bluuebunny/crossref_metadata_2025 huggingface dataset:
Automated Early Phase Breast Cancer Detection using Hybrid Machine Learning Algorithms
Authors: Poornima E. , Mamatha P. , Krishnamai M. , Sruthi Ch. , Kumar Shah Sanjeev , Raghu Kumar L.
Published: October 2023

Breast cancer is the most common cancer among women. It occurs when few breast cells begin to grow abnormally. The national average for 2022 is 100.4 cases per 1,00,000 people, with a large number of women being diagnosed with breast cancer. The objective is to design a prediction system that can predict breast cancer at early stages using a set of attributes that have been selected from a critical dataset. The Wisconsin Kaggle dataset is used for this experiment. The goal of this work is to predict breast cancer utilizing hybrid machine learning methodologies, such as SVM and PCA. ML algorithms that could help to predict cancer, as the early detection of this disease would help to slow down the progression of other diseases. In our paper, we are implementing Hybrid algorithms like PCA and SVM and optimizing SVM with k-fold cross-validation for predicting Breast cancer at early stages with high accuracy. The goal is to raise the fraction of early-stage breast cancer detection and to reduce mistake rates with maximum precision, which are sustainable.
Decentralized and Automated Online Voting System using Blockchain Technology
Authors: Sanjeeva Polepaka , Sai Sathwik M. , Sai Prasad G. , Praneeth Reddy G. , Sajwan Vijaylakshmi , Ganesh Bande
Published: October 2023

A decentralized and automated online voting system refers to an electronic voting method that leverages Blockchain technology to guarantee both transparency and security. It removes the need for intermediaries, making it more efficient and cost-effective than traditional voting methods. Aim of the paper is to develop an online voting system using Blockchain technology for secure and transparent voting. The proposed approach involves developing a decentralized voting system using Ethereum Blockchain technology. Smart contracts are used to manage the voting process and ensure its integrity. The datasets used in this paper will consist of mock voting data to simulate a real-world scenario. The results and discussions include an analysis of the system’s performance in terms of security, scalability, and usability. Future enhancements include integrating biometric authentication for enhanced security and accessibility.
Feasible Prediction of Diabetes in Pregnant Woman and Neonatal Mellitus in New Born Child using Machine Learning
Authors: Shamila M. , Srinivas M. , Aryan Suresh H. , Viswa Sai Poojith T. , Kumar Dharmendra , Harikrishna Bommala
Published: October 2023

Diabetes during pregnancy is a major source of health problems in unborn infants and their moms. Because gestational diabetes can develop to permanent diabetes, ML is an important method for predicting the likelihood of such progression based on the given features. Although the current study may predict lifelong diabetes in pregnant women, it cannot predict the likelihood of neonatal diabetes. As a result, new characteristics are required to improve the forecasting of neonatal mellitus and provide the most accurate and feasible diabetes persistence results in pregnant women. Python scripting and the application of Machine Learning methods such as SVM, KNN, and LR can assist in achieving this aim. The preprocessing ML dataset focusing on Diabetes from the Pima Indian diabetes database collected through Kaggle. In addition, two new attributes were added to the paper’s dataset. According to research, machine learning models using characteristics like SVM and decision trees may successfully predict the risk of diabetes in pregnant women. Various factors have been used to predict the beginning of this condition during pregnancy.
Feasible Trend Prediction for 2019 Indian General Elections
Authors: Poornima Ediga , Abhishek Ganji , Rushi Hari Haran Krishna Shastry , Rishik Kumar Banala , Faizan Ruby
Published: October 2023

The popularity and accessibility of social media applications, such as Twitter, has increased over the past few years at a rapid pace. Users from different parts of the world use it to share thoughts with each other. Politicians use these platforms at every viable opportunity and increase support and following for themselves and their parties. Sentiment analysis has become a key methodology to gain insight from social networks. We perform sentiment analysis using a lexicon-based sentiment analyser and sentiment trend prediction for a short interval of time to model the sentiment trend towards the top contenders of the Indian General Election 2019 on twitter. Sentiment Analysis is done on the tweets posted during the campaign period of the Indian General Elections of 2019. This is done using a pre-trained sentiment analyser called VADER of the NLTK library. VADER is optimized for social media data and can produce useful results. The dataset used for this paper is created using web scraping modules written in Python. In addition to that, sentiment trend prediction was done for a period of 10 days from the day of result announcement using Linear Regression, to achieve sustainable reports.
Automated Weapon Detection System in CCTV’s Through Image Processing
Authors: Siri Dharmapuri , Bhanu Prasad Reddy Palle , Harika K.V.S.L. , Ritwika S. , Sisodia Shivani , Madhavi Karanam
Published: October 2023

In our study, we aim to detect various weapons through image processing using a combination of traditional machine learning algorithms and deep learning techniques. This would prove beneficial in anticipating unusual occurrences. The utilization of Closed-Circuit Televisions (CCTVs) has become widespread in the security and surveillance industry; however, it requires constant human monitoring to extract useful information, which is both tedious and prone to errors. The base paper deals with identifying only firearms. We intend to utilize machine learning and deep learning methods to recognize different weapons automatically, not only firearms and alert the CCTV monitor to that specific area.
An Automated Framework for Summarizing YouTube Videos Using NLP
Authors: Dharmapuri Siri , Desu Sashank , Alladi Karthik , Gummadi Harika , Gupta Harshit , Shareef S. Noor Mohammad
Published: October 2023

In recent times, YouTube has increasingly become the preferred platform to consume educational content. In order to learn complex and intricate concepts, a student must sit through many of hours of YouTube videos where an average video length is about 20 minutes. To see if the content of a given YouTube video is relevant to what the user is looking for, YouTube Video Summarizer was conceptualized. YouTube Video Summarizer is a Chrome Extension tool which can be used to quickly generate the summary of a YouTube video using the English-language transcript of the video Automation. This allows for a seamless generation of a synopsis without spending hours watching the content to determine its relevancy.
Sustainable Societal Empowerment through an Efficient Novel Paradigm on Industrial Internet of Things for Smart Medicare box
Authors: Beena Bethel G.N. , Reddy G. Vijender , Sai Vemuri Pavan Sri Surya , Rachamalla Charath , Pandey Divya , Shapuram Sathish Reddy
Published: October 2023

The main objective of this research is to develop a user-friendly medicine box for patients, ensuring they take the correct medication at the right time. The design allows for easy customization with minor modifications based on specific requirements. Caretakers or family members can enter and update tablet data in the medicine box, including expiry, count, and dosing schedule. Equipped with real-time clock data, the medicine box activates slot-specific LED lights and alarming sounds when it matches the designated medication schedule. These indicators turn off only when the patient takes the correct medicine from the respective slot, detected by ultrasonic sensors. The medicine box also features a reminder system, sending notifications via WhatsApp to the designated caretaker or family member to track medication adherence. Additionally, it includes a repeat button for patients to easily access and retake the previous dose. In case of emergencies, the medicine box is equipped with an emergency button, enabling patients to contact their caretakers or family members promptly. Furthermore, the medicine box automates the medicine ordering process by placing orders when any tablet is nearing its expiry or when the count falls below the minimum required level. Hence, these features ensure patient’s medication taken promptly.
Intelligent Agribusiness System-An Echo Friendly IOT based Approach
Authors: Gundu Venkateswarlu , Singamaneni Kranthi Kumar , G. Ramesh , Kandukuri Prabhakar , Sharma Deepti , Karanam Madhavi
Published: October 2023

Internet of Things (IoT) innovation is one of the fastest growing fields in various regions or aspects which include irrigation. IoT works on the character of our lives by way of bringing and cultivating modifications in many fields of exercises to motive them to come to be convenient, savvy and enriched with the aid of adequate guy-made recognition. As a result of this innovation, smart cultivating frameworks recognize a social trade towards current agri-business that is more useful, consumes less water, and is extraordinarily less luxurious. The primary goal of this paper is to make use of IoT within the agribusiness subject to accumulate facts right away (soil Moister, temperature), with a purpose to help one with staring at a few climate situations distantly, effectively and improve massively the creation and thus the pay of ranchers. The modern version is created utilizing NodeMCU innovation, which contains express sensors, and a Wifi module that assists with amassing moment records on the internet. It is worth concentrating on the testing of this model created, profoundly precise data in light of the fact that any herbal changes were outstanding in a flash and taking into consideration to decide. This paper speculating about integrating the IoT with different other technologies.
Sensing Users Emotional Intelligence in Social Networks
Authors: Raghavendra C. , Kiran Kumar P. , Ramesh G. , Varadhi Keerthi , Ahmad Vasim
Published: October 2023

In this age of constant digital communication and social interaction, people are paying a lot of attention to how users' emotional intelligence affects their interactions and well-being on social networks. This research investigates the application of information systems and telecommunications technologies in the detection and analysis of users' emotional intelligence within the realm of social networks. The concept of emotional intelligence, which involves the capacity to notice, comprehend, regulate, and use emotions in a proficient manner, has significant importance in influencing encounters and relationships in the online domain. This article explores potential models of emotional intelligence based on sentiment analysis of social network data. Self-awareness, self-regulation, intrinsic motivation, and interpersonal connections are based on four principles. These four-dimensional models aggregate four numerical indicators to quantify emotional quotient. This study uses Twitter, a popular social network, to predict emotional intelligence in individuals or groups. This finding assesses users' emotional intelligence using four variables and shows their positive, negative, and neutral sentiments. The program we are developing is based on uploading Twitter datasets and forecasting emotional intelligence using algorithms and tools based on tweets, retweets, and followers, among other scenarios. The four dimensions allow us to feel emotions. Twitter datasets are in text files with JSON data.
Sustainable Facial Authentication and Expression Prediction using Deep Learning Techniques
Authors: Rajasekhar N. , Sreekar T. , Revanth D. , Karthik S. , Sadhna Awasthi S.
Published: October 2023

To make machines more human-like, computer vision is essential. Computer vision is a field that focuses on mimicking the capabilities of the human visual framework to capture high-level understanding from enhanced images or recordings. Such a computer vision application gives the machine the ability to recognize a person and detect their emotions in order to process them appropriately. Facial verification can be a process of identifying or validating an object through an image, video, or any audio-visual component of their face. It could be a biometric discriminant proof strategy that works directly and confronts measures of discriminating individuals through their facial design and biometric information. The innovation collects a unique set of biometric information from each individual regarding their face and facial expressions to identify an individual. Facial sensory recognition can be an innovation used to analyse estimates from a variety of sources, such as images and recordings. It makes a difference as machines get better the way humans do and treat them according to their emotions. We are using a deep learning computation called Convolutional Neural Networks (CNN) to prepare for this demonstration that determines the sentiment of certain input images. We need to pre-process the images to prepare and test the model. For pre-processing, we do image enhancement combining resizing, equalizing and converting the image to grayscale for the machine to achieve. This demonstration can have multiple applications in both surveillance and feedback systems.
DFR-TSD: A Sustainable Deep Learning Based Framework for Sustainable Robust Traffic Sign Detection under Challenging Weather Conditions
Authors: Jeevan Nagendra Kumar Y. , Ledalla Sukanya , Pavithra Avvari , Vijendar Reddy G. , Joshi Rachana , Jayahari L.
Published: October 2023

The development of reliable and sustainable traffic sign detection under difficult weather conditions, or DFR-TSD, is a key step in creating effective, safe, and sustainable autonomous driving systems. The suggested sustainable framework makes use of deep learning techniques to overcome the drawbacks of the current traffic sign detection systems, especially in difficult weather circumstances like haze and snow. The system uses a sustainable CNN pre-processing step to make traffic signs more visible in photos that have been impacted by the weather, followed by a sustainable pre-trained ResNet-50 model to recognize traffic signs. On the CURE-TSD dataset, which includes difficult weather circumstances such as haze, snow, and fog, the suggested sustainable framework was assessed. The testing findings showed how sustainably well the suggested framework performed in identifying traffic signs in adverse weather. The suggested sustainable framework outperforms previous approaches with a sustainable accuracy rating of 98.83%. The outcomes show that sustainable deep learning methods have the potential to enhance traffic sign identification models' functionality. The proposed sustainable framework’s front end offers a user-friendly interface that enables users to upload test photographs and view the results of the detection. There are four sustainable buttons on the UI for loading the model, uploading test photographs, spotting signs, and seeing the training graph. The Tkinter framework, which offers a user-friendly GUI toolkit that enables developers to quickly design and customize sustainable GUI programs, is used to develop the front end. The suggested sustainable DFR-TSD framework is a potential sustainable option for reliable traffic sign detection in adverse weather due to the sustainable pre-processing step, the sustainable pre-trained ResNet-50 model, and the sustainable user-friendly interface.
Investigation of Microstructure and Mechanical Properties of High-Temperature Super Alloy under Room and Elevated Temperature
Authors: Balaji B. , Shiva Kumar P. , Parmar Ashish , Arora Vandana , Abdul-Zahra Dalael Saad , Nijhawan Ginni
Published: October 2023

This research investigates the microstructural characteristics and mechanical properties of a high-temperature superalloy under different temperature settings. The objective of this study is to analyse the alloy’s reaction to thermal stress, with a specific focus on both room and increased temperatures. By employing sophisticated microscopy techniques, researchers are able to closely examine the development of microstructural characteristics, which provides valuable understanding of phase changes and the dynamics of grains. Simultaneously, evaluations of mechanical properties, including tensile strength, hardness, and resilience, offer a holistic comprehension of the alloy’s operational characteristics. This research enhances the overall understanding of the alloy’s appropriateness for high-temperature applications by considering a wide range of temperatures. The results not only contribute to our fundamental understanding of materials science but also have ramifications for the development of alloys that can endure severe heat conditions.
Sustainable Manufacturing of High-Performance Composites from Recycled Materials
Authors: Sonia Pankaj , Kumar A. Sathish , Khan Irfan , Pahwa Shilpa , Salman Zahraa N. , Singh Navdeep
Published: October 2023

The increasing environmental issues linked to traditional petroleum-based packaging materials have stimulated a rising curiosity in investigating sustainable alternatives, especially in the field of food packaging. The present study investigates the characterisation of bio-based materials that have the potential to significantly transform food packaging applications. The main aim of this study is to evaluate the feasibility of using these materials as ecologically sustainable substitutes, taking into account their physical, mechanical, barrier, and thermal characteristics. The study process includes the careful selection of a wide array of bio-based materials, such as biopolymers derived from agricultural wastes, chemicals derived from algae, and derivatives of cellulose. The findings from the characterization provide insight into the complex attributes of these bio-based materials, elucidating their advantages and disadvantages when compared to conventional packaging materials. The research findings presented in this study make a valuable contribution to the expanding corpus of information pertaining to sustainable packaging options. As there is a growing worldwide focus on reducing plastic waste and minimising ecological impacts, the findings of this research contribute to the promotion of a more sustainable approach to food packaging. These findings are in line with the concepts of a circular and bio-based economy.
Characterization of Microstructure and Mechanical Properties of Cast Materials using Advanced Techniques
Authors: Singh Bharat , Kumar C. Praveen , Kalra Ravi , Dhamija Koushal , Salman Zahraa N. , Kumar Manish
Published: October 2023

In this study, we present an in-depth analysis of the microstructure and mechanical properties of cast materials, employing advanced characterization techniques. The research focuses on the utilization of Scanning Electron Microscopy (SEM), X-ray Diffraction (XRD), and Electron Backscatter Diffraction (EBSD) for microstructural analysis, alongside nanoindentation and tensile testing for mechanical property evaluation. The materials under investigation include a variety of industrially relevant cast alloys, providing a comprehensive understanding of their behavior under different casting conditions. Our findings reveal a strong correlation between the microstructural features, such as grain size, phase distribution, and defect morphology, and the mechanical properties, including hardness, yield strength, and ductility. The study also highlights the influence of casting parameters on these properties, offering insights for optimizing casting processes. The results of this research not only contribute to the existing body of knowledge on cast materials but also pave the way for the development of advanced materials with tailored properties for specific applications. This work underscores the importance of integrated microstructural and mechanical characterization in understanding and predicting the performance of cast materials, thereby aiding in their effective utilization in various industrial sectors.
FEA-Based Investigation of Fatigue Life and Durability of Materials and Structures in Automotive Applications
Authors: Agrawal Manoj Kumar , Sree V. Bindu , Maan Preeti , Pratap Bhishm , Zabibah Rahman S. , Sharma Vishal
Published: October 2023

In the rapidly evolving automotive industry, the longevity and reliability of materials and structures are paramount. This research paper presents a comprehensive Finite Element Analysis (FEA)-based investigation into the fatigue life and durability of materials and structures commonly employed in automotive applications. Utilizing state-of-the-art FEA tools, the study evaluates the stress distributions, strain concentrations, and fatigue-induced deformations under cyclic loading conditions representative of real-world automotive scenarios. A comparative analysis of various automotive materials, including advanced high-strength steels, aluminium alloys, and novel composite materials, is conducted to discern their fatigue performance. The results elucidate the critical regions susceptible to fatigue failure and provide insights into the underlying mechanisms governing material degradation. Furthermore, the study introduces a novel fatigue life prediction model, calibrated against experimental data, offering enhanced accuracy in predicting the lifespan of automotive components. The findings of this research not only contribute to the fundamental understanding of fatigue phenomena in automotive materials but also pave the way for the development of more durable and sustainable vehicles in the future. This work serves as a cornerstone for engineers and researchers aiming to optimize material selection and design strategies, ensuring safer and longer-lasting automotive structures.
Characterization and Modelling of Nanomaterials Synthesized by Chemical Vapor Deposition
Authors: Kumar Sunil Prashanth , Babitha L. , Srivastava Arun Pratap , Kumar Rajeev , Ali Hanaa Addai , Lakhanpal Sorabh
Published: October 2023

In recent years, Chemical Vapor Deposition (CVD) has emerged as a pivotal technique for the synthesis of high-quality nanomaterials, owing to its ability to produce uniform and scalable thin films with controlled properties. This study presents a comprehensive characterization and modelling of nanomaterials synthesized via CVD, elucidating the intricate relationship between process parameters and the resultant material properties. Utilizing advanced characterization techniques, including Transmission Electron Microscopy (TEM), XPS, and Raman Spectroscopy, we have discerned the morphological, compositional, and structural attributes of the synthesized nanomaterials. The experimental data were subsequently employed to develop a predictive model, leveraging machine learning algorithms, to forecast the properties of nanomaterials based on CVD parameters. The model exhibited high accuracy and can serve as a robust tool for optimizing CVD processes in real-time. Our findings underscore the potential of CVD in tailoring nanomaterial properties for specific applications and provide a foundational framework for researchers and industries aiming to harness the full potential of nanomaterials synthesized via CVD. This work not only advances our understanding of CVD-synthesized nanomaterials but also paves the way for their application in next-generation electronic, photonic, and energy devices.
Super Alloy Coatings for Enhanced Corrosion and Oxidation Resistance in Extreme Environments
Authors: Abhishek Kumar , Anupama B. , Singh Harjeet , Gupta Nisha , Mashkour Muthana Saleh , Kansal Lavish
Published: October 2023

The use of super alloy coatings is an innovative method for enhancing the durability of materials against the detrimental effects of corrosion and oxidation, especially in areas with severe circumstances. This study explores the forefront of super alloy coatings, examining their significant role in minimising the adverse effects of corrosive and oxidative processes on materials working in harsh conditions. This study highlights the transformative potential of super alloy coatings in extending the lifespan and enhancing the reliability of critical components. It achieves this by presenting a comprehensive overview of the fundamental principles, fabrication methodologies, and practical applications associated with these coatings. As many sectors navigate more difficult environments, the effective incorporation of advanced coatings presents a potential direction, advancing the field of materials science and guaranteeing consistent performance in the presence of significant challenges. The emergence of super alloy coatings represents a significant transformation in the field of corrosion and oxidation control, providing a robust defence against the persistent deteriorating factors seen in highly challenging settings. The combination of complex production procedures and superior material qualities empowers these coatings to strengthen materials, therefore assuring their durability.
Advances in Design and Development of High-Performance Super Alloys for Extreme Environments
Authors: Swathi Baswaraju , Varasree B. , Kumari Vandna , Jayronia Sonali , Saeed Hazim Y. , Kumar Manish
Published: October 2023

This study centres on the current progressions in the domain of superalloy design and development, with a particular emphasis on their customization to endure the demanding conditions of highly challenging settings. The manuscript emphasises the importance of superalloys in diverse sectors, including aerospace, energy, and manufacturing, where materials are exposed to elevated temperatures and corrosive environments. The primary aims of this research encompass the investigation of innovative alloy compositions, techniques for microstructural engineering, and advanced methods of processing. The objective is to augment the mechanical strength, creep resistance, corrosion resistance, and overall durability of superalloys under circumstances of severe exposure. The manuscript emphasises the intricate nature of the problems encountered in this endeavour, highlighting the need of striking a balance between different material qualities in order to get the most favourable performance. In addition, the manuscript provides a concise overview of the paper’s methodology, which involves the use of sophisticated tools for characterising materials, computer modelling, and experimental verification. The potential of these novel high-performance superalloys to bring about a paradigm shift in industries that heavily rely on materials with the ability to endure severe circumstances is considerable. Superalloys offer enhanced qualities that can be advantageous in many applications, including as aerospace components, gas turbines, and petrochemical equipment.
Innovative Approaches to Thermal Management in Next-Generation Electronics
Authors: Bandhu Din , Khadir M.D. , Kaushik Abhishek , Sharma Shekhar , Ali Hanaa Addai , Jain Alok
Published: October 2023

In conclusion, the analysis and measurement of thermal properties are crucial for a wide range of applications in science, technology, and industry. For energy efficiency optimisation, the design of sophisticated materials, and the creation of cutting-edge technologies, it is essential to comprehend how heat is transmitted and handled within materials. Researchers can precisely evaluate thermal conductivity, heat capacity, and other thermal parameters using a variety of experimental methodologies, including both conventional and cutting-edge technologies. This enables accurate material characterisation and performance evaluation. The landscape of thermal management and energy conversion has been significantly shaped by nanostructured materials. Their distinct nanoscale characteristics provide chances to modify thermal behaviour, boost effectiveness, and add new features. Researchers are able to manage heat conduction, phonon behaviour, and charge transport through the use of designed nanostructures, which has led to breakthroughs in a variety of industries, including electronics, energy storage, thermoelectric devices, and more. In addition to promoting energy efficiency and waste heat recovery, these developments pave the path for sustainable solutions to the world’s rising energy needs and environmental problems. We are on the verge of ground-breaking discoveries that have the potential to restructure industries, enhance energy sustainability, and pave the way for a more effective and linked society as we continue to investigate and harness the complex behaviour of heat within materials.
A Review on Metal Binder Jetting 3D Printing
Authors: Venukumar Sarila , Cheepu Murali Mohan , Kantumunchu Venkata Charan , Balaji Viswanadhapalli , Bisht Amita
Published: October 2023

Binder jetting (BJ) is one of the major metal additive manufacturing (AM) technology used for the production of intricate metal components using a layer-by-layer approach. It belongs to the more general family of processes known as powder bed fusion procedures, in which a bed of metal powder is first selectively fused together with the help of a binder and then sintered in order to produce the final metal component. Binder Jetting is the sole non-fusion-based powder bed additive manufacturing technology; this means that, unlike laser-based AM procedures, the resulting parts are completely free of residual stresses. Small to medium batch production can be cost-effective due to lower tooling and setup expenses. This analysis focuses on the capacity of some of the most important engineering materials, including titanium, Inconel and stainless steel, to produce intricate geometries with a high degree of precision and accuracy. These materials find extensive use across many applications, including defence, industry, biomedical, aerospace, and other fields.
Carbon Quantum dots doped Chitosan/HPMC nano composites and their Functional, Structural, Morphological, Dielectric and Tensile properties
Authors: Shareef S. Noormohammad , Narasaiah Boya Palajonnala , Madhuri W. , Vagdevi K. , Ramnarayan
Published: October 2023

Carbon Quantum Dots (CQDs) were prepared from modified hydrothermal method using Citric acid and ethane diamine as a source material. The synthesized CQDs were characterized by UV-Vis spectroscopy, Fluorescence Studies (FL), Atomic force microscopy (AFM). The particle size is conformed from Dynamic Light Scattering (DLS) analysis. The synthesized CQDs were doped in polymer blend with various weight percentages and the further characterizations were carried out for X-Ray Diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), dielectric properties, and tensile properties at room temperature and higher temperatures with the help of Universal Testing Mission (UTM). The dielectric behavior of Chitosan/HPMC/CQDs polymer nanocomposites (PNCs) were studied in the range of 50 Hz to 5 MHz frequency and the temperature ranging from 30-100 °C, using LCR meter. The dielectric constant (ε'), dielectric loss (ε') are found with different wt% of CQDs in the PNCs.
Predicting the Spread of the Corona Virus Disease Requires Analyzing Data from Cases across Multiple States in India
Authors: Ganesh Bande , Naik V. Ravinder , Ramji Banothu , Aerranagula Veerender , Babu B. Sankara , Sharma Sandeep
Published: October 2023

Data analysis is very sophisticated tool in recent corona virus pandemic to find the trend of spreading pattern for controlling the infection. In this perspective, predictive analytics can be useful for data analysis to forecast the corona virus pandemic. This paper presents the infection pattern of corona virus disease, termed as COVID-19 in top seven states in India. Prophet Algorithm forecasting model was used to analyze state-wise spreading pattern of corona virus disease with respect to confirmed, deaths and cured cases. This predictive model can be very helpful to government and health care communities to combat this deadly virus by initiating suitable actions to control its spread.
IoT-Based System for Automated Accident Detection and Rescue
Authors: Manchala Manasa , Bommala Harikrishna , Raju Vijaya Rama , Pant Ruby
Published: October 2023

One of the most common causes of death is auto accidents. The worst thing that may happen to a road user is a traffic accident, despite the fact that they happen regularly. The worst part is that we fail to learn from our on-the-road errors. Most people who use roads regularly are extremely familiar with the fundamental guidelines and safety procedures that should be followed, but it is only their own negligence that results in accidents and wrecks. Accidents and crashes are primarily caused by human error. Here are some examples of normal human actions that result in accidents. 1. Driving too fast; 2. Driving while intoxicated; 3. Distracting the driver; 4. Running red lights; 5. Avoid utilizing safety equipment, such as seatbelts and helmets; 6. Driving erratically and overtaking improperly in order to save lives in a traffic collision, we’re going to construct an Arduino-based car accident alert system that combines GPS, GSM, and an accelerometer. If the accelerometer detects an abrupt shift in the vehicle’s axis, the GSM module alerts you and communicates the location of the accident to your cell phone. The GPS module’s latitude and longitude are utilized to pinpoint the accident’s location, which is provided as a Google Map link. The message also contains the vehicle’s speed in knots.
A Coal Mine Safety from Conventional to Modern Method Through LoRaWAN
Authors: Vandana B. , Varalakshmi Rongali , Malik Kalyani , Abhishek Lyagala , Samson Mamatha , Singh Negi Gaurav
Published: October 2023

In this paper, a data transmission method called Thing Speak is used to construct a coal mine safety system. The system is used to monitor and regulate a number of characteristics in coal mines, including light detection, gas leak detection, temperature and humidity conditions, and coal mine fire detection. These sensors are all installed in coal mines and are regarded as a single unit. For analysis, all sensor values are continuously uploaded to Thingspeak and buzzer is utilized to notify the staff. The created technology is primarily used to enhance worker safety and the working environment in coal mines.
Influence of Additive for Optimize and Sustainable Fly Ash Suspension
Authors: Kumar Kaushal , Singh Jarnail , Arora Rishabh , Chaudhary Jyoti , Gautam Anjali , Dixit Saurav , C. Vivek Kumar , Lakhanpal Sorabh , Shankar Shiva
Published: October 2023

The pipeline at the thermal power station is now being used to conveying fly ash in the form of slurry. The objective of this research is to investigate the rheological behaviour of slurry suspensions of finer particles (FA) with and without coarser particles added (BA). In terms of weight, the ratios of fly ash to bottom ash (BA) are as follows: 9:1, 8:1, 7:3, and 6:4 respectively. Experiments on the rheology of each and every sample of slurry are carried out at shear rates ranging from 100 to 250 seconds-1. The temperature of the slurry suspension might range anywhere from 25 to 35 °C when it has a solid concentration of 30% (by weight). When finer fly ash slurry particles are combined with coarser bottom ash particles, the rheological properties of the resulting slurry suspension are significantly improved in terms of sustainable flow. The exhaustive assessments also investigate whether or not it is possible to conveying ash slurry by pipeline through sustainability.
Green and Sustainable Manufacturing with Implications of ESG In Energy Sector: A Comprehensive Review
Authors: Sharma Kshama , Bhattacharjee Priyanka , Arora Rishabh , Kumar Kaushal , Kirola Madhu , Kumar Awaar Vinay , Ahuja Suniana , Ganesh Bande
Published: October 2023

Environmental, social, and corporate governance, which is commonly shortened to ESG, is becoming an increasingly important part of the oil and gas industry as it faces a transition towards the usage of renewable energy sources. Today, businesses are increasingly looking for new ways to promote ESG initiatives, as a growing number of customers and investors are urging organisations to take ESG issues more seriously. Businesses are also looking for new ways to promote initiatives related to environmental, social, and governance (ESG) issues. This pattern can be explained by the fact that consumers are becoming more conscious of the significance of the problems being addressed. Even if the pressure on oil and gas companies is rising, the sector now has a lot of alternatives thanks to the increased emphasis on environmental, social, and governance concerns. This paper explores how ESG is redefining the sustainable energy sector as well as the reasons why it is necessary for businesses to address environmental challenges and adapt to this new paradigm. In addition, it explains how ESG is transforming the energy industry.
Sustainability and role conflict: A bibliometric analysis of research themes, trends, and future research directions: 2013-2022
Authors: Neha  , Sharma Yogita , Yadav Anshu , Ramnarayan  , Swapna G.
Published: October 2023

Information Technology (IT) Sector is known for its fast paced and dynamic work environment, which often leads to role conflict among IT professionals. This paper presents a bibliometric analysis and systematic literature review of the phenomenon of role conflict in the IT sector. The study analyses a total 77 academic papers published till 2022, indexed in Scopus and Web of Science database. The bibliometric analysis identifies the most influential authors, journals and keywords related to the topic of role conflict in the IT sector. The systematic literature review identifies and synthesizes the major themes, theoretical perspectives and research method used in the literature on role conflict in the IT sector. The findings suggests that role conflict in the IT sector is a complex phenomenon that can result from a variety of factors including conflicting expectations, unclear job responsibilities, and organisational, and environmental factors that contribute to role conflict, as well as the strategies that can be used to manage and reduce it. The study concludes with recommendations for future research and practical implications for organisations seeking to mitigate the negative effects of role conflict on their employees and performance.
Neurocognitive Mechanisms of Anti-Lingual & Accent Bias Stereotyping in Virtual Reality and the Sustainable Development of Linguistic Response
Authors: Ghosh Abhijeet , Kumar Ambika , Kumar Umesh , Mahadeva Rajesh , Gupta Vinay , Suthar Bhivraj , Patel Vivek , Dixit Saurav , Madhavi K. , Ganapathi Raju N.V. , Lakhanpal Sorabh , Rao Y. Venkat , Bhandari Prabhakar
Published: October 2023

Raising awareness through Virtual Experiencing (RAVE) and a Cross-Cultural Perspective on Raising Awareness through Virtual Experiencing (C-RAVE) approaches are used in this article to promote awareness of concerns relating to linguistic stereotyping. Virtual Reality (VR) technology has completely changed several facets of modern life, including instruction, training and entertainment. We give a summary of the techniques employed to increase awareness of how stereotypes might distort our vision. The patterns of the answers provided by the participants demonstrate that the reported gender of the speaker in addition to the accent (native vs. non-native), has an impact on the respondents' assessments of performance. Additionally, we were able to show that the discussions and ideas produced by these response patterns led to a rise in self-awareness of language and stereotyping-related problems. The paper gives a general description of RAVE and examines how it may improve education, create empathy and foster good social change. Focus on a critique of our methodologies and place our work within a larger debate of strategies and efforts for how educational institutions might actively contribute to combating (language) discrimination and bias in many ways. The relevance of Raising Awareness by Virtual Reality and Cross-Cultural Raising of Awareness by Virtual Reality in fostering inclusion and understanding in a society that is becoming more sustainable globally connected is highlighted in the article’s conclusion.
Exploring the Uncharted Territory: Future Generation Materials for Sustainable Energy Storage
Authors: Kumar Kaushal , Dixit Saurav , Haq Md. Zia ul , Maksudovna Vafaeva Khristina , Vatin Nikolai Ivanovich , Rao D.S. Naga Malleswara , Awaar Vinay Kumar , Nijhawan Ms. Ginni , Rani K. Swapna
Published: October 2023

This study explores the domain of developing material categories for the purpose of sustainable energy storage, with the objective of addressing the constraints inherent in existing technologies and facilitating the development of inventive resolutions. The research examines the potential of nanomaterials, metal-organic frameworks (MOFs), polymers, and two-dimensional (2D) materials as a means to overcome the obstacles presented by current energy storage systems. This study investigates the qualities and potential of various materials, examining them in conjunction with a range of thorough characterization techniques. These approaches include electrochemical analysis, structural methodologies, nanoscale observations, and computer modelling. In the next analysis, this study will examine the future direction of research on energy storage materials, including prospective advancements and the critical obstacles related to scalability, cost-efficiency, and integration within energy systems. In general, this investigation highlights the significant impact of new materials on the development of a more environmentally friendly energy infrastructure. The present study focuses on the investigation of emerging materials for sustainable energy storage. Specifically, the research explores the potential of nanomaterials, metal-organic frameworks, polymers, and two-dimensional materials in this context. By examining the properties and characteristics of these materials, this study aims to contribute to the understanding and development of efficient and environmentally friendly energy storage solutions.
Now and Future Challenges of the Automobile Industry in the Developing World
Authors: Monye Stella Isioma , Afolalu Sunday Adeniran , Lawal Sunday Lukeman , Gisanrin Toluwalope Tomisin , Oluwatoyin Ojo Augustine , Adeyemi Adewale George
Published: October 2023

The automotive sector has fuelled economic expansion in several countries. The automotive industry is changing quickly in the areas of response to shifting consumer tastes, the adoption of stronger government rules, and technology innovation. This study examines the current and future challenges faced by the automotive industry in developing countries and explores strategies for fostering growth and addressing these challenges. The automobile industry in developing countries confronts various obstacles, like infrastructure limitations, environmental concerns, lack of skilled workforce and market competitiveness. These challenges hinder the industrial growth and sustainability. However, there are also promising opportunities and future trends that can reshape the industry, such as electric vehicles, autonomous and connected vehicles, shared mobility services, advanced manufacturing techniques, and sustainable materials. To overcome these challenges and promote growth, several recommendations are proposed. These include: infrastructure development to improve accessibility, skill development programs to address skilled workforce shortage and effective policies. By addressing these challenges and implementing the recommended strategies, developing countries can advance growth, improve sustainability, and create a vibrant and competitive automobile industry. Conclusively, collaboration between governments, industry players, academia, and research institutions are vital for overcoming challenges, and achieving long-term success in evolving automotive landscape.
Viability of selected agro-waste as case hardening materials for cutting tools – A review
Authors: Ogedengbe Temitayo Samson , Afolalu Sunday Adeniran , Ikumapayi Omolayo Michael , Abdulkareem Sulaiman , Ajimotokan Habeeb , Emetere Moses Eterigho
Published: October 2023

Machining is an indispensable part of production technology with cutting tool. with cutting tool playing key roles in its operations. The demand for more efficient cutting tool increases continuously with technology. Most of the cutting tools in use are imported and the cost of replacement is high. This problem had resulted in series of studies into the development of cutting tools from indigenous materials, particularly agrowastes. This study was a review of the various tool development approaches using various agrowaste types. The challenges and recorded successes as well as gaps in knowledge have also been identified. Summarily, the use of cutting tools developed from steel types that have been case-hardened by agro wastes is a viable alternative that can be explored for use in machining technology.
Condition Monitoring of Farm Machinery, a Maintenance Strategy for a Sustainable Livestock Production: A Review
Authors: Salawu Enesi Yekini , Airewa Innocent , Akerekan Opeyemi Ernest , Afolalu Sunday Adeniran , Kayode Joseph Friday , Ongbali Samson Oyaka , Awoyemi Olanrewaju Olaniyi , Edun Bose Mosunmola
Published: October 2023

The agricultural industry is crucial to the development of the national economy. Inadequate agricultural equipment maintenance could result to a huge economic impact, especially during the harvest period. Thus, this study highlighted on the importance of condition monitoring of agricultural machinery/equipment for enhanced agricultural productions. The study established that adequate condition monitoring of agricultural machineries provides reliability data that will help in the implementation of the integrity of maintenance strategies. Additionally, adequate health monitoring of the advanced machineries will help in improving the efficiency of the machines as well as improving the overall agricultural productivity. This study provides great insight to farmers on the way to monitor and maintain the health of their agricultural machineries.
Condition monitoring and reliability assessment, an essential tool for Boiler Plant Maintenance - A review
Authors: Salawu Enesi Yekini , Akerekan Opeyemi Ernest , Afolalu Sunday Adeniran , Kayode Joseph Friday , Ongbali Samson Oyaka , Edun Bose Mosunmola , Airewa Innocent , Awoyemi Olanrewaju Olaniyi
Published: October 2023

Condition monitoring is an essential technique which is usually deployed to monitor the health parameters and conditions of a boiler plant in such a way that variations or significant changes can like failure can be identified and proffer adequate solutions to it. It is an important aspect of condition-based maintenance which is used in maintaining an equipment according to its conditions. Thus, this study focused on the fundamental principles of condition monitoring which involve the identification and selection of a physical measurement that will show the deterioration stage and the importance of taking the readings at intervals. More so, the study established that monitoring and measurement should focus more at critical components that have high frequency of failure. Thus, condition-based maintenance of boilers will help in improving the ,availability of the boiler.