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Dual Stages of Speech Enhancement Algorithm Based on Super Gaussian Speech Models
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Various speech enhancement Algorithms (SEA) have been developed in the last few decades. Each algorithm has its advantages and disadvantages because the speech signal is affected by environmental situations. Distortion of speech results in the loss of important features that make this signal challenging to understand. SEA aims to improve the intelligibility and quality of speech that different types of noise have degraded. In most applications, quality improvement is highly desirable as it can reduce listener fatigue, especially when the listener is exposed to high noise levels for extended periods (e.g., manufacturing). SEA reduces or suppresses the background noise to some degree, sometimes called noise suppression algorithms. In this research, the design of SEA based on different speech models (Laplacian model or Gaussian model) has been implemented using two types of discrete transforms, which are Discrete Tchebichef Transform and Discrete Tchebichef-Krawtchouk Transforms. The proposed estimator consists of dual stages of a wiener filter that can effectively estimate the clean speech signal. The evaluation measures' results show the proposed SEA's ability to enhance the noisy speech signal based on a comparison with other types of speech models and a self-comparison based on different types and levels of noise. The presented algorithm's improvements ratio regarding the average SNRseq are 1.96, 2.12, and 2.03 for Buccaneer, White, and Pink noise, respectively.

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Publication Date
Mon May 20 2019
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Modeling Dynamic Background based on Linear Equation
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     Detection moving car in front view is difficult operation because of the dynamic background due to the movement of moving car and the complex environment that surround the car, to solve that, this paper proposed new method based on linear equation to determine the region of interest by building more effective background model to deal with dynamic background scenes. This method exploited the permitted region between cars according to traffic law to determine the region (road) that in front the moving car which the moving cars move on. The experimental results show that the proposed method can define the region that represents the lane in front of moving car successfully with precision over 94%and detection rate 86

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Publication Date
Thu Apr 27 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Signature Verification Based on Moments Technique
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In this research we will present the signature as a key to the biometric authentication technique. I shall use moment invariants as a tool to make a decision about any signature which is belonging to the certain person or not. Eighteen voluntaries give 108 signatures as a sample to test the proposed system, six samples belong to each person were taken. Moment invariants are used to build a feature vector stored in this system. Euclidean distance measure used to compute the distance between the specific signatures of persons saved in this system and with new sample acquired to same persons for making decision about the new signature. Each signature is acquired by scanner in jpg format with 300DPI. Matlab used to implement this system.

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Engineering
Intelligent Congestion Control of 5G Traffic in SDN using Dual-Spike Neural Network
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Software Defined Networking (SDN) with centralized control provides a global view and achieves efficient network resources management. However, using centralized controllers has several limitations related to scalability and performance, especially with the exponential growth of 5G communication. This paper proposes a novel traffic scheduling algorithm to avoid congestion in the control plane. The Packet-In messages received from different 5G devices are classified into two classes: critical and non-critical 5G communication by adopting Dual-Spike Neural Networks (DSNN) classifier and implementing it on a Virtualized Network Function (VNF). Dual spikes identify each class to increase the reliability of the classification

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Publication Date
Tue Feb 20 2018
Journal Name
Reporters, Markers, Dyes, Nanoparticles, And Molecular Probes For Biomedical Applications X
Dual-radiolabeled nanoparticle probes for depth-independent in vivo imaging of enzyme activation
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Publication Date
Fri Jan 01 2016
Journal Name
Modern Applied Science
New Combined Technique for Fingerprint Image Enhancement
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This paper presents a combination of enhancement techniques for fingerprint images affected by different type of noise. These techniques were applied to improve image quality and come up with an acceptable image contrast. The proposed method included five different enhancement techniques: Normalization, Histogram Equalization, Binarization, Skeletonization and Fusion. The Normalization process standardized the pixel intensity which facilitated the processing of subsequent image enhancement stages. Subsequently, the Histogram Equalization technique increased the contrast of the images. Furthermore, the Binarization and Skeletonization techniques were implemented to differentiate between the ridge and valley structures and to obtain one

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Publication Date
Mon Mar 01 2021
Journal Name
Iraqi Journal Of Physics
Enhancement CT Scan Image and Study Electronic, Structural and Vibrational Properties of Iobenguane
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This work is divided into two parts first part study electronic structure and vibration properties of the Iobenguane material that is used in CT scan imaging. Iobenguane, or MIBG, is an aralkylguanidine analog of the adrenergic neurotransmitter norepinephrine and a radiopharmaceutical. It acts as a blocking agent for adrenergic neurons. When radiolabeled, it can be used in nuclear medicinal diagnostic techniques as well as in neuroendocrine antineoplastic treatments. The aim of this work is to provide general information about Iobenguane that can be used to obtain results to diagnose the diseases. The second part study image processing techniques, the CT scan image is transformed to frequency domain using the LWT. Two methods of contrast

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Publication Date
Mon Jan 01 2018
Journal Name
International Journal Of Data Mining, Modelling And Management
Association rules mining using cuckoo search algorithm
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Association rules mining (ARM) is a fundamental and widely used data mining technique to achieve useful information about data. The traditional ARM algorithms are degrading computation efficiency by mining too many association rules which are not appropriate for a given user. Recent research in (ARM) is investigating the use of metaheuristic algorithms which are looking for only a subset of high-quality rules. In this paper, a modified discrete cuckoo search algorithm for association rules mining DCS-ARM is proposed for this purpose. The effectiveness of our algorithm is tested against a set of well-known transactional databases. Results indicate that the proposed algorithm outperforms the existing metaheuristic methods.

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Publication Date
Sat Mar 01 2008
Journal Name
Iraqi Journal Of Physics
Adaptive Smoothing Technique for Remotely Sensed Images Enhancement
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Spatial and frequency domain techniques have been adopted in this search. mean
value filter, median filter, gaussian filter. And adaptive technique consists of
duplicated two filters (median and gaussian) to enhance the noisy image. Different
block size of the filter as well as the sholding value have been tried to perform the
enhancement process.

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Publication Date
Thu Jan 01 2015
Journal Name
Iraqi Journal Of Science
Improved Rijndael Algorithm by Encryption S-Box Using NTRU Algorithm
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With the wide developments of computer applications and networks, the security of information has high attention in our common fields of life. The most important issues is how to control and prevent unauthorized access to secure information, therefore this paper presents a combination of two efficient encryption algorithms to satisfy the purpose of information security by adding a new level of encryption in Rijndael-AES algorithm. This paper presents a proposed Rijndael encryption and decryption process with NTRU algorithm, Rijndael algorithm is widely accepted due to its strong encryption, and complex processing as well as its resistance to brute force attack. The proposed modifications are implemented by encryption and decryption Rijndael

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Publication Date
Wed Feb 22 2023
Journal Name
Iraqi Journal Of Science
Improved Rijndael Algorithm by Encryption S-Box Using NTRU Algorithm
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With the wide developments of computer science and applications of networks, the security of information must be increased and make it more complex. The most important issues is how to control and prevent unauthorized access to secure information, therefore this paper presents a combination of two efficient encryption algorithms to satisfy the purpose of information security by adding a new level of encryption in Rijndael-AES algorithm. This paper presents a proposed Rijndael encryption and decryption process with NTRU algorithm, Rijndael algorithm is important because of its strong encryption. The proposed updates are represented by encryption and decryption Rijndael S-Box using NTRU algorithm. These modifications enhance the degree of

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