order for the experiments to work correctly, the solutions must be prepared completely correctly. In this project, a software, ATLaS (Assistant Toolkit for Laboratory Solutions), has been developed to eliminate solution errors arising from calculations. Python programming language was used in the development of ATLaS. Tkinter and Pandas libraries were used in the program. ATLaS contains five main modules (1) Percent Solutions, (2) Molar Solutions, (3) Acid-Base Solutions, (4) Buffer Solutions and (5) Unit Converter. Main modules have sub-functions within themselves. With PyInstaller, the software was converted into a stand-alone executable file. The source code of ATLaS is available at https://github.com/cugur1978/ATLaS.

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