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Moving Objects Detection Based on Frequency Domain: image processing
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In this research a proposed technique is used to enhance the frame difference technique performance for extracting moving objects in video file. One of the most effective factors in performance dropping is noise existence, which may cause incorrect moving objects identification. Therefore it was necessary to find a way to diminish this noise effect. Traditional Average and Median spatial filters can be used to handle such situations. But here in this work the focus is on utilizing spectral domain through using Fourier and Wavelet transformations in order to decrease this noise effect. Experiments and statistical features (Entropy, Standard deviation) proved that these transformations can stand to overcome such problems in an elegant way.

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Publication Date
Thu Jun 26 2014
Journal Name
Engineering Optimization
A new modified differential evolution algorithm scheme-based linear frequency modulation radar signal de-noising
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The main intention of this study was to investigate the development of a new optimization technique based on the differential evolution (DE) algorithm, for the purpose of linear frequency modulation radar signal de-noising. As the standard DE algorithm is a fixed length optimizer, it is not suitable for solving signal de-noising problems that call for variability. A modified crossover scheme called rand-length crossover was designed to fit the proposed variable-length DE, and the new DE algorithm is referred to as the random variable-length crossover differential evolution (rvlx-DE) algorithm. The measurement results demonstrate a highly efficient capability for target detection in terms of frequency response and peak forming that was isola

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Publication Date
Sat Feb 01 2020
Journal Name
International Journal Of Computer Science And Mobile Computing
Hierarchical Fixed Prediction of Mixed based for Medical Image Compression.
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Publication Date
Tue Sep 19 2017
Journal Name
Al-academy
Aesthetic performance in the mobile sculptures
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Aesthetic performance in the mobile sculptures
Ali Abd Almohsen Ali
Abstract
Chapters of this research are discussed one of the turning points in the In the history of sculpture, which sparked a debate in artistic circles, namely the introduction of the actual movement in sculpture . The researcher highlighted on one of the corners of the controversy on this subject for discussion and looking in and Found results contribute to answer some questions . the Beginning been allocated to the statement of this Research Methodology , research problem, and its importance, and its goal, and borders , the main problem is Lack of clarity of the concept of real motion (physical) in the sculpture , And how the audience understand the aspects

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Publication Date
Tue Jan 29 2019
Journal Name
Journal Of The College Of Education For Women
Animation from a legitimate perspective
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This study aims at investigating the partial Islamic rules of preparing and distributing cartoons in order to issue an overall Islamic rul. To reach an end, descriptive and analytical approaches are adopted to clarify the nature of cartoons and other related concepts. The researcher, as well, with reference to verses of the Holy Quran, tradition (Hadith) and Islamic jurists, adopts a deductive approach to issue Islamic rules related to the industry of cartoons and it's distribution
The study consists of three sections. The first Section addresses the following issues: Definition animation; and related wordy. The second Section: Origin of Cartoon's history and it's negative and positive effects. The third Section: Islamic rules related

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Publication Date
Wed Jan 01 2025
Journal Name
Iv. International Rimar Congress Of Pure, Applied Sciences
A New Intrusion Detection Approach Based on RNA Encoding and K-Means Clustering Algorithm Using KDD-Cup99 Dataset
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Intrusion detection systems (IDS) are useful tools that help security administrators in the developing task to secure the network and alert in any possible harmful event. IDS can be classified either as misuse or anomaly, depending on the detection methodology. Where Misuse IDS can recognize the known attack based on their signatures, the main disadvantage of these systems is that they cannot detect new attacks. At the same time, the anomaly IDS depends on normal behaviour, where the main advantage of this system is its ability to discover new attacks. On the other hand, the main drawback of anomaly IDS is high false alarm rate results. Therefore, a hybrid IDS is a combination of misuse and anomaly and acts as a solution to overcome the dis

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Publication Date
Sat Oct 31 2020
Journal Name
International Journal Of Intelligent Engineering And Systems
Automatic Computer Aided Diagnostic for COVID-19 Based on Chest X-Ray Image and Particle Swarm Intelligence
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Publication Date
Sun Mar 01 2015
Journal Name
Journal Of Engineering
Digital Orthophoto Production Using Close-Range Photographs for High Curved Objects
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Orthophoto provides a significant alternative capability for the presentation of architectural or archaeological applications. Although orthophoto production from airphotography of high or lower altitudes is considered to be typical, the close range applications for the large-scale survey of statue or art masterpiece or any kind of monuments still contain a lot of interesting issues to be investigated.

In this paper a test was carried out for the production of large scale orthophoto of highly curved surface, using a statue constructed of some kind of stones. In this test we use stereo photographs to produce the orthophoto in stead of single photo and DTM, by applying the DLT mathematical relationship as base formula in differenti

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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of Cybersecurity And Information Management
Machine Learning-based Information Security Model for Botnet Detection
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Botnet detection develops a challenging problem in numerous fields such as order, cybersecurity, law, finance, healthcare, and so on. The botnet signifies the group of co-operated Internet connected devices controlled by cyber criminals for starting co-ordinated attacks and applying various malicious events. While the botnet is seamlessly dynamic with developing counter-measures projected by both network and host-based detection techniques, the convention techniques are failed to attain sufficient safety to botnet threats. Thus, machine learning approaches are established for detecting and classifying botnets for cybersecurity. This article presents a novel dragonfly algorithm with multi-class support vector machines enabled botnet

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Research on Emotion Classification Based on Multi-modal Fusion
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Nowadays, people's expression on the Internet is no longer limited to text, especially with the rise of the short video boom, leading to the emergence of a large number of modal data such as text, pictures, audio, and video. Compared to single mode data ,the multi-modal data always contains massive information. The mining process of multi-modal information can help computers to better understand human emotional characteristics. However, because the multi-modal data show obvious dynamic time series features, it is necessary to solve the dynamic correlation problem within a single mode and between different modes in the same application scene during the fusion process. To solve this problem, in this paper, a feature extraction framework of

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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of Al-farabi For Engineering Sciences Vol
Prototyping of Multi-Factors Based Vehicle Accident Detection and Reporting System Relying on GPS and GSM
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