Search Results (64)

The conventional cascaded control strategies using proportional-integral-derivative controllers often result in high settling times, considerable oscillations, poor voltage regulation, and low bandwidth. This leads to unsatisfactory performance in systems where multiple input variables are each subject to high levels of temporal variability, such as in DC microgrids (MGs) with renewable sources of generation. To overcome these challenges, a new combined control technique including average current mode and PI controllers based on root locus tuning is proposed for DC MGs to maintain small-signal stability. An analytical small-signal equivalent model of DC MG, including the proposed control, is developed to examine the impact of control parameter variations on system dynamics. The stability of the DC MG is assessed to evaluate the effectiveness of the designed controller, while a sensitivity analysis identifies critical parameters affecting system performance. The effectiveness of the proposed control scheme is demonstrated through a comprehensive comparative analysis with a conventional PID controller and a terminal sliding mode controller, which specifically addresses small-signal disturbances. Results demonstrate that the proposed control scheme provides superior robustness against small-signal disturbances, minimises settling time, and eliminates oscillations. Moreover, it offers improved power quality, bandwidth, and voltage regulation compared to conventional methods under both normal operating conditions and in response to small-signal perturbations. Full article

A centrifugal pump incorporating two inlets and a double-layered impeller is proposed for transporting a mixture of sand and water. The double-layered impeller (primary impeller) encircles a secondary impeller. To reveal the operating and flow characteristics of such a pump, numerical work is conducted with a validated numerical method. The effects of the feed rate of sand and the rotational speed of the impeller are investigated. The results show that the pump efficiency is not monotonically related to the solid volume fraction. At a feed rate of sand of 2.10 m³/min and a rotational speed of 950 rpm, the lowest pump efficiency is reached. In the volute chamber, vortices of various sizes are evidenced. With increasing rotational speed, the overall solid volume fraction in the pump decreases. Meanwhile, when the solid volume fraction attains 0.28, sand particles tend to accumulate near the outer rim of the volute chamber. The axial force acting on the primary impeller increases with the rotational speed. Under different operating conditions, the radial forces point unanimously toward the third and fourth quadrants. Full article

Aim: In order to understand the global variations in the growth trajectories of cerebral palsy patients, this study aimed to compare the growth patterns of cerebral palsy patients in Saudi Arabi with United States and United Kingdom counterparts. Method: Anthropometric data from 107 participants with cerebral palsy in Saudi Arabia were collected, including age, gender, cerebral palsy type, Gross Motor Function Classification System level, birth weight, weight at assessment, height at assessment, body mass index, and head circumference at assessment. Results: This study found discrepancies between the growth patterns of Saudi Arabian children with cerebral palsy and United Kingdom and the United States growth charts, particularly among those with severe cerebral palsy. Significant differences were observed in weight, height, and body mass index z-scores when comparing Saudi Arabian data with the United kingdom and United States reference data. Interpretation: These findings emphasize the importance of validating growth charts across different populations to ensure accurate monitoring and clinical management of children with cerebral palsy. Additionally, this study highlights the need for region-specific growth references to better address the diverse needs of individuals with cerebral palsy worldwide. Full article

In this paper, a novel Multi-Objective Hypergraph Particle Swarm Optimization (MOHGPSO) algorithm for structural health monitoring (SHM) systems is considered. This algorithm autonomously identifies the most relevant sensor placements in a combined fitness function without artificial intervention. The approach utilizes six established Optimal Sensor Placement (OSP) methods to generate a Pareto front, which is systematically analyzed and archived through Grey Relational Analysis (GRA) and Fuzzy Decision Making (FDM). This comprehensive analysis demonstrates the proposed approach’s superior performance in determining sensor placements, showcasing its adaptability to structural changes, enhancement of durability, and effective management of the life cycle of structures. Overall, this paper makes a significant contribution to engineering by leveraging advancements in sensor and information technologies to ensure essential infrastructure safety through SHM systems. Full article

The diversity in the global food market is expanding as thousands of new products enter the business every year, among which nutraceutical and functional foods hold important positions. The present research work aimed at the nutritional evaluation of three medicinal herbs, i.e., turmeric (Curcuma longa L.), ginger (Zingiber officinale), and black cumin (Nigella sativa). A bread formulation was enriched with the individual/combined supplementation (1–3%) of these herbs. Later, the bread was analyzed for nutritional, rheological, textural, and sensorial characteristics. The results revealed that the herbs improved the nutritional composition of bread, especially ash and fiber, as the maximum ash and fiber contents were noticed in T₁₅ (2.0% dried powder of each plant) with values of 1.64 ± 0.04% and 4.63 ± 0.16%, respectively. The results regarding the rheological behavior showed minor variations in the rheological traits and a slight increase in dough development time up to 4.50 ± 0.20 min in T₁₀ from 2.80 ± 0.13 min in T₀. The sensorial attributes also indicated their marked suitability as external and internal characteristics were least affected by the addition of the herbs. Although some parameters like the crust and crumb colors were affected by the addition of black cumin, showing values of 6.25 ± 0.52 and 4.44 ± 0.19, respectively, in T₁₅, and aroma characteristics were affected by the addition of ginger, supplementation with a combination of herbs at lower doses mitigated the adverse effects of other herbs. Moreover, shelf-life extension, especially with the addition of turmeric powder, was the hallmark of this research. This study concluded that medicinal herbs can be incorporated into baked products to improve the nutritional and sensorial attributes of functional herbal bread. Full article

The role of antennas in wireless communication is critical for enabling efficient signal transmission and reception across various frequency bands, including those associated with IoT (Internet of Things), X-band, S-band, and RFID (radio-frequency identification) systems. This paper presents a small quadruple-band antenna with 25 × 40 × 1.5 mm³ dimensions designed for diverse wireless applications. It is adept at operating in the S-band (2.2 GHz), wireless local area network (WLAN) (5.7 GHz), microwave RFID frequency band (5.8 GHz), and X-band (7.7 GHz and 8.3 GHz). While the majority of existing research focuses on antennas covering two or three bands, our work stands out by achieving quad-band operation in the proposed antenna design. This antenna is constructed on a semiflexible Rogers RT5880 substrate, making it well-suited for wearable applications. Computer Simulation Technology (CST) Microwave studio (2019) simulation package software is chosen for design and analysis. The antenna design features a comb-shaped radiating structure, where each “tooth” is responsible for resonating at a distinct frequency with an appropriate bandwidth. The antenna retains stability in both free space and on-body wearability scenarios. It achieves a low specific absorption rate (SAR), meeting wearable criteria with SAR values below 1.6 W/Kg for all resonating frequencies. The proposed antenna demonstrates suitable radiation efficiency, reaching a maximum of 82.6% and a peak gain of 6.3 dBi. It exhibits a bidirectional pattern in the elevation plane and omnidirectional behavior in the azimuth plane. The antenna finds applications across multiple frequencies and shows close agreement between simulated and measured results, validating its effectiveness. Full article

The world is progressing towards sustainable, eco-friendly, recyclable materials to enhance the circular economy and mitigate the issues of carbon footprint, overburdened landfills, and waste of natural resources. As increasing greenhouse gas (GHG) emissions are a major contributor towards climate change and given that the construction industry is one of the major producers of GHG emissions, it is crucial to meticulously quantify and lower its emissions, especially in the context of developing countries. This research presents a novel framework by combining advanced tools i.e., building information modeling (BIM), life-cycle assessment (LCA), geographic information systems (GISs), and quantification of embodied emissions to optimize construction’s design, material-selection, operations, maintenance, and waste-management processes. The effectiveness of the proposed approach has been demonstrated with the help of a real-world case study in Islamabad, Pakistan. A building model has been generated using BIM, and a comprehensive LCA has been conducted. Additionally, GIS tools have been utilized to identify the locations and accessibility of available-waste-management facilities. Based on this data, embodied emissions related to handling and transportation of waste material to disposal facilities have been computed using mathematical analyses. Furthermore, targeted mitigation strategies have been proposed and an optimized route has been designed using GIS-based route-optimization tools along the suggested facility centers in the Islamabad region. The case study has been reassessed with alleviation strategies, and the results show that 29.35% of the materialization stage, 16.04% of the operational stage, and 21.14% of the end-of-life-phase GHG emissions can be effectively reduced. Hence, pre-evaluating the environmental degradation caused by construction projects throughout their life cycle might offer an opportunity to comprehend and reduce prospective environmental impacts. Full article

The use of solar energy has shown the fastest global growth of all renewable energy sources. Efforts towards careful evaluation are required to select optimal locations for the installation of photovoltaics (PV) because their effectiveness is strongly reliant on exposure to solar irradiation. Assessing the shadows cast by nearby buildings and vegetation is essential, especially at the city scale. Due to urban complexity, conventional methods using Digital Surface Models (DSM) overestimate solar irradiation in dense urban environments. To provide further insights into this dilemma, a new modeling technique was developed for integrated 3D city modeling and solar potential assessment on building roofs using light detection and ranging (LiDAR) data. The methodology used hotspot analysis to validate the workflow in both site and without-site contexts (e.g., trees that shield small buildings). Field testing was conducted, covering a total area of 4975 square miles and 10,489 existing buildings. The results demonstrate a considerable impact of large, dense trees on the solar irradiation received by smaller buildings. Considering the site’s context, a mean annual solar estimate of 99.97 kWh/m²/year was determined. Without considering the site context, this value increased by 9.3% (as a percentage of total rooftops) to 109.17 kWh/m²/year, with a peak in July and troughs in December and January. The study suggests that both factors have a substantial impact on solar potential estimations, emphasizing the importance of carefully considering the shadowing effect during PV panel installation. The research findings reveal that 1517 buildings in the downtown area of Austin have high estimated radiation ranging from 4.7 to 6.9 kWh/m²/day, providing valuable insights for the identification of optimal locations highly suitable for PV installation. Additionally, this methodology can be generalized to other cities, addressing the broader demand for renewable energy solutions. Full article

In this paper, the application and future vision of Artificial Intelligence (AI)-based techniques in microgrids are presented from a cyber-security perspective of physical devices and communication networks. The vulnerabilities of microgrids are investigated under a variety of cyber-attacks targeting sensor measurements, control signals, and information sharing. With the inclusion of communication networks and smart metering devices, the attack surface has increased in microgrids, making them vulnerable to various cyber-attacks. The negative impact of such attacks may render the microgrids out-of-service, and the attacks may propagate throughout the network due to the absence of efficient mitigation approaches. AI-based techniques are being employed to tackle such data-driven cyber-attacks due to their exceptional pattern recognition and learning capabilities. AI-based methods for cyber-attack detection and mitigation that address the cyber-attacks in microgrids are summarized. A case study is presented showing the performance of AI-based cyber-attack mitigation in a distributed cooperative control-based AC microgrid. Finally, future potential research directions are provided that include the application of transfer learning and explainable AI techniques to increase the trust of AI-based models in the microgrid domain. Full article

Background and Objectives: Dermatological disorders are highly prevalent among children in Pakistan. The present cross-sectional study aims to identify the spectrum of dermatological conditions among children and adolescents in Pakistan. Materials and Methods: A total of 582 patients (50.9% males; 49.1% females) were included in the study based on their age (5.7 ± 4.1 years), dermatological condition, and epidemiology. The youngest patient was aged ten days, whereas the eldest was seventeen. Age criteria were further stratified into three categories: infants and toddlers (≤5 years), children (≥5 to <12 years), and adolescents (≥12 to <18 years). Amongst them, the majority was from Punjab (81.6%), while the other regions included were Azad Jammu and Kashmir (14.4%), Islamabad (3.3%), and Khyber Pakhtunkhwa (0.7%). Results: Scabies was the highest reported skin condition with 281 (45.55%) patients, followed by 114 (19.6%) with eczema, 60 (10.3%) with dermatitis, 33 (5.7%) with tinea capitis, 17 (2.9%) with tinea corporis, 16 (2.7%) with impetigo, and 15 (2.6%) with folliculitis. Other conditions include urticaria, burns, infections, pediculosis, tinea inguinalis, tinea faciei, nappy rashes, alopecia, warts, tinea incognito, tinea cruris, and acne vulgaris. The chi-squared test showed a high prevalence of tinea corporis and acne among adolescents (12–17 years), whereas eczema, dermatitis, and impetigo were more prevalent among infants and toddlers. Conclusions: Pets or livestock and poor hygiene were found to be highly reported risk factors for many dermatological conditions like scabies and fungal infections. Dermatological conditions are common in younger individuals, but unfortunately, many children do not receive the desired medical assistance. Full article

Phishing attacks are evolving with more sophisticated techniques, posing significant threats. Considering the potential of machine-learning-based approaches, our research presents a similar modern approach for web phishing detection by applying powerful machine learning algorithms. An efficient layered classification model is proposed to detect websites based on their URL structure, text, and image features. Previously, similar studies have used machine learning techniques for URL features with a limited dataset. In our research, we have used a large dataset of 20,000 website URLs, and 22 salient features from each URL are extracted to prepare a comprehensive dataset. Along with this, another dataset containing website text is also prepared for NLP-based text evaluation. It is seen that many phishing websites contain text as images, and to handle this, the text from images is extracted to classify it as spam or legitimate. The experimental evaluation demonstrated efficient and accurate phishing detection. Our layered classification model uses support vector machine (SVM), XGBoost, random forest, multilayer perceptron, linear regression, decision tree, naïve Bayes, and SVC algorithms. The performance evaluation revealed that the XGBoost algorithm outperformed other applied models with maximum accuracy and precision of 94% in the training phase and 91% in the testing phase. Multilayer perceptron also worked well with an accuracy of 91% in the testing phase. The accuracy results for random forest and decision tree were 91% and 90%, respectively. Logistic regression and SVM algorithms were used in the text-based classification, and the accuracy was found to be 87% and 88%, respectively. With these precision values, the models classified phishing and legitimate websites very well, based on URL, text, and image features. This research contributes to early detection of sophisticated phishing attacks, enhancing internet user security. Full article

In Pakistan, residential energy consumption is predominantly devoted to ensuring thermal comfort, making energy reduction a significant task in building load management. Windows, which are notorious for having poor thermal barriers, contribute considerably to energy losses under harsh weather conditions. Incorporating high thermal inertia materials in windows, such as transparent insulation materials (TIM) and phase change materials (PCM), offers the potential for energy reduction. Using numerical simulations in ANSYS Fluent, this study compares three window types and explores their influence on interior temperature. The findings show that PCM-based windows have a low temperature increase during the melting phase, indicating their great energy-saving potential. Furthermore, PCM absorbs almost 90% of exposed heat, emphasizing its usefulness for energy saving in the Pakistani building industry. Full article

The hydraulic performance of stilling basins is affected by their size and geometry, which can be predicted by local scour. In 2008, based on a rigid bed study, the stilling basin of Taunsa barrage was remodeled, in which the old friction and baffle blocks were replaced with chute blocks and end sills. However, the study did not consider the effects of the remodeled basin on the erodible bed and only investigated hydraulic jumps. Therefore, this study developed FLOW-3D scour models for a designed flow of 24.28 m³/s/m to investigate the flow field and local scouring downstream of old and remodeled basins. The results showed that as compared to Large Eddy Simulation (LES) and Standard K-ε models, the Renormalization Group (RNG-K-ε) model predicted the scour profiles with better accuracy, for which the coefficient of determination (R²) reached 0.736, 0.823, and 0.747 for bays 33, 34, and 55, respectively. Downstream of the remodeled basin, the net change in sediment bed was 88%, 91%, and 95% in the LES, Standard, and RNG-K-ε models, respectively. However, downstream of the old basin, the net change in sediment bed reached 51%. Conclusively, based on the results, the study suggests investigating scour downstream of Taunsa Barrage using other discharges and sediment transport rate equations. Full article

Electrolytes are one of the most influential aspects determining the efficiency of electrochemical supercapacitors. Therefore, in this paper, we investigate the effect of introducing co-solvents of ester into ethylene carbonate (EC). The use of ester co-solvents in ethylene carbonate (EC) as an electrolyte for supercapacitors improves conductivity, electrochemical properties, and stability, allowing greater energy storage capacity and increased device durability. We synthesized extremely thin nanosheets of niobium silver sulfide using a hydrothermal process and mixed them with magnesium sulfate in different wt% ratios to produce Mg(NbAgS)_x)(SO₄)_y. The synergistic effect of MgSO₄ and NbS₂ increased the storage capacity and energy density of the supercapattery. Multivalent ion storage in Mg(NbAgS)_x(SO₄)_y enables the storage of a number of ions. The Mg(NbAgS)_x)(SO₄)_y was directly deposited on a nickel foam substrate using a simple and innovative electrodeposition approach. The synthesized silver Mg(NbAgS)_x)(SO₄)_y provided a maximum specific capacity of 2087 C/g at 2.0 A/g current density because of its substantial electrochemically active surface area and linked nanosheet channels which aid in ion transportation. The supercapattery was designed with Mg(NbAgS)_x)(SO₄)_y and activated carbon (AC) achieved a high energy density of 79 Wh/kg in addition to its high power density of 420 W/kg. The supercapattery (Mg(NbAgS)_x)(SO₄)_y//AC) was subjected to 15,000 consecutive cycles. The Coulombic efficiency of the device was 81% after 15,000 consecutive cycles while retaining a 78% capacity retention. This study reveals that the use of this novel electrode material (Mg(NbAgS)_x(SO₄)_y) in ester-based electrolytes has great potential in supercapattery applications. Full article