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An Improved Cuckoo Search Algorithm for Maximizing the Coverage Range of Wireless Sensor Networks
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The issue of increasing the range covered by a wireless sensor network with restricted sensors is addressed utilizing improved CS employing the PSO algorithm and opposition-based learning (ICS-PSO-OBL). At first, the iteration is carried out by updating the old solution dimension by dimension to achieve independent updating across the dimensions in the high-dimensional optimization problem. The PSO operator is then incorporated to lessen the preference random walk stage's imbalance between exploration and exploitation ability. Exceptional individuals are selected from the population using OBL to boost the chance of finding the optimal solution based on the fitness value. The ICS-PSO-OBL is used to maximize coverage in WSN by converting regional monitoring into point monitoring utilizing the discretization method in WSN. In the experiments, the ICS-PSO-OBL with the standard CS and three CS variants (MACS, ICS-2, and ICS) are utilized to execute the simulation experiment under different numbers of nodes (20 and 30, respectively). The experimental results reveal that the optimized coverage of ICS-PSO-OBL is 18.36%, 7.894%, 15%, and 9.02% higher than that of standard CS, MACS, ICS-2, and ICS when the number of nodes is 20. Moreover, it is 16.94%, 9.61%, 12.27%, and 7.75% higher when the quantity of nodes is 30, the convergence speed of ICS-PSO-OBL, and the distribution of nodes is superior to others.

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Publication Date
Fri Feb 08 2019
Journal Name
Iraqi Journal Of Laser
Photoacoustic Imaging for Tumor Detection: An in vitro Simulation Study
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Photoacoustic is a unique imaging method that combines the absorption contrast of light or radio frequency waves with ultrasound resolution. When the deposition of this energy is sufficiently short, a thermo-elastic expansion takes place whereby acoustic waves are generated. These waves can be recorded and stored to construct an image. This work presents experimental procedure of laser photoacoustic two dimensional imaging to detect tumor embedded within normal tissue. The experimental work is accomplished using phantoms that are sandwiched from fish heart or blood sac (simulating a tumor) 1-14mm mean diameter embedded within chicken breast to simulate a real tissue. Nd: YAG laser of 1.064μm and 532nm wavelengths, 10ns pulse duration, 4

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Publication Date
Fri Mar 31 2017
Journal Name
Al-khwarizmi Engineering Journal
Design an Integral Sliding Mode Controller for a Nonlinear System
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The goal of this paper is to design a robust controller for controlling a pendulum
system. The control of nonlinear systems is a common problem that is facing the researchers in control systems design. The Sliding Mode Controller (SMC) is the best solution for controlling a nonlinear system. The classical SMC consists from two phases. The first phase is the reaching phase and the second is the sliding phase. The SMC suffers from the chattering phenomenon which is considered as a severe problem and undesirable property. It is a zigzag motion along the switching surface. In this paper, the chattering is reduced by using a saturation function instead of sign function. In spite of SMC is a good method for controlling a nonlinear system b

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Publication Date
Tue Jan 01 2008
Journal Name
Lecture Notes In Computer Science
IRPS – An Efficient Test Data Generation Strategy for Pairwise Testing
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Publication Date
Sat Jan 01 2011
Journal Name
International Journal Of Computer Theory And Engineering
MIPOG - An Efficient t-Way Minimization Strategy for Combinatorial Testing
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Publication Date
Thu Aug 01 2024
Journal Name
Smart Agricultural Technology
Smart fertilizer technologies: An environmental impact assessment for sustainable agriculture
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The global food supply heavily depends on utilizing fertilizers to meet production goals. The adverse impacts of traditional fertilization practices on the environment have necessitated the exploration of new alternatives in the form of smart fertilizer technologies (SFTs). This review seeks to categorize SFTs, which are slow and controlled-release Fertilizers (SCRFs), nano fertilizers, and biological fertilizers, and describes their operational principles. It examines the environmental implications of conventional fertilizers and outlines the attributes of SFTs that effectively address these concerns. The findings demonstrate a pronounced environmental advantage of SFTs, including enhanced crop yields, minimized nutrient loss, improved nut

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Publication Date
Sat Jul 09 2022
Journal Name
Wireless Communications And Mobile Computing
An Optimized Approach for Industrial IoT Based on Edge Computing
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The Internet of Things (IoT) is an information network that connects gadgets and sensors to allow new autonomous tasks. The Industrial Internet of Things (IIoT) refers to the integration of IoT with industrial applications. Some vital infrastructures, such as water delivery networks, use IIoT. The scattered topology of IIoT and resource limits of edge computing provide new difficulties to traditional data storage, transport, and security protection with the rapid expansion of the IIoT. In this paper, a recovery mechanism to recover the edge network failure is proposed by considering repair cost and computational demands. The NP-hard problem was divided into interdependent major and minor problems that could be solved in polynomial t

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Publication Date
Fri Feb 01 2019
Journal Name
Indian Journal Of Natural Sciences
Design and Test of Electrochemistry of Electrodes Catalysis for an Alkaline Fuel Cell
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Publication Date
Wed Jan 15 2020
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The responsibility of the administration in compliance with the going concern assumption during the preparation for their financial statements: Research practically at muster of companies
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This research aims to demonstrate the impact of the going concern assumption in different accounting applications to provide a realistic look and more accurate result of activity and financial situation, as well as determining the responsibility of the Company's administration in compliance with the going concern assumption during the preparation for their financial statements, and to clarify the concept of integration between internal audit and external audit about going concern assumption, besides its importance and usefulness on the work of both of the internal auditor and the external auditor, as well as on the company under auditing process.This research purports preparing an internal audit program, including a set of auditing actio

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Publication Date
Tue Dec 01 2020
Journal Name
Journal Of Economics And Administrative Sciences
Analysis of the structure of salaries of public sector workers for strategic planning purposes An analytical study in the general body of groundwater
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The research discusses the problem of salaries in the public sector in terms of the process of analyzing its structure and the possibility of benefiting from the information provided by the analysis process for the strategic planning process, and the General Authority for Groundwater has been adopted and one of the formations of the Ministry of Water Resources, which is centrally funded, to represent the salary structure of its employees (1117) employees be a field of research, as the salary structure in it was analyzed for the period between (2014-2019) using the quantitative approach to analysis and by relying on a number of statistical tools in the analysis process, including mathematical circles, upper limits, lower limits, p

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
An Observation and Analysis the role of Convolutional Neural Network towards Lung Cancer Prediction
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Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c

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