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bsj-1431
A Comparison of the Methods for Estimation of Reliability Function for Burr-XII Distribution by Using Simulation.
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This deals with estimation of Reliability function and one shape parameter (?) of two- parameters Burr – XII , when ?(shape parameter is known) (?=0.5,1,1.5) and also the initial values of (?=1), while different sample shze n= 10, 20, 30, 50) bare used. The results depend on empirical study through simulation experiments are applied to compare the four methods of estimation, as well as computing the reliability function . The results of Mean square error indicates that Jacknif estimator is better than other three estimators , for all sample size and parameter values

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Publication Date
Tue Jun 01 2021
Journal Name
Journal Of Engineering
Designing a Secure Software-Defined Radio Transceiver using the Logistic Map
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The need to exchange large amounts of real-time data is constantly increasing in wireless communication. While traditional radio transceivers are not cost-effective and their components should be integrated, software-defined radio (SDR) ones have opened up a new class of wireless technologies with high security.  This study aims to design an  SDR  transceiver was built using one type of modulation, which is 16 QAM, and adding a  security subsystem using one type of chaos map, which is a  logistic map, because it is a very simple nonlinear dynamical equations that generate a random key and  EXCLUSIVE  OR with the originally transmitted data to protect data through the transmission. At th

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Publication Date
Tue Jan 01 2019
Journal Name
Advances On Computational Intelligence In Energy
A Theoretical Framework for Big Data Analytics Based on Computational Intelligent Algorithms with the Potential to Reduce Energy Consumption
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Within the framework of big data, energy issues are highly significant. Despite the significance of energy, theoretical studies focusing primarily on the issue of energy within big data analytics in relation to computational intelligent algorithms are scarce. The purpose of this study is to explore the theoretical aspects of energy issues in big data analytics in relation to computational intelligent algorithms since this is critical in exploring the emperica aspects of big data. In this chapter, we present a theoretical study of energy issues related to applications of computational intelligent algorithms in big data analytics. This work highlights that big data analytics using computational intelligent algorithms generates a very high amo

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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
Deep Learning Techniques in the Cancer-Related Medical Domain: A Transfer Deep Learning Ensemble Model for Lung Cancer Prediction
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Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

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Publication Date
Mon May 17 2021
Journal Name
Indian Journal Of Forensic Medicine & Toxicology
The Effect of Exercises with a Proposed Device to Improving Some Bio-Kinematic Variables and the Performance of the Arab Round off Skill on Floor Movement Mat Device of the Artistic Gymnastics for Women
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The importance of the research lies in preparing exercises using a proposed device to learn the skill of thehuman wheel on a machine rug of ground movements of the artistic gymnastics. As for the research problem:Through the presence of the two researchers as teachers and observers of this sport in the gymnastics hall,they noticed that there is difficulty in the students’ performance of the skill of the round off on the machineof the mat of ground movements, according to the researchers’ opinion, the reason for this is that skillsare taught with the limited availability of assistive devices, as well as the lack of use of these devices inexercises according to biomechanical variables, although they facilitate the learning process

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Publication Date
Tue Apr 30 2024
Journal Name
Iraqi Journal Of Science
Topology-Based Modularity and Modularity Density for Detecting Protein Complexes: A Comparative Study
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     Binary relations or interactions among bio-entities, such as proteins, set up the essential part of any living biological system. Protein-protein interactions are usually structured in a graph data structure called "protein-protein interaction networks" (PPINs). Analysis of PPINs into complexes tries to lay out the significant knowledge needed to answer many unresolved questions, including how cells are organized and how proteins work. However, complex detection problems fall under the category of non-deterministic polynomial-time hard (NP-Hard) problems due to their computational complexity. To accommodate such combinatorial explosions, evolutionary algorithms (EAs) are proven effective alternatives to heuristics in solvin

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Publication Date
Tue Dec 01 2020
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
A Haptic feedback system based on leap motion controller for prosthetic hand application
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Leap Motion Controller (LMC) is a gesture sensor consists of three infrared light emitters and two infrared stereo cameras as tracking sensors. LMC translates hand movements into graphical data that are used in a variety of applications such as virtual/augmented reality and object movements control. In this work, we intend to control the movements of a prosthetic hand via (LMC) in which fingers are flexed or extended in response to hand movements. This will be carried out by passing in the data from the Leap Motion to a processing unit that processes the raw data by an open-source package (Processing i3) in order to control five servo motors using a micro-controller board. In addition, haptic setup is proposed using force sensors (F

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Publication Date
Tue Oct 01 2019
Journal Name
Biochemical & Cellular Archives
A RE-SATURATION IMPACT ON SOIL RETENTION CURVE FOR FIVE DIFFERENT TEXTURED SOILS
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Soil water retention curves (SWRCs) are crucial for characterizing soil moisture dynamics and are particularly relevant in the context of irrigation management. A study was carried out to obtain the SWRC, inflection point, S index, pore size distribution curve, macro porosity, and air capacity from samples submitted to saturation and re-saturation processes. Five different-texture disturbed soil samples Sandy Loam, Loam, Sandy Clay Loam, Silt Loam, and Clay were collected. After obtaining SWRC, each air-dried soil samples were submitted to particle size distribution and clay dispersed in water analyses to verify the soil lost clay. The experimental design was completely randomized with three replications using two processes of SWRC (saturat

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Publication Date
Tue Jan 01 2019
Journal Name
Energy Procedia
Quadrupole Moment & Deformation Parameter for Even-Even 38Sr (A=76-102) Nuclide
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Publication Date
Thu Jun 01 2023
Journal Name
Bulletin Of Electrical Engineering And Informatics
A missing data imputation method based on salp swarm algorithm for diabetes disease
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Most of the medical datasets suffer from missing data, due to the expense of some tests or human faults while recording these tests. This issue affects the performance of the machine learning models because the values of some features will be missing. Therefore, there is a need for a specific type of methods for imputing these missing data. In this research, the salp swarm algorithm (SSA) is used for generating and imputing the missing values in the pain in my ass (also known Pima) Indian diabetes disease (PIDD) dataset, the proposed algorithm is called (ISSA). The obtained results showed that the classification performance of three different classifiers which are support vector machine (SVM), K-nearest neighbour (KNN), and Naïve B

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Publication Date
Sun Oct 01 2017
Journal Name
Iecon 2017 - 43rd Annual Conference Of The Ieee Industrial Electronics Society
Optimal second order integral sliding mode control for a flexible joint robot manipulator
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The flexible joint robot manipulators provide various benefits, but also present many control challenges such as nonlinearities, strong coupling, vibration, etc. This paper proposes optimal second order integral sliding mode control (OSOISMC) for a single link flexible joint manipulator to achieve robust and smooth performance. Firstly, the integral sliding mode control is designed, which consists of a linear quadratic regulator (LQR) as a nominal control, and switching control. This control guarantees the system robustness for the entire process. Then, a nonsingularterminal sliding surface is added to give a second order integral sliding mode control (SOISMC), which reduces chartering effect and gives the finite time convergence as well. S

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