Volume 12 | Issue 5 |

 Abstract

Solar energy is one of the most important and fastest growing renewable energies. One of the main design goals of a PV system is to obtain the maximum output power from solar PV with minimum losses. To achieve this, various techniques for tracking the peak performance point of PV system are reported in several literatures. In this paper, the theoretical details for the development and implementation of a Maximum Power Point Tracking (MPPT) controller using an artificial neural network for a stand-alone photovoltaic system are carried out. A 350W solar PV array from MATLAB/Simulink is used. Real-time data about changing environmental conditions, such as changing irradiance and temperature, is used to train and test the neural network. Simulation results are presented under rapid changes in solar radiation and temperature along with changing load conditions, which confirms the effectiveness of the proposed method in terms of efficiency. Small to negligible oscillations around the maximum power point and easy implementation are the main advantages of the proposed MPPT control method.

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 Keywords

Maximum Power Point Tracking (MPPT), Solar photovoltaic (PV) system, Neural Network (NN).

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 Abstract

Smart sort is a project using artificial intelligence (AI) to revolutionize waste segregation. It integrates Edge Impulse Studio, a leading platform for edge AI development, to create an intelligent, real-time system that enhances recycling efforts and reduces landfill burden. The AI models classify waste types using advanced voice recognition and machine learning techniques. The system's real-time capabilities allow for immediate sorting, recycling operations, and minimizing contamination. The project aims to create a sustainable waste management system that promotes environmental awareness and responsibility.

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 Keywords

Artificial Intelligence .Audio Classification, Waste Management , Edge AI

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 Abstract

Abstract The main purpose of this study was to assess the status of women participation in educational leadership of government secondary schools in Dessie zuria woreda. Hence, to realize this purpose, secondary school teachers, principals, vice-principals, parent teacher association (PTA) and woeda education officers were used as the target population. In order to make manageable, the sample government secondary schools teachers were selected by simple random sampling technique, and vice-principals, principals, wordea education officers and members of PTA were selected though comprehensive sampling techniques. This study had employed mixed research design particularly concurrent design. Both closed-ended and open-ended questionnaires, semi-structured interviews, and document analyses were used to collect data. The pilot-study was conducted to check the reliability of instruments. Frequency counts, percentages, mean and standard deviations were employed for quantitative data through closed-ended questionnaire and data through qualitative questionnaire were narrated. The finding showed that there is still low participation of women in secondary school leadership and attitude and challenges like misperception of stakeholders, women conflict of roll between their professional duty and family issues, women's poor self-image remain unchanged. Thus, it was concluded that there is a gap in creating awareness in implementation of policies, rules and regulations in people's attitude towards women's secondary schools leadership and competency of female principals is not included in this study. Therefore, it was recommended that the government, the woreda education office society and stakeholders should give great emphasis to work on women leadership; the school leaders should arrange continuous training for school community particularly for female teachers to alleviate the cultural and capacity related factors. The government should seriously look into issues of low women's participation in educational leadership institutions.

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 Keywords

Key words: Secondary Schools, Educational leadership, Participation, Leadership, Stakeholder, Feminist, Status, Woreda

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 Abstract

In computer science, object detection is an impor- tant role in the domain of computer vision. Object detection helps in locating and identifying objects present in an image or video sequences. It has many applications including traffic control systems, face detection algorithms and robotics among other applications. The high accuracy experienced here means most of its applications are so sensitive to errors hence required accompanying such high precision levels at all times. Object detection task is to recognize what things are present in an image. The process involves defining a bounding box around the object(s) and identifying the class of the object within that box using various algorithms like SVMs and Neural Networks which are common techniques used for this purpose by researchers working on projects related with machine learning or otherwise artificial intelligence fields when they use digital images/videos taken from a digital camera mounted on an object or recorded by CCTV lenses at the street corners for better strategic positioning of cameras.

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 Keywords

object detection, machine learning, deep learn- ing, YOLO, SSD, R-CNN, RNN, real-time object detection convolutional neural networks.

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Automated Conversation Analysis (ACA) has emerged as a critical area of research, fueled by advancements in artificial intelligence and natural language processing. This paper provides an overview of ACA, exploring its methodologies, applications across various domains, and the challenges it faces. Through a comprehensive review of literature and analysis, this paper aims to elucidate the current state of ACA, its potential implications, and avenues for future research. Automated Conversation Analysis (ACA) has emerged as a pivotal research domain, propelled by advancements in artificial intelligence (AI) and natural language processing (NLP). This paper presents a comprehensive overview of ACA, examining its methodologies, applications, and challenges. ACA involves the use of computational techniques to analyze conversational data, extracting valuable insights and patterns. Keywords: Automated Conversation Analysis, Natural Language Processing, Artificial Intelligence, Conversational Data, Insights, Patterns.

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Automated Conversation Analysis, Natural Language Processing, Artificial Intelligence, Conversational Data, Insights, Patterns, Customer Service

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 Abstract

ABSTRACT: University libraries play a crucial role in encouraging the academic mission of educational institutions by providing access to information resources, services, and spaces that pave the way for teaching, learning, and research. In today's robust and competitive higher education panorama, the potent management of university libraries is necessary for assuring the delivery of high-quality services that meet the unfolding needs of users. Total Quality Management (TQM) puts forward a strategic framework for strengthening the quality and productiveness of library operations through constant improvement, consumer focus, and employee empowerment. This paper analyses the significance of Total Quality Management in university libraries. It underscores the distinctive challenges confronted by academic libraries, including rapid technological advancements, changing user expectations, and budget constraints, and testifies how TQM principles can help address these issues. By accepting TQM principles such as customer focus, employee involvement, process improvement, and leadership dedication, university libraries can enhance their operations, boost user satisfaction, and expand the value they provide to the academic community. Through an inspection of TQM principles and their application in university library settings, this paper designs to provide intuitions into the benefits of implementing TQM practices. Case studies, examples, and theoretical insights will be used to demonstrate how TQM can authorise university libraries to acclimatize to changing atmosphere, enhance service quality, and nurture a culture of incessant improvement. Eventually, this paper stresses the consequence of Total Quality Management as a strategic approach for ensuring the everlasting success and sustainability of university libraries in a developing academic landscape.

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: University library, TQM strategies and applications, Efficient library services, TQM approach, User satisfaction, New library culture.

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 Abstract

In today's digital era, navigating through vast volumes of online information poses a formidable challenge. Extracting accurate insights from this abundance demands efficient tools like Textbyte. These tools play a pivotal role in condensing extensive content into concise summaries, empowering users to grasp complex data swiftly. While Wikipedia articles are renowned for their depth, abstraction techniques aid in distilling this information without diluting its essence. Abstracting content involves minimizing its volume while retaining its core meaning, a crucial aspect for streamlined research and information processing. Textbyte leverages advanced features, including YouTube video summarization, PDF chatbot integration, and file summarization. Users can input a video link for summarization, inquire about a provided PDF, or receive a summary of a text file. Notably, Textbyte employs cutting-edge NLP techniques, utilizing the LLM architecture and an extractive model, powered by SQL lite, to ensure accurate and efficient summarization.

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 Keywords

Text Summarization, chat with PDF, YouTube Video Summarization, NLP, LLM Architecture, Extractive model, Abstractive model

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 Abstract

This project delves into the financial intricacies of raw material management and obsolescence in automotive industries, with a specific focus on BMW Plant Chennai, A world renowned global leader shaping the automotive industry, within the broader context of thew automotive industry raw material obsolescence occurs when previously used materials become outdated or unused due to various advancements, regulatory changes and other factors. The core of the report is to explore how outdated and damaged materials can disrupt production, cause inventory written-offs and incur redesign expenses, ultimately affecting the plant's profitability. The automotive industry is particularly susceptible to this issue, as advancements in technology and regulations can render previously utilized materials unusable. The company's international market presence is a key focus of this abstract, leveraging a well-established global level production and a keen understanding of the prevailing market trends. The ultimate goal is to provide the plant with actionable insights to mitigate these financial repercussions by involving strategies like supplier diversification, design for adaptability, optimized stock management practices, by proactively addressing raw material obsolescence and material management.

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Financial impacts, Material management, Inventory Obsolescence, Automotive Industry

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Instant messaging applications have become ubiquitous tools for modern communication, facilitating real-time interaction and connection across the globe.(1)Among the multitude of options available, WhatsApp, Facebook Messenger, WeChat, and Telegram emerge as the foremost contenders in this digital arena. (2)This elongated abstract provides a comprehensive overview and analysis of these top four instant messaging applications, examining their features, user bases, security measures, business models, and societal impacts. WhatsApp, with its acquisition by Facebook, boasts an extensive user base exceeding 2 billion globally. Offering end-to-end encryption, multimedia sharing capabilities, and voice/video calls, WhatsApp provides a user-friendly interface for seamless communication. However, concerns regarding privacy and data sharing practices with its parent company persist.(3) Facebook Messenger, integrated with the Facebook social media platform, serves over 1.3 billion users worldwide. Its features include chatbots, group chats, voice/video calls, and an array of expressive stickers and emojis. Despite its popularity, Facebook Messenger faces scrutiny for its data collection practices, raising privacy concerns among users.(4) WeChat, developed by Tencent, has evolved into a comprehensive super app, encompassing messaging, social media, mobile payments, gaming, and more. With a staggering 1.2 billion monthly active users predominantly in China, WeChat dominates its home market and has expanded globally. However, its close ties to the Chinese government raise questions about privacy and censorship. Telegram distinguishes itself with a strong focus on privacy and security, offering features such as secret chats, self-destructing messages, and optional end-to-end encryption. (5)With over 500 million users, Telegram prioritizes user privacy and refrains from targeted advertising. Nonetheless, its commitment to privacy has drawn criticism for potentially facilitating illicit activities. A comparative analysis of these four instant messaging applications reveals their respective strengths and weaknesses. While WhatsApp and Facebook Messenger excel in user base and features, they face privacy concerns due to data sharing practices. WeChat's multi functionality and dominance in China contrast with concerns about government surveillance. Telegram's emphasis on privacy may hinder monetisation efforts and raise challenges in combating misuse.(6) Beyond their technical functionalities, instant messaging applications have profound societal impacts, influencing communication patterns, social interactions, and even political dynamics. These platforms facilitate global connections, empower businesses, and enable activism, but they also raise concerns about privacy, misinformation, and surveillance.

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 Keywords

Instant messaging applications,, WhatsApp Facebook ,Messenger ,WeChat ,Telegram, User privacy ,Data sharing practices ,End-to-end encryption ,,Societal impact Comparative analysis

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Public transport is the cheapest and most reliable transportation system in India, hence it has always been popular with the masses. Buses are an integral means of public transport which plays an vital role in transportation in India. The advancement in transport system has been increasing in day-to- day life as more and more people rely on public transport to go to work, school, hospitals, etc. Even though the public transport buses have been providing fairly satisfactory services, there is a need for smart and reliable system. The major problem in local buses are about issuing bus tickets, which often leads to conflict between the passenger and the conductor. Keeping this in mind we are developing an android application which will provide an efficient and smooth bus ticketing experience for both the user(passenger) and the service provider(conductor). The android application provides an interface for the bus ticketing system combined with the technology of QR Code for quick money transfer. QR Code or the Quick Response Code is the most dominant form of storing and exchanging information between devices. It's a type of matrix Bar Code and has more capacity than UPC Codes. Typically scanned and interpreted by camera enabled smartphone, but also can be interpreted or generated by any camera device implemented with QR decoding logic. The passengers can go cashless using this application, neither the conductor has to worry about returning change for the paid bus fare. By this application, we can minimize the usage of paper tickets which will also help in green India.

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 Keywords

Bus ticket, Application

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