python language
Recently Published Documents


TOTAL DOCUMENTS

228
(FIVE YEARS 148)

H-INDEX

8
(FIVE YEARS 4)

2022 ◽  
Author(s):  
Sertaç Yaman ◽  
Barış Karakaya ◽  
yavuz erol

Abstract COVID-19 is still a fatal disease, which has threatened all people by affecting the human lungs. Chest X-Ray or computed tomography (CT) imaging is commonly used to make a fast and reliable medical investigation to detect the COVID-19 virus from these medical images is remarkably challenging because it is a full-time job and prone to human errors. In this paper, a new normalization algorithm that consists of Mean-Variance-Softmax-Rescale (MVSR) processes respectively is proposed to provide facilitation pre-assessment and diagnosis Covid-19 disease. In order to show the effect of MVSR normalization technique on image processing, the algorithm is applied to chest X-ray images. Therefore, the normalized X-ray images with MVSR are used to recognize via one of the neural network models as known Convolutional Neural Networks (CNNs). At the implementation stage, the MVSR algorithm is executed on MATLAB environment, then it is implemented on FPGA platform. All the arithmetic operations of the MVSR normalization are coded in VHDL with the help of fixed-point fractional number representation format. The experimental platform consists of Zynq-7000 Development Board and VGA monitor to display the both original X-ray and MVSR normalized image. The CNN model is constructed and executed using Anaconda Navigator interface with python language. Based on the results of this study, infections of Covid-19 disease can be easily diagnosed for MVSR normalized image. The proposed MVSR normalization makes the accuracy of CNN model increase from 83.01%, to 96.16% for binary class of chest X-ray images.


2022 ◽  
pp. 842-858
Author(s):  
Segun Aina ◽  
Samuel Dayo Okegbile ◽  
Perfect Makanju ◽  
Adeniran Ishola Oluwaranti

The need to remotely control home appliances is an important aspect of home automation and is now receiving lot of attentions in the literature. The works so far are still at a development level making further research necessary. This article presents a framework for chatbot-controlled home appliance control system and was implemented by programming a Raspberry Pi using the Python language while the chatbot server was also implemented using a Node.js on JavaScript. The Raspberry Pi was connected to the chatbot server via Wi-Fi using a websockets protocol. The chatbot server is linked to Facebook Messenger using the Messenger Application Protocol Interface. Messages received at the chatbot server are analyzed with RasaNLU to classify the user's intention and extract necessary information which are sent over websocket to the connected Raspberry pi. The system was evaluated using control precision and percentage correct classification with both producing a significant level of acceptance. This work produced a Facebook Messenger chatbot-based framework capable of controlling Home Appliances remotely.


Author(s):  
Panana Tangwannawit ◽  
Sakchai Tangwannawit

<p>In this modern age, several new methods have been developed, especially in image processing for agriculture business, which consists of technologies derived from artificial intelligence (AI) capabilities called machine learning. Classify is a widely used method to analyze patterns, trends, as well as the body of knowledge from the data visualization. Image classification application improves discrimination and prediction efficiency. The objective of this research was to feature extraction of sweet tamarind and compare the algorithm for classification. This research used images from golden sweet tamarind species with the use of MATLAB and Python language. The steps of this research consisted of 1) preprocessing step for finding the distance to appropriate of the image quality, 2) feature extracting for finding the number of black pixels and the number of white pixels, perimeter, diameter, and centroid, and 3) classifying for algorithms' comparison. The results showed that the camera's distance to the image was 60 cm. The coefficient of determination was at 0.9956, and the Standard Error of Estimate was 7,424.736 pixels. The conclusion of classification found that the random forest had the highest accuracy at 92.00%, SD. = 8.06, precision = 90.12, recall = 92.86, and F1-score = 91.36.</p>


2021 ◽  
Vol 4 (2) ◽  
pp. 55-68
Author(s):  
Seyed Ghorashi

The Internet of Things (IoT) and Wireless Sensor Network (WSN) devices are prone to security vulnerabilities, especially when they are resource-constrained. Lightweight cryptography is a promising encryption concept for IoT and WSN devices, that can mitigate these vulnerabilities. For example, Klein encryption is a lightweight block cipher, which has achieved popularity for the trade-off between performance and security. In this paper, we propose one novel method to enhance the efficiency of the Klein block cipher and the effects on the Central Processing Unit (CPU), memory usage, and processing time. Furthermore, we evaluate another approach on the performance of the Klein encryption iterations. These approaches were implemented in the Python language and ran on the Raspberry PI 3. We evaluated and analyzed the results of two modified encryption algorithms and confirmed that two enhancing techniques lead to significantly improved performance compared to the original algorithm


2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Ravika Nur Melinda ◽  
Laisita Meitya Ningrum ◽  
Ida Bagus Suryabrata ◽  
Gede Swarna Bayu Artha Dwipa ◽  
Tyas Pratama Sukoco

ABSTRACT Making a budget plan in a project is often done manually which of course takes a long time to complete. In determining the budget plan, there are many types of work such as preparatory work, reinforced concrete work, and steel work, so it is quite difficult to work on. The budget plan can only be done by experts in the field, so it requires quite expensive processing costs. From the problems described above, we need a program that can simplify the calculation of the budget plan, especially in steel works (WF Beam). In this case, we created a program using the python language that needed to input some data such as rod length, number of bars, type of steel, steel prices, and work wages so that it would immediately produce a value or amount of the volume and price of a steel work that could help contractors especially steel subcontractors in calculating steel work (WF Beam). Keywords: python, RAB, WF beam, work volume, job price. ABSTRAK Pembuatan rencana anggaran dan biaya dalam sebuah proyek sering dilakukan secara manual yang tentunya membutuhkan waktu yang cukup lama untuk menyelesaikannya. Dalam menentukan rencana anggaran dan biaya, ada banyak jenis pekerjaan seperti pekerjaan persiapan, pekerjaan beton bertulang, dan pekerjaan baja, sehingga cukup sulit untuk dikerjakan. Rencana anggaran dan biaya juga hanya bisa dikerjakan oleh tenaga ahli pada bidang tersebut sehingga membutuhkan biaya pengerjaan yang cukup mahal. Dari permasalahan yang sudah dijabarkan diatas maka dibutuhkan sebuah program yang dapat mempermudah perhitungan rencana anggaran dan biaya khususnya di pekerjaan baja (WF Beam). Dalam hal ini, kami membuat sebuah program menggunakan bahasa python yang perlu menginputkan beberapa data seperti panjang batang, jumlah batang, jenis baja, harga baja, dan upah pekerjaan sehingga  akan langsung menghasilkan nilai atau besaran dari volume dan harga suatu pekerjaan baja yang dapat membantu kontraktor khususnya sub kontraktor baja dalam melakukan perhitungan pekerjaan baja (WF Beam). Kata kunci: python, RAB , WF beam, volume pekerjaan, harga pekerjaan.


2021 ◽  
Vol 7 (4) ◽  
pp. 33-42
Author(s):  
Thaw Zin Htay ◽  
Vladimir A. Glushenkov ◽  
Vladimir G. Komarov

Background: The development and research of the applicability of various mathematical models for calculating the solar radiation of companies is an urgent task for the innovative transport system of Myanmar. Aim: Determination of the daily balance of energy generated by solar panels to perform a given operation of the transport system. Materials and methods: Mathematical, algorithmic and software (based on the Python language) have been developed for energy supply and creation of interactive geo-information models for the ELTRO transport system. Results: To estimate solar resources at a point with coordinates ( = 19.76 s. w.; = 96.07 w. d.), data from the databases "NASA", "Meteonorm" and the Myanmar GMS were used and compared with the actual data on the Myanmar GMS database in order to determine the reliability of the information presented in them. Conclusion: The results obtained made it possible to determine the structure of the solar energy supply system and the parameters of typical solar energy modules that provide energy supply not only to the transport system, but also to the adjacent territories.


2021 ◽  
Vol 10 (16) ◽  
pp. e359101624007
Author(s):  
Filipe Morais Frade de Faria ◽  
Reginaldo Gonçalves Leão Junior

The computational study of intermolecular relationships of a given material can be used as a route for predicting quantities impossible or difficult to be determined experimentally. Furthermore properties of new materials can also be predicted by techniques of this type, when they are still in the modeling phase. This technique reproduces the classical dynamic relationships between the constituent elements of the material, atoms or unicorpuscular approximations of molecules, from interaction potential models called force fields. This work aims to develop a tool that performs the composition of linear polymeric chain systems through a self-avoided walk. For this, the concept of self-experimentation of long walks (SAWLC) was used, together with the Python language to develop MpolSys Modeler. This tool is a non-overlapping polymer chain generator, which in turn generates outputs that can be used as input to Moltemplate. To validate the tool's results, experiments were carried out in which the numbers and polymerization chains of the simulated polymer were varied, observing the overlap or not of the molecules that make up the simulation. At the end of the simulations, there were positive results that indicate a promising usage of the tool for the creation of polymers with a high number of chains and degrees of polymerization.


2021 ◽  
Vol 948 (1) ◽  
pp. 012090
Author(s):  
A Nurhiman ◽  
A Almira ◽  
R Raffiudin ◽  
M N Indro ◽  
A Maddu ◽  
...  

Abstract The flight behavior of honey bee Apis cerana is influenced by environmental conditions. The observation of the number of bees flying in and out from the hives is needed to detect the Colony Collapse Disorder (CCD) phenomena. In this research, we build a prototype of an automatic monitoring system based on image processing. This instrument is intended to automatically monitor and count the number of in and out activities of A. cerana forager bees. This monitoring system detects the red, green, blue, and yellow marked bees by using a camera module of Raspbery Pi mini-computer which is programmed in Python language (and assisted by OpenCV library). The monitoring system is also equipped with temperature, humidity, and light intensity sensors to accurately describe the environmental condition during the measurement. The results show that the highest number of flight activities occurred around 8:00.-09:00 am, then decrease to noon and increased again at 1:00 pm - 3:00 pm.


Author(s):  
Moaiad Khder

Web scraping or web crawling refers to the procedure of automatic extraction of data from websites using software. It is a process that is particularly important in fields such as Business Intelligence in the modern age. Web scrapping is a technology that allow us to extract structured data from text such as HTML. Web scrapping is extremely useful in situations where data isn’t provided in machine readable format such as JSON or XML. The use of web scrapping to gather data allows us to gather prices in near real time from retail store sites and provide further details, web scrapping can also be used to gather intelligence of illicit businesses such as drug marketplaces in the darknet to provide law enforcement and researchers valuable data such as drug prices and varieties that would be unavailable with conventional methods. It has been found that using a web scraping program would yield data that is far more thorough, accurate, and consistent than manual entry. Based on the result it has been concluded that Web scraping is a highly useful tool in the information age, and an essential one in the modern fields. Multiple technologies are required to implement web scrapping properly such as spidering and pattern matching which are discussed. This paper is looking into what web scraping is, how it works, web scraping stages, technologies, how it relates to Business Intelligence, artificial intelligence, data science, big data, cyber securityو how it can be done with the Python language, some of the main benefits of web scraping, and what the future of web scraping may look like, and a special degree of emphasis is placed on highlighting the ethical and legal issues. Keywords: Web Scraping, Web Crawling, Python Language, Business Intelligence, Data Science, Artificial Intelligence, Big Data, Cloud Computing, Cybersecurity, legal, ethical.


Sign in / Sign up

Export Citation Format

Share Document