Today many people suffering from health problems like dysfunction in lungs and cardiac. These problems often require surveillance and follow up to save a patient's health, besides control diseases before progression. For that, this work has been proposed to design and developed a remote patient surveillance system, which deals with 4 medical signs (temperature, SPO2, heart rate, and Electrocardiogram ECG. An adaptive filter has been used to remove any noise from the signal, also, a simple and fast search algorithm has been designed to find the features of ECG signal such as Q,R,S, and T waves. The system performs analysis for medical signs that are used to detected abnormal values. Besides, it sends data to the Base-Station with a data block (ECG signals) that contains the problem. In addition, it generates an alarm to the physicians via ringing up mobile and SMS to overcome the internet disconnected. Also, the system has been designed to achieve precision, low cost, and low energy consumption. Three types of sensors has been used in this work, ECG, SPo2, and temperature sensors. Also, a sim800L GSM module has been used for communications, the main controller in this work is ESP32 unit.
Correct grading of apple slices can help ensure quality and improve the marketability of the final product, which can impact the overall development of the apple slice industry post-harvest. The study intends to employ the convolutional neural network (CNN) architectures of ResNet-18 and DenseNet-201 and classical machine learning (ML) classifiers such as Wide Neural Networks (WNN), Naïve Bayes (NB), and two kernels of support vector machines (SVM) to classify apple slices into different hardness classes based on their RGB values. Our research data showed that the DenseNet-201 features classified by the SVM-Cubic kernel had the highest accuracy and lowest standard deviation (SD) among all the methods we tested, at 89.51 % 1.66 %. This
... Show MoreThe petroleum industry, which is one of the pillars of the national economy, has the potential to generate vast wealth and employment possibilities. The transportation of petroleum products is complicated and changeable because of the hazards caused by the corrosion consequences. Hazardous chemical leaks caused by natural disasters may harm the environment, resulting in significant economic losses. It significantly threatens the aim for sustainable development. When a result, determining the likelihood of leakage and the potential for environmental harm, it becomes a top priority for decision-makers as they develop maintenance plans. This study aims to provide an in-depth understanding of the risks associated with oil and gas pipeli
... Show MoreThe university course timetable problem (UCTP) is typically a combinatorial optimization problem. Manually achieving a useful timetable requires many days of effort, and the results are still unsatisfactory. unsatisfactory. Various states of art methods (heuristic, meta-heuristic) are used to satisfactorily solve UCTP. However, these approaches typically represent the instance-specific solutions. The hyper-heuristic framework adequately addresses this complex problem. This research proposed Particle Swarm Optimizer-based Hyper Heuristic (HH PSO) to solve UCTP efficiently. PSO is used as a higher-level method that selects low-level heuristics (LLH) sequence which further generates an optimal solution. The proposed a
... Show MoreProtecting information sent through insecure internet channels is a significant challenge facing researchers. In this paper, we present a novel method for image data encryption that combines chaotic maps with linear feedback shift registers in two stages. In the first stage, the image is divided into two parts. Then, the locations of the pixels of each part are redistributed through the random numbers key, which is generated using linear feedback shift registers. The second stage includes segmenting the image into the three primary colors red, green, and blue (RGB); then, the data for each color is encrypted through one of three keys that are generated using three-dimensional chaotic maps. Many statistical tests (entropy, peak signa
... Show MoreAcute appendicitis is one of the commonest causes of acute abdomen. There is a wide discussion and controversy on the surgical and nonsurgical treatment of acute uncomplicated appendicitis. The aim of this study was to evaluate the efficacy and outcomes of the conservative management of selected cases of acute appendicitis with an antibiotic first plan.
This was a single hospital-based prospective study with a durat
Face recognition and identity verification are now critical components of current security and verification technology. The main objective of this review is to identify the most important deep learning techniques that have contributed to the improvement in the accuracy and reliability of facial recognition systems, as well as highlighting existing problems and potential future research areas. An extensive literature review was conducted with the assistance of leading scientific databases such as IEEE Xplore, ScienceDirect, and SpringerLink and covered studies from the period 2015 to 2024. The studies of interest were related to the application of deep neural networks, i.e., CNN, Siamese, and Transformer-based models, in face recogni
... Show MoreThe implementation of the concept of project scheduling in the organizations generally requires a set of procedures and requirements, So, most important of all is the understanding and knowledge of the tools and techniques which are called the methods of scheduling projects. Consequently, the projects of the municipality administration in the holy governorate of Karbala suffer from the problem of delaying their projects and chaos in the ways of implementation. To provide assistance to this directorate and to demonstrate how to schedule projects using one of the advanced scientific methods that proved their ability to schedule any project and its potential to accelerate the time of completion, as well as ease of use and effectiven
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