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Transverse momentum spectra of strange hadrons within extensive and nonextensive statistics
Using generic (non)extensive statistics, in which the underlying system likely autonomously manifests its extensive and nonextensive statistical nature, we extract various fit parameters from the CMS experiment and compare these to the corresponding results obtained from Tsallis and Boltzmann statistics. The present study is designed to indicate the possible variations between the three types of statistical approaches and characterizes their dependence on collision energy, multiplicity, and size of the system of interest. We analyze the transverse momentum spectra pT of the strange hadrons Ks
Recognizing Clothing Patterns and Colors for BVI People Using Different Techniques
For blind and visually impaired (BVI) people, it is an arduous task to recognize clothing patterns and colors. It is especially complex to recognize them automatically. This is a highly researched area in image processing. This paper provides BVI with the ability to detect patterns and colors without depending on personal assistance, leading to increasing their confidence. The user first captures an image; then, our system detects colors and patterns. The color model used here is the hue saturation value (HSV). The main colors detected by our system are magenta, cyan, blue, green, red and
HSAS-MD Analyzer: A Hybrid Security Analysis System Using Model-Checking Technique and Deep Learning for Malware Detection in IoT Apps
Established Internet of Things (IoT) platforms suffer from their inability to determine whether an IoT app is secure or not. A security analysis system (SAS) is a protective shield against any attack that breaks down data privacy and security. Its main task focuses on detecting malware and verifying app behavior. There are many SASs implemented in various IoT applications. Most of them build on utilizing static or dynamic analysis separately. However, the hybrid analysis is the best for obtaining accurate results. The SAS provides an effective outcome according to many criteria related to the
Arabic fake news detection using deep learning
Nowadays, an unprecedented number of users interact through social media platforms and generate a massive amount of content due to the explosion of online communication. However, because user-generated content is unregulated, it may contain offensive content such as fake news, insults, and harassment phrases. The identification of fake news and rumors and their dissemination on social media has become a critical requirement. They have adverse effects on users, businesses, enterprises, and even political regimes and governments. State of the art has tackled the English language for news and
Intelligent Arabic-Based Healthcare Assistant
Text classification has been one of the most common natural language processing (NLP) objectives in recent years. Compared to other languages, this mission with Arabic is relatively restricted and in its early stages, and this combination in the medical application area is rare. This paper builds an Arabic health care assistant, specifically a pediatrician that supports Arabic dialects, especially Egyptian accents. The proposed application is a chatbot based on Artificial Intelligence (AI) models after experimenting with Two Bidirectional Encoder Representations from Transformers (BERT) models
Real-Time Fish Detection Approach on Self-Built Dataset Based on YOLOv3
Creating a model to detect freely moving fish underwater in real-time is a challenging process for two main reasons. First, the available datasets suffer from some limitations that severely affect the results of the detection models operating in challenging and blurry environments. These models should be able to capture all of the fish movement given different types of surroundings. Second, choosing the convenient detection model system which matches the desired requirements from having high accuracy with satisfying frames per second (FPS). To overcome the first challenge, a new dataset was
Design and Analysis of A Reliable Quadcopter UAV for Wireless Communication Purposes
Unmanned aerial vehicles (UAVs) are used for a wide range of applications, including wireless communication systems, which have the potential to provide cost-effective wireless connectivity for a wide variety of applications. The present UAV models lack the flexibility needed to carry the mission's varied payloads. As a result, appropriate design and analysis of the UAV structure are essential. This work presents a complete design and analysis of a quadcopter UAV for wireless communications purposes, which is carried out using computer-aided design (CAD) tools and techniques. Several design
AiroDiag: A sophisticated tool that diagnoses and updates vehicles software over air
This paper introduces a novel method for diagnosing embedded systems and updating embedded software installed on the electronics control units of vehicles through the Internet using client and server units. It also presents the communication protocols between the vehicle and the manufacturer for instant fault diagnosis and software update while ensuring security for both parties. AiroDiag ensures maximum vehicle efficiency for the driver and provides the manufacturer with up-to-date vehicle performance data, allowing enhanced future software deployment and minimum loss in case of vehicle
Future of public organizations in the digital transformation era
Introduction and Purpose: Digital transformation has been a “buzz” word over the last few years. Government of Egypt has initiated various ambitious initiatives and projects for transforming the economy into digital economy. Since the outlook of the future organizations would be different from what we know today, therefore, such transformation mandates radical change in the way public leaders manage their organizations, operations and workforce. Consequently, there is a necessity for foreseeing the drivers of change, as well as the technological evolution, which are shaping the future
Radio optical network simulation tool (ronst)
This paper presents a radio optical network simulation tool (RONST) for modeling optical-wireless systems. For a typical optical and electrical chain environment, performance should be optimized concurrently before system implementation. As a result, simulating such systems turns out to be a multidisciplinary problem. The governing equations are incompatible with co-simulation in the traditional environments of existing software (SW) packages. The ultra-wideband (UWB) technology is an ideal candidate for providing high-speed short-range access for wireless services. The limited wireless reach
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