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alkej-37
Performance Improvement of Neural Network Based RLS Channel Estimators in MIMO-OFDM Systems
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The objective of this study was tointroduce a recursive least squares (RLS) parameter estimatorenhanced by using a neural network (NN) to facilitate the computing of a bit error rate (BER) (error reduction) during channels estimation of a multiple input-multiple output orthogonal frequency division multiplexing (MIMO-OFDM) system over a Rayleigh multipath fading channel.Recursive least square is an efficient approach to neural network training:first, the neural network estimator learns to adapt to the channel variations then it estimates the channel frequency response. Simulation results show that the proposed method has better performance compared to the conventional methods least square (LS) and the original RLS and it is more robust at high speed mobility.

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Publication Date
Tue Jan 01 2019
Journal Name
Ieee Access
Sensing Performance of Modified Single Mode Optical Fiber Coated With Nanomaterials-Based Ammonia Sensors Operated in the C-Band
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Publication Date
Sun Jun 30 2024
Journal Name
Management And Social Perspectives
The Role of Green Target Costing in Improving Supplier Relations
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This study aims to explain the role of green target costing technique in improving the relationship with suppliers in a sample of industrial companies listed on the Iraq Stock Exchange. The descriptive analytical approach was used, where a questionnaire was designed that included a set of questions that were directed to a sample of 84 individuals including production managers, finance managers, quality managers, and purchasing managers in these companies. The study uses some statistical analyzes such as correlation analysis and regression analysis to analyze the questionnaires. The study finds a positive impact of the green target costing technique on improving the relationship with suppliers. The results indicate that the relation

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Publication Date
Thu Jun 01 2023
Journal Name
Baghdad Science Journal
Modeling The Power Grid Network Of Iraq
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Recently, the theory of Complex Networks gives a modern insight into a variety of applications in our life. Complex Networks are used to form complex phenomena into graph-based models that include nodes and edges connecting them. This representation can be analyzed by using network metrics such as node degree, clustering coefficient, path length, closeness, betweenness, density, and diameter, to mention a few. The topology of the complex interconnections of power grids is considered one of the challenges that can be faced in terms of understanding and analyzing them. Therefore, some countries use Complex Networks concepts to model their power grid networks. In this work, the Iraqi Power Grid network (IPG) has been modeled, visua

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Publication Date
Mon Feb 02 2026
Journal Name
Al–bahith Al–a'alami
THE SEMIOTICS OF PROPAGANDA SPEECH IN SOCIAL MEDIA SITES (A Semiotic Study of the News Reports on the Israeli "Makan" Channel)
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Technological and digital development has allowed the emergence of many methods of producing semantics on social media sites within semiotic and propagandistic frameworks. This is what made the image appear in different molds and shapes, especially as it is the first material for visual perception.
This made the Israeli propaganda discourse use it as an important tool to manage the content of suggestive messages with semiological connotations. By doing so, such tool uses social networking sites as an appropriate environment to achieve those goals, which are related to cases of manipulating emotions and minds. It, moreover, changes convictions, attitudes, trends and behaviors according to what the propaganda planner wants.
Many Isra

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Publication Date
Mon Jan 01 2024
Journal Name
Fifth International Conference On Applied Sciences: Icas2023
Facial deepfake performance evaluation based on three detection tools: MTCNN, Dlib, and MediaPipe
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Publication Date
Thu Jun 20 2019
Journal Name
Baghdad Science Journal
Using Backpropagation to Predict Drought Factor in Keetch-Byram Drought Index
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Forest fires continue to rise during the dry season and they are difficult to stop. In this case, high temperatures in the dry season can cause an increase in drought index that could potentially burn the forest every time. Thus, the government should conduct surveillance throughout the dry season. Continuous surveillance without the focus on a particular time becomes ineffective and inefficient because of preventive measures carried out without the knowledge of potential fire risk. Based on the Keetch-Byram Drought Index (KBDI), formulation of Drought Factor is used just for calculating the drought today based on current weather conditions, and yesterday's drought index. However, to find out the factors of drought a day after, the data

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Publication Date
Fri Dec 31 2021
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
IMPACT OF COMBINATION OF FENUGREEK SEEDS (Nigella sativa), LAURELS LEAVE (Laurus nobilis) AND VITAMIN C ON SOME EGG QUALITY CHARACTERISTICS OF QUAIL: IMPACT OF COMBINATION OF FENUGREEK SEEDS (Nigella sativa), LAURELS LEAVE (Laurus nobilis) AND VITAMIN C ON SOME EGG QUALITY CHARACTERISTICS OF QUAIL
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The results of the study showed the statistical significant difference (P≥0.05) for each of the relative weight of the yolk and egg whites, the relative weight of the shell and the Hauh unit, which is affected positively by the addition of ground fenugreek seed and Laurels leave to the quail bird's diet. There is also a statistically significant difference positively for each of the percentage of ash, protein and carbohydrates for qualis egg, while there is no significant difference for both the percentage of moisture and fat. The results of the mineral estimation showed an increase in each of the elements of iron, copper and cadmium from the addition of fenugreek and laurels leave, while there was no significant difference for

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Publication Date
Sat Dec 01 2018
Journal Name
Nano Hybrids And Composites
Specific NH<sub>3</sub> Gas Sensor Worked at Room Temperature Based on MWCNTs-OH Network
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Functionalized Multi-Walled Carbon Nanotubes (MWCNTs-OH) network with thickness 4μm was made by the vacuum filtration from suspension (FFS) method. The morphology, structure and optical properties of the MWCNTs film were characterized by SEM and UV-Vis. spectra techniques. The SEM images reflected highly ordered network in the form of ropes or bundles with close-packing which looks like spaghetti. The absorbance spectrum revealed that the network has a good absorbance in the UV-Vis. region. The gas sensor system was used to test the MWCNT-OH network to detect NH3gas at room temperature. The resistance of the sensor was increased when exposed to the NH3gas. The sensitivities of the network w

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Publication Date
Sat Mar 31 2018
Journal Name
Journal Of Engineering
Energy and Exergy Analysis of Dual Channel Solar Air Collector with Different Absorber Plates Geometry
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Flat-plate collector considers most common types of collectors, for ease of manufacturing and low price compared with other collectors. The main aim of the present work is to increase the efficiency of the collector, which can be achieved by improving the heat transfer and minimize heat loss experimentally. Five types of solar air collectors have been tested, which conventional channel with a smooth absorber plate (model I), dual channel with a smooth absorber plate (model II), dual channel with perforating “V” corrugated absorber plate (model III), dual channel with internal attached wire mesh (model Ⅳ), and dual channel with absorber sheet of transparent honeycomb, (model Ⅴ). The dual channel collector used for

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Publication Date
Fri Aug 12 2022
Journal Name
Future Internet
Improved DDoS Detection Utilizing Deep Neural Networks and Feedforward Neural Networks as Autoencoder
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Software-defined networking (SDN) is an innovative network paradigm, offering substantial control of network operation through a network’s architecture. SDN is an ideal platform for implementing projects involving distributed applications, security solutions, and decentralized network administration in a multitenant data center environment due to its programmability. As its usage rapidly expands, network security threats are becoming more frequent, leading SDN security to be of significant concern. Machine-learning (ML) techniques for intrusion detection of DDoS attacks in SDN networks utilize standard datasets and fail to cover all classification aspects, resulting in under-coverage of attack diversity. This paper proposes a hybr

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Scopus (37)
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