Transforming Vehicular Networks: How 6G can Revolutionize Intelligent Transportation?

Vehicular Ad-hoc Networks (VANETs) have enabled intelligent transportation systems by facilitating communication between vehicles and roadside infrastructure. However, the current 5G and 4G networks that support VANETs have certain limitations that hinder the full potential of VANET applications. These limitations include constraints in bandwidth, latency, connectivity, and security. The upcoming 6G network is expected to revolutionize VANETs by introducing several advancements. 6G will provide ultra-fast communication with significantly reduced latency, enabling real-time and high-bandwidth data exchange between vehicles. The network will also offer highly reliable and secure connectivity, ensuring the integrity and privacy of VANET communications. Precise localization and sensing capabilities will be enhanced in 6G-based VANETs, enabling accurate positioning of vehicles and improved situational awareness. This will facilitate collision avoidance, traffic management, and cooperative driving applications. Moreover, integrating edge computing in 6G networks will bring computing resources closer to the edge, lowering response times and facilitating faster decision-making in time-critical scenarios. This paper explores the key features and capabilities of 6G technology and how it can revolutionize intelligent transportation, addressing challenges and opportunities for adopting 6G in VANETs

Optimizing Biomedical Facilities Performance with Dombeya Fiber-Paper Particle Hybrid Reinforced Epoxy Composites

Since the last two decades, the use of natural fiber reinforced polymer composites has garnered significant application considerations over the synthetic fiber reinforced composites due to their numerous advantages and unique properties. Likewise, epoxy resin has attracted the interest of many researchers for composite synthesis, basically because of its chemical stability, thermal and mechanical characteristics. Hence, the primary aim of this study was to investigate the influence of dombeya fiber and paper particulate on the physical and mechanical properties of dombeya fiber and paper particulate-reinforced polymer composites for structural applications. Dombeya fiber and paper particles are renewable and biodegradable materials, thereby making them environmentally friendly materials to replace synthetic materials. Hand lay-up technique was utilized to fabricate the hybrid-reinforced biocomposites after which they were subjected to mechanical, wear, density, and moisture absorption properties. The surface morphology of the fractured surface was also analyzed to investigate its microstructural features. It was discovered from the results that hybrid biocomposites demonstrated improved properties over the unreinforced composite, with composites from 9-wt% dombeya fiber-paper particles reinforced biocomposite exhibiting the most suitable properties with commensurate density with the unreinforced epoxy matrix. These obtained characteristics support the material as a suitable material for biomedical apparatus application such as orthopedic implants, surgical instruments, and bone fixation devices.

Characteristics and Efficiency of Heat Transfer for Natural Convection by Ag-CuO/H2O Hybrid Nanofluid Inside a Square Cavity with Corrugated Walls

A parametric numerical study is conducted on laminar natural convection and heat transfer in a cavity with opposing undulated walls saturated with a hybrid Ag-CuO/water nanofluid. The two vertical walls of the sinusoidally undulated cavity are maintained at hot and cold temperatures, while the upper and lower walls are thermally insulated. The investigation examines the effects of relevant parameters such as the sinusoidally undulated geometry of the walls for different volumetric fractions of nanoparticles (0% ≤φ≤6%) and Rayleigh numbers (103 ≤ Ra ≤ 106) Thefinite-volumee discretization method is employed to solve the system of governing equations. The results indicate that an increase in the volumetric fraction of nanoparticles enhances the heat exchange rate in the cavity. Additionally, the Rayleigh number, with a significant increase in surface area, strongly influences the dominant heat transfer mode in the cavity. Furthermore, an increase in the number of wall undulations leads to a reduction in the heat transfer rate

Recycling of Brick and Road Demolition Waste in the Production of Concrete

Construction and public works sites generate a significant amount of waste that is often costly to dispose of. To reduce the environmental impact and promote sustainability, recycling and recovering this waste is increasingly being recognized as a viable solution. This paper presents the findings of an experimental program investigating the feasibility of using brick and road demolition waste as concrete components. By substituting a portion of sand and cement with recycled materials, this study compares the properties of the reference concrete with concrete containing varying amounts of brick waste and road demolition debris. The obtained results demonstrate that the produced concrete with up to 40 % recycled content achieved a compressive strength exceeding 20 MPa after 28 days. This study suggests that recycled brick and road demolition waste could be a sustainable and economical substitute for conventional aggregates. Incorporating these materials into concrete reduces the cement content while maintaining or even improving the fresh and hardened properties of the concrete. However, it is crucial to limit the use of road demolition sand to 10 %, crushed brick fines to 20%, and brick sand (CBS) to 30% to ensure optimal performance

An Ultra High Frequency Radio Frequency Identification Compatible Circular Polarized Microstrip Antenna Array

This study focuses on the development, simulation, and practical validation of a metal-only microstrip patch antenna and its array designed to increase gain. The antenna is specifically designed to meet the growing demand for reliable and efficient RFID systems in various fields, such as asset tracking, inventory management, and smart logistics. Our design utilizes a truncated patch with an air substrate to achieve high gain and circular polarization. The antenna\u27s dimensions measure 468 × 188 × 31 mm³ and deliver impressive performance metrics, boasting a return loss |S11| of -18.21 dB and an estimated gain exceeding 10.6 dBi. These figures compare favorably with the simulated results, which indicate an |S11| of -20.8 dB and a total gain of 11.2 dBi. Our microstrip antenna array demonstrated consistent Circular Polarization quality throughout the radiation angle, with an Axial Ratio of less than 3 dB. This antenna has emerged as a compelling solution for UHF-band RFID technology to meet the demands of various real-world applications

A Review of Fatigue Failure and Life Estimation Models: From Classical Methods to Innovative Approaches

This review paper encompasses a comprehensive exploration of fatigue failure and fatigue life estimation techniques which spans from the classical methods to new and innovative approaches. The paper looks into the limitations and advancements of these techniques and highlights their respective strengths and areas for improvement. Some of the models such as artificial neural networks and genetic algorithms exhibit clear advantages in terms of processing speed, accuracy, and adaptability to diverse materials and loading scenarios. For instance, in estimating fatigue life under multiaxial loading, the stress scale factor model emerges as a viable alternative to the critical plane-based approach, as this technique offers superior efficiency under both constant and variable amplitude loadings. Additionally, optimization algorithms such as artificial neural networks and genetic algorithms show promising potential in efficiently estimating fatigue life due to their rapid computational capabilities. Despite the notable successes achieved by these techniques, none of them can be ascribed as a universal model capable of accurately estimating the fatigue life of all materials across diverse operating conditions as each of the techniques possesses its unique strengths and weaknesses, thus, necessitating the study for a better understanding of their applicability. Hence, this paper serves as a valuable compilation of various fatigue analysis techniques, targeted at paving the way towards the development of a universal model capable of handling different materials and loading conditions

Utilizing Support Vector Machines to Detect Hate Speech on Social Media

This paper presents a novel application of Support Vector Machines (SVM) in developing automated systems to detect hate speech on social media platforms, addressing a critical need for scalable solutions to enhance online safety and societal cohesion. By leveraging SVM\u27s proven efficacy in managing high-dimensional data and optimizing the balance between precision and recall, the study offers a comprehensive methodology that includes data collection, preprocessing, model training, deployment, and evaluation. The results demonstrate robust average performance across key metrics, affirming the model\u27s reliability in accurately identifying hate speech while minimizing false positives. This research advances the field by showcasing the practical and theoretical contributions of SVM in automated hate speech detection, highlighting its potential to significantly improve content moderation practices. The findings underscore the necessity for ongoing refinement of detection systems and collaborative efforts among researchers, technology firms, and policymakers to create more inclusive online environments that promote respectful discourse and community well-being

NPK Biofertilizer Production from Banana Peel, Feather and Bone Ashes and their Comparative Advantage to 20:10:10 Inorganic Fertilizer

The possibility of formulating nitrogen, phosphorus and potassium (NPK) biofertilizer from ashes of waste organic materials such as chicken feathers, bone and banana peels is investigated in this study by first subjecting the agricultural waste to 80-250  heat in a muffle furnace to produce ash. Kjeldatherm block digestion unit, UV spectrophotometer, and flame photometers, respectively helped in measuring the concentrations of N, P and K inherent in the fertilizer precursors as well as in 5 formulated blends (i.e., A, B, C, D & E). It was discovered that NPK in the single substrate and blends favorably compared with standard NPK 20:10:10 chemical fertilizer to some extent. Among single material fertilizer sources, feather ash with 0.179:1:0.134 NPK and bone ash with 0.009:1:0.021 NPK had the closest nutrient content with the standard, showing potential promise. On the other hand, Blend E is the same as the standard, followed by Blend A, B, D and C, which are hierarchically close in elemental composition to the standard. The choice of these biofertilizers is dependent on their nutrient compositions, the type of crops to be grown, and the soil mineral requirements. Most importantly, different NPK ratio organic fertilizers produced in this study can competitively be produced in a large scale to address huge costs associated with the NPK 20:10:10 standard commercial fertilizer. Blend E (NPK 20:10:10) can be formulated locally by farmers in rural areas easily using this particular agricultural residue or a host of other confirmed farm wastes

Comparative Performance Evaluation of Magnetron Sputtered TiN, AlCrN, and TiAlCrN Coatings

This study presents a comparative performance evaluation of magnetron-sputtered TiN, AlCrN, and TiAlCrN coatings on tool steel substrates. Coatings play a pivotal role in enhancing the durability of engineering components exposed to harsh conditions. TiN is known for outstanding hardness and durability, AlCrN for superior wear resistance, and TiAlCrN for exceptional thermal stability and oxidation resistance. The substrate (EN 1.2363) underwent PVD coating using a closed-field unbalanced magnetron sputter ion plating (CFUBMSIP) process in a water-cooled stainless-steel vacuum chamber with four magnetron ports, operating for 3 hours per batch followed by 12 hours of natural convection cooling, utilizing TiN, AlCrN, and TiAlCrN films deposited for 180 minutes in an Ar and nitrogen atmosphere. X-ray diffraction (XRD) revealed distinctive crystal structures, with all coatings exhibiting a common preferred orientation of the (111) plane and TiAlCrN showing a ternary nitride phase. Scanning electron microscopy (SEM) images displayed the compact nature of TiAlCrN with finer grains, while TiN exhibited a densely compacted with no evidence of delamination and AlCrN showed denseness with smaller grains. Nano-indentation test was conducted to assess the coatings\u27 hardness and elastic modulus. TiAlCrN exhibited the highest hardness (3091±243 HV), highest elastic modulus (369.86±54.19 GPa), and the best wear rate (0.1887 x 10-4 mm3/Nm-1) suggesting potential suitability for applications demanding superior rigidity and wear resistance. The study provides valuable insights for materials scientists and engineers in optimizing coating selection for specific applications

Automated Data Quality Control System in Health and Demographic Surveillance System

The automated data quality management system serves as a comprehensive solution developed to enhance the precision, dependability, and uniformity of data within data-driven organizations. Such systems play an important role in eliminating the shortcomings associated with manual data quality management, which is prevalent in health and demographic surveillance systems (HDSS). The ongoing difficulty of ensuring data quality through manual processing hinders the HDSS\u27s capacity to optimize data quality effectively. To address this challenge, our study adopted design science methodologies to provide guidelines for the design and implementation of the automated data quality control system. The open source technologies (Pentaho data integration, R Studio, SQL, Windows task scheduler) were used to facilitate the automation and validation of the incoming and database resident data. The quality of data has vastly improved since the implementation of the proposed system. The findings suggest that the automated data quality control system exhibited superior performance compared to the manual methods, thereby minimizing errors and time-wasting efforts.