Volume 12 | Issue 6

 Abstract

Women education has always been traditionally ignored or not given enough importance due to undervaluation of their contribution in family income especially of the natal family. Therefore, parents are reluctant to invest much in daughter's education. However, parental attitude towards their education has changed as societal outlook and labour market dynamics have changed over time. This paper tries to shed lights on the progress of women education since independence. The study reveals that there had been significant positive change in women participation in school education as well as higher education though there is gap in the progression from lower stages of education to higher levels. Besides, in higher education though their participation has increased largely but it is more prominent in general degree courses rather than professional degrees. Faculty wise distribution reveals that women are still far behind men in terms of their participation in professional education.

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Women's education, gross enrolment ratio, higher education, faculty wise distribution

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Cyber environments have been prone to unethical activity in the past few years. Social media platforms are becoming more and more prone to the identification of hate speech (HS) in modern culture. For online platforms to eliminate hate speech content in real-time they need powerful hate speech identification algorithms. A range of techniques exists to detect HS, including ML, Dictionary, DL, and so forth. The purpose of this study is to demonstrate an extensive understanding of DL and ML classification techniques, with their advantages and applications.

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Hate Speech (HS), HS Techniques: Machine learning (ML) and Deep Learning (DL), Comparison of ML and DL, Advantages, and Application of Classification Techniques.

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The integration of Artificial Intelligence (AI) in addressing climate change presents significant opportunities for tackling this global challenge. This review examines the use of AI in climate modeling, optimizing renewable energy, reducing carbon footprints, and environmental monitoring. It emphasizes AI's role in improving prediction accuracy, optimizing energy systems, reducing emissions, and enhancing monitoring capabilities. Despite its potential, AI's contribution to climate mitigation faces obstacles such as data gaps, high computational costs, and the need for interdisciplinary collaboration. This analysis underscores the importance of improving data quality, developing energy-efficient AI algorithms, and fostering interdisciplinary connections to fully leverage AI's potential for a sustainable future. Strategic decision-making and evidence-based governance are crucial for maximizing the benefits of AI while minimizing its environmental impact..

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 Keywords

Acoustic Sensors, Climate Change, Predictive Maintenance, Energy Consumption, Wildlife Monitoring, Deep Learning (DL), Machine Learning (ML), Data Availability, Smart Grid Management, Environmental Monitoring, Reinforcement Learning (RL), Renewable EnergyOptimization, Biodiversity Monitoring, Computational Resources, Artificial Intelligence (AI), Earth System Models, Supply Chain Optimization, Carbon Footprint Reduction, Climate Modelling, Computer Vision, Interdisciplinary Collaboration, Data

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Purpose - The purpose of this study is to empirically study the relationship between financial services and economic growth, and contribute to the already available literature on the relationship of financial services or sectors to economic growth Design/methodology/approach - The study used the Ordinary least square regression approach. The sample covered yearly time-series data from 1990 to 2022, i.e. 32 years. Findings - The results suggest that financial services related to economic growth were as Liquid liability as % of GDP and the commercial bank branch as per 100,000 positively correlated to the economic growth and investment and saving and capital formation negatively correlated to economic growth, given the financial liberation and reforms the country is currently enjoying, the country has not fully brought the desired positive effects on economic growth.

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 Keywords

Financial service, Economic growth, OLS regression, financial Liberalisation

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In India energy demands are expected to be more than double by 2030, and there is a pressing need to develop ways to conserve energy for future generations. Thus energy consumption can be reduced drastically by using energy efficient appliances. In India, the Union Ministry of power's research pointed out that about 20-25% of the total electricity utilized in government buildings in India is wasted due to unproductive design, resulting in an annual energy related financial loss of about Rs 1.5 billion. Conventional Heating Ventilation and Air Conditioning systems (HVAC) consume approximately 50% of the building energy. This type of air conditioning is therefore neither eco-friendly or sustainable. Selection of proper air conditioning system for buildings can not only help the country to save electrical energy but also reduce green house emissions. As renewable energies become a growing part of the energy, the focus is being put on increased performance and efficiency of proven sources such as horizontal axis air coolers. Generally air coolers are predominantly horizontal-axis, three-bladed with a fixed blade design. The domestic air coolers, which are cost effective, play a positive role in providing human comfort during hot weather. However the performance is dissatisfactory in the high humid regions. This project paves a way to investigate the performance of air cooler integrated by eliminating the problem of rise in humidity that usually encountered in the conventional air cooler. The objective of the present invention is to provide cooled air to maintain the room temperature according to the requirement. This paper presents a simplified analysis model for Cooling Effect of 360 degree Air Cooler for Vertical Axis to make computation tractable with better performance and efficiency by varying speed, number of blades and energy utilization and comparing suitable for cooling effect over a site-specific air cooling distribution.

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Energy consumption, cooling effect, vertical axis

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This research paper provides a thorough examination of the evolving landscape of cyber security threats and the corresponding strategies employed to mitigate them. In an era where technology plays an integral role in everyday life, the importance of safeguarding digital assets cannot be overstated. The paper explores various categories of cyber threats, including malware, data breaches, and social engineering attacks, while also discussing emerging threats such as AI-driven cyberattacks and the challenges posed by the Internet of Things (IoT). Furthermore, it delves into the multifaceted approaches employed by organizations and individuals to defend against these threats, including encryption, intrusion detection systems, and user awareness training. By shedding light on the latest developments in the field, this paper serves as a valuable resource for professionals and researchers seeking to stay ahead in the ongoing battle for cyber security.

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cybersecurity, threats, robotics, computer network, firewall, malware, cybercrime

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Welding is a permanent joining process both by using gas torch or electricity to generate heat and also by using filler materials. Similar materials or dissimilar materials both can be joined by implementing welding process. Pressure can be used instead of filler materials to get the permanent joint. For fabricating various engineering components Welding has been considered as one of the best process in the recent years. Various applications include constructions, automotive industries, ship building, aerospace, etc. Gas Tungsten Arc Welding (GTAW) is one of the majorly applied welding processes. There are different welding factors which determine the soundness of weld and investigate the weldability of a metal. Weldability is defined as the easiness with which two or more similar or dissimilar metals can be joined without any problem. In GTAW, the Heat Input and the Gas Flow Rate are two major factors during the welding process. They have an influence on Weld Bead Geometry. One of the important characteristics of welding is consider as weld beads. Metals weldability has been determined by reinforcement height, width if the weld beads, and depth of penetration. In the present research work the Tungsten Gas Arc Welding (GTAW) was carried on AA6063 aluminium alloy. of Response Surface Methodology (RSM) has been implemented to design the experiment that too CCD (Central Composite Design). Gas Flow Rate and Heat Input are the two factors and three level has been considered to create DOE. Bead geometry parameters were studied for different combinations of the mentioned factors. The influence of each factor on the bead geometry was analysed using ANOVA. It was observed that the maximum depth of penetration was obtained at heat input values of 0.36-0.4 kJ/mm and gas flow rate of 15.5 l/min. Minimum bead width is recommended and this was obtained at heat input of 0.45-0.48 kJ/mm and gas flow rate of 15-16 l/min. Nominal positive reinforced height is acceptable and this is obtained through the entire range of heat input and gas flow rate of 10.5-13.5 l/min.

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Weldability, GTAW, Bead Geometry, Response Surface Methodology, ANOVA

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Nearest Neighbour Analysis, also known as K-nearest neighbour (KNN) and neighbourhood component analysis (NCA), is a method that stores training samples in an n-dimensional pattern space and calculates the distance between samples using a distance metric formula. An example of the search for order in settlement or other patterns in the landscape is the use of a technique known as nearest neighbour analysis. This attempts to measure the distributions according to whether they are clustered, random or regular. Here, settlement distribution may be expected to be regular, rather than the random or scattered pattern.

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Clustered, Random, Hexagonal, Concentration, Dispersed, High concentration.

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This paper introduces a Chat-bot Assisted Multilingual Platform for Re-use, Re-Cycle, Re-Sale, Disposal of Industrial Material, and Electronics," represents a pivotal intersection of technology and environmental responsibility. In the past, waste management posed challenges, leaving consumers unaware of proper disposal methods. The digital age, chatbots emerged as intelligent conversational agents, bridging the gap between users and information on industrial material and electronics. Originally designed for customer support, chatbots evolved into sophisticated virtual assistants, automating tasks. In our project, chatbots serve as a linchpin, creating an efficient, user-friendly platform for re-use, recycling, sale, and disposal. The initiative addresses the multilingual aspect, seamlessly integrating English, Hindi, and Kannada to ensure inclusivity and accessibility. The project classifies industrial materials, distinguishing plastics for informed decision-making. In electronics, it emphasizes reuse and recycling, diverting devices from landfills. In essence, it stands as a beacon for technology-driven environmental responsibility. The multilingual interface fosters familiarity, transcending linguistic barriers.

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This paper introduces a Chat-bot Assisted Multilingual Platform for Re-use, Re-Cycle, Re-Sale, Disposal of Industrial Material, and Electronics," represents a pivotal intersection of technology and environmental responsibility. In the past, waste management posed challenges, leaving consumers unaware of proper disposal methods. The digital age, chatbots emerged as intelligent conversational agents, bridging the gap between users and information on industrial material and electronics. Or

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India's legal framework is witnessing a transformative shift with the introduction of the Bharatiya Nyaya Sanhita (BNS) Act, 2023. This new legislation aims to replace the Indian Penal Code (IPC) of 1860, bringing about significant changes to modernize the criminal justice system. Here, we delve into the key aspects, innovations, and implications of the BNS.

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BNS, The Bharatiya Nyaya Sanhita

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Due to their effectiveness and eco-friendliness, electric golf carts are growing in popularity on golf courses. With the use of a literature review and data analysis, this research paper intends to present a cost report and business report on electric golf carts. The study examines electric golf cart pricing patterns and how they affect the golf cart market. According to the study's findings, electric golf carts are more cost- and environmentally-friendly than gas-powered golf carts.

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Electric Vehicles, Electric Golf Cart, Business model of electric Golf Cart & Analysis, Sector wise Analysis.

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This review paper presents a comparative analysis of 16-bit and 32-bit Reduced Instruction Set Computing (RISC) pipelined processors, with a focus on their design and implementation using Verilog Hardware Description Language (HDL). The study explores key architectural differences, performance metrics, and resource utilization associated with both processor types. By delving into the pipeline stages, instruction sets, and data paths, the review highlights the trade-offs between the two architectures in terms of complexity, speed, power consumption, and scalability. Detailed simulations and synthesis results will be analyzed to provide a comprehensive understanding of the advantages and limitations of each processor size. The findings aim to guide designers in selecting the appropriate processor configuration for specific applications, balancing the need for efficiency, cost, and performance. The paper concludes with insights into future trends in RISC processor design and potential areas for further research in the context of evolving computational demands and technological advancements.

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Keywords: RISC Architecture, Pipeline Stages, Verilog HDL, Performance Metrics, Resource Utilization

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Attendance tracking is a crucial aspect of daily operations in educational institutions, organizations, and offices. Traditionally, this task involves manual methods like calling out names or roll numbers, which can be time-consuming and prone to errors. The aim of this project is to revolutionize attendance management by implementing a Face Recognition-based system, automating the process and enhancing efficiency. This innovative system, installed in classrooms or designated areas, utilizes facial recognition technology to identify and mark attendance. Students' information, including their names, roll numbers, class, section, and photographs, is stored and trained within the system. OpenCV is employed to extract facial images for training purposes .The system operates by capturing images of individuals approaching the device before the start of the class. These images are then processed through several stages: facial detection using a Haar cascade classifier, facial recognition utilizing the LBPH (Local Binary Pattern Histogram) Algorithm, comparison of histogram data with the established dataset, and automatic attendance marking. An Excel sheet is generated and updated regularly with attendance information, ensuring accurate record-keeping. Overall, this project offers a modernized approach to attendance management, leveraging advanced technology to streamline processes and improve time management in educational and organizational settings.

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Face Recognition-based system, OpenCV, Haar cascade classifier, LBPH (Local Binary Pattern Histogram) Algorithm

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Amidst the dynamic and ever-changing business environment of today, entrepreneurs encounter a multitude of obstacles in streamlining their activities and attaining long-term expansion. Artificial intelligence (AI) integration has become a promising tool for improving efficiency, simplifying processes, and overcoming operational challenges in startup ecosystems. This paper examines the current use of artificial intelligence (AI) to improve the efficiency of startup operations. It discusses the importance of adopting AI, the main obstacles faced, and the rising trends in the startup industry. This paper explores the complex and diverse role of artificial intelligence (AI) in startup environments, using secondary data analysis. The paper highlights the potential of AI to revolutionize operations and enhance competitiveness by analyzing existing literature. Ethical AI practices are becoming increasingly important in the adoption of AI in startups. These policies prioritize transparency, justice, and responsibility in the decision-making processes driven by AI. Furthermore, it is crucial to make investments in AI-powered cybersecurity solutions in order to protect against ever-changing cyber threats and secure valuable data. In addition, the report emphasizes developing patterns such as the integration of artificial intelligence (AI) in edge computing. This integration provides startups with chances to analyze data in proximity to its origin, hence decreasing delays and facilitating instantaneous decision-making. Startups can improve their operational agility, responsiveness, and scalability by adopting these new trends and utilizing AI technologies.

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Artificial Intelligence, Startups, Operational Efficiency, Ethical AI, Cybersecurity, Emerging Trends.

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The growing ecological disaster caused by plastic waste is one of the most urgent concerns of our day. Plastic, a substance once praised for its long-lasting and adaptable nature, has now become a lasting and poisonous kind of garbage, polluting our environments and bodies of water. This initiative, dubbed "Conversion of Waste Plastic Bottles into 3D Printing Filament," presents a ground breaking solution to this issue by transforming discarded plastic into a lucrative asset for the expanding 3D printing sector. The advent of 3D printing technology has brought about a significant transformation in several industries, such as manufacturing and healthcare, by facilitating the fabrication of intricate objects with exceptional accuracy. Nevertheless, the filaments often used in 3D printing, which are referred to as materials, frequently originate from finite resources, hence intensifying the ecological impact. This research suggests an alternate method by creating 3D printing filaments from recycled plastic bottles, so converting a widespread environmental pollution into a valuable resource. Our approach consists of collecting discarded plastic bottles, mostly made of polyethylene terephthalate (PET), which is a commonly used polymer in packaging. The bottles undergo a thorough cleaning, shredding, and controlled heating process using modern nozzle technology. Further, the liquefied plastic is forced out via a small opening to form slender threads, which are further cooled and coiled onto spools to produce filaments for 3D printing. This procedure not only redirects plastic trash away from landfills but also reduces the need for the manufacturing of new plastic, so contributing to a circular economy. The study further investigates the characteristics and efficiency of reused filaments in 3D printing applications. Initial findings suggest that the recycled filaments show similar quality to filaments that are commercially accessible, thereby proving the viability of this method. Moreover, the experiment highlights the possibility of producing filaments locally, which may help decrease emissions from shipping and promote self-reliance in 3D printing materials. Ultimately, this idea represents a fundamental change in how we handle trash and produce materials, transforming the issue of plastic waste into a viable option for environmentally-friendly manufacturing. Through the conversion of discarded plastic bottles into 3D printing filaments, we reduce the negative environmental effects of plastic waste and support the development of sustainable manufacturing methods. This programme demonstrates human creativity in addressing ecological concerns and highlights the capacity of new technology to promote sustainable development. This project represents progress towards a future in which garbage is not considered a final product, but rather a valuable.

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Sustainability, Waste Recycling, Plastic Waste, Plastic Bottles, 3D Printing Filament

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Nowadays, different types of replacement of sand by plastic grains in concrete is getting important in researches. In order to better understand the behavior of concrete piles during curing, exposure to different climatic conditions, and potential deterioration, this study investigates the compressive strength of plastic grain concrete pile by use of embedded temperature sensors. After analysing characteristics of different plastic grain concrete (low density polyethylene, high density polyethylene and polypropylene), HDPE (high density polyethylene) is more sustainable with concrete mix. For this study compressive strength of plastic grain (high density polyethylene) pile is compared with M20 grade concrete pile. During the casting process, temperature sensors are first strategically inserted into concrete piles at top, centre and bottom as part of the research. The exothermic hydration response may be examined by the continuous temperature data recording that these sensors will provide during the curing process. From temperature data maturity and strength is calculated using Nurse- Saul (MNS) function.

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Concrete pile, Plastic grain, LDPE, HDPE, Polypropylene, Temperature sensor

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In pursuit of sustainable development, global economies have banded together. This stands in stark contrast to earlier approaches, in which governments actively sought to advance their economies. Several natural resources have been exhausted and ecological balances have been upset because of nation's competing for economic development. This effect manifests itself in various ways, one of which is the acceleration of global warming. A solution that would make the world a better place for generations to come is urgently required because this endangers human life as we know it. To guarantee that development occurs in a manner that preserves and passes on to future generations undamaged natural resources, the phrase "sustainable development" was coined. This paper attempts to understand and analyze the challenges that India faces in reaching its Sustainable Development Goals and presents solutions to overcome them.

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Sustainable Development Goals (SDG), Global Warming, Natural Resources

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Road traffic accidents are increasing rapidly in India with the increase in traffic density. An accident is the result of factors such as road defects, human errors, engineering defects of the vehicles, non-availability of pedestrian facilities, cyclist facilities, circumstantial factors such as weather conditions, visibility etc. Accidents cause death, disablement, damage to property and health, social suffering, and also general degradation of the environment. In this project study, Traffic accident analysis of selected stretch of Yavatmal district in Maharashtra state is carried out project study aims to calculate accident rate and frequency for a particular road stretch. Literature review is conducted the traffic agencies and public concentrates at the measures to reduce such accident severity in order to reduce the fatality rate. The location of high risk where crash tends to concentrate over the time are hazardous locations .The analysis of traffic signals and road safety devices present on the road using geodetic techniques. The road stretch chosen for purpose of our study is extending from Sharda chowk to Lohara square. This 5 kilometer road stretch is divided into segments of 1000 meter each, for the purpose of analysis . The calculations described in this project is based on recorded accidents and data about accidents. The information available for accidents studies is taken form local police stations in form of FIR, the data of last two years (2022-2024) is extracted form FIR records. The type of data extracted is like location of accidents and fatalities in the selected stretch. We have calculated accident rate and accident frequency by using methods. Monthly variation, hourly variation of accident rate on the road and vehicle. Road safety awareness should be raise among users to reduce accidents.

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Accident anaylsis, FIR

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Hullabaloo in the Guava Orchard emerges as an insightful reinterpretation of Jameson's enduring assertion that "all third world literature is national allegory." The novel exemplifies how localized literature from the Global South functions allegorically as global literature, dramatizing the impact of multinational capitalism on rural and semi-urban spaces. Desai introduces themes of capitalism, exploitation, and globalization through her characters' actions, rendering the narrative an allegory of the extensive modernization projects that swept the nation and their repercussions on rural India. This paper engages with the theories of David Damrosch, Franco Moretti, and Pascale Casanova to delineate features of World Literature, incorporating aspects of ecocriticism to interpret the novel and its events as a national allegory.

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World Literature, Allegory, Ecocriticism

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Creative Commons Attribution 4.0 and The Open Definition