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ETL and Business Analytics Correlation Mapping with Software Engineering
Large information approach can't be effectively accomplished utilizing customary information investigation strategies. Rather, unstructured information requires specific information demonstrating methods, apparatuses, and frameworks to separate experiences and data varying by associations. Information science is a logical methodology that applies scientific and measurable thoughts and PC instruments for preparing large information. At present, we all are seeing an exceptional development of data created worldwide and on the web to bring about the idea of large information. Information science is a significant testing zone because of the complexities engaged with consolidating and applying various strategies, calculations, and complex programming procedures to perform insightful investigation in huge volumes of information. Thus, the field of information science has developed from enormous information, or huge information and information science are indistinguishable. In this article we have tried to create bridge between ETL and software engineering. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Analysis of Reinforced Concrete Structure Subjected to Blast Loads Without and with Carbon Fibres
In the past few decades, the terrorist attack on buildings has significantly increased. Blast loads due to explosions cause severe damage to the buildings structural and non-structural elements which may also lead to progressive collapse of the building. Hence, there is a need for the structures to be analysed and designed for blast loads in addition to the conventional loads. An investigation is undertaken to minimize the damage of a G+3 storied building and by improving the mechanical properties such as compressive strength, nonlinear behaviour of M40 grade concrete by adding carbon fibres in different dosages. A finite element model of G+3 storied building has been created using Ansys/LS Dyna to analyse the structure subjected to a blast load with charge weights of 50 kg, 100 kg, 150 kg at 3000 mm standoff distance. The lateral deflections and strains of the structure are determined for different charge weights to study the behaviour of the structure when subjected to blast loads. The addition of carbon fibres has improved the behaviour of structure by reducing the strains and deflections and optimum dosage of fibres is also determined in this paper. 2023, Springer Science and Business Media Deutschland GmbH. All rights reserved. -
An Outlook of Gender Differential Happiness in India
Studies on happiness and subjective wellbeing, in general, are aplenty, but applying a gender lens to it is comparatively rare, especially in the Indian context. The social construction of gender roles will influence happiness being a subjective matter. This paper explores this idea of gender differential happiness in light of India's peculiar social and cultural context. Using the World Value Survey (WVS) for India (Wave 6) in 2012 and Ordinary Least Square (OLS) regression analysis, the study finds that self-reported happiness is gender differential in India. Factors such as marital status, educational attainments, managerial roles and thrust on women empowerment were found to be vital for happiness for all. However, there are visible patriarchal gender stereotype notions with factors such as individual autonomy and homemaking. 2024 IEEE. -
Integration of enterprise resource planning system as an effective technology for increasing business productivity
Enterprise Resource Planning (ERP) refers to a potential software, which organisations utilise for managing daily basis activities such as proper accounting, project management, compliance as well as procurement actions within organisational standards for achieving better business performance. This research focuses on understanding ways of ERP usage of businesses for enhancing potential procurement as well as accounting for assuring best performance achievement. Literature from different company reports and other sources has been implemented that brings out an understanding of productivity optimisation of organisations using ERP. It also focuses on illustrating different types of ERP along with assuring better data visibility aspects of the ERP usage for allowing consumers to view real time data while progressing with business relationships and enabling higher procurement standards. The research aims to investigate ways in which different types of ERP are used by organisations for assuring better accounting performance and procurement standards in their marketing environment. Hypothesis is a positive association between ERP utilisation and implementation in organisation and its accounting and procurement standards, achieving high performance in the competitive market. Methodology used in this research involves Exploratory research design with a probability sampling for bringing out best possible outcomes of the research. Sample sizes include secondary sources such as articles, journals and relevant company reports and databases for understanding ways in which ERP helps in attaining suitable accounting and procurement practices of businesses within organisational standards. Results as well as implications indicate an optimal relation of proper risk management through enhancing ERP and usage of most suitable ERP that assures best possible procurement and accounting practices for businesses to get competitive advantage in the market. 2024 Author(s). -
Synergizing Insights for Precise Rice Leaf Disease Diagnosis Via Multi-Modal Fusion
Rice holds a significant position in India, especially in the southern part of the country, where people tend to eat some rice at least once a day. Farmers are facing a huge loss due to diseases in leaf, which is the main problem of agriculture. By using techniques like machine learning, main problems detection can be done. This review, discusses common plant diseases that affect the leaf. Some include Leaf Spots, Rusts, Fusarium Wilt, Early Blight, Powdery Mildew and Downey Mildew. Our research found that machine learning techniques on rice plants make finding diseases on leaves easier. Finally, we concluded that the most accurate method is the Enhanced VGG16, with an accuracy of 99.60% because it is really good at spotting diseases on rice leaves because it's great at recognizing the small details and patterns in leaf pictures. This helps it to tell the diseases apart more accurately and make fewer mistakes in identifying them. 2024 IEEE. -
Analysis on thermal sensitivity of 2D Profilometer used for TMT Glass Polishing
TMT adopts Stressed Mirror Polishing (SMP) technology for the polishing of mirror segments. In this process, the meniscus type spherical shape glass blanks are converted in to a desired aspheric shape by spherical grinding and polishing in the stressed condition. After each grinding and polishing activity metrological measurements are done using different metrology tools. The metrology tool named as 2D-Profilometer is used for low frequency error/foam measurements. It consists of 61 high precision length gauges attached to Carbon Fiber Reinforced Polymer (CFRP) sandwiched Aluminum panel of diameter 1.6 meter in spiral direction. The coefficient of thermal of CFRP is very low however, a small delta temperature variation between the top and bottom sheet of CFRP of the panel will lead to panel bowing which will result in increasing power error. Hence, the objective this work is to analyse the thermal sensitivity of the 2D Profilometer. 2024 SPIE. -
Adoption of Fintech Towards Asset and Wealth Management: Understanding the Recent Scenario in India
The finance sector as a whole has seen a significant transformation as a result of technological advances, which has impacted how financial institutions function and how financial activities are carried out. Fintech is currently a facilitator and a disruptor. Today Fintech companies have the greatest influence on the wealth management industry financial technology, or Fintech, began with nimbler start-ups upending banks with their innovative methods, and later developed into the latter forging partnerships with banks to strengthen the whole financial services ecosystem. At the intersection of both money and technology, the term wealthtech was developed. Any digital solution designed to simplify wealth management procedures is referred to as digital wealth management solutions. The fintech sector, which also encompasses digital payments, regulatory technology, insurance technology, etc., includes wealthtech. Fintech in wealth management has created a paradigm change in the investing sector. Wealthtech's technology is disrupting the wealth management industry. This study analyses the recent development of the wealth management industry and financial investment in the digital Indian age. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2023. -
A Voting Enabled Predictive Approach for Hate Speech Detection
In today's digital environment, hate speech, which is defined as disparaging and discriminating communication based on personal characteristics, presents a big difficulty. Hate crimes and the rising amount of such content on social media platforms are two examples of how it is having an impact. Large volumes of textual data require manual analysis and categorization, which is tedious and subject to prejudice. Machine learning (ML) technologies have the ability to automate hate speech identification with increased objectivity and accuracy in order to overcome these constraints. This article intends to give a comparative analysis of various ML models for the identification of hate speech. The proliferation of such content online and its negative repercussions on people and society are explored, as is the necessity for automated hate speech recognition. This paper intends to support the creation of efficient hate speech detection systems by performing a comparative analysis of ML models. Random forest records the best performance with higher accuracy and low response delay period for hate speech detection. The results will help enhance automated text classification algorithms and, in the end, promote a safer and more welcoming online environment by illuminating the benefits and drawbacks of various approaches. 2023 IEEE. -
Organizational Preparedness for Navigating Disruption Towards Sustainability: Strategies Analysis
The study explores how design thinking principles can be leveraged to enhance an organization's preparedness for disruptive innovation. To address this challenge, the authors sought to empathize with their clients, recognizing the need for a comprehensive evaluation. A framework guided by five fundamental principles - Scrutiny, Bravery, Resilience, Prosperous and Perseverance - was developed that integrates user-centred design methodologies to evaluate an organization's strengths and weaknesses in the face of disruption. We analysed and interpreted the intricacies of emerging market disruptions, providing organizations with the GroKalp Assessment Tool, an automated tool for self-evaluation and strategic adjustment leading towards a sustainable future. These principles were further broken down into fifteen distinct parameters, each thoughtfully designed to offer organizations a detailed and insightful method for evaluating their responses to the relentless waves of transformative innovation. By utilizing the GroKalp Assessment Tool, organizations can position themselves in one of three categories: Innovators, Adapters, or Resistance Fighters. Design thinking tools are vital in this process, as they encourage creative problem-solving, innovation, and adaptation in an era of rapid technological change. The Authors. -
Effect of Temperature on Electrical Properties of Reduced Graphene Oxide (rGO)/Li-ion Embedded Flexible Solid Polymer Electrolyte Films
Reduced graphene oxide (rGO) was synthesized from graphite powder by modified Hummers method. The rGO is emerged with Polystyrene sulfonic acid/Lithium phosphate to prepare PL-rGO solid polymer electrolyte films. The electrical properties of Polystyrene sulfonic acid/Lithium phosphate/reduced graphene oxide composites were analyzed, which is an essential property to obtain the performance, reliability and lifetime of battery with respect to temperature. The mass and charge transfer process that takes place at the interface of electrode and electrolyte was obtained by Impedance analyzer. The Nyquist plots were plotted in the frequency range 1 Hz-35 MHz at different temperatures (30-100OC). The ionic conductivity of PL-rGO polymer electrolyte is 1.4x10-3 S/c.m has been observed for the composition PSSA/Li3PO4/rGO::50:45:05 wt%. The conductivity of PL-rGO composites is directly related to temperature. The hopping of the ions in the PL-rGO is observed by using dc conductivity which follows the Arrhenius relationship. 2019 Elsevier Ltd. -
An Innovative Way of Trackable GDS in the Field of CC
It is important to provide security and efficient data exchange in cloud infrastructure and achieve traceability and anonymity of data. mean For high levels of safety and performance in one Anonymously, this article addresses the topic It allows data to be exchanged and stored between members of the same group in the cloud. Proposed arrangement creates unique and traceable group data sharing policies using group signatures and special agreements Strategies to accomplish these goals. this Facilitates anonymous communication between systems Public clouds have many users and. Real people following up when needed. Also, the system implements the main agreement programs to make it easier for team members to. Obtain a shared session key for secure data exchange and storage facilities. Basic generation processes a Symmetric Balanced Incomplete Block Theory (SBIBD), significantly reducing the workload of team members a shared session key must be introduced. In cloud computing contexts, the suggested system guarantees efficiency and security for group data sharing, as shown by theoretical analysis and experimental validation. 2024 IEEE. -
Blockchain Technology: Applications and Challenges in Computer Science
In the growth of computer science blockchain technology has emerged as a disruptive force that is enhancing various area of software and the way data is managed, stored, and safeguarded. This essay offers a thorough examination of the uses and difficulties of blockchain technology in computer science. In this essay, blockchain technology has shown itself to be a game-changing innovation with numerous computer science applications. It has the enormous potential to completely transform sectors including finance, supply chain management, healthcare, voting systems, and IoT devices. The software technology is completely achieved with blockchain technology and the main security issue is solved with energy use and scalability. The new opportunities are examined and addressed with this innovation sector for creating effective solutions. 2023 EDP Sciences. All rights reserved. -
Advancing Road Safety through Driver Drowsiness Detection Using Deep Learning Model
Driver drowsiness poses a significant threat to public safety, contributing to numerous road accidents and fatalities annually. Drowsy drivers exhibit characteristic changes in facial expressions and behaviors, including eye closure, head nodding, and yawning. These indicators can be detected through various techniques, including image processing, computer vision, and machine learning. This research investigates a promising approach: utilizing a ResNet-101 deep convolutional neural network (CNN) for driver drowsiness detection based on eye, head, and mouth states. The model was trained on a vast dataset of 2.2 million images, covering diverse driving conditions. Despite achieving a 69% accuracy, suggesting real-world potential, computational limitations restricted training to only a quarter of the data. This necessitates further research with larger datasets and increased resources to enhance accuracy and robustness. 2024 IEEE. -
Mental Workload Estimation Using EEG
Mental workload contributes considerably to the outcome or the performance of any task. The concern of human workload increases during a human-machine collaboration task or in a multitasking environment. This paper presents a comparative study of machine learning algorithms used to estimate workload using Electroencephalography (EEG) data. An open-access EEG dataset acquired during a 'simultaneous capacity (SIMKAP) experiment' and 'no task' is used to create and validate models for binary classification of workload as present and absent respectively. The paper presents an implementation of various classification models that use EEG data to predict the workload. In this paper, implementation for KNN classifier (57.3%), Random Forest classifier (57.19%), MLP network classifier (58.2%), CNN+ LSTM network classifier (58.68%), and LSTM network classifier (61.08%) has been reported. The paper can be further extended to study operator workload in real-time using a brain-computer interface paradigm for any kind of task in a real-world application. The workload classification can be further used in human-machine tasks to decide task allocation between the system to achieve optimal performance in a complex critical system. 2020 IEEE. -
Impact of Homophily on Patient Empowerment: A Study of Online Patient Support Groups
Internet facility has led to emergence of patient support groups. These have gained prominence as these fulfils important benefits to patients. One such benefit is patient empowerment. These online groups provide opportunity to patients to interact with similar ailments and predicaments and who can understand the pain and discomfort felt by the patient. This provides validation for the patient and patients experiences. How does this homophily impacts patient empowerment? This question has been explored in this study. The methodology is based on an online survey of patients visiting such online platforms. In all 701 patients provided the data. Independent variable (homophily) and dependent variable (patient empowerment) have been measured using a 7-point Likert scale. Findings provide that both are weakly correlated, but this correlation is significant. Regression analysis led to a regression model that is fit statistically. This provides basis to encourage patients to visit online support groups. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. -
Impact of Perceived Social Support on Patient Empowerment: A Study of Online Patient Support Groups
Disease-specific online patient support groups have emerged predominantly in last 30years, and these are being visited by a large number of patents. These platforms obviously bring important benefits to the patients visiting them. An important variable is the perceived social support that patients feel they derive while interacting with healthcare providers and fellow patients over there. Patient empowerment is another variable, and which has been found to be a critical factor in overall well-being of patients. How does the perceived social support felt by patients visiting an online patient support group impact their perceived empowerment? This paper explores this question. Research design is associative, and for which the data has been procured online from the patients visiting online patient support groups. The questionnaire comprises of an independent variable (perceived social support) and a dependent variable (patient empowerment). Validated scales have been used. For analysis, a factor analysis was undertaken to reconfirm the validity of the scales. Thereafter, regression equation has been developed to measure the impact. Results show that the model obtained passes the fitness and the independent variable has a significant positive association with patient empowerment. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Hybrid Convolutional Neural Network and Extreme Learning Machine for Kidney Stone Detection
When it comes to diagnosing structural abnormalities including cysts, stones, cancer, congenital malformations, swelling, blocking of urine flow, etc., ultrasound imaging plays a key role in the medical sector. Kidney detection is tough due to the presence of speckle noise and low contrast in ultrasound pictures. This study presents the design and implementation of a system for extracting kidney structures from ultrasound pictures for use in medical procedures such as punctures. To begin, a restored input image is used as a starting point. After that, a Gabor filter is used to lessen the impact of the speckle noise and refine the final image. Improving image quality with histogram equalization. Cell segmentation and area based segmentation were chosen as the two segmentation methods to compare in this investigation. When extracting renal regions, the region-based segmentation is applied to obtain optimal results. Finally, this study refines the segmentation and clip off just the kidney area and training the model by using CNN-ELM model. This method produces an accuracy of about 98.5%, which outperforms CNN and ELM models. 2023 IEEE. -
Self-adaptive Butterfly Optimization for Simultaneous Optimal Integration of Electric Vehicle Fleets and Renewable Distribution Generation
Fuel prices and environmental concerns have prompted an increase in the use of electric vehicle (EV) technology in recent years. Charging stations (CSs) are a great way to support this shift to sustainability. This has increased the demand for EV charging on electrical distribution networks (EDNs). However, optimal EV charging stations along with renewable energy sources (RES) integration can maintain EDN performance. This paper proposes a novel hybrid approach based on self-adaptive butterfly optimization algorithm (SABOA) for optimal integration of EV CSs and RES problems under various EV load growth scenarios. A multi-objective function is created from distribution losses, GHG emissions, and VSI. The ideal locations for CSs and RES are found using SABOA while minimizing the proposed multi-objective function. The simulation results on IEEE 33-bus EDN validate the suggested technique's superiority in terms of global optima. This type of hybrid strategy is required for optimal real-time integration of EV CSs and RES, taking into account emerging high EV load penetrations. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Butterfly Optimization Algorithm-Based Optimal Sizing and Integration of Photovoltaic System in Multi-lateral Distribution Network for Interoperability
In this paper, a new and simple nature-inspired meta-heuristic search algorithm, namely butterfly optimization algorithm (BOA), is proposed for solving the optimal location and sizing of solar photovoltaic (SPV) system. An objective function for distribution loss minimization is formulated and minimized via optimally allocating the SPV system on themain feeder. At the first stage, the computational efficiency of BOA is compared with various other similar works and highlights its superiority in terms of global solution. In thesecond stage, the interoperability requirement of SPV system while determining the location and size of SPV system among multiple laterals in a distribution system is solved without compromises in radiality constraint. Various case studies on standard IEEE 33-bus system have shown the effectiveness of proposed concept of interline-photovoltaic (I-PV) system in improving the distribution system performance in terms of reduced losses and improved voltage profile via redistributing the feeder power flows effectively. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Inverse Hilbert Fractal-Metamaterial Rings for Microstrip Antennas and Wideband Applications
A Novel Metamaterial (MTM) property is obtained using a fractal pattern known as Inverse Hilbert. The Mu-negative(MNG) characteristics have been recovered by adopting NRW method. This MTM characteristic is studied for 2.45 GHz using FR4 epoxy as substrate. The dimension of the substrate is 30mm36mm 1.6mm. This fractal metamaterial structure can be amalgamated with an optimized Microstrip antenna (MSA) for improvement in antenna parameters and can be used for RF energy harvesting. 2022 IEEE.