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Optimum Scheduling of the Disinfection Process for COVID-19 in Public Places with a Case Study from Egypt, a Novel Discrete Binary Gaining-Sharing Knowledge-Based Metaheuristic Algorithm

The aim of this paper is to introduce an improved strategy for controlling COVID-19 and other pandemic episodes as an environmental disinfection culture for public places. The scheduling aims at achieving the best utilization of the available working day-time hours, which is calculated as the total consumed disinfection times minus the total loosed transportation times. The proposed problem in network optimization identifies a disinfection group who is likely to select a route to reach a subset of predetermined public places to be regularly disinfected with the most utilization of the

Artificial Intelligence
Healthcare
Software and Communications

Towards Intelligent Web Context-Based Content On-Demand Extraction Using Deep Learning

Information extraction and reasoning from massive high-dimensional data at dynamic contexts, is very demanding and yet is very hard to obtain in real-time basis. However, such process capability and efficiency might be affected and limited by the available computational resources and the consequent power consumption. Conventional search mechanisms are often incapable of real-time fetching a predefined content from data source, without concerning the increased number of connected devices that contribute to the same source. In this work, we propose and present a concept for an efficient approach

Artificial Intelligence
Circuit Theory and Applications
Software and Communications
Innovation, Entrepreneurship and Competitiveness

Transmit and receive cooperative cognition: Protocol design and stability analysis

In this paper, we investigate the stability of a cooperative cognitive system. We propose a cooperative secondary transmitter-receiver system (CSTR), where, the secondary transmitter (ST) and the secondary receiver (SR) increase the spectrum availability for the ST packets by relaying the unsuccessfully transmitted packets of the primary transmitter (PT). We assume receiving nodes with multipacket reception capability (MPR). We provide two inner bounds and two outer bounds on the stability region of the considered system. © 2013 ICST - The Institute for Computer Sciences, Social Informatics

Artificial Intelligence
Circuit Theory and Applications
Software and Communications

Logically Centralized-Physically Distributed Software Defined Network Controller Architecture

Due to the large usage of internet, our environment is transformed into digital society, in which everything is connected together and can be accessed from anywhere. This is the Internet of things (IoT), which refers to the usage of intelligently connected devices and systems. These devices usually collect their data from sensors and actuators in machines and other physical objects. This makes Wireless Sensor Network (WSN) a subset of an Internet of things (IoT) topology, and hence it acts like a bridge that connects the real world to the digital world. So it is important to find a flexible

Artificial Intelligence

Self-Driving Car Lane-keeping Assist using PID and Pure Pursuit Control

Detection of lane boundaries is the primary role for monitoring an autonomous car's trajectory. Three lane identification methodologies are explored in this paper with experimental illustration: Edge detection, Hough transformation, and Birds eye view. The next step after obtaining the boundary points is to add a regulation rule to effectively trigger the regulation of steering and velocity to the motors. A comparative analysis is made between different steering controllers like PID or by using PID with a pure pursuit controller for the Lane Keeping Assist (LKA) system. A camera that sends

Artificial Intelligence
Software and Communications
Mechanical Design

Hybrid Self-Balancing and object Tracking Robot Using Artificial Intelligence and Machine Vision

Over the past decade, mobile autonomous robots have been widely used efficiently for different applications. Recently, self-balancing robots attracted more attention and showed impressive performance. A self-balancing robot is simply a two-wheeled robot; hence it needs to be balanced vertically using a closed-loop control algorithm. In this paper, a new hybrid two-wheeled self-balancing robot is fully designed and implemented, which is able to track objects and to avoid obstacles efficiently. The proposed robot consists of a two-wheeled chassis equipped with an ultrasonic sensor, camera

Artificial Intelligence

3PCNNB-Net: Three Parallel CNN Branches for Breast Cancer Classification Through Histopathological Images

Purpose: Diagnosis of breast tumors using histopathological imaging is considered a difficult task. Oncologists may have different opinions on how to use this imaging technique to diagnose tumors. This technique requires classification experience owing to the contrasting appearance caused by tissue preparation, staining processes, and disease heterogeneity. Cancerous breast tissues are classified into malignant and benign tumors according to cell diversity and density. Computer-aided diagnosis (CAD) helps oncologists improve breast tumor diagnosis efficiently and accurately while saving time

Artificial Intelligence

IoT ethics challenges and legal issues

IoT systems have different technologies such as: RIFD, NFC, 3G, 4G, and Sensors. Their function is to transfer very large sensitive and private data. There are many ethical challenges that need to be taken into consideration by individuals and companies that use this technology. Amongst the challenges is the user awareness of attack risks. This paper discusses different ethical and legal challenges that need to be taken in account for IoT health care applications during the near future. © 2017 IEEE.

Artificial Intelligence
Circuit Theory and Applications
Software and Communications

Diabetes Prediction Using Machine Learning: A Comparative Study

Diabetes is a common, metabolic disease, that results in a high level of blood sugar. Patients diagnosed with diabetes suffer from a body that cannot effectively use the insulin or cannot produce a sufficient amount of insulin. Providing a method of detection via symptoms that can be noticed by the patient can prompt the patient to seek medical assistance more promptly and in turn to be correctly diagnosed and treated. This paper proposed a solution for the problem using machine learning techniques. We applied eight algorithms on a data set of 521 subjects. The results are compared to each

Artificial Intelligence
Healthcare

IoT Agile Framework Enhancement

Internet of Things (IoT) is considered as a trend nowadays. Devices connected to the internet interact with surrounding; this poses strong challenges in handling big data with a certain level of security. In this paper IoT devices will be divided in to two categories high vulnerability devices and low vulnerability devices. The classification depends on the ease of attacks. In order to ensure the security of IoT devices, an agile approach is used to secure high vulnerability devices as first step and then low vulnerability devices by applying encryption algorithms. © 2018 IEEE.

Artificial Intelligence
Circuit Theory and Applications
Software and Communications