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Data Aggregation in Wireless Sensor Networks Using Modified Voronoi Fuzzy Clustering Algorithm
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Data centric techniques, like data aggregation via modified algorithm based on fuzzy clustering algorithm with voronoi diagram which is called modified Voronoi Fuzzy Clustering Algorithm (VFCA) is presented in this paper. In the modified algorithm, the sensed area divided into number of voronoi cells by applying voronoi diagram, these cells are clustered by a fuzzy C-means method (FCM) to reduce the transmission distance. Then an appropriate cluster head (CH) for each cluster is elected. Three parameters are used for this election process, the energy, distance between CH and its neighbor sensors and packet loss values. Furthermore, data aggregation is employed in each CH to reduce the amount of data transmission which lead to extend the network lifetime and reduce the traffic that may be accrue in the buffer of sink node. Each cluster head collected data from its members and forwards it to the sink node. A comparative study between modified VFCA and LEACH protocol is implemented in this paper and shows that the modified VFCA is more efficient than LEACH protocol in terms of network lifetime and average energy consumption. Another comparative study between modified VFCA and K-Means clustering algorithm is presented and shows that the modified VFCA is more efficient than K-Means clustering algorithm in terms of  packets transmitted to sink node, buffer utilization, packet loss values and running time. A simulation process is developed and tested using Matlab R2010a program in a computer having the following properties: windows 7 (32-bit operating system), core i7, RAM 4GB, hard 1TB.

 

 

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Publication Date
Sun Jan 01 2023
Journal Name
Ieee Access
Fuzzy-Based Ensemble Feature Selection for Automated Estimation of Speaker Height and Age Using Vocal Characteristics
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Publication Date
Sun Sep 24 2023
Journal Name
Journal Of Al-qadisiyah For Computer Science And Mathematics
Iris Data Compression Based on Hexa-Data Coding
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Iris research is focused on developing techniques for identifying and locating relevant biometric features, accurate segmentation and efficient computation while lending themselves to compression methods. Most iris segmentation methods are based on complex modelling of traits and characteristics which, in turn, reduce the effectiveness of the system being used as a real time system. This paper introduces a novel parameterized technique for iris segmentation. The method is based on a number of steps starting from converting grayscale eye image to a bit plane representation, selection of the most significant bit planes followed by a parameterization of the iris location resulting in an accurate segmentation of the iris from the origin

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Publication Date
Thu May 31 2012
Journal Name
Al-khwarizmi Engineering Journal
Channel Estimation and Prediction Based Adaptive Wireless Communication Systems
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Wireless channels are typically much more noisy than wired links and subjected to fading due to multipath  propagation which result in ISI and hence high error rate. Adaptive modulation is a powerful technique to improve the tradeoff between spectral efficiency and Bit Error Rate (BER). In order to adjust the transmission rate, channel state information (CSI) is required at the transmitter side.

In this paper the performance enhancement of using linear prediction along with channel estimation to track the channel variations and adaptive modulation were examined. The simulation results shows that the channel estimation is sufficient for low Doppler frequency shifts (<30 Hz), while channel prediction is much more suited at

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Publication Date
Fri Jun 01 2018
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Improvement of Fading Channel Modeling Performance for Wireless Channel
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Fading channel modeling is generally defined as the variation of the attenuation of a signal with various variables. Time, geographical position, and radio frequency which is included. Fading is often modeled as a random process. Thus, a fading channel is a communication channel that experiences fading. In this paper, the proposed system presents a new design and simulate a wireless channel using Rayleigh channels. Rayleigh channels using two approaches (flat and frequency-selective fading channels) in order to calculate some path space loss efforts and analysis the performance of different wireless fading channel modeling. The results show that the bite error rate (BER) performance is dramatically improved in the value of signal to

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Publication Date
Wed May 30 2018
Journal Name
International Journal Of Computer Networks &amp; Communications
Robot Human Interface for Housekeeper Robot with Wireless Capabilities
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Publication Date
Fri Dec 20 2024
Journal Name
Al-qadisiyah Journal Of Pure Science
Weakly and Strongly Forms of Fibrewise Fuzzy ω--Topological Spaces
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Abstract This paper is devoted to introduce weak and strong forms of fibrewise fuzzy u-topological spaces, namely the fibrewise fuzzy q-u-topological spaces, weakly fibrewise fuzzy q-u-topological spaces and strongly fibrewise fuzzy q-utopological spaces. Also, Several characterizations and properties of this class are also given as well. Finally, we focused on studying the relationship between weakly fibrewise fuzzy q-u-topological spaces and strongly fibrewise fuzzy q-utopological spaces.

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Publication Date
Tue Mar 08 2022
Journal Name
International Journal Of Online And Biomedical Engineering (ijoe)
Data Hiding in 3D-Medical Image
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Information hiding strategies have recently gained popularity in a variety of fields. Digital audio, video, and images are increasingly being labelled with distinct but undetectable marks that may contain a hidden copyright notice or serial number, or even directly help to prevent unauthorized duplication. This approach is extended to medical images by hiding secret information in them using the structure of a different file format. The hidden information may be related to the patient. In this paper, a method for hiding secret information in DICOM images is proposed based on Discrete Wavelet Transform (DWT). Firstly. segmented all slices of a 3D-image into a specific block size and collecting the host image depend on a generated key

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Publication Date
Tue Jan 01 2019
Journal Name
Journal Of Communications
SDN Implementation in Data Center Network
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Publication Date
Tue Jul 19 2022
Journal Name
Handbook Of Moth-flame Optimization Algorithm
Moth-Flame Optimization Algorithm, Arithmetic Optimization Algorithm, Aquila Optimizer, Gray Wolf Optimizer, and Sine Cosine Algorithm
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Publication Date
Thu Dec 01 2011
Journal Name
Journal Of Economics And Administrative Sciences
Dynamic algorithm (DRBLTS) and potentially weighted (WBP) to estimate hippocampal regression parameters using a techniqueBootstrap (comparative study)
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Bootstrap is one of an important re-sampling technique which has given the attention of  researches recently. The presence of outliers in the original data set may cause serious problem to the classical bootstrap when the percentage of outliers are higher than the original one. Many methods are proposed to overcome this problem such  Dynamic Robust Bootstrap for LTS (DRBLTS) and Weighted Bootstrap with Probability (WBP). This paper try to show the accuracy of parameters estimation by comparison the results of both methods. The bias , MSE and RMSE are considered. The criterion of the accuracy is based on the RMSE value since the method that provide us RMSE value smaller than other is con

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