In these recent years, the world has witnessed a kind of social exclusion and the inability to communicate directly due to the Corona Virus Covid 19 (COVID-19) pandemic, and the consequent difficulty of communicating with patients with hospitals led to the need to use modern technology to solve and facilitate the problem of people communicating with each other. healthcare has made many remarkable developments through the Internet of things (IOT) and cloud computing to monitor real-time patients' data, which has enabled many patients' lives to be saved. this paper presents the design and implementation of a Private Backend Server Software based on an IoT health monitoring system concerned emergency medical services utilizing biosensors to detect multivital signs of an individual with an ESP32 microcontroller board and IoT cloud. The device displays the vital data, which is then uploaded to a cloud server for storage and analysis over an IoT network. Vital data is received from the cloud server and shown on the IoT medical client dashboard for remote monitoring. The proposed system allows users to ameliorate healthcare jeopardy and minify its costs by recording, gathering, sharing, and analyzing vast biodata streams such as Intensive Care Units (ICU) (i.e., temperature, heartbeat rate, Oxygen level (CO2), etc.), efficiently in real-time. In this proposal, the data will send from sensors fixed in the patient body to the Web and Mobile App continually in real time for collection and analysis.
Voting is an important procedure in democratic societies in different countries, including Iraq. Electronic voting (E-voting) is becoming more prevalent due to reducing administrative costs and burdens. E-voting systems have many restrictions that affect the electoral process. For example, fraud, tampering with ballot boxes, taking many hours to announce results, and the difficulty of reaching polling stations. Over the last decade, blockchain and smart contract technologies have gained widespread adoption in various sectors, such as cryptocurrencies, finance, banking, and most notably in e-voting systems. If utilized properly, the developer demonstrates properties that are promising for their properties, such as security, privacy, trans
... Show MoreAn Intelligent Internet of Things network based on an Artificial Intelligent System, can substantially control and reduce the congestion effects in the network. In this paper, an artificial intelligent system is proposed for eliminating the congestion effects in traffic load in an Intelligent Internet of Things network based on a deep learning Convolutional Recurrent Neural Network with a modified Element-wise Attention Gate. The invisible layer of the modified Element-wise Attention Gate structure has self-feedback to increase its long short-term memory. The artificial intelligent system is implemented for next step ahead traffic estimation and clustering the network. In the proposed architecture, each sensing node is adaptive and able to
... Show MoreThis paper presents an improved technique on Ant Colony Optimization (ACO) algorithm. The procedure is applied on Single Machine with Infinite Bus (SMIB) system with power system stabilizer (PSS) at three different loading regimes. The simulations are made by using MATLAB software. The results show that by using Improved Ant Colony Optimization (IACO) the system will give better performance with less number of iterations as it compared with a previous modification on ACO. In addition, the probability of selecting the arc depends on the best ant performance and the evaporation rate.
Electromyogram (EMG)-based Pattern Recognition (PR) systems for upper-limb prosthesis control provide promising ways to enable an intuitive control of the prostheses with multiple degrees of freedom and fast reaction times. However, the lack of robustness of the PR systems may limit their usability. In this paper, a novel adaptive time windowing framework is proposed to enhance the performance of the PR systems by focusing on their windowing and classification steps. The proposed framework estimates the output probabilities of each class and outputs a movement only if a decision with a probability above a certain threshold is achieved. Otherwise (i.e., all probability values are below the threshold), the window size of the EMG signa
... Show MoreThe subject of an valuation of quality of construction projects is one of the topics which it becomes necessary of the absence of the quantity standards in measuring the control works and the quality valuation standards in constructional projects. In the time being it depends on the experience of the workers which leads to an apparent differences in the valuation.
The idea of this research came to put the standards to evaluate the quality of the projects in a special system depending on quantity scale nor quality specifying in order to prepare an expert system “ Crystal “ to apply this special system to able the engineers to valuate the quality of their projects easily and in more accurate ways.
The need to exchange large amounts of real-time data is constantly increasing in wireless communication. While traditional radio transceivers are not cost-effective and their components should be integrated, software-defined radio (SDR) ones have opened up a new class of wireless technologies with high security. This study aims to design an SDR transceiver was built using one type of modulation, which is 16 QAM, and adding a security subsystem using one type of chaos map, which is a logistic map, because it is a very simple nonlinear dynamical equations that generate a random key and EXCLUSIVE OR with the originally transmitted data to protect data through the transmission. At th
... Show MoreThe object of the presented study was to monitor the changes that had happened in the main features (water, vegetation, and soil) of Al-Hammar Marsh region. To fulfill this goal, different satellite images had been used in different times, MSS 1973, TM 1990, ETM+ 2000, 2002, and MODIS 2009, 2010. A new technique of the unsupervised classification called (Color Extracting Technique) was used to classify the satellite images. MATLAP programming used the technique and separated Al-Hammar Marsh from other water features (rivers, irrigated lands, etc.) when calculated the changes in the water content of the study region. ArcGIS 9.3 (arcMAP, arcToolbox) were used to achieve this work and calculate area of each class.