Sukkur IBA Journal of Emerging Technologies

Terahertz Waveguides: A Bibliometric Analysis of the Past 20 Years

Wed, 01 Jan 2025 00:00:00 +0100

Advancement in technology has opened the doors for the terahertz (THz) frequency range to be applied in different fields for a variety of applications and efficient propagation of THz waves is an important parameter to consider. This paper is a bibliometric analysis of the past twenty years’ research progress toward the terahertz waveguides and their propagation. The analysis is
supported by the VOSviewer software. The analysis includes the distribution of the journal publications, contributions by the different authors in the THz waveguide field, affiliations, highly impacted journals, top keywords, and countries working in this area. The analysis discussed in this paper is based on the published reports of the last 20 years extracted from the Scopus database. The main aim of this analysis is to identify the research map, identify the research gap, and the potential of the THz waveguides in future applications. These evaluations would provide a general overview of the development and advancement of the THz waveguide and provide appropriate direction for continuing research in this field

Blue Light Therapy: A Skin Treatment Mask using Blue Light to cure Skin Disorders

Tue, 31 Dec 2024 00:00:00 +0100

Skin acne and disease are the most common medical conditions that lead from mild to moderate if not treated in time. There are several treatments such as Chemical peel, Dermabrasion, and many others these hyped techniques have proven to be extremely beneficial for improving and smoothening the skin texture, through treatments with chemicals and devices. Unfortunately, such techniques have various side effects such as redness, scabbing, irritation, and swelling, which do not provide a better medical treatment. These treatments require continuous medical examination and an expert opinion. Light therapy can be used non-invasively to overcome such side effects and treat a large number of skin damages. Blue light exhibits tons of advantages to human skin by reducing sebaceous glands' activeness so that they produce low amounts of oil that ultimately hook into the pores of the skin and result in skin breakouts and acne popping. Blue light can cure severe skin conditions such as sun damage, fine lines, wrinkles, acne scars, blemishes, and much more. Blue light therapies are generally used to treat the conditions, that are present superficial and under the skin surface. In this research, the face mask has been designed and incorporated with the Blue light strips to provide the blue light on the facial skin. The microcontroller has been programmed to control the intensity and time during the therapy session. This skin treatment mask has proven to be a pain-free and effective procedure to make the skin look healthy and beautiful. Statistical analysis of the results revealed promising outcomes: 60-70% success rates were observed in participants with mild to moderate skin conditions, while even in severe cases, significant improvements were noted with success rates ranging from 25-50%. The results have been incredible and satisfactory in improving the skin conditions of the user.

Novel Continuous Terminal Sliding Mode Observer Based Sensorless Speed Control of PMSM Drive System

Wed, 01 Jan 2025 00:00:00 +0100

The permanent magnet synchronous motor (PMSM) control is demanding task because, which is a nonlinear multivariable coupling system. The vector control has been widely used in the control of PMSM system, where the rotor position information is needed for close loop control system. The mechanical sensors are used for rotor position, which increased the cost of the system. These sensors can be eliminated by adopting the sensorless control methods. In this paper a new continuous terminal sliding mode observer (CTSMO) based speed sensorless control method is proposed, which is substitute of the conventional SMO (CSMO). The suggested the CTSMO is robust against parametric change and load disturbances, which is used to estimate the speed and rotor position from the back EMF (BEMF) of the PMSM system. The conventional SMO needs the low pass filter (LPF), position compensation techniques and sigmoid function instead of sign function to decrease the chattering phenomena. To eliminate the chattering phenomena effectively the new CTSMO based speed sensorless method is designed in this paper, which has also ability of minimization of the speed and rotor position error. The stability of the proposed technique is analyzed by Lyapunov function, the simulation have been carried out for the validation of the suggested technique.

Dual closed-loop vector PI control and deadbeat current control of permanent magnet synchronous motor

Syed Abid Ali Shah Bukhari, Vikram Kumar, Muhammad Ahsan , Qazi Sajid — Thu, 02 Jan 2025 00:00:00 +0100

Permanent magnet synchronous motors (PMSMs) offer advantages such as high torque, power density, and energy efficiency, making them essential in power electronics, aerospace, and daily life. Designing PMSM control systems is complex yet crucial for optimizing performance. Field Oriented Control (FOC) is widely adopted due to its benefits including low torque ripple, high DC bus voltage utilization, and stable variable frequency speed regulation, aligning with diverse motor applications. However, achieving high-performance requires dynamic current loop control. Traditional Proportional-Integral (PI) control, though widely used, suffers from limited bandwidth and overshoot. Alternatively, deadbeat control, leveraging current prediction, offers superior dynamic response. In this study, deadbeat control demonstrates a significant improvement of approximately 20% in current loop response compared to PI control, as evaluated through simulations. Addressing challenges posed by varying motor parameters, this study incorporates Luenberger observer for parameter disturbance compensation, further enhancing control robustness by 15%. The effectiveness of the proposed method, emphasizing deadbeat control, is validated through Simulink simulations, promising a robust future for PMSM control.

The Design and Validation of a Biocompatible and Cost-Effective Biomaterial Based Arm Patch for Intravenous Training Applications

Fizza Zaheer, Moiz Wali Khan, Maida Nadeem, Fahad Shakeel, Jahanzeb Gul — Fri, 03 Jan 2025 00:00:00 +0100

The objective of this study was to construct an efficient arm patch for intravenous medical simulation and training using easily accessible biomaterials to make a realistic and affordable training model for healthcare workers. In this assessment, factors like durability, biocompatibility and ease of fabrication were considered in order to determine the appropriate biomaterials. It was important to have realistic veins together with skin texture in the arm patch in order to achieve the best psychological imitation. The experiment was designed to make glycerinated gelatin skin layers for an arm patch with IV tubing as veins. The material was subjected to compression and bending tests to confirm that the mechanical properties required for realistic and sustainable simulation. Findings indicated that the arm patch was capable of accommodating a lot of pressure and possessed elastic properties like human skin. Arm patch users demonstrated enhanced performance and accuracy level in IV catheter insertion procedures. In this way, excluding a live patient, this arm patch improves patient safety forgoing ethical issues in the education of medical personnel.

Predictive Modeling of Chronic Kidney Disease Progression with Ensemble Learning Techniques

priha bhatti — Wed, 08 Jan 2025 00:00:00 +0100

The present study aims to tackle the significant issue of prompt identification of chronic kidney disease (CKD), a highly prevalent and potentially fatal medical illness. Given the crucial function of the kidneys in maintaining homeostasis, we put forth a novel ensemble learning model to forecast the onset of chronic kidney disease (CKD). Utilizing an extensive dataset, the study employs ten carefully designed stages, covering data analysis, missing data management, normalization, and training of machine learning models. The model that we have proposed exhibits superior performance compared to the existing approaches, attaining a noteworthy accuracy rate of 98.74%. Additionally, it demonstrates a sensitivity rate of 100%, a specificity rate of 96.54%, and an F1 score of 99.02%. The visual representation of the confusion matrix effectively showcases the strong performance of the model. The results of this study indicate that our ensemble technique holds promise as a valuable tool for the prompt detection of chronic kidney disease (CKD). It has the potential to improve diagnostic accuracy in clinical settings and alleviate the financial burden associated with advanced CKD treatments.

An experimental and numerical investigation on aerodynamic characteristics for different airfoil sections for external flow

Irsa TALIB — Wed, 08 Jan 2025 00:00:00 +0100

This research presents the development of a subsonic wind tunnel designed for streamlined airflow, featuring a squared cross-sectional area along its length. The primary focus is on measuring drag and lift on external flow across two different airfoil models. Utilizing a variable-speed centrifugal blower motor in the absence of converging and diverging sections ensures streamlined airflow in the test section. Two airfoil models, NACA-0012 and NACA-2414, fabricated from galvanized iron thin gauge sheet metal, undergo analysis through wind tunnel experiments and numerical simulation. Within the wind tunnel, strain gauge load cells are incorporated to accurately measure drag and lift across the airfoils. Comparative assessments of drag and lift coefficients are conducted at four varying angles of attack (-6.3 degrees to 12.6 degrees) for each airfoil. Results from both wind tunnel experiments and numerical simulations demonstrate precision, closely aligning with literature.

Interference Analysis of Very Fast Transient Overvoltages in Gas-Insulated Substations Using a Hybrid Algorithm

Mon, 13 Jan 2025 00:00:00 +0100

The reliable and efficient computational approach for the cable interference in gas insulated substations (GIS) is presented. The hybrid domain decomposition method-multilevel fast multi-pole algorithm (DDM-MLFMA) is presented herein. This technique determines the specifications of GIS cables for RG58 and AWG23. Self and mutual interference are identified utilizing the very fast transient overvoltage (VFTO) transient interference signal. The hybrid technique offers a numerical simulation to replicate the impact of the VFTO interference signal. Utilizing the matrix-vector multiplication product (MVX) to address compression and approximation challenges, the hybrid approach proves reliable and pragmatic. Because of its computational nature and explicit factorization reduction, this strategy reduces computation time and memory requirements. Consequently, the system's complexity follows a linear trend under this proposed approach. The computed results are juxtaposed with traditional methodologies to validate the effectiveness of the proposed algorithm.

Robust Face Detection and Identification under Occlusion using MTCNN and RESNET50

Eiman Wahab, Wajeeha Shafique, Habiba Amir, Sameena Javed, Muhammad Marouf — Sun, 19 Jan 2025 00:00:00 +0100

In today's rapidly evolving world, where technology is progressing swiftly, there is an increasing demand for facial recognition systems. Technologies are similar to digital forensics in that they can recognize people by scanning faces. However, one key problem they confront is dealing with covered or occluded faces, which might restrict recognition of faces in real-world situations. To overcome this issue, we created a system that is capable of identifying individuals even when their faces are veiled. We used the face detector algorithm called Multi-Task Cascaded Convolutional Neural Network (MTCNN) for face detection with 99.8% accuracy. Further we have conducted feature extraction and pre-processing on our self-created dataset. Our project utilizes the power of deep learning model: Residual Network (ResNet50), the form of deep neural network architectures well-suited for the job of features extraction. These features are matched by using Cosine similarity with accuracy of 92%. By leveraging the capabilities in the deep learning algorithms, this project provides a robust solution for automating the recognition of partially occluded faces.

Development of a Cost-Effective Plasma Thawer: A Potential Game-Changer in Blood Transfusion Technology

Tue, 28 Jan 2025 00:00:00 +0100

Plasma thawers are vital in healthcare, ensuring safe thawing of frozen plasma for life-saving transfusions. To address challenges such as specialized operator training and high initial costs in low-resource settings, we developed a cost-effective and efficient plasma thawer in Pakistan. The device consisted of two compartments: one dedicated to thawing plasma and equipped with a water-filled heater, a continuous temperature sensor, and an agitating frame for plasma bags, and the other housing the control box. Optimized thawing conditions were defined. The regulation of temperature and control of motors were coordinated through an Arduino microcontroller and relays which allowed users to set temperature limits through push buttons. Our device was able to thaw frozen plasma, accurately maintaining water temperature between 37-40°C. The samples were clear of solid and gelatinous particles, indicating no protein denaturation or overheating. A buzzer signaled the completion of each cycle. The microcontroller cut off power to the heater if the temperature exceeded the upper limit. Relays activated heater to maintain water temperature above the lower limit and activated DC motor which converted rotational motion into linear motion through gears. The device was 10 times more cost-effective compared to commercially available alternatives. We demonstrated that plasma can be thawed using our prototype without any negative influence on the plasma quality, presupposed that optimized settings defined for this plasma product are used. We plan to further assess plasma coagulation, inhibition activity and hemostatic potency.