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There are many Africans who hold the view that the philanthropic underpinnings of the openness movement have been hijacked by commercial publishers, violating the altruistic principles of open access to advance a business model that guarantees exorbitant profits. To address these challenges, the University of Cape Town (UCT) developed a diamond open access publishing alternative via the continental publishing platform whose core goals are to advance inclusivity, equity and diversity. The platform uses the tenant infrastructure model as it offers participating institutions the prospect of enhancing their prestige through showcasing their academically sound scholarship. This paper spotlights the success of one of its publications to showcase the impact of library publishing from two perspectives, firstly, the advancement of OA movement and secondly, the contribution of the publication to student success. Both perspectives demonstrate how libraries can reclaim the philanthropic underpinnings of OA and accelerate inclusivity, equity and diversity. The platform demonstrates its potential to disrupt the current alienating publishing ecosystem and resurect the founding philanthropic principles of OA.

Cipadessa baccifera es un arbusto leñoso que se propaga a través de semillas y raíces subterráneas. Las flores muestran androceo urceolado, protandria fuerte y receptividad del estigma mostrada por la cabeza del estilo turbinada que permite un mecanismo de polinización secundaria. Son autocompatibles, nectaríferas y producen los tres azúcares comunes y ciertos aminoácidos en el néctar, y también ciertos aminoácidos en el polen. Además, las flores presentan un síndrome de polinización generalista adaptado a la polinización por diferentes clases de insectos. Las abejas, avispas y mariposas actúan como polinizadores; el primer grupo efectúa principalmente geitonogamia, mientras que los otros dos, principalmente xenogamia. En esta especie, la autogamia espontánea no es funcional porque la protandria la impide. Sin embargo, los visitantes de las flores podrían efectuar la autogamia después de que el estigma alcance la receptividad, pero en ese momento los insectos han dispersado la mayor parte del polen de la flor. Las pruebas de polinización manual indicaron que la autogamia, la geitonogamia y la xenogamia manipuladas son funcionales con la mayor producción de frutos en el último modo. Tal sistema de reproducción indica la función de xenogamia facultativa que retrasa la autopolinización por protandria fuerte y promueve la polinización cruzada. El fruto es una drupa globular carnosa que produce de 5 a 10 semillas unidas por un arillo carnoso común. Los modos de dispersión de semillas son por ornitocoria, barocoria e hidrocoria. Por lo tanto, el modo dual de propagación, la xenogamia facultativa, el mecanismo de polinización secundaria, el síndrome de polinización generalista, la entomofilia y la policoria funcional de permite a C. baccifera crecer prolíficamente y ampliar su distribución en áreas donde no hay cobertura arbórea.

Potable water remains a global issue as the world continues to consume water from untreated sources. Almost all human activities such as domestic, agricultural and industrial need water. Quality of water is crucial for all. The Water Quality Index (WQI) has a distinctive ranking that summarizes the state of water quality at a glance for any particular region. Policymakers and other stakeholders generally agree with this approach since it can represent a complete picture of the quality of water bodies. The WQI is based on the analysis of various physicochemical parameters. In this research work, the WQI assessment of the water quality of river Swarnamukhi was taken up and conducted the study during the winter season, for 6 different locations along the River at Chandragiri town and 1 location within town in Tirupati region from Andhra Pradesh state, India. The parameters such as pH, temperature, turbidity, DO, BOD5, NO3 and PO4 were considered for analysis purposes as per the BIS and WHO norms. The National Sanitation Foundation Water Quality Index method (NSFWQI) is used in WQI calculations. The average WQI value obtained is 67.25. It indicates medium water quality helps locals to know the quality at a glance and provides information to improve the quality of the river.

Geopolymer binders have become a cutting-edge, environmentally friendly substance with the potential to replace Portland cement in a variety of applications and potentially cut the carbon footprint of concrete production by up to 80%. Precursors and alkali activator solution are the essential part of geopolymer. Precursor material can be industrial wastes and Ground Granulated Blast Furnace Slag is used in this investigation. However, the requirement of synthetic alkali activator solutions has to be addressed to fully realize the sustainability benefits of geopolymer concrete. In this aspect, an effort has been taken to synthesis sodium silicate solution from the processed rice husk ash using hydrothermal process and utilize the same for the production of geopolymer concrete. The different parameters that influence the properties of synthesized sodium silicate solution such as ratio of sodium hydroxide to rice husk ash, temperature maintained in the hydrothermal process and duration of hydrothermal process was varied and investigated in this study. The ratio of sodium hydroxide to rice husk ash was varied in different proportions such as 1:0.5, 1:1, 1:1.5, 1:2. Temperature was varied as 80, 100, 120 degree Celsius and reaction time was varied as 60, 90, 120, 150 minutes. The geopolymer concrete was tested for setting time, compressive strength, split tensile strength and water absorption capacity. The strategy is thought to have a good chance of significantly lowering the global warming potential of geopolymers. Findings of this study unleash hefty potential in the arena of geopolymer concrete towards sustainable development.

The primary focus of this research is to determine the optimal stirrup configuration to prevent shear failure. This project aims to investigate the behavior of beam-column joint frames under concentrated loads. Specimens with dimensions of 700mm x 500mm and cross-sectional dimensions of 200mm x 100mm, using M30 Grade concrete, were prepared for this study. The specimen was tested in the linear, non-linear range and up to ultimate load limit for a concentrated load. The load responses are measured with LVDT & Data logger in this experimental work. The code of practice recommends (Bureau of Indian standards-13920-1993) the bond, shear, and ductility, reinforcement for shear and moment carrying capacity. This code aims to fulfill both bond and shear requirements. This paper provides a thorough review and offers recommendations on the design and detailing of beam-column joint connections. Analytical value of the load carrying capacity of the beam column joint was assessed using limit state method by eliminating the partial safety factors for the load and strength. The results were compared between experiments and analytical values and suggestions are presented in this paper.

This paper provides a thorough examination of the recycling process for solar panels and the environmentally-friendly disposal of photovoltaic (PV) elements. By combining experimental data synthesis and a thorough analysis of literature, many important conclusions may be drawn about the makeup of solar panels, the effectiveness of recycling photovoltaic components, the materials that can be recovered by recycling, and the environmental impact comparison between recycling and disposal techniques. The composition study indicates that the main components of PV modules include silicon, glass, aluminum, copper, plastic, and other elements, with silicon being the predominant constituent. An assessment of recycling efficiency reveals that silicon, glass, aluminum, and copper exhibit high rates, suggesting that these materials may be effectively recovered and reused. Moreover, the evaluation of recycled components reveals significant amounts of silicon, glass, aluminum, and copper are retrieved, indicating the possibility for reclaiming resources and achieving circularity in the solar sector. An environmental effect comparison demonstrates the environmental advantages of photovoltaic (PV) recycling, which include decreased energy usage, CO2 emissions, and trash formation in contrast to disposal options. These results emphasize the significance of PV recycling in advancing environmental sustainability, optimizing resource use, and fostering circularity in the solar sector. Nevertheless, in order to promote the extensive implementation of PV recycling methods, it is necessary to tackle obstacles like as technical constraints, economic feasibility, and legal frameworks. This research enhances understanding and aids decision-making in the realm of sustainable energy and resource management by combining data and insights from different studies. Ongoing research, innovation, and policy interventions are essential for speeding up the shift towards a circular economy in the solar business. This will promote environmental sustainability and resource efficiency in the renewable energy sector.

This research investigates the integration of vision-based navigation into the charging procedure of autonomous electric vehicles (AEVs). The study offers a comprehensive examination of the precision of calibration, the ability to identify objects, the navigation capabilities of autonomous cars, and the effectiveness of charging sessions. The visual systems undergo meticulous calibration, which leads to inherent traits that are crucial for accurate perception. Object recognition algorithms have exceptional proficiency in precisely spotting electric vehicles, charging stations, cables, and obstacles, while also exhibiting heightened levels of confidence. The adaptive navigation framework exhibits improved precision, as seen by developments in velocity and steering angle, enabling AEVs to effectively navigate through complex urban scenarios. Examining the data from charging sessions indicates that the integration of vision- based navigation has led to enhanced operational effectiveness of AEVs. This is apparent via the significant reduction in charging duration and the favorable boost in energy output. The cross-parameter analysis reveals the interconnectedness, emphasizing the influence of accurate calibration on the recognition and movement of objects. It showcases a holistic integration of perception, navigation, and charging procedures. The findings have significant implications for the widespread adoption of vision-based navigation, providing a groundbreaking method for seamlessly incorporating autonomous electric vehicles (AEVs) into real-world scenarios. Future research should give priority to enhancing calibration techniques, exploring advanced object detection algorithms, and resolving challenges related to dynamic urban environments. This will serve to validate the agility and reliability of the vision-based navigation architecture. In summary, this research offers valuable insights into the potential impact of vision-based navigation on the process of charging autonomous electric vehicles. Vision-based navigation is essential for the successful operation of AEVs in dynamic urban contexts.

The innovative elevated step-up gain DC-DC converter with switched capacitor and regenerative Boost configuration is a pivotal advancement in solar photovoltaic (PV) energy conversion. With a focus on enhancing solar PV applications, this converter efficiently elevates the low-voltage DC output of solar panels, addressing the challenge of low-voltage outputs inherent in solar panels. This breakthrough technology facilitates energy storage, off-grid power supply, and grid integration, contributing to a sustainable solution for optimizing solar power consumption. The converter's regenerative qualities promise to revolutionize solar PV applications, increasing sustainability and efficiency. Its main feature, a significant increase in step-up gain, ensures the effective conversion of low-voltage DC output from solar panels to higher levels, crucial for diverse applications in solar PV systems. This transformative technology plays a vital role in creating a more environmentally and energy-resilient world.

Concentrated solar power has the potential to produce large-scale renewable energy sources. Concentrated solar energy is produced using mirrors, reflective materials, or lenses on conical surfaces such as a parabolic dishes, parabolic troughs, towers, Fresnel reflector systems, and dish sterling collectors. The concentrated light source was converted into heat energy, which drove the heat engine into an electrical power generator. To gain more heat energy, the solar rays must be trapped and concentrated on their conical focus points. To increase the net overall efficiency of the system, it is vital to know the optical performances of the subsystem formed by the solar receiver and the parabolic concentrator. In this study, a beam of incident solar rays was traced on a parabolic dish collector, and a simulation is performed for concentrator behaviour using the ray-tracing code SolTrace developed by the NREL laboratory. For an incident radiation of 1000 W/m2 (considering 10000 photon rays), their optical performance and solar heat flux were simulated. The results show that the number of elements in SolTrace varies depending on the CFD mesh density, the number of rays utilised in the Monte Carlo technique and their impact on generating a resolution-independent solution. Investigating the ray tracing of the disc concentrator, the propulsive energy for viable applications can be analysed.

Finding increasingly efficient heat exchangers requires a critical task: the development of fin profiles for prolonged life of equipment. The present study uses numerical analysis for better plate-finned heat exchangers hydraulic and thermal performance. Fin patterns are used in the analysis to evaluate a four-tube in-line heat exchanger. The proposed approach involves use of simulation and numerical methods to solve the heat transfer problem on different materials and wind velocity data as boundary conditions for improved heat transfer. The Reynolds-Averaged Navier-Stokes (RANS) model will be used to correct the average turbulent air flow over finned tubes in three dimensions using the ANSYS-Fluent software. The evaluation plan compares the current findings with published Nusselt number empirical correlations for the justification. Finally, the presentation of a parametric study on the impact of fin perforation size and shape on different materials and the behaviour of fluid dynamics and heat transfer. Larger fin perforation sizes (circular, rectangle, rhombus, and ellipse shapes) are found to enhance the heat exchangers' overall PEC and thermal efficiency for sustainability of the thermal equipment. The comparison was made between non-perforated and perforated fin types. Ultimately, it was determined that the best option for plate fin heat exchangers is the circular type perforated fin. When compared to without perforated fins, the circular type perforated fin has a higher heat transfer coefficient. A circular perforated fin has high performance, and the rhombus type perforated fin has lower performance.

ETABS software is used to analyze the structural response of reinforced concrete (RCC) and post-tensioned (PT) slabs under lateral loading. This study investigates RCC and PT slabs’ behavior by using finite element analysis to determine bending moments, shear forces, and storey drift. Prestrassed slabs display lower bending moments and shear forces than RCC slabs, demonstrating the effectiveness of prestressing in reducing structural requirements. A reduction in storey drift also indicates improved resistance to lateral deformations in PT slabs. In terms of structural performance and cost-effectiveness, PT slabs offer potential benefits for constructing layouts and construction, making them an attractive choice.

This study optimizes the production of activated carbon (AC) from two distinct agricultural wastes, barley husk and maize cob. The process is refined using the Taguchi method with the goal of enhancing water treatment techniques. The study emphasizes how crucial it is to make the transition towards renewable and affordable raw materials for the manufacturing of AC given the predicted expansion of the worldwide demand for AC. The study assessed the impact of four crucial variables on the production and quality of AC using a L9 orthogonal array: phosphoric acid concentration, heating by microwave time, power from the microwave, and nitrogen flow rate. Findings indicated that the most important element for maximizing the production of AC from these agricultural leftovers was microwave power, along with the percentage of phosphoric acid and the time frame of the heating process.

Renewable energy sources are sporadic in nature, they supplement conventional energy sources. The stability of the distribution system is impacted by the inclusion of these traditional sources. The power quality of the system is also impacted by random fluctuations. Systems for storing energy are therefore created. Therefore, a battery and capacitor integrated power management method for grid-connected photovoltaic systems is devised. Battery and supercapacitor work together to stabilize the system by grabbing both steady and sporadic power and regulating the DC link voltage. The purpose of supercapacitor is to reduce battery’s current stress.

The researchers are focusing on harnessing the electricity form the renewable energy resources by overcoming the challenges faced by them due its variable nature. This study discusses the developing significance of renewable energy sources (RES), in particular wind and solar electricity, in meeting future electricity demands. India’s geographical length is highlighted as beneficial for integrating variable renewable energy outputs into its grid. The paper also addresses Power-quality (PQ) issues springing up from integrating renewable energy sources, proposing solutions including single and Unified active power filter (SUAPF) and distributed Static Compensators (DSTATCOM). The work examines power quality issues associated with grid-related solar PV systems and the combination of Unified Power Quality Conditioners (UPQCs) in hybrid solar-wind systems. The analysis of the UPQC integration with the solar wind energy based hybris system concludes the enhancement in the power quality issues such as total harmonic distortions along with balancing the reactive power in the line.

This study reports the biosorption of nickel using powdered fallen coffee leaves. BET, SEM, FTIR, and XRD characterize the biosorbents. We go over the findings from thermodynamic, kinetic, and equilibrium biosorption experiments. Here are some of the factors that were studied: agitation duration (t), biosorbent size, pH of the aqueous solution (ranging from 1 to 8), initial nickel concentration (C0), pH (ranging from 5 to 150), temperature (ranging from 283 to 323), and so on. Coffee leaf powder is best when the pH is 4. This biosorbent pair works best when dosed at 18 g/L for nickel biosorption. Nitrogen absorption is 4.219 mg/g when coffee leaf powder is used. For nickel biosorption, CCD has optimized four parameters. The data on nickel biosorption are tightly matched to the biosorbent model of pseudo-second-order. The negative sign of the free energy change (ΔG) for coffee leaf powder (-1546 J/mol) reflects both the practicality and spontaneous nature of the biosorbent-material. Powdered coffee leaves are predicted to undergo enthalpy changes of 62.99 J/mol K and entropy changes of 51.08 J/mol K. When the value of ΔS is positive, it indicates that the randomness is increasing, and when the value of enthalpy change is positive, it indicates that the process is endothermic.

By combining silicon-based microelectronics with micromachining technology, microelectromechanical systems (MEMS) have been identified as one of the most promising technologies for the 21st Century. With its microsystem-based devices and technologies, it will have a dramatic impact on the way we live and the way we live our lives. With an emphasis on both commercial applications and device fabrication methods, the paper provides an introduction to the field of MEMS. As well as discussing the range of MEMS sensors and actuators, the phenomena that MEMS devices can sense and act upon, and the major challenges facing the industry, the presentation discusses the challenges faced by the MEMS industry. An introduction to the field of MEMS is presented in this paper, which is divided into four sections. A section on MEMS introduces the reader to its definitions, history, current applications, and miniaturization-related issues. Photolithography, bulk micromachining, surface micromachining, and high-aspect-ratio micromachining are among the fundamental fabrication methods discussed in the second section, as well as assembly, system integration, and packaging of MEMS devices. A brief description of the basic principles of sensing and actuation mechanisms is provided in the third section, which discusses the range of MEMS sensors and actuators, as well as the phenomena that can be sensed or acted upon with MEMS devices. Toward the commercialization and success of MEMS, the final section illustrates the challenges facing the industry.

Parking spaces, lobby areas, terrace gardens, and other amenities are highly sought-after in densely populated urban regions. Although floating columns can be useful and an achievable choice, it is important to research their structural performance and cost-effectiveness in the event of substantial ground motion imposed on by an earthquake. A building’s overall dimensions, geometry, and shape all impact how it acts and acts when subjected to seismic loads. For this reason, it is necessary to assess how well floating column buildings perform in seismically vulnerable places in comparison to conventional buildings. In this work, the performance of structures with floating columns for seismic loading is observed using dynamic analytic techniques in accordance with IS 1893 (2005). This study analyses both the floating columns and the conventional building without floating columns. When compared to a regular building, the research reveals that the floating column buildings exhibit a very quick increase in base shear and story displacement. The horizontal displacements experienced by floating column buildings are proportionally larger due to an increase in the fundamental time period. If the lateral displacement exceeds the codespecified maximum limit, damage to structural and non-structural parts may result. Because of the discontinuity in the load distribution path, seismic base shear and overturning moment are also increasing in the case of buildings with floating columns. Additionally, while asymmetrically introducing floating columns, torsional irregularity has been produced but the modal mass participation ratio has decreased. While it is true that the use of floating columns in high-rise structures allows for continuous open floor plans, they are also dangerous and susceptible in seismically active locations

The instabilities in the power supply, such as voltage spikes, transients, and distorted waves, can cause consumer electronics to malfunction or even fail altogether. It is one of the biggest worries for gridconnected WECS in the present and future.In a variety of ways, specialized power electrical devices can improve power quality. These days, power applications make use of a broad variety of flexible controllers that take use of advanced power electronic components.In order to effectively minimize various forms of power quality concerns in a grid-connected wind energy conversion system, this article evaluates the reliability of two distinctive electrical devices, the Distribution Static Compensator (DSTATCOM) and the Dynamic Voltage Restorer (DVR). MATLAB/SIMULINK is used to examine the devices’ performance.

Water is not only necessary for survival, but it also adds significantly to the quality of our lives. The rapid increase in population, economic expansion, and industrialization in developing nations has led to an unexpected need for water in cities. The capacity for water uses and wastewater generation in residential sectors has significantly risen during the past few decades. Wastewater treatment is an essential procedure in the sanitation system. Reusing resources and adhering to environmental regulations require efficient treatment and pollution management of municipal wastewater resources. The most preferred method for treating wastewater among the many options currently available is the coagulation and flocculation processes. People widely use this treatment due to its low energy consumption, reliability, affordability, and ease of use. This study evaluated the use of banana and lemon peels as coagulants in water treatment using coagulation-flocculation procedures as a potential substitute for alum. We determined the pH and coagulant dose for both banana and lemon peel combinations. The results of this experiment show that lemon peel works well as a coagulant to absorb biological oxygen demand. It has been discovered that the dehydration procedure works better with peels from bananas and lemons. The ideal duration of contact between lemon and banana peels is 90 minutes. For peels of bananas and lemons, the optimal particle size is 300μm, and the ideal dosage of adsorbent is 0.3g.

Most high-rise structures today are designed with floating columns for aesthetic purposes and the need for efficient use of space. Lattice columns are vertical load-bearing elements that do not extend the entire height of the building, they are usually located on one or more intermediate floors and support beams. These design innovations have benefits such as increased architecture and space allocation. Loads include load and side load. Heavy loads, including dead loads and live loads, are evaluated to determine the overall load distribution. Lateral loads resulting from earthquakes and wind forces are calculated based on local building codes. In seismic design, multistorey buildings with floating columns are analysed at different levels on curved planes to determine safe floating column locations. Structures can be analysed with symmetric information and dynamic analysis methods such as response spectrum or potential time. Preliminary analysis and equivalent static analysis using ETABS 2022. A 3D structural model was created to accurately represent the geometry of the building and its behavior under different load combinations was used to compare the building's response to seismic forces. The result is the behavior of the structure: shear strength, bending moment, deflection, and displacement. The results are obtained in the form of tables and graphs. The structures were built with M30 concrete and various types of steel. Reinforcement spacing and detailing is done in CSI Detail.

The importance of using recycled materials like rubber in construction materials is rising rapidly today. By incorporating used rubber into cement and mortar, we can save landfill space and reduce our dependence on natural resources. Rubber scrap can be mixed in as either fine or coarse aggregate. Add it to Portland cement for a stronger, more durable product (PC). This paper reviews the studies conducted so far on the feasibility of using waste rubber in place of conventional PC-based mortar and concrete’s natural fine aggregate. The strength and water-absorption capacity of materials made from ash from scrap rubber tyres were measured. Test results indicate that waste rubber ash was substitute with natural sand up 10% then strengths of the sample were enhanced after increasing the content of waste rubber tyre ash then strength was decreased. Water absorption capacity of samples was improved as increased the content of waste rubber tyre ash into concrete mix.

This study investigates the optimization of the size of a solar-wind hybrid microgrid using Particle Swarm Optimization (PSO) to improve energy production efficiency, economic feasibility, and overall sustainability. By using past solar and wind resource data, load demand profiles, and system component specifications, the PSO algorithm effectively maximized the capabilities of solar panels and wind turbines. The findings indicate a significant rise in daily energy production, with a 15% enhancement in solar panel capability and a 12% boost in wind turbine capability. The increased energy production plays a crucial role in dealing with the natural irregularity of renewable resources, hence enhancing the resilience and self-reliance of the microgrid. The economic calculations demonstrate significant improvements in the economic feasibility of the microgrid designs. The Levelized Cost of Energy (LCOE) undergoes a significant 10% decrease, suggesting a more economically efficient energy generation. Moreover, the payback time for the original expenditure is reduced by 15%, indicating faster returns on investment. The economic improvements highlight the practical advantages of using PSO for microgrid size, in line with the goal of creating sustainable energy solutions while minimizing economic costs. The improved performance of Particle Swarm Optimization (PSO) is shown by a thorough comparison study with other optimization approaches, such as Genetic Algorithms (GA) and Simulated Annealing (SA). The superior convergence rate of PSO, together with a 15% enhancement in solution quality relative to GA and SA, underscores the efficiency and efficacy of PSO in traversing the complex solution space associated with microgrid size. PSO’s comparative advantage makes it an effective tool for tackling the intricacies of integrating renewable energy, highlighting its potential for extensive use in microgrid design and optimization. The sensitivity evaluations demonstrate that the solutions optimized by the PSO are resilient even when important parameters vary, thereby highlighting the stability and dependability of the approach. In addition to technical and economic factors, the study evaluates the environmental consequences and social aspects of the optimum microgrid designs. The land use efficiency has seen a 10% enhancement, demonstrating the optimum application of area for renewable energy infrastructure. In addition, there is a 7% improvement in community approval, which demonstrates the algorithm’s ability to effectively handle social aspects and promote a comprehensive and socially acceptable approach to renewable energy projects.

This study presents a novel Fuzzy Logic-Based Energy Management model that aims to optimize the incorporation of renewable energy sources into smart grids. The research used simulated data to evaluate the model’s performance in important metrics, revealing significant improvements in the consumption of renewable energy, stability of the grid, dependability of energy storage, and overall efficiency of the system. The Fuzzy Logic Controller adjusts energy distribution in response to current inputs, leading to a significant 20% improvement in the usage of renewable energy. The capacity to adapt is crucial in dealing with the inherent fluctuation of solar, wind, and biomass sources. The approach greatly improves grid stability, as shown by a 15% decrease in grid frequency variations, highlighting its efficacy in assuring a more regulated and steady electricity supply. Furthermore, the dependability of energy storage systems exhibits a notable 25% enhancement in the state of charge, suggesting optimal cycles of charging and discharging. This increased dependability enhances the stability of the energy supply during times of high demand and variations in the power system. The Fuzzy Logic-Based Energy Management model exhibits a significant 22% improvement in total system efficiency when compared to conventional management systems. This indicator encompasses the model’s combined effect on the usage of renewable energy, the stability of the power grid, and the optimization of energy storage. Comparative analyses conducted against traditional control strategies, such as proportional-integralderivative controllers, consistently demonstrate the superiority of the fuzzy logic approach. This approach results in a 10% decrease in grid frequency deviations, a 15% enhancement in energy storage state of charge, and a 12% boost in overall system efficiency. The resilience of the Fuzzy Logic Controller is highlighted by sensitivity analysis, since it demonstrates consistent performance even when parameters vary significantly. The model’s practical usefulness and adherence to ethical principles are further confirmed by validation using real-world data from operational smart grid installations. This study provides valuable insights, establishing the Fuzzy Logic-Based Energy Management model as an innovative method for addressing the difficulties associated with integrating renewable energy into smart grids. This model promotes a more sustainable and efficient energy environment for the future.

This paper explores the revolutionary approach of enhancing aluminum composite manufacturing through the integration of Cr2O3 reinforcement using the Friction Stir Technique. The pivotal role of the vertical milling machine in executing Friction Stir Processing (FSP) is emphasized, detailing precise parameters crucial for achieving optimal results. The even dispersion of Cr2O3 throughout the matrix is highlighted as essential for ensuring consistent mechanical and chemical properties, enhancing overall strength, durability, and resistance to corrosion. Experimental findings reveal significant improvements across multiple mechanical properties, including a remarkable 21.56% increase in tensile strength, a notable 36.89% enhancement in hardness, a significant 24.33% improvement in fatigue strength, and a substantial 29.04% increase in wear resistance. These results underscore the effectiveness of Cr2O3 reinforcement via FSP in revolutionizing aluminum composite manufacturing, offering a pathway towards the development of high-performance materials with diverse industrial applications.

This study investigates the advancements in Aluminum-Based Composite Manufacturing through the incorporation of lanthanum oxide (La2O3) reinforcement using the Friction Stir Process (FSP). The pivotal role of precision machining, particularly the vertical milling machine, in executing FSP is emphasized. Specific parameters, including pin diameter, tool tilt angle, and rotational speed, were meticulously selected to ensure optimal performance. The uniform distribution of La2O3 particles within the composite matrix highlights the effectiveness of the fabrication process, indicating proper mixing and dispersion techniques. Experimental findings reveal significant improvements in mechanical properties, with a notable 22.78% enhancement in tensile strength, a significant 35.21% increase in hardness, a noteworthy 24.44% improvement in fatigue strength, and a substantial 28.68% increase in wear resistance observed in aluminum-La2O3 composites produced via FSP. These results underscore the potential of leveraging FSP for aluminum-based composite manufacturing, offering opportunities for the development of high-performance materials with enhanced mechanical properties and durability.

The rapid urbanization and population growth in cities have led to an unprecedented increase in municipal waste generation. Efficient management of this waste is crucial to maintaining a clean and healthy environment. Traditional waste management methods often fall short in addressing the dynamic nature of waste generation patterns. This project presents a Garbage Monitoring System (GMS) that utilizes advanced sensor technologies and data analytics to revolutionize waste collection processes in urban areas. The system integrates different sensors, devices for communication, and software applications to furnish real-time monitoring and data analysis for waste management. The system not only enhances the operational efficiency of waste management but also promotes environmental sustainability. By optimizing collection schedules, reducing waste overflow, and reducing environmental negative impact, the system represents a significant step towards building smart and eco-friendly cities. The approach is to help in an innovative way while collecting garbage and monitoring systems in an effective way.

Artificial Intelligence (AI) is transforming all of the technologies we use every day. More than ever, we are very near to the objective of vehicle autonomy, which has long been desired. Large automakers are also spending billions of dollars on the development of autonomous vehicles (AVs). Among the advantages of this new technology are the possibility for increased passenger safety, less congested roads, reduced traffic, optimized traffic, reduced fuel consumption, less pollution, and improved travel experiences. However, there are also new security and privacy problems associated with this paradigm change. Previously simple mechanical devices, vehicles are today computerized, networked, and intelligent. They gather vast amounts of data, which must be shielded from intrusions. In this paper, we examine privacy issues and security hurdles in AVs. We investigate several attacks using a layer-by-layer methodology. It summarizes the contributions of these research works and categorizes them based on application domains. It also identifies open problems and research challenges that need to be addressed to fully realize the potential of AI in advancing V2X systems. Our intention is to provide insights into the unresolved research issues surrounding AVs and to suggest future lines of inquiry.

The execution of initiatives that are focused at employee satisfaction is always required in order to maintain skilled human resources, regardless of whether the firm in question is small, medium, local, or global. The turnover rate of employees has a significant impact on the total performance of an organization, which includes the performance of each individual employee, as well as the profitability of any given company. It is possible that the ineffective administration of human resources is the result of a lack of awareness regarding the significance of working individuals as well as a lack of continual practices regarding talent management. Without regard to the nature and level of the organizations in which the workers are engaged, it is possible to view them as "knowledge banks," and it is also possible that they are not necessarily positioned at the highest levels of the organization. The primary objective of carrying out this research study is to investigate the relationship between the practices of talent management in information technology industries and the retention of employees. Listed below are the two primary goals that the paper aims to accomplish: to learn about the strategies that are used for talent management in the information technology sector. And to investigate and demonstrate the relationship between the practices of talent management and the maintenance of employee retention. There are a few important results in this study about how to keep employees. It has been seen that workers with less than two years of experience are having a hard time adjusting to their new jobs and aren't seeing enough career growth. However, experienced workers have seen growth and are able to adapt to the work culture and freedom in their schedules.

You In most cases, doctors and the use of image processing tools can assess the placenta—the actual site of physical birth—during pregnancy. Models built using Machine Learning produce performance metrics such as Accuracy, ROC, Precision, Recall, and F-Measure, which quantify this support. This research makes use of the tailored strategy built into the Weka tool, namely the DeepLearning4j package.Using common architectures such as LeNet, VGGnet, ResNet, and Alexnet yields results that are comparable. By iterating over the input layer's Loss functions and the output layer's errors, DeepLearning4j evaluates and optimizes the suggested architecture based on its quality. The experimental results show that out of seven distinct loss functions, the one with the abbreviation "MCXENT" (meaning "Multi-class Cross Entropy") produces the most accurate and least error-prone results. Additionally, a maximum accuracy of 95.7% is obtained, which is considered the best performance. These findings lend credence to an additional machine learning strategy that employs an interactive development tool for gynecologists and offer fresh assurance in its efficacy.

Primary Colour Detection in an Image, Traditional methods of color cast detection do not discriminate between images with true cast and those with dominant colors. This may result in an inaccuracy of the color cast measurement. In order to overcome the limitation of traditional methods, an approach based on image semantic is present. It can improve the accuracy and reliability of the detecting results by the means of recognizing and removing the dominant color objects · and analyzing the color distribution of the whole image. Class specific color detection is already implemented in some systems, but image classification usually relies on global image features only. The method of recognizing the dominant color objects is based on block-features and region-features by using K-Means Clustering in this project. It shows a significant improvement over previously achieved classification for a variety of critical image classes. The comparison of the results of the approach proposed to that of people shows that it is reliable and effective. This project proposes the use of Machine Learning Techniques and Deep Learning Algorithms.

Science-based agriculture is increasing due to the rapid development of science and technology. To keep up with today's technology, many agricultural experts are turning to the Internet of Things (IoT) to drive advances in this field. For India, agriculture is the backbone of the Indian economy. The most important issue in today's technology is climate change. This review aims to provide an overview of IoT in agriculture and food to better understand the use of IoT and how it solves the above problems. Start by defining and further explaining the concept of IoT. The next section summarises the analysis results and discusses application areas, technical support, and future challenges.

Job stress causes increased absenteeism, which is a physical and emotional response to the work load. Employee presenteeism can be beneficial, yet it can also lead to a lack of productivity. Organisations must develop initiatives to promote employee well-being and manage job stress. Addressing job stress benefits both companies and individuals. Work-Life Balance (WLB) refers to the necessity for an employee to maintain a balance between work and personal life. Employee is able to prioritize both family and professional needs equally. Employee well-being and work-life balance are addressed through flexible working arrangements. Work-life balance is challenging to achieve in our daily lives; individuals should prioritize professional development, organizational progress, and job happiness. Conflicts at work and in the family emerge when work-life balance is not maintained, and individual progress is impeded. The current study's goal is to discover and suggest elements that contribute to job stress/strain among employees. Strategies to improve employee well-being and reduce stress. The study used the questionnaire method. A questionnaire with well-developed scales that covers all of the study's dimensions, including 9 items for job stress, 8 items for work-life balance, 6 items for work-family conflicts, and 4 items for family-work conflicts. Surveys and questionnaires make use of the convenience sampling technique. The questionnaire has 27 items and uses a 5-point LIKERT SCALE. The researcher can make a few recommendations. Employees that lack work expertise, have excessive job demands, or are unable to perform their duties experience work stress. •Organizations must address staff stress initiatives. A structured questionnaire is utilized to collect data from 220 employees for the study. Job stress reduces productivity and happiness while also causing a loss of physical and emotional equilibrium. Increased job strain causes excessive absenteeism and makes it difficult to concentrate at work. Tight deadlines and a high workload cause strain.

This study examines the use of artificial neural networks (ANNs) in real-time adaptive control for electric vehicle (EV) propulsion systems, with the goal of enhancing performance and efficiency. The neural network-based control system is developed and validated using experimental data that includes vehicle speed, battery temperature, battery voltage, and motor temperature. The neural network demonstrates precise control output predictions by effectively adapting to dynamic changes in input parameters, exhibiting a remarkable level of responsiveness to diverse operating settings. The analysis of the experimental findings reveals a strong correlation between the expected and actual control values, confirming the system's dependability and effectiveness in managing torque and voltage instructions for the electric vehicle (EV). The performance indicators, such as mean squared error (MSE), R-squared, mean absolute error (MAE), and root mean squared error (RMSE), demonstrate a small difference between the anticipated and actual values, indicating that the system has a high level of accuracy and predictive capacity. Furthermore, the system displays remarkable responsiveness to changes in velocity, battery temperature, and voltage, showcasing its capacity to adjust to different driving situations while still staying within acceptable levels of fluctuation. This research highlights the capacity of artificial neural networks (ANNs) to facilitate accurate and flexible control systems for electric vehicles (EVs), representing a substantial advancement in improving the performance, efficiency, and adaptability of electric vehicle propulsion in sustainable transportation systems. The neural network-based control system has been proven to be accurate, responsive, and reliable. This highlights its potential to revolutionize future electric vehicle (EV) technologies and contribute to advancements in real-time adaptive control strategies for environmentally friendly transportation systems.

The ecology and all of its components are suffering greatly as a result of the unchecked speed of development. At this rate, environmental degradation will have an impact on humanity and associated fields. In order to prevent the consequences of expansion from pushing the environment into a situation from which it is incapable of recovering, there should be ongoing, earnest efforts made towards sustainable development. The three pillars of ecodevelopment are the environment, humanity, and economy. A stable growth rate is necessary to attain a just balance between these pillars. Since agriculture employs the majority of the population, it also has an impact on the balance of the ecosystem. Because every unplanned step towards progress puts us back in the environmental front, we must thus be mindful of the boundaries of environmental challenges in order to achieve equitable economic growth. The hope for sustainable development lies in decreased deforestation, greater food security, conservative agricultural practices, the use of biopesticides, and prudent use of natural resources. To be effective, environmental policy probably needs to employ a variety of tools, each addressing a distinct aspect of the issue and attempting to minimise redundancies and pointless regulations. Appropriately pricing environmental inputs facilitates sustainable resource provision and use management. Long-term corporate investment in new technology and innovation is encouraged by a consistent and clear environmental policy, which also increases investment certainty. Environmental and economic success are interdependent. Economic activity and advancement depend on the natural environment because it provides the resources needed to produce goods and services and because it processes and absorbs waste and pollution, which are unwanted byproducts. This paper focuses on how environmental assets assist control risks associated with social and economic activities, flood risks, local climate regulation (temperature and air quality), and the availability of clean water and other resources.

Forest fires are a type of natural catastrophe that poses a risk to the vegetation and fauna of the hill stations. Due to the presence of vast enormous areas of land adorned with aged trees, vegetation, and wild life, safeguarding the ecosystem is both critical and arduous. A Geographic Information System and Remote Sensing assist in resolving this issue through the continuous monitoring of the forest using satellite, aerial, and drone-based imagery gathered from a variety of sources in India and Abroad. Landsat8 series Band 4, Band 5, Band 6 and Band 7 is used for the study. Following the correction and analysis of reflectance values for pre-fire and post-fire imagery, the Normalized Burn Ratio (NBR) is computed and processed. Finally, the difference in NBR based on the pre-fire event and post-fire event for the Yercaud hill station is analyzed and the severity level is classified for the chosen area of interest.

Water is the most required element next to air for terrestrial living being. Though the water is everywhere but no direct use is possible as the fresh water is getting contaminated through various human activities. The conventional treatment methods using activated sludge process, attached growth systems such as trickling filters, rotating biological contactors, aerated lagoons and stabilization ponds are normally practiced in many places with each one having its own merits and demerits depending on space availability, energy requirements etc. An alternative solution called phytoremediation method can save energy requirements to the great extent but space required will be more and it can be used advantageously where space is not a constraint. This method involves using plants to absorb and metabolize pollutants found in wastewater, including nutrients such as nitrogen and phosphorus, heavy metals and other organic and inorganic contaminants. In this study, sewage is passed through a bed of plants, which takes up nutrients and contaminants while releasing oxygen during their photosynthesis process. This promotes the growth of beneficial bacteria that further break down pollutants. In the present work, Spider lily (Hymenocallis littoralis) and Heliconia (Heliconia psittacorum) are two species of tropical plants used in constructed wetlands and that have shown potential in the treatment of sewage. Conducted the performance studies on both plants separately. The efficiency achieved with spider lily plants Heliconia plants are 87.2% and 79.6% in BOD removal respectively. These systems are also relatively low-cost and require minimal maintenance, making them a viable option for wastewater treatment in areas where conventional treatment systems may be too expensive or impractical.

India is a country whose roots are buried deep in agriculture. The livelihood of about 58% of the population depends on farming. Yet technological progress in the country’s agricultural practices is lacking. The growing technology and increased demand for agriculture calls for the incorporation of technology into sustainable agriculture. The proposed work, therefore aimed at building a drone to serve this purpose. The rapid growth of the Electric Vehicle (EV) market and India’s aim to shift to the complete use of EVs by the year 2023 demand a paradigm shift in the agriculture sector. The use of aerial electric vehicles would be an impeccable execution of EVs in agriculture, serving a vast set of functions. The proposed work focuses on one specific application: remote spraying of pesticides in an efficient way so that the overhead costs of farming are reduced. The harmful effects of exposure to pesticides are eminent. Farmers who take it upon themselves to spray these pesticides are at risk of contracting a wide range of health adversities and deadly chronic diseases. As a solution to this imminent need, it is proposed to design a drone to spray pesticides according to the requirement, as directed by the farmer. The Agriculture Drone has a hexagonal structure controlled using BLDC motors and Electronic Speed Controllers (ESCs). For flight control, Pixhawk 2.4.6 is used. It is equipped with a GPS module that can track the location of the drone and plan its mission. The drone operates on autopilot and requires no manual control for flight. Specific coordinates are given to the Drone so that it moves along the given coordinates for its flight using the software ‘Mission Planner.’ The designed drone has a removable tank for the storage of pesticides, which is placed under the landing gear. The tank has a spraying system that operates on the instructions of the farmer, which are given to the drone using a Radio transmitter.

Sustainable construction materials for resource efficiency and environmental effect have grown in popularity .Coconut shells, a waste product of the coconut industry, are plentiful in tropical climates. They are lightweight and permeable, making them an attractive alternative to coarse aggregates. Coconut shells can reduce trash disposal and gravel and sand use by adding them to concrete mixtures. Coconut shell aggregates improve concrete’s mechanical strength and durability, although at a lesser rate than conventional aggregates. Coconut shell replacement depends on particle size, surface properties, and curing conditions. Coconut shells with concrete improve thermal insulation, density, and acoustics. In this investigation compressive and flexural strengths of Grade M20 has been studied by replacing natural coarse aggregates with coconut shells at 0%, 10%, 20% and 30% by weight at curing intervals of 7,14 and 28 days. Cubes and beams were casted and then tested and the tests revealed that coconut shells can be used upto 10% in replacement of natural aggregates imparting a strength almost equivalent to conventional concrete.

Natural language processing (NLP) is a sustainable subfield of Artificial Intelligence that focuses on the interaction between computers and humans through natural language. NLP algorithms enable computers to comprehensively understand, interpret, and generate human language, thus facilitating the sustainable analysis and comprehension of vast amounts of textual data. Within the context of sustainable style change detection, NLP algorithms play a pivotal role in analyzing multi-author documents and identifying the points at which authors transition. This sustainable step is critical in authorship recognition as it furnishes a more precise comprehension of which sections were authored by different individuals. A multi-author document’s writing style can evolve over time, and this sustainability can prove invaluable in fields such as forensics, journalism, and literary studies, among others.The sustainable goal of this project is to investigate various NLP methods for sustainable style change detection. By scrutinizing datasets and juxtaposing them with advanced methodologies in the existing literature, the effectiveness of these strategies will be ascertained. The overarching aim of our study is to foster the progress of both the field of NLP research and its sustainable practical applications.

Utility distribution networks, crucial commercial operations, and critical industrial loads can suffer considerable financial losses as a result of a variety of service interruptions and outages. In developing countries like India, where alterations in power frequency and numerous other factors affecting power quality are a worry, it is crucial to take appropriate action to make power networks sustainable. To control and reduce voltage disturbances, a variety of techniques are available. For their benefits, including suitable output waveforms, inverters with multilevel outputs, such as multilevel D-STATCOMs, are frequently utilized in the power system and industry (voltage and current). Multilevel D-STATCOM control can be accomplished with several controllers. A closed loop controller is one of the controllers that use a feedback system to automatically control a system that ensures a desirable state or accepted value. Among the improvements are voltage sags and swells. The performance of the suggested controller is explained by contrasting it with both multilevel D-STATCOM and traditional PWM controls. In addition to its simplicity, robustness, and flexibility, the proposed method allows for all defects to be compensated.

Raising awareness through Virtual Experiencing (RAVE) and a Cross-Cultural Perspective on Raising Awareness through Virtual Experiencing (C-RAVE) approaches are used in this article to promote awareness of concerns relating to linguistic stereotyping. Virtual Reality (VR) technology has completely changed several facets of modern life, including instruction, training and entertainment. We give a summary of the techniques employed to increase awareness of how stereotypes might distort our vision. The patterns of the answers provided by the participants demonstrate that the reported gender of the speaker in addition to the accent (native vs. non-native), has an impact on the respondents' assessments of performance. Additionally, we were able to show that the discussions and ideas produced by these response patterns led to a rise in self-awareness of language and stereotyping-related problems. The paper gives a general description of RAVE and examines how it may improve education, create empathy and foster good social change. Focus on a critique of our methodologies and place our work within a larger debate of strategies and efforts for how educational institutions might actively contribute to combating (language) discrimination and bias in many ways. The relevance of Raising Awareness by Virtual Reality and Cross-Cultural Raising of Awareness by Virtual Reality in fostering inclusion and understanding in a society that is becoming more sustainable globally connected is highlighted in the article’s conclusion.

One of the most common causes of death is auto accidents. The worst thing that may happen to a road user is a traffic accident, despite the fact that they happen regularly. The worst part is that we fail to learn from our on-the-road errors. Most people who use roads regularly are extremely familiar with the fundamental guidelines and safety procedures that should be followed, but it is only their own negligence that results in accidents and wrecks. Accidents and crashes are primarily caused by human error. Here are some examples of normal human actions that result in accidents. 1. Driving too fast; 2. Driving while intoxicated; 3. Distracting the driver; 4. Running red lights; 5. Avoid utilizing safety equipment, such as seatbelts and helmets; 6. Driving erratically and overtaking improperly in order to save lives in a traffic collision, we’re going to construct an Arduino-based car accident alert system that combines GPS, GSM, and an accelerometer. If the accelerometer detects an abrupt shift in the vehicle’s axis, the GSM module alerts you and communicates the location of the accident to your cell phone. The GPS module’s latitude and longitude are utilized to pinpoint the accident’s location, which is provided as a Google Map link. The message also contains the vehicle’s speed in knots.

To achieve enhanced flux dissipation, microchannels heat sink are being effectively implemented in various engineering processes. Here, a numerical analysis is to be carried out on an open stepped micro pin fin heat sink (MPFHS) with different step size. The stepped pin fin heat sink (PFHS) having varied fin height in an array of two fins having inline arrangement. For the simulation purpose, a single-phase water was used as working fluid with variable thermophysical properties. The present configuration has operated for Reynolds number =100-500, heat flux of 500 kW/m2. The step variation of 100 µm, 200 µm and 300 µm has been considered. It was observed that with increase in step size, the heat transfer augmentation also increases. However, at higher Reynold number, the present studies does not provide effective results in terms of sustainability.

Military, law enforcement, surveillance, leisure, scientific, and research have benefited from drones. Recent decades have seen considerable advances in aerial robot structure, working method, flying features, and navigation control, notably small UAVs and drones. Their use in civilized places needs regulation. Early covid products delivery and sanitization involved drones. This thorough analysis of UAV applications in numerous domains from respected journals and scientific reports during the past decade. Summary of UAV-based sanitization research inputs. This review helps inexperienced researchers evaluate studies. This concise review of materialistic and sustainable drone sanitization literature is useful for novice researchers and practitioners.

The sustainable exploitation of natural stone resources poses a multifaceted dilemma that lies at the confluence of environmental protection and the preservation of cultural heritage. This study explores the complex interplay between the exploitation and use of natural stone resources, the consequent environmental ramifications, and the necessity of preserving cultural legacy for posterity. The procurement of natural stone resources, although being indispensable for the purposes of building, architecture, and artistic endeavours, sometimes gives rise to substantial ecological ramifications. Quarrying activities have been found to result in a range of detrimental consequences, including deforestation, soil erosion, water pollution, and habitat destruction. The intricate equilibrium between the preservation of natural resources and their utilisation necessitates the implementation of inventive approaches to minimise ecological harm and save cultural heritage. In order to effectively tackle these difficulties, it is imperative to adopt a holistic strategy. The use of sustainable quarrying practises, which encompass waste minimization, reclamation of abandoned quarries, and the utilisation of new technology for resource extraction, has the potential to mitigate ecological damage. The use of circular economy concepts has the potential to significantly improve the utilisation of stone resources in a more effective manner. The preservation of cultural heritage necessitates thorough documentation, continuous monitoring, and proper care, as well as the use of protective coatings and materials that effectively minimise degradation while preserving the aesthetic and historical significance. This study argues for the cohabitation of natural stone extraction with cultural heritage preservation by examining the intersection of environmental issues and cultural relevance.

Sheet metal forming processes are extremely important in the production of many different items. However, the issue of plastic instability, which frequently results in damaged goods, still exists in this industry. To solve this problem during production, it is crucial to take into account a number of factors, limiting diagram of forming. Present case, the Aluminum Alloy (AA2014) has been used to examine its formability at various temperatures (423,523 and 623K) and at strain rates (0.1 mm/s). Stretch forming was used to acquire the study’s findings, and the Nakajima test was used. The findings were evaluated using fractography investigations carried out with SEM. The outcomes demonstrated that as the temperature rose, the material’s limiting stresses became more favorable. Utilizing LS-dyna software, the simulations were carried out. The experimental findings are within the acceptability limit according to this study.

Clickbait is a significant problem on online media platforms. It misleads users and manipulates their engagement. A user who clicks on a clickbait link may be taken to a website full of ads, or that requires them to pay for something. The goal of this project is to create a system that can recognize clickbait posts so that user can access only to sustainable content. The system will analyze data using natural language processing (NLP) and machine learning techniques. NLP pre-processing techniques, such as tokenization, lemmatization, and stemming, will be utilized to extract essential elements from the headlines. These features will subsequently be used to train a machine learning model, specifically a supervised classifier, to distinguish between clickbait and non-clickbait news headlines. The project will explore a range of algorithms and techniques, including popular text representation models such as TF-IDF or word embeddings, as well as classifier models like logistic regression or random forests. The model will be evaluated using a variety of metrics, such as Accuracy, Precision, Recall, and F1 score. By making it easier for users to identify clickbait, the system can help to reduce the amount of time and money wasted on this type of content.

A heat pipe is a form of heat exchanger that is used to transmit heat from one end to another end. By incorporating an evaporation-condensation system cycle, a Tapered heat pipe can transport heat by capillary action. Heat pipe is comprised of three segments: Adiabatic, Evaporator, and Condenser. Condenser section (D) diameter is bigger than evaporator section (d) diameter in a tapered heat pipe design, allowing for an increase in vapor volume. The investigation deals with the design and CFD analysis of Tapered heat pipe will be performed. From the existing experimental data, the numerical analysis on tapered heat pipe is performed. In this numerical analysis the different D/d ratios are considered i.e., 1,2,3 and 4. Heat input values considered are 20 Watt and 50 Watt for all the D/d ratios. On investigating the tapered heat pipe for different D/d ratios we observed approximately 12% variation between existing experimental results and numerical results. A large variation in heat transfer coefficient in higher D/d ratios at higher temperatures are observed. At lower temperatures the variation of heat transfer coefficient along the D/d ratios is neglectable. These higher heat transfer coefficients of the tapered heat pipe are best suitable for cooling electrical components such as CPUs, circuit boards and transistors. In the present world of electric vehicles, the tapered heat pipe can also be used battery thermal management systems.

Water is one of the most essential elements of life. The water shortage is becoming a lurid issue in many regions, with over a billion people without passable water for drinking purposes. The leachate from landfill sites is a major problem and poses a threat to aquatic ecosystems and public health. To overcome this situation, either to remove contaminants or to reduce the amount of contamination, constructed wetlands using phytoremediation can be considered the best solution. This green low-cost technology uses plants to remove heavy metals from soil and water. The objective of this report is to study the removal of specific heavy metals such as Zinc (Zn), Nickel (Ni), Chromium (Cr), Cadmium (Cd), Iron (Fe) and Lead (Pb) from landfill leachate by using two laboratory scaled wetlands. These wetlands were filled with soil and planted with Typha Latifolia. One system was operated without recirculation and the other with effluent recirculation with an interval of one day. The influent and effluent physicochemical parameters were analyzed after 30 days and the concentrations of the heavy metals were observed. The wide variation is seen in the case of Nickel, Lead, Chromium, Cadmium, Zinc and Iron. The percentage of removal with recirculation and without recirculation is 100% for Cadmium and Iron, in the case of Nickel, Lead, Chromium and Zinc the percentage difference between recirculation and without recirculation was found to be 1.6, 2.4, 0, 0. Since the removal efficiency for Cadmium and Iron is predominant this study indicates that this technology gives good removal of heavy metals and has a scope for its effective analysis since it has low working and conservation costs; it is comparatively a step toward a sustainable economy.

In today’s world, a large number of videos are uploaded in everyday, which contains information about something. The major challenge is to find the right video and understand the correct content, because there are lot of videos available some videos will contain useless content and even though the perfect content available that content should be required to us. If we not found right one it wastes your full effort and full time to extract the correct usefull information. We propose an innovation idea which uses NLP processing for text extraction and BERT Summarization for Text Summarization. This provides a video main content in text description and abstractive summary, enabling users to discriminate between relevant and irrelevant information according to their needs. Furthermore, our experiments show that the joint model can attain good results with informative, concise, and readable multi-line video description and summary in a human evaluation.