bluuebunny/crossref_metadata_2025 huggingface dataset:
AI DRIVEN BLOOD CELL ANALYSIS FOR MALARIA AND BLOOD CANCER SCREENING
Authors:   Assistant Professor , Department of Computer Science and Engineering , Info Institute of Engineering., P Mrs..Gokila
Published: May 2024

Malaria and blood Cancer is one of the deadliest diseases cross the globe. This is caused by the bite of female Anopheles mosquito that transmits the Plasmodium parasites. Some current malaria detection techniques include manual microscopic examination and RDT. These approaches are vulnerable to human mistakes. Early detection of malaria can help in reducing the death rates across the globe.Deep Learning can emerge as a highly beneficial solution in the diagnosis of disease. This model gives a faster and cheaper method for detecting plasmodium parasites. It Was Designed to Identify Malaria Parasites and Cancerous Cell Presence in Blood Using Images of Blood Samples which got Tested with Giemsa-stain. Convolutional neural networks (CNNs) are then trained on these extracted features to accurately classify blood cell images into disease positive or disease-negative categories. The CNN detects malaria parasites in microscopic images by classifying them into parasitized and healthy cells, enabling the detection of malaria parasites. The proposed model consists of three convolutional layers and fully connected layers each. The neural network presented is a cascade of several convolutional layers having multiple filters present in layers, which yields the exceptionally good accuracy as per the available resources. The experiment results demonstrate a significant improvement in malaria parasite and blood cancer recognition. Compared to traditional manual microscopy, the proposed system is more accurate and faster. Finally, this study demonstrates the need to provide robust and efficient solutions by leveraging state-of-the-art technologies to combat malaria and blood cancer. Keywords : Deep Learning, CNN, Image analysis , InceptionresnetV2
Examining the Influence of Gratitude on Sleep Quality Among Young Adult Population: A Scientific Exploration
Authors:   AMITY INSTITUTE OF PSYCHOLOGY AND ALLIED SCIENCES  Amity University Uttar Pradesh, Noida, Thadani Kanishka
Published: May 2024

The study investigates the intricate relationship between gratitude and sleep quality within the young adult population, delving into the realms of positive psychology, diverse cultural perspectives, and the physiological underpinnings of these phenomena. The study also uncovers the cross-cultural relevance of gratitude in influencing sleep quality among young adults. The methodology employed encompasses a mixed-methods approach, incorporating quantitative surveys to measure gratitude levels and sleep quality. The sample comprises a diverse group of young adults, ensuring the study's applicability across various demographic backgrounds. The results demonstrate the cross-cultural significance of gratitude in promoting well-being by showing a strong positive connection between gratitude and sleep quality. These results underscore the importance of fostering gratitude as a means to enhance sleep quality among young adults, irrespective of cultural backgrounds.
Study of factors influencing women entrepreneurship in Kabul Afghanistan
Authors:   MBA, Department of HR, Lovely Professional University, Dixi Dr. Anuj
Published: May 2024

This research aims to dissect the intricate factors hindering women's entrepreneurship in Kabul, Afghanistan. By delving into these barriers, we seek to empower women through targeted support programs, therefore catalyzing economic growth and fostering innovation. Our study uncovers the profound impact of societal expectations and cultural norms on women's entrepreneurial endeavors. It illuminates the constraints imposed by limited mobility, the social stigma surrounding women in business, and entrenched gender roles dictating access to resources. These findings underscore the necessity of tailored interventions to dismantle systemic obstacles and cultivate a conducive environment for female entrepreneurship. By examining the unique challenges faced by women entrepreneurs in Kabul, this research offers original insights into the socio-cultural landscape of a post-conflict society. It contributes to a nuanced understanding of entrepreneurship dynamics, enriching scholarly discourse and informing policy initiatives aimed at promoting gender equality and economic development. Key Words: Women Entrepreneurs, Kabul, Afghanistan, Entrepreneurial Challenges, Gender Barriers
FRUIT DISEASE DETECTION USING COLOR AND TEXTURE ANALYSIS BY CNN
Authors:   Vignan’s Institute of Information Technology(A), Beside VSEZ, Duvvada, Vadlapudi Post,  Gajuwaka, Visakhapatnam-530049., Devi P Uma
Published: May 2024

Now-a-days as there is prohibitive demand for agricultural industry, effective growth and improved yield of fruit is necessary and important. For this purpose farmers need manual monitoring of fruits from harvest till its progress period. But manual monitoring will not give satisfactory result all the times and they always need satisfactory advice from expert. So it requires proposing an efficient smart farming technique which will help for better yield and growth with less human efforts. We introduce a technique which will diagnose and classify external disease within fruits. Whereas system that we have come up with, uses image processing techniques for implementation as image is easy way for conveying. In the proposed work, OpenCV library is applied for implementation, the images are catalogue and mapped to their respective disease categories on basis of four feature vectors colour, morphology, texture and structure of hole on the fruit. Convolutional Neural Network (CNN) concept is used for pattern matching and classification of diseases.. Keywords: CNN Algorithm ,OpenCV ,Image processing techniques
Anomaly Detection in Smart Grid Application
Authors:   Asst Professor, Dept. Of CSE, Sambhram Institute of Technology, Bengaluru-560097, V Anuradha
Published: May 2024

The smart grid, a modernized electrical grid integrating advanced communication and information technologies, enables bidirectional flow of electricity and information, offering numerous benefits such as enhanced reliability, efficiency, and sustainability. However, the complexity and scale of the smart grid introduce new challenges, including the need for effective anomaly detection to ensure its secure and reliable operation. This research paper presents a comprehensive review of state-of-the-art anomaly detection techniques in smart grid applications. We explore various methodologies, including statistical methods, machine learning algorithms, and hybrid approaches, highlighting their strengths and limitations. Furthermore, we discuss the importance of accurate data preprocessing and feature selection to enhance anomaly detection performance. Through a comparative analysis, we demonstrate the effectiveness of different techniques in detecting anomalies in smart grid datasets. Our findings provide valuable insights for researchers and practitioners in developing robust anomaly detection systems for smart grid applications, ultimately contributing to the advancement of smart grid technology.
Prediction of Diabetes Using Machine Learning Algorithms in Healthcare
Authors:   Department of ISE JNN College of Engineering,, S R Sharath Kumar
Published: May 2024

This study introduces a new approach to prognosticating the onset of detection of diabetes via using machine learning ways. By assaying a dataset containing different demographic, clinical, and life factors, the study identifies crucial predictors for assessing diabetes threat. Several ML algorithms, similar as logistic regression, KNN, Ada-boost, and support vector machine, are utilized and estimated for their prophetic performance. The results demonstrate that the ML- grounded models effectively identify individualities at high threat of developing diabetes. These models give precious decision making aids for healthcare interpreters, easing early intervention and substantiated operational strategies. Overall, this approach has the implicit to significantly reduce the burden of diabetes on public health systems. Keywords: : prognosticating, individualities, operational strategies, Public health systems.
INAPPROPRIATE CONTENT DETECTION IN IMAGE
Authors:   Department of Artificial Intelligence & Machine Learning.  Sri Shakthi Institute of Engineering and Technology, S Mrs. Hemalatha
Published: May 2024

The proliferation of social media platforms has led to a significant increase in the sharing of memes and other image-based content. However, some of these images may contain inappropriate or offensive text, which can be challenging to detect using traditional methods. Because the open-source existing solutions does not classify the text content in images. This project aims to develop a robust solution for detecting Not Safe for Work (NSFW) text content in images, with a particular focus on social media memes. The objectives of this project are to accurately extract text from images using optical character recognition (OCR) techniques, and to classify the extracted text as either NSFW or Safe for Work (SFW) using a fine-tuned natural language processing (NLP) model. The methodology employed in this project involves several key steps. First, the Keras OCR library is utilized to extract text from input images, as it has demonstrated superior performance compared to other OCR tools for social media images. Next, a preprocessing step is performed to align the extracted text in the correct sequence using coordinates, distance from the image origin, and the Pythagorean theorem. The pre-processed text is then passed to a fine-tuned BERT-BASE-UNCASED language model, which has been trained on a dataset of Reddit posts (NSFW and SFW) to classify the text as either NSFW or SFW. Key Words: OCR, Inappropriate, BERT, NSFW, SFW, Image, Text
Review Paper - Recruitment and Selection Process at HDFC Bank
Authors:   PG Student, ARMIET, Mumbai University,, chillala Ms Sunanda N
Published: May 2024

This research explores the complexities of the recruiting and selection process at HDFC Bank, a prominent financial organization in India. The main goal is to provide a thorough understanding of the techniques, processes, and difficulties associated with acquiring, evaluating, and selecting skilled individuals inside the bank. Data was collected using a mixed-methods approach that included qualitative and quantitative research approaches. The data was received from several sources, including HR professionals, existing workers, and relevant paperwork. The study emphasizes the significance of efficient recruiting and selection methods in preserving a competitive advantage in the banking industry. The analysis focuses on the congruence between HDFC Bank's recruiting tactics and its organizational goals, highlighting the significance of talent acquisition in propelling corporate performance and attaining long-term expansion. Moreover, the research investigates the use of technology and advanced approaches to make the recruiting process more efficient and improve the experience of candidates. The key results highlight the importance of cultural compatibility, alignment of talents, and inclusion of diversity in the selection process, demonstrating HDFC Bank's dedication to creating an inclusive work environment. In addition, the report highlights obstacles such as a shortage of skilled workers, growing competition, and changing market conditions, which compel the bank to constantly adjust and improve its recruiting methods. In summary, this study adds to the current understanding of recruiting and selection techniques in the banking industry. It provides valuable insights and suggestions for HR professionals and organizational leaders who want to improve their talent acquisition methods. The statement highlights the essential significance of recruiting and selection in influencing the achievement of an organization and promoting a culture of exceptional performance within HDFC Bank.
NON-CARCINOGENIC VCI SOLUTION FOR LONG TERM METAL PROTECTION
Authors:   HOD & Professor, Department of Mechanical Engineering, Vidyavardhaka College of engineering, Mysuru, Karnataka, India, Prakash G V Naveen
Published: May 2024

Corrosion is a dangerous and extremely costly problem. Because of it, buildings and bridges can collapse, oil pipelines break, chemical plants leak, and bathrooms flood. Corroded electrical contacts can cause fires and other problems, corroded medical implants may lead to blood poisoning, and air pollution has caused corrosion damage to work around the world. Corrosion threatens the safe disposal of radioactive waste that must be stored in containers for tens of thousands of years. When reduction and oxidation take place on different kinds of metal in contact with one another, the process is called galvanic corrosion. In electrolytic corrosion, which occurs most commonly in electronic equipment, water or other moisture becomes trapped between two electrical contacts that have an electrical voltage applied between them. The result is an unintended electrolytic cell. VCI is the generic term for “volatile corrosion inhibitor” a revolutionary technology that simplifies corrosion protection and is ideal for keeping enclosed void spaces (e.g., packages, equipment internals, or structural metal cavities) rust-free. Keywords: Corrosion; VCI; Rust.
SMART SANITARY NAPKINS VENDING MACHINE
Authors:   Student, Dept. of  ISE, East West Institute of Technology, Bengaluru, Kumar Mr. Hemanth
Published: May 2024

Our project, the Smart Sanitary Napkins vending machine, is an innovative solution that combines the functionalities of dispensing sanitary pads and medicines while incorporating advanced features for user convenience. Utilizing Arduino, LCD display, keypad, RFID technology, DC motor, and Node MCU, we've developed a robust system that enhances accessibility and usability. At its core, our vending machine boasts a user-friendly interface, featuring an LCD display and keypad for seamless interaction. Users can easily navigate through the menu to select and purchase either sanitary pads or medicines according to their specific needs. The integration of RFID technology ensures secure user authentication, granting access only to authorized individuals. The dispensing mechanism is driven by a precise DC motor, guaranteeing accurate and controlled distribution of sanitary pads and medicines. Additionally, we've incorporated a disposal unit to promote environmental sustainability by facilitating proper disposal of used sanitary pads. Keywords--- Arduino, LCD display, keypad, RFID technology, DC motor,
Learnings from Shri Adi Shankara’s Life: A Management Perspective
Authors:   CEO & ED, Sigma Research and Consulting, Founder, Sri Rama Seva Samiti, Varanasi., U V Dr Somayajulu
Published: May 2024

Religion, philosophy, science, and management cannot work in isolation in the long run. These need to be harmonized and synchronized for the success of a society. It is also needed to live, feel and practice a balanced and ideal life and is imperative for a successful and great leader. Shri Adi Shankara is one of the greatest philosophers the world has ever seen. He was not only a Tattva Jnani (man of wisdom), but also a great expert in managing worldly affairs. During the 8th century, a chaotic situation prevailed in the Hindu society of Bharata Desha (India) with its very existence in jeopardy and its values, culture, and traditions in peril, on the verge of vanishing. Shri Adi Shankara strode across the country debating with scholars and propounding his philosophy of Advaita (Non-duality) and unifying people of differing viewpoints. Without him, Hindu religion would not have been in subsistence. Keeping this in view, an attempt is made in this paper to discuss the management perspectives that emerge from the life, works, and teachings of Jagadguru Shri Adi Shankara Bhagavatpaada. It looks at his leadership qualities and the effort he made at integrating India into one unified whole. Keywords: Adi Shankara, Philosophy, Hinduism, Management Learnings
Smart School Application: Enhancing Educational Outcomes and Processes
Authors:   Anjuman College of Engineering and Technology, Nagpur, India.(RTMNU University), Nagani Akbar
Published: May 2024

As digital tools become more integral to education, smart school applications are gaining prominence due to their diverse functionalities, including e-libraries, attendance systems, leader boards, quizzes, event scheduling, real-time notifications, and more. This review delves into how these applications enhance administrative efficiency, foster better communication, increase student engagement, and improve learning outcomes, while also considering the implementation challenges and proposing strategies for successful integration. The paper highlights the necessity for educational institutions to carefully evaluate these technologies before adoption, focusing on how they can effectively enhance academic performance and streamline educational processes. Through a comprehensive exploration of these tools, it provides valuable insights and recommendations for schools contemplating the integration of advanced technological solutions into their educational framework. Key Words: edtech, degitalization, smartschools, performance, management
The Impact of AI on Job Roles, Workforce and Employment
Authors:   B.Tech student Computer Science& Engineering, kalinga university naya Raipur (C.G), raj, Harsh
Published: May 2024

rtificial Intelligence (AI) has become a transformative force in the modern workplace, reshaping job roles across various industries. This comprehensive review explores the multifaceted impact of AI on employment, delving into the opportunities it presents for innovation and efficiency, as well as the challenges it poses in terms of job displacement and skills evolution. Through an in-depth analysis of automation, augmentation, and the emergence of new job roles, this paper aims to provide insights into how individuals and organizations can navigate the evolving job landscape shaped by AI technologies.
Gear Train Optimization of High Speed Machinery by using CATIA and ANSYS
Authors:   Department of Mechanical Engineering, Avanthi Institute of Engineering & Technology, Makavarapalem 531113., Kumari Y.Jaya Santhoshi
Published: May 2024

This project aims to optimize gear trains for high-speed machinery using CATIA and ANSYS. Gear trains are crucial in various mechanical systems, especially in high-speed applications where efficiency and reliability are essential. The objective is to combine CATIA for designing and modelling gear trains with ANSYS for analysing their performance under high rotational speeds. Helical gear train use for Reverses Motion design as per requiment of power and motor speed. Same design check for maximium load by load on pinion taken as step of 13K, 15K, 20K, 25K and 30K Newtons are applied on helical gear and check the stress and other parameters material High speed steel. Dynamic analysis model also be carried for mode frequency Keywords: Gear trains, Finite element analysis, CATIA, ANSYS.
PESTI GUARD: FARMER-FRIENDLY PESTICIDE ROBOT
Authors:   department of EEE & Vidya Vikas institute of engineering and technology, P Sahana
Published: May 2024

Agriculture is the primary source of revenue for India's population, which accounts for nearly 60% of the country's total. Farmers work in their fields to cultivate various crops based on the environment and resources available. Farmers must use large quantities of pesticides to increase food production in order to meet such high food demand for such a large population. Traditional manual pesticide spraying operations is full of direct exposure to the pesticide liquid work environment, great harm to human body and when this pesticide may come into contact with the farmer during spraying, which may trigger skin cancer and asthma illnesses. Increased pesticide spraying can impact consumer health as it enters the food chain. The widespread use of pesticides in agriculture presents significant health risks to both farmers and consumers. The pesticide spraying robot is equipped with state-of-the-art sensors to record real-time temperature and humidity levels, providing crucial environmental data for optimized pesticide application. Farmers can remotely control the robot using a user-friendly interface, instructing it to perform specific spraying tasks while maintaining a safe distance from potentially hazardous chemicals. To address this challenge, this paper proposes a Pesticide Spraying Robot designed to minimize human contact during operation while prioritizing human health through advanced environmental monitoring and remote-control capabilities.
BLINDS EYE: Advancing Navigation for the Visually Impaired with Arduino Uno
Authors:   Assistant Professor, Ballari institute of technology and management, M Sreenivasa
Published: May 2024

Blinds Eye Advancing Navigation for the Visually Impaired with Arduino Uno. Navigating their surroundings independently, visually impaired individuals encounter challenges with traditional aids. This advanced blind navigation system, integrating an Arduino Uno for processing, a GPS module for real-time tracking, and a panic button for emergencies, presents a groundbreaking solution. Ultrasonic and IR sensors detect obstacles, issuing audio alerts and adjusting routes. An RF module aids in locating a misplaced smart stick. Overcoming limitations of existing solutions, the system's audio output provides crucial information, ensuring safer and more efficient independent travel for the visually impaired." Key Words: Arduino Uno, Blind navigation, Visually impaired, GPS module, Ultrasonic sensors, Infrared sensors, RF module, Assistive technology
TOTAL QUALITY MANEGMENT
Authors:   Alamuri Ratnamala Institute of Engineering and Technology, HAMARE Mr. RAVINDRA LALU
Published: May 2024

Title: Total Quality Management: A Test of the Effect of TQM on the Performance and Stakeholder Satisfaction Background and Problem Discussion: The performance of TQM Airlines and Non TQM airlines is measured comparing statistically three major performance indicator Customer satisfaction, Employee satisfaction and Operational effectiveness. To establish a link between TQM and performance and showing the need for the adoption of total quality culture in the local airline sector of the Nigeria aviation industry. Purpose: The purpose of this thesis is to highlight the benefit of TQM implementation in the Nigerian Airline industry by examining the basic principles of TQM in the airlines. The impact of TQM implementation of the three performance indicator will be assessed. Method: Quantitative and qualitative method. Primary data is collected from the airline companies by questionnaires and interview. Secondary data is gotten from articles, journals and online resources. Theory: The theory section looks at different concepts of quality as defined and viewed by various authors. Also the benefits and hindrances of TQM implementation were reviewed. Analysis: We have used a T-test hypothesis to measure the difference in means of TQM airline and Non-TQM airlines using the three performance indicator. Conclusion: The research findings confirmed the benefits that ensue from the implementation of TQM. It showed that TQM is a strategic tool industry can employ in the quest to remain competitive. It was also discovered that for the TQM to be properly implemented, everybody in the organization must be involved from the management to the employees and even the customers.
Seismic and Wind Resillence Study of a 15 Story High-Rise Building with Floating Columns in Seismic Zones II & V
Authors:   Miracle Educational Society Group of Institutions, Vizianagaram-535216, Rajeswari Palla
Published: May 2024

The use of floating columns in the construction of high-rise buildings, specifically in the context of G+15 structures in metropolitan cities, as per Indian standards. The structural design of a building is crucial for its durability, strength, stability, and lifespan. Floating columns play a significant role in transferring loads from the floors to the beams, affecting the overall stability of the building.Several factors impact the structural design, including bending moments, shear forces, torsion, and deflection. Due to the growing population in metropolitan areas, there is a need for high-rise buildings that can accommodate both commercial and residential spaces on a single platform. Commercial and residential floors have different load requirements. Therefore, floating columns are specifically used for residential floors to address these varying load demands. The structural analysis considers seismic and wind forces as per Indian standards (IS 1893-2016 for seismic analysis and IS 875-2015 for wind analysis) for different seismic zones (Zone- Ⅱ, Ⅲ, Ⅳ, and Ⅴ). The materials used in the construction include concrete with a grade of M40 and steel with a grade of Fe550. These material grades are commonly used in construction for their respective strength properties. The floor height for residential floors is 3 meters, while commercial floors have a height of 4 meters. This distinction in floor height is considered in the structural design. The design of high-rise buildings, especially in seismic-prone regions, requires a thorough understanding of structural engineering principles and adherence to local building codes and standards to ensure the safety and stability of the structure. The use of floating columns can be a part of a structural design strategy to address varying load requirements in different parts of the building.Safety is paramount in the design and construction of high-rise buildings, particularly in areas susceptible to seismic activity and strong winds.
SMART CONVEYOR BELT WITH PRODUCTION COUNT DISPLAY
Authors:   Faculty of Department Of Mechanical Engineering  Sudarshan Chavan B.M. Polytechnic Belati, Solapur., Gaikwad Rushikesh
Published: May 2024

Today's world is very competitive. Technology is an important part of this. The country has a lot of innovations and dominates the world. It is important to survive in technology. The country's economy can be impacted by trade. There should be production where there is work. Business needs technological development to get better products. It's important for businesses to have automation. It is used on the production line. The items can be sorted by height. The product must be placed on the conveyor belt. After checking the height of the product, the product with the correct height will be thrown into the product box, the product with the incorrect height will be left in the waste from the automatic process. They dash aren't counted as legitimate users. Keywords: Belt, Microcontroller, Sensors, Simulation.
Analysis Seismic Behavior of Structures with Planar Imperfections: A Comprehensive Numerical Analysis
Authors:   Department Of Civil Engineering, Oriental University, Indore., Dhurve Sonu
Published: May 2024

This paper presents a comprehensive approach to the seismic analysis and design of a tall hospital building, accounting for horizontal irregularities and employing equivalent static analysis (ESA) methodology. The study initiates with the collection of relevant site data and building specifications, including the identification and characterization of horizontal irregularities such as setbacks, mass distribution variations, and irregular floor plans. Equivalent static lateral loads are calculated based on applicable building codes and standards, taking into account the effects of horizontal irregularities on seismic response. Structural modeling and analysis are then conducted using sophisticated software to evaluate the building's behavior under seismic forces, considering the influence of irregularities on structural performance. Design criteria, encompassing drift limits, strength requirements, and detailing considerations for mitigating irregularity effects, are rigorously adhered to ensure compliance with safety regulations and performance objectives. The iterative process of evaluation and adjustment ensures optimal seismic performance and adherence to design criteria despite the presence of horizontal irregularities. Documentation of the analysis and design process, coupled with meticulous construction oversight, guarantees the implementation of a robust seismic design strategy tailored to the unique characteristics of the tall hospital building. Post-construction evaluations are carried out to validate predicted seismic performance, accounting for the influence of horizontal irregularities. Through collaborative efforts and adherence to best practices, the seismic design of the tall hospital building prioritizes safety and resilience, even in the face of horizontal irregularities, aiming to safeguard occupants and critical healthcare infrastructure during seismic events.
CONCEPTUAL STUDY OF FINANCIAL LITERACY AND FINANCIAL INCLUSION: AMONG THE MILLENNIAL’S
Authors:   Junior Research Fellow, Department of Commerce and Business Administration, University of Allahabad, Shukla Shruti
Published: May 2024

In an evolving period of tremendous technological advancement and intensifying global competitiveness, an economy and its citizens need to operate with awareness, adaptability, and alignment with changes and development in order to stand ahead of and thrive with the dynamics. In spite of conventional and foundational work, modernism's recent introduction and its various benefits are something that one ought to weigh. It turns into a drive for improvement to make things now better in order to achieve the future better. In order to this, Financial Literacy is something which assist to gain meaningful insight and leads to decide more rationally in managing the finance. Hence Relationship between financial literacy and financial inclusion among millennials is examined in this study. Millennials have particular financial opportunities and challenges because they are the first generation grown up in the digital era. This research examines how financial literacy affects the millennials use and access to financial services through an extensive literature reviews and qualitative analysis. It also looks at how educational initiative and technology supports financial inclusion and literacy. The result highlights the significance of focused training programs and digital platforms in boosting millennials financial capacities by pointing to a favourable association between financial inclusion and financial literacy levels. Policy makers, financial institutions and educators must comprehend these dynamics in order to create specialized plans that enable millennials to engage fully in the financial system and make wise financial decisions. Keywords: Financial Inclusion, Financial Literacy, Millennials, Financial Skill, Financial Decisions.
Bibliometric Analysis of Fintech Trends
Authors:   Galgotias University, Sharma Roshan Kumar
Published: May 2024

The significant significance that the fast growth of financial technology (Fintech) has had in the creation of numerous academic research is clear. The patterns, impacts, and prospective future directions of this phenomenon that is changing the industry have been the focus of several studies. To gain a better understanding of the current developments in the financial technology industry, we conduct a survey of the academic publications that correspond to them as part of our comprehensive bibliometric study. Our research in the area of financial technology (Fintech) makes use of bibliometric techniques to examine trends in publication, citation networks, and subject clusters. Our major focus is a massive dataset that spans many years and includes data from economics, computer science, and finance. Notable authors, major publications, and new categories are illuminated by the most significant findings in the field of financial technology research. When we set out to conduct this research, we hoped to fill knowledge gaps, paint a full picture of the ever-changing fintech industry, and increase our familiarity with this extraordinary sector. Keywords: Fintech, bibliometric analysis, trends, financial technology, citation networks, scholarly literature, research themes, interdisciplinary, systematic approach.
Design and Simulation of Clock Divider using VHDL
Authors:   Student, Department of Electronics & Telecommunication Engineering, Priyadarshini College of Engineering, Nagpur, India, Patil Archana
Published: May 2024

This paper presents the diesign and simulation of clock divider circuit using VHDL(VHSIC Hardware Description Language) on an FPGA(Field Programmable Gate Array). The clock divider circuit is a fundamental component in digital system for generating lower frequency clocks from a higher frequency reference clock. The paper starts up with simple divider where the clock is divided by even numbers, odd numbers and then later expands it into non- integer dividers. Keywords:- clock divider, D flipflop, FPGA
DESIGN AND FABRICATION OF AUTOMATED SIEVE MACHINE
Authors:   Mechanical Engg. Department, VIT, Nagpur, Nakoriya Satyam Ganeshsinh
Published: May 2024

The paper describes the basic model and operation of a smart multifunctional sieving machine. The sieving machine is a multi-layer sieving machine that can be used for a variety of tasks such as sieving sand, eliminating stone from grains, and so on. The size and number of sieves may be adjusted depending on the need. This article covers the idea of the Design and Fabrication of a Multi-purpose Sieving Machine, which was primarily completed for manufacturing-based enterprises. Because of technological innovation, every work in today's world has become faster and faster, and every industry aspires to retain a high production rate while preserving the quality and standard of the product at a low average cost. We created a conceptual idea of a machine that can conduct several tasks concurrently and quickly. In this machine, we drive to the main shaft with a motor that is directly connected to the slider-crank mechanism; the slider-crank mechanism is employed in the sieving operation. With the assistance of a wiper motor, the table is fastened with a crank that rotates the tray to vibrate it and function as a separator. Consequently, the purpose of designing and manufacturing the Sieving Machine is to assist industrialists and farmers on the global market. The benefit is the ability to easily separate objects based on mesh, as well as cost savings linked with power use, an improvement in productivity rate, and the production of less space, among other things. We have further automated this sieving process and can operate the machine via the blynk interface Key Words: Sieving, slider crank mechanism, blynk, multi-purpose, multi-layer, technology, productivity
ARTIFICIAL INTELLIGENT SYSTEM FOR AUTOMATIC DEPRESSION LEVEL ANALYSIS THROUGH VISUAL AND VOCAL EXPRESSIONS
Authors:   Student, Department of VLSI & Embedded System, Tambe Sarita Pandharinath
Published: May 2024

Depression is a major mental health disease of human which is rapidly affecting lives worldwide. Early detection and intervention are crucial for effective treatment and management. Depression is regularly identified with thoughts of suicide. Significant depression can bring about a determination of social and physical side effects. It could remember changes in rest, craving, vitality level, concentration, day by day conduct or confidence. In recent years, deep-learned applications concentrated on neural networks have shown superior performance at hand-crafted apps in various areas. This system presents an innovative artificial intelligence (AI) system designed for automatic depression level analysis by analyzing visual and vocal expressions. Leveraging advances in computer vision and natural language processing, the proposed system extracts relevant features from facial expressions and speech patterns to assess depression severity levels accurately. Deep-learned apps that settle the above issues that may precisely assess the degree of voice and face depression. In the proposed method, Convolutionary Neural Networks (CNN) is developed for learning deep-learned features and descriptive raw waveforms for visual expressions. Second. Keywords: Artificial Intelligence, Depression, Vocal, Facial Expressions, Deep Learning
Music Information Retrieval using Deep Learning Techniques
Authors:   Student, Information Technology, MCT’s Rajiv Gandhi Institute of Technology, Mumbai, Subramanian Vignesh
Published: May 2024

Music Information Retrieval (MIR) is gaining attention due to the surge in digital music and the need for efficient search and recommendation systems. Traditional MIR methods rely on hand-crafted features and rule-based systems, limiting their adaptability. Deep Learning (DL) shows promise in automatically extracting complex patterns from raw data. This paper offers an extensive overview of MIR tasks like classification, genre recognition, similarity search, and recommendation, along with DL models like Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), including LSTM and Transformer architectures, tailored for MIR. Challenges such as data scarcity, computational complexity, and interpretability persist, with proposed solutions like data augmentation, transfer learning, and attention mechanisms. Experimental results on benchmark datasets demonstrate DL's superiority in accuracy, scalability, and robustness over traditional methods. Practical examples highlight DL's potential to revolutionize music search, recommendation, and analysis. Emphasizing the importance of large annotated datasets for training high-quality DL models, strategies for data collection, labeling, and preprocessing are outlined. DL offers promising prospects for advancing MIR by addressing its inherent challenges and establishing new performance benchmarks. Further DL development is expected to drive innovation and enhance digital music consumption experiences through MIR systems. Keywords: Deep Learning, Convolution Neural Network (CNNs), Recurrent Neural Network (RNNs), Digital Music Consumption, Genre recognition.
Fairness-Aware Oversampling Algorithm Based on Distributions of Sensitive Attributes
Authors:   Students, Computer Science and Engineering, Babu Banarasi Das Northern India Institute of Technology, Kumar Ashish
Published: May 2024

Given the growing utilization of machine learning algorithms in decision-making processes that impact individuals, it is crucial to ensure that predictions do not exhibit bias towards specific population subgroups, such as race or gender. Bias occurs when the likelihood of a positive outcome varies among different groups defined by these sensitive attributes. Research has demonstrated that this bias often stems from imbalanced datasets, where one class is significantly underrepresented compared to others. Understanding the nature of this imbalance, particularly the distribution of minority classes, is essential. This study introduces FAWOS, a Fairness-Aware oversampling technique designed to mitigate unfair treatment related to imbalances in sensitive attributes. FAWOS classifies data points based on their proximity to specific local neighborhoods defined by sensitive attributes, identifying those that are more challenging for classifiers to learn. To address dataset imbalance, FAWOS synthesizes new data points by oversampling from identified challenging data types. The impact of FAWOS on various classifiers is evaluated, assessing which ones are better equipped to handle imbalances related to sensitive attributes. Empirical findings indicate that FAWOS effectively enhances fairness in classifier outcomes without compromising overall performance. Key Words: Fairness-Aware Oversampling, Bias Mitigation, Imbalanced Datasets, Classifier Performance
A REVIEW ON TOTAL PRODUCTIVE MAINTENANCE (TPM)
Authors:   Anjuman College 0f Engineering and Technology, Sadar, Nagpur, India., Wasnik Akshay
Published: May 2024

Total Productive Maintenance (TPM) is transforming manufacturing landscapes. This review investigates its impact, revealing how TPM fosters a culture of continuous improvement through employee involvement and proactive maintenance strategies. By analyzing 30 research papers, it unveils the potent link between TPM and increased productivity alongside reduced waste. Highlighting Overall Equipment Effectiveness (OEE) as a crucial metric, the review emphasizes the importance of 5S as a foundational step for successful TPM implementation. With global adoption surging, TPM is solidifying its position as a world-class strategy for achieving peak manufacturing performance." Keywords: Total Productive Maintenance (TPM), OEE, Improve Productivity, 5S.
AN EFFICIENT VLSI IMPLEMENTATION OF EDGE DETECTION OF IMAGES
Authors:   Assistant Professor Sir C.R Reddy college of Engineering, PRAKASH CH.JAYA
Published: May 2024

Edge detection is a fundamental process in image processing with significant implications across multiple domains. Within the realm of object detection, the accurate delineation of image perimeters forms the bedrock for subsequent analysis. In this study, we present an optimized Laplacian Edge Detection algorithm tailored for efficient implementation in hardware.Leveraging approximation methodologies and strategic pipelining, we streamline complex operations, thereby reducing latency and resource consumption. Our implementation, realized through the Verilog Hardware Description Language (VHDL), stands as a testament to the efficacy of our approach. Through rigorous optimization and meticulous comparison with conventional Sobel edge detection, we demonstrate superior performance metrics, including enhanced Area utilization, reduced Time Delay, and improved Power Efficiency. This work underscores the importance of methodological refinement and technological innovation in advancing edge detection techniques for practical applications. Keywords: Laplacian, Sobel, Kernel, Pixel range, Area, Power
PERSONALITY PREDICTION SYSTEM
Authors:   Department of Computer Science and Engineering, D. Y. Patil College of Engineering and Technology, Kolhapur, Maharashtra., Shenavi, Sakshi
Published: May 2024

Personality prediction is a challenging yet crucial task in various fields such as psychology, human resources, and marketing. In this study, we propose a questionnaire-based approach using the random forest algorithm to predict personality traits. The questionnaire is designed to gather information related to the personality traits: openness, conscientiousness, extraversion, agreeableness, and neuroticism. The dataset used for this study consists of responses from individuals who completed the questionnaire. Responses to specific questions are used as input variables for the random forest algorithm. The algorithm is trained on a portion of the dataset and then tested on the remaining portion to evaluate its performance in predicting personality traits. Our results show that the random forest algorithm achieves high accuracy in predicting personality traits, outperforming other machine learning algorithms such as logistic regression and support vector machines. This approach has the potential to be used in various applications, such as personalized marketing, recommendation systems, and mental health assessment. Key Words: Personality prediction, Random forest algorithm, personality traits, Questionnaire-based approach.
ADVANCED SHOPLIFTING PREVENTION AND ALERT STSYEM
Authors:   B. S. Abdur Rahman Crescent Institute of Science and Technology  Vandalur, Chennai-600048, RAHMAN M. MUSHARUF
Published: May 2024

Detecting human beings accurately in a visual surveillance system is crucial for diverse application areas including abnormal event detection, human gait characterization, congestion analysis, person identification, gender classification and fall detection for elderly people. The first step of the detection process is to detect an object which is in motion. Object detection could be performed using YOLOv7, optical flow and spatio-temporal filtering techniques. Once detected, a moving object could be classified as a human being using shape-based, texture-based or motion-based features. A comprehensive review with comparisons on available techniques for detecting human beings in surveillance videos is presented in this paper. The characteristics of few benchmark datasets as well as the future research directions on human detection have also been discussed. We can use camera for Human Motion Detection. The Camera is used to catch the live images of the area in which it is being implemented, if any object is moving. The captured images are stored for further work. If motion is found in this video, the computer will start recording, buzz an alarm and send SMS to people listed in its database. In this way the system will provide the security against any misdeed. Keywords: YOLOv7, SMS, E-mail, CCTV, SMTP, RFID
FOOD CLASSIFICATION AND CALORIE ESTIMATION USING CNN
Authors: M Ethesh
Published: May 2024

This research paper explores the transformative impact of deep learning methodologies in the domains of food image recognition, classification, and calorie estimation. By utilizing the convergence of machine learning with convolutional neural networks (CNNs), the study tackles the growing concerns surrounding obesity and health difficulties, highlighting the need for creative methods of nutritional monitoring. Motivated by challenges in fruit classification and the limitations of traditional methods, the research progressively shifts towards efficient and accurate image-based approaches, particularly highlighting the effectiveness of CNNs. The methodology focuses on machine learning-based approaches for food calorie estimation, with a specific emphasis on parameter-optimized lightweight CNN models utilizing TensorFlow's Object Detection API and CNN. The results showcase impressive accuracy levels, often exceeding 90%, across diverse food items, albeit with persistent challenges such as limited datasets, computational costs, and real-world application constraints. In conclusion, this comprehensive review underscores the transformative potential of deep learning in fostering healthier lifestyles, combating obesity, and providing valuable insights for dietary guidance and health management. Further research is recommended to enhance dataset representativeness and optimize model generalization for broader practical applicability Keywords: Calorie estimation, Classification, Convolutional neural network, Object detection.
SURVEY ON FOOD CLASSIFICATION AND CALORIE ESTIMATION USING CNN
Authors: M Ethesh
Published: May 2024

This research paper explores the transformative impact of deep learning methodologies in the domains of food image recognition, classification, and calorie estimation. By utilizing the convergence of machine learning with convolutional neural networks (CNNs), the study tackles the growing concerns surrounding obesity and health difficulties, highlighting the need for creative methods of nutritional monitoring. Motivated by challenges in fruit classification and the limitations of traditional methods, the research progressively shifts towards efficient and accurate image-based approaches, particularly highlighting the effectiveness of CNNs. The methodology focuses on machine learning-based approaches for food calorie estimation, with a specific emphasis on parameter-optimized lightweight CNN models utilizing TensorFlow's Object Detection API and Mask R-CNN. The results showcase impressive accuracy levels, often exceeding 90%, across diverse food items, albeit with persistent challenges such as limited datasets, computational costs, and real-world application constraints. In conclusion, this comprehensive review underscores the transformative potential of deep learning in fostering healthier lifestyles, combating obesity, and providing valuable insights for dietary guidance and health management. Further research is recommended to enhance dataset representativeness and optimize model generalization for broader practical applicability Keywords: Calorie estimation, Classification, Convolutional neural network, Object detection.