bluuebunny/crossref_metadata_2025 huggingface dataset:
Honorary Doctorate Prof. Mary Beckman
Authors: Beckman Mary , Ernestus Mirjam
Published: April 2024

On October 17, 2023, during the 100th Dies Natalis of Radboud University, Mary Beckman received an honorary doctorate from Radboud University. This doctorate was awarded in recognition of her innumerable contributions to the field of linguistics. This edition includes, among other things, honorary promotor Mirjam Ernestus’ laudatio, Mary Beckman’s acceptance speech, and a detailed recollection of Beckman’s professional history. Mary Beckman made an impact early in her career by launching the Conference on Laboratory Phonology together with John Kingston, which was instrumental in the process of unifying research into the formal system of speech and research into the physical properties of speech. She then went on to co-create the ToBI system for prosody transcription, which allows researchers from many different fields to work and collaborate on speech research. Her academic contributions have fundamentally altered the course of speech research by synthesizing numerous different areas of research that once seemed incompatible. Honorary promotor Mirjam Ernestus, professor of psycholinguistics: “It is a great honor that someone with these qualities and achievements and who has materialized all the principles that we find important at Radboud University has agreed to become an honorary doctor at our university.”
Intelligent Enhanced Mobile Robotics Navigation: Integrating Neural Networks with Type-2 Fuzzy Logic for Dynamic Environments
Authors:   College of Computer Science and Information Technology; University of Anbar, Ramadi, Anbar, Iraq, Mohammed Mohammed ,   Computer Science Department, Al-Maarif University Collage, Ramadi, Anbar, Iraq,   College of Computer Science and Information Technology; University of Anbar, Ramadi, Anbar, Iraq,   College of Computer Science and Information Technology; University of Anbar, Ramadi, Anbar, Iraq, .. Mahmood Abdulrazzaq , .. Ruqayah R. Al , Aliesawi Salah A.
Published: April 2024

Intelligent mobile robots move on uncertain grounds, thus requiring good navigation strategies for things like path tracking and obstacle avoidance. This research uses an Omni-drive mobile robot to autonomously approach given objectives in different situations encountered in static and dynamic environments. The paper compares two distinct controllers – fuzzy logic controller and neural network controller- that lead the mobile robot towards its destination without hitting obstacles. These are responsible for adjusting the linear and angular velocities of a mobile robot which makes adaptive navigation possible during real-time. The experimental results have depicted the adaptability of each controller as well as its efficiency especially when dealing with uncertainties involved with the mobile robot navigation system. By systematically evaluating and contrasting them, this study brings out the best performance between Fuzzy Logic and Neural Network Controllers regarding enhancing the autonomy and robustness of Mobile Robots. This research helps to advance knowledge in autonomous systems for practical applications, which will give rise to more efficient navigational techniques for mobile robots; thus, efficient systems that are autonomous become more reliable today. The results show that these controllers are effective in safely steering the robot from its starting point to a specified destination without hitting obstacles.
Growth performance, physiological response, and tissue microarchitecture of the carp Labeo rohita challenged with AFB1 are improved by supplementing with turmeric
Authors: Bhatt Deepa , Holeyappa Shanthanagouda A. , Pandey Abhed , Bansal Neelam , Hundal Jaspal S. , Khairnar Sachin O.
Published: April 2024

Aim of study: To examine the impact of dietary supplementation with turmeric (TM) (Curcuma longa) on growth, haematological, biochemical parameters, and histoarchitecture in rohu (Labeo rohita) challenged with aflatoxin B1 (AFB1).
Area of study: Ludhiana, Punjab, India.
Material and methods: A completely randomized design involved the utilization of 225 fingerlings distributed across five treatments with three replicates each. Diets were allocated as follows: T1 denoted the negative control diet, T2 comprised AF100, while T3, T4, and T5 were formulated with AF25TM, AF50TM, and AF100TM, respectively.
Main results: The results indicated a negative correlation between AFB1 dosage in feed and fish growth, with higher doses resulting in decreased growth. Significant changes were observed in haematological parameters, including reductions in total erythrocyte count, total leukocyte count, haemoglobin, and packed cell volume, alongside alterations in biochemical parameters, such as decreases in total protein, albumin, and globulin levels, and an increase in glucose levels and albumin/globulin ratio. Additionally, elevated levels of aspartate aminotransferase, alanine aminotransferase, catalase and superoxide dismutase were noted in T2 and T5 compared to other treatments. AFB1 exposure also led to damage in the microarchitecture of the brain, kidney, and liver tissues, although inclusion of TM at 25 ppb AFB1 showed signs of recovery.
Research highlights: The changes observed were dose-dependent, and supplementation of TM showed increased resistance against AFB1 and the greatest improvement in T3. Therefore, a diet containing 5 g TM kg-1 would lower AFB1 contamination of 25 ppb compared to 50 and 100 ppb. In conclusion, supplementing TM in fish feeds can help regulating the AFB1, which in turn can improve sustenance-based output.
Explore How to Refine Social Media Marketing Strategies and Shape Consumer Travel Preferences: An In-depth Study on Airbnb
Authors: Weng Yinuo
Published: April 2024

In a post-COVID-19 era of digital transformation and a gradually recovering tourism economy, the travel industry must continually seek innovative ways to enhance social media marketing strategies and better understand consumer behaviour. This paper provides insights into how social media marketing strategy optimisation can shape consumer travel preferences. Using Airbnb as a case study, this paper analyses the social media comments of Airbnb users to reveal consumers' overall positive attitudes towards Airbnb's services through sentiment analysis and explore how methods such as predictive analytics can be used to tailor social media marketing campaigns to provide a more personalised and effective service to potential travellers. The results show that consumers are very concerned about whether the service experience differs from what is advertised on social media, such as quality of accommodation, customer service and pricing strategies. Therefore, Airbnb should prioritise consumer feedback, improve social media content quality, and use predictive analytics to identify its target audience. Future research should incorporate diverse data sources and advanced analytics techniques to understand consumer needs better, establish stronger customer connections, and influence travel choices.
Applications of Natural Language Processing for Automated Clinical Data Analysis in Orthopaedics
Authors: AlShehri Yasir , Sidhu Arashdeep , Lakshmanan Laks V.S. , Lefaivre Kelly A.
Published: April 2024

Natural language processing is an exciting and emerging field in health care that can transform the field of orthopaedics. It can aid in the process of automated clinical data analysis, changing the way we extract data for various purposes including research and registry formation, diagnosis, and medical billing. This scoping review will look at the various applications of NLP in orthopaedics. Specific examples of NLP applications include identification of essential data elements from surgical and imaging reports, patient feedback analysis, and use of AI conversational agents for patient engagement. We will demonstrate how NLP has proven itself to be a powerful and valuable tool. Despite these potential advantages, there are drawbacks we must consider. Concerns with data quality, bias, privacy, and accessibility may stand as barriers in the way of widespread implementation of NLP technology. As natural language processing technology continues to develop, it has the potential to revolutionize orthopaedic research and clinical practices and enhance patient outcomes.
Medición de la situación de inseguridad alimentaria a nivel del hogar en los municipios de cobertura del Ejercicio Profesional Supervisado de la Escuela de Nutrición de la Universidad de San Carlos de Guatemala
Authors: Hernández Bal Cecilia Maria Anita , Enríquez Obando Emily Gabriela Enríquez Obando , Barrios Morales Andrea María , García Solórzano Ana María , Liska de León Cecilia , Velásquez Sigüenza Miriam Mercedes
Published: April 2024

La inseguridad alimentaria (INSA) es la condición que resulta de un acceso incierto o nulo a alimentos nutricionalmente adecuados socialmente aceptables y/o insuficiente ingestión de alimentos. Las causas de la INSA son múltiples y difieren en cada país, entre ellas están inadecuado acceso, y disponibilidad a los alimentos nutricionalmente adecuados y a los capitales de desarrollo. Según los resultados de la Encuesta Nacional de Condiciones de Vida del 2014, la INSA afecta a más de la mitad de la población guatemalteca con repercusiones en su calidad de vida y desarrollo. El objetivo de la investigación fue determinar el nivel de INSA en hogares de los 29 municipios pertenecientes a 12 departamentos de cobertura del EPS de la Universidad de San Carlos de Guatemala. Se realizó un estudio de tipo cuantitativo, descriptivo, transversal, utilizando la metodología de recolección, validación y análisis de información establecida en el Manual de la Escala Latinoamericana y Caribeña de Seguridad Alimentaria (ELCSA). La muestra fue de 2,750 hogares, obtenida por medio de un muestreo probabilístico para poblaciones finitas. Los datos analizados fueron desagregados según sexo y edad de jefe de hogar, lugar de residencia, número de miembros en el hogar y presencia de menores de 18 años. La investigación mostró que, al momento de la entrevista, 2,035 (74%) [72.3, 75.7] hogares fueron clasificados en situación de INSA. Se presentó un mayor porcentaje de INSA en los hogares del área rural (85% [82.5, 87.4]) y en los hogares con niños menores de 18 años (80% [78.0, 81.5]). También se observó que, a mayor número de miembros del hogar, mayor porcentaje de INSA. Con los resultados obtenidos, se pretende motivar la implementación de estrategias que coadyuven a mejorar la situación de INSA en la población.
The advancement of microsensors in the age of IoT and Industry 4.0
Authors: Gazis Alexandros
Published: April 2024

Sensors are devices that receive input and produce an analog or digital output signal. They are found in almost every aspect of human activity, from robotics, medical devices, consumer electronics, automobiles, to residential appliances and industrial automation [1]. In recent years, the rapid increase of interconnected devices that are connected to the internet has defined a new technological term: the “Internet of Things” (IoT). IoT has created a demand for acquiring, collecting, and processing vast amounts of data, thus shaping the upcoming new industrial revolution “Industry 4.0” [2].
Comprehensive evaluation of modern agricultural development level in contiguous destitute area of Lvliang Mountain, Shanxi Province
Authors: Ji Qin , Yang Jianping , Xu Manhou
Published: April 2024

An evaluation model was established using a combination of AHP and multi-objective linear weighted function methods to comprehensively evaluate the development level of modern agriculture in the contiguous poverty-stricken areas of Lvliang Mountain in Shanxi Province. The results show that: (1) As a whole, the contiguous poverty-stricken areas have a low degree of agricultural modernization and are in the initial stage of development. The degree of modernization of agricultural production conditions, agricultural production results, and farmers’ living standards is gradually decreasing; at the municipal level, the degree of agricultural modernization in the three cities is the same. Not high, the order is Xinzhou City > Linfen City > Lvliang City; at the county level, the degree of agricultural modernization varies greatly. The counties in Xinzhou City are in the high-level sub-stage of the initial stage, and the counties in Lvliang City are in the low-level sub-stage of the initial stage. The overall degree of agricultural modernization in counties shows a spatial pattern of low in the middle and high in the north and south; (2) The contributions of agricultural production conditions, production results and farmers’ living standards to modern agriculture are 16.4%, 29.7% and 53.9% respectively. The low level of agricultural electrification and mechanization and backward production conditions are bottlenecks in the development of modern agriculture. The backward agricultural production conditions lead to inefficient production results, low disposable income of farmers, and low living standards of farmers, which are the root causes of the slow development of modern agriculture in the region.
Fermat surfaces and hypercubes
Authors: Carbó-Dorca Ramon , Nath Debraj
Published: April 2024

Fermat’s last theorem appears not as a unique property of natural numbers but as the bottom line of extended possible issues involving larger dimensions and powers when observed from a natural vector space viewpoint. The fabric of this general Fermat’s theorem structure consists of a well-defined set of vectors associated with  dimensional vector spaces and the Minkowski norms one can define there. Here, a special vector set is studied and named a Fermat surface. Besides, a connection between Fermat surfaces and hypercubes is unveiled.
Using social exchange theory to predict residents’ perspective on factors influencing tourism development in Pokhara
Authors: Poudel Samikshya , Basyal Devid Kumar , Devkota Niranjan , Paudel Udaya Raj , Lawaju Purnima , Danuwar Ranjana Kumari
Published: April 2024

Tourism development involves sustainably creating and managing destinations, products, and services that balance economic, social, and environmental factors while meeting visitor and local community expectations. The purpose of this study is to understand the local people’s perception of tourism development in Pokhara, Nepal. An explanatory research design is used to show the cause-and-effect relationship between variables. The research was conducted using Social Exchange Theory (SET). The data was examined using both descriptive and inferential statistics. The sample size was determined to be 403 using non-probability sampling. A structured questionnaire was designed to collect the data using the KOBO toolbox. Furthermore, the Structure Equation Model (SEM) was the analytical approach used to process the data. Results reveal a noteworthy relationship between independent variables (such as cultural impact, social impact, environmental impact, and economic impact) and dependent variables (support for tourism development). The major challenges in tourism development have been identified, including deficient infrastructure, suboptimal tourism strategies and implementation, and inadequate government oversight. Effective mitigation of these challenges necessitates the implementation of appropriate infrastructure and development initiatives, proficient governmental management, and a concerted effort to augment the quantity and quality of hotels and accommodations. The significance of cultural, social, environmental, and economic impact cannot be understated or overstated in the context of tourism development. Addressing major challenges, the study suggests focused efforts in enhancing infrastructure and development, adopting effective management practices, and augmenting the quantity and quality of hotels and accommodations.
A Novel Training Method for Endovascular Clot Retrieval Using a Portable Vascular Model and Red Film
Authors: Ioku Tetsuya , Ohshima Tomotaka , Kawaguchi Reo , Matsuo Naoki , Miyachi Shigeru
Published: April 2024

Hands-on training is a crucial part of education in neuroendovascular treatment to ensure safe and rapid acquisition of techniques. However, there is a significant gap between training and actual clinical practice. This study will introduce innovations for more practical thrombus retrieval training that was developed in this process. A Smart Vascular Model 3 in 1 was used. A pink pseudothrombus was inserted into the M1 (horizontal segment of the middle cerebral artery) section of the model. Then, a “red underlay” purchased at a stationery store was placed to cover the proximal part of M1 and beyond so that the pseudothrombus was not visible. The thrombus was retrieved during training by looking for the location of the thrombus based on the behavior and resistance of the tip of the guidewire and deployment of the stent retriever. The participants were required to have detailed observation skills and precise manipulation skills using a red film to prevent the direct visualization of the pseudothrombus. The implementation of this innovation to the previous hands-on training made the training more practical and effective. If the exact thrombus location can be determined by the behavior of the wire tip, the device’s capabilities can be maximized, and rapid retrieval can be expected. It could also reduce complications, as unnecessary peripheral guidance of the device could be avoided.
The Influence of Environment Environments on Organizational Loyalty in Small and Mid-sized Enterprises from Yangsan Industrial Complex
Authors:   Academy of Paractical Business Administration, Kim Oh-Gon , Kim Chang-Tae
Published: April 2024

This study attempted to analyze the influence of employment environments on job satisfaction against small and mid-sized enterprises in Yangsan Industrial Complex and suggest a direction for future development. After all, a company is composed with employees, and their competitiveness becomes business competitiveness In this study, ‘employment environment’ was chosen for an independent variable, and its sub factors were set to ‘wage’, ‘employment stability’, ‘terms of employment’ and ‘company welfare’. In addition, ‘job satisfaction’ was selected as a dependent variable, and for its sub factors, ‘job satisfaction’, ‘organizational commitment’ and ‘turnover intention’ were selected. The hypothesis, “employment environments had an influence on job satisfaction”, was partially supported. In addition, an additional empirical study was performed provided that there would be differences in job satisfaction depending on subjects’ general characteristics.
The impact of specialty steel purchase factors on satisfaction and behavioral intentions
Authors:   Academy of Paractical Business Administration, Hong Ryu-Geum
Published: April 2024

This study was conducted to investigate the mediating effect of satisfaction in the relationship between specialty steel purchase factors and behavioral intentions. As a result of statistically analyzing data collected through a survey, it was found that awareness and responsiveness among the factors for purchasing special steel materials had a significant effect on behavioral intentions by mediating immersion. In addition, among the factors for purchasing special steel materials, product quality, supply price, safety, and responsiveness were found to have a significant effect on behavior by mediating customer satisfaction. Through this result, the researcher suggests practical implications.
Smart Shopping Trolley with Automated Billing using Arduino
Authors: Anuvarshitha Pamisetty
Published: April 2024

Shopping can be an exciting experience, but the long queues at checkout can often leave us feeling drained. customers have to wait in line to have each item individually scanned at the counter, which can be time-consuming, especially during peak shopping hours. This inefficiency not only leads to customer frustration but also affects the overall shopping experience. To tackle this issue, a solution is proposed: the smart shopping trolley with automated billing. This innovative approach allows customers to breeze through their shopping journey. With the smart trolley, shoppers can effortlessly select their items and complete their purchases without the hassle of traditional checkout lines. The trolley automatically generates bill, which is conveniently sent to the customer via app. The customer can make the payment using the app. This system incorporates various components, including an Arduino board, RFID reader for item identification, LCD display for user interaction, Wi-Fi module for connectivity, and sensors for theft detection and an app for the payment. This process not only reduces waiting times but also enhances overall efficiency,making shopping a more pleasant experience for customers. Index Terms-Arduino, RFID Display, RFID tag, LCD dis- play,load cell, wifi module,IR sensor
Trinal Optics for Blind People Using Smart Object Recognition for Navigation Through Voice Assistant
Authors:   1JSPM’s Bhivrabai Sawant Institute of Technology and Research, Wagholi, Pune 412207. principal@jspmbsiotr.edu.in, Patil Prof. Shrishail
Published: April 2024

The project Trinal Optics is a wearable device, it will be able to make blind people to live their lives more independently. The device is combination of hardware, software and Technologies such as Camera, Arduino Uno, Voice Assistant, Bluetooth Headset/Earphone, Ultrasonic Sensor, Object Detection, and Distance Analysis. These components help user to understand the environment better. The Camera is used to capture the image for object detection and then Voice assistant is conveying audio message to the user along with the Distance analysis of object, Arduino Uno is used to integrate hardware and software, navigation is used to guide the users to its destination Ultrasonic sensor is used to make the beep sound if there is any object in front of the user. Trinal Optics looks forward to help blind individuals to have a bit easy life with the help of technology. Keywords: Arduino Uno, Camera, Bluetooth Earphone, Voice Assistant, Object Detection, Distances Analysis, Ultrasonic Sensor.
Design of High Performance Dual-band Microstrip Patch Antenna for Wi-Fi Applications
Authors:   ECE, RVRJCCE, INDIA, Reddy Y. Keerthi
Published: April 2024

Micro strip antennas are low-profile occupies less space and requires less power. A metal patch mounted at a ground level with a di-electric material in-between constitutes a Micro strip or Patch Antenna. In this paper, it is proposed to design a Microstrip patch antenna operating at 2.4 GHz and 5.8 GHz frequencies. The primary aim is to create a compact, easily fabricated, and high-performance antenna. It is proposed to incorporate a copper patch with strategically placed slots on an FR-4 substrate, along with a 50Ω microstrip feed line. In this paper, it is proposed to measure the VSWR, Return loss, Directivity and radiation pattern of the proposed antenna. It is proposed to design this antenna using CST Microwave studio software. Top of Form Keywords: Microstrip Patch Antenna, Wi-Fi, Dual-Band, 2.4/5.8 GHz, CST Simulation
SOCIAL MEDIA INFLUENCE ON BEAUTY TRENDS
Authors:   Faculty of Management Studies,  JAIN (Deemed-to-be University)  Bengaluru, India, Upagna Maganti
Published: April 2024

Social media has greatly influenced the changes of beauty in recent years. An increasing number of people resort to such social media platforms as Instagram or YouTube for inspiration in terms of style, hair, or makeup ideas. The purpose of this research is to prove the vast impact of influencers, especially those on Instagram, YouTube, and Tiktok, on the creation, distribution, and result of beauty trends in the modern digital period. Authentic and relatable content from influencer help to bridge the gap between them and their audience. However, if beauty ideals are unattainable and self-esteem and body image can suffer greatly from constantly seeing meticulously planned content about beautiful women. Given the global reach of social media, there is also the problem of culture appropriation. The study highlights the complex relationship between beauty trends and social media. This calls for investigations into models that promote healthier beauty standards, responsible content creation; and a more inclusive representation of beauty on these networks. Key words: Social network, fashion trends, ideal looks, the age of digitization, power
Intersectoral Interventions in School to Develop Strategies to Prevent the Use of Alcohol and Other Drugs: A Scoping Review
Authors: Andrade Aurélio Matos , Girardi Juliana da Motta , Pinto Alexandro Rodrigues , Lima Maria da Glória , Köptcke Luciana Sepúlveda , Costa Lourenço Faria
Published: April 2024

It is important to prioritize intersectoral action at schools to prevent the use of alcohol and other drugs. This strategic act should be organized with multidisciplinary learning characteristics and with the involvement of different stakeholders. The aim of a recent scoping review was to identify the factors that benefit and hinder intersectoral actions at school resulting from the elaboration of policies to prevent drug use. It seems like the research study was a scoping review that used the P-population, C-context, and C-concept structure. The study searched for information in various databases like Embase, Proquest, Lilacs, Medline via Pubmed, PsycInfo, WHO-Iris, and PAHO-Iris on April 17, 2023. According to the results, there were 5 studies that were eligible to answer the research question. One of the advantages of intersectoral actions is the role of schools in creating a support network with different social actors, particularly with family involvement. On the other hand, one of the challenges is inconsistencies in legal regulations, which do not provide enough guidance to schools on how to prevent alcohol and drug use. While public and private schools may be affected differently by social and economic factors, it is essential to invest in developing policies that focus on drug prevention for children and adolescents who are learning in schools.
BRIDGING TRADITION & TECHNOLOGY: A REVIEW OF THE PRAN-PRATISTHA CEREMONY AT AYODHYA
Authors: Rai Rajat , Shukla Ayushi , Chaturvedi Dr. Shivi , Kumar Dr. Abhishek
Published: April 2024

The significance of maintaining a delicate balance between cultural reverence and technological progress in the context of the Pran Pratistha ceremony at Ayodhya's Ram Mandir lies in preserving the authenticity and sanctity of the event while embracing advancements that enhance the overall experience. This delicate balance ensures that technological interventions do not compromise the cultural significance of the ceremony but rather complement and elevate the spiritual experience for all participants. The impact of this balance on the integration of Artificial Intelligence (AI) into the ceremony is profound. It involves a progressive leap forward, marking a transformative shift in security measures. The integration of AI into the Pran Pratistha ceremony's security framework, particularly within CCTV camera surveillance and the utilization of government records for intruder detection, represents a harmonious coexistence of tradition and innovation. The aim is to ensure that the integration of AI enhances security without overshadowing the spiritual and cultural essence of the ceremony. This delicate equilibrium is crucial for harmonizing technological progress with cultural authenticity, signifying not only a technological evolution but also a cultural metamorphosis. The integration of AI into the ceremony is undertaken with a keen awareness of the need to preserve the sanctity of time-honored practices while leveraging cutting-edge innovation to elevate the overall security framework. Ultimately, the impact of maintaining a delicate balance between cultural reverence and technological progress ensures that the integration of AI into the Pran Pratistha ceremony respects and enriches the cultural legacy of Ayodhya's Ram Mandir. This research paper offers a comprehensive exploration of the contemporary application of Artificial Intelligence (AI) in Closed-Circuit Television (CCTV) camera surveillance during the Pran Pratistha ceremony at Ayodhya's sacred Ram Mandir. Focusing on the utilization of government records for intruder detection, the paper dissects the intricacies of the existing system. Furthermore, it envisions the potential future integrations of AI and the Internet of Things (IoT) for bolstering security measures in these sacred events. The study not only provides insights into current practices but also emphasizes the ethical considerations and opportunities that lie ahead.This paper explores how smart cameras with Artificial Intelligence (AI) are keeping the Pran Pratistha ceremony at Ayodhya's Ram Mandir safe. We'll look at how these cameras, using information from government records, can spot potential intruders. Additionally, we'll imagine how AI and smart devices (Internet of Things or IoT) could team up in the future to make security even better. This research aims to show the current safety methods and suggest ways to improve them while keeping things ethical and respectful
CAREER GUIDANCE AND ROADMAPS TO SUCCESS USING GPT-MODEL
Authors: Sharma Aman , Kumaar Aditya , Mishra Kanishk , Mishra Umang , Agarwal Rohit
Published: April 2024

In this growing world of technology and education, proper career counseling and guidance are primary for the bright minds of our nation. Our system is completely AI-driven and uses a GPT model to generate a personalized roadmap for the user. Many countries in the world are using LLMs to guide and provide career counseling to students based on their own interests. Users like conversations and an in-depth understanding of requirements. Our GPT model is trained for the Indian Education System. This GPT model, in the form of a chatbot on our portal, provides services of a career counsellor and offers real-time personalized roadmaps, defining prerequisites for any prestigious government or entrance exams. Easily available and accessible across all devices and platforms, this paper thoroughly explains the problem and the implementation of our solution to the problem of finding the proper route to one’s educational or career venture.
DIGITALLY EMPOWERED AGRICULTURE: INNOVATIONS, CHALLENGES, AND FUTURE DIRECTION
Authors: Singh Sakshi , Singh Shivanya , Tripathi Rachana , Chauhan Prachi
Published: April 2024

Modern technologies bring about a fundamental change in the ever-evolving landscape of global agriculture. Driven by a dedication to environmentally friendly farming practices, this combination increases farmer empowerment and productivity. Predictive modelling has become necessary today because to machine learning, which works on large data sets. Despite obstacles such as low land holdings and illiteracy among farmers, technology integration in Indian agriculture has enormous potential to create a digitally empowered future. Strategic interventions are essential for inclusivity and sustainability on this transformative journey.
DISASTER GUARD AI: A SYNERGISTIC SOLUTION FOR INTELLIGENT DISASTER MANAGEMENT
Authors: Kumar Rahul , Sharma Dr. Suman , Saxena Hima
Published: April 2024

Disaster Guard AI is a novel and synergistic approach to intelligent disaster management, combining advanced artificial intelligence, advanced sensor networks, and real-time data analytics. This innovative solution aims to revolutionize the way we prepare for, respond to, and recover from disasters. As the frequency and intensity of natural disasters continue to rise, there is an urgent need for advanced technologies to enhance disaster response and mitigation strategies. Disaster Guard AI combines machine learning algorithms, real-time data analytics, and advanced sensor networks to provide a comprehensive and adaptive approach to disaster preparedness, response, and recovery. The paper presents the conceptual framework, architecture, and potential applications of Disaster Guard AI, emphasizing its potential to revolutionize the way we approach disaster preparedness, response, and recovery. The escalating frequency and intensity of natural disasters have underscored the pressing need for advanced technologies to enhance disaster management strategies. By combining advanced machine learning algorithms, real-time data analytics, and state-of-the-art sensor networks, Disaster Guard AI aims to mitigate the impact of disasters and improve overall response efficiency. In conclusion, Disaster Guard AI is a pioneering solution that combines the power of AI, machine learning, and sensor technologies to revolutionize disaster preparedness, response, and recovery. Its potential to enhance resilience and mitigate the devastating impacts of various types of disasters underscores the urgent need for advanced and intelligent disaster management solutions.
DRIVING SUSTAINABLE INNOVATION: THE HYBRID RECOMMENDATION ENGINE APPROACH
Authors: Tiwari Mr. Sanjeev , Asrani Dr. Deepak
Published: April 2024

The need for efficient recommendation systems has grown in importance in the quickly developing digital age across a range of industries, such as social media, streaming services, and e-commerce. Conventional recommendation techniques, such content-based and collaborative filtering, have shown great promise but have several drawbacks as well. In order to improve the precision and variety of personalized suggestions, this research paper aims to investigate how these two paradigms can be combined to create a seamless hybrid recommendation engine. It does this by utilizing the ways in which collaborative and content-based approaches complement each other.The paper will conduct a comprehensive analysis of the theoretical underpinnings of content-based and collaborative filtering techniques. The goal of the research is to find synergies that may be used to maximize the combined effectiveness of theseparadigms in a hybrid model by dissecting their subtleties. We will carefully examine implementation options in order to provide useful insights into the hybrid recommendation engine's design and deployment.Important components of this research are the empirical assessments, which offer insightfulinformationonhowwellthehybridrecommendationengineperformsin real-world scenarios. The research will specifically concentrate on how well it can tackle the ongoing issue of the “cold start problem" which arises when traditional methods are unable to propose new users or things. Additionally, the study will evaluate how much the hybrid approach may improve suggestion quality and provide users with a more relevant and interesting content experience.This paper aims to provide a substantial contribution to the understanding of the design, optimization, and practical applications of hybrid recommendation systems byan extensive review of the literature and empirical analyses. The goal istoimproveour knowledge of how these technologies can be used successfully in a variety of application domains by doing this. In the end, this research aims to improve system performance and user happiness in the dynamic field of digital suggestions.
ENHANCING LEARNING OUTCOMES THROUGH EFFECTIVE E-LEARNING STRATEGIES
Authors: Prakash Ravi , Kumar Dr. Somesh
Published: April 2024

This research paper explores the dynamic realm of E-Learning and its pivotal role in modern education, aiming to enhance learning outcomes through effective strategies. Investigating the current state of E-Learning, the study addresses challenges such as technological disparities and the need for sustained learner engagement. It identifies key strategies, including pedagogical design, technology integration, collaboration, and continuous assessment, offering insights into their implementation for optimal results. Through the examination of successful case studies, the paper provides tangible examples of how these strategies can be applied in real-world educational contexts. As education continues to embrace digital transformation, this research serves as a valuable resource for educators and stakeholders, fostering a deeper understanding of E-Learning's potential and guiding the development of practices that maximize learning outcomes in diverse educational settings.
WORKFORCE ATTRITION AND ENGAGEMENT ANALYSIS USING MACHINE LEARNING
Authors: Tripathi Aniket Kumar , Kumari Pratima , Katiyar Purnima , Chaudhary Vijay Shanker , Sharma Manish Kumar
Published: April 2024

Organizations invest a lot of money in finding and developing skilled people. Every worker plays a crucial role in a company's success. On our dataset, we trained a model, and evaluated its performance using a variety of measures, including accuracy, precision. We also looked at the dataset to find the main causes of workers quitting their jobs. Employee attrition significantly impact an organization's productivity, costs, and brand value. It leads to an inexperienced workforce, disrupted work chains, delayed deadlines, and lower customer satisfaction, ultimately affecting the overall business. Our study will help understand attrition more thoroughly by predicting the chances of attrition of an employee and by looking at the analysis of the training data present they can know about the factors responsible for the attrition and thus try to increase employee engagement increasing retention rates
A REVIEW ON CHALLENGES IN RECENT OPINION EXTRACTION TECHNIQUES
Authors: Kumar Devendra , Ahamad Faiyaz
Published: April 2024

With the introduction of Web 2.0, people are now encouraged to share information about events in their community as well as to voice their opinions and beliefs. People utilize social media, blogs, review sites, news sites, user feedback portals, and other platforms to express themselves regarding events, locations, decisions made by leaders, policies, and other topics. Opinion extraction is a method that automatically extracts and analyzes people's sentiments from their thoughts. Manufacturers may find this collected data helpful in analyzing their products. Sentiment analysis, also referred to as opinion extraction, has been the subject of intense research over the past 15 years by academics, research communities, and service corporations in an effort to gather and examine public opinions and moods. This work focuses on the difficulties encountered in opinion extraction at many levels, including word-, sentence-, and language-related difficulties as well as some generic difficulties. The study provided clear examples and a thorough discussion of 30 hurdles, which aid in presenting problems for text or opinion extraction research. Opinion extraction tools are briefly presented in this section to help novice researchers get started. The published material spans the years 2004 to 2022.
HOUSE PRICE PREDICTION USING MACHINE LEARNING
Authors: Gupta Vivekanad , Yadav Abhishek , Nishad Vineeta , Haider Atebar
Published: April 2024

The real estate market, characterized by intense competition and continual pricing fluctuations, stands as a prime candidate for the application of machine learning techniques to achieve enhanced and accurate cost predictions. This paper focuses on the overarching objective of predicting the market value of real estate properties, particularly in Mumbai. The proposed system employs machine learning methodologies, specifically the Decision Tree Regressor, to establish a starting price for a property based on geographical variables.The research findings underscore the effectiveness of the Decision Tree Regressor model, revealing an impressive accuracy rate of 89%. This high accuracy level affirms the model's proficiency in predicting real estate market values in Mumbai. The significance of this research lies in its potential to assist clients in making informed investment decisions, enabling them to navigate the real estate market without relying on traditional brokers. The results emphasize the valuable role of machine learning, particularly the Decision Tree Regressor, in augmenting accuracy and efficiency in predicting real estate prices, thereby contributing to more informed decision-making in this dynamic market. The study ensures authenticity by adhering to plagiarism-free practices, both conventional and AI-based.
IMPACT OF URBAN VEGETATION IN SUSTAINABLE SMART CITIES DEVELOPMENT: A COMPREHENSIVE APPRAISAL
Authors: Ali Mr. Shadab , Ahmed Dr. Tasneem , Dwivedi Dr. Santosh Kumar , Singh Mr. Ajeet , Shrivastava Mr.  Ashwin Kumar
Published: April 2024

Urban vegetation is the crucial need for the sustainable development of green smart cities. In the current green smart cities, absence of urban vegetation causes unusual high temperature and adverse effect of human health like heat stroke, headache, dehydration, cardiovascular, respiratory etc. This article offers an extensive examination of image processing methods employed in the assessment of urban vegetation. Urban environments often suffer from a scarcity of green areas, underscoring the importance of comprehending and tracking vegetation's condition and distribution for both environmental and human welfare. Notably, high-resolution aerial and satellite imagery, especially satellite images, serve as invaluable resources for evaluating urban vegetation. Within this paper, we delve into cutting-edge image processing techniques used in urban vegetation research, with a primary focus on classification, segmentation, and change detection algorithms. The study scrutinizes a range of approaches for feature extraction and classification, encompassing methodologies like texture analysis, spectral indices, and object-based analysis. Additionally, we explore machine learning and deep learning integration, multi-sensor data fusion, and the adoption of emerging technologies such as LiDAR and hyper spectral imaging as limitations and future avenues in urban vegetation analysis. The insights derived from this review will prove beneficial to researchers, practitioners, and policymakers involved in endeavors aimed at monitoring and enhancing green spaces within urban areas.
BEYOND CODE: REVOLUTIONIZING DATA INTEGRATION FOR E-COMMERCE THROUGH A DYNAMIC JAVA PROGRAM
Authors: Maurya Raj Gaurav , Srivastava Ratan Rajan
Published: April 2024

To tackle the challenges of connecting e-commerce with databases, this research paper introduces a user-friendly Java program. It helps link Oracle databases to online sales platforms without developers getting stuck in fixed code. The program is flexible, adapting to different data formats used in web interfaces and mobile apps.
ONLINE EVENT TICKET BOOKING SYSTEM VIA QR CODE
Authors: Verma Himanshu , Dubey Ayushi , Singh Er. Sarika
Published: April 2024

This review paper explores the contemporary landscape of online event ticket booking systems, specifically focusing on the integration of QR codes as a streamlined and efficient solution. In recent years, the paradigm of ticketing has shifted towards digital platforms, and QR codes have emerged as a pivotal technology in this evolution. The paper investigates the advantages of QR code implementation in online ticketing, including enhanced security, ease of access, and improved user experience. Furthermore, it delves into the challenges and potential areas for improvement in this technology. Drawing from a comprehensive analysis of existing literature and case studies, this review aims to provide insights into the current state of online event ticket booking systems via QR codes, offering a valuable resource for researchers, practitioners, and industry stakeholders in the field.
INVESTIGATING THE USE OF BLOCKCHAIN FOR SECURE AND EFFICIENT SUPPLY CHAIN MANAGEMENT
Authors: Sachan Ritik , Singh Prachi , Sharma Niharika , Kaur Dr. Inderpreet
Published: April 2024

The global supply chain landscape has evolved significantly in recent years, becoming increasingly complex and vulnerable to various challenges such as fraud, counterfeiting, information asymmetry, and inefficient processes The purpose of this research is to ascertain how blockchain technology might raise the efficacy and security of supply chain management. This article integrates concepts from information technology, logistics, and business management to investigate the potential applications of blockchain in supply chain management. It looks at organisational and regulatory issues along with technological aspects of blockchain implementation, like consensus algorithms and smart contracts. Furthermore, the research project assesses case studies and real-world examples where blockchain has been successfully deployed in supply chain operations. By analyzing these cases, the project aims to identify best practices, potential pitfalls, and lessons learned, offering insights for organizations considering blockchain adoption in their supply chain processes. Ultimately, this research contributes to the growing body of knowledge about how blockchain technology may revolutionise supply chain management and emphasises the importance of collaboration among industry players.
A SMARTPHONE SENSOR BASED REAL-LIFE HUMAN ACTIVITY RECOGNITION SYSTEM USING DEEP NETS METHOD
Authors: Zainab Dr. Kaneez , Srivastava Ratan Rajan
Published: April 2024

The proliferation of sensor devices in recent years has made Human Activity Recognition (HAR) a hotspot for academic interest. Smartphones with built-in sensors make it possible to employ such sensors for activity detection tasks like assisting the elderly with their everyday tasks. A plethora of high-tech sensors, such as global positioning systems (GPS), cameras, accelerometers, microphones, light sensors, and compass, are standard on these smartphones. Activity recognition is a promising field of study that might be used to provide consumers with flexible and efficient services. The purpose of our research is to evaluate a system that makes use of accelerometers, which are acceleration sensors that are built into smartphones. For the purpose of running the model and understanding six distinct human activities through supervised machine learning classification, twenty-six users' accelerometer data is collected while they go about their daily lives, including sitting, standing, lying down, walking, and climbing and descending stairs. Following the merging and aggregation of the sample data, supervised machine learning techniques were employed to generate prediction models from the instances. To get beyond the limitations of the lab, we used the Google Android platform and the Physics Toolbox Sensor Suite to gather this time series data. In this work, we take a look at how Machine Learning and Deep Nets have been used to address issues with human activity identification using smartphone sensors. Furthermore, we proved that data collected with lower frequencies can still serve their intended purpose. Our most basic Deep Nets model yielded a maximum accuracy of 95.71% for the male dataset and 94.62 % for the female dataset.