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Performance of 2- Link Robot by utilizing Adaptive Sliding Mode Controller
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The Sliding Mode Control (SMC) has been among powerful control techniques increasingly. Much attention is paid to both theoretical and practical aspects of disciplines due to their distinctive characteristics such as insensitivity to bounded matched uncertainties, reduction of the order of sliding equations of motion, decoupling mechanical systems design. In the current study, two-link robot performance in the Classical SMC is enhanced via Adaptive Sliding Mode Controller (ASMC) despite uncertainty, external disturbance, and coulomb friction. The key idea is abstracted as follows: switching gains are depressed to the low allowable values, resulting in decreased chattering motion and control's efforts of the two-link robot system. Un-known uncertainty bounded and reducing switching gains can be considered major advantages of ASMC leading to outperform ASMC upon CSMC. Simulink MATLAB 2019a was used to obtain the simulation outcomes. The outcomes have shown that both methodologies had good tracking performance to the desired position and made the system asymptotically stable through the steady-state errors investigate approaching zero. ASMC is better than CSMC illustrated by minimizing gains values, control efforts, and chattering for each link.

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Publication Date
Sun Dec 15 2019
Journal Name
Journal Of Baghdad College Of Dentistry
The Effects of Nano Alumina On Mechanical Properties of Room Temperature Vulcanized Maxillofacial Silicone (Pilot Study)
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Background: Facial disfigurement can be the result of a congenital anomaly, trauma or tumor surgery, in many cases the prosthetic rehabilitation is indicated. Maxillofacial prosthetic materials should have desirable and ideal physical, aesthetic, and biological properties and those properties should be kept for long period of time in order to reach patient acceptance. Silicone elastomer are the most commonly used material for facial restoration because of its favorable properties mechanically and physically as the biocompatibility and good elasticity. Aim of this study: This study aimed to evaluate the effect of addition of Aluminum oxide (Al2O3) Nano fillers in different concentrations on tear strength and hardness of VST 50F room tempe

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Publication Date
Thu Mar 31 2022
Journal Name
Iraqi Geological Journal
Development of Artificial Intelligence Models for Estimating Rate of Penetration in East Baghdad Field, Middle Iraq
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It is well known that the rate of penetration is a key function for drilling engineers since it is directly related to the final well cost, thus reducing the non-productive time is a target of interest for all oil companies by optimizing the drilling processes or drilling parameters. These drilling parameters include mechanical (RPM, WOB, flow rate, SPP, torque and hook load) and travel transit time. The big challenge prediction is the complex interconnection between the drilling parameters so artificial intelligence techniques have been conducted in this study to predict ROP using operational drilling parameters and formation characteristics. In the current study, three AI techniques have been used which are neural network, fuzzy i

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Publication Date
Thu Jun 30 2022
Journal Name
Iraqi Geological Journal
Integrating Petrophysical and Geomechanical Rock Properties for Determination of Fracability of the Iraqi Tight Oil Reservoir
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Tight oil reservoirs have been a concerned of the oil industry due to their substantial influence on oil production. Due to their poor permeability, numerous problems are encountered while producing from tight reservoirs. Petrophysical and geomechanical rock properties are essential for understanding and assessing the fracability of reservoirs, especially tight reservoirs, to enhance permeability. In this study, Saadi B reservoir in Halfaya Iraqi oil field is considered as the main tight reservoir. Petrophysical and geomechanical properties have been estimated using full-set well logs for a vertical well that penetrates Saadi reservoir and validated with support of diagnostic fracture injection test data employing standard equations

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Publication Date
Fri Dec 15 2023
Journal Name
Journal Of Baghdad College Of Dentistry
Effect of tea tree oil on candida adherence and surface roughness of heat cure acrylic resin
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Background: Denture cleansing was an important step that could prevent the spread of infection and improve a patient's health, the durability of the dentures, and the overall quality of life; therefore, it was necessary to choose a suitable cleanser that, in addition to being effective, did not have an unfavorable effect on the qualities of the denture base resin itself when used for an extended period. For this purpose, this study aimed to evaluate the effect of tea tree oil (TTO) on Candida albicans adhesion and the surface roughness property of poly(methyl methacrylate) denture material after immersion in TTO. Methods: A total of 55 heat-cured acrylic resin specimens were used for C. albicans adherence and surface roughness tests. The

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Publication Date
Fri Mar 15 2019
Journal Name
Al-khwarizmi Engineering Journal
Experimental and Theoretical Study of the Energy Flow of a Two Stages Four Generators Adsorption Chiller
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This work is concerned with a two stages four beds adsorption chiller utilizing activated carbon-methanol adsorption pair that operates on six separated processes. The four beds that act as thermal compressors are powered by a low grade thermal energy in the form of hot water at a temperature range of 65 to 83 °C.  As well as, the water pumps and control cycle consume insignificant electrical power. This adsorption chiller consists of three water cycles. The first water cycle is the driven hot water cycle. The second cycle is the cold water cycle to cool the carbon, which adsorbs the methanol. Finally, the chilled water cycle that is used to overcome the building load. The theoretical results showed that average cycle cooling power

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Publication Date
Fri Jul 19 2024
Journal Name
Baghdad Science Journal
An Analytical Comparison of the Behavior of Machine Learning and Deep Learning in Stock Market Prediction
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Machine learning is considered a powerful technique in many applications such as classification, clustering, recognition and prediction. Deep learning is a modern, vital and superior machine learning that gives stunning performance, especially with huge data. Stock market price prediction is the process of determining the future value of a prospect of a financial instrument traded in the market, to gain a great profit a successful prediction must be conducted, in order to achieve that machine learning is used, in this article, two approaches are proposed to predict the stock market prices and movement using two datasets, the first approach employs two machine learning models (J48 & logistic regression) while the second approach based on rec

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Publication Date
Sun Jan 31 2021
Journal Name
International Journal Of Advanced Research
STUDY THE EFFECT OF COATING USING NANOPARTICLES ON THE CORROSION OF ALUMINUM ALLOY IN DIFFERENT SOLUTIONS
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Corrosion resistance of metals is one of the most important topics for researchers. In this work, epoxy-TiO2 nanocomposite has been developed for protection of 6061AL alloy. The dip-coating technique used to deposit the coating on 6061 Al alloy substrate. Different concentrations of TiO2 NPs (1,3,5 )Wt% have been used to study the corrosion behavior in 3.5% NaCl medium. Also, 200,150 and 100 mm/min dipping speeds have been employed for 1%wt TiO2 to show their effects on coating layer and corrosion rate. Characterization of coated surfaces were investigated by AFM, FESEM andEDS,while theelectrochemical measurementswas using to evaluate protective nature of the coating. The results have shown that the corrosion rate has decreased with

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Publication Date
Wed Jan 03 2024
Journal Name
Revista Brasileira De Engenharia Agrícola E Ambiental
Effect of cold plasma technique on the quality of stored fruits - A case study on apples
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The consumption of fresh fruits has increased nowadays due to the lifestyle of the consumers. Maintaining the quality and nutritional value of cut fruits during storage is difficult compared to whole fruits. Deterioration of internal and external quality usually occurs in freshly harvested fruits. It is necessary to use different techniques to maintain the quality and increase the shelf life of the freshly cut product. This research studied the effect of treating apple slices with cold plasma once and with filtered water again on quality characteristics (hardness, moisture content, sugar content, carbohydrate content, and color) after being stored for five days. The best treatment was determined using two different pressures of the plasma j

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Publication Date
Sat Dec 28 2019
Journal Name
International Journal Of Environmental Research And Public Health
Predominant Mechanisms in the Treatment of Wastewater Due to Interaction of Benzaldehyde and Iron Slag Byproduct
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Iron slag is a byproduct generated in huge quantities from recycled remnants of iron and steel factories; therefore, the possibility of using this waste in the removal of benzaldehyde from contaminated water offers an excellent topic in sustainability field. Results reveal that the removal efficiency was equal to 85% for the interaction of slag and water contaminated with benzaldehyde at the best operational conditions of 0.3 g/100 mL, 6, 180 min, and 250 rpm for the sorbent dosage, initial pH, agitation time, and speed, respectively with 300 mg/L initial concentration. The maximum uptake capacity of iron slag was 118.25 mg/g which was calculated by the Langmuir model. Physical sorption may be the major mechanism for the removal of

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Publication Date
Mon Jun 04 2018
Journal Name
Baghdad Science Journal
Structural Analysis of Chemical and Green Synthesis of CuO Nanoparticles and their Effect on Biofilm Formation
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Copper oxide nanoparticles (CuO NPs) were synthesized by two methods. The first was chemical method by using copper nitrate Cu (NO3)2 and NaOH, while the second was green method by using Eucalyptus camaldulensis leaves extract and Cu (NO3)2. These methods easily give a large scale production of CuO nanoparticles. X-ray diffraction pattern (XRD) reveals single phase monoclinic structure. The average crystalline size of CuO NPs was measured and used by Scherrer equation which found 44.06nm from chemical method, while the average crystalline size was found from green method was 27.2nm. The morphology analysis using atomic force microscopy showed that the grain size for CuO NPs was synthesized by chemical and green methods were 77.70 and 89.24

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