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Optimization of Friction Stir Welding Parameters Using Taguchi Method for Aerospace Applications
The current research work investigated the optimization of the input parameters for the friction stir welding of AA3103 and AA7075 aluminum alloys for its applications in aerospace components. Friction stir welding is rapidly growing welding process which is being widely used in aerospace industries due to the added advantage of strong strengths without any residual stresses and minimal weld defects, in addition to its flexibility with respect to the position and direction of welding. Thus, the demand for this type of welding is very high; however, the welding of aluminum alloys is a key aspect for its use in aircraft components, particularly with respect to bracket mounting frames, braces and wing components. Henceforth in the current work, research is focused on optimization of welding of aluminum alloys, viz. AA 3103 and AA 7075; AA 3103 is a non-heat treatable alloy which is having good weldability, while AA 7075 is having higher strength. Therefore, the welding of these aluminum alloys will produce superior mechanical properties. The optimization of input parameters was accomplished in this work based on L9 orthogonal array designed in accordance with Taguchi methodusing which the friction stir welding experiment was conducted. There were nine experimental runs in total after formulating the L9 orthogonal array table in Minitab software. The input parameters which were selected for optimization weretool rotation speed, feed rate, tool pin profile. The output parameters which were optimized were hardness, tensile strength and impact strength. In addition, the microstructure of the fractured surfaces of the friction stir welded joint was analyzed. It was found from the optimization of the process parameters that strong friction stir welded joints for aerospace applications can be produced at an optimized set of parameters of tool rotational speed of 1100rpm, traverse speed of 15mm/min with a FSW tool of triangular pin profile of H13 tool steel material. 2020, Springer Nature Singapore Pte Ltd. -
Optimizing energy consumption in wireless sensor networks using python libraries
Wireless sensor networks (WSNs) are widely utilized in various fields, including environmental monitoring, healthcare, and industrial automation. Optimizing energy consumption is one of the most challenging aspects of WSNs due to the limited capacity of the batteries that power the sensors. This chapter explores using Python libraries to optimize the energy consumption of WSNs. In WSNs, various nodes, including sensor, relay, and sink nodes, are introduced. How Python libraries such as NumPy, Pandas, Scikit-Learn, and Matplotlib can be used to optimize energy consumption is discussed. Techniques for optimizing energy consumption, such as data aggregation, duty cycling, and power management, are also presented. By employing these techniques and Python libraries, the energy consumption of WSNs can be drastically decreased, thereby extending battery life and boosting performance. 2023, IGI Global. All rights reserved. -
Optimizing operational cost and delivery of online food delivery apps using high-tech vending machines
Consider the present scenario of placing online food orders while traveling, waiting for them, and struggling to collect them on time. This issue can be addressed by creating and deploying a fully functional high-tech vending machine. With the evolution of technology and the necessity for constant improvement in service quality, customers are thriving for a better customer experience. This article aims to design and methodologically assess the importance of installing vending machines around the most crowded public transportation hubs by dispensing purchased food or beverages online. It focuses on providing a convenient delivery mode for online-ordered food at travel boarding points and public gatherings. Vending machines at these locations gather and distribute food to consumers based on orders from online food delivery apps such as Swiggy, and Zomato, thus optimizing and improving the delivery experience. It focuses on optimizing the operational cost associated with online food delivery platforms and reducing the carbon emissions contributed by multiple deliveries that happen towards the common drop-off points. 2024 Srinesh Thakur, Anvita Electronics, 16-11-762, Vijetha Golden Empire, Hyderabad. -
Orality, Literacy, and Modernity: A Reading of The Legends of Khasak
What is the relationship between literacy and culture? It is not possible to give a simple answer to this question. Eric Havelock, while commenting on ancient Greek culture and literacy, observes that the classic culture of Greece had attained an advanced stage even before the emergence of Greek script. It continued to exist as an oral culture for a long time (Havelock 1963, 117120). A culture without a script is not uncivilized or underdeveloped. Havelock observes: One can propose with assurance that the pre-Homeric epoch the Dark Age yields for the historian what might be called a controlled experiment in non-literacy. Here, if anywhere, we can study those conditions on which a total culture, and a very complex one, relied for its preservation upon oral tradition alone. (pp. 11718) 2025 selection and editorial matter, E.V. Ramakrishnan and K.C. Muraleedharan; individual chapters, the contributors. -
Organizing data using lists: A sequential data structure
Computer programming aims to organize and process data to get the desired result. Software developer chooses a programming language for application development based on the data processing capabilities of the language. The list is one of the sequential data structures in Python. A list is limited to a particular data type, such as numbers or strings. Occasionally, a list may include data of mixed types, including numbers and strings. Elements in the list can be accessed by using the index. Usually, a list's elements are enclosed within square brackets and divided using commas. The list may be referred to as a dynamic-sized array, which denotes that its size increases as additional data is added and that its size is not predefined. List data structure allows repetition; hence, a single data item may appear several times in a list. The list assists us in solving several real-world problems. This chapter deals with the list's creation and manipulation, the complexity of processing the list, sorting, stack, and queue operations. 2023, IGI Global. All rights reserved. -
Overview of Cyber Security in Intelligent and Sustainable Manufacturing
With the advent of the Internet of Things (IoT), a new transformation is predominant in the manufacturing industry, termed Industry 4.0. The revolution of IoT with artificial intelligence, Web3, robotics, and automation has transformed the traditional manufacturing system into a smart manufacturing system (SMS) by adding an intelligent component capable of automatic data collection through using sensors, processing data autonomously, and controlling machines remotely. However, adding automated intelligence, autonomous systems, and real-time data processing presents an insecure surface to cyber attackers to penetrate these cyber-physical systems (CPSs) and cause physical damage. This chapter presents a detailed discussion of cyber threats and incidents in the intelligent manufacturing industry, along with the available acceptable mitigation strategies. A taxonomy of cyber attacks on intelligent manufacturing systems clearly shows the difference between information technology threats and smart manufacturing cyber-threats. A detailed discussion on the limitations of SMSs in implementing cyber security is presented. Finally, some innovative machine learningbased security mechanisms (ML-based intrusion detection systems) are discussed that promise to detect anomalies/intrusions in such systems. 2025 selection and editorial matter, Ajay Kumar, Parveen Kumar, Yang Liu, and Rakesh Kumar. -
Pandemic recovery strategies: A disaster management tourism framework
Purpose: The leisure industry is colossally impacted by varied types of crisis. Assessing the volatility; an attempt is made towards disaster planning and a response system. This chapter indicates an all-inclusive integrated approach to deal with disasters and narrates conceptual and latest factual findings in the space of disaster management. An efficient and self-equipped attraction demands a competent and efficient disaster management system in place. Methodology: This chapter devises measures to deal with the capacity of a destination during pandemic and proposes recovering strategies for the leisure business. Destination governance and disaster management techniques are well explored in the proposed chapter. Findings: An imperative study of this nature will determine the role of cultural perceptions of varied risk and threats in a pandemic scenario. Innovative practices of disaster governance and Post-disaster recovery strategies are crucial mechanisms for the sustenance of tourism and hospitality sector. Originality-Value: The conceptual ideas and outcomes obtained in this chapter helps policy makers not only to find new strategies to placate the negative impacts of COVID-19 on the organic image of tourist destinations but also assists in accelerating the recovery timeframe just after the pandemic. 2022 Joseph Chacko Chennattuserry, Bindi Varghese, N Elangovan and H Sandhya. -
Pandemic Resilient Organizational Behaviour: From the Lens of Stakeholder and Legitimacy Theory
The Covid-19 pandemic spread on global map with unprecedented speed and created an environment of uncertainty, anxiety and disruption. India, being a densely populated country, had been looked upon with apprehension and later on with great admiration in controlling and managing the pandemic and its devastating effect. The study has built a thematic model for short-term and long-term pandemic resilient organizational practices based on stakeholder and legitimacy theory, which focuses on aligning business with societal values and stakeholder expectations. The foci have been stakeholder groups of employees, customers, suppliers and community. Sustainability reports of selected Indian companies based on GRI standards for FY from 2019 to 2022 are then scored based on the developed model. Further analysis explored changes in risk reporting framework in pandemic and post pandemic. The thematic coverage in sustainability reports for employees and community found a prominent place emphasizing the importance of these groups. The thematic disclosures for suppliers are the least disclosed, indicating areas for improvement in the business practices. Based on this thematic model, suggestions are also made for additional disclosure indicators in the GRI framework for stakeholder group of suppliers and customers. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Pandemic, War and Geo-Political Risk: The Outlook for Global Economy
This Chapter analyses the world economic outlook in the backdrop of the Pandemic, the Russia-Ukraine war, geo-political tensions, and social unrest emerging around the world. The COVID-19 Pandemic an unwanted gift from the nature spreading across the nations in multiple waves and mutation has devastated the global economy. The governments and central banks responded with huge bailouts to beat the potential recession that led to excess liquidity and demand-pull inflation. The global GDP declined due to multiple lockdowns to contain the spread of the virus. Due to scarcity of inputs, labour and supply chain disruptions the cost of production surged and augmented cost-push inflation. Further, the Russian invasion of Ukraine aggravated the supply-side shocks from sanctions and energy and food inflation surgeda 38-year highto 6.7 percent in advanced economies and 8.7 percent in emerging markets and developing economies creating misery among people particularly in the low-income countries. The running magnitude of inflation complicated the policy efforts, and the central banks and governments reversed the trade-off for inflation from safeguarding the growth. Besides, the social unrest in developed countries (Canada, New Zealand, the US, Austria, the Netherland) and developing countries (Chile, Algeria, Iran, Iraq, Lebanon, Brazil, Belarus, Sri Lanka, Ethiopia, Burkina Faso, Tajikistan, and Sudan) have added the geo-political tensions (China and Taiwan) worsening the world economic outlook. The first section of this chapter narrates the COVID-19 pandemic impact (loss of lives and livelihood), leading to declining trends in global GDP, income, employment and international trade, and increasing trends in poverty, unemployment, inequality and inflation. The second section analyses the impact of the Russian invasion of Ukraine and social unrest gathering around the world leading to geo-political tensions, supply-side shocks and inflation trending to a level not seen in the last four decades. The policy efforts reversed to monetary tightening and increasing the interest rates causing capital outflows, currency depreciation and foreign exchange reserve meltdown. Developing countries with limited fiscal space to counteract are prone to prolonged stagflation (inflation plus unemployment) and skewflation risk (product prices rising but asset prices falling). In the near-term, the global economy is facing an extremely challenging outlook due to sharply rising food, fertilizer and energy prices, and rising interest rates, capital outflows, currency depreciation and unsustainable levels of external debt. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Paradigm shift from AI to XAI of Society 5.0: Machine-centric to human-centric
Artificial intelligence (AI), the Internet of things (IoT), and robotics have gained significant momentum to meet expectations in many applications. Data management has become a tedious job as businesses grow. The interruption of AI in business functions and a growing web-based service economy in the last decade have led the IoT to grow faster, reducing the tedious job. Timely interruption of eXplainable artificial intelligence (XAI) reduces the technical complexities. On the one hand, the AI of Industry 4.0 promises the easiness of business functions. On the other hand, XAI of Society 5.0 tends to ease people's social life. This chapter ascertains the impact of AI on significant business functions and tries to bring out challenges AI faces and ethical values that must be considered in business functions. This chapter also tries to shed some light on the evolution of XAI of Society 5.0 and reasons for the shift from AI to XAI or machine-centric to human-centric and concludes by highlighting the future of XAI. 2024 Elsevier Inc. All rights reserved. -
Parallel organizations and subversion of the grass-roots democracy in Andhra Pradesh
[No abstract available] -
Patents and Innovations for Digital Sustainability
With technology growing at a rapid pace, a major issue which is being faced is the problem of effective energy usage and sustainability such that the future generation does not have to bear the brunt of our actions. Through the course of the chapter, the various innovations and patents in the field of digital sustainability are explored which are vital for the preservation of the planet. Patents play a crucial role in promoting innovations and development, as well as protecting the rights of inventors. The varied recent developments in the field of energy sustainability and explaining their work while assessing their contribution to the field are the focus of this chapter. The chapter also provides a comprehensive overview of the relationship between patents and innovations in digital sustainability, offering insights and guidance for researchers, practitioners, and policymakers working in this field. 2024 selection and editorial matter, Vandana Sharma, Balamurugan Balusamy, Munish Sabharwal, and Mariya Ouaissa. -
Pathway toDetect Cancer Tumor byGenetic Mutation
Cancer detection is one of the challenging tasks due to the unavailability of proper medical facilities. The survival of cancer patients depends upon early detection and medication. The main cause of the disease is due to several genetic mutations which form cancer tumors. Identification of genetic mutation is a time-consuming task. This creates a lot of difficulties for the molecular pathologist. A molecular pathologist selects a list of gene variations to analyze manually. The clinical evidence strips belong to nine classes, but the classification principle is still unknown. This implementation proposes a multi-class classifier to classify genetic mutations based on clinical evidence. Natural language processing analyzes the clinical text of evidence of gene mutations. Machine learning algorithms like K-nearest neighbor, linear support vector machine, and stacking models are applied to the collected text dataset, which contains information about the genetic mutations and other clinical pieces of evidence that pathology uses to classify the gene mutations. In this implementation, nine genetic variations have been taken, considered a multi-class classification problem. Here, each data point is classified among the nine classes of gene mutation. The performance of the machine learning models is analyzed on the gene, variance, and text features. The gene, variance, and text features are analyzed individually with univariate analysis. Then K-nearest neighbor, linear support vector machine, and stacking model are applied to the combined features of a gene, variance, and text. In the experiment, support vector machine gives better results as compared to other models because this model provides fewer misclassification points. Based on the variants of gene mutation, the risk of cancer can be detected, and medications can be given. This chapter will motivate the readers, researchers, and scholars of this field for future investigations. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Pattern of Carbon Dioxide Emission, Economic Growth and Energy Consumption in South-Asian Countries: An Empirical Analysis
The main aim of this chapter is to analyse the pattern of environmental pollution as represented by per capita carbon dioxide emission (PCCO2), per capita gross domestic product (PCGDP) and per capita energy consumption (PCEC) and their nexus in case of South-Asian countries for the time period 19912014. Econometric tools such as panel co-integration and fully modified ordinary least squares have been used to study the relations. A positive significant relationship has been observed between PCGDP and PCCO2 emission. In addition, an increase in PCEC also has a positively significant impact on PCCO2 emission. Therefore, the governments of all the countries need to come together and take steps to curb the rising carbon emission since neither the problem nor the responsibility is restricted to one country alone. There is a need for countries to increase the consumption of renewable energy and explore alternate options that are fewer dependents on coal or any other fossil fuel. On priority, economies in South-Asian region should focus on sustainable economic activities by balancing growth of economy with clean environment. 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
Perceived cyber security challenges in adoption and diffusion of FinTech services in India
FinTech is a term that refers to a new type of digital technology that intends to build up and automate the distribution and management of financial services. FinTech is an abbreviation for "financial technology." FinTech, or financial technology, assists companies, business holders, and consumers in managing their financial procedures and methods. The high adoption rate of fintech services creates a whole ecosystem of looters and hackers. This indeed is scary, and this chapter makes an attempt to understand the adoption rate of fintech services and diffusion challenges at the same time. 2023, IGI Global. -
Perception about inventory management and control at quick service restaurants
India's quick service restaurant market has expanded significantly in recent years. For small-scale QSRs, inventory management continues to be an essential challenge. Inventory management enhances the efficiency of business operations by influencing the stockpile and supply of essential products and materials. The research aims to highlight the importance of inventory control and management in QSRs. Primary data was collected from 120 operational QSRs in Bangalore in Karnataka and 30 from Kottayam in Kerala. It was found that most of the respondents felt that proper inventory management and control could help to improve their service quality and help to reduce costs. It has been found that the factors service, savings, and risk have a strong positive correlation with inventory cost. Several techniques and strategies like techniques for cooking with no waste, menu planning with fewer ingredients, networks for local sourcing, matching demand and supply through seasonal planning have been identified to increase the performance of QSRs. 2024, IGI Global. All rights reserved. -
Perception of online adult education in different countries
Adult education has gained immense popularity during a pandemic. Adult learners are able to meet their educational requirements through online education. Adult learners also prefer online education due to convenience and self-learning interests. Online education also poses challenges and discomfort to online learners. Statistics indicate a higher dropout rate among adult online learners due to various factors. This chapter focuses on the significant challenges adult online learners face and has identified tools, strategies, and techniques to empower and motivate them. This chapter will also help us to understand how tools and techniques, such as information and communication technology, allow us to increase the number of such learners in different countries. Information and communication technology tools are used in developed and developing countries to encourage and motivate adult learners to improve their education virtually at their convenience. 2023, IGI Global. All rights reserved. -
Performance analysis and interpretation using data visualization
The matrix plot library (Matplotlib) is a unique feature in python that helps in the visualization of data via entering certain dataset and codes. It is a portable two-dimension of plot and images are mainly focused on visualizing scientific, technical, and financial data. These matrix plots are performing with the help of python programming and various user interface applications. Most familiar versions of joint photographic and supportable picture graphics are used for the picture visualization. These additional features include the various navigation processes, pages with the line, as well as images. The financial charts of open source website are used for tables and mathematical texts. The library is based on numerical python arrays, giving us visual access to massive quantities of data in readily consumable graphics. The problem statement here delves further into the functions of this feature, which will aid in a better understanding of Python's involvement in the data visualization. 2023 Scrivener Publishing LLC. -
Performance Analysis of Logistic Regression, KNN, SVM, Nae Bayes Classifier for Healthcare Application During COVID-19
Heart disease is one of the main causes of mortality in India and the USA. According to statistics, a person dies out of a heart-related disease every 36s. COVID-19 has introduced several problems that have intensified the issue, resulting in increased deaths associated to heart disease and diabetes. The entire world is searching for new technology to address thesechallenges. Artificial intelligence [AI] and machine learning [ML] are considered as the technologies, which are capable of implementing a remarkable change in the lives of common people. Health care is the domain, which is expected to get the desirable benefit to implement a positive change in the lives of common people and the society at large. Previous pandemics have given enough evidence for the utilization of AI-ML algorithm as an effective tool to fight against and control the pandemic. The present epidemic, which is caused by Sars-Cov-2, has created several challenges that necessitate the rapid use of cutting-edge technology and healthcare domain expertise in order to save lives. AI-ML is used for various tasks during pandemic like tracing contacts, managing healthcare-related emergencies, automatic bed allocation, recommending nearby hospitals, recommending vaccine centers nearby, drug-related information sharing, recommending locations by utilizing their mobile location. Prediction techniques are used to save lives as early detections help to save lives. One of the problems that might make a person suffering from COVID-19 extremely sick is heart disease. In this research, four distinct machine learning algorithms are used to try to detect heart disease earlier. Many lives can be saved if heart disease can be predicted earlier. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.