bluuebunny/crossref_metadata_2025 huggingface dataset:
نبی کریم ﷺ کا وفد نجران کے ساتھ تعامل کا احادیث کی روشنی میں تحقیقی مطالعہ
Authors: Hassan Syed Shah , Sajjad Hafiz Muḥammad
Published: January 2025

The event of the delegation of Najrān has multi-dimensional aspects, i.e. the aspect of dogma and reasoning, jurisprudence, ethics and morality, preaching and teaching, psychology and sociology, diplomacy and political strategy etc. The event is imbibed with the political and administrative wisdom of the Holy Prophet Muḥammad (Ṣal  Allah-u-‘alaihe wa sallam). It contains Ṣaḥīḥ, Ḥasan and Marfoo’ Muttaṣil narrations. Though some of them are Dha’if but they have been invigorated by the sturdy and Ṣaḥīḥ ones. Mainly there are five types of narrations, i.e. (1) the narrations of the invocation of the curse, (2) the request for a reliable representative of Islamic government, (3) the gold-ring prohibition for men, (4) mutual contract between the Holy Prophet Muḥammad (Ṣal Allah-u-‘alaihe wa sallam) and the Christians of Najrān, and (5) the inquiry about the timing of the prayers. The delegation of Najrān visited the Holy Prophet Muḥammad (Ṣal Allah-u-‘alaihe wa sallam) more than once. The largest part of the delegation was well-dressed and consisted of nearly sixty people. They asked questions and the Holy Prophet Muḥammad (Ṣal Allah-u-‘alaihe wa sallam), answered them accordingly under the revelation of Allah۔
حضرت ابو بکر صدیق رضی اللہ عنہ کی قلت روایت سے متعلق اعتراضات کاتجزیاتی مطالعہ
Authors: Shabana Razia , Taiba Saira
Published: January 2025

As a source of Islamic law, the word Ḥadīth  is not a necessary introduction in academic circles. It has fundamental importance in Islām. The companions of The last Prophet used to say by name, "Did we see the Holy Prophet (peace and blessings of Allah be upon him) doing this?" Sometimes they used to say that we used to do this during the time of the Holy Prophet (peace and blessings of Allah be upon him) and sometimes it happened that the companions' religious deeds were considered a sign of the teachings of the Holy Prophet (peace and blessings of Allah be upon him). When the knowledge of Ḥadīth  became embedded in books and writings, it did not require hard work in memorizing it orally and copying it, which was very important from a religious and scholarly point of view before the formal editing of this knowledge. But this does not mean that the principle of oral transmission and tradition does not remain, but it is a fact. It continued to be transmitted to the living disciples, but this natural rotation of circumstances and the principled convenience of the writings of Ḥadīth  left only oral memory behind, collections of Ḥadīth s were prepared, guidance was obtained from the Ḥadīth  after the Qur'an. If there was room for doubt, the companions of the Prophet (peace and blessings of Allah be upon him) would have been consulted. Despite this, mu'tarzin left no stone unturned to prove to you the disbelievers.
انٹر نیٹ اور سوشل میڈیا کے مثبت اور منفی اثرات کا اسلامی تعلیمات کی روشنی میں جائزہ
Authors: Gulzar Rukhsar , Ahmad Matloob
Published: January 2025

The internet and social media have become integral components of modern society, influencing communication, education, entertainment, and business on a global scale. This article explores both the positive and negative uses of these platforms, highlighting their profound impact on individuals and communities. On the positive side, social media enables global connectivity, fosters online communities, supports educational and professional networking, and serves as a platform for social activism. It provides opportunities for knowledge sharing and personal growth, creating spaces for creativity and expression. However, the internet and social media also pose significant risks, including the spread of misinformation, cyber bullying, privacy concerns, and addiction. The constant barrage of digital content can lead to mental health issues, such as anxiety and depression, particularly among young users. This article critically examines these dual aspects of internet and social media use, emphasizing the need for responsible engagement and digital literacy. By understanding the benefits and drawbacks, individuals and society can better navigate the digital landscape, fostering a healthier and more productive online environment.
Energy Efficient Large Language Models: Advancements and Challenges
Authors: Agrawal Vishakha
Published: January 2025

Abstract—The rapid growth of Large Language Models

(LLMs) has revolutionized the field of natural language process-
ing (NLP), achieving unparalleled levels of linguistic nuance and

precision. The debut of ChatGPT, a cutting-edge LLM, has cat-
alyzed widespread adoption across diverse applications. Built on

the GPT-3.5 architecture, ChatGPT’s 175 billion parameters were
honed through reinforcement learning from human feedback,
yielding remarkable performance. Nevertheless, the escalating

scale and intricacy of LLMs, epitomized by ChatGPT’s substan-
tial parameter count, have sparked pressing concerns regarding

their ecological footprint and energy expenditure. As demand for
LLMs continues to surge, developing sustainable, energy-efficient
solutions is crucial to mitigating their environmental impact.
This paper undertakes a comprehensive examination of energy
consumption monitoring, challenges, and areas for improvement
necessary for the development of energy efficient Large Language
Models.
Index Terms—BERT, Large Language Model, Energy-aware
training, GPU, Footprint, GPT-3, Profiling, CO2 emissions
The Role of Artificial Intelligence in Enhancing Commodity Trading and Risk Management Solutions
Authors: Arora Manu Handa and Ridhima
Published: January 2025

This paper explores the transformative impact of Artificial Intelligence (AI) on commodity trading and risk
management. It delves into how AI technologies can enhance the efficiency and effectiveness of front office, middle

office, and back office operations. The paper discusses various applications of AI, including price forecasting, real-
time market insights, risk assessment, fraud detection, and the generation of Business Intelligence (BI) reports and

dashboards. Additionally, it examines how AI can automate reconciliation processes, simulate prices, and audit
master and transactional data for compliance purposes. Real-life examples of AI-enhanced Commodity Trading and
Risk Management (CTRM) software are provided to illustrate these benefits. The paper also addresses the challenges
and future prospects of AI implementation in this sector.
Keywords
Artificial Intelligence, Commodity Trading, Risk Management, CTRM, Price Forecasting, Market Insights, Risk
Assessment, Fraud Detection, Business Intelligence, Reconciliation, Price Simulation, Data Auditing, Compliance,
Automation.
Advancing Robotics-Enabled STEM Education in K-12: Frameworks for Comprehensive Learning Outcomes Assessment and Inclusivity
Authors: Chandak Parth
Published: January 2025

This systematic literature review examines the integration of robotics in K-12 STEM education, focusing on
assessment frameworks and inclusive teaching practices. Through analysis of empirical studies from 2006 to 2021,
we identify key themes in educational robotics implementation, including technical skill development, cognitive
growth, and social-emotional learning. The review synthesizes findings from 15 selected papers, highlighting the
effectiveness of constructivist and constructionist approaches in robotics education. Particular attention is given to
assessment methodologies that promote inclusive learning environments and support diverse student populations.
The findings reveal that successful robotics integration requires comprehensive assessment frameworks that balance
technical competency with broader educational outcomes. We present structured frameworks for evaluating student
engagement, learning outcomes, and program effectiveness, while emphasizing the importance of adaptable
teaching strategies that accommodate different learning styles and abilities. This review contributes to the growing
body of knowledge on educational robotics by providing evidence-based recommendations for implementing
inclusive, assessment-driven robotics programs in K-12 education.
Keywords
Educational robotics, Assessment frameworks, Systematic review, K-12 STEM education, Inclusive education,
Learning outcomes, Constructivist learning, Student engagement, Robotics integration, Educational technology
Implementing Secure and Scalable APIs in Java Spring Boot: RESTful vs. GraphQL Services
Authors:   Senior Software Engineer (Independent Researcher), Bhosale Pradeep
Published: January 2025

As modern web applications continue to evolve, secure and scalable APIs have become essential building blocks for
dynamic, data-driven platforms. Java Spring Boot, renowned for its developer-friendly approach and extensive
ecosystem serves as a common foundation for implementing microservice APIs. Two prominent architectural styles,
RESTful and GraphQL, each offer distinct approaches to request handling, data fetching, and schema management in
a microservices or distributed environment. This paper presents an extensive study of REST vs. GraphQL for
developing secure and scalable APIs in Spring Boot, focusing on performance, data modeling, ease of adoption, and
real-world pitfalls. We examine security best practices covering authentication, authorization, and data encryption
while highlighting scaling techniques such as load balancing, container orchestration, and caching. Through diagrams,
code snippets, and references to real-world scenarios, we provide a practical guide for architects and developers aiming
to choose the right approach. In doing so, we also discuss known anti-patterns that undermine security or hamper
throughput, and propose best practices to ensure robust, future-proof APIs.

Keywords
Java Spring Boot, REST, GraphQL, Microservices, Security, Scalability, API Design, Authentication, Authorization,
Cloud-Native
Metrics Catalog - Enabling Reusability And Consistency In Enterprise Analytics
Authors:   AWS Data Platform  Amazon Web Services, Amazon.com Corp LLC Seattle, United States of America, Thangaraju Dinesh
Published: January 2025

This paper explores the concept and implementation of a metrics catalog as a critical component in ensuring
reusability and consistency in enterprise analytics. As organizations grapple with increasing data volumes and
diverse analytical needs, maintaining consistent definitions and calculations for key business metrics becomes
paramount. We examine how a centralized metrics catalog can serve as a single source of truth, fostering
collaboration between data producers and consumers while reducing redundancy and inconsistencies. Key aspects
discussed include metadata management, version control, data lineage tracking, and integration with existing data
governance frameworks. The paper also addresses challenges in adoption and strategies for successful
implementation across large-scale enterprises.
Index Terms: metrics catalog, data reusability, analytics consistency, enterprise data management, data
governance, metadata management, data quality (key words)
Use of Cleanrooms for Privacy-Safe Measurement of User-Based Randomized Control Trials
Authors: Chivukula Varun
Published: January 2025

The increasing need for user privacy in the digital age has challenged conventional approaches to measuring the
effectiveness of user-based Randomized Control Trials (RCTs). Cleanrooms, designed to ensure data security and
privacy, offer an innovative solution for conducting RCTs while adhering to stringent privacy standards. This paper
explores the role of cleanrooms in privacy-safe measurement of RCTs, discussing their architecture, implementation,
and the implications for research and business practices. It articulates the technical guardrails necessary for cleanroom
functionality and effectiveness while addressing challenges and proposing recommendations for optimizing their use
in diverse settings. The discussion is substantiated by references to the latest advancements in cleanroom technology
and privacy-preserving analytics.
Keywords: Cleanrooms, CCPA, GDPR, Randomized control trial(RCT)
MIGRATING BANKING SYSTEMS TO AZURE: CHALLENGES AND SOLUTIONS
Authors:   Vice President, Lead Software Engineer, Kulkarni Vikas
Published: January 2025

This paper explores the intricacies of migrating banking systems to Microsoft Azure. It highlights challenges such

as compliance, data security, and operational risks, while proposing solutions to address these issues. With real-
world examples, this paper delves into the design and implementation of resilient, scalable, and fault-tolerant

architectures tailored for banking systems. It emphasizes security considerations, operational excellence, and the
significant impact of cloud-native features in modernizing legacy systems.
Synthetic Data Generation: Enabling Secure Use of Data for AI, Machine Learning, and Testing
Authors:   Dinesh Thangaraju AWS Data Platform  Amazon Web Services, Amazon.com Corp LLC Seattle, United States of America, Thangaraju Dinesh
Published: January 2025

This paper explores the critical role of synthetic data generation in enabling secure and privacy-preserving use of
data for artificial intelligence, machine learning, and software testing applications. As organizations face
increasing regulatory pressures and data privacy concerns, synthetic data emerges as a powerful solution to
maintain data utility while mitigating risks associated with sensitive information. We examine the challenges in
using real-world data, the need for synthetic data generation, and technical approaches to implementing robust
synthetic data solutions. The paper also addresses how synthetic data can enhance AI and ML model development,
improve testing processes, and support overall data governance strategies in enterprise environments.
This paper explores the challenges organizations face in accessing secure and compliant data, highlights the need
for synthetic data, and presents a technical framework for implementing synthetic data generation solutions.
Furthermore, it outlines metrics for measuring effectiveness and provides insights into the future potential of
synthetic data.
Index terms: synthetic data, data privacy, machine learning, artificial intelligence, data security, data
augmentation, generative models (key words)
Calibrating Marketing Mix Models (MMMs) with Incrementality Tests
Authors: Chivukula Varun
Published: January 2025

Marketing Mix Models (MMMs) are essential tools for determining the effectiveness of various marketing activities,
but their reliance on aggregated data can limit causal insights. Incrementality tests, on the other hand, offer robust
causal evidence at a granular level. This paper proposes a systematic approach to calibrating MMMs using
incrementality test results to enhance predictive accuracy and decision-making. We also emphasize the evolving
importance of MMMs in the context of heightened privacy regulations and changes such as Apple’s App Tracking
Transparency (ATT) framework. We outline a step-by-step methodology, discuss potential challenges, and provide
a case study to demonstrate the practical application of this integration.
Keywords: MMM, ATT, GDPR, Randomized Control Trials, Bayesian Priors
Microservices in Banking: Challenges and Best Practices in Scaling Core Applications
Authors:   Vice President, Lead Software Engineer, Kulkarni Vikas
Published: January 2025

The banking industry is undergoing a rapid digital transformation, with microservices architecture at the forefront
of scalable, resilient, and flexible application development. This paper explores the critical challenges and best
practices in implementing microservices for banking systems, focusing on the scalability of core applications.
Through in-depth analysis, detailed metrics, and real-world examples from major banks such as JPMorgan Chase
[3] and HSBC [4], we examine the unique demands of the banking sector, propose effective solutions, and outline
an optimized architecture. Furthermore, we provide empirical evidence to demonstrate the benefits of
microservices, highlighting their role in driving operational efficiency, enhancing performance, and improving
customer satisfaction.
Intelligent Automation for Retail: Solving Inventory Management Challenges with RPA
Authors: Singh Chandra Prakash
Published: January 2025

Intelligent Robotic Process Automation (IRPA) integrates Artificial Intelligence (AI) with Robotic Process
Automation (RPA) to automate complex, unstructured tasks, enhance decision-making, and adapt to evolving
scenarios. This paper explores how IRPA can address the challenges of retail inventory management by ensuring
real-time stock updates, improving replenishment accuracy, and optimizing processes. A framework for IRPA
adoption was developed through extensive research and expert consultations, highlighting key factors such as
accuracy, human involvement, and task standardization as primary drivers for successful implementation. Secondary
considerations, including digital data input, system integration, and cost implications, were also analyzed. The study
leverages Relative Importance Index (RII) analysis and Causal-Loop Diagrams (CLD) to provide actionable insights
for organizations. This framework serves as a practical guide for leveraging IRPA to transform inventory
management, improve operational efficiency, and enhance value creation.
Keywords: Retail, Inventory Management, Robotic Process Automation (RPA), Intelligent Automation, Stock
Replenishment, Real-Time Updates, Optimization, Digital Transformation, Process Analysis Framework.
Integration of ESG Data in the Retail Sector (Essential for Sustainable business and Risk Management)
Authors: Kalyanam Ashok Kumar
Published: January 2025

The ESG data integrated into the
retail industry have grown as an essential driver
of sustainable business practices and robust risk
management strategies. With sustainability
concerns being highly critical for businesses
around the world, retail organizations have taken
up the ESG metrics as the yardstick to measure,
report, and act upon environmental and social
impact, ensuring good governance. It explains
how AI-driven business intelligence integrates
ESG factors for the improvement of sustainability
metrics in the retail industry, focusing on how
such integration supports the creation of
sustainable business strategies and improves
financial performance. It discusses challenges and
opportunities in adopting sustainability reporting
and ESG metrics, drawing on global evidence
from retail performance-related studies and
providing insight into how ESG adoption may
influence operational efficiency, consumer trust,
and long-term value creation. The study also
underlines the role of AI in the automation of ESG
factor scoring; it thus facilitates decision-making,
transparency, and risk management. This paper
also articulates how ESG integration relates to
better performance of the firm within a transition
towards the Circular Economy and vice versa in
the retail sector.

Keywords:ESG, Retail Sector, Sustainable Business
Practices, AI-driven Integration, Risk Management,
Sustainability Reporting, Circular Economy,
Business Intelligence, Firm Performance, and
Corporate Social Responsibility.
Expanding Horizons in Prompt Engineering: Techniques, Frameworks, and Challenges
Authors:   Stamford, CT, USA, Wu Nan
Published: January 2025

Abstract—Prompt engineering is a critical method
for guiding large language models (LLMs) to perform
diverse tasks effectively. This paper reviews prompt
engineering techniques, including example-driven
approaches, logic steps, and modular frameworks,
highlighting their adaptability and limitations. It
emphasizes the need for robust evaluation metrics,
addressing gaps in reasoning quality and task
adherence. By proposing novel evaluation approaches
such as token-level entropy, this study advances
understanding of prompt effectiveness, paving the
way for more reliable, ethical, and domain-specific
LLM applications.
Keywords—prompt engineering, language models,
chain of thought, AI benchmark
DIGITAL TWINS IN CONSTRUCTION: CREATING REAL-TIME REPLICAS OF LARGE-SCALE PROJECTS
Authors:   Chesapeake, USA, Pandit Aditya
Published: January 2025

Integrating digital twins in construction represents a transformative leap in project management and operational
efficiency. These dynamic virtual replicas of physical assets enable real-time monitoring, performance simulation,
and optimization throughout the construction lifecycle. Despite technological, organizational, and financial
barriers, their adoption shows promising results, including significant cost savings and operational improvements.
This paper explores how digital twins optimize planning, enhance risk management, and allow remote inspections,
contributing to efficiency, sustainability, and cost-effectiveness. Emerging applications in disaster resilience and
economic impact, combined with future research directions like AI integration and urban infrastructure modeling,
underscore their potential to revolutionize the construction industry.
Keywords—Digital twins, construction management, real-time monitoring, disaster resilience, economic impact, AI
integration, sustainability, Building Information Modeling (BIM), Internet of Things (IoT).
Urban Planning and Development: A Case Study of Sustainable Zonal Development and Infrastructure Design for Hindaun City (North Zone)
Authors:   Research Scholar, Jagannath University Jaipur, Prajapat Pooja
Published: January 2025

This dissertation examines the urban planning and development strategies for Hindaun City's North Zone through the creation of a Zonal Development Plan (ZDP) for 2036. Hindaun City, a significant urban center in Rajasthan, is experiencing rapid population growth and urbanization, necessitating a comprehensive and sustainable development plan. The Master Plan for Hindaun City 2036 provides a broad framework, and this dissertation delves into the specific proposals for the North Zone, known as Zone A.

The research employs a multi-method approach, including Geographic Information System (GIS) mapping, analysis of existing conditions, stakeholder consultations, and policy reviews. The study identifies critical areas for intervention in residential, commercial, industrial, and recreational sectors, proposing detailed land use plans and infrastructure improvements. Special attention is given to enhancing social and physical infrastructure, addressing environmental sustainability, and ensuring equitable development.

Key findings reveal that while Hindaun City has made significant strides in urban development, challenges such as inadequate infrastructure, unplanned growth, and environmental degradation persist. The proposed ZDP aims to address these issues through targeted policies and strategic interventions. The dissertation concludes with recommendations for implementing the ZDP effectively, emphasizing the need for continuous monitoring, stakeholder engagement, and adaptive management to ensure the plan's success.

By providing a detailed case study of Hindaun City's North Zone, this dissertation contributes to the broader discourse on urban planning and development in rapidly growing cities. The findings and recommendations offer valuable insights for policymakers, urban planners, and researchers focused on sustainable urban development

Key Words: urbanization , GIS , ZDP , policymakers
Mobile Camera Application to Monitor Residential Society Vehicle Activity
Authors:   Student in computer and engineering, presidency university, Bangalore, Srujan Kaluva
Published: January 2025

This project presents a machine learning-enabled surveillance system designed for real-time monitoring and tracking of vehicles in urban and residential environments. With rapid advancements in autonomous technologies, there is an increasing demand for intelligent systems that can enhance public safety, streamline traffic management, and provide secure access control within private and public spaces. The proposed system leverages deep learning algorithms for vehicle detection, classification, and speed monitoring, while utilizing IoT infrastructure to enable seamless data collection and remote access.

Key words- Machine Learning, IoT, Surveillance System, Vehicle Tracking, Autonomous Technology, Deep Learning, Real-time Monitoring, Smart City, Traffic Management, License Plate Recognition, Predictive Analysis, Access Control, Situational Aware
Smart Communication E-Commerce Website
Authors:   Student in computer and engineering, presidency university, Bangalore, Shakir Mohamad
Published: January 2025

This paper considers the integration of digital platforms as a way of empowering rural artisans through the gap created between traditional craftsmanship and global markets. The system will include easy-to-use web and mobile interfaces, effective management tools for the products, and real-time analytics to facilitate the selling of products on the platforms. It will address limited market access, lack of technical knowledge, and poor inventory management to ensure the platform promotes economic growth and preserves cultural heritage. In this regard, the study outlines the importance of technology in the development of a rural area. It focuses on scalability, accessibility, and data-driven strategies as ways to promote artisans' participation in a competitive digital economy.

Key Words:  Rural artisans, digital platforms, traditional craftsmanship, market access, cultural heritage, inventory management, sales analytics, rural development, web and mobile interfaces, economic empowerment
Herbal Facial Toner: A Review
Authors:   Department of Pharmacy, Shivlingeshwar College of Pharmacy, Almala, sagar Anuja
Published: January 2025

Herbal facial toners have gained popularity for their natural and soothing properties, offering an effective solution for skin care. These toners, derived from plant-based ingredients, help to refresh, hydrate, and balance the skin's pH while providing essential nutrients. Rich in antioxidants, vitamins, and minerals, herbal toners are gentle on the skin, making them suitable for all skin types, including sensitive skin. By incorporating botanicals such as aloe vera, witch hazel, rose water, and chamomile, these toners not only cleanse the skin but also promote healing and calm irritation. Their natural formulation ensures minimal side effects, unlike harsh chemical-based alternatives. Herbal facial toners play a vital role in maintaining healthy, radiant skin while offering a holistic approach to beauty care.

Keywords: Herbal facial toner, Plant based ingredients, Anti-inflammatory, Eco-friendly
Evaluation of socio-economic inequalities in the use of maternal health services in rural and peri-urban areas of Birbhum district, West Bengal, India
Authors:   Government of West Bengal and Research Scholar in Anthropology, Ranchi University, Jharkhand, India, Majumdar Saikat
Published: January 2025

Inequalities in maternal health care services prevent women of reproductive ages from accessing required care. The existence of equitable distribution channels can substantially diminish these discrepancies. Since the implementation of National Rural Health Mission (NRHM) in 2005, Maternal Mortality Ratio has significantly declined in India through a noticeable improvement in maternal health care services. However, India lags behind to achieve the target of millennium development goal (MDG5) to reduced maternal mortality ratio and improve universal reproductive health by 2015 The objective of this study was to evaluate the socio-economic inequalities, and factors associated to the use of maternal health services in rural and peri-urban areas of Birbhum district, West Bengal.
Voice Based Hot Cold- Water Dispenser Using Arduino
Authors:   ECE & IARE, Veeraswamy D
Published: January 2025

Technology is a never-ending process. To be able to design a product using the current technology that will be valuable to the lives of others is a huge contribution to the neighbourhood. Voice Based Water Dispenser Automation method using controller is the plan will be very useful for old age people and disabled people, basically one’s who cannot achieve basic actions efficiently. It is the idea Corresponds to the new area of automation and technology. This presents the design and implementation of a low cost but flexible Secure voice based hot and cold-water dispenser system. The Between the cell phone and the controller board is wireless. Voice Command sends from mobile to the micro controller, to understand whether the water required by the person should be hot or cold. The Micro controller processes the information to the IR sensor to Determine where the glass is placed below the pipe or not. The method uses IR sensors to detect the presence of stream beaker and then the IR sensor sends the signal to the micro controller about the presence of the glass, accordingly the motor starts and the  Water flows though the pipes from the particular jar (hot/cold). Key Words: IR sensor, Water glass, Micro controller, Blue-tooth.
MENTAL HEALTH AI CARE CHATBOT
Authors:   Ajeenkya D.Y.Patil School Of Engineering  Pune Maharashtra, Purkar Ayesha Shehbaz
Published: January 2025

Always Mental disability and Mental health care have been overlooked. This is puzzling considering that 8% of the world's population suffers from mental impairments, which are widespread. A scalable option that offers an interactive way to engage consumers in behavioral health interventions powered by artificial intelligence is a chatbots.

Anxiety, stress, etc. provides a critical first step in enhancing chatbot design and revealing the advantages and disadvantages of the chatbots. In this report, a customized chatbot framework is proposed with a blended neural network design. The recommended chatbot is a virtual health assistant & it is cost-effective and less time-consuming. It includes chat features, many languages voice input & a recommendation tool to improve users’ mood.

To improve the performance of the proposed system, the chatbot is further integrated with
Assistive Communication Web App: A Multi-Model Solution for Individuals with Disabilities”
Authors:   Presidency University  Bangalore, India, N Bhanu Prakash
Published: January 2025

The Assistive Communication Web App is an innovative platform designed to address the communication challenges faced by individuals with speech, hearing, and motor impairments. By integrating advanced technologies such as speech recognition, head-gaze tracking, and gesture-based sign language recognition, the app provides real-time speech-to-text, text-to-speech, and gesture-to-text functionalities. This research outlines the app's system architecture, methodology, and user interface, emphasizing its potential to enhance accessibility and empower users with greater independence. Through its multi-modal approach, the web app fosters inclusivity and sets a new benchmark for assistive technologies.

Keywords: Assistive communication, Speech-to-text, Text-to-speech, Sign language recognition, Head gaze tracking, WebGazer.js, Real-time interaction, Gesture recognition, MediaPipe FaceMesh, TensorFlow HandPose, Web Speech API, Real-time transcription, Multilingual support, Cross-platform compatibility, Emotion detection, User-centered design, Modular architecture
Wireless Communication based Water Surface Cleaning Boat
Authors:   ECE & IARE, Abhiram S.
Published: January 2025

—It is very dreadful that huge liters of excrement are being deposited into the rivers across our country. The pollutants and toxins are assisting the amassing of the toxicant in water thus affecting aquatic life. Only when the detritus floating above the water bodies become persistent, the governments’ plan of action is set about and unfortunately by that time, the life cycle in that water body breaks. This research work focuses on deploying a solution for the unfavorable effects on the floating refuse, and henceforth reduces the pollution caused due to the unsettled wastes including plastics and plant weeds. The project aims to develop a waste collecting boat to scavenge the water body and abolish the floating waste. This is done by employing a conveyor belt connected to the front line of the boat. Boat movement is established using a remotecontrol application by incorporating an RF module along with an encoder-decoder pair. This method will reduce the cost of operation because of less human involvement and labor. Major challenges in implementing the boat are compact mechanical design and reliable power supply. The principle feature of this boat is the collection of refuse and floating weeds from the surface of the water into a basket which is removable [2].

Key Words: IoT (Internet of Things), Water Surface Cleaning, Gear Motors, Conveyor System, Arduino Uno, IR Sensors, Boat Controller, Arduino IoT Cloud, Garbage Collection, Autonomous Navigation, Remote Monitoring, Environmental Cleanup, Sustainability, Pollution Control, Scalable Solution, Real-time Feedback, Smart Technologies, Automation, Water Pollution, Adaptive Systems
Monitoring Vehicle Activity in Residential Societies
Authors:   Department of Computer Science and Technology, Presidency University, Bengaluru, India, SHAIJAN SHARON
Published: January 2025

An increase in vehicles within residential societies has resulted in issues, including congestions during parking, unpermitted vehicle access, and raised security concerns. For such issues, this paper has looked into developing a low-cost mobile application camera system intended to track the vehicle activity in such communities. Low in terms of cost, efficient with regards to vehicle management as well as security, and has the ability to utilize free-of-charge mobile technologies in tandem with strategically place camera systems around the community, which can track a vehicle's movement and provide on-the-spot recording and indication of unauthorized entry with respective alerts to residents and relevant security personnel. The mobile application is also a user-friendly interface by which residents can monitor the real-time footage, can receive alerts, and easily manage access to parking areas. Moreover, the system promotes community engagement by allowing participation in the monitoring process. It enhances vigilance generally. This solution is not only affordable but also scalable, thus accessible to residential societies of a wide variety. This would enable the system to focus more on cost-effectiveness and user-friendliness while, at the same time, improving security, vehicle management, and contributing to an organized, safer living space for its residents.
Customer Service Chatbot With ML
Authors:   Presidency University, Bangalore, N Thrimoorthy Dr .
Published: January 2025

In the modern business landscape, customer support plays a critical role in shaping customer experiences and building brand loyalty. With the growing demand for instant responses and 24/7 availability, organizations are increasingly exploring artificial intelligence (AI) solutions to enhance the efficiency and effectiveness of their customer service operations. This work aims to design and develop an intelligent customer support chatbot that leverages machine learning (ML) and natural language processing (NLP) techniques to deliver automated, yet personalized, customer assistance. The core objective is to build a machine learning-based chatbot capable of understanding and responding to a wide array of customer queries in real-time. Traditional customer service models often require significant human resources, leading to high operational costs and long response times. By integrating an AI powered chatbot into the customer support process, businesses can streamline operations, reduce response time, and provide customers with timely, accurate information.

Keywords:
·       Natural Language Understanding (NLU):

The chatbot uses NLTK and Speech recognition to process and understand the user's input in natural language. It can identify the intent and extract key details from user queries to provide relevant responses[6].

·       Integration in Flask Backend

Flask supports the light-weight fast backend with requests that routes those to the correct machine learning model. It manages all the interactions with the users by processing inputs and passing on[4].

·       Model Training of Machine Learning Model:

The OpenAI models are trained on labelled data for the improvement in recognizing intents of the chatbot. user and giving suitable responses of the model keeps learning and evolving as it processes new data of the users[3].

·       Real-Time Error Handling:

The system handles errors such as unrecognized queries or technical issues efficiently. It logs errors and provides feedback to the user, ensuring a smooth experience[2].

·       Sentiment Analysis:

Based on NLTK, it analysis the sentiment of all user inputs to establish possible emotions such as frustration and satisfaction. This will provide the chatbot with means to respond in addition to adjusting its tone[4].
HEALTH NEXUS
Authors: BIRADAR HARSHA S
Published: January 2025

This feasibility study entitles us to identifying the type of health-related analytics that we can deliver through the application of both AI-based analytics in healthcare as well as other health areas of HMOs. AI is employed in this study for facilitating in diagnosis of different diseases through the analysis of the records of the patients. The implementation of AI in the healthcare sector is called health analytics. For instance, one can compare the records of patients and find characteristics that tie the two together. This is a case study for a pilot implementation of the City of Chicago´s hepatitis screening program. It differentiates the people who have been vaccinated from the people who need to be vaccinated but are not yet vaccinated. In this way, the environment in Chicago would be extremely clean according to our plan. This research would also allow the clinics to notify the respective patients on time for the success of the prevention, treatment, and other medical interventions.

Keywords - Healthcare Analytics, AI-Driven Insights, Role-Based Access, Real-Time Predictive Analytics, Web Application Development, Flask Framework, Machine Learning Models
IOT based Smart Pothole Detection System using ESP32
Authors:   ECE & IARE, Veeraswamy D
Published: January 2025

This project presents a comprehensive pothole detection and navigation system aimed at improving road safety and reducing vehicle wear and tear. The system utilizes an ESP32 microcontroller, a gyroscope, and a GPS module, integrated into car tires to enable real-time detection of potholes. The gyroscope measures vibrations and deviations caused by uneven road surfaces, while the GPS module pinpoints the exact geographic location of the detected potholes. The system also measures the depth and width of the potholes to provide detailed information. This data is transmitted wirelessly to a central server, where an AI-based algorithm processes it to eliminate duplicate entries and filter out false detections. Once validated, the pothole information is mapped onto a user-friendly mobile application, providing users with real-time updates on road conditions. By allowing users to choose safer and smoother routes with minimal potholes, this system ensures enhanced driving safety, reduced maintenance costs, and a more efficient travel experience. Additionally, the mapped pothole data can serve as valuable feedback for road maintenance authorities to prioritize repairs and improve infrastructure.

Key Words:  pothole detection, ESP32, gyroscope, GPS, AI, road safety.
ELECTIVE RECOMMENDATION SYSTEM
Authors:   Presidency university, Yelahanka, Bengaluru, Karnataka, India, John Josephine
Published: January 2025

Our digital lives in the modern world are fueled by data. We use recommendation engines to help us choose which goods, services, and information to purchase, and they have become an integral part of our digital life. This paper has covered a lot of ground on the changing field of deep learning-based recommendation systems. The evaluation of recommendation systems, individualized recommendation methods, and the integration of several data sources are the primary areas of study. The ethical and privacy issues surrounding recommendation systems are also covered. A critical evaluation of the state of recommendation systems today has been provided in order to provide insightful information for future developments in this field.

Keywords: Recommendation systems, collaborative filtering, elective course recommendation, Singular Value Decomposition (SVD), personalized recommendations, academic decision-making, machine learning, data integration, ethical concerns, performance evaluation, RMSE, MAE
Uplifting a Farmer through Connected Ecosystem
Authors:   Student of Presidency University Bengaluru, India, U ShriNidhi
Published: January 2025

This project consists of developing a unified platform which can help farmers and consumers to come on the same platform and buy the agricultural products directly from the farmers. The application offers smooth online payment, user and farmer profile administration and real time inventory up to date. They are also key in establishing trust as they onboard verified farmers, and upload schemes which are advantageous to the farmers. Further down the line, vehicle and land renting functionalities, as well as tiny fertilizer management, will give farmers more support. Using this app, farmers can rent so agricultural machinery that includes tractor and harvesters at nominal costs finally using technology which was earlier not affordable for them. Farmer's use user friendly interfaces and robust backends to communicate with rental providers, manage bookings and track real time updates. The system is administered by an administration access pool who are responsible for overseeing the system (transaction transparency and efficient dispute resolution) as well as providing the users with the freedom to explore the ecosystem and contribute to it when they wish. We aim to help the agricultural community eliminate costs, increase production of goods, and work together. With this app, digital tools help fill the gap between modern tech and old school farming so we can farm a prosperous and sustainable future.

Keywords—- Farm-to-Consumer, Agriculture, Scheme Management, Vehicle Renting, Fertilizer, Land Renting.
Predictive Maintenance in Semiconductor Manufacturing: Leveraging IoT Sensor Data for Equipment Reliability
Authors:   Austin, TX, Parmar Tarun
Published: January 2025

Abstract—Predictive maintenance (PdM) has emerged as a
transformative approach in semiconductor manufacturing,
leveraging IoT sensor data to enhance equipment reliability and
optimize production processes. This review explores the
implementation of predictive maintenance strategies in
semiconductor manufacturing, focusing on the role of IoT sensor
networks, advanced analytics techniques, and integration with
Manufacturing Execution Systems (MES). IoT sensor networks
enable comprehensive real-time data collection on equipment
performance and environmental conditions, thereby providing a
foundation for predictive maintenance. Time series forecasting
algorithms, such as ARIMA, exponential smoothing, and machine
learning-based approaches, are employed to anticipate potential
equipment failures. Anomaly detection techniques, including
statistical methods and machine-learning algorithms, are used to
identify unusual patterns or behaviors that are indicative of
impending issues. The integration of predictive maintenance
insights with MES allows for real-time decision making, process
optimization, and improved overall equipment effectiveness.
However, challenges persist in terms of data quality, scalability,
and cybersecurity, requiring ongoing research and industry
collaboration. Early adopters reported significant reductions in
unplanned downtime, optimized maintenance schedules, and
improved product quality. As the semiconductor industry
continues to evolve, predictive maintenance is expected to play a
crucial role in maintaining competitiveness and meeting the
growing demand. Further research, standardization efforts, and
development of best practices are essential to fully realize the
potential of predictive maintenance in semiconductor
manufacturing.
Keywords—predictive maintenance (PdM), semiconductor
manufacturing, IoT sensor data, equipment reliability, forecasting,
anomaly detection, unplanned downtime, product quality
The Role of Adstock and Saturation Curves in Marketing Mix Models: Implications for Accuracy and Decision-Making
Authors: Chivukula Varun
Published: January 2025

Adstock and saturation curves are fundamental concepts in marketing mix modeling (MMM) that enable marketers to
quantify the effects of advertising over time and identify diminishing returns. By modeling the lagged and cumulative
impact of marketing spend (adstock) and incorporating nonlinear response functions (saturation curves), MMMs offer
actionable insights for optimizing budgets. This paper explores the theoretical foundations and practical applications of
adstock and saturation curves in MMMs. Through empirical examples, we illustrate their influence on model outcomes,
highlighting how they enhance interpretability, accuracy, and the reliability of marketing ROI estimates. Furthermore,
we discuss challenges and best practices in implementing these mechanisms.
Artificial Intelligence (AI) & BOTS in Testing
Authors: Thiruthuraipondi Natarajan Rajalakshmi
Published: January 2025

The knowledge gathered using Artificial Intelligence (AI), coupled with the efficiency of BOTs is a boon for
testing activity in the IT world. This can, not only bring down the human errors, but can also significantly speed up
the whole testing process and by extension the project timeline. As part of test preparation, the AI needs be exposed
to a range of different paths the product can take, so that it can learn operations and the BOTs designed to each of the
possible variations in input and outcome. With detailed data gathering and careful design, AI and BOTs can
effectively handle every scenario and ensure the end product meets the needs and goals of the organization. Once the
BOTS are in place, they can be reused at will to actively test any enhancements or modifications that the product
might have to undergo in its lifetime on the IT world. Similarly, with AI constantly observing the application, it can
be used to dynamically identify the differences, both in source and the expected result for building targeted testing
document and execution.
Keywords : AI, BOTs, Automated Testing, IT testing, Machine Learning, Regression testing. Application
Evolution monitoring. And learning, Automated Test data gathering, Programmatic test execution