: In modern optical communication system, noise rejection multiple access interference (MAI) must be rejected in dense access network (DAN). This paper will study the dual optical band pass and notch filters. They will be extracted with tunable FWHM using 10cm (PMF) with different cladding diameters formed with etching 125μm PMF after immersing it with 40% of hydrofluoric acid (HF). This fiber acts as assessing fiber to perform Sagnac interferometer with splicing regions that placed 12cm (SMF) for performing hybrid Sagnac interferometer that consists of Mach-Zehnder instead of Sagnac loop which is illuminated by using laser source with centroid wavelength of 1546.7nm and FWHM of 286 pm or 9 ns in the time domain. . Firstly, Three PMF with the same lengths but with different etching durations (10, 20 and 30) min. Secondly, each of these PMFs with different etching durations will affected under tunable stressing forces (10, 20, 50 and100) g applying on cross sectional area and two weights of (5, 10, 25 and 50) g putting on both micro splicing area separately. The minimum FWHM of dual optical band pass and notch filters at specific etching time with mechanical forces getting the best values equal to 123pm and 90pm, respectively. The study found that the HSI interferometer can be used efficiently as a narrow notch filter in integrated optical communication systems since it has high sensitivity in the pm range.
Polynomial IIR digital filters play a crucial role in the process of image data compression. The main purpose of designing polynomial IIR digital filters of the integer parameters space and introduce efficient filters to compress image data using a singular value decomposition algorithm. The proposed work is designed to break down the complex topic into bite-sized pieces of image data compression through the lens of compression image data using Infinite Impulse Response Filters. The frequency response of the filters is measured using a real signal with an automated panoramic measuring system developed in the virtual instrument environment. The analysis of the output signal showed that there are no limit cycles with a maximum radius
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Image compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye
... Show MoreThe complexity and variety of language included in policy and academic documents make the automatic classification of research papers based on the United Nations Sustainable Development Goals (SDGs) somewhat difficult. Using both pre-trained and contextual word embeddings to increase semantic understanding, this study presents a complete deep learning pipeline combining Bidirectional Long Short-Term Memory (BiLSTM) and Convolutional Neural Network (CNN) architectures which aims primarily to improve the comprehensibility and accuracy of SDG text classification, thereby enabling more effective policy monitoring and research evaluation. Successful document representation via Global Vector (GloVe), Bidirectional Encoder Representations from Tra
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The fiscal position of governments in rentier economies depends heavily on oil revenues. The relationship between oil prices and the budget surplus or deficit is often nonlinear and characterized by complex temporal dependencies, which may limit the predictive capability of conventional econometric models. Accordingly, this study aims to forecast the Iraqi budget surplus and deficit and compare the predictive performance of the ARDL, NARDL, LSTM, 1D-CNN, and hybrid 1D-CNN-LSTM models using oil prices as the primary predictive variable. The hybrid model integrates the feature-extraction capability of One-Dimensional Convolutional Neural Networks (1D-CNN) with the ability of Long Short-Term Memory (LSTM) networks to capture long-term
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This paper introduces a novel nonparametric hybrid cyber-intelligence-based statistical process control and anomaly detection framework in time series data. It is developed to overcome the shortcomings of the classical control schemes in dealing with complex, abnormal, and noisy input data, especially when it is autocorrelated. The proposed methodology combines three technical pillars: First, it utilizes a bidirectional long-short-term memory architecture (Bi-LSTM) to capture long-term time dependency and learn nonlinear patterns, leaving only true deviations as residuals that remove trends and noises from the market. Second, it adopts the Golden Eagle Optimizer (GEO) algorithm for optimal parameter selection. This intelligent algor
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The plethora of the emerged radio frequency applications makes the frequency spectrum crowded by many applications and hence the ability to detect specific application’s frequency without distortion is a difficult task to achieve.
The goal is to achieve a method to mitigate the highest interferer power in the frequency spectrum in order to eliminate the distortion.
This paper presents the application of the proposed tunable 6th-order notch filter on Ultra-Wideband (UWB) Complementary Metal-Oxide-Semiconductor (CMOS) Low Noise
Visual discourse in cinema and television is an expressive medium that carries its audio and visual elements and is effective in influencing the memory of the recipient, according to multiple patterns of forms and representations aimed at persuasion, influence, entertainment, enjoyment and knowledge. This speech will not pass by the recipient without difficulty, as the multiplicity of forms and techniques of image presentation and the diversity of contents derived from different beliefs, concepts, ideas and perceptions may sometimes reach intersections and conflicts, which is reflected in the form of the screen and the theory of television. This motivates us to know the ways in which audio-visual discourse is produced on television, whic
... Show MoreThe present work focuses on the changing of the structural characteristics of the grown materials through different material characterization methods. Semiconductor CdSxSe 1-x nano crystallines have been synthesized by chemical vapor depostion. (X- ray Diffraction; XRD), (Field Emission Scanning Electron Microscopy; FESEM), measured the characterization of Semiconductor CdSxSe1-x nano crystallines. The optical properties of semiconductor CdSxSe1-x nanocrystallines have been studied by the photoluminescence (PL) (He-Cd pulsed ultraviolet laser at 325nm excitation wavelength) at room temperature. The results showed the change rule of photoluminsence peak at different S
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