This paper focuses on the optimization of drilling parameters by utilizing “Taguchi method” to obtain the minimum surface roughness. Nine drilling experiments were performed on Al 5050 alloy using high speed steel twist drills. Three drilling parameters (feed rates, cutting speeds, and cutting tools) were used as control factors, and L9 (33) “orthogonal array” was specified for the experimental trials. Signal to Noise (S/N) Ratio and “Analysis of Variance” (ANOVA) were utilized to set the optimum control factors which minimized the surface roughness. The results were tested with the aid of statistical software package MINITAB-17. After the experimental trails, the tool diameter was found as the most important factor that has effect on the surface roughness. The optimal drilling factors that minimized the surface roughness are (20mm/min cutting speed, 0.2 mm/rev feed rate, and 10mm tool diameter).
Building numerical reservoir simulation model with a view to model actual case requires enormous amount of data and information. Such modeling and simulation processes normally require lengthy time and different sets of field data and experimental tests that are usually very expensive. In addition, the availability, quality and accessibility of all necessary data are very limited, especially for the green field. The degree of complexities of such modelling increases significantly especially in the case of heterogeneous nature typically inherited in unconventional reservoirs. In this perspective, this study focuses on exploring the possibility of simplifying the numerical simulation pr
In recent decades, the identification of faces with and without masks from visual data, such as video and still images, has become a captivating research subject. This is primarily due to the global spread of the Corona pandemic, which has altered the appearance of the world and necessitated the use of masks as a vital measure for epidemic prevention. Intellectual development based on artificial intelligence and computers plays a decisive role in the issue of epidemic safety, as the topic of facial recognition and identifying individuals who wear masks or not was most prominent in the introduction and in-depth education. This research proposes the creation of an advanced system capable of accurately identifying faces, both with and
... Show MoreThe aim of human lower limb rehabilitation robot is to regain the ability of motion and to strengthen the weak muscles. This paper proposes the design of a force-position control for a four Degree Of Freedom (4-DOF) lower limb wearable rehabilitation robot. This robot consists of a hip, knee and ankle joints to enable the patient for motion and turn in both directions. The joints are actuated by Pneumatic Muscles Actuators (PMAs). The PMAs have very great potential in medical applications because the similarity to biological muscles. Force-Position control incorporating a Takagi-Sugeno-Kang- three- Proportional-Derivative like Fuzzy Logic (TSK-3-PD) Controllers for position control and three-Proportional (3-P) controllers for force contr
... Show MoreWellbore stability is considered as one of the most challenges during drilling wells due to the
reactivity of shale with drilling fluids. During drilling wells in North Rumaila, Tanuma shale is
represented as one of the most abnormal formations. Sloughing, caving, and cementing problems
as a result of the drilling fluid interaction with the formation are considered as the most important
problem during drilling wells. In this study, an attempt to solve this problem was done, by
improving the shale stability by adding additives to the drilling fluid. Water-based mud (WBM)
and polymer mud were used with different additives. Three concentrations 0.5, 1, 5 and 10 wt. %
for five types of additives (CaCl2, NaCl, Na2S
Wellbore instability is a significant problem faced during drilling operations and causes loss of circulation, caving, stuck pipe, and well kick or blowout. These problems take extra time to treat and increase the Nonproductive Time (NPT). This paper aims to review the factors that influence the stability of wellbores and know the methods that have been reached to reduce them. Based on a current survey, the factors that affect the stability of the wellbore are far-field stress, rock mechanical properties, natural fractures, pore pressure, wellbore trajectory, drilling fluid chemicals, mobile formations, naturally over-pressured shale collapse, mud weight, temperature, and time. Also, the most suitable ways to reduce well
... Show MoreThe internet of medical things (IoMT), which is expected the lead to the biggest technology in worldwide distribution. Using 5th generation (5G) transmission, market possibilities and hazards related to IoMT are improved and detected. This framework describes a strategy for proactively addressing worries and offering a forum to promote development, alter attitudes and maintain people's confidence in the broader healthcare system without compromising security. It is combined with a data offloading system to speed up the transmission of medical data and improved the quality of service (QoS). As a result of this development, we suggested the enriched energy efficient fuzzy (EEEF) data offloading technique to enhance the delivery of dat
... Show MoreThe internet of medical things (IoMT), which is expected the lead to the biggest technology in worldwide distribution. Using 5th generation (5G) transmission, market possibilities and hazards related to IoMT are improved and detected. This framework describes a strategy for proactively addressing worries and offering a forum to promote development, alter attitudes and maintain people's confidence in the broader healthcare system without compromising security. It is combined with a data offloading system to speed up the transmission of medical data and improved the quality of service (QoS). As a result of this development, we suggested the enriched energy efficient fuzzy (EEEF) data offloading technique to enhance the delivery of dat
... Show MoreThe primary objective of this paper is to improve a biometric authentication and classification model using the ear as a distinct part of the face since it is unchanged with time and unaffected by facial expressions. The proposed model is a new scenario for enhancing ear recognition accuracy via modifying the AdaBoost algorithm to optimize adaptive learning. To overcome the limitation of image illumination, occlusion, and problems of image registration, the Scale-invariant feature transform technique was used to extract features. Various consecutive phases were used to improve classification accuracy. These phases are image acquisition, preprocessing, filtering, smoothing, and feature extraction. To assess the proposed
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