System for Fake Currency Detection Using Image Processing

Counterfeit money has always existed an issue that has caused many problems in the market. Technological growth development has made it possible to create extra counterfeit items which are distributed in the mitigation market the global economy. Bangui existing banking equipment and so on trading sites to check the authenticity of funds. But the average person does not do that have access to such systems and that is why they are needed in order for the software to receive counterfeit money, which can be used by ordinary people. This the proposed system uses image processing to find out if the money is real or fake. System built uses the Python system completely language. It contains similar steps grayscale modification, edge detection, separation, etc. made using appropriate methods. Keyword: Counterfeit currency, Image Processing, Python programming language, grayscale conversion, edge detection, segmentation.

РОЗРОБЛЕННЯ ПРОГРАМНОГО ЗАБЕЗПЕЧЕННЯ ДЛЯ ОЦІНЮВАННЯ ОДНОРІДНОСТІ РОЗПОДІЛУ НАПОВНЮВАЧА В ПОЛІМЕРНІЙ МАТРИЦІ

Purpose. Creation of software for evaluating the uniformity of distribution of the filler in a polyethylene matrix.Methodology. Software development was carried out using the Python programming language and libraries: PIL, Numpy, Matplotlib, Xlsxwriter. The suitability of the developed software for use was determined by verifying it. During this verification, polyethylene compositions filled with colloidal graphite in the form of compressed films were evaluated. To obtain these compositions, we chose P6006AD grade polyethylene and C-1 colloidal graphite. Samples of polyethylene compositions were obtained in two stages: 1) obtaining a strand by extrusion; 2) additional mixing of the composition on a disc mixer and pressing the obtained compositions into a film.Findings. The software has been developed to assess the uniformity of the distribution of the filler in the polyethylene matrix. The data were established on the dependence of the coefficient of heterogeneity of polyethylene compositions on the content of colloidal graphite with use of the developed software. The increase in the content of the filler leads to a decrease in its heterogeneity. It is shown that this effect can be explained by the structuring of the filler in the polyethylene matrix. Despite the formation of aggregates in polyethylene compositions, a significant amount of small colloidal particles of graphite is located between the aggregate space. This leads to a certain leveling of the concentration in the film and reduces its inhomogeneity.Scientific novelty. The influence of the content of colloidal graphite on the homogeneity of polyethylene compositions is determined. It is shown that with an increase in the graphite content from 0 to 20% vol. the coefficient of heterogeneity of the composition decreases from 5.3% to 3.9%, which is due to the structuring of the filler in the polyethylene matrix.Practical value. Software that makes it possible to evaluate the uniformity of the distribution of filler particles in a polymer matrix, and can be used to study the quality of mixing of polymer composite materials has been developed.

SYSTEM FOR ANALYSIS, RESEARCH AND FORECAST OF EVENTS IN DISCRETE TIME DATA SEQUENCES

This paper is devoted develop software for time series forecasting using Python programming language. SARIMA model was used to develop the system.

Development of Focused Crawlers for Building Large Punjabi News Corpus

Web crawlers are as old as the Internet and are most commonly used by search engines to visit websites and index them into repositories. They are not limited to search engines but are also widely utilized to build corpora in different domains and languages. This study developed a focused set of web crawlers for three Punjabi news websites. The web crawlers were developed to extract quality text articles and add them to a local repository to be used in further research. The crawlers were implemented using the Python programming language and were utilized to construct a corpus of more than 134,000 news articles in nine different news genres. The crawler code and extracted corpora were made publicly available to the scientific community for research purposes.

Methodology for solving the task no. 8 of the unified state exam in informatics and ICT by a combinatory method and method of programming on python

The article discusses the metodology for solving the task No. 8 of the Unified State Exam in informatics and ICT in two ways: by mathematical combinatorial calculation and writing a program in the Python programming language. The purpose of this methodology is the successful completion of task No. 8 (until 2021 — No. 10) in the Unified State Exam in informatics and ICT by graduates. The article is of an interdisciplinary nature, touches upon issues at the intersection of mathematics and informatics. The relevance of the work is due to the fact that tasks of this type are annually present in the Unified State Exam in informatics and ICT, but the success of this task is too low for tasks of the basic level of complexity. The use of programming tools in the Unified State Exam in informatics and ICT is available starting in 2021. The scientific novelty of the work lies in the use of the Python programming language to solve tasks of this type. The peculiarity of the metodology lies in the gradual increase in the complexity of the algorithms and the "modular" application of parts of the code, which allows using the "modules" of previous tasks to solve subsequent ones. Specific versions of the programs are proposed, a comparative analysis of methods for various prototypes of the corresponding tasks is given. As a result, it was determined that task No. 8 can be effectively solved by the programming method.

APPLICATION OF NEURAL NETWORKS TO DETERMINE THE COORDINATES OF THE SEAT OF FIRE BY MULTIPOINT ELECTRO-OPTICAL SYSTEM

Статья посвящена исследованию методов проектирования интеллектуальных информационных систем и применение моделей искусственных нейронных сетей для диагностического прогнозирования развития пневмонии посредством анализа рентгеновских снимков. В этой работе основное внимание уделяется классификации пневмонии и туберкулеза - двух основных заболеваний грудной клетки - на основе рентгеновских снимков грудной клетки. Данное исследование проводилось при помощи открытой нейросетевой библиотеки Keras и языка программирования Python. Система дает пользователю заключение о том, болен он или нет, тем самым помогая врачам и медицинскому персоналу принять быстрое и информированное решение о наличии заболевания. Разработанная модель, может определить, является ли рентгеновский снимок нормальным или имеет отклонения, которые могут быть пневмонией с точностью 94,87%. Полученные результаты указывают на высокую эффективность применения нейронных сетей при диагностировании пневмонии по рентгеновским снимкам. This paper is devoted to the study of methods of designing intellectual information systems and neural network models application on diagnostic prediction of pneumonia development by X-ray images analysis. This article focuses on the classification of pneumonia and tuberculosis - the two main chest diseases - based on chest x-rays. This study was carried out using the Keras open neural network library and the Python programming language. System returns user a conclusion whether the patient is ill or not helping medical staff to make a quick and informed decision about the presence of the disease. The developed model can determine is the X-ray image normal or has anomalies that can be pneumonia with accuracy up to 94.87%. The results obtained indicate the high performance of the applying neural networks in the diagnosis of pneumonia by X-ray images.

AUTOMATION HR PROCESSES

Статья посвящена изучению эффективных инструментов для автоматизации HR процессов. Чтобы разобраться в современных цифровых технологиях и быстро меняющихся условиях в области HR, специалисту по кадровому производству необходимо интегрировать в свою работу инновационные IT-инструменты, одним из которых является внедрение корпоративного программного обеспечения. Проведено исследование инструментов управления персоналом в условиях глобальной цифровизации, выявлены положительные и отрицательные аспекты автоматизации HR процессов. Рассмотрен вопрос развития автоматизации HR процессов в условиях эпидемиологической ситуации. Приведены наиболее перспективные ИТ-технологии в управлении персоналом. Автоматизация HR процессов экономит время, которое кадровый работник может использовать для выполнения других важных задач. Для этого на языке программирования PYTHON разработан проект извлечения телефонных номеров и адресов электронной почты. Данный проект протестирован на браузере страницы контактов сайта Ykt.ru. The article focuses on the study of effective tools for automating HR processes. To understand modern digital technologies and the rapidly changing environment in the field of HR, an HR specialist needs to integrate innovative IT tools into his work, and one of such tools is the implementation of corporate software. A study of human resources management tools in the context of global digitalization is carried out, the positive and negative aspects of the automation of HR processes are identified. The issue of the development of automation of HR processes in the context of an epidemiological situations is considered. The most promising IT technologies in personnel management are presented. Automating HR processes saves time that an HR worker can use to complete other important tasks. For this purpose, a project for extracting telephone numbers and e-mail addresses has been developed in the Python programming language. This project has been tested on the browser of the contact page of the website of Ykt.ru

Comparative Analysis of the Simple WISP and Some Prominent MCDM Methods: A Python Approach

This article presents a comparison of the results obtained using the newly proposed Simple Weighted Sum Product method and some prominent multiple criteria decision-making methods. For comparison, several analyses were performed using the Python programming language and its NumPy library. The comparison was also made on a real decision-making problem taken from the literature. The obtained results confirm the high correlation of the results obtained using the Simple Weighted Sum Product method and selected multiple criteria decision-making methods such as TOPSIS, SAW, ARAS, WASPAS, and CoCoSo, which confirms the usability of the Simple Weighted Sum Product method for solving multiple criteria decision-making problems.

BUCKLE PROPAGATION OF SANDWICH PIPES UNDER EXTERNAL PRESSURE

Buckle propagation of local collapse appearing in the damaged pipes is one of the failure modes that are of particular interest for deepwater application. The local collapse can propagate along the pipeline for long distances in both directions when the external pressure magnitude is up to the propagation pressure. In this paper, the buckle propagation pressure of sandwich pipes (SP) with different material properties and geometric characteristics is investigated by numerical simulation using Python programming language based on general finite element code. The results of the pressure history data obtained are verified by comparing those published previously. The effect of material properties, geometric characteristics and adhesion conditions on the propagation pressure are analyzed.