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Security In Wireless Sensor Networks Based On Lightweight Algorithms : An Effective Survey
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At the level of both individuals and companies, Wireless Sensor Networks (WSNs) get a wide range of applications and uses. Sensors are used in a wide range of industries, including agriculture, transportation, health, and many more. Many technologies, such as wireless communication protocols, the Internet of Things, cloud computing, mobile computing, and other emerging technologies, are connected to the usage of sensors. In many circumstances, this contact necessitates the transmission of crucial data, necessitating the need to protect that data from potential threats. However, as the WSN components often have constrained computation and power capabilities, protecting the communication in WSNs comes at a significant performance penalty. Due to the massive calculations required by conventional public-key and secret encryption methods, information security in this limited context calls for light encryption techniques. In many applications involving sensor networks, security is a crucial concern. On the basis of traditional cryptography, a number of security procedures are created for wireless sensor networks. Some symmetric-key encryption techniques used in sensor network setups include AES, RC5, SkipJack, and XXTEA. These algorithms do, however, have several flaws of their own, including being susceptible to chosen-plaintext assault, brute force attack, and computational complexity.

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Publication Date
Sun Aug 25 2019
Journal Name
Civil Engineering Journal
Optimum Efficiency of PV Panel Using Genetic Algorithms to Touch Proximate Zero Energy House (NZEH)
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By optimizing the efficiency of a modular simulation model of the PV module structure by genetic algorithm, under several weather conditions, as a portion of recognizing the ideal plan of a Near Zero Energy Household (NZEH), an ideal life cycle cost can be performed. The optimum design from combinations of NZEH-variable designs, are construction positioning, window-to-wall proportion, and glazing categories, which will help maximize the energy created by photovoltaic panels. Comprehensive simulation technique and modeling are utilized in the solar module I-V and for P-V output power. Both of them are constructed on the famous five-parameter model.  In addition, the efficiency of the PV panel is established by the genetic algorithm

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Publication Date
Sat Oct 30 2021
Journal Name
Iraqi Journal Of Science
The Effects of Conductance on Metastable Switches in Memristive Devices Based on Anti-Hebbian and Hebbian (AHaH) Learning Rules
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     In the last few years, the literature conferred a great interest in studying the feasibility of using memristive devices for computing. Memristive devices are important in structure, dynamics, as well as functionalities of artificial neural networks (ANNs) because of their resemblance to biological learning in synapses and neurons regarding switching characteristics of their resistance. Memristive architecture consists of a number of metastable switches (MSSs). Although the literature covered a variety of memristive applications for general purpose computations, the effect of low or high conductance of each MSS was unclear. This paper focuses on finding a potential criterion to calculate the conductance of each MMS rather t

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Publication Date
Sun Jan 01 2023
Journal Name
International Journal Of Nonlinear Analysis And Applications
Rock facies classification and its effect on the estimation of original oil in place based on petrophysical properties data
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The most significant function in oil exploration is determining the reservoir facies, which are based mostly on the primary features of rocks. Porosity, water saturation, and shale volume as well as sonic log and Bulk density are the types of input data utilized in Interactive Petrophysics software to compute rock facies. These data are used to create 15 clusters and four groups of rock facies. Furthermore, the accurate matching between core and well-log data is established by the neural network technique. In the current study, to evaluate the applicability of the cluster analysis approach, the result of rock facies from 29 wells derived from cluster analysis were utilized to redistribute the petrophysical properties for six units of Mishri

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
Recognizing Different Foot Deformities Using FSR Sensors by Static Classification of Neural Networks
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Sensing insole systems are a promising technology for various applications in healthcare and sports. They can provide valuable information about the foot pressure distribution and gait patterns of different individuals. However, designing and implementing such systems poses several challenges, such as sensor selection, calibration, data processing, and interpretation. This paper proposes a sensing insole system that uses force-sensitive resistors (FSRs) to measure the pressure exerted by the foot on different regions of the insole. This system classifies four types of foot deformities: normal, flat, over-pronation, and excessive supination. The classification stage uses the differential values of pressure points as input for a feedforwar

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Publication Date
Mon Oct 01 2018
Journal Name
Al–bahith Al–a'alami
The credibility of satellite news channels directed in Arabic from the perspective of Iraqi media, Survey Study
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This research aims at identifying the commitment of satellite news channels in Arabic to the set of important standards that reflect their credibility in dealing with the media material, and considering that these channels give special importance to events in Iraq, as well as the Arab region and the world, decide to choose them and study them with a problem The research was a question about the level of credibility of Iraqi media. This research is descriptive research, which used the survey method on an objective sample of 245 items, while the questionnaire was used as a data collection tool. Seven channels were selected in Arabic for the study. The three most watched channels were chosen. These channels included the channels of Russia t

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Publication Date
Tue Oct 23 2018
Journal Name
Journal Of Economics And Administrative Sciences
Processing of missing values in survey data using Principal Component Analysis and probabilistic Principal Component Analysis methods
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The idea of ​​carrying out research on incomplete data came from the circumstances of our dear country and the horrors of war, which resulted in the missing of many important data and in all aspects of economic, natural, health, scientific life, etc.,. The reasons for the missing are different, including what is outside the will of the concerned or be the will of the concerned, which is planned for that because of the cost or risk or because of the lack of possibilities for inspection. The missing data in this study were processed using Principal Component  Analysis and self-organizing map methods using simulation. The variables of child health and variables affecting children's health were taken into account: breastfeed

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Publication Date
Thu Aug 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
Development of methods of treatment of medical waste in the hospitals of Baghdad health Department / (Rusafa survey)
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Purpose: To contribute to the development of an appropriate program for the management of medical waste based on clear-cut principles in order to reach the overall goal of improving the public health and environment of the population in our country.

Design / Approach / Introduction: The research is based on the analytical descriptive approach as a method of study in the field of data collection using a check list and analysis of the data through the use of some statistical treatments.

 Results: The need is to establish a medical waste management in hospitals and follow international standards in all stages of waste management from sorting, collection, transportation and treat

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Publication Date
Sun Oct 29 2023
Journal Name
Iraqi National Journal Of Nursing Specialties
A Survey of Diabetes Mellitus in a Sample of Children below 15 Years Attending Child Welfare Hospital
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Objectives: Determine the age and gender distribution of children who experience diabetes mellitus (DM) under
the age of 15 years and the presence of some associated factors that might be a predisposing factor for the
disease including obesity.
Methodology: A cross-sectional study was conducted at diabetic clinic in Children Welfare Teaching Hospital
in Baghdad City during 2006. The study sample included diabetic children less than 15 years of age. Data were
taken from the patients' record and by direct interview with the patients' parents. Information included
demographic data, as well as past history of the patient and his/her family relative to diabetes and other immune
diseases.
Results: Data analysis showed t

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Publication Date
Tue Jun 20 2023
Journal Name
Bulletin Of The Iraq Natural History Museum
SURVEY WITH REVISED CHECKLIST OF COMPOSITAE IN THE HERBARIUM OF IRAQ NATURAL HISTORY RESEARCH CENTER AND MUSEUM
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A survey and revised checklist of the species belonging to the family of Compositae for the specimens which are collected and deposited previously at the herbarium of the Iraq Natural History Research Center and Museum, in addition to the current specimens collected for the period 2016-2021. A total of 85 species belonging to 49 genera and 16 tribes are revised with their synonyms, locality, and distributions, flowering and fruiting period.

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Publication Date
Sat Oct 01 2011
Journal Name
Journal Of Engineering
MODIFIED TRAINING METHOD FOR FEEDFORWARD NEURAL NETWORKS AND ITS APPLICATION in 4-LINK SCARA ROBOT IDENTIFICATION
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In this research the results of applying Artificial Neural Networks with modified activation function to
perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance
Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of
identification strategy consists of a feed-forward neural network with a modified activation function that
operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have
been trained online and offline have been used, without requiring any previous knowledge about the
system to be identified. The activation function that is used in the hidden layer in FFNN is a modified
version of the wavelet func

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