Characteristics of the Solution of a Certain Riccati Differential Equation Using GeoGebra in Engineering Students through a Case Study | Chapter 9 | Mathematics and Computer Science: Research Updates Vol. 6

 

The objective of this study was to explore how engineering students at the University of Sinú (Colombia) understand and solve a Riccati differential equation using GeoGebra during the first semester of 2024. A qualitative approach was adopted with a case study design, involving three students selected at the researchers’ discretion from a total of nine students in the differential equations course. Through semi-structured interviews, the study aimed to identify the usefulness of the software for visualising and verifying solutions, as well as to recognise students’ perceptions of its advantages and limitations. The results show that GeoGebra facilitated the graphical representation of the comparison between manual and computational solutions, and the analysis of conceptual errors, which strengthened the understanding of the behaviour of differential solutions. Among the advantages, participants highlighted the immediacy in verifying results and the visual clarity for the graphical interpretation of equations, while as limitations, they pointed out technological dependence and the initial difficulty in learning the digital environment. In conclusion, the use of GeoGebra not only increases students’ motivation but also constitutes a valuable pedagogical resource for improving the teaching and learning of differential equations, providing relevant implications for engineering education. Learning differential equations provides relevant implications for engineering education.

 

 

Author(s) Details

Jorge Olivares Funes
University of Antofagasta, Chile.

 

Eber Javier Lenes Puello
University of Sinú, Cartagena Section, Area of Exact Basic Sciences, Colombia.

 

Pablo Martin
University of Antofagasta, Chile.

 

Please see the book here :- https://doi.org/10.9734/bpi/mcsru/v6/6186

 

Real-Time Object Detection via Cloud-Enabled Deep Learning: A Systematic Review | Chapter 6 | Mathematics and Computer Science: Research Updates Vol. 6

 

Automated vehicles, advanced surveillance systems, AR, and robots are just a few of the many new uses for real-time object recognition.  While deep learning models are becoming increasingly complex and accurate, they might be challenging to execute on edge devices with limited resources due to the computational demands. By offloading computationally intensive processes to scalable cloud infrastructure, cloud-enabled deep learning enables real-time processing without sacrificing detection accuracy, offering an effective alternative.  This study takes a close look at the current setup of cloud-based object recognition methods that work in real time. When considering latency, bandwidth, privacy, and processing costs, the pros and cons of several architectural paradigms are evaluated, including hybrid methodology, distributed inference, and edge-cloud cooperation. Additionally, the developments of lightweight convolutional neural networks (CNNs), single-shot detectors, and model compression techniques are examined, all of which are aimed at real-time performance in cloud environments.  Improving fault tolerance, optimizing data transmission, safeguarding data security and privacy, and developing more adaptive and efficient cloud resource management strategies for dynamic real-time object detection contexts are all areas that could be further explored in this review.

 

 

Author(s) Details

Abdul Razzak Khan Qureshi
Department of Computer Science, Medicaps University, Indore, Madhya Pradesh, India.

 

Ruby Bhatt
Department of Computer Science, Medicaps University, Indore, Madhya Pradesh, India.

 

Govinda Patil
Department of Computer Science, Medicaps University, Indore, Madhya Pradesh, India.

 

Please see the book here :- https://doi.org/10.9734/bpi/mcsru/v6/5867

 

Book of Contemporary Multidisciplinary Research | Book Publisher International

 

This volume stems from the International Conference on Business and Management Dynamics (ICBMD) which seeks to understand the socio-economic problems and prospects of the global intricacies of the cycle of global evolution and socio-economic development and in the sphere of business and management. It exemplifies the ICBMD’s commitment to Interdisciplinary scholarship and the context-sensitive constructive scholarship of theory, practice and policy.

 

The diverse contributors to this volume have one thing in common – an attempt to understand how various organisations, institutions, and communities manage and respond to the complexities of volatility, inequality, digital disruption, and structural change in both developing and developed worlds. Despite the varying backgrounds of the contributors which include business management, economics, entrepreneurship, technology, public governance and development, they are united in their interest toward the study of the economy and the socio-system of technologies and governance and the democratic structures of society. In this regard, this volume is a manifestation of ICBMD’s commitment to support cross-disciplinary scholarship.

 

The focus of analyses is on Africa and the Global South, particularly emergent and transitional economies. This focus is neither a coincidence, nor is it a mere tokenism. It speaks to the appreciative of the conference that the production of global knowledge is to acknowledge the margins and the context and the consequences of the knowledge production. Therefore, the chapters go beyond the abstract theorisation, and address, in particular, economic and other forms of inequalities, digital divides, and other ecosystem issues, entrepreneurial ecosystem issues, organisational resilience and governance, and value(s) in sustainability.

 

The volume demonstrates a range of methodologies. The combination of conceptual, empirical, qualitative and quantitative, and normative and applied work is deliberate and speaks to ICBMD’s preference for responding to complex societal challenges with integrative and adaptive approaches rather than reductive ones.

 

This publication is intended to serve several purposes linked to possible audiences co-related to ICBMD. For scholars, we address current debates and construct empirically backed theoretical propositions. For practitioners and policymakers, we offer insights and analytical frameworks to support flexible decision-making in difficult and turbulent situations. For postgraduate and early career researchers, we exemplify scholarly rigour, contextual prominence, and ethical reflexivity.

 

What we do know and can say with confidence is that business and management scholarship ought to remain socially responsive and intellectually courageous, and future oriented. We hope the chapters in this volume spark research, stimulate discourse, and advocate for more socially inclusive, creatively innovative, and economically sustainable flexible systems.

 

Editor(s) Details

Prof. Michael Twum-Darko

Faculty of Business and Management Sciences at Cape Peninsula University of Technology in Cape Town, South Africa.

 

Please see the book here :- https://doi.org/10.9734/bpi/mono/978-81-998711-6-8

 

 

Emerging Horizons in Scientific Research | Book Publisher International

 

Scientific research is undergoing a profound transformation driven by rapid technological advances, interdisciplinary integration, and an urgent global need for sustainable and innovative solutions. The edited volume Emerging Horizons in Scientific Research is conceived against this dynamic backdrop, with the aim of presenting contemporary developments across diverse yet interconnected domains of science. This book brings together ten thoughtfully curated chapters authored by experts, offering a panoramic view of how fundamental science and applied research are jointly shaping the future.

 

The opening chapters lay a strong foundation by highlighting the pivotal role of core scientific disciplines in modern innovation. Chapter 1 explores the role of biotechnology in advancing medical diagnostics and therapeutics, emphasizing cutting-edge tools that are redefining healthcare outcomes. Chapter 2 traces the contribution of chemistry to scientific innovations from past milestones to present achievements and future prospects, underscoring its central role as the “central science” linking multiple disciplines. Advances in materials science and nanotechnology are addressed in Chapters 3 and 5. Chapter 3 focuses on bio-nanocomposites, covering their synthesis, characterization, and multifunctional applications in areas ranging from biomedicine to environmental remediation. Chapter 5 provides a comprehensive review of computational approaches in nanomaterials, with particular emphasis on Density Functional Theory (DFT) and Machine Learning applications that are accelerating materials discovery and design. Energy sustainability and environmental stewardship form another major theme of this volume. Chapter 4 presents analytical and mathematical approaches for modeling and optimizing solar wind renewable energy systems, offering insights into efficient energy harvesting and system optimization. Chapter 6 discusses transformative approaches in green chemistry aimed at minimizing environmental impact while maximizing efficiency and innovation. Complementing this, Chapter 7 addresses water quality, focusing on strategies to transform pollution into purity and ensure both human health and environmental sustainability. Frontiers of fundamental science and advanced synthesis are explored in the concluding chapters. Chapter 8 delves into quantum technologies, presenting them as the next frontier in physics with far-reaching implications for computation, communication, and sensing. Chapter 9 reviews emerging trends in polymer science, highlighting novel materials and applications driving industrial and technological progress. Finally, Chapter 10 examines recent advances in the multicomponent synthesis of thiazoles, showcasing innovative synthetic strategies relevant to pharmaceuticals and functional materials.

 

Collectively, the chapters in this book reflect the convergence of theory, experimentation, and computation, as well as the growing emphasis on sustainability and societal impact. Emerging Horizons in Scientific Research is intended to serve as a valuable reference for researchers, academicians, postgraduate students, and professionals across scientific disciplines. It is our hope that this volume will not only inform readers about recent advances but also inspire new ideas, collaborations, and future research directions at the frontiers of science.

 

Editor(s) Details                 

Anshul Bansal

Department of Chemistry at S. A. Jain (PG) College, Ambala City, Haryana, India.

 

Nitya Kaushik

Department of Chemistry, Kurukshetra University, Kurukshetra (Haryana), India.

 

Poonam

Department of Chemistry, Ambedkar Government College, Kaithal (Haryana), India.

 

Please see the book here :- https://doi.org/10.9734/bpi/mono/978-81-998711-7-5

Algorithmic Society and the Future of Sociology: Epistemic, Theoretical and Global South Interventions | Chapter 7 | New Horizons of Science, Technology and Culture Vol. 7

 

The rapid proliferation of artificial intelligence (AI) and algorithmic infrastructures has created a profound epistemic turning point for sociology. This chapter provides a theoretical and critical conceptual analysis, highlighting how algorithmic systems restructure knowledge production, social interaction, rationality, and governance. Drawing upon sociological, philosophical, decolonial, and media theoretical frameworks, the chapter argues that sociology must undergo epistemic realignment to sustain intellectual authority and conceptual relevance in the twenty-first century. Selective empirical illustrations, such as India’s Aadhaar system and African language AI initiatives, demonstrate how Global South interventions challenge Eurocentric and techno-centric approaches, producing alternative epistemologies and social imaginaries.

 

Author(s) Details

Sameena Z Mir
School of Law & Liberal Arts, Ajeenkya DY Patil University, India.

 

Please see the book here :- https://doi.org/10.9734/bpi/nhstc/v7/6936

Spatial Assessment of Soil Suitability for Major Tree Crops Using GIS and Local Knowledge Systems in Ejisu-Juabeng District | Chapter 5 | Agricultural Sciences: Techniques and Innovations Vol. 7

 

Sustainable land management is crucial for mitigating land degradation, restoring degraded areas, and ensuring the optimal use of land resources for the benefit of both present and future generations. There is a growing interest and recognition of the importance of local technical knowledge in the planning, use, and sustainable management of land resources. This study assessed indigenous knowledge of soil suitability and compared it with technical soil evaluation approaches in four villages within the Ejisu–Juabeng District of the Ashanti Region, Ghana. Two contrasting but complementary soil mapping approaches were employed: a geopedologic approach following Zinck (1988), representing expert-driven soil classification, and a farmer-based approach that relied on local spatial knowledge, experience, and land-use history. Farmers first developed soil maps based on their understanding of landscape features and soil behaviour, and subsequently evaluated the suitability of mapped soils for economically important tree crops—cocoa, oil palm, and citrus. In parallel, expert-based soil suitability evaluation was conducted using the Automated Land Evaluation System (ALES), which applies the Food and Agriculture Organisation (FAO) land evaluation framework by matching land characteristics and qualities with specific crop requirements. The resulting farmer-derived and expert-derived suitability maps were integrated and analysed within a Geographic Information Systems (GIS) environment to assess spatial correlation and agreement between the two knowledge systems. Farmers’ suitability assessments indicated that 81% of the study area was suitable for cocoa, while citrus and oil palm accounted for 71% and 26%, respectively. In contrast, expert-based evaluations classified 66% of the area as suitable for cocoa, with citrus and oil palm suitability covering 41% and 39%, respectively. Comparative map analysis revealed overall accuracies of 67% for cocoa, 43% for citrus, and 14% for oil palm, reflecting varying degrees of concordance between local and technical assessments. The spatial correlation analysis highlights both convergences and divergences in soil classification between indigenous and expert systems, with topsoil characteristics emerging as a critical factor influencing farmer decision-making. The findings underscore the importance of integrating local soil knowledge with scientific land evaluation tools to enhance sustainable land management and informed agricultural planning in smallholder farming systems.

 

 

Author(s) Details

Edward Calys-Tagoe
Department of Soil Fertility and Plant Nutrition, CSIR - Soil Research Institute, Ghana.

 

Adams Sadick
Department of Soil Analytical Services, CSIR - Soil Research Institute, Ghana.

 

Prince Martin Gyekye
Department of Soil Genesis, Accra Centre, CSIR - Soil Research Institute, Ghana.

 

Gideon Asamoah
Department of Microbiology, CSIR-Soil Research Institute, Ghana.

 

Ben Amoah
Department of Microbiology, CSIR-Soil Research Institute, Ghana.

 

Please see the book here :- https://doi.org/10.9734/bpi/asti/v7/6913

 

Synthesis, Morphological Studies of Nanocellulose Fibers of Mango Wood| Chapter 10 | Chemical and Materials Sciences: Research Findings Vol. 6

 

Agricultural biomasses are the prominent natural sources of cellulose currently available on the planet. When this was treated chemically, this acquires the properties such as toughness, good biocompatibility, and higher thermal stability. The purpose of this study is to transform agricultural biomass into value-added material through green synthesis, and hence, the nanocellulose is synthesised from Mango wood. In this study, Nanocellulose was extracted from Mango wood (Mangifera indica), a widely available agricultural biomass. The cellulose was alkali-treated, followed by bleaching to remove lignin and hemicellulose, pectins, and waxes. The green solvent, i.e., Ionic liquid (1-butyl-3-methylimidazolium chloride ([Bmim]Cl) was used to dissolve cellulose to yield Nanocellulose through sonication and centrifugation. FT-IR, X-Ray Diffraction, SEM, TEM, and Thermo Gravimetry studies were used to examine the functionality, crystallinity, and morphology of synthesised nanocellulose. The functional groups and significant conversion of cellulose to nanocellulose are confirmed by FT-IR spectra. The crystallinity of the synthesised nanocellulose is illustrated by XRD. The surface architecture and size obtained are represented by SEM and TEM monographs. The TEM images depict that the synthesised nanocellulose has a dimension between 27.33 and 34.85 nm. The thermal studies evidenced that the synthesised nanocellulose shows superior thermal stability up to 473.8°C. As a result of high thermal resistance, this can be used in the manufacture of high-temperature-resistant materials. Due to their smaller size, these can be used to manufacture high-strength nanocomposites. The efficient conversion of agricultural waste into value-added material is achieved through a greener pathway. This study demonstrates the practical application of nanocellulose synthesised from agricultural biomass, providing a sustainable approach to solid waste management and reducing chemical usage in nanocellulose production in India.

 

 

Author(s) Details

Prasannakumar J K
Department of Chemistry, Bapuji Institute of Engineering and Technology, Affiliated to VTU, Belagavi, Karnataka, India.

 

Krishnakumar T K
Department of Physics, Bapuji Institute of Engineering and Technology, Affiliated to VTU, Belagavi, Karnataka, India.

 

Vijayakumar T N
Department of Mechanical Engineering, Bapuji Institute of Engineering and Technology, Davanagere-577004, Affiliated to VTU, Belagavi, Karnataka, India.

 

Please see the book here :- https://doi.org/10.9734/bpi/cmsrf/v6/6740