Applied Science and Engineering Journal for Advanced Research
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Comprehensive Analysis of Recent developments of control strategies and Modular Multilevel Converter for HVDC
Get PDFThe growing need for Renewable Energy Sources (RESs) has made Wind Energy Conversion Systems (WECS)—that is, systems that use Modular Multilevel Converters (MMC) and Doubly Fed Induction Generators (DFIG)—essential components of modern power generation. Although these systems have advantages including enhanced grid integration and variable-speed operation, complex control techniques are required to realize their full potential. This requirement is acknowledged in the proposed study, which also presents proportional-integral (PI) and particle swarm optimization (PSO) controllers as essential components of an advanced control system. Optimizing WECS performance is the major goal, with a focus on achieving and sustaining a steady DC link voltage. In order to ensure overall system reliability and efficiency, DC link voltage stability is crucial, especially when using High-Voltage Direct Current (HVDC) technology to transmit electrical power across long distances. The MATLAB Simulink platform is employed to demonstrate the efficacy of the suggested work
Innovative Waste Management: Incorporating CETP Sludge in Concrete for Sustainable Construction
Get PDFIn response to growing concerns about environmental sustainability and waste management, the exploration of alternative construction materials has gained prominence. One such alternative is common effluent treatment plant (CETP) sludge, a by-product of industrial wastewater treatment that poses significant environmental challenges. This study aims to evaluate the feasibility of substituting conventional fine aggregate with CETP sludge in concrete mixtures, addressing waste disposal issues and enhancing the sustainability of concrete construction. The research investigates the physical, chemical, and mechanical properties of CETP sludge to determine its suitability as a partial replacement for fine aggregate. Concrete mixtures with varying percentages of CETP sludge (0%, 10%, 20%, 30%, 40%, 50%) will be prepared and evaluated for compressive strength, durability, and workability. The study examines the potential benefits and challenges of incorporating CETP sludge, including its environmental impact, cost-effectiveness, and regulatory compliance. Initial findings suggest that CETP sludge possesses properties that make it a promising candidate for partial fine aggregate replacement. Further investigation will focus on its effect on the fresh and hardened properties of concrete, determining the optimal replacement ratio for desired performance. Environmental assessments will also be conducted to gauge the overall sustainability of concrete mixtures containing CETP sludge. This study aims to provide a novel solution for the responsible disposal of CETP sludge and promote environmentally friendly alternatives in construction. The research will explore the specific mechanical and durability properties of concrete with 10% CETP sludge replacement, aiming to identify an optimal balance between environmental benefits and structural integrity. The outcomes will contribute valuable insights into sustainable construction practices, encourage waste utilization in a circular economy, and reduce the environmental footprint of concrete materials
Enhancing Energy Efficiency in Green Buildings through Artificial Intelligence
Get PDFArtificial Intelligence (AI) is poised to revolutionize the architectural design and energy management of green buildings, offering significant advancements in sustainability and efficiency. This paper explores the transformative impact of AI on improving energy efficiency and reducing carbon emissions in commercial buildings. By leveraging AI algorithms, architects can optimize building performance through advanced environmental analysis, automation of repetitive tasks, and real-time data-driven decision-making. AI facilitates precise energy consumption forecasting and integration of renewable energy sources, enhancing the overall sustainability of buildings. Our study demonstrates that AI can reduce energy consumption and CO2 emissions by approximately 8% and 19%, respectively, in typical mid-size office buildings by 2050 compared to conventional methods. Further, the combination of AI with energy efficiency policies and low-emission energy production is projected to yield reductions of up to 40% in energy consumption and 90% in CO2 emissions. This paper provides a systematic approach for quantifying AI\u27s benefits across various building types and climate zones, offering valuable insights for decision-makers in the construction industry
Lidar and Monocular Sensor Fusion Depth Estimation
Get PDFIn this project, we present a novel approach to depth perception using a monocular camera by incorporating information from both RGB and LiDAR modalities. Our primary objective is to investigate the performance and effectiveness of different techniques to generate accurate depth estimation. We first implemented the Swin Transformer-based depth estimation model and evaluated its performance on KITTI dataset containing RGB images and their corresponding ground truth depth maps. Next, we proposed an RGB-LiDAR fusion model. We performed necessary preprocessing steps on the dataset, such as resizing, normalization, and data augmentation, and trained both models with identical configurations for a fair comparison. Our results demonstrate that the proposed RGB- LiDAR fusion model achieves superior depth estimation performance compared to the original Swin Transformer based model. We evaluated the models on the test dataset using metrics such as mean absolute error (MAE) and root mean squared error (RMSE). The enhanced performance indicates the potential benefits of RGB-LiDAR fusion for monocular depth perception tasks. This study offers valuable insights into the strengths [1] and weaknesses of combining RGB and LiDAR inputs and lays the foundation for future research in monocular depth perception, aiming to further improve model architectures and training techniques
Big Data and Computer-Human Interaction for Real-Time Illness Diagnosis
Get PDFOne particularly significant technology for deterrence of many chronic diseases is the constant plus real time tracking system, which is made possible through IoT and human computer interaction. Big data streaming stays the enormous volume of data that wearable medical procedures with sensors, healthcare clouds as well as mobile applications constantly produce. The increased pace of data collecting makes it challenging to gather, process as well as analyses such massive data sets in actual time in order to respond quickly in an emergency situation and unearth the hidden value. To offer an effective and scalable solution, real-time large data stream processing is therefore significantly needed. This work suggests a novel architecture for a big data based real time health prestige prediction as well as analytics system to address this problem. The system focuses on using a disseminated ML model to analyze health data events that are streamed into Spark via Kafka topics. First, we replace Hadoop MapReduce with Spark to produce a parallel, distributed, scalable, and rapid decision tree algorithm, which develops constrained for the real time computation. Second, this model is utilized to stream data from various sources that deal with numerous diseases in order to forecast health status. It is used to forecast health status using streaming data commencing distributed sources that represent various disorders
A Software Engineering Approach on Developing a Real Time Radar Target Generator for Airborne Targets
Get PDFThis paper presents a novel method of a radar system testing in a simulated environment using an artificial Target Generator. This work follows the software engineering approach into implementing the radar software system. Waterfall software development life cycle model if adopted for the Target Generator radar system implementation. The radar system can measure any type of radar target parameters supplied by a Radar Controller and can also transmit any radar signals generated by the Radar Target Generator. This work is essential for radar-related software development, testing, production, and maintenance. If radar targets are to be tested using real flights, though it would produce accurate performance testing results, it would consume increased amounts of time and would be prohibitively costly and complex. Additionally, there is no guaranteed method of flying multiple flights with the same velocity, acceleration, direction, azimuth (angle), altitude, etc. The slight change in every flight affects the accuracy of the final testing results. Hence, virtual radar targets are generated in real time via a virtual flight-testing environment to allow radar systems to be tested with flexible parameters’ settings and high accuracy results. To accomplish this, aircraft dynamics, aircraft’s Radar Cross Section (RCS), and other environmental effects are adjusted and customized in the virtual radar system testing environment. Then, the system will be ready to simulate as many flights as needed. This proposed software proved to be a faster and a more cost-effective solution. It is also programmable in any object-oriented programming language. In addition, due to the high modularity programming approach followed, this implementation is highly scalable and upgradable to any advanced deployment environment, such as governmental platforms
Study on Effect of Curing for Red Soil Based Geopolymer Bricks
Get PDFThe main problem facing the world today is pollution. In the construction industry, especially during the production of Portland cement, pollutants are emitted which lead to environmental pollution. in the present study, to make the geopolymer bricks, the ordinary Portland cement is fully replaced with fly ash and the fine aggregate is replaced with stone dust and alkaline liquids are used for the binding of materials. In this study an attempt is made to identify the optimum methodology of curing, by curing the red soil based geopolymer bricks with various curing temperature from 600c to 1200c with a variation of 100c for 24 hours in oven. From the optimum elevated temperature obtained, specimens are cured for 24 hours,48 hours and 72 hours in oven and also comparative study is carried out between elevation curing and ambient curing. The specimens are tested for physical and durable aspects
Blockchain based Federated Learning Models Methods and Applications
Get PDFThis paper systematically discusses the application and development of federated learning in data privacy protection and data value sharing. With the rapid development of global information technology, especially the explosive growth of data from Internet of Things devices, data security and privacy protection are facing unprecedented challenges. This paper first analyzes the growth trend of global data volume and its importance to next generation technologies such as artificial intelligence technologies such as deep learning. Second, the paper provides an in-depth look at the impact of current data privacy regulations on data flows and value creation, particularly the EU\u27s GDPR and China\u27s Data Security and Personal Information Protection Law. Then, this paper introduces in detail federated learning, as a new distributed machine learning paradigm, which effectively solves the contradiction between existing data sharing and privacy protection by protecting individual data privacy and realizing global model collaborative construction. Finally, this paper discusses the combination of blockchain technology and federated learning, and proposes BeFL architecture as a new secure, decentralized and trusted federated learning system, which is expected to provide a comprehensive solution for large-scale data processing and value creation in multi-party scenarios. The research in this paper not only deepens the understanding of federation learning in theory, but also provides important reference and enlightenment for future research and application in related fields
AI-Enhanced Security for Large-Scale Kubernetes Clusters: Advanced Defense and Authentication for National Cloud Infrastructure
Get PDFThis paper presents an AI-enhanced security framework for large-scale Kubernetes clusters, addressing the critical need for advanced defense and authentication mechanisms in national cloud infrastructures. The proposed system combines machine learning models for threats, policy creation, and intelligent resource allocation to provide security across the environment. An experiment simulating a 1,000-node Kubernetes cluster was used to evaluate the framework\u27s performance over 30 days. The results showed a significant improvement over traditional security methods, including 99.97% threat detection accuracy, a false positive rate of 0.005%, and an 85% reduction in average response time to security threats. The framework exhibits excellent performance, maintaining consistent performance up to 10,000 nodes with only 7% degradation. Notably, the change resulted in a 27% improvement in overall stability throughout the trial. This research has a significant impact on the security of the country\u27s airspace, providing effective protection against threats, insider attacks, and ongoing threats. The study concludes by discussing limitations and future research directions, emphasizing the need for real-world deployment and research on possible AI architectures. Better for limited spaces
Essential Inspection of Kolhapur City\u27s RCC Building
Get PDFA structural audit is required for framed structures in order to determine the proper corrective actions for different types of structural flaws and shortcomings. so that it can continue to meet the requirements for appropriateness and longevity. A structural audit needs to be done on any kind of structure at least once every five years. Every three years, a structural audit should be completed for buildings that are more than fifteen years old. It appears that the primary causes of structural member deterioration are aging and corrosion. There are several reasons why structural elements corrode, such as wall cracks, moisture, slab leaks, and more. Therefore, the building\u27s appropriateness and strength can be strengthened by completing the following tasks: installing slabs to stop water damage