During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve
... Show MoreThis study introduces a highly sensitive trapezium-shaped PCF based on an SPR refractometric sensor with unique design features. The structure of a sensor was designed and analyzed using COMSOL Multiphysics v5.6 based on Finite Element Method (FEM) with a focus on investigating the influence of various geometric parameters on its performance. The two channels were coated with a metallic gold layer to provide chemical stability, and a thin layer of TiO₂ improved the gold's adhesion to the fiber. The findings indicate that the proposed sensor achieves maximum amplitude and wavelength sensitivities of 1,779 RIU⁻¹ and 30,500 nm/RIU, respectively, with corresponding resolutions of 3.2
Weed control with chemicals is a challenging process that should be performed in a rational way to reduce their negative impact on the surrounding environment. The growth of artificial intelligence algorithms encourages researchers to develop smart spraying robots that detect and spray weeds and distinguish them from the main crop which leads to sustainable use of these chemicals and achieves some of the sustainable development goals. However, few studies are available to comprehensively compare different versions of YOLO algorithm to detect weed. In this research, seven versions of YOLO algorithms were evaluated for their performance to detect and spray four t
The internet of medical things (IoMT), which is expected the lead to the biggest technology in worldwide distribution. Using 5th generation (5G) transmission, market possibilities and hazards related to IoMT are improved and detected. This framework describes a strategy for proactively addressing worries and offering a forum to promote development, alter attitudes and maintain people's confidence in the broader healthcare system without compromising security. It is combined with a data offloading system to speed up the transmission of medical data and improved the quality of service (QoS). As a result of this development, we suggested the enriched energy efficient fuzzy (EEEF) data offloading technique to enhance the delivery of dat
... Show MoreThe internet of medical things (IoMT), which is expected the lead to the biggest technology in worldwide distribution. Using 5th generation (5G) transmission, market possibilities and hazards related to IoMT are improved and detected. This framework describes a strategy for proactively addressing worries and offering a forum to promote development, alter attitudes and maintain people's confidence in the broader healthcare system without compromising security. It is combined with a data offloading system to speed up the transmission of medical data and improved the quality of service (QoS). As a result of this development, we suggested the enriched energy efficient fuzzy (EEEF) data offloading technique to enhance the delivery of dat
... Show MoreDuring COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve
... Show MoreObjective: To measure the effect of the pharmacist-led medication reconciliation service before hospital discharge on preventing potential medication errors. Methods: This behavioral interventional study took place in a public teaching hospital in Iraq between December 2022 and January 2023. It included inpatients who were taking four or more medications upon discharge from the internal medicine ward and the cardiac care unit. The researcher provided the patients with a medication reconciliation form and reconciliation form (including medication regimen and pharmacist instructions) before discharging them home. Any discrepancies between the patients’ understanding and the actual medication recommendations prescribed by the physici
... Show MoreNeed organizations today to move towards strategic thinking which means analyzing situations faced by particular challenges of change in the external environment, which makes it imperative for The Organization That to reconsider their strategies and orientations and operations, a so-called re-engineering to meet those challenges and pressures, to try to achieve improvement root in the installation of the organization and methodscompletion of its work towards achieving high levels of performance and that is reflected to achieve its objectives, and this is what aims to Current search to deal with implications characteristics of strategic thinking in the stages of application re-engineering business of the company General Industries
... Show MoreThis study presents an adaptive control scheme based on synergetic control theory for suppressing the vibration of building structures due to earthquake. The control key for the proposed controller is based on a magneto-rheological (MR) damper, which supports the building. According to Lyapunov-based stability analysis, an adaptive synergetic control (ASC) strategy was established under variation of the stiffness and viscosity coefficients in the vibrated building. The control and adaptive laws of the ASC were developed to ensure the stability of the controlled structure. The proposed controller addresses the suppression problem of a single-degree-of-freedom (SDOF) building model, and an earthquake control scenario was conducted and simulat
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