Sri Shakthi SIET Journals
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Differential Configurational Entropy Measurement of Optical Dark Simlaritons
Get PDFThe nonlinear Schrödinger equation (NLSE) describes various types of physical systems such as water waves, nonlinear optics, plasma Physics. In optics, NLSE describes a wide range of non-linearity effects in fiber optics. The solution to the above equation might be examined in order to investigate these consequences. Differential configurational entropy (DCE) is used to analyze the dark similariton solution in this specific situation of NLSE with bright and dark similariton solutions. DCE provides us with the measure of information required to examine stability for various physical systems and to characterize a systems spatial profile using the Fourier transform. It is show that even for the same solitonic solution of the NLS equation, the variations in the spatial shape is induced by different choices of the relevant parameter α. The global minima of the DCE correspond to the saturation of the breadth of dark solitons. While dark similariton waves propagate through waveguides, such low entropic values result in minimum dispersion of momentum modes, and this should be taken into consideration while designing the waveguides
Enhancing the Usability, Visibility, and Responsiveness of an Airline Reservation System: A User-Centered Design Approach
Get PDFThis paper presents the idea, design, and prototype of a flight search and airline booking system based on the perspective of user-centered design. The system is first sketched roughly on paper in the form of a sketched plan and implemented through the proper system by connecting with the rapid API to develop a responsive web application. Booking travel tickets is a hassle and quite stressful because there is a chance that the webpages take time, and several decisions to make, hard to choose a discounted or less expensive flight, and the user will have to put in a lot of effort with many browser tabs may leave open. If a user is looking for the lowest travel options within a range of dates, they need to search a lot of websites looking for better options. As UX designers, it is our responsibility to do some user research and identify the problem areas, then we will recommend some design options based on the research findings. After that, we will create a wireframe and prototype before jumping into web design by collecting all the requirements and analyzing the problems. We will be focusing on UI controls such as location picker, date picker, color contrast, accessibility, and so on. In this paper, we present the design and development of a user-centered flight search and booking system for the airline industry. Our goal is to create a system that would meet the needs and preferences of a diverse set of users. This paper will summarize the design, development, and implementation of an airline reservation system. We have used bubble.io to design the overall system and MYSQL as the database management system for this webpage. Our objective is to upgrade the current website by improving the usability, visibility, and responsiveness of the functions that the user will experience while buying a flight ticket. We have generated and managed the design documentation and a perfect user-based online flight booking system
Enhancing M30 Grade Concrete: A Comparative Study of Hooked vs. Crimped Steel Fibers in Fly Ash Mixes
Get PDFThe realm of concrete offers vast opportunities for inventive applications, design, and construction methodologies, given its adaptability and cost-effectiveness. Its versatility in meeting diverse requirements has established it as a highly competitive building material. To address escalating structural demands and harsh environmental factors, new cementitious materials and concrete composites are continually being developed, followed by the need for enhanced durability and performance, as well as pressure to utilize industrial waste materials. The research explores the impact of incorporating fly ash and steel fiber into M30-grade concrete, alongside cement, coarse, and fine aggregate, through experimental methods, with the primary aim of determining optimal ingredient proportions for achieving desired strength. The study evaluates compressive strength variations with fly ash ranging from [10%] to [30%] while hooked and crimped steel fibers [ranging from 0% to 1.5%] in concrete, alongside cement, fine and coarse aggregate. Environmental considerations and the imperative to utilize industrial waste have significantly contributed to advancements in concrete technology and sustainability. Through meticulous analysis of results, meaningful inferences are made in relation to the strength attributes of fly ash fiber-reinforced concrete. Two sets of experiments were conducted, one altering fly ash content while maintaining fixed steel fiber content, and the other varying steel fiber content while keeping other parameters constant. The study aims to provide practical insights for engineers seeking cost-effective and sustainable building construction methods, adhering to specified norms (IS Code: 456-2000)
Image processing and Machine learning in Concrete Cube Crack detection
Get PDFConcrete cube testing plays a crucial role in various aspects of modern construction. The structural performance of concrete cubes under direct compressive stress can result in failure through concrete cube breakout. Failure modes related to concrete can be classified into two types: acceptable and non-acceptable, with further classification into various modes. However, most of the time 80% to 90% of the cubes are inaccurately selected, leading to lower strength and sustainability of concrete. Moreover, the excessive usage of cement required due to these inaccuracies contributes to global warming and increases costs. To address these issues, this research aims to develop an industry 4.0 solution for the construction and civil engineering fields. The proposed solution will be reliable, efficient, and based on image processing techniques. Convolutional Neural Networks (CNN) is used to detect and analyze cracks in concrete cubes. By examining the crack patterns, the damage area can be determined. By leveraging industry 4.0 technologies and advanced analysis techniques, this research aims to revolutionize the way concrete cube testing is conducted. The proposed solution will provide a reliable and efficient method for evaluating concrete cube quality, mitigating the negative impacts associated with inaccurate cube selection, and improving the performance and environmental sustainability of concrete in construction applications
Influence of High-Pressure Processing on Foxtail Millet Protein Concentrate (FMPC) and its Characteristics
Get PDFThe pre-treated Foxtail millet were collected with milk sample to obtain a FMPC by biochemical extraction process. The optimized milk ratio for the testing prepared sample was done with the ratio of the1:2 (Foxtail millet: Distilled water). The effect of HPP (High Pressure Processing) treatment for the millet milk was optimized at 550 MPa for 5 minutes to improve the yield of FMPC as well as improvement in Total Phenolic Content 1403.51 mg GAE/ g, dry weight for the prepared FMPC. The freeze-dried FMPC in dry powder was obtained with the optimized time period of 24 hours at -40℃. The prepared FPMC was characterized with FTIR analysis and compared with commercial protein powder. Further analysis of proximate studies revealed that the FMPC contains a higher amount of Protein content with ranging from 13-17% for the utility towards the commercial application as millet protein supplement in food products
Investigation on Sisal Fibre Concrete with Waste Foundry Sand as Partial Replacement of Fine Aggregate
Get PDFThe growing demand for sustainable building materials has led to exploring ecological alternatives to traditional concrete components. This study studies the mechanical properties and sustainability of reinforced concrete of sisal fibers incorporating waste foundry sand (WFS) in partial replacement of fine aggregates. Known for its natural strength, Sisal fibers increase the elasticity and flexible properties of concrete, while WFS from the metal industry provides an effective solution for waste disposal and resource preservation. In this study, class M30 concrete was prepared with different proportions of WFS (10%, 20%, 30%, 40%), replacing the fine aggregates and 1 % by volume of cement sisal fibers are added. Experimental tests were conducted to assess compression resistance, flexural strength, and tension resistance. The results show that inclusion of WFS improves the properties of concrete resistance to optimal exchange levels, while sisal fibers increase crack resistance and the ability to absorb energy. In addition to 20% of WFS replacements, there is a decline in productivity due to poor performance and increased vacuum content. This study concludes that the combination of Sisal and WFS offers a promising alternative for sustainable concrete production, contributing to environmental preservation and reducing construction costs
Utilisation of Convolutional Neural Networks (CNNS) in the Automated Diagnosis of Covid-19 from Chest X-Ray
Get PDFThe COVID-19 pandemic has especially exacerbated the issues faced by the healthcare field, regarding how to ensure rapid and correct infection diagnoses. This study evaluates how Convolutional Neural Networks (CNNs) can be used to automate the diagnosis of COVID-19 using chest X-ray images. The CNN model, as proposed, received training using a publicly available dataset and assessed according to important performance metrics that included accuracy, sensitivity, and specificity. The model accomplished an overall accuracy of 96%, along with a sensitivity of 89% and a specificity of 96%, which points to its strong performance in recognizing COVID-19 cases. The results reveal that diagnostics built on CNN can significantly enhance the use of traditional methods such as PCR tests, supplying quick, reliable, and scalable diagnostic capabilities. Through the addition of AI-enhanced diagnostic capabilities in healthcare processes, the stress on healthcare professionals is lessened by automating image interpretation and quickening patient management. The investigation points out the promise of CNN models in raising diagnostic precision and efficiency in emergent situations, particularly during pandemic outbreaks, and stresses the importance of future research on model generalizability and ethical factors
Applicable Nonthermal Preservation and Decontamination Technologies for Small to Medium-Scale Perishable Juice Processing
Get PDFNonthermal decontamination technologies are gaining prominence as an alternative to thermal sterilization, aiming to prevent the thermal degradation of juice quality. This paper reviews existing studies and the commercial viability of nonthermal techniques for processing and decontaminating perishable juices. Effective nonthermal methods for small to medium-scale commercial operations include sanitation and refrigeration, chemical preservatives, freezing, UV-C processing, microfiltration, and ultrasonic and ozone sterilization. The paper discusses microfiltration, UV-C processing, and ultrasonic designs studied for perishable juices in the author's laboratory. A significant challenge with nonthermal processes is their product-specific nature, necessitating further research to establish optimal process parameters. The advantages of these technologies include improved sensory and nutritional qualities and minimal or no use of preservatives. However, combined treatments are often necessary to meet microbial safety standards
Artificial Intelligence and Agricultural Biotechnology for Sustainable Farming Practices
Get PDFAgriculture is facing unprecedented challenges, including climate change, resource limitations, and the growing demand for sustainable practices. This article explores how the integration of biotechnology and artificial intelligence (AI) can address these issues. Biotechnology tools such as GMOs, CRISPR-Cas9, and synthetic biology enable the development of robust crops, enhanced pest resistance, and improved resource efficiency. AI complements these advancements through machine learning, predictive analytics, and robotics, facilitating better crop management, health monitoring, and yield prediction. The review highlights AI’s role in refining data analysis for genetic modifications and optimizing crop management strategies, showcasing the synergy between biotechnology and AI. Notable applications include the optimization of CRISPR technologies and the creation of disease-resistant crops. However, significant challenges remain, such as technical limitations, ethical concerns surrounding genetic modifications, and the economic impact on small-scale farmers. Addressing these challenges requires a comprehensive approach involving robust regulatory frameworks and stakeholder collaboration. Future directions include leveraging AI for precision breeding and integrating advancements in synthetic biology to enhance agricultural sustainability and productivity. Continued collaboration between biotechnology and AI will be essential to overcoming current limitations and achieving a sustainable future for agriculture
Design and Optimization of Piezoelectric Pressure Sensor with AlN as piezo electric material for High-Temperature Application using COMSOL 5.3
Get PDFDynamic pressure sensors in contrast to static pressure sensors measure pressure changes in liquids or gases generated due to a blast, a propulsion or an explosion, where the temperature is normally high which is above 700°C[1]. Piezoelectric pressure sensors with their inherent advantage of direct transduction capability are drawing attention for high-temperature applications. Lead Zirconate Titanate (PZT) and Zinc Oxide (ZnO) are popular ferroelectric materials for Piezoelectric sensor applications. Aluminum Nitride (AlN) is a suitable candidate for high-temperature applications with its high melting point of 2673 K, the piezoelectric property remaining stable even up to 1423K, the energy band gap of 6.2eV, piezoelectric coefficient d33 of 7pC/N and pressure handling capacity up to 10 MPa. In this study, COMSOL Multiphysics 5.3 was used to analyse the pressure sensing capability of AlN film by optimizing the crystal orientation and the dimension of AlN in addition to studying suitability of using at high temperature. Also a comparison is done on the high temperature performance of pressure sensor using Silicon and Silicon Carbide as diaphragm