This research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.

Background: Fifteen percent of small for gestational age are small as a result of fetal growth restriction, which could be due to maternal, placental or fetal factors. It is an important clinical problem associated with increase perinatal mortality and morbidity. Leptin is a protein that produced by many tissues including the placenta (syncytiotropholoast). Dysregulation of leptin metabolism may be implicated in preeclampsia and IUGR pathogenesis.
Aim of the study: To study the trend of leptin level alteration in maternal serum and cord blood in pregnancies complicated by fetal growth restriction and its relation with fetal outcome.
Methods: An Analytic, cross- sectional study conducted in Al-Elwyia Maternity Teaching Hospital and

Whenever, the Internet of Things (IoT) applications and devices increased, the capability of the its access frequently stressed. That can lead a significant bottleneck problem for network performance in different layers of an end point to end point (P2P) communication route. So, an appropriate characteristic (i.e., classification) of the time changing traffic prediction has been used to solve this issue. Nevertheless, stills remain at great an open defy. Due to of the most of the presenting solutions depend on machine learning (ML) methods, that though give high calculation cost, where they are not taking into account the fine-accurately flow classification of the IoT devices is needed. Therefore, this paper presents a new model bas

Detection of early clinical keratoconus (KCN) is a challenging task, even for expert clinicians. In this study, we propose a deep learning (DL) model to address this challenge. We first used Xception and InceptionResNetV2 DL architectures to extract features from three different corneal maps collected from 1371 eyes examined in an eye clinic in Egypt. We then fused features using Xception and InceptionResNetV2 to detect subclinical forms of KCN more accurately and robustly. We obtained an area under the receiver operating characteristic curves (AUC) of 0.99 and an accuracy range of 97–100% to distinguish normal eyes from eyes with subclinical and established KCN. We further validated the model based on an independent dataset with

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Artist kicks off in his production through creative artistic assimilation to the production of concepts and experiences, which can decode the artist blades through the re-built and converted to the subject of my mind according to the processes of analysis and synthesis. Artist need the expertise and experience to complete the technical work, and to develop taste aesthetic, and achieve certain goals belonging to Resume artist, diversity of artistic experiences between mechanism represents a female form and expression of contents and visions that carry letters of freedom in accordance with the creative visual surfaces embody the image of women, the main speeches adopted by propositions technical artists, and artists who relied female form

The management of wisdom is concerned with the level of expertise, methods of transmission, use and ability to problems and their impact on behavior and human behavior in order to improve it in the form of successful decisions. The importance of management of wisdom in making successful decisions that ensure the survival and development of society through the provision of leaders capable of planning, organization and decision-making to achieve the goals and objectives required in a complex and changing environment. Where the administration faces positions and problems that require operational decisions to organize the activities of the institution in line with the strategic decisions already taken under the proper strategic planning. The ex

E-wallet, also referred to as digital wallet, is a software application designed to replace physical wallets, with the primary purpose of facilitating online transactions when users wish to make virtual payments. Nowadays, E-wallets are not limited to mobile applications, but they have also been extended to wearable devices, such as smartwatches, enabling users to make payments via their watches. This research study focuses on three main E-wallet service providers in Malaysia, namely TouchNGo E-wallet, Boost, and Grab pay, as they are the top three E-wallets in the country. The aim of this paper is to explore the real-world implementation of E-wallets among mobile phone users in Malaysia, employing the Technology Adoption Model as the th