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Perceptually Important Points-Based Data Aggregation Method for Wireless Sensor Networks
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The transmitting and receiving of data consume the most resources in Wireless Sensor Networks (WSNs). The energy supplied by the battery is the most important resource impacting WSN's lifespan in the sensor node. Therefore, because sensor nodes run from their limited battery, energy-saving is necessary. Data aggregation can be defined as a procedure applied for the elimination of redundant transmissions, and it provides fused information to the base stations, which in turn improves the energy effectiveness and increases the lifespan of energy-constrained WSNs. In this paper, a Perceptually Important Points Based Data Aggregation (PIP-DA) method for Wireless Sensor Networks is suggested to reduce redundant data before sending them to the sink. By utilizing Intel Berkeley Research Lab (IBRL) dataset, the efficiency of the proposed method was measured. The experimental findings illustrate the benefits of the proposed method as it reduces the overhead on the sensor node level up to 1.25% in remaining data and reduces the energy consumption up to 93% compared to prefix frequency filtering (PFF) and ATP protocols.

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Publication Date
Wed Aug 01 2018
Journal Name
Engineering And Technology Journal
A Proposed Method for the Sound Recognition Process
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Publication Date
Tue Jan 06 2026
Journal Name
Journal Of Physical Education
The Contribution of Ball Launching and Ring Entrance Angle Variables in 3 points Jump Shot in Basketball
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The research aimed at identifying the values of ball launch and ring entrance angle and relations among them as well as identifying the contribution of ball launch and angle variables in 3 point jump in basketball. The researchers hypothesized statistical relation between ball launch and entrance angle. They used the descriptive method on (10) basketball players best known for their 3 point jump shot. Each player is given (10) attempts and only attempts with a larger entrance angle in recorded. The results showed that the height of ball launch players an integral role in decreasing entrance angle as well as ball launch angle did not correlate with the entrance angle. Finally, ball launch variables have no effect or contribution on ball entr

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Publication Date
Tue Sep 28 2021
Journal Name
Journal Of Physical Education
The Contribution of Ball Launching and Ring Entrance Angle Variables in 3 points Jump Shot in Basketball
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    The research aimed at identifying the values of ball launch and ring entrance angle and relations among them as well as identifying the contribution of ball launch and angle variables in 3 point jump in basketball. The researchers hypothesized statistical relation between ball launch and entrance angle. They used the descriptive method on (10) basketball players best known for their 3 point jump shot. Each player is given (10) attempts and only attempts with a larger entrance angle in recorded. The results showed that the height of ball launch players an integral role in decreasing entrance angle as well as ball launch angle did not correlate with the entrance angle. Finally, ball launch variables have no effect or contribution on ba

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Publication Date
Mon Jun 19 2023
Journal Name
Journal Of Engineering
Data Classification using Quantum Neural Network
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In this paper, integrated quantum neural network (QNN), which is a class of feedforward

neural networks (FFNN’s), is performed through emerging quantum computing (QC) with artificial neural network(ANN) classifier. It is used in data classification technique, and here iris flower data is used as a classification signals. For this purpose independent component analysis (ICA) is used as a feature extraction technique after normalization of these signals, the architecture of (QNN’s) has inherently built in fuzzy, hidden units of these networks (QNN’s) to develop quantized representations of sample information provided by the training data set in various graded levels of certainty. Experimental results presented here show that

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Publication Date
Mon Dec 05 2022
Journal Name
Baghdad Science Journal
K-Nearest Neighbor Method with Principal Component Analysis for Functional Nonparametric Regression
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This paper proposed a new  method to study functional non-parametric regression data analysis with conditional expectation in the case that the covariates  are functional and the Principal Component Analysis was utilized to de-correlate the multivariate response variables. It  utilized the formula of the Nadaraya Watson estimator (K-Nearest Neighbour (KNN)) for prediction with different types of the semi-metrics, (which are based on Second Derivative and Functional Principal Component Analysis (FPCA))  for measureing the closeness between curves.  Root Mean Square Errors is used for the  implementation of this model which is then compared to the independent response method. R program is used for analysing data. Then, when  the cov

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Publication Date
Sat Dec 30 2023
Journal Name
Journal Of Economics And Administrative Sciences
The Cluster Analysis by Using Nonparametric Cubic B-Spline Modeling for Longitudinal Data
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Longitudinal data is becoming increasingly common, especially in the medical and economic fields, and various methods have been analyzed and developed to analyze this type of data.

In this research, the focus was on compiling and analyzing this data, as cluster analysis plays an important role in identifying and grouping co-expressed subfiles over time and employing them on the nonparametric smoothing cubic B-spline model, which is characterized by providing continuous first and second derivatives, resulting in a smoother curve with fewer abrupt changes in slope. It is also more flexible and can pick up on more complex patterns and fluctuations in the data.

The longitudinal balanced data profile was compiled into subgroup

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Publication Date
Sun Oct 21 2018
Journal Name
Journal Of Planner And Development
مشكلات البنى التحتية وسبل معالجتها بأستخدام نظم المعلومات الجغرافية شبكة مياه الشرب –الصرف الصحي –الاتصالات اللاسلكية
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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
Wireless Propagation Multipaths using Spectral Clustering and Three-Constraint Affinity Matrix Spectral Clustering
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This study focused on spectral clustering (SC) and three-constraint affinity matrix spectral clustering (3CAM-SC) to determine the number of clusters and the membership of the clusters of the COST 2100 channel model (C2CM) multipath dataset simultaneously. Various multipath clustering approaches solve only the number of clusters without taking into consideration the membership of clusters. The problem of giving only the number of clusters is that there is no assurance that the membership of the multipath clusters is accurate even though the number of clusters is correct. SC and 3CAM-SC aimed to solve this problem by determining the membership of the clusters. The cluster and the cluster count were then computed through the cluster-wise J

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Publication Date
Wed Dec 30 2009
Journal Name
Journal Of The College Of Languages
نظرة إلى سينية الخنساء
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حاولت الباحث دراسة القصيدة من الناحية الإيقاعية

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Publication Date
Sun Dec 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
Contemporary Challenges for Cloud Computing Data Governance in Information Centers: An analytical study
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Purpose – The Cloud computing (CC) and its services have enabled the information centers of organizations to adapt their informatic and technological infrastructure and making it more appropriate to develop flexible information systems in the light of responding to the informational and knowledge needs of their users. In this context, cloud-data governance has become more complex and dynamic, requiring an in-depth understanding of the data management strategy at these centers in terms of: organizational structure and regulations, people, technology, process, roles and responsibilities. Therefore, our paper discusses these dimensions as challenges that facing information centers in according to their data governance and the impa

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