With the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor sets, resulting in four trained models. The test sets are used to evaluate the trained models using many evaluation metrics (accuracy, TPR, FNR, PPR, FDR). Results of Google Net model indicate the high performance of the designed models with 99.34% and 99.76% accuracies for indoor and outdoor datasets, respectively. For Mobile Net models, the result accuracies are 99.27% and 99.68% for indoor and outdoor sets, respectively. The proposed methodology is compared with similar ones in the field of object recognition and image classification, and the comparative study proves the transcendence of the propsed system.
In this paper, image compression technique is presented based on the Zonal transform method. The DCT, Walsh, and Hadamard transform techniques are also implements. These different transforms are applied on SAR images using Different block size. The effects of implementing these different transforms are investigated. The main shortcoming associated with this radar imagery system is the presence of the speckle noise, which affected the compression results.
The study consisted in the development and use of a practical method to detect and
monitor, analyze and produce maps of changes in land use and land cover in the district of
Mahmudiya in Baghdad during the period 1990-2007 using the applications of remote sensing
techniques and with the assisstant of geographic information systems (GIS),as a valuable
contribution to land degradation studies.
This study is based maiuly on the processing on two subsets of landsat5 TM images picked up
in August 1990 and 2007 respectively in order to facilitate comparision and were thengeometrically and radiometrcally calibrated ,to used for digital classification purposes using
maximum liklihoods classification or six spectral bands of
The COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system
... Show MoreThe present study deals with the websites of Iraqi political parties on the internet to identify the effectiveness in providing communicative applications that help audience to participate, express their opinions, their positions, and other aspects reflecting the extent of employing modern technological tools to allow opportunities for political, and democratic participation since the internet has become an effective tool for political communications of political parties. The research sample includes eight political parties. The research concludes that the Iraqi political parties do not employ interactive communication patterns to reflect their interests in communicating with the public, providing opportunities for their participation an
... Show MoreA thin film of AgInSe2 and Ag1-xCuxInSe2 as well as n-Ag1-xCuxInSe2 /p-Si heterojunction with different Cu ratios (0, 0.1, 0.2) has been successfully fabricated by thermal evaporation method as absorbent layer with thickness about 700 nm and ZnTe as window layer with thickness about 100 nm. We made a multi-layer of p-ZnTe/n-AgCuInSe2/p-Si structures, In the present work, the conversion efficiency (η) increased when added the Cu and when used p-ZnTe as a window layer (WL) the bandgap energy of the direct transition decreases from 1.75 eV (Cu=0.0) to 1.48 eV (Cu=0.2 nm) and the bandgap energy for ZnTe=2.35 eV. The measurements of the electrical properties for prepared films showed that the D.C electrical conductivity (σd.c) increase
... Show MoreThis investigation integrates experimental and numerical approaches to study a novel solar air heater aimed at achieving an efficient design for a solar collector suitable for drying applications under the meteorological conditions of Iraq. The importance of this investigation stems from the lack of optimal exploitation of solar energy reaching the solar collector, primarily attributable to elevated thermal losses despite numerous designs employed in such solar systems. Consequently, enhancing the thermal performance of solar collectors, particularly those employed in crop drying applications, stands as a crucial focal point for researchers within this domain. Two identical double-pass solar air heaters were designed and constructed for
... Show MoreThis study presents, for the first time, an innovative Jet Plasma-assisted technique for the green synthesis of TiO₂@Ag core–shell nanoparticles using chard leaf extract as a natural reducing and stabilizing agent. The Jet Plasma provides a highly energetic environment that accelerates nucleation and core–shell formation at low temperatures without toxic precursors. The synthesized nanoparticles exhibited uniform and stable structures, as confirmed by comprehensive characterization techniques including X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), ultraviolet–visible (UV–Vis) spectroscopy, transmission electron microscopy (TEM), and zeta potential analysis. XRD patterns confirmed the crystalline anatase
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