Digital Elevation Model (DEM) is one of the developed techniques for relief representation. The definition of a DEM construction is the modeling technique of earth surface from existing data. DEM plays a role as one of the fundamental information requirement that has been generally utilized in GIS data structures. The main aim of this research is to present a methodology for assessing DEMs generation methods. The DEMs data will be extracted from open source data e.g. Google Earth. The tested data will be compared with data produced from formal institutions such as General Directorate of Surveying. The study area has been chosen in south of Iraq (Al-Gharraf / Dhi Qar governorate. The methods of DEMs creation are kriging, IDW (inverse distance weight), spline, and natural neighbor. This research used different software for processing and analysis such as ArcGIS 10.2, TCX and Civil 3D. Two- sample t-test has been adopted to investigate the mean of elevation differences between compared datasets. The results showed that the spline is the best method that can be used to build DEM in this study area.
In this article, the research presents a general overview of deep learning-based AVSS (audio-visual source separation) systems. AVSS has achieved exceptional results in a number of areas, including decreasing noise levels, boosting speech recognition, and improving audio quality. The advantages and disadvantages of each deep learning model are discussed throughout the research as it reviews various current experiments on AVSS. The TCD TIMIT dataset (which contains top-notch audio and video recordings created especially for speech recognition tasks) and the Voxceleb dataset (a sizable collection of brief audio-visual clips with human speech) are just a couple of the useful datasets summarized in the paper that can be used to t
... Show MoreIn this article, the research presents a general overview of deep learning-based AVSS (audio-visual source separation) systems. AVSS has achieved exceptional results in a number of areas, including decreasing noise levels, boosting speech recognition, and improving audio quality. The advantages and disadvantages of each deep learning model are discussed throughout the research as it reviews various current experiments on AVSS. The TCD TIMIT dataset (which contains top-notch audio and video recordings created especially for speech recognition tasks) and the Voxceleb dataset (a sizable collection of brief audio-visual clips with human speech) are just a couple of the useful datasets summarized in the paper that can be used to test A
... Show Morelanguage is universal and that of Fairclough’s (1992), image can be a source of ambiguity and creativity, has pushed the researchers to conduct the present study. Besides, surveying the literature review of caricature images, the researchers have found that still much work needs to be done as far as images are concerned in different disciplines in general and in linguistics in particular to bridge the many gaps there. Accordingly, the objective of the current research is to examine students’ ability to identify the denotative key-signs that help access and share the intended denotative meaning and/or highlight other denotative meaning potentials from a detextualised image caricature. To achieve the objective of the study, the researcher
... Show MoreThe interests toward developing accurate automatic face emotion recognition methodologies are growing vastly, and it is still one of an ever growing research field in the region of computer vision, artificial intelligent and automation. However, there is a challenge to build an automated system which equals human ability to recognize facial emotion because of the lack of an effective facial feature descriptor and the difficulty of choosing proper classification method. In this paper, a geometric based feature vector has been proposed. For the classification purpose, three different types of classification methods are tested: statistical, artificial neural network (NN) and Support Vector Machine (SVM). A modified K-Means clustering algorithm
... Show MoreDue to the popularity of radar, receivers often “hear” a great number of other transmitters in
addition to their own return merely in noise. The dealing with the problem of identifying and/or
separating a sum of tens of such pulse trains from a number of different sources are often received on
the one communication channel. It is then of interest to identify which pulses are from which source,
based on the assumption that the different sources have different characteristics. This search deals with a
graphical user interface (GUI) to generate the radar pulse in order to use the required radar signal in any
specified location.
Many image processing and machine learning applications require sufficient image feature selection and representation. This can be achieved by imitating human ability to process visual information. One such ability is that human eyes are much more sensitive to changes in the intensity (luminance) than the color information. In this paper, we present how to exploit luminance information, organized in a pyramid structure, to transfer properties between two images. Two applications are presented to demonstrate the results of using luminance channel in the similarity metric of two images. These are image generation; where a target image is to be generated from a source one, and image colorization; where color information is to be browsed from o
... Show MoreMunicipal solid waste generation in Babylon Governorate is often affected by changes in lifestyles, population growth, social and cultural habits and improved economic conditions. This effect will make it difficult to plan and draw up future plans for solid waste management.In this study, municipal solid waste was divided into residential and commercial solid wastes. Residential solid wastes were represented by household wastes, while commercial solid wastes included commercial, institutional and municipal services wastes.For residential solid wastes, the relational stratified random sampling was implemented, that is the total population should be divided into clusters (socio-income level), a random sample was taken in e
... Show MoreToday, the architecture field is witnessing a noticeable evolution regarding the used tools that the designer should invest in a peculiar way that is made available in architecture through the concept of synergy generally and algorithmic synergy specifically. The synergy is meant to study and analyze the cooperative behavior of complex systems and self-organizing systems that leads to different outputs referred to by the synergy as the (whole), which is bigger than the sum of parts and in architecture, it's translated as the architectural form. This point resulted in a need of a specific study regarding the concept of synergy that focuses on the cooperative, synergistic relations within the trilogy of (form, structure, and material) and
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