bluuebunny/crossref_metadata_2025 huggingface dataset:
Challenges in Multilingual High-Density Government Secondary School Classrooms in the Midlands Province in Zimbabwe
Authors: Dube Precious , Mugomba Moreen , Gumbo Lettiah
Published: September 2022

Midlands is multi-linguistic and multicultural province situated at the heart of Zimbabwe, and Gweru is its major city where people from different parts of the country converge. Many languages including Shona, Ndebele¸ Zim English, Chewa¸ Zulu, and Venda are spoken. This study aimed to explore challenges in multi-lingual high density government secondary school classrooms in the Midlands province in Zimbabwe. The study used a qualitative approach involving document analysis, semi-structured interviews, and classroom observations. A purposive sampling was used, and three high density government secondary schools were selected. Nine teachers and 30 learners participated in the study. Data were analyzed by using thematic analysis. Findings have shown a number of challenges, which include lack of confidence among learners, resource constraints, and lack of trained teachers. The study suggests that school management committees should obtain adequate learning materials for learners. Governments should organize professional development courses to train teachers on how to handle multilingual classes.
Multilingualism and Its Impact in Teaching and Learning of Science Education
Authors: Ndlovu Yolanda
Published: September 2022

South Africa is often referred to as the “rainbow nation.” This is due to its many languages and cultural diversity. One would assume that since the country carries its diversity with pride they would honor and celebrate the different languages; however, this is not the case. Most South African schools use English as the medium of instruction although the dominating population are English second language speakers. Recent results from TIMSS prove that learners are performing poorly in science, and previous research has proved the crucial role played by language in the process of teaching and learning. However, not many changes have been implemented by the Department of Education to counteract the challenges. The main objective of the chapter is to present and discuss why multilingualism should be practiced at schools with the focus being on science education. In doing so, the author will discuss and present the shortcomings of the monolingual pedagogy and the impact that multilingualism has in the teaching and learning of science education.
Translanguaging With Immigrant Languages
Authors: Dhokotera Clarah
Published: September 2022

This study reports on the experiences of immigrant parents as they engaged in their children's learning during the COVID-19 lockdowns. Research has shown that the pandemic caused challenges for parents who could not balance family and work. Schoolwork and homework were done with the assistance of the parents. However, there is a paucity of research that seeks to explore parents' and children's practices during homework sessions, and the research engages translanguaging during the homework sessions. Two immigrant children, Taurai (16) and Yeukai (10), and their mother are the participants. A total of 24 homework sessions were recorded in six weeks with each child in the two subjects English Language and Natural Science and five-minute reflective conversations that were recorded after every lesson. The findings reveal that translanguaging was best for the meaning-making process, and the children were able to mirror themselves in the learning content.
Museums in the Digital Age
Authors: Ergin Gamze
Published: September 2022

This chapter examines the transformation of museums into a hybrid space. In this context, a fully digital contemporary museum in Paris, Atelier des Lumieres, has been chosen as a case study. The research aims to answer the following questions: What is the historical process of change in artworks and museum spaces through technical reproduction? What are the factors that shape the museum experience? What is the hybrid museum? How does the museum space and experience transform with digital technological representation methods? The theoretical framework investigates the technological development of museums with a comprehensive literature review. In addition, the study creates a theoretical construct for the hybrid museum experience by examining the changing museum experience with the effects of digitalization. Atelier des Lumieres was investigated for its characteristics of the hybrid museum experience by field research. As a result, the study offers alternative solutions to increase the hybrid museum experience.
Validating the Potency of Attitude in Predicting Intention to Purchase Non-Deceptive Counterfeit Branded Products
Authors: Prabhakar Tushar
Published: September 2022

This study examined the effect of attitude towards counterfeit branded products on purchase intention for such products. It also investigated the difference in the attitude and purchase intention of past buyers and non-buyers of counterfeit branded products. Data were collected from a sample of 133 respondents, using snowball sampling technique. The results of structural equation modeling (SEM) indicated that attitude positively predicts counterfeit purchase intention. Demographic variables had no effect on either of the two constructs. Additionally, the results of an independent sample t-test revealed that past buyers of counterfeit branded products had more favorable attitudes and higher purchase intention towards such products in comparison to non-buyers. The findings provide useful practical insights that can be leveraged by the manufacturers of genuine branded products to combat counterfeiting.
Health Workforce Talent Management in a Post-COVID-19 Digital Age
Authors: Aggarwal Divya , Chaturvedi Vijit , Ramachandran Anandhi
Published: September 2022

The increased usage of digital technology at the workplace is in turn impacting the utilization of human resources in every sector. Technology has proven to be an effective boon in addressing various healthcare issues as evidenced during the recent pandemic. The pandemic has also impacted the healthcare providers and professionals in the way they work, their work-life balance, and their physical, financial, social, and mental wellbeing. While many health workers have lost their lives, those alive have been affected emotionally and have started to change their careers to non-healthcare sectors. With the existing shortage in the health workforce in India, there is a need to ensure the availability of an adequate number of healthcare professionals who are highly motivated and properly trained (aka talent management). This chapter draws on factors affecting the retention of a talented health workforce, influence of the pandemic in the changing healthcare paradigm, and increased adoption of digital technologies to assist human resource managers in developing holistic talent management in the upcoming years.
A Multimodal Writing Framework to Promote Agency
Authors: Dilgard Cortney , Si Qi
Published: September 2022

Digital and online-based writing practices are not a novel or emerging trend. However, multimodal writing instructional practices need more updated guidelines to support teachers in planning effective instruction. Recent research indicates low teacher efficacy scores related to online teaching during the COVID-19 pandemic. In response, this chapter details a multimodal writing framework to promote agency for K-12 instruction and provides guidelines for educators to effectively facilitate students in the multimodal writing process. The authors use the theory of multiliteracies, the theory of design knowledge, and personal digital inquiry to develop the framework's components. The result is a practical framework with practitioner-focused examples of writing projects. By leveraging multimodal writing, teachers can facilitate a higher capacity for writing instruction and personal agency than allowed by traditional methods.
Blockchain-Based Data Market (BCBDM) Framework for Security and Privacy
Authors: Khapre Shailesh Pancham , Dhasarathan Chandramohan , T. Puviyarasi , Goundar Sam
Published: September 2022

In the internet era, incalculable data is generated every day. In the process of data sharing, complex issues such as data privacy and ownership are emerging. Blockchain is a decentralized distributed data storage technology. The introduction of blockchain can eliminate the disadvantages of the centralized data market, but at the same time, distributed data markets have created security and privacy issues. It summarizes the industry status and research progress of the domestic and foreign big data trading markets and refines the nature of the blockchain-based big data sharing and circulation platform. Based on these properties, a blockchain-based data market (BCBDM) framework is proposed, and the security and privacy issues as well as corresponding solutions in this framework are analyzed and discussed. Based on this framework, a data market testing system was implemented, and the feasibility and security of the framework were confirmed.
A Novel Intrusion Detection System for Internet of Things Network Security
Authors: Bediya Arun Kumar , Kumar Rajendra
Published: September 2022

Internet of things (IoT) comprises a developing ecosystem of responsive and interconnected devices, sensors, networks, and software. The internet of things keeps on extending with the number of its different equipment segments for smart cities, healthcare, smart homes, assisted living, smart vehicles, transportation, framework, and many more are the areas where the internet of things benefits human lives. IoT networks are meant to be monitored on real-time events, and if these devices get attacked, it can have an unfavorable effect on the system. This paper discussed many possible attacks at IoT networks and distributed denial of service (DDoS) attack is one of the most dangerous among them. Blockchain technology can be utilized to develop a framework to protect IoT systems; blockchain is a new technology used for cryptocurrency transactions. This paper proposed BIoTIDS an intrusion detection system for the IoT network using blockchain. BIoTIDS is able to detect an intruder in the IoT network and also able to identify DDoS attacks in IoT networks.
A Survey of Blockchain-Based Solutions for IoTs, VANETs, and FANETs
Authors: Abdelhafidh Maroua , Charef Nadia , Ben Mnaouer Adel , Chaari Lamia
Published: September 2022

Recently, the internet of things (IoT) has gained popularity as an enabling technology for wireless connectivity of mobile and/or stationary devices providing useful services for the general public in a collaborative manner. Mobile ad-hoc networks (MANETs) are regarded as a legacy enabling technology for various IoT applications. Vehicular ad-hoc networks (VANETs) and flying ad-hoc networks (FANETs) are specific extensions of MANETs that are drivers of IoT applications. However, IoT is prone to diverse attacks, being branded as the weakest link in the networking chain requiring effective solutions for achieving an acceptable level of security. Blockchain (BC) technology has been identified as an efficient method to remedy IoT security concerns. Therefore, this chapter classifies the attacks targeting IoT, VANETs, and FANETs systems based on their vulnerabilities. This chapter explores a selection of blockchain-based solutions for securing IoT, VANETs, and FANETs and presents open research directions compiled out of the presented solutions as useful guidelines for the readers.
IoT Data Compression and Optimization Techniques in Cloud Storage
Authors: Hossain Kaium , Rahman Mizanur , Roy Shanto
Published: September 2022

This article presents a detailed survey on different data compression and storage optimization techniques in the cloud, their implications, and discussion over future directions. The development of the smart city or smart home systems lies in the development of the Internet of Things (IoT). With the increasing number of IoT devices, the tremendous volume of data is being generated every single day. Therefore, it is necessary to optimize the system's performance by managing, compressing and mining IoT data for smart decision support systems. In this article, the authors surveyed recent approaches with up-to-date outcomes and findings related to the management, mining, compression, and optimization of IoT data. The authors then discuss the scopes and limitations of present works and finally, this article presents the future perspectives of IoT data management on basis of cloud, fog, and mobile edge computing.
BLOFF
Authors: Agbedanu Promise , Jurcut Anca Delia
Published: September 2022

In this era of explosive growth in technology, the internet of things (IoT) has become the game changer when we consider technologies like smart homes and cities, smart energy, security and surveillance, and healthcare. The numerous benefits provided by IoT have become attractive technologies for users and cybercriminals. Cybercriminals of today have the tools and the technology to deploy millions of sophisticated attacks. These attacks need to be investigated; this is where digital forensics comes into play. However, it is not easy to conduct a forensic investigation in IoT systems because of the heterogeneous nature of the IoT environment. Additionally, forensic investigators mostly rely on evidence from service providers, a situation that can lead to evidence contamination. To solve this problem, the authors proposed a blockchain-based IoT forensic model that prevents the admissibility of tampered logs into evidence.
Identification of a Person From Live Video Streaming Using Machine Learning in the Internet of Things (IoT)
Authors: Zeba Sana , Amjad Mohammad
Published: September 2022

In this paper, the authors develop an efficient face recognition algorithm from images or live video streaming for IoT systems based on K-nearest neighbor and support vector machine learning to recognize the person from the local database and extract the features of the face. Because of the complexity of the conditions, there might be some factors of facing errors like the size; the angle; the distance from the ear, nose, and eyes; etc. This sustainable machine learning-based IoT system is designed for sovereign face recognition with features extraction with improved accuracy near about 96%. The experimental study is done to test the performance of the face recognition in the changes of number of persons in video or images. Finally, this manuscript recognized persons from live video or images with accuracy approximately 96% by using the SVM and KNN classifiers and discussed with the block diagram and proposed algorithm.
Cyber Security and Cyber Resilience for the Australian E-Health Records
Authors: Venkatachalam Nagarajan , O'Connor Peadar , Palekar Shailesh
Published: September 2022

Cybersecurity is a critical consideration for all users of electronic health records (EHR), particularly for patients. With the advent of Healthcare 4.0, which is based on the internet of things (IoT) and sensors, cyber resilience has become a key requirement in ensuring the protection of patient data across devices. Blockchain offers crypto-enforced security, data immutability, and smart contracts-based business logic features to all the users in the network. This study explores how blockchain can be a single digital option that can address both the cybersecurity and cyber resilience needs of EHR. The effective use lens is adopted to analyze how blockchain can be leveraged to meet cybersecurity needs while the novel use lens is adopted to analyze how blockchain can be leveraged to address cyber resilience needs originating from IoT. Based on the analysis, this study proposes two Hyperledger-based security models that contribute to individual privacy and information security needs.
Conceptual Insights in Blockchain Technology
Authors: Gaurav Anup Bihari , Kumar Pushpendra , Kumar Vinod , Thakur Ramjeevan Singh
Published: September 2022

The global popularity of digital cryptocurrencies and research in a decentralized system have led to the foundation of blockchain, which is fundamentally a public digital ledger to share information in a trustworthy and secure way. The concept and applications of blockchain have now spread from cryptocurrencies to various other domains, including business process management, smart contracts, IoT, and so on. Cryptocurrency is a mechanism designed to work for the online secure payments system using cryptography. Cryptography maintains confidentiality, integrity, and authentication. Cryptocurrency has come as a novel way of making payments that keep all the transactions secure and safe, which avoids any type of intermediaries such as a bank. This chapter will shed light on the concept of blockchain technology, security, and its applications in various domains.
Securing IoT Applications Using Blockchain
Authors: K. Sreelakshmi K. , Bhatia Ashutosh , Agrawal Ankit
Published: September 2022

The internet of things (IoT) has become a guiding technology behind automation and smart computing. One of the major concerns with the IoT systems is the lack of privacy and security preserving schemes for controlling access and ensuring the security of the data. A majority of security issues arise because of the centralized architecture of IoT systems. Another concern is the lack of proper authentication and access control schemes to moderate access to information generated by the IoT devices. So the question that arises is how to ensure the identity of the equipment or the communicating node. The answer to secure operations in a trustless environment brings us to the decentralized solution of Blockchain. A lot of research has been going on in the area of convergence of IoT and Blockchain, and it has resulted in some remarkable progress in addressing some of the significant issues in the IoT arena. This work reviews the challenges and threats in the IoT environment and how integration with Blockchain can resolve some of them.
Comprehensive Study on Incorporation of Blockchain Technology With IoT Enterprises
Authors: Yadav Ashok Kumar
Published: September 2022

Unprecedented advancement in wireless technology, storage, and computing power of portable devices with the gigabyte speed of internet connectivity enables the possibility of communication among machine to machine. IoT has a different way to connect many nodes simultaneously to store, access, and share the information to improve the quality of life by the elimination of the involvement of human. Irrespective of unlimited benefit, IoT has so many issues that arise to eclipse IoT in reality because of its centralized model. Scalability, reliability, privacy, and security challenges are rising because of the huge numbers of IoT nodes, centralized architecture, and complex networks. Centralized architecture may lead to problems like a single point of failure, single way traffic, huge infrastructure cost, privacy, security, and single source of trust. Therefore, to overcome the issues of the centralized infrastructure of the IoT, the authors diverted to decentralized infrastructure. It may be the best decision in terms of performance, reliability, security, privacy, and trust. Blockchain is an influential latest decentralization technology to decentralize computation, process management, and trust. A combination of blockchain with IoT may have the potential to solve scalability, reliability, privacy, and security issues of IoT. This chapter has an overview of some important consensus algorithms, IoT challenges, integration of the blockchain with IoT, its challenges, and future research issues of a combination of blockchain and IoT are also discussed.
Optimization of Consensus Mechanism for IoT Blockchain
Authors: Khapre Shailesh Pancham , Satpathy Shraddha P. , D. Chandramohan
Published: September 2022

The essence of blockchain is a decentralized distributed ledger system; the IoT is formed by accessing and interconnecting a large number of heterogeneous terminals and has a natural distributed feature. Therefore, the combination of the two IoT blockchains is widely optimistic. At the same time, due to the heterogeneity of IoT sensing terminals, limited computing storage, and data transmission capabilities, the IoT blockchain is facing greater challenges, among which cryptographic consensus technology has become a key issue. In this chapter, based on the summary of the current blockchain consensus algorithm, applicability to the IoT-blockchain has been analyzed, the application status of several major IoT-blockchain platforms and consensus mechanisms have been introduced, and also the IoT-blockchain research progress on optimization of consensus mechanism has been expounded. Looking forward to the optimization techniques of the IoT blockchain, potential research directions have been summarized.
Blockchain-Based Industrial Internet of Things for the Integration of Industrial Process Automation Systems
Authors: Garrocho Charles Tim Batista , Ferreira Célio Márcio Soares , Cavalcanti Carlos Frederico Marcelo da Cunha , Oliveira Ricardo Augusto Rabelo
Published: September 2022

The industrial internet of things is expected to attract significant investment to the industry. In this new environment, blockchain presents immediate potential in industrial IoT applications, offering several benefits to industrial cyber-physical systems. However, works in the blockchain literature target environments that do not meet the reality of the factory and do not assess the impact of the blockchain on industrial process requirements. Thus, this chapter presents an investigation of the evolution of industrial process automation systems and blockchain-based applications in the horizontal and vertical integration of the various systems in a supply chain and factories. In addition, through an investigation of experimental work, this work presents issues and challenges to be faced for the application of blockchain in industrial processes. Evaluations and discussions are mainly focused on aspects of real-time systems in machine-to-machine communication of industrial processes.
Role and Impact of Blockchain in Cybersecurity
Authors: Abbas Syed
Published: September 2022

Blockchain is a staggering innovation with possibilities to change business, particularly in developing business sector global partnerships. Blockchain innovation is a circulated and decentralized record framework that can record exchanges between various PCs. The innovation is viewed as a solid online protection convention because of its abilities of showing any injustice and giving sureness in the trustworthiness of exchanges. The blockchain is another creative innovation that is in the period of being taken on by associations for overseeing records.
Blockchain and the Research Libraries
Authors: Paganelli Anthony L. , Paganelli Andrea L.
Published: September 2022

This chapter will examine the theoretical uses of blockchain technologies in research libraries. Technology has enhanced the services and operations of research libraries since the early implementation of computerized cataloging systems. Blockchain technology provides research libraries with the opportunity to decentralize services, while also maintaining and strengthening digital rights management. Research libraries will be able locate services that can be decentralized to provide patrons with a more effective and efficient service. The blockchain technology has the potential to expand library collections through distributed verifiable sovereign identity, which would allow patrons to securely access information from multiple libraries while maintaining their privacy. Libraries will be able to evaluate services and programs to determine best uses for blockchain technology.
Applying Blockchain Security for Agricultural Supply Chain Management
Authors: Vidhate Amarsinh V. , Saraf Chitra Ramesh , Wani Mrunal Anil , Waghmare Sweta Siddarth , Edgar Teresa
Published: September 2022

Blockchain technology permits a highly secured record keeping and digital transaction. Blockchain technology is changing the digital world and industry by bringing a new view to security, transparency, and efficiency of systems. It provides a safe way for the exchange of products, services, or transaction. Blockchain will enable more agile value chains, faster product innovations, closer customer relationship sector. This paper provides an overview of blockchain technology and its potential in developing a secure and reliable agriculture supply chain management. Agriculture supply chain management systems are vital for getting food products delivered from farmers to the consumers. Blockchain technology can also be used to achieve better prices and payment options, land title registration and for transparent disbursement of subsidies to farmers.
Security Issues of Blockchain-Based Information System to Manage Supply Chain in a Global Crisis
Authors: Pal Kamalendu
Published: September 2022

Global supply chain crisis management has become increasingly crucial for tackling unusual incidents (e.g., natural disaster, terrorism, pandemic). While crisis management has focused on a few organizations involved in supply chain operations (manufacturers, governments, carriers, and the consuming public), it has primarily received a functional focus. Due to their decentralized network structure, supply chains are prone to suffer from disruptive events solved by supply chain crisis management. This chapter presents the blockchain technologies' possibilities and limits used in an integrated IoT-based information system architecture. The chapter describes how the scalability limits of blockchain technology affect the proposed architecture performance that uses it. Also, the chapter presents a review of the academic literature, pointing out how some solutions use a centralization process to improve response time and security of the blockchain-based architecture. Finally, the chapter provides security threat models, which consider by blockchain protocols in IoT networks.
The Efforts of Deep Learning Approaches for Breast Cancer Detection Based on X-Ray Images
Authors: Ismael Aras Masood , Gomes Juliana Carneiro
Published: September 2022

In this chapter, deep learning-based approaches, namely deep feature extraction, fine-tuning of pre-trained convolutional neural networks (CNN), and end-to-end training of a developed CNN model, are used to classify the malignant and normal breast X-ray images. For deep feature extraction, pre-trained deep CNN models such as ResNet18, ResNet50, ResNet101, VGG16, and VGG19 are used. For classification of the deep features, the support vector machines (SVM) classifier is used with various kernel functions namely linear, quadratic, cubic, and Gaussian, respectively. The aforementioned pre-trained deep CNN models are also used in fine-tuning procedure. A new CNN model is also proposed in end-to-end training fashion. The classification accuracy is used as performance measurements. The experimental works show that the deep learning has potential in detection of the breast cancer from the X-ray images. The deep features that are extracted from the ResNet50 model and SVM classifier with linear kernel function produced 94.7% accuracy score which the highest among all obtained.
Computer Techniques for Detection of Breast Cancer and Follow Up Neoadjuvant Treatment
Authors: Araujo Adriel dos Santos , Resmini Roger , Moran Maira Beatriz Hernandez , Issa Milena Henriques de Sousa , Conci Aura
Published: September 2022

This chapter explores several steps of the thermal breast exams analysis process in detecting breast abnormality and evaluating the response of pre-surgical treatment. Topics concerning the process of acquiring, storing, and preprocessing these exams, including a novel segmentation proposal that uses collective intelligence techniques, will be discussed. In addition, various approaches to calculating statistical and geometric descriptors from thermal breast examinations are also considered of this chapter. These descriptors can be used at different stages of the analysis process of these exams. In this sense, two experiments will be presented. The first one explores the use of genetic algorithms in the feature selection process. The second conducts a preliminary study that intends to analyze some descriptors, already used in other works, in the process of evaluating preoperative treatment response. This evaluation is of fundamental importance since the response is directly associated with the prognosis of the disease.
Entropy-Based Breast Cancer Detection in Digital Mammograms Using World Cup Optimization Algorithm
Authors: Razmjooy Navid , Estrela Vania V. , Loschi Hermes Jose
Published: September 2022

Breast cancer is one of the deadliest cancers for women. Early detection of skin cancer gives a high chance for the women to escape from the malady and obtain a cure at the initial stages. In other words, early detection of breast cancer has a direct relation by the women's quality of life. In this case, mammography images are important. Indeed, the main test used for screening and early diagnosis of breast cancer is mammography. In recent years, computer-aided cancer detection has been turned into an active field of research and showed a promising future. In this study, a new optimization algorithm based on thresholding is introduced. A WCO algorithm is employed as the optimization algorithm. WCO is a new meta-heuristic approach which is inspired by the FIFA world cup challenge. The presented method utilizes random samples as candidate solutions from the search space inside the image histogram with considering to the objective function that is utilized by the Kapur's method.
An Intelligent-Based Wavelet Classifier for Accurate Prediction of Breast Cancer
Authors: Haldorai Anandakumar , Ramu Arulmurugan
Published: September 2022

The detection of cancer in the breast is done using mammograms (x-ray images). The authors propose a CAD framework for distinguishing little changes in mammogram which may demonstrate malignancies which are too little to be felt either by the lady herself or by a radiologist. In this chapter, they build up a framework for analysis, visualization, and prediction of cancer in breast tissue by utilizing Intelligent based wavelet classifier. Intelligent-based wavelet classifier is a new approach constructed using texture value and wavelet neural network. The proposed framework is applied to the genuine clinical database of 160 mammograms gathered from mammogram screening focuses. The execution of the CAD framework is examined utilizing ROC curve. This will help the specialists in determination of the breast tissues either cancerous or noncancerous in an accurate way.
Using Machine Learning Algorithms for Breast Cancer Diagnosis
Authors: El-Lamey Mazen Mobtasem , Eid Mohab Mohammed , Gamal Muhammad , Bishady Nour-Elhoda Mohamed , Mohamed Ali Wagdy
Published: September 2022

There are many cancer patients, especially breast cancer patients as it is the most common type of cancer. Due to the huge number of breast cancer patients, many breast cancer-focused hospitals aren't able to process the huge number of patients and might expose some women to late stages of cancer. Thus, the automation of the process can help these hospitals in speeding up the process of cancer detection. In this paper, the authors test several machine learning models such as k-nearest neighbours (KNN), support vector machine (SVM), and artificial neural network (ANN). They then compare their accuracies and losses with themselves and other models that have been developed by other researchers to see whether their approach is efficient or not and to decide what machine learning algorithm is best to use.
The Dynamics of Demographic and Macroeconomic Variables in India
Authors: Mukherjee Sovik
Published: September 2022

The theory of economic growth is one of the principal branches of macroeconomics that tries to highlight the factors that have influenced the long-run trend of the growth of an economy. One of the leading issues in the literature on India's economic growth has been the manifold effects of inflation and employment among many others. The present paper aims to examine the relationship between economic growth rates, inflation, employment, and population growth in a Simultaneous Equations System (SES) framework, with an exclusive focus on the experience since economic liberalization in 1991. The literature on this subject has up till now analyzed the determinants of these endogenous variables disconnectedly. Not only does this paper endeavour to ascertain the existence of endogeneity among these variables but also highlight a multitude of factors that are connected in this regard. This paper comes to a close by discussing the possibilities for developing strategies that are overtly concerned with productive employment generation.
Macroeconomic Sensitivity, Risk-Return Trade-Off and Volatility Dynamics Evidence From Developed and Developing Markets
Authors: Khan Faisal , Khan Hashim , Khan Saif Ur-Rehman , Jumaa Muhammad , Jan Sharif Ullah
Published: September 2022

This study aims to examine the impact of macroeconomic factors on the stock return volatility along with the pricing of risk, and asymmetry and leverage effect on a comparative basis for the USA and UAE markets. Further, these three dimensions are also investigated with regard to various firm's features (such as firm's size and age). The daily data for the period 4th January 2010 to 29th December 2017 of firm stock returns from the New York Stock Exchange (NYSE), the Abu Dhabi Securities Exchange (ADSE), and the Dubai Financial Market (DFM) is considered and three time-series models were applied. The results from GARCH (1. 1) indicated that all the economic factors have significant impact on the stock return volatility in both the markets. Similarly, the study also found evidence of asymmetry & leverage effect using EGARCH in the NYSE (for all firms) and the UAE (partially). Finally, for a majority of the firms, a positive risk-return relationship is found in the UAE and a negative risk-return relationship is found in the NYSE using GARCH-in the mean. Interestingly, these results in context of both markets were different with respect to various firm features such as firm size and age. In light of these results, it is concluded that both the markets have different dynamics with regard to all three dimensions. Hence, the investors have a clear opportunity to diversify their risk and investments across developed and emerging markets.
Artificial Intelligence as an Emerging Technology in Global Trade
Authors: Garg Seema , Mahajan Navita , Ghosh Jayanta
Published: September 2022

With Industry 4.0 and now 5.0 technologies, the entire globe is embracing these changes. Artificial intelligence-powered systems have immense potential to eliminate international geographical barriers and prove to influence global trade worldwide. The present study highlights how AI increases productivity, economic development, and provides international trade with new horizons. The global value chains, prediction of future trends like changes in consumer demand, risk management, supply chain links are some of the key applications of AI in the sector. AI empowers international trade negotiations to analyze economic trajectories of negotiating partners, adjustments of trade barriers at different rates and scenarios. The chapter will cover the support of AI to access global trade data, its response to diverse challenges, international expansions through digital platforms, support in translations, mechanism of demand prediction, automation of administration with increased efficiency and utility, smart manufacturing, barriers, and influences.
The Politics of Public Debt Management Among Rising Hegemonies and the Role of ICT
Authors: Amu Christian Ugwueze , Nwezeaku Nathaniel Chinedum , Akujuobi Linus Ezewunwa , Ozurunba Benedict Anayo , Njie Sharon Nanyongo , Wogu Ikedinachi Ayodele Power , Misra Sanjay
Published: September 2022

While scholars like Wogu and Misra unanimously affirmed the beneficial roles of adopting AI powered ICT systems in various sectors of government and endeavours, most countries in OECD and the Commonwealth - for reasons described as ‘a political reckless attitude' - have shied away from fully adopting and implementing intelligent debt management systems for their country's financial sectors, hence, the looming debt crisis hanging over them. Premised on the Public Choice theory, the study adopts Marilyn's Ex-post facto research design and Creswell's mix-method research approaches to interrogate the arguments proffered for and against the public debt management and the benefits of ICT, with a view to identifying the nexus that exists between the politics of debt management crisis and the role of ICT for 21st-century polities. The article identified a high degree of political rascality amongst political elites and a lackadaisical will towards the full implementation of intelligent debt management systems in the countries with looming debt crisis. Viable recommendations were proffered.
Analysis of the Monetary Policy Dynamics in Romania Using a Structural Vector Autoregressive Model
Authors: Spulbar Cristi , Birau Ramona
Published: September 2022

This chapter aims to provide an elaborate empirical analysis of the monetary policy dynamics in Romania using a structural vector autoregressive model. This chapter contributes to literature based on an empirical framework regarding the implications of exchange rate channel within the monetary policy, and the impact of the monetary aggregates channels in order to explain the evolution of the prices level in Romania.
Investigation of Robin Hood Tax in Financial Crisis Periods and Analysis of Social State Policy in Taxation
Authors: Bozdoğan Doğan
Published: September 2022

Taxes cannot be denied in order to prevent financial crises and economic crises. In times of crisis, it is sometimes possible to intervene in these periods by decreasing the existing tax rates and sometimes by applying new taxes. The Robin Hood tax is based on the idea of giving it to the poor. According to this idea, the financial sector will be taxed in times of crisis and the tax burden that countries have to bear will be reduced. Moreover, the important point here is related to the usage area of the income derived from taxation of the financial sector. These taxes will be transferred directly to the public (i.e., to the people who suffer from the crisis). Thus, the idea of transferring from the rich to the poor will take place. In this chapter, the applicability of Robin Hood tax will be determined by considering the main features of the tax, and the tax will be examined before the social state principle. In this direction, the superior aspects of the said tax will be determined, and some suggestions will be made.
Economic Growth and Changes in Public Expenditures of the States in the Time of the COVID-19 Pandemic
Authors: Yusufi Ferimah
Published: September 2022

Fiscal policies are changing due to the conditions required by the COVID-19 pandemic towards the new world order. Under these circumstances, developed countries use their resources for their citizens, and international financial institutions step in for underdeveloped and developing countries with insufficient public resources of their own or are in debt and offer new credit opportunities to these countries. This study aims to analyze how public expenditures, one of the important policies in economic growth and development, will change during and after the COVID-19 pandemic. In light of the findings obtained from the literature review, the economic effects of the pandemic are explained by making a descriptive analysis of secondary data at the levels of country groups classified according to development and income level. Secondly, factors affecting the changes in the public expenditure of countries due to the pandemic were examined, and evaluations are made on the public expenditures in fiscal policies that will ensure the economic recovery and growth of countries after the pandemic.
Do Family Control and Macroeconomic Fluctuations Impact Firm Performance?
Authors: Lisboa Ines , Teixeira Nuno , Costa Teresa
Published: September 2022

This chapter aims to analyze performance differences between family and non-family firms. Additionally, it aims to see if economic downturns and upturns cause impact in this relation. For it, a panel data of Portuguese non-financial-listed firms in Euronext Lisbon during the period from 2010 till 2019 is analyzed. Performance is studied in accounting-based and market-based views. Three types of variables are considered: corporate governance characteristics, macroeconomic factors, and firm's characteristics. Results depend on the performance proxy used. While to ROA no difference is found, Tobins' Q family firms outperform non-family ones, but results are the inverse using ROE, MTBV, and MVA. Moreover, macroeconomic fluctuations are relevant to explain firms' performance, specially to family firms. Therefore, firms must analyze specific characteristics to avoid losing value, especially in crisis periods.
Innovation, Macroeconomic Effects, and Environmental Degradation
Authors: Gedikli Ayfer , Derindağ Mehmet Rıza
Published: September 2022

All over the world, rising population, diminishing natural resources, and the necessity of sustainable growth pointed out the importance of innovation. In the growth strategies, the ability to innovate, as knowledge capital, is one of the most important determinants of sustainable development for all developing countries as their aim is to generate added value, higher development, and a sustainable environment. The aim of this study is to present the importance of innovation for sustainable growth performance in the 13 Mediterranean countries. In the chapter, the role of innovation in macroeconomic performance and sustainable environment in the aforementioned countries will be analyzed. This chapter not only provides an analysis of the relationship between the innovation, macroeconomic factors, and environmental degradation but also policy suggestions to put forth to have more innovative technologies, sustainable growth performance, and environment conservation.
An Analysis of Risk Transfer and Trust Nexus in International Trade With Reference to Turkish Data
Authors: Taşbaşı Aslı , Sarıca Pınar Yeşim , Yüksel Ahmet Hakan
Published: September 2022

International trade introduces a range of risks, which causes uncertainty over the timing of delivery and payment between exporters and importers. This chapter is a first attempt in dissecting Turkey's trade data in terms of risk allocation and trust between the parties involved. Breaking down Turkish export and import data for the years 2000 to 2018 according to methods of payment and use of currencies, the chapter first finds the risk is distributed unevenly between the exporter and the importer. Then findings are evaluated to open a new avenue of future research, constructed on the inquiry whether emerging economies like Turkey can establish trust in their trade with developed economies by using blockchain technology.
Leverage Structure Dynamics and Firm Value
Authors: Uddin Mohammad Nazim , Khan Mohammed Shamim Uddin , Hosen Mosharrof , Chowdhury Md. Shahnur Azad
Published: September 2022

The paper aims to examine the impact of leverage structure dynamics on firm value in Bangladesh. To this end, the panel techniques (GMM and PCSE) were used to control for serial correlation, heteroskedasticity, and cross-sectional difficulties in the panel data set. The paper found that leverage structure influences firm value. The result also supports the trade-off theory, which asserts that tax savings on interest expenses result in a lower total cost of capital and ultimately upturn firm value. Lastly, the paper highlights the significance of endogenous variables such as liquidity, profitability, tangibility, and tax rate on firm value in Bangladesh.
A Pediatric Intensive Care Checklist for Interprofessional Rounds: The R-PICniC Study
Authors: dos Santos Alves Daniela Fernanda , Moraes Érika Sana , Conti Patrícia Blau Margosian , Bueno Giselli Cristina Villela , de Souza Tiago Henrique , Pereira Elisandra Oliveira Parada , Brandão Marcelo Barciela , Peterlini Maria Angélica Sorgini , Pedreira Mavilde Luz Gonçalves
Published: September 2022

Background

The use of checklists in the pediatric intensive care unit can help improve the quality of care and patient safety.

Objectives

To build and validate a checklist for use in interprofessional rounds in a pediatric intensive care unit.

Methods

This methodological study was conducted in a 20-bed pediatric intensive care unit serving children up to 14 years old. A checklist prototype was constructed through review of the literature and achievement of consensus among the professionals providing care in the unit. Content validation was performed using a modified Delphi technique involving specialists with more than 5 years of experience in pediatric intensive care, methodological studies, and patient safety. Content validity ratios were calculated for the elements of the checklist, which were considered valid when they reached values greater than 0.78. The checklist was tested for usability, application time, and effects on patient care, and feedback was obtained from potential users.

Results

Before content validation, the checklist contained 11 domains, 32 items, and 6 daily goals. The invitation to validate content was sent to 86 specialists, and content validity was achieved after 2 rounds of evaluation, with the checklist elements having content validity ratios ranging from 0.94 to 0.97. The mean application time of the checklist was 5 minutes. The final version consisted of 11 domains, 33 items, and 8 daily goals.

Conclusions

This study resulted in a useful and valid instrument for application in interprofessional rounds that was tailored to the needs of local health care professionals.
Biosensors
Authors: Karami Elmira , Kazemi-Lomedasht Fatemeh
Published: September 2022

Fast and precise diagnostic techniques are required for the treatment of many disorders. Biosensors are one of the diagnostic devices that are applicable in biological and medical sciences. Biosensors could be utilized to recognize biological molecules with high sensitivity. Biosensors are consisted of different components and have different types. Each type of biosensor is used in a particular field according to its specific features. Nanobodies are a novel class of antibodies with small size, high affinity, and specificity to their target. The unique properties of nanobodies make them appropriate tools for diagnostic applications. In this paper, we review biosensors, and their features and roles in medicine. Antibody/nanobody-based biosensors are also specifically discussed.