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Implementation of digital chaotic signal generator based on reconfigurable LFSRs for multiple access communications
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This paper describes the digital chaotic signal with ship map design. The robust digital implementation eliminates the variation tolerance and electronics noise problems common in analog chaotic circuits. Generation of good non-repeatable and nonpredictable random sequences is of increasing importance in security applications. The use of 1-D chaotic signal to mask useful information and to mask it unrecognizable by the receiver is a field of research in full expansion. The piece-wise 1-D map such as ship map is used for this paper. The main advantages of chaos are the increased security of the transmission and ease of generation of a great number of distinct sequences. As consequence, the number of users in the systems can be increased. Recent investigations show that wireless communication systems are very promising application area of chaotic dynamics. A feature of chaotic signals is super wide bandwidth; the power spectrum extends both to the region of very low frequencies as well as to high frequencies. For the proposed system, the bandwidth is extended from approximately 100 Hz to 50 MHz. The nature of chaotic signal is an aperiodic. Therefore, the resolution of the proposed system is high to provide an aperiodicity of the chaotic signal. In practice the following simulation results on MATLAB software platform show that the effectiveness of the model described which has low-cross-correlation and can meet the actual need. Simulation results show sequence length in 264-1-bit with cross-correlation less than 0.0025 for our architecture.

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Publication Date
Tue Oct 20 2020
Journal Name
International Journal Of Civil Engineering
Structural Performance Under Monotonic Static Loading of Reinforced Concrete Gable Roof Beams with Multiple Web Openings
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In the present study, an attempt has been made to experimentally investigate the flexural performance of ten simply supported reinforced concrete gable roof beams, including solid control specimen (i.e., without openings) and nine beams with web openings of different dimensions and configurations. The nine beams with openings have identical reinforcement details. All beams were monotonically loaded to failure under mid-span loading. The main variables were the number of the created openings, the total area of the created openings, and the inclination angle of the posts between openings. Of interest is the load-carrying capacity, cracking resistance and propagation, deformability, failure mode, and strain development that represent the behav

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Publication Date
Mon Dec 01 2014
Journal Name
Iraqi Journal Of Science
Detection of human leukocyte antigen and celiac disease auto antibodies in serum of patients with multiple sclerosis
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To determine the important pathogenic role of celiac disease in triggering several autoimmune disease, thirty patients with Multiple Sclerosis of ages (22-55) years have been investigated and compared with 25 healthy individuals. All the studied groups were carried out to measure anti-tissue transglutaminase antibodies IgA IgG by ELISA test, anti-reticulin antibodies IgA and IgG, and anti-endomysial antibodies IgA and IgG by IFAT. There was a significant elevation in the concentration of anti-tissue transglutaminase antibodies IgA and IgG compared to control groups (P≤0.05), there was 4(13.33%) positive results for anti-reticulin antibodies IgA and IgG , 3(10%) positive results for anti-endomysial antibodies IgA and IgG . There were 4 pos

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Publication Date
Mon Dec 01 2014
Journal Name
Iraqi Journal Of Science,
Detection of human leukocyte antigen and celiac disease auto antibodies in serum of patients with multiple sclerosis
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To determine the important pathogenic role of celiac disease in triggering several autoimmune disease, thirty patients with Multiple Sclerosis of ages (22-55) years have been investigated and compared with 25 healthy individuals. All the studied groups were carried out to measure anti-tissue transglutaminase antibodies IgA IgG by ELISA test, anti-reticulin antibodies IgA and IgG, and anti-endomysial antibodies IgA and IgG by IFAT. There was a significant elevation in the concentration of anti-tissue transglutaminase antibodies IgA and IgG compared to control groups (P≤0.05), there was 4(13.33%) positive results for anti-reticulin antibodies IgA and IgG , 3(10%) positive results for anti-endomysial antibodies IgA and IgG . There were 4 pos

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Publication Date
Tue Mar 09 2021
Journal Name
Romanian Neurosurgery
Primary multiple cerebral hydatid disease in a young patient with surgically-treated intracerebral haemorrhage
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Introduction:  Cerebral hydatid disease (CHD) is rare and the multiple-cystic variety is even rarer. In this paper, we report a case of multiple CHD and explore a possible link with a preceding spontaneous intracerebral haemorrhage (ICH).   Case presentation: A 27-year old gentleman with a history of surgically-evacuated, spontaneous ICH presented with severe headache, left-sided weakness - Medical Research Council (MRC) grade II - and recurrent tonic-clonic seizures, while on a full dose of anti-epileptic medication. Brain magnetic resonance imaging (MRI) scans showed multiple intra-axial cystic lesions in the right hemisphere. The cysts were removed intact using Dowling’s technique through a large temporoparietal crani

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Publication Date
Mon Mar 15 2021
Journal Name
Al-academy
tv series with multiple parts from the viewers viewpoint: عبد الكريم حسين عباس السوداني
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TV drama has gone through many developmental stages until it reached and settled in the form of TV series of thirty episodes. Alongside the development of the TV technologies and the widespread of satellite channels, the form of the TV drama has changed and the series has consisted of two parts and then parts multiplied until they amounted to ten parts and more. This form of TV drama has become an artistic phenomenon, that once the series is displayed on one of the channels and achieves a noticeable success, its producers work to produce a second part of that series and so on. This form of TV drama has remained away from being researched.
This has urged the researcher to accomplish this study entitled (TV series of multiple parts fro

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Publication Date
Thu Jun 01 2023
Journal Name
Neurology Asia
Integrin alpha-4 gene polymorphism in relation to natalizumab response in multiple sclerosis patients
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Objectives: The aim of this study was to assess the possible the association between +3061 (G>A, rs1143676) missense mutation in exon 24 of the integrin α-4 subunit (ITGA-4) gene and the response to natalizumab in a sample of Iraqi multiple sclerosis patients. Methods: A sample of 59 patients with multiple sclerosis (16 males and 43 females; mean age of 32 years; age range of 15 to 52 years) receiving natalizumab for at least 12 consecutive months were involved in the study between March and August/ 2022. The sample was categorized into two groups according to their response to natalizumab treatment (responders and non-responders). Polymerase chain reaction and Sanger’s sequencing for the extracted deoxyribonucleic acid was pe

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Publication Date
Tue Jul 01 2014
Journal Name
Computer Engineering And Intelligent Systems
Static Analysis Based Behavioral API for Malware Detection using Markov Chain
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Researchers employ behavior based malware detection models that depend on API tracking and analyzing features to identify suspected PE applications. Those malware behavior models become more efficient than the signature based malware detection systems for detecting unknown malwares. This is because a simple polymorphic or metamorphic malware can defeat signature based detection systems easily. The growing number of computer malwares and the detection of malware have been the concern for security researchers for a large period of time. The use of logic formulae to model the malware behaviors is one of the most encouraging recent developments in malware research, which provides alternatives to classic virus detection methods. To address the l

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Publication Date
Sun Apr 01 2018
Journal Name
2018 9th International Conference On Information And Communication Systems (icics)
An intersection-based segment aware algorithm for geographic routing in VANETs
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In networking communication systems like vehicular ad hoc networks, the high vehicular mobility leads to rapid shifts in vehicle densities, incoherence in inter-vehicle communications, and challenges for routing algorithms. It is necessary that the routing algorithm avoids transmitting the pockets via segments where the network density is low and the scale of network disconnections is high as this could lead to packet loss, interruptions and increased communication overhead in route recovery. Hence, attention needs to be paid to both segment status and traffic. The aim of this paper is to present an intersection-based segment aware algorithm for geographic routing in vehicular ad hoc networks. This algorithm makes available the best route f

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
Indoor/Outdoor Deep Learning Based Image Classification for Object Recognition Applications
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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 se

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
AlexNet-Based Feature Extraction for Cassava Classification: A Machine Learning Approach
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Cassava, a significant crop in Africa, Asia, and South America, is a staple food for millions. However, classifying cassava species using conventional color, texture, and shape features is inefficient, as cassava leaves exhibit similarities across different types, including toxic and non-toxic varieties. This research aims to overcome the limitations of traditional classification methods by employing deep learning techniques with pre-trained AlexNet as the feature extractor to accurately classify four types of cassava: Gajah, Manggu, Kapok, and Beracun. The dataset was collected from local farms in Lamongan Indonesia. To collect images with agricultural research experts, the dataset consists of 1,400 images, and each type of cassava has

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