bluuebunny/crossref_metadata_2025 huggingface dataset:
Results and Lessons of GULAG System Implementation in Historical Perspective
Authors: Drobyshevskaya T. A.
Published: December 2023

oday, in conditions of limited supply in the labor market both at the regional level and from the rostrum of the State Duma proposals are being made on the use of forced labor in the national economy. In this regard, it is important to return to the study of the historical experience of our country. The proposed work provides a comprehensive review of the results of studying the consequences of the use of forced labor within the framework of the economic system of the Gulag in modern scientific literature. The author argues that short-term results achieved through the use of forced labor are fraught with protracted negative consequences for generations, difficult to overcome and hindering further sustainable development.
INTERNALIZING DISCIPLINE CHARACTER TO SENIOR HIGH SCHOOLS’ STUDENTS
Authors: Hasan Nurangsih S , Suabuana Cik , Warlim Warlim
Published: December 2023

The internalization of discipline is a necessary character value to follow the many regulations of a school. Students at SMA Negeri 1 Halmahera and SMA Negeri 7 in the South Halmahera Regency were surveyed for this study with the hope of encouraging them to adopt a more disciplined mindset. Qualitative research techniques were used for this analysis. Using an approach based on habituation of disciplinary values, experience, and exercises to strengthen discipline values, and exemplary application by exemplary teachers and students as role models. The results showed that SMA Negeri 1 and SMA Negeri 7 in South Halmahera Regency, North Maluku Province successfully internalized disciplinary values. Students who 1) arrive at school promptly at 7.00 WIT; 2) read a short letter for 15 minutes before beginning the lesson; and 3) stay for 5 minutes after the end of class to sing the national anthem are more likely to internalize the discipline. These three activities are performed daily. The cultivation of discipline in students, particularly through adherence to established norms and programs, enables them to effectively incorporate these principles into their daily lives. Keywords: values internalization; character; students’ discipline; senior high school
Analysis of Rainfall Trends in India, Incorporating Non-Parametric Tests and Wavelet Synopsis over the Last 117 Years
Authors:   Civil Engineering Department, National Institute of Technology Raipur, Raipur, Chhattisgarh, 492010 India, Kumar K. , Verma S. , Sahu R. , Verma M. K.
Published: December 2023

Rainfall trend analysis is very important in the economic and sociocultural context of the country, like the development of irrigation and water resource management practices. In this paper, Mann-Kendall (M-K), Sen’s slope estimator, and wavelet analysis were used to analyze long-term (1901 ~ 2017) annual and seasonal rainfall trends in India. The sequential Mann-Kendall (SQMK) test is used to estimate the temporal variation of rainfall. The analysis shows monsoon precipitation in “Jammu and Kashmir, Himachal Pradesh, Uttarakhand, Uttar Pradesh, Chhattisgarh, Sikkim, Arunachal Pradesh, Mizoram, Assam, Karnataka, Nagaland, Kerala, Meghalaya, and Goa” have significant trends. The above-mentioned states were subjected to a discrete wavelet transform (DWT) analysis using Daubechies (db5-db10) and Symlet (sym5-sym10) mother wavelet families. The analysis revealed that the trends of subdivisions had a short-term periodicity of less than a decade. Therefore, the present study indicates significant changes over time. By utilizing wavelet techniques, it is possible to gain insight into both short- and long-term tendencies, making it simpler to spot patterns and sudden changes. Therefore, the present study by combining non-parametric tests with wavelet synopsis, offers a thorough comprehension of rainfall trends in India. The collaborative use of these techniques improves the precision of trend identification, offering valuable insights to make well-informed decisions for water resource management and climate adaptation strategies.
Biodiversity Conservation and Sustainable Livelihoods Diversification: Insights and Policy Implications for Rural Communities in South Africa
Authors: MNISI Pearl Thobeka
Published: December 2023

This paper aims to analyze the effects of biodiversity conservation on sustainable livelihood diversification of rural communities in South Africa. Global evidence demonstrated a nuanced connection between biodiversity conservation and sustainable livelihood diversification. Biodiversity conservation is flourishing, and its industry has grown to a point where it accounts for a big part of South Africa's Gross Domestic Product. However, it remains a concern that the poverty levels in rural communities continue to rise, and there is no improvement brought by biodiversity conservation towards sustainable livelihood diversification. This is a theoretical paper that adopted the qualitative research method. The data for the paper was compiled through a desktop study wherein newspapers, scholarly journal articles, and government documents related to the effects of biodiversity conservation on sustainable livelihood diversification of rural communities in South Africa. Therefore, Document analysis was appropriate and selected to analyze the data. The paper found that balancing biodiversity conservation and sustainable livelihood diversification remains challenging in South Africa. This makes it difficult for rural communities to have sustainable livelihood diversification. This paper concludes that biodiversity conservation needs to do more justice to ensuring sustainable livelihood diversification for rural communities in the country. Therefore, it recommends the government delegate candidates or departments to continuously monitor and ensure that nature reserves practicing biodiversity conservation give back to nearby rural communities. Biodiversity conservation policies and legislations in line with the development of rural communities should be reviewed, adjusted, and ensured that they have operated accordingly.
The Effects of Public Participation on Local Economic Development in South African Municipalities
Authors: KGOBE France Khutso Lavhelani , MABEBA Selaelo John , MAMOKHERE John
Published: December 2023

In recent years, the concept of Local Economic Development (LED) has gained prominence to enhance the economic well-being of communities at the grassroots level. In South Africa, a country marked by a history of inequality and spatial disparities, fostering LED has become crucial. Public participation is crucial in shaping the LED trajectory in South African municipalities. By analyzing existing literature, this article underscores the importance of inclusive and meaningful engagement of citizens in the process of LED, highlighting its benefits and challenges. In other words, this article explores the effects of public participation on LED in South African municipalities. This study adopted a qualitative research methodology. The study specifically reviewed secondary data to understand the effects of public participation on local economic development in South African municipalities. In conclusion, to address public participation challenges in LED, local government should design participation processes that actively involve all segments of the population, especially marginalized and historically disadvantaged groups.
The Importance of Persuasion Strategies in Doctors’ Social Media Messages
Authors: ASSEGAFF Syafiq B. , LILIWERI Alo , SERAN Alexander
Published: December 2023

This study investigates how doctors employ persuasion strategies (Ethos, logos, and pathos) on Instagram to influence the health behaviors of their followers during the COVID-19 pandemic. Analyzing three influential doctors on social media (DSMIs), the research applies Aristotle's persuasive strategies to understand how these doctors craft messages that drive behavior change and enhance COVID-19 awareness among their 581 followers. Employing a mixed methods approach within the pragmatism paradigm, the study utilizes interviews, literature reviews, content analysis, and surveys for comprehensive data collection. The study reveals that approximately 41% of followers demonstrated a firm intention, with an additional 43% showing a solid intention to change their attitudes and behaviors. About 84% expressed a strong commitment to adopting a healthier lifestyle. The research also identified followers who initially had doubts or confusion about COVID-19 due to misinformation. However, it became convinced of its existence after following the DSMIs' posts, mainly through engaging video content. Engagement is more significant for video content than photos, with pathos, Ethos, and logos effectively fostering engagement. Around 52,438 (314,000) DSMI followers shifted from initial skepticism to meaningful positive attitude transformations, driven by successful engagement through pathos, Ethos, and logos. The study underscores the significance of delivering persuasive and appealing messages to influence behaviors positively. It suggests active social media participation can extend beyond the pandemic, fostering ongoing health awareness.
Macro-economic Variables and Bank Performance in Nigeria: Fourth Republic Perspective
Authors: OGUNLOKUN Ayodele , ADEBISI Adebola Olubunmi
Published: December 2023

Purpose: The vagaries of the macroeconomic variables make the business environment unpredictable, and this often portends mammoth implications for various businesses, primarily critical businesses such as banking, which the successive governments within the Fourth Republic have strived to protect jealously. Therefore, this study assessed the impact of macroeconomic factors on the performance of Nigerian banks from 1999 to 2021.Methodology:Data for the study period came from the World Bank reports and the CBN and SEC Statistical Bulletins. An ARDL (Autoregressive Distributed Lag) model was employed to evaluate the data.Findings: Lending interest rates had a negative and statistically insignificant impact on the performance of Nigerian banks with a coefficient of -0.0422 (p-value = 0.3860 & gt; 0.05), in contrast to the unemployment rate, which had a negative but statistically significant impact with a coefficient of -0.0534 (p-value = 0.0012 & gt; 0.05).Implication:Lending interest rate and unemployment rate impeded banks' performance, gross domestic savings, GDP per capita income, and exchange rate facilitated banks' performance in Nigeria.
The Influence of Product Quality, Prices and Promotions on Customer Loyalty UD. Setya Abadi D.M
Authors: ANIKAWATI Vika , HARIYANA Nanik
Published: December 2023

Purpose: In today's competitive business era, maintaining customer loyalty is one of the critical factors for the long-term success of a company. This research aims to determine the impact of product quality, Price, and promotion on customer loyalty. This research was conducted at UD. Setya Abadi D.M in October 2023.Methodology:The method used is a quantitative study using primary data. Primary data was obtained from research participants through online Google forms and questionnaires. The population in this study were all buyers of UD. Setya Abadi D.M. This research uses 12 indicators, so the test estimate is 75-150. Based on these considerations, the test size for this research was set at 100 respondents.Findings: Based on the research conducted, the conclusion of this research states that product quality has a significant influence on customer loyalty. It means that the higher the quality of the product, the greater the consumer's loyalty to the product.Implication:Price has an essential impact on customer loyalty. It means that the higher the product price, the higher the consumer's dependence on that product. Promotion has an essential impact on customer loyalty. It means that the better the promotion, the higher the customer loyalty.
Decision Support System in E-Commerce in Purchasing Saw with Method Woven Fabric
Authors: ANUARIDLO Mochamad Aldi Yusuf , FIRLIANA Rina , DANIATI Erna
Published: December 2023

Purpose: Choosing ikat woven fabric has several predetermined criteria. These criteria include price, quality, product type, and color. The decision support system for selecting ikat fabric purchases for buyers in e-commerce using the SAW (simple additive weighting) method is a system that can determine the results of the decision to select one of the ikat fabrics based on predetermined criteria and alternatives.Methodology:The SAW method is one of the decision-making methods often used in DSS. The research method refers to a literature study that aims to find references that suit the problem, then observation by collecting data at the specified research location and interviewing the owner and one of the MSME employees to obtain detailed information.Findings: This research determines the purchase of good woven fabric via e-commerce for ikat woven fabric products in Bandar Kidul village, Mojoroto subdistrict, Kediri city. Calculating the best-woven fabric for ikat products can use the simple additive weight (SAW) method so that one best-selling ikat fabric, namely silk woven fabric, is selected and meets the requirements, with a score of 0.76675.Implication:Based on this research, we can determine which suitable woven fabrics to buy using e-commerce for ikat woven fabric products in Bandar Kidul village, Mojoroto subdistrict, Kediri city. The simple additive weight (SAW) method can calculate the best-woven fabric for ikat products.
Review and Analysis of Applications and Frameworks of Information Systems in Supply Chain Management
Authors: Kumar Manish
Published: December 2023

In this era of information systems, humankind has benefitted enormously. The rapid growth in information system technology has made human life very easy and has significantly increased the efficiency, speed, and reliability of different processes. It is the need of the hour to study the interface between the information system and supply chain management. This chapter specifically tried to study the applications and frameworks of information systems in operation and supply chain management. For the study, the authors reviewed the articles published in top-quality journals. This chapter aimed to identify and discuss how different information systems frameworks solve problems related to operation and supply chain management. This study dealt with seven subsections involving supply chain, logistics, partnership, transparency, and decision-making. The study further identified that the use of information systems also contributes to competitive advantage. Finally, the understanding from the literature review has been concluded, and the existing gap has been highlighted for future research.
Critical Role of HR Professionals in the Adoption and Integration of AI in HRM
Authors: Aftab Atia , Khalid Komal
Published: December 2023

In this chapter, HR professionals are spotlighted as pivotal players in integrating artificial intelligence (AI) into human resource management (HRM). Drawing inspiration from literary figures, they champion a culture of continuous learning and adaptation, ensuring that AI adoption complements rather than replaces human capabilities. Ethical leadership, inclusivity, and collaboration underpin their strategies, while a profound emphasis is placed on preserving the essence of human connection. They navigate the complexities of AI-driven decision-making, emphasizing data-driven insights and agile innovation. By fostering a symbiotic relationship between humans and AI, HR professionals elevate HRM, harmonizing technology with the organization's strategic vision. This chapter underscores HR's transformative role in marrying AI's potential with human-centric values.
A Bibliometric Analysis of Artificial Intelligence and Human Resource Management Studies
Authors: Morshidi Azizan Bin , Satar Nurhizam Safie Mohd , Azizan Azueryn Annatassia Dania Aqeela , Idris Rizal Zamani , Idris Rafiq , Radzi Mohammad Shaukhi Md , Yusoff Sitinurbayu Mohd , Sarjono Fauzie
Published: December 2023

The pervasiveness of artificial intelligence (AI) within contemporary organisations is an undeniable phenomenon. The primary objective of this chapter is to undertake a meticulous bibliometric analysis of the scholarly literature that investigates the interconnected exploration of the utilisation and ramifications of artificial intelligence (AI) within the realm of human resource management (HRM). The researchers consulted the valued scientific database Scopus, which proved to be a fount of knowledge. Ninety-one documents were initially retrieved and meticulously chosen for the analysis. The data underwent processing through the esteemed Bibliometrix software and the sophisticated Biblioshiny application tool. The results evince that the application of artificial intelligence (AI) to human resource management (HRM) constitutes an emerging domain of inquiry, characterised by a continuous and unwavering expansion and a promising trajectory for the future. Finally, the discourse examined the comparative themes that emerged before and after the advent of the COVID-19 pandemic.
AI-Powered Employee Experience
Authors: Dwivedi Dwijendra Nath , Mahanty Ghanashyama
Published: December 2023

AI has become an indispensable tool for businesses seeking to enhance the employee experience. Businesses that implement it can increase employee satisfaction, enhance customer service, and decrease cost per employee served – ultimately adding significant business value. Artificial intelligence instruments can improve employee experiences across several areas: recruitment, onboarding, training, and performance management. Furthermore, this use case will profoundly impact customer experiences overall.
Integrated Model for Asynchronous Learning and Predictive Analytics for Enhanced Learner Experience
Authors: Dhamija Ankit , Dhamija Deepika
Published: December 2023

Organizations of every size and industry are embracing data analytics to extract insightful information from the data with the goal of enhancing decision-making, boosting productivity, streamlining workflows, and reducing costs. The adoption of data, more especially learning analytics, which is the act of obtaining, measuring, and analyzing data on learners in order to better understand their requirements and learning preferences, is an excellent possibility for the education industry. Predictive learner analytics can be used to gain a variety of insights that can help institutions improve learner retention, engagement, and performance measurement, particularly in asynchronous online learning where students feel helpless and distracted. In light of this, the chapter suggests a methodology and model for integrating asynchronous learning and predictive analytics.
Enhancing Self-Regulated Learning With Artificial Intelligence-Powered Learning Analytics
Authors: Yildirim-Erbasli Seyma N. , Gorgun Guher , Bulut Okan
Published: December 2023

This chapter explores the dynamic synergy between artificial intelligence (AI) and learning analytics (LA) as catalysts for self-regulated learning (SRL). By examining the intersection of AI, LA, and SRL, this chapter sheds light on the evolving landscape of education and the opportunities it offers for tailored, data-driven learning experiences. It delves into the transformative potential of AI-powered LA, providing personalized insights, prediction, recommendation, and interactive scaffolding; thus promoting SRL development among learners. It also addresses ethical considerations, challenges, and the need for interdisciplinary collaboration among educators, data scientists, and policymakers. Ultimately, this chapter underscores the importance of responsible implementation and continuous research to harness the full benefits of AI-powered LA in supporting SRL and improving educational outcomes.
Designing Achievement Tests for Language Learners Through Contemporary Technologies
Authors: Kahraman-Ozkurt Sibel
Published: December 2023

The chapter aims at giving insights to English as a foreign language (EFL) teachers on creating and designing achievement tests through digital tools for checking their student' progress and teaching/learning process. As language learners may have concerns and barriers regarding the assessment and testing issues, the administration of digital tools for that purpose is believed to contribute to both students' development by lowering their anxiety levels and accordingly teachers' future practices. Based on the feedback on students' performance gathered through digital tools, teachers and other stakeholders can find the opportunity to re-organize teaching materials, tasks, or the coursebooks. EFL teachers may also be provoked to use some other digital tools not included in that chapter by following the procedures in the activity plans for their future assessment practices.
Integration of Digital Picture Books Into Young Learners' Language Classrooms
Authors: Köroğlu Zeynep Çetin
Published: December 2023

The world we live in now is more technological than in the past and continues to change and develop day by day. Our children, who are accepted as 'digital natives,' start to live a life intertwined with technology from the first years of their lives. To prepare them for the age they are in and the lives that await them in the future, digital picture books should be used effectively, especially in early childhood. This chapter discusses the use and importance of picture books in early childhood foreign language learning, the features and usage areas of digital picture books, the role and importance of digital picture books in vocabulary teaching, examples of well-designed digital picture books, websites and applications that offer these examples, and the effects of digital picture books on young learners' foreign language learning.
Human vs. AI
Authors: Kınık Betul , Çetin Hande
Published: December 2023

The current study seeks to investigate whether ChatGPT 3.5 can be used as an aid to help diminish the teachers' workload in assessing writing. To this aim, a mixed-methods research design was employed for the study. Randomly selected, 20 descriptive essays written by freshman student teachers of English Language Teaching were scored by an experienced human rater and ChatGPT 3.5. An adapted ‘descriptive essay rubric' by the researchers was used to assess the descriptive essays of the student teachers. The quantitative aspect of the study involved frequency and percentage analysis, while the qualitative dimension centered on analyzing the written feedback provided by both ChatGPT and the human rater. The findings showed that there is a disagreement between ChatGPT 3.5 and the human rater. Furthermore, there are some problems with the written feedback it provides. It is clear that it is rapid in terms of providing feedback. Thus, it is recommended that ChatGPT 3.5 can be employed as a tool under the supervision of teachers.
Natural Language Processing Applications in Language Assessment
Authors: Toprak-Yıldız Tuğba Elif
Published: December 2023

Natural language processing is a subfield of artificial intelligence investigating how computers can be utilised to understand and process natural language text or speech to accomplish useful things in various areas, and it draws on various disciplines, such as computer science, linguistics, and robotics. Natural language processing applications, including automated speech recognition and scoring, have several exciting prospects for language testing and assessment practices. These prospects include addressing practical constraints associated with test administration and scoring, securing standardisation in test delivery, ensuring objectiveness and reliability in scoring procedures, and providing personalised feedback for learning. This chapter focuses on automated speech scoring and its applications in language testing and assessment and discusses how these systems can be employed in assessment contexts. The chapter also discusses the potential benefits and drawbacks of automated speech scoring while focusing on construct-related and practical challenges surrounding such systems.
Energy Transition Toward a Low-Carbon Economy in Malaysia
Authors: Ghazali Farahdilah , Shukor Siti Fazilah Abdul , Ismon Nur Yuhanis
Published: December 2023

Some studies have found that liberalized electricity market led to acceleration of the development of renewable energy sector, particularly with community-based financing for local renewable projects in place. The idea of liberalization of electricity market focuses on the fair competition especially among the key players which subsequently entice more investment on infrastructures and reduce electricity tariff. Energy liberalization has dramatically enhanced monopoly utility governance, competition, innovation prospects, and the policy for environmental emissions management by creating trading mechanisms. This chapter discusses the practices of power liberalization, especially in Europe, regarding the benefits and challenges. Moreover, the chapter examines Malaysian practices in pursuing renewable energy programs to attain sustainability and energy security goals, which is also vital to support a more competitive energy sector.
Exploring Ethical Considerations in Utilizing Generative AI for Global Knowledge Sharing in Higher Education
Authors: Yu Poshan , Lu Shengyuan , Long Zixian , Chen Yijun , Qian Jianguo , Shah Zain Ali
Published: December 2023

This chapter delves into the ethical considerations surrounding the utilization of generative artificial intelligence (AI) for global knowledge sharing in higher education. As AI technologies continue to advance, their potential for transforming the educational landscape is becoming increasingly evident. However, the ethical implications of employing generative AI in this context warrant careful examination. The study explores the ethical dimensions related to the use of generative AI in higher education, focusing on issues such as data privacy, algorithmic bias, intellectual property rights, and the impact on human creativity and critical thinking. The findings of this study contribute to the ongoing discourse on the ethical implications of utilizing generative AI in higher education. By addressing these considerations, educators and policymakers can make informed decisions regarding the implementation of generative AI technologies, fostering a responsible and inclusive approach to global knowledge sharing in the higher education sector.
Exploring the Role of AI-Driven Tools in Evaluating Pedagogical Competencies
Authors: Das Rajashree , Samanta Durga Prasad Singh , Nanda Gouranga , Mohanty Minakshi Rani
Published: December 2023

This chapter aims to evaluate the pre-service teacher education curriculum at the secondary level with the integration of technology. The study uses a mixed-methods approach, including surveys, interviews, and document analysis, to gather data from pre-service teachers, teacher educators, and educational experts. The study evaluates the effectiveness of the current curriculum in preparing pre-service teachers for the demands of teaching in a digital age, and explores the potential benefits and challenges of integrating technology in teacher education. The study also assesses the attitudes, beliefs, and perceptions of pre-service teachers towards technology and their level of technology integration in their teaching practice. The findings of the study provide insights into the strengths and weaknesses of the current pre-service teacher education curriculum at the secondary level and the potential benefits and challenges of integrating technology in teacher education.
Innovative Teaching Methodology in Higher Education With Generative AI- Engineering Education in Developing Countries
Authors: Umme Laila , Shah Zain Ali , Yu Poshan , Mulli James , Khurram Muhammad , Ahmed Muzammil
Published: December 2023

The rapidly evolving landscape of higher education is causing significant changes in the educational system. The needs of the digital world cannot be satisfied by conventional teaching and learning approaches. To improve educational quality, fostering global collaboration and knowledge sharing has become imperative for preparing students for a connected world. Therefore, technological integration in the classroom has become essential. Generative artificial intelligence (AI) has emerged as a powerful tool in this endeavour. In addition to examining the possible advantages and difficulties of incorporating technology in higher education, this study also assesses the extent of technology integration in teaching, referred to as innovative teaching methodologies (ITM). This chapter explores how generative AI can be leveraged to enhance teaching methods.
Intelligent Resource Allocation and Optimization for Industrial Robotics Using AI and Blockchain
Authors: Vashishth Tarun Kumar , Sharma Vikas , Sharma Kewal Krishan , Kumar Bhupendra , Chaudhary Sachin , Panwar Rajneesh
Published: December 2023

This chapter focuses on the application of intelligent resource allocation and optimization techniques for industrial robotics systems using the synergistic integration of artificial intelligence (AI) and blockchain technologies. Efficient resource allocation is crucial for maximizing the performance and productivity of industrial robotics, and AI-based approaches offer the ability to dynamically allocate resources based on real-time data and system requirements. Additionally, blockchain technology provides a decentralized and secure platform for recording and verifying resource allocation transactions, ensuring transparency and trust in the allocation process. The chapter explores various AI algorithms and models that can be employed for resource allocation and optimization in industrial robotics, including machine learning, evolutionary algorithms, and reinforcement learning. Furthermore, the chapter investigates how blockchain technology can enhance resource allocation and optimization by providing a distributed ledger for recording and verifying resource transactions.
Multi-Layered Blockchain-Based Security Model for Electronic Health Record Systems
Authors: Hiremath Mrutyunjaya S. , Biradar Rajashekhar C.
Published: December 2023

The multi-layered blockchain-based electronic health records (ML-BbEHR) framework aims to address persistent healthcare issues such as data privacy and access control. Utilizing a multi-layered blockchain architecture, ML-BbEHR segments EHR data into categories like medical histories and clinical datasets, each managed within its distinct blockchain layer. This enhances security and optimizes data management. Unlike single-layer systems, this architecture mitigates latency issues. Additionally, the framework incorporates fingerprint authentication as an alternative to traditional cryptographic keys, bolstering patient identity verification. Smart contracts are also deployed across layers to delineate rules and permissions for healthcare data access, enhancing data integrity and security. This architecture is built on a general, non-specific blockchain platform chosen for its robust security features.
Enhancing Money Laundering Detection Through Machine Learning
Authors: Mishra Soumya Ranjan , Pranati  , Anika  , Mohapatra Hitesh
Published: December 2023

Money laundering is a worldwide issue that jeopardizes the stability and integrity of financial institutions. Many countries have implemented anti-money laundering laws and regulations to combat this. The basics of money laundering and its influence on the financial system, as well as existing strategies for detecting and combating it, are covered in this chapter. K- nearest neighbors, random forest, naive bayes, deep neural networks, and evolution metrics are examples of machine learning techniques and algorithms used to identify suspicious transactions. Financial institutions and regulatory bodies can strengthen their ability to detect and prevent money laundering activities and help to protect the integrity of the financial system by utilizing a variety of measures. In this work, the authors have presented a deep comparative analysis among various machine learning algorithms that are used in money laundering detection.
From 3D to 4D
Authors: Khaira Ashish
Published: December 2023

This chapter traces the evolution of additive manufacturing (AM) from a rapid prototyping technique to a disruptive technology that impacts various industries. It reviews the latest research and expert opinions on the effects of AM on industrial, societal, and environmental aspects. It also explores 4D printing (4DP), a novel branch of AM that creates dynamic and adaptive objects, and discusses its challenges and opportunities. It also considers the conjunction of AM with other emerging technologies such as AI, IoT, and blockchain, and how they shape the future of smart products and services. This chapter offers valuable insights into the development of AM, its transformative potential, and its crucial role in shaping the industries of tomorrow.
Prototype of the Multi-Points IoT-Based Heat and Smoke Monitoring for Open Sites
Authors: Bato Pancress Eddie , Wahid Norfaradilla , Azemi Nur Liesa Mohammad
Published: December 2023

Public awareness is one of the most neglected causes of fire. To ensure the security of the premises and its clients, the crucial highlights rely upon the fire precautionary measure framework and hardware which ought to accord the standard necessities. This also means that the fire safety precautions also need to be taken in an open site working space. This application with all means is to operate a portable fire alarm and monitoring system built using IoT in order to provide fire safety to open site working space. The prototype is developed using the Arduino IDE, Android Studio, PyCharm, and Command Prompt. Meanwhile, the hardware used during the development of this system are MQ-2 smoke sensor, MPL3115A2 12C temperature sensor, MH Flying Fish infrared sensor, NodeMCU ESP8266, and a buzzer. At the end of this application prototype development, the testing phase has shown that the development of the application is a success and the application was able to conduct its functional requirements.
Cloud-Enabled Fire Safety in Industry 5.0 Smart Factories
Authors: Babu C. V. Suresh , Auroshaa A. , Sowmi Saltonya M. , Sathyanarayanan A. S.
Published: December 2023

This chapter explores the critical intersection of Industry 5.0 and fire safety in smart factories. It introduces the concept of cloud-enabled fire monitoring, emphasizing its significance in mitigating fire risks. The analysis delves into fire incident understanding, limitations of conventional systems, and the necessity for real-time monitoring. The cloud-enabled fire monitoring system is detailed, highlighting its scalability and advanced analytics integration for proactive prevention. Real-time fire monitoring and early warning mechanisms are discussed alongside intelligent data analysis and proactive measures. Case studies and future prospects are presented, concluding with the importance of this technology in Industry 5.0 and the broader implications of emerging technologies in smart factories.
Application of Augmented Reality in Manufacturing
Authors: Jose Bibin , Adarsh S. J.
Published: December 2023

AR is a distinctive interface between humans and machines that overlays virtual information generated by computers onto a practical application environment. In the past few years, it has been discovered that AR has the potential to be used in various fields, such as military training, maintenance, assembly, product design, and other production processes. AR is now playing a key role in overcoming the problems of integrating technology to speed up Industry 4.0. It enables workers to convert from mass production to mass customization. AR technology is gaining popularity because of the ease with which it can be implemented in the production and wide accessibility of hardware devices, including smartphones and tablets, that are capable of supporting it. This chapter provides a comprehensive evaluation of the latest AR applications and advancements in the manufacturing industry. Efforts are also made to understand the major challenges in AR applications and the scope for overcoming them in the future.
Digital Wisdom in Education
Authors: Ramdas Girija , Umar Irfan Naufal , Jamiat Nurullizam , Mhd Alkasirah Nurul Azni
Published: December 2023

The pace of change in technology is relentless, and this has a profound impact on how educators' function. Information and communication technology (ICT), which is a significant component of digitalized learning components, has become an essential component of education, requiring all parties involved in the field of education, such as teachers, students, parents, administrators, and education policy-makers, to be fully engaged in their roles towards digitalized education. This chapter would seek to provide a conceptual comprehension of digital wisdom, its significance and methods of practical application within the educational context, and discuss relevant insights from previous studies.
Unleashing the Potential of Every Child
Authors: Riapina Natalia
Published: December 2023

The chapter explores how artificial intelligence (AI) can transform the field of education by providing customized learning experiences that meet the strengths and requirements of students. By investigating a range of real-world case studies, this chapter analyzes how AI-driven, learner-centered technologies can unlock the capabilities of each child. This chapter also scrutinizes the impact of AI on student engagement, performance, and outcomes. Moreover, ethical considerations such as ensuring fair access and balancing technology with human interaction related to the assimilation of AI technologies in educational environments are discussed. The primary objective of this chapter is to provide educators, researchers, and policymakers with insights into thoughtfully using AI to promote learner-centric instruction that customizes curricula, feedback, and support for students. Ultimately, this study seeks to further discourse on the transformation of one-size-fits-all education into dynamic experiences that meet each child's unique capabilities.
Addressing Illegal Workplace Discrimination and the Interactions That Lead to Complaints in Healthcare Organizations
Authors: Burrell Darrell Norman , Huff Allison J. , Crowe Margaret , Springs Delores , Richardson Kevin , Finch Aikyna , Duncan Terrence
Published: December 2023

A study of healthcare organizations found that 87% reported instances of discrimination, the highest industry rate. Illegal workplace discrimination can have many impacts, from reduced employee morale to higher recruitment and litigation costs. Healthcare organizations must address this issue because it can significantly impact their ability to provide quality patient care. Discrimination can lead to a decrease in employee morale, a decrease in productivity, and a decrease in the quality of care that is provided. It can also lead to higher turnover rates and costs associated with recruiting and training new employees. In addition, it can lead to an increase in patient complaints and a decrease in patient satisfaction. This chapter explores how leadership and organizational culture interventions can make a difference.
Hybrid Algorithms for Medical Insights Using Quantum Computing
Authors: Kapoor Nitika , Singh Parminder , Kom Kusrini M. , Bharti Vishal
Published: December 2023

In the field of medicine, machine learning has become very important. It's helping us identify diseases better, take care of patients more personally, and improve many important parts of healthcare. With more and more medical information available, machine learning, which relies on big sets of data, can make predictions more accurate and help doctors make better decisions. This chapter looks closely at how machine learning is being used in medicine right now. It also talks about how quantum computing could change healthcare. First, it explains different ways machine learning is used and how it's being used in medicine. It talks about things like diagnosing diseases, finding new medicines, and treating patients in a way that's right for them. Then, it explores how machine learning and quantum computing could work together. Quantum computing uses special particles to do many calculations at once. This could help process medical information much faster. Quantum computing could also help simulate how molecules interact, which is important for developing new medicines.
Machine Learning and Quantum Computing in Biomedical Intelligence
Authors: Sarangi Pradeepta Kumar , Kumari Shreya , Sawhney Mani , Vajpayee Amit , Rohra Mukesh , Mallik Srikanta
Published: December 2023

The digital world is replete with data like cyber security data, internet of things (IoT) data, enterprise data, mobile data, health data, and more. To analyse this data brilliantly and develop intelligent and automated applications, everyone has to know artificial intelligence (AI) algorithms, deep learning (DL) and machine learning (ML). Therefore, in today's technology-driven or digital world, no company can afford to ignore artificial intelligence or machine learning. Machine learning is a subfield of artificial intelligence, which is the scientific study of algorithms and statistical models that a computer system utilises to effectively carry out a given task without the need for any explicit instructions. This chapter begins with the basics of machine learning and its diverse range of techniques. This chapter also discusses various classification and clustering methods along with their applications and concludes with some real-world applications and examples and research development using machine learning and quantum computing in healthcare.
Disruptive Technologies in Computational Finance
Authors: Kashif Mohammad , Kumar Puneet , Ghai Sachin , Kumar Satish
Published: December 2023

Computational finance plays a pivotal role in addressing the challenges posed by the dynamic and interconnected nature of financial markets. By combining mathematical rigor with computational power, this field contributes to the development of innovative solutions for pricing, risk management, and decision-making in the financial industry. Computational finance is a field that leverages mathematical techniques, statistical methods, and computational tools to analyze and solve complex financial problems. In recent years, the intersection of finance and technology has given rise to a transformative wave, reshaping the landscape of traditional financial systems. This study delves into the dynamic realm of computational finance, exploring the profound impact of disruptive technologies on established practices and processes of computational finance.
Challenges and Opportunities of Machine Learning in the Financial Sector
Authors: Kour Manjit
Published: December 2023

In the field of finance, machine learning has become a potent instrument that is transforming conventional methods of data analysis, decision-making, and risk management. This study examines how machine learning techniques are applied in the financial sector, discussing the challenges and opportunities of machine learning in the financial sector. Machine learning algorithms have been successfully used in fields including stock market forecasting, credit risk assessment, fraud detection, algorithmic trading, and portfolio optimization by utilising enormous volumes of financial data. However, issues with model robustness, interpretability, data quality, and regulatory compliance continue to be major roadblocks. By analyzing the applications, identifying challenges, and exploring opportunities for further development, this chapter seeks to contribute to the understanding and advancement of machine learning in the financial sector.
A Study on Rural BPL Households' Perception Towards Financial Inclusion Schemes
Authors: Singh Harvinder , Mishra Kaushal Kishore , Singh M. P.
Published: December 2023

The chapter aims to study the respondents' perceptions regarding financial inclusion schemes launched by the government of India. The provision of financial services at affordable prices to significant portions of economically underprivileged and low-income populations is known as financial inclusion. The union government and central banks worldwide have made financial inclusion their main priority to promote inclusive growth. It is crucial to look at respondents' opinions of different financial inclusion programs because doing so will pave the way for improving financial services. The study found that the perception level of PM-Jan Dhan Yojana and PM-Jan Arogya Yojana is more assessable and affordable; however, PM-Mudra Yojana and PM-Jan Arogya Yojana are adequate in both states.
AI Implementation Techniques for Finding Earth's Frozen Zones
Authors: M. S. Kavitha , P. Mahalakshmi , L. Manimegalai , S. Sundaramoorthi
Published: December 2023

Implementing artificial intelligence (AI) techniques for finding frozen zones worldwide has received sizeable attention in recent years because of the rising worries concerning climate exchange and its results. This summary outlines the diverse AI techniques employed in this area and highlights their blessings and limitations. In recent years, AI has emerged as an effective device for figuring out and analyzing frozen zones on the Earth. Frozen zones, along with glaciers, ice caps, and permafrost regions, play a vital role within the Earth's weather device, appearing as water reservoirs and affecting sea-degree upward push. This essay explores the programs of AI in identifying frozen zones and the implementation techniques used in this technique. The AI strategies must operate autonomously, with minimal human intervention. By applying AI strategies, researchers can reap extra unique and dependable statistics regarding the state and behavior of these regions, leading to deeper expertise of climate alternate and its influences.
An Early Warning System for Predicting Earthquakes
Authors: T. Gnanasekaran , J. Sofia Vincent , M. Dinesh Babu , T. Harish Babu , K. R. Chairma Lakshmi
Published: December 2023

Earthquakes have long pose a vast danger to human existence and infrastructure. Over time, sizeable studies have been performed in the field of earthquake prediction, mainly on the improvement of an early warning machine. This essay aims to discover the background of earthquake prediction, the want for an early warning system, and the advancements made in this vicinity to mitigate the impact of seismic occasions. This chapter offers the development of a complicated and reliable early warning machine that utilizes a combination of seismic information analysis and device learning techniques. The goals of an early warning system for predicting earthquakes are to offer timely statistics to permit suitable actions, reduce the lack of existence and assets, and foster resilience in affected groups. The advancements in era and studies have provided us with the gear and expertise essential to construct a robust and reliable system that can save limitless lives and limit harm to infrastructure.
Human-Touch Integration in AI Frameworks for Earth Monitoring
Authors: Nalagandla Rambabu , Varagantham Anitha Avula , Pattanaik Ojasvi , Pattanaik Balachandra , Pattnaik Manjula
Published: December 2023

The goal of this chapter is to offer an outline of how humans may be integrated into AI frameworks for Earth tracking. It's going to take a look at the benefits of human-contact integration and speak about how this technique can be adapted to a diffusion of tracking situations. Furthermore, the human-touch integration additionally gives a human-in-the-loop management device that could evaluate and approve any outputs produced by using the AI models. The human contact can also assist with AI version calibration and validation that might, in any other case, be extra tough or not possible with the AI algorithms on my own. For instance, floor fact information from skilled professionals may be used to cross-validate and calibrate the AI fashions to ensure that they may be producing correct outcomes. Taking those measures can assist us in balancing the advantages of human-contact integration with the capability risks that include it, allowing us to use AI frameworks to monitor and respond to worldwide environmental adjustments.