This research deals with unusual approach for analyzing the Simple Linear Regression via Linear Programming by Two - phase method, which is known in Operations Research: “O.R.”. The estimation here is found by solving optimization problem when adding artificial variables: Ri. Another method to analyze the Simple Linear Regression is introduced in this research, where the conditional Median of (y) was taken under consideration by minimizing the Sum of Absolute Residuals instead of finding the conditional Mean of (y) which depends on minimizing the Sum of Squared Residuals, that is called: “Median Regression”. Also, an Iterative Reweighted Least Squared based on the Absolute Residuals as weights is performed here as another method to estimate the regression coefficients.
The current study aims at using non-hatchable artemia eggs of local origin and making use of these eggs by decapsulating and presenting them as food for the larvae of the Cyprinus carpio as a source of animal protein with high nutritional value instead of throwing them away. The results showed that the second parameter (A2) was highly significant at the level (P≤0.05) in the growth rates of the larvae that were fed on decapsulated artemia eggs alone, and it was better than the two control parameters (A1), in which the larvae were fed with feed designated for Cyprinus carpio fish. It also outperformed the third parameter (A3), in which the feed was mixed with artemia eggs with 50% decapsulation, which also outperformed the control paramete
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Community detection is an important and interesting topic for better understanding and analyzing complex network structures. Detecting hidden partitions in complex networks is proven to be an NP-hard problem that may not be accurately resolved using traditional methods. So it is solved using evolutionary computation methods and modeled in the literature as an optimization problem. In recent years, many researchers have directed their research efforts toward addressing the problem of community structure detection by developing different algorithms and making use of single-objective optimization methods. In this study, we have continued that research line by improving the Particle Swarm Optimization (PSO) algorithm using a
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This study proposed control system that has been presented to control the electron lens resistance in order to obtain a stabilized electron lens power. This study will layout the fundamental challenges, hypothetical plan arrangements and development condition for the Integrable Optics Test Accelerator (IOTA) in progress at Fermilab. Thus, an effective automatic gain control (AGC) unit has been introduced which prevents fluctuations in the internal resistance of the electronic lens caused by environmental influences to affect the system's current and power values and keep them in stable amounts. Utilizing this unit has obtained level balanced out system un impacted with electronic lens surrounding natural varieties.
A two time step stochastic multi-variables multi-sites hydrological data forecasting model was developed and verified using a case study. The philosophy of this model is to use the cross-variables correlations, cross-sites correlations and the two steps time lag correlations simultaneously, for estimating the parameters of the model which then are modified using the mutation process of the genetic algorithm optimization model. The objective function that to be minimized is the Akiake test value. The case study is of four variables and three sites. The variables are the monthly air temperature, humidity, precipitation, and evaporation; the sites are Sulaimania, Chwarta, and Penjwin, which are located north Iraq. The model performance was
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This paper describes a newly modified wind turbine ventilator that can achieve highly efficient ventilation. The new modification on the conventional wind turbine ventilator system may be achieved by adding a Savonius wind turbine above the conventional turbine to make it work more efficiently and help spinning faster. Three models of the Savonius wind turbine with 2, 3, and 4 blades' semicircular arcs are proposed to be placed above the conventional turbine of wind ventilator to build a hybrid ventilation turbine. A prototype of room model has been constructed and the hybrid turbine is placed on the head of the room roof. Performance's tests for the hybrid turbine with a different number of blades and different values o
... Show MoreProsthetic is an artificial tool that replaces a member of the human frame that is absent because of ailment, damage, or distortion. The current research activities in Iraq draw interest to the upper limb discipline because of the growth in the number of amputees. Thus, it becomes necessary to increase researches in this subject to help in reducing the struggling patients. This paper describes the design and development of a prosthesis for people able and wear them from persons who have amputation in the hands. This design is composed of a hand with five fingers moving by means of a gearbox ism mechanism. The design of this artificial hand has 5 degrees of freedom. This artificial hand works based on the principle of &n
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Laser assisted skin wound closure offers many distinct advantages over conventional closure
techniques. The objective of this in vitro experimental study, carried out at the Institute of Laser for
Postgraduate Studies/Baghdad University, was to determine the effectiveness of 980 nm diode laser in
welding of human skin wounds. Multiple 3-4 cm long full thickness incisions in a specimen of human
skin obtained from the discarded panniculus of an Abdominoplasty operation were tried to be laser
welded using a 4 mm spot diameter laser beam from a 980 nm diode laser at different laser parameters
and modes of action. The tensile strength at the weld site was analyzed experimentally. Although laser
assisted wound welding did
The complexity and variety of language included in policy and academic documents make the automatic classification of research papers based on the United Nations Sustainable Development Goals (SDGs) somewhat difficult. Using both pre-trained and contextual word embeddings to increase semantic understanding, this study presents a complete deep learning pipeline combining Bidirectional Long Short-Term Memory (BiLSTM) and Convolutional Neural Network (CNN) architectures which aims primarily to improve the comprehensibility and accuracy of SDG text classification, thereby enabling more effective policy monitoring and research evaluation. Successful document representation via Global Vector (GloVe), Bidirectional Encoder Representations from Tra
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