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A comparison study on node clustering techniques used in target tracking WSNs for efficient data aggregation
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Wireless sensor applications are susceptible to energy constraints. Most of the energy is consumed in communication between wireless nodes. Clustering and data aggregation are the two widely used strategies for reducing energy usage and increasing the lifetime of wireless sensor networks. In target tracking applications, large amount of redundant data is produced regularly. Hence, deployment of effective data aggregation schemes is vital to eliminate data redundancy. This work aims to conduct a comparative study of various research approaches that employ clustering techniques for efficiently aggregating data in target tracking applications as selection of an appropriate clustering algorithm may reflect positive results in the data aggregation process. In this paper, we have highlighted the gains of the existing schemes for node clustering based data aggregation along with a detailed discussion on their advantages and issues that may degrade the performance. Also, the boundary issues in each type of clustering technique have been analyzed. Simulation results reveal that the efficacy and validity of these clustering-based data aggregation algorithms are limited to specific sensing situations only, while failing to exhibit adaptive behavior in various other environmental conditions.

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Publication Date
Wed Jan 01 2025
Journal Name
Journal Of Engineering And Sustainable Development
Improving Performance Classification in Wireless Body Area Sensor Networks Based on Machine Learning Techniques
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Wireless Body Area Sensor Networks (WBASNs) have garnered significant attention due to the implementation of self-automaton and modern technologies. Within the healthcare WBASN, certain sensed data hold greater significance than others in light of their critical aspect. Such vital data must be given within a specified time frame. Data loss and delay could not be tolerated in such types of systems. Intelligent algorithms are distinguished by their superior ability to interact with various data systems. Machine learning methods can analyze the gathered data and uncover previously unknown patterns and information. These approaches can also diagnose and notify critical conditions in patients under monitoring. This study implements two s

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Publication Date
Sun Mar 01 2015
Journal Name
5th International Conference On Energy Aware Computing Systems & Applications
Area efficient test circuit for library standard cell qualification
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High cost of qualifying library standard cells on silicon wafer limits the number of test circuits on the test chip. This paper proposes a technique to share common load circuits among test circuits to reduce the silicon area. By enabling the load sharing, number of transistors for the common load can be reduced significantly. Results show up to 80% reduction in silicon area due to load area reduction.

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Publication Date
Wed Feb 01 2023
Journal Name
Baghdad Science Journal
Efficient Approach for Solving (2+1) D- Differential Equations
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     In this article, a new efficient approach is presented to solve a type of partial differential equations, such (2+1)-dimensional differential equations non-linear, and nonhomogeneous. The procedure of the new approach is suggested to solve important types of differential equations and get accurate analytic solutions i.e., exact solutions. The effectiveness of the suggested approach based on its properties compared with other approaches has been used to solve this type of differential equations such as the Adomain decomposition method, homotopy perturbation method, homotopy analysis method, and variation iteration method. The advantage of the present method has been illustrated by some examples.

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Publication Date
Fri Jul 19 2019
Journal Name
Iraqi Journal Of Science
Efficient Iterative Method for Solving Korteweg-de Vries Equations
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The Korteweg-de Vries equation plays an important role in fluid physics and applied mathematics. This equation is a fundamental within study of shallow water waves. Since these equations arise in many applications and physical phenomena, it is officially showed that this equation has solitary waves as solutions, The Korteweg-de Vries equation is utilized to characterize a long waves travelling in channels. The goal of this paper is to construct the new effective frequent relation to resolve these problems where the semi analytic iterative technique presents new enforcement to solve Korteweg-de Vries equations. The distinctive feature of this method is, it can be utilized to get approximate solutions for travelling waves of 

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Publication Date
Tue Oct 08 2024
Journal Name
Technology In Agronomy
Harnessing automation techniques for supporting sustainability in agriculture
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Automation is one of the key systems in modern agriculture, providing potential solutions to the challenges related to the growing world population, demographic shifts, and economic situation. The present article aims to highlight the importance of precision agriculture (PA) and smart agriculture (SA) in increasing agricultural production and the importance of environmental protection in increasing production and reducing traditional production. For this purpose, different types of automation systems in the field of agricultural operations are discussed, as well as smart agriculture technologies including the Internet of Things (IoT), artificial intelligence (AI), machine learning (ML), big data analysis, in addition to agricultural robots,

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Publication Date
Mon Apr 11 2011
Journal Name
Icgst
Employing Neural Network and Naive Bayesian Classifier in Mining Data for Car Evaluation
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In data mining, classification is a form of data analysis that can be used to extract models describing important data classes. Two of the well known algorithms used in data mining classification are Backpropagation Neural Network (BNN) and Naïve Bayesian (NB). This paper investigates the performance of these two classification methods using the Car Evaluation dataset. Two models were built for both algorithms and the results were compared. Our experimental results indicated that the BNN classifier yield higher accuracy as compared to the NB classifier but it is less efficient because it is time-consuming and difficult to analyze due to its black-box implementation.

Publication Date
Fri May 29 2020
Journal Name
International Journal Of Psychosocial Rehabilitation
Image Fusion Techniques: A Review
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Image Fusion is being used to gather important data from such an input image array and to place it in a single output picture to make it much more meaningful & usable than either of the input images. Image fusion boosts the quality and application of data. The accuracy of the image that has fused depending on the application. It is widely used in smart robotics, audio camera fusion, photonics, system control and output, construction and inspection of electronic circuits, complex computer, software diagnostics, also smart line assembling robots. In this paper provides a literature review of different image fusion techniques in the spatial domain and frequency domain, such as averaging, min-max, block substitution, Intensity-Hue-Saturation(IH

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Publication Date
Mon Jun 05 2023
Journal Name
Journal Of Engineering
An Investigation to the Abrasive Wear in Pipes Used for Oil Industry
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The work reported in this study focusing on the abrasive wear behavior for three types of pipes used in oil industries (Carbone steel, Alloy steel and Stainless steel) using a wear apparatus for dry and wet tests, manufactured according to ASTM G65. Silica sand with
hardness (1000-1100) HV was used as abrasive material. The abrasive wear of these pipes has been measured experimentally by measuring the wear rate for each case under different sliding speeds, applied loads, and sand conditions (dry or wet). All tests have been conducted using sand of particle size (200-425) µm, ambient temperature of 34.5 °C and humidity 22% (Lab conditions).
The results show that the material loss due to abrasive wear increased monotonically with

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Publication Date
Sun Jan 14 2018
Journal Name
Journal Of Engineering
Efficient Cost Management in the Housing Projects
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The cost management of cost indicators in housing projects, on the level of planning and design, is the most important quality indicators, for adoption of strategies of planning and design efficient in managing these indicators. So this research points out the need to highlight the most effective and influential cost indicators in housing projects, and to determine strategies in the management of these indicators in order to raise the efficiency of housing projects quality, to seemly the income level target group, taking into consideration the quality of housing standards, to achieve the basic requirements of housing. This paper highlights the importance of the cost  management, the types of housing cost, the method

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Publication Date
Thu Oct 01 2015
Journal Name
Journal Of Engineering
Development of Spatial Data Infrastructure based on Free Data Integration
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In recent years, the performance of Spatial Data Infrastructures for governments and companies is a task that has gained ample attention. Different categories of geospatial data such as digital maps, coordinates, web maps, aerial and satellite images, etc., are required to realize the geospatial data components of Spatial Data Infrastructures. In general, there are two distinct types of geospatial data sources exist over the Internet: formal and informal data sources. Despite the growth of informal geospatial data sources, the integration between different free sources is not being achieved effectively. The adoption of this task can be considered the main advantage of this research. This article addresses the research question of ho

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