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Improving SVR Horse Herd Optimization Algorithm for Forecasting Daily Gold Prices
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Accurate and correct price prediction of gold is significant to maintain the stability and fair operation of gold markets as well as the efficiency and proper functioning of financial markets related to gold trading. Gold prices have a long history of non-linear and non-stationary behavior that generates highly complex datasets which are very difficult to forecast with high accuracy and reliability. At the same time Support Vector Regression (SVR) has been utilized as a robust information for prediction not only gold prices but also overall metal price movements. First, the predictive capability of SVR is highly sensitive to hyperparameter selection which needs to be thoroughly tuned and optimized for potentially optimal performance. Therefore, the suitable and cautious selection of these hyperparameters can play a significant and direct role in determining the success and precision of SVR. In this study, the focus is on proposing a new technique through horse herd optimization (HHO), which can be used for hyperparameter estimation and tuning of support vector regression (SVR) based on the collective behavior of horse herds to achieve efficient forecasting accuracy and reliability in gold prices. The outcomes and conclusions illustrate that the hybrid algorithm can furnish an increase to the general accuracy of our gold prices, showing superior overall performance as in contrast with two classical benchmark techniques on this area. These enhancements are time to market and useful for enabling faster global economic regeneration and restoration, but also enable the demand side characteristics of integrating international trade commodity price discovery mechanisms into explanations for AI techniques in the context of learning tasks and financial oscular analytics.

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Publication Date
Sat Jun 19 2021
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
The Role of Ginkgo biloba Extract as Monotherapy in Improving the Outcomes of Patients with Metabolic Syndrome: A Pilot Comparative Study with Metformin
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The present study evaluates the effects of Ginkgo biloba extract as monotherapy on the glycemic status, insulin resistance (IR), body mass index (BMI), and visceral adiposity index (VAI), in addition to the inflammatory markers, oxidative status and leptin level in patients with metabolic syndrome in comparison with metformin.

The study is a randomized, double-blind pilot study conducted during the period May to September, 2020. Fifty patients were recruited in the study and they were allocated into two groups (25 per each group): Ginkgo biloba and Metformin groups, they received (120 mg Ginkgo biloba extract/ capsule) and (500 mg Metformin/ capsule) respectively; orally as a single dose for 90 days. Blood samples were taken at z

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Publication Date
Tue Sep 01 2026
Journal Name
Natural Resources For Human Health
The Effect of Rehabilitation Exercises Using Cryotherapy on Pain Reduction and Improving Range of Motion in a Sample of Patients with Frozen Shoulder
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This research aims to develop rehabilitation exercises using cryotherapy for patients with frozen shoulder, Identify the effect of rehabilitation exercises combined with cryotherapy on pain relief and improved range of motion in the experimental group , and identify the effect of standard rehabilitation exercises on pain relief and improved range of motion in the control group, and identify the differences between the experimental and control groups in the post-tests for the variables of pain and range of motion. The researchers used an experimental design with two equivalent groups (experimental and control) using pre- and post-tests, as it was suitable for the nature of the research problem and its objectives, the research populat

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Publication Date
Sat Dec 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of the method of partial least squares and the algorithm of singular values decomposion to estimate the parameters of the logistic regression model in the case of the problem of linear multiplicity by using the simulation
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The logistic regression model is an important statistical model showing the relationship between the binary variable and the explanatory variables.                                                        The large number of explanations that are usually used to illustrate the response led to the emergence of the problem of linear multiplicity between the explanatory variables that make estimating the parameters of the model not accurate.    

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Publication Date
Tue Aug 01 2023
Journal Name
Innovative Food Science & Emerging Technologies
Non-thermal pasteurization of milk by an innovative energy-saving moderate electrical field equipped with elongated electrodes and process optimization
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Publication Date
Mon Jun 16 2025
Journal Name
Progress In Additive Manufacturing
Parametric optimization of layer thickness, speed, and high acceleration on surface roughness, productivity, and quality of 3D printed PLA objects
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Despite the broad approbation of additive manufacturing technologies over diverse industries, printed parts’ performance, quality, and related build time are still greatly influenced by printing parameters. These parameters majorly affect mechanical strength, surface finish, dimensional accuracy, and overall production time of the printed part. Customized 3D printing layer thickness, speed, and acceleration are crucial parameters that affect the speedy printing process and final product quality. The current work considers layer thickness in addition to speed and high acceleration values effect on the surface quality, surface roughness and productivity time of 3D printed Polylactic Acid (PLA). The experimental methodology implemented withi

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Publication Date
Wed Dec 13 2017
Journal Name
Al-khwarizmi Engineering Journal
Optimization of Friction Stir Welding Process Parameters of Dissimilar AA2024-T3 and AA7075-T73 Aluminum Alloys by Using Taguchi Method
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The aim of present study is to determine the optimum parameters of friction stir welding process and known the most important parameter along with percentage contribution of each parameter which effect on tensile strength and joint efficiency of FS welded joint of  dissimilar aluminum alloys AA2024-T3 and AA7075-T73 of 3 mm thick plates by applied specific number of experiments using Taguchi method .AA2024 was placed on the advancing side and AA7075 on the retreating side. FSW was achieved under three different rotation speeds (898, 1200 and 1710) rpm, three different welding speeds (20, 45 and 69) mm\min , three different pin profiles (cylindrical, threaded cylindrical and cone) and tool tilt angle 2◦. Taguchi method w

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Publication Date
Tue Nov 01 2022
Journal Name
Environmental Technology & Innovation
Photo-Fenton-like degradation of direct blue 15 using fixed bed reactor containing bimetallic nanoparticles: Effects and Box–Behnken optimization
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This study involved the treatment of textile wastewater contaminated with direct blue 15 dye (DB15) using a heterogeneous photo-Fenton-like process. Bimetallic iron/copper nanoparticles loaded on bentonite clay were used as heterogeneous catalysts and prepared via liquid-phase reduction method using eucalyptus leaves extract (E-Fe/Cu@BNPs). Characterization methods were applied to resultant particles (NPs), including SEM, BET, and FTIR techniques. The prepared NPs were found with porous and spherical shapes with a specific surface area of particles was 28.589 m2/g. The effect of main parameters on the photo-Fenton-like degradation of DB15 was investigated through batch and continuous fixed-bed systems. In batch mode, pH, H2O2 dosage, DB15 c

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Publication Date
Sun Jan 01 2023
Journal Name
Desalination And Water Treatment
Optimization of chemical oxygen demand removal from petroleum refinery wastewater by electrocoagulation using tubular electrochemical reactor with a novel design
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Publication Date
Tue May 01 2018
Journal Name
Journal Of Engineering
Performance enhancement of Echo Cancellation Using a Combination of Partial Update ( PU) Methods and New Variable Length LMS (NVLLMS) Algorithm
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In this paper, several combination algorithms between Partial Update LMS (PU LMS) methods and previously proposed algorithm (New Variable Length LMS (NVLLMS)) have been developed. Then, the new sets of proposed algorithms were applied to an Acoustic Echo Cancellation system (AEC) in order to decrease the filter coefficients, decrease the convergence time, and enhance its performance in terms of Mean Square Error (MSE) and Echo Return Loss Enhancement (ERLE). These proposed algorithms will use the Echo Return Loss Enhancement (ERLE) to control the operation of filter's coefficient length variation. In addition, the time-varying step size is used.The total number of coefficients required was reduced by about 18% , 10% , 6%

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Publication Date
Tue Oct 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
Determination of the lot size using the Wagner-Whitin algorithm under the Constraint Theory / Case Study of Diyala Public Company
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         International companies are striving to reduce their costs and increase their profits, and these trends have produced many methods and techniques to achieve these goals. these methods is heuristic and the other Optimization.. The research includes an attempt to adapt some of these techniques in the Iraqi companies, and these techniques are to determine the optimal lot size using the algorithms Wagner-Whitin under the theory of constraints. The research adopted the case study methodology to objectively identify the problem of research, namely determining lot size optimal for each of the products of electronic measurement laboratory in Diyala and in light of the bottlenecks in w

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