scholarly journals Software Service with a Plug-in Architecture for Text Readability Assessment

2021 ◽  
Vol 6 (1) ◽  
pp. 77-85
Author(s):  
Bohdan Tsebryk ◽  
◽  
Alexey Botchkaryov
Keyword(s):  
Natural Language ◽  
Programming Language ◽  
Python Programming Language ◽  
Text Readability ◽  
Software Service ◽  
Python Programming ◽  
Readability Assessment

The problem of developing a software service with a plug-in architecture for assessing the readability of text has been considered. The problem of text readability assessment has been analyzed. Approaches to the development of a software service for text readability assessment have been considered. The structure of the service for text readability assessment has been proposed. The structure of the service has been implemented using the Python programming language and the library Natural Language Toolkit (NLTK). The results of testing the service for text readability assessment have been presented.

Practical Programming for NLP

2012 ◽  
pp. 122-156
Author(s):  
Patrick Jeuniaux ◽  
Andrew Olney ◽  
Sidney D’Mello
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Programming Language ◽  
Language Processing ◽  
Python Programming Language ◽  
Programming Tools ◽  
Python Programming

This chapter is aimed at students and researchers who are eager to learn about practical programmatic solutions to natural language processing (NLP) problems. In addition to introducing the readers to programming basics, programming tools, and complete programs, we also hope to pique their interest to actively explore the broad and fascinating field of automatic natural language processing. Part I introduces programming basics and the Python programming language. Part II takes a step by step approach in illustrating the development of a program to solve a NLP problem. Part III provides some hints to help readers initiate their own NLP programming projects.

Application of Convolutional Neural Network (CNN) for the Prediction of Spam Mail

2021 ◽  
Vol 28 (1) ◽  
Author(s):  
C.I. Ejiofor ◽  
L.C. Ochei
Keyword(s):  
Neural Network ◽  
Natural Language ◽  
Convolutional Neural Network ◽  
Programming Language ◽  
Financial Cost ◽  
Training Time ◽  
Python Programming Language ◽  
Value Loss ◽  
The Rich ◽  
Python Programming

Spam mail has indeed become a global dilemma due to its coevolutionary nature. It has resulted in the loss of organizational resources, possibly financial cost incurred as well as time spent in addressing spam related issues. This has pushed organizations and researchers to the pinnacle of research with the aim of identifying needed solutions. This research paper explores the rich capabilities of Convolutional Neural Network (CNN) for predicting spam mail taking cognizant natural language capabilities. Spam mail prediction was simulated using a simulator built utilizing python programming language to capture the fundamentals of CNN. The CNN training was actualized using 10 epochs. The 1st epoch offers a training time of 4mins, 39s with a loss of 1.7578, accuracy of 0.3508, value loss of 1.2130 and value accuracy 0f 0.5719 while the 10th epoch presents a training time of 4mins, 6s with a loss of 0.5896, accuracy of 0.7936, value loss of 0.8941 and value accuracy of 0.6986.

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.

scholarly journals New implementation of OGC Web Processing Service in Python programming language. PyWPS-4 and issues we are facing with processing of large raster data using OGC WPS

2016 ◽  
Vol XLI-B7 ◽  
pp. 927-930 ◽  
Author(s):  
Jáchym Čepický ◽  
Luís Moreira de Sousa
Keyword(s):  
Programming Language ◽  
Binary Data ◽  
Security Risks ◽  
Raster Data ◽  
Server Side ◽  
Python Programming Language ◽  
Technical Issues ◽  
Numeric Representation ◽  
Python Programming ◽  
Processing Service

The OGC® Web Processing Service (WPS) Interface Standard provides rules for standardizing inputs and outputs (requests and responses) for geospatial processing services, such as polygon overlay. The standard also defines how a client can request the execution of a process, and how the output from the process is handled. It defines an interface that facilitates publishing of geospatial processes and client discovery of processes and and binding to those processes into workflows. Data required by a WPS can be delivered across a network or they can be available at a server. <br><br> PyWPS was one of the first implementations of OGC WPS on the server side. It is written in the Python programming language and it tries to connect to all existing tools for geospatial data analysis, available on the Python platform. During the last two years, the PyWPS development team has written a new version (called PyWPS-4) completely from scratch. <br><br> The analysis of large raster datasets poses several technical issues in implementing the WPS standard. The data format has to be defined and validated on the server side and binary data have to be encoded using some numeric representation. Pulling raster data from remote servers introduces security risks, in addition, running several processes in parallel has to be possible, so that system resources are used efficiently while preserving security. Here we discuss these topics and illustrate some of the solutions adopted within the PyWPS implementation.

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