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Audio Compression Using Transform Coding with LZW and Double Shift Coding
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Home New Trends in Information and Communications Technology Applications Conference paper Audio Compression Using Transform Coding with LZW and Double Shift Coding Zainab J. Ahmed & Loay E. George Conference paper First Online: 11 January 2022 126 Accesses Part of the Communications in Computer and Information Science book series (CCIS,volume 1511) Abstract The need for audio compression is still a vital issue, because of its significance in reducing the data size of one of the most common digital media that is exchanged between distant parties. In this paper, the efficiencies of two audio compression modules were investigated; the first module is based on discrete cosine transform and the second module is based on discrete wavelet transform. The proposed audio compression system consists of the following steps: (1) load digital audio data, (2) transformation (i.e., using bi-orthogonal wavelet or discrete cosine transform) to decompose the audio signal, (3) quantization (depend on the used transform), (4) quantization of the quantized data that separated into two sequence vectors; runs and non-zeroes decomposition to apply the run length to reduce the long-run sequence. Each resulted vector is passed into the entropy encoder technique to implement a compression process. In this paper, two entropy encoders are used; the first one is the lossless compression method LZW and the second one is an advanced version for the traditional shift coding method called the double shift coding method. The proposed system performance is analyzed using distinct audio samples of different sizes and characteristics with various audio signal parameters. The performance of the compression system is evaluated using Peak Signal to Noise Ratio and Compression Ratio. The outcomes of audio samples show that the system is simple, fast and it causes better compression gain. The results show that the DSC encoding time is less than the LZW encoding time.

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Publication Date
Tue Jan 01 2019
Journal Name
Indian Journal Of Public Health Research & Development
Anterior Loop Presence and Extension Using Cone-Beam Computed Tomography
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Publication Date
Sun Dec 01 2019
Journal Name
Al-khwarizmi Engineering Journal
Evaluation and Improvement of Manufacturing System Using Computer Software Arena
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The main purpose of the paper is to identify the controllability of an existing production system; yogurt production line in Abu Ghraib Dairy Factory which has several machines of food processing and packing that has been studied. Through the starting of analysis, instability in production has been found in the factory. The analysis is built depending on experimental observation and data collection for different processing time of the machines, and statistical analysis has been conducted to model the production system. Arena Software is applied for simulating and analyzing the current state of the production system, and results are expanded to improve the system production and efficiency. Research method is applied to contribute in knowi

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Publication Date
Mon Oct 10 2016
Journal Name
Iraqi Journal Of Science
Satellite image classification using KL-transformation and modified vector quantization
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In this work, satellite images classification for Al Chabaish marshes and the area surrounding district in (Dhi Qar) province for years 1990,2000 and 2015 using two software programming (MATLAB 7.11 and ERDAS imagine 2014) is presented. Proposed supervised classification method (Modified Vector Quantization) using MATLAB software and supervised classification method (Maximum likelihood Classifier) using ERDAS imagine have been used, in order to get most accurate results and compare these methods. The changes that taken place in year 2000 comparing with 1990 and in year 2015 comparing with 2000 are calculated. The results from classification indicated that water and vegetation are decreased, while barren land, alluvial soil and shallow water

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Publication Date
Wed May 10 2023
Journal Name
Journal Of Engineering
3-D OBJECT RECOGNITION USING MULTI-WAVELET AND NEURAL NETWORK
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This search has introduced the techniques of multi-wavelet transform and neural network for recognition 3-D object from 2-D image using patches. The proposed techniques were tested on database of different patches features and the high energy subband of discrete multi-wavelet transform DMWT (gp) of the patches. The test set has two groups, group (1) which contains images, their (gp) patches and patches features of the same images as a part of that in the data set beside other images, (gp) patches and features, and group (2) which contains the (gp) patches and patches features the same as a part of that in the database but after modification such as rotation, scaling and translation. Recognition by back propagation (BP) neural network as

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Publication Date
Mon Jan 02 2012
Journal Name
Journal Of Engineering
3-D Object Recognition using Multi-Wavelet and Neural Network
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This search has introduced the techniques of multi-wavelet transform and neural network for recognition 3-D object from 2-D image using patches. The proposed techniques were tested on database of different patches features and the high energy subband of discrete multi-wavelet transform DMWT (gp) of the patches. The test set has two groups, group (1) which contains images, their (gp) patches and patches features of the same images as a part of that in the data set beside other images, (gp) patches and features, and group (2) which contains the (gp) patches and patches features the same as a part of that in the database but after modification such as rotation, scaling and translation. Recognition by back propagation (BP) neural network as com

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Publication Date
Tue Dec 17 2019
Journal Name
Lecture Notes In Electrical Engineering
Aspect Categorization Using Domain-Trained Word Embedding and Topic Modelling
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Aspect-based sentiment analysis is the most important research topic conducted to extract and categorize aspect-terms from online reviews. Recent efforts have shown that topic modelling is vigorously used for this task. In this paper, we integrated word embedding into collapsed Gibbs sampling in Latent Dirichlet Allocation (LDA). Specifically, the conditional distribution in the topic model is improved using the word embedding model that was trained against (customer review) training dataset. Semantic similarity (cosine measure) was leveraged to distribute the aspect-terms to their related aspect-category cognitively. The experiment was conducted to extract and categorize the aspect terms from SemEval 2014 dataset.

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Publication Date
Fri Jan 01 2021
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Stamps extraction using local adaptive k- means and ISODATA algorithms
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<span>One of the main difficulties facing the certified documents documentary archiving system is checking the stamps system, but, that stamps may be contains complex background and surrounded by unwanted data. Therefore, the main objective of this paper is to isolate background and to remove noise that may be surrounded stamp. Our proposed method comprises of four phases, firstly, we apply k-means algorithm for clustering stamp image into a number of clusters and merged them using ISODATA algorithm. Secondly, we compute mean and standard deviation for each remaining cluster to isolate background cluster from stamp cluster. Thirdly, a region growing algorithm is applied to segment the image and then choosing the connected regi

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Publication Date
Wed Jan 19 2022
Journal Name
International Journal Of Inventions In Engineering & Science Technology
Biodiversity in the Northern Region using GIS and Remote Sensing
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Biodiversity, biological diversity, biological diversity, biological diversity, biological diversity, biological diversity, biological diversity (by developmental factors) environmental factors and environmental factors environmental factors and environmental factors and environmental factors Correlation between biology and the succession of geological and historical factors of living organisms and geological and historical factors to the site and what It is surrounded by natural and tourist attractions and the pursuit of scientific methods in order to advance the studies of biological diversity in the region .

Publication Date
Wed Jan 01 2025
Journal Name
Fusion: Practice And Applications
Enhanced EEG Signal Classification Using Machine Learning and Optimization Algorithm
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This paper proposes a better solution for EEG-based brain language signals classification, it is using machine learning and optimization algorithms. This project aims to replace the brain signal classification for language processing tasks by achieving the higher accuracy and speed process. Features extraction is performed using a modified Discrete Wavelet Transform (DWT) in this study which increases the capability of capturing signal characteristics appropriately by decomposing EEG signals into significant frequency components. A Gray Wolf Optimization (GWO) algorithm method is applied to improve the results and select the optimal features which achieves more accurate results by selecting impactful features with maximum relevance

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Publication Date
Sat Oct 09 2021
Journal Name
Applied System Innovation
Design and Optimization of Vertical Axis Wind Turbines Using QBlade
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Wind energy is considered one of the most important sources of renewable energy in the world, because it contributes to reducing the negative effects on the environment. The most important types of wind turbines are horizontal and vertical axis wind turbines. This work presents the full details of design for vertical axis wind turbine (VAWT) and how to find the optimal values of necessary factors. Additionally, the results shed light on the efficiency and performance of the VAWT under different working conditions. It was taken into consideration the variety of surrounding environmental conditions (such as density and viscosity of fluid, number of elements of the blade, etc.) to simulate the working of vertical wind turbines under di

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