bluuebunny/crossref_metadata_2025 huggingface dataset:
Analysis and design of silos by the post-tensioned method
Authors: Mallikarjuna Reddy V. , Umesh Kumar Dumma , Aggarwal Saurabh , Venkata Sai Prasad G.
Published: October 2023

This design focuses on the analysis and design of silos exercising the post-tensioned system, aiming to facilitate these critical storehouse structure’s structural effectiveness and safety. Silos are extensively used in colourful diligence to store bulk accoutrements, and their structural integrity is of consummate significance to ensure dependable and secure operations. The study involves a relative analysis between conventional silo designs and those employing the post-tensioned system. The geste of silos under different loading conditions is simulated and evaluated. The assessment considers key performance indicators such as load-bearing capacities, deflection, cracking behavior, and overall stability. The findings indicate that post-tensioning significantly enhances the structural performance of silos. The post-tensioned method offers a sustainable and cost-effective alternative to traditional silo construction by reducing cracking and improving overall stability. The results contribute valuable insights to the optimization of silo design, offering engineers and stakeholders in the industry a practical and efficient solution for industrial storage requirements. In conclusion, the analysis and design of silos using post-tensioning techniques provide a promising approach to enhancing the effectiveness and safety of silo structures. Implementing these innovative methods can improve performance and reduce maintenance costs, making them an attractive option for future silo construction systems.
Smart Attendance Automation System
Authors: Shamila M. , Prakash Bhanu , Ahmed Asrar , Prajeet Poshak , Pant Ruby
Published: October 2023

The smart attendance marking system, which is based on face recognition technology, is a modern solution that may aid in the automation of the attendance management process in a variety of organizations, including schools, colleges, and corporations. Using facial recognition technology, the research team hopes to create an efficient system for tracking and recording attendance. The system will be developed by gathering and analysing data in order to construct a database of faces that will be used to train deep learning algorithms to recognise faces effectively. Compared to traditional attendance tracking systems, the smart attendance marking system based on face recognition technology has various advantages. For starters, it saves time and lowers manual labour because attendance is automatically tracked. Second, it enhances precision, lowering the possibility of errors. Third, it delivers real-time attendance updates, making it simple for instructors or administration to monitor attendance and take appropriate action. The aim of the work is expected to improve attendance management in various organisations by optimising attendance monitoring methods while decreasing manual effort and errors. Because the system may be connected with existing attendance management systems or utilised as a standalone solution, it is a versatile and adaptable option for a variety of organisations. The paper’s effort is to design, develop, and implement an efficient system that can track and record attendance accurately using facial recognition technology, giving benefits such as time savings, accuracy, real-time updates, and better security.
Network Intrusion Detection using ML Techniques for Sustainable Information System
Authors: Chandra Mouli K. , Indupriya B. , Ushasree D. , Raghavendran Ch.V. , Rawat Babita , Madhu Bhukya
Published: October 2023

Network intrusion detection is a vital element of cybersecurity, focusing on identification of malicious activities within computer networks. With the increasing complexity of cyber-attacks and the vast volume of network data being spawned, traditional intrusion detection methods are becoming less effective. In response, machine learning has emerged as a promising solution to enhance the accuracy and efficiency of intrusion detection. This abstract provides an overview of proper utilization of machine learning techniques in intrusion detection and its associated benefits. The base paper explores various machine learning algorithms employed for intrusion detection and evaluates their performance. Findings indicate that machine learning algorithms exhibit a significant improvement in intrusion detection accuracy compared to traditional methods, achieving an accuracy rate of approximately 90 percent. It is worth noting that the previous work experienced computational challenges due to the time-consuming nature of the utilized algorithm when processing datasets. In this paper, we propose the exertion of more efficient algorithms to compute datasets, resulting in reduced processing time and increased precision compared to other algorithms to provide sustainability. This approach proves particularly when computational resources are limited or when the relationship between features and target variables is relatively straightforward.
OCL Based Approach for Sustainable ML Model Development
Authors: Hanumanthu Gautam , Lendale Venkateswarlu , Ramesh G. , Kandukuri Prabhakar , Amir Mohd
Published: October 2023

It became a bottleneck for the Machine Learning (ML) researchers to select/develop a sustainable model for a particular problem. Hence, there is a need for an approach to prepare a model with all constraints of the software system. The proposed approach is based on Object Constraint Language (OCL) which is a declarative language for writing constraints on software artifacts, it is widely used for effective representation of Functional Requirements (FR’s) and Non-Functional Requirements (NFR’s). In the proposed system, the paddy leaf disease identification system is considered and proposed Leaf Identification Constraints (LIC) and Leaf Disease Identification Constraints (LDIC) based on OCL, for the proposed constraints the Convolutional Neural Network (CNN) is chosen, as it can handle diverse range of input data and large volume of concurrent requests. To satisfy other constraints of the system, the Auto encoders are used along with CNN and the input data was take in the form of thermal imaging. This system was evaluated with test data and validation data and obtained the accuracy of 90.6%. And 84.8 was attained by earlier researchers before this approach.
Beyond Binary: The Capabilities of Classical and Quantum Computing for Securing Data Transmission
Authors: Prasad Paruchuri B.V.N. , Veerapaneni Madhu Latha , Rames G. , Awaar Vinay Kumar , Chauhan Abhilasha
Published: October 2023

In the present times, the demand for sophisticated encryption methods has escalated, especially for securing data transmission in vulnerable environments. These methods leverage diverse algorithms to fortify the integrity of communication channels. Quantum mechanics plays a pivotal role in two specific areas: quantum key distribution and property-based cryptography, both of which contribute to establishing secure communication protocols. This study focuses on conducting a comparative evaluation of classical and quantum cryptography, employing various cryptography algorithms. The objective is to ascertain the optimal algorithm within each realm classical and quantum cryptography for ensuring robust security.
IoT-Powered Intelligent Framework for Detecting Food Adulteration: A Smart Approach
Authors: Gundavarapu Mallikarjuna Rao , Bhavita Mandapati , Sahithi Meesal , Varsha Naidu , Kumar Rakesh , Prasanna Y. Lakshmi
Published: October 2023

Food adulteration refers to the practice of deliberately adding substances to food to increase its volume, weight, or to improve its appearance, texture, or flavor; it is a significant issue that affects the health and safety of consumers. With the increasing demand for food, the risk of contamination and the intentional addition of harmful substances has increased. There are several existing methods for detecting food adulteration, including chemical analysis, microscopy, sensory analysis, etc. While these methods are helpful, they can be time-consuming, labor-intensive, and may not provide Real-time results. Using the Internet of Things (IoT), Machine Learning (ML) can significantly enhance the ability to identify food adulteration.Within this Framework, we are propose a solution to detect food adulteration using IoT and machine learning. The system comprises IoT sensors and devices to gather data on various parameters such as color, pH, gas content, etc. The collected data is fed into machine learning algorithms for preprocessing, analysis, and testing. Any anomalies or deviations from the standard patterns are flagged for further investigation. ML algorithms can continuously learn from the collected data, enabling them to enhance their accuracy and effectiveness over time. By implementing this system, we aim to create a Real-time, data- driven approach to detecting food adulteration, ensuring food safety and quality for consumers by creating a warning system.
Sustainable IoT-Enabled Coma Patient Health Monitoring System
Authors: K. Ravikiran , Pashikanti Adithya Varasiddi , Rupesh Patlolla , Teja Bussa Sai , Rautela Indra , Abhilash P.K.
Published: October 2023

While the patient is asleep and unable to reply, vital bodily processes like breathing and blood circulation are still largely functioning. Comas can emerge as a result of injuries like head trauma or as a side effect of underlying disorders. When the patient’s recovery will occur is not predictable. These individuals require the best treatment and constant monitoring for sustainable care. In this work, patient data is continuously monitored and recorded without human intervention, contributing to a sustainable healthcare approach. Unexpected variations in the patient’s usual range of physical parameters are detected, whether they are awake and blink their eyelids or experience abrupt changes in body temperature. Additionally, the system has the capability to instantly alert a medical expert, ensuring timely intervention. The inclusion of a tilt sensor allows for the detection of even subtle movements, further enhancing the ability to provide sustained monitoring. A medical professional can continuously monitor the patient’s condition as it is displayed on an LCD screen, promoting sustainable and effective healthcare management.
Developing a Sustainable IoT-based Smart Weather Station for Real Time Weather Monitoring and Forecasting
Authors: Kanaka Durga Bella H. , Khan Mohammed , Shreyash Naidu M. , Sai Jayanth Digumarti , Khan Yasir
Published: October 2023

Weather forecasting is an important aspect of many industries and activities, from agriculture to transportation. The main motive of this research is to design a sustainable smart weather station to track temperature, humidity, wind speed, and other weather parameters, and send the data to the IOTA network via a Wi-Fi module. The GISMO micro controller provides the necessary processing power to collect and store data, while the Wi-Fi module allows for real-time monitoring and remote access to the data. The data collected by the smart weather station can be used for weather forecasting, climate research, and disaster management. The proposed model is used to develop the accurate weather information in real-time, making it an ideal solution for individuals and organizations looking to monitor local weather conditions. By leveraging IoT technology, smart weather stations offer numerous advantages over traditional weather monitoring systems. The research mainly focuses to enable seamless data collection from multiple sensors placed strategically in various locations, providing a comprehensive view of weather conditions across different areas.
An Efficient Novel Approach for Detection of Fuel Monitoring System through IoT Sensors for a Sustainable Environment
Authors: Yamini Devi J. , Murki Karthikeya , Hanmanthu B. , Ram Ayush , Kamran Mohd.
Published: October 2023

To address the Fuel Theft situation currently faced by society, a project has been designed to create a Fuel Theft and Monitoring system. Fuel theft is an illegal act that involves stealing fuel from vehicles or storage facilities. With the rising fuel prices, this issue has become a growing problem. There are various methods employed by fuel thieves, including siphoning, drilling, burglary, and tampering with fuel gauges. Among these, siphoning is the most frequently used method, where thieves use a hose to extract fuel from the vehicle’s tank. They may suck on the hose or use a pump to facilitate the process, which can be done quickly and easily in a matter of minutes. Burglary is a more destructive method where thieves break into a vehicle to directly access and steal fuel from the tank, potentially causing damage to the vehicle. Tampering with fuel gauges is another method used by fuel thieves, whereby they manipulate the gauges to make it appear as if the tank is empty when it is actually full. This allows them to fill up the tank without paying for the fuel. Fuel theft has significant financial implications for businesses and individuals alike. In the United States, it is estimated to cost businesses billions of dollars annually. Furthermore, fuel theft can also result in environmental pollution, as thieves may dispose of the stolen fuel on the ground or in waterways. Additionally, fuel theft during transit is a common occurrence, with reports suggesting that around 16% of diesel filled in trucks is stolen. This alone amounts to a theft of significant value each year. Addressing fuel theft requires proactive measures to protect oneself and prevent such crimes. One solution involves leveraging IoT technology, specifically using modules like GSM, GPS, and cloud computing. By implementing these technologies, we can work towards eradicating the problem of fuel theft and a sustainable environment.
Sustainable Smart Helmet For Coal Miners
Authors: Madhuri T.N.P. , Abhilash P.K. , Vineel Sai G. , Sai Gowtham K. Krishna , Sharma Manoj Kumar , Haranatt Jagadish Shrisaila
Published: October 2023

The “Sustainable Smart Safety Helmet for Coal Miners” paper aims to enhance the safety and well-being of coal miners by implementing an innovative monitoring system. The paper utilizes the ESP32 microcontroller, integrated with a suite of sensors, including DHT11 for temperature and humidity measurement, MQ135 for gas detection, IR Sensor for helmet status monitoring, and a Heartbeat Sensor for real-time pulse rate tracking. A Buzzer is also integrated to provide immediate audible alerts when potential hazards are detected. The system continuously collects sensor data in real-time, which is then processed and analysed within the ESP32 microcontroller. The data is transmitted to a user-friendly mobile application developed using Blynk. Through the Blynk app, miners and relevant personnel receive critical information regarding environmental conditions and the miners' vital signs. In case of any hazardous conditions, the system generates prompt alerts, triggering the Buzzer and sending notifications to the app to ensure timely responses to potential threats. By combining advanced sensor technology, real-time data monitoring, and swift alert mechanisms, this paper endeavours to safeguard the lives of coal miners in hazardous working environments, providing them with a smart safety solution and empowering them to work with increased confidence and security.
Evaluation of the Environmental Performance of Traditional Leather Materials in Fashion Industry
Authors: Kumari Soni , Raju G. Sarat , Singh Shivani , Chandra Pradeep Kumar , Salman Zahraa N. , Sethi Gaurav
Published: October 2023

The sustainable exploitation of natural stone resources poses a multifaceted dilemma that lies at the confluence of environmental protection and the preservation of cultural heritage. This study explores the complex interplay between the exploitation and use of natural stone resources, the consequent environmental ramifications, and the necessity of preserving cultural legacy for posterity. The procurement of natural stone resources, although being indispensable for the purposes of building, architecture, and artistic endeavours, sometimes gives rise to substantial ecological ramifications. Quarrying activities have been found to result in a range of detrimental consequences, including deforestation, soil erosion, water pollution, and habitat destruction. The intricate equilibrium between the preservation of natural resources and their utilisation necessitates the implementation of inventive approaches to minimise ecological harm and save cultural heritage. In order to effectively tackle these difficulties, it is imperative to adopt a holistic strategy. The use of sustainable quarrying practises, which encompass waste minimization, reclamation of abandoned quarries, and the utilisation of new technology for resource extraction, has the potential to mitigate ecological damage. The use of circular economy concepts has the potential to significantly improve the utilisation of stone resources in a more effective manner. The preservation of cultural heritage necessitates thorough documentation, continuous monitoring, and proper care, as well as the use of protective coatings and materials that effectively minimise degradation while preserving the aesthetic and historical significance. This study argues for the cohabitation of natural stone extraction with cultural heritage preservation by examining the intersection of environmental issues and cultural relevance.
Advanced Welding of Dissimilar Materials for Aerospace and Automotive Applications
Authors: Kumari Soni , Patro E. Krishna Rao , Singh Shivani , Chandra Pradeep Kumar , Kareem Safa Abdul , Kansal Lavish
Published: October 2023

The aerospace and automotive sectors are now experiencing a growing need for lightweight and high-performance components. As a result, there is a significant interest in investigating new welding methods that can effectively fuse different materials. The process of welding different materials poses notable difficulties as a result of disparities in physical qualities, metallurgical attributes, and thermal expansion coefficients. The research starts by examining the rationales for employing diverse materials in various sectors, emphasising the benefits they provide in relation to decreased weight, greater fuel economy, and improved mechanical characteristics. Following this, the study explores a range of sophisticated welding techniques that have arisen in response to these issues. This paper examines several fusion welding techniques, including laser welding, electron beam welding, and friction stir welding. Each approach is discussed in detail, with a comprehensive description of its fundamental concepts. This discussion focuses on the advantages of each approach in relation to the reduction of heat-affected zones, the attainment of precise control over the welding process, and the minimization of intermetallic compound formation. The study also emphasises the use of case studies and practical instances to showcase the effective implementation of sophisticated welding techniques on dissimilar materials. The feasibility and efficiency of these approaches in combining incompatible materials, such as aluminium to steel, titanium to composites, and others, are exemplified by instances observed in the aerospace and automotive sectors.
Modelling and Simulation of Fracture Mechanics and Failure Analysis of Materials using FEA
Authors: Singhal Piyush , Srividhya Ch. , Kumar Ashwani , Chauhan Shilpi , Salman Zahraa N. , Jain Alok
Published: October 2023

This paper presents a comprehensive study on the modelling and simulation of fracture mechanics and failure analysis of materials using Finite Element Analysis (FEA). The research introduces a novel approach to predict and analyze the fracture behavior and failure mechanisms of various engineering materials under different loading conditions. The developed model incorporates advanced material constitutive relations and fracture criteria, providing a more accurate representation of the complex physical phenomena involved in material failure. The simulation results are validated against experimental data, demonstrating high accuracy and reliability of the proposed model. The study also explores the influence of microstructural characteristics on the fracture behavior, thereby bridging the gap between microscale and macroscale fracture mechanics. The findings of this research not only enhance our understanding of fracture mechanics but also provide a powerful tool for engineers to design more durable and reliable materials and structures. This work has significant implications for industries where material failure can lead to catastrophic consequences, such as aerospace, automotive, and civil engineering.
Investigating the Corrosion Behaviour and Electrochemical Properties of Intermetallic Matrix Composites
Authors: Nagendra J. , Sujani Singavarapu , Vishkarma Manoj Kumar , Bhati Savita , Al-Saady Fouad A. , Gupta Lovi Raj
Published: October 2023

In the realm of advanced materials, intermetallic matrix composites (IMC) have garnered significant attention due to their potential for high-temperature applications and superior mechanical properties. This research delves into the corrosion behaviour and electrochemical characteristics of selected IMCs to elucidate their performance in aggressive environments. Employing potentiodynamic polarization tests and electrochemical impedance spectroscopy (EIS) , the study provides a comprehensive analysis of the corrosion kinetics and mechanisms inherent to these materials. The results indicate that the microstructural features, including the distribution of secondary phases and the nature of the matrix, play a pivotal role in determining the corrosion resistance. Furthermore, the presence of certain alloying elements was found to impart passivation capabilities, thereby enhancing the overall corrosion resistance. The EIS data revealed distinct time constants, suggesting multiple electrochemical processes at the interface. This study not only advances our understanding of the corrosion behaviour of IMCs but also underscores the importance of microstructural engineering in tailoring their electrochemical properties. The insights garnered hold profound implications for the design and application of IMCs in industries where corrosion resistance is paramount.
Innovative Technologies for Sustainable Recycling and Re-manufacturing of Materials and Components
Authors: Tanuja G. Gayatri , Srimani Pendyala Shamili , Rao A.L.N. , Sharma Shekhar , Mashkour Muthana Saleh , Singh Navdeep
Published: October 2023

The increasing demand for sustainable manufacturing and recycling processes has driven the development of innovative technologies to address the challenges associated with the re-manufacturing and recycling of materials and components. This research paper presents a comprehensive review of the latest advancements in sustainable recycling and re-manufacturing technologies, with a focus on their potential to reduce environmental impact, enhance resource efficiency, and promote circular economy principles. We explore cutting-edge technologies such as additive manufacturing, smart disassembly, and advanced material separation techniques, which have shown promise in enabling efficient recycling and re-manufacturing of materials and components. Additionally, we investigate the integration of digital technologies, including the Internet of Things (IoT), machine learning, and blockchain, to optimize recycling and re-manufacturing processes. Our analysis reveals that these technologies can significantly improve the quality and efficiency of recycled and re-manufactured products, reduce waste generation, and minimize energy consumption. Furthermore, we discuss the potential economic and environmental benefits of adopting these technologies, as well as the challenges and barriers to their widespread implementation. The findings of this research provide valuable insights for policymakers, industry stakeholders, and researchers working towards the development and adoption of sustainable recycling and re-manufacturing technologies.
Thermal Modulation in Nanostructured Materials for Advanced Applications
Authors: Swathi Baswaraju , Praveena K. , Chahuan Neeraj , Sharma Niti , Saeed Hazim Y. , Jain Alok
Published: October 2023

Due to their remarkable thermal characteristics and the potential they hold to revolutionise a number of cutting-edge applications, nanostructured materials have attracted considerable attention in recent years. In this review, the topic of thermal modulation in nanostructured materials is explored, along with those materials' distinctive thermal behaviours and their revolutionary effects on several technological fields. The creation of innovative materials with customised thermal conductivity, expansion coefficients, and heat capacities has been made possible by the manipulation of thermal characteristics at the nanoscale. Researchers have discovered a way to alter the arrangement, composition, and shape of nanostructures, enabling unprecedented control over heat transfer processes. This ability has significant effects on the thermoelectric, photonic, electrical, and catalytic areas. Nanostructured materials have demonstrated the potential to effectively transform waste heat into useable electrical energy in the thermoelectrics field, addressing issues with energy sustainability. In order to shed light on how these materials might spur creativity across disciplines and open the door for a new age of technological growth, this review attempts to provide a thorough grasp of the mechanisms influencing thermal characteristics at the nanoscale.
Revolutionizing Material Science: Exploring the Novel Applications of Thermally-Enhanced Processes in Next-Generation Materials
Authors: Bandhu Din , Pravallika B. , Kaushik Abhishek , Paul Surovi , Ali Hanaa Addai , Sharma Vishal
Published: October 2023

With the emergence of novel thermally accelerated methods, the area of material science has undergone a paradigm shift, opening up previously unimaginable possibilities for the creation of next-generation materials with improved properties and functionalities. In order to shape the materials of the future, this paper explores the ground-breaking uses of thermally accelerated techniques such quick thermal annealing, spark plasma sintering, and laser-assisted deposition. Due to sluggish diffusion rates and incomplete reactions, traditional materials synthesis and processing processes frequently have trouble producing materials with the appropriate characteristics. This allows for accurate atomic-level manipulation of material microstructures. The engineering of materials with specific mechanical, electrical, thermal, and optical properties is made possible by the fine-tuning of microstructures. The importance of thermally accelerated processes in a variety of material classes, including metals, ceramics, polymers, and composites, is highlighted in this research. The use of thermally enhanced processes shows potential in promoting sustainable practises, as materials play a crucial part in addressing global concerns. These procedures help to reduce waste and conserve resources by enabling the effective recycling and upcycling of materials through controlled thermal treatments. The report also highlights the potential effects of thermally enhanced techniques on future industries such as flexible electronics, renewable energy systems, and medicinal devices, where specialised materials with outstanding performance are crucial.
Design and Fabrication of staircase elevator with lead screw mechanism for elderly people
Authors: Kalpana Kilaru , Reddy M. Balavanth , Sailani Shaik , Poornima E. , Chaudhary Prashant
Published: October 2023

The development of an indoor and outdoor stairlift is the primary goal of this Project. A chair that moves up and down a staircase on a leadscrew is known as a stair lift. While the primary concern when using the stairs is safety, modern, high-quality lifts come with a variety of features to maximise comfort, usability, and aesthetic appeal in the home. They are a safe and cost-effective solution to the special requirements and difficulties that people face when using the stairs, making them. With the aid of programmes like fusion 360 and autocad, we have created stairlifts designs.stair lifts are protablr cair-like mobility aids that are mounted on the side of stairways. They makes its easier for older individuals to makes between levels of ahome and allow many people with mobility challenges to live independently. Hence, we consider prototype with an different mechanism to reduce the cost of staircase with an offered price in the market everyone can and to cut down on production costs and the amount of time needed for escalators and elevators to be built, we are building a single leadscrew with stair elevator. Construction of escalators with stairs (stair lifts) that use a leadscrew mechanism to raise and lower the platform to transfer people. This aids the person who is having trouble climbing stairs.
Enhancing Impulsive Hatred Detection with Ensemble Techniques and Active Learning
Authors: Bommala Harikrishna , Bhargavi P. , Yanamadni Venkata Rao , Kumar Y. Jeevan Nagendra , Pandey S.D.
Published: October 2023

The increasing propagation in recent years of hatred on social media and the dire requirement for counter measures have drawn critical speculation from state run administrations, organizations, and analysts. Despite the fact that specialists have observed that disdain is an issue across different Social media stages, there is an absence of models for online disdain location utilizing this multi-stage information. Different techniques have been produced for robotizing disdain discovery on the web. Here we will begin by giving the current issue that comes the right to speak freely of discourse on the Internet and the abuse of virtual entertainment stages like Twitter, as well as distinguishing the holes present in the current works. At long last, figured out how to tackle these issues. It is a considerably more testing task, as examination of the language in the common datasets shows that disdain needs one of a kind, discriminative highlights and in this manner making it challenging to find. Removing a few exceptional and significant elements and joining them in various sets to look at and dissect the presentation of different machine learning classification calculations as to each list of capabilities. At long last, subsequent to leading a top to bottom investigation, results show that it is feasible to fundamentally expand the classification score acquired.
Evaluating Clustering Algorithms: An Analysis using the EDAS Method
Authors: Siva Shankar S. , Maithili K. , Madhavi K. , Bisht Yashwant Singh
Published: October 2023

Data clustering is frequently utilized in the early stages of analyzing big data. It enables the examination of massive datasets encompassing diverse types of data, with the aim of revealing undiscovered correlations, concealed patterns, and other valuable information that can be leveraged. The assessment of algorithms designed for handling large-scale data poses a significant research challenge across various fields. Evaluating the performance of different algorithms in processing massive data can yield diverse or even contradictory results, a phenomenon that remains insufficiently explored. This paper seeks to address this issue by proposing a solution framework for evaluating clustering algorithms, with the objective of reconciling divergent or conflicting evaluation outcomes. “The multicriteria decision making (MCDM) method” is used to assess the clustering algorithms. Using the EDAS rating system, the report examines six alternative clustering algorithms “the KM algorithm, EM algorithm, filtered clustering (FC), farthest-first (FF) algorithm, make density-based clustering (MD), and hierarchical clustering (HC)”—against, six clustering external measures. The Expectation Maximization (EM) algorithm has an ASi value of 0.048021 and is ranked 5th among the clustering algorithms. The Farthest-First (FF) Algorithm has an ASi value of 0.753745 and is ranked 2nd. The Filtered Clustering (FC) algorithm has an ASi value of 0.055173 and is ranked 4th. The Hierarchical Clustering (HC) algorithm has the highest ASi value of 0.929506 and is ranked 1st. The Make Density-Based Clustering (MD) algorithm has an ASi value of 0.011219 and is ranked 6th. Lastly, the K-Means Algorithm has an ASi value of 0.055376 and is ranked 3rd. These ASi values provide an assessment of each algorithm’s overall performance, and the rankings offer a comparative analysis of their performance. Based on the result, we observe that the Hierarchical Clustering algorithm achieves the highest ASi value and is ranked first, indicating its superior performance compared to the other algorithms.
Design of Farmer Assistance System Through IoT/ML
Authors: Prasad D. Shiva , Mounika N. , Sekhar N. Raja , Thakur Gaurav
Published: October 2023

Agriculture is a crucial profitable motorist. It is the main basis for the entire human life. Life cannot be imagined without agriculture. It is a source of livelihood. Everyone should pay attention to agriculture in the society. Agriculture plays an important role in improving the economy. With the rise in worldwide population farmers are facing problems in increasing the production of crops by choosing unsuitable crop for there field without knowing the field status. For increasing growth of crops IoT-smart agriculture improves the entire farming husbandry system by covering the field characteristics and weather conditions like soil moisture, temperature, humidity,electric conductivity etc. For getting more accurate results we need to train the dataset by taking the IoT results as an input and stored in the thing speak. But for analyzing the cloud data ML algorithms are required for tested data can help in choosing of a better crop. Based on these three algorithms such as random forest, Decision tree, KNN the better accuracy algorithm is choosen from percentage comparision of algorithms then the prediction of field status is acquired and makes the farmers to estimate their harvests, plan logistics and make decisions based on it. These proposed system can estimate the field characteristics to the farmers whether it is good or bad.
Sustainability in electric vehicles: A bibliometric analysis of life cycle assessment
Authors: Kumar Vinay , Sharma Yogita , Chadha Priyanka , Dixit Saurav , Jugge Praveen , Bobba Phaneendra Babu
Published: October 2023

This bibliometric analysis delves into the intricate realm of sustainability within the life cycle assessments (LCAs) of electric vehicles (EVs). Our study navigates the vast body of literature to uncover the evolving landscape, emerging trends, and critical research areas concerning the environmental impact of EVs throughout their entire life cycle. By placing a strong emphasis on sustainability, this analysis sheds light on how EVs can significantly contribute to eco-friendly transportation solutions. A systematic search was conducted using the Web of Science database, covering publications from 2001 to 2023. The search strategy used a combination of keywords related to LCA and EVs. The study found a total of 161 publications that met the inclusion criteria. The analysis revealed that the number of publications on LCA of EVs has been increasing steadily over the years, with a sharp rise in the last decade. The study identified the main research themes in the field, including LCA methodology, environmental impacts, energy use, and policy analysis. The analysis also highlighted the research gaps, such as the lack of studies on social impacts and the need for more comprehensive and comparative assessments. The findings of this study provide insights into the current state of research on LCA of EVs and can guide future research in this field.
EoG based Biopotential Instrumentation Amplifier
Authors: Katikala Hima Bindu , Intenaka Dilleswara Rao , Tulabandula Bhagat Srı Ani , Kumar Kommuri Manoj , Koli Sakshi , Awaar Vinay Kumar , Chhabra Soosan , Narsaiah M.N.
Published: October 2023

To examine the biomedical signals from the human body is of a challenging task. Signal acquisition of the biosignal needs proper design methodology with the estimation of consequences further. In this paper we discuss about the signal acquisition of EoG using the surface electrodes and to amplify the weak biopotential signal an amplifier is proposed with the additive noise reduction filter. The biopotential instrumentation amplifier is designed using standard operational amplifier that posses the high voltage swing. However the major artifacts present in the EoG signal acquisition is because of power line interference can be eliminated by notch filter.
Suitability of Agro-Wastes Based Flux as Enhancement for Welded Joints in Steels – A Review
Authors: Ogedengbe Temitayo S. , Alonge Oluwasanmi I. , Ikumapayi Omolayo M. , Afolalu Sunday A. , Bob-Manuel Samuel , Uwaifo Samuel , Akinlabi Esther T.
Published: October 2023

Failure of engineering materials is most often catastrophic but yet avoidable. This possibility has resulted in various studies into possible ways to strengthen engineering materials with quite a lot of opinions surfacing. The rapid development in world population has brought about high demand for agricultural products, which in turn results in daily increase in environmental degradation and pollution, hence their consideration as agro-based flux. This study was a review of approaches to strengthen carbon steels using a few agro waste types (Date seed, Palm kernel shell & Banana peel). The characteristic properties and engineering value of these various wastes have been closely studied. The review shows that Date Seed and Palm kernel shell shows better strength abilities and could enhance steel types better than Banana Peel and is recommended for use.
Sustainable Manufacturing in Africa: The Pros and Cons- A Pragmatic Review
Authors: Ogedengbe Temitayo S. , Ikumapayi Omolayo M. , Alabi Ismaila , Abiola Oluranti A. , Alonge Oluwasanmi I. , Sobowale Adeniyi , Afolalu Sunday A. , Akinlabi Stephen A.
Published: October 2023

Manufacturing is an essential aspect of every thriving economy. It is a driver that cannot be overemphasized. This is so because production of goods and service is what ensures a continuous growth of the economy. It is therefore imperative to ensure the sustainability of this key tool. This study reviews the various elements of manufacturing, the strengths and constraints of sustainable manufacturing especially in Africa. The study concludes that manufacturing is sustainable provided the needed support from key players is available and can drive an economy to fast development.
Response of Various Extrusion Parameters to Different Outputs: Review
Authors: Mufutau Azeez Temitayo , Aderemi Bello Kazeem , Saheed Akande , Princess Okokpujie Imhade , Sunday Afolalu Adeniran
Published: October 2023

Extrusion as a process involves the introduction of compressive force to drive metal sample out of the die in order to subject it to plastic deformation which in turn will enhance both mechanical and metallurgical properties of aluminum. One input parameter can as well impact other parameters of extrusion. The extent of mechanical properties improvement and effects on other factors depends on adequate selection of the process (input) parameters. The interaction of these parameters influenced the responses (output parameters) in different way. Therefore, this review paper focused on extrusion processes, different extrusion input and responses and related work by different researchers on how different extrusion parameters influences different responses
Investigating the Influence of Rubber Seed Oil and Used Cooking Oil on Diesel
Authors: Aderemi Bello Kazeem , Mufutau Azeez Temitayo , Mariam Tawose Olayinka , Olabisi Odesanya Kazeem , Odumosu Odumuyiwa A. , Ajani Oyelaran Olatunde
Published: October 2023

In view of the multiple issues associated with fossil fuels, an environmentally friendly and economically feasible alternative energy source is required. While sufficient research has been conducted on diesel and single biodiesel blends, only a few studies on dual blended biodiesel have been conducted in this respect. The significance of blending waste cooking oil and rubber seed oil mixed with diesel at different proportions is investigated in the present research. At different braking power levels, the impacts of dual biodiesel (DB) performance and exhaust fumes on the stationary single-cylinder four-stroke air-cooled diesel engine with electrical loads were evaluated. The engine speed was held constant at 2800 rpm all through the testing. Each load was tested three times. Blend A had relatively better thermal and mechanical efficiency than diesel, based on experimental investigation results. Blends B and C were almost identical to the diesel values. Specific fuel consumption statistics for dual biodiesel blends were similar to diesel. The influence of different mixes on CO, CO2, HC, NOx, and smoke opacity were studied using emission tests. In contrast to diesel, the dual biodiesel blends produced more fumes, hydrocarbons, and nitrogen oxides. Dual biodiesel blends, on the other hand, have lesser emissions temperatures than diesel.
Impact of material selection on the efficiency of the crushing unit low-medium carbon steel
Authors: Edun Bose Mosunmola , Ajayi Oluseyi Olanrewaju , Afolalu Sunday Adeniran , Nwankwo Samuel Obinna
Published: October 2023

The quest for sustainability in feed production industries and crushing machines in agricultural sectors that are more efficient have introduced the use of proper material for hammer material. Around the world, the manufacture of feed from animal waste is expanding quickly, and crushing equipment is now essential to enabling reliability. The issue of early failure of the crushing machine’s main components, however, is a challenge for the feed industries and has a direct impact on the machine’s maintenance, dependability, and running costs. A significant number of technical components have been created during the past decade for industrial applications employing novel materials and cutting-edge technologies through the development of carburisation. As a result, this review offers a concise summary of the most recent analysis of tribological issues related to crushing hammers made of low and medium-carbon steels. Recent studies on innovative crushing material design, improvement in hammer surface engineering, use of case-hardened hammers with a focus on material selection, crushing machine design optimisation, and failure mode analysis are included in the study. Additionally, it will intricate on the heat treatment technology’s present constraints and its future opportunities.
Recycling of animal bone as partial replacement for coarse aggregate in lightweight hollow sandcrete blocks
Authors: Edun Bose Mosunmola , Ajayi Oluseyi Olanrewaju , Afolalu Sunday Adeniran , Nwankwo Samuel Obinna , Fajugbagbe Atinuke Afolabi
Published: October 2023

Animal bone waste (ABW) is hazardous to the environment and necessitates a sizable area for disposal. This study aims to employ animal bone waste (ABW) in functionalised compact concrete as a partial substitution for cementitious materials, the source of which are both unswerving and appropriate for substitute preventive solutions promotes the industry’s ecological sustainability by minimizing and reducing the negative impact of the concrete industry due to the explosive usage of raw materials. As a result, this paper examines the impact of using crushed animal bones as coarse aggregates in place of sand and cement in the production of concrete. With an improved step level of 10% through cement mass, ABW was applied at a percentage range of 0 to 40%. Bone’s various characteristics in its fresh and hardened states were looked examined. A Sieve shaker machine was employed to sieve the bone after which the bone was boiled and dried to remove moisture. To evaluate whether the employed aggregates and crushed animal bone were suitable for use in concrete, a physical analysis of each was performed.
Development of a nano-hybrid coolant for machining operation
Authors: Afolalu Sunday Adeiran , Ogedengbe Temitayo Samson , Ikumapayi Omolayo Michael , Emetere Moses Eterigho , Oyebode Oluwadare Joshua
Published: October 2023

This study involved the development of a nanofluid and its experimental use during a machining operation for enhancement of the surface profile of a mild steel rod. Silica nanoparticles were made from coconut shell and rice husk using a chemical process, and then disseminated into distilled water to create the hybrid nanofluid. A control sample was used to compare the performance of the created nano machining fluid. The mild steel samples had a better surface roughness when nano machining fluids were used.
Experimental Investigation and Optimization of EDM process in different Paramaters on NICKEL material (nimonic 8A)
Authors: R. Jayaraj , N. Sateesh , Ram Subbiah , B.Ch. Nookaraju
Published: October 2023

Newly prepared Nickel alloy (Nimonic80A As Per ASTM B637 Alloy-N07080) using powder metallurgy is considered in this investigation. In Conventional machining, Nickel alloys produce higher tool wear rate , poor surface Finish, but this can be reduced by Electrical Discharge Machining (EDM) method. Nickel alloy(Nimonic80Aas per ASTM B637 Alloy-N07080) presently used in wide variety of applications such as Automobiles, Aerospace industries, because of their high strength to temperature ratio. In this project, Nickel alloy (Nimonic80A as per ASTM B637 Alloy-N07080) is taken with different types of EDM Properties. Before that Chemical characteristics in addition machinelike possessions as well as to a degree Tensile test,Charpy test are administered on for judgment substance moreover severity of the material plus from that timeforward we acted EDM process by utilizing of TAGUCHI procedure. Results of tests are resolved to select high quality surface finish moreover fastest process for material request.
Failure Investigation of Superheater Through Investigate the Nearest Component
Authors: Latif Nizhamul , Triwibowo  , Yuliani Hanif , Astini Vita
Published: October 2023

The failure of the superheater (SH) tube can cause the power plant to stop operating. A study was conducted to detect the cause of tube leak at the failure of the superheater in HRSG. This study investigated the mechanism of degradation and leak of SH HRSG by examining the SH tube adjacent to the failed SH tube. Because the failed sample was not found, this investigation was essential for the failure prevention of the recurring problem. This problem was analyzed through metallography examination, hardness test, Finite Element Method (FEM) simulation, SEM/EDS review, and tensile testing. The analysis showed that the cause of the superheater tube bending was the presence of a hotspot, which was assumed to happen when the lower flue gas flap was opened for a long time while the fluid circulation system in the superheater tube was not functioning perfectly. As a result, the thermal stress that occurs exceeds the yield strength.