bluuebunny/crossref_metadata_2025 huggingface dataset:
Enhancing Public Knowledge of Sharia Insurance Products in Indonesia Through Effective Management Strategies
Authors: Maulana Anwar  , Raden Arfan Rifqiawan  , Amir Tajrid  , Supangat Supangat  , Sahidin Sahidin
Published: December 2024

Islamic insurance, known as Sharia Insurance, has emerged as a vital aspect of Indonesia's financial landscape. Sharia Insurance adheres to Islamic economic principles, offering products such as takaful (mutual guarantee) and mudharabah (profit-sharing). The potential for growth in Indonesia's Sharia insurance sector is substantial, bolstered by the country's predominantly Muslim population, which constituted 87.2% of the total population in 2021. Moreover, under Financial Services Authority Regulation (FSAR) Number 11 of 2023, Article 15, Sharia financial institutions are mandated to prioritize Sharia-compliant financial products. Despite these regulatory supports, however, Sharia insurance has achieved only a modest market share, with premiums accounting for just 4.76% as of December 31, 2022. In response to these challenges and opportunities, this study aims to examine the barriers, particularly the issue of public awareness, where many individuals lack a comprehensive understanding and appreciation of the advantages offered by Sharia insurance products. Consequently, this paper addresses two main objectives: 1) identifying factors contributing to public misconceptions and limited awareness of Sharia insurance benefits, and 2) exploring initiatives aimed at addressing these issues. This research employs a qualitative approach, employing systematic literature review techniques to analyze relevant books and literature focused on the identified themes. The findings aim to offer insights into the challenges faced by Sharia insurance and propose strategies to enhance public awareness and understanding of Islamic insurance products.
Design and Validation of Super-Capacitor Assisted Photovoltaic Array for Roof-Top Solar Powered Electric Vehicle Applications
Authors: K. Karunanithi , Saravanan S. , S Ramesh. , Raja S.P. , Kannan S. , Vijayakumar S.C.
Published: December 2024

Upkeeping the Battery State-Of-Charge (SoC) and its life are of great significance in Battery Electric Vehicle (BEV) & Hybrid Electric Vehicles (HEV). This is possible by integrating Solar Photovoltaic Panels (PPs) on the Roof-top of the BEVs & HEVs. However, unlike Solar Powered Vehicle Charging stations and other PV applications where the solar panels are installed in such a way to extract the maximum Photon energy incident on the panel, vehicle Roof-top mount Solar PPs face many challenges in extracting maximum Power due to partial shading issues especially under dynamic conditions when passing under trees, high rise buildings and cloud passages. This paper proposes a new strategy called ``Super-capacitor Assisted Photovoltaic Array". In which Photovoltaic Modules are integrated with Super-capacitors to improve the transient performance of the Photovoltaic Array system. The design of proposed Super-capacitor Assisted PV array is validated & its performance is compared with conventional PV array in Matlab/ Simulink environment.
Optimal Assimilation of Distributed Generation in Radial Power Distribution System Using Hybrid Approach
Authors: Pradeepkumar CH S K B , A Sakthidasan , R Sundar , Kumar M Senthil , P Rajakumar , P Baburao
Published: December 2024

The performance of power distribution systems (PDS) has improved greatly in recent times ever since the distributed generation (DG) unit was incorporated in PDS. DG integration effectively cuts down the line power losses (PL) and strengthens the bus voltages (BV) provided the size and place are optimized. Accordingly, in the present work, a hybrid optimization technique is implemented for incorporating a single DG unit into radial PDS. The proposed hybrid method is formed by integrating the active power loss sensitivity (APLS) index and whale optimization meta-heuristic algorithm. The ideal place and size for DG are optimized to minimize total real power losses (TLP) and enhance bus voltages (BV). The applicability of the proposed hybrid technique is analyzed for Type I and Type III DG installation in a balanced IEEE 33-bus and 69-bus radial PDS. Optimal inclusion of type I and III DG in a 33-bus radial test system cut down TLP by 51.85% and 70.02% respectively. Likewise, optimal placement of type I and III DG reduced TLP by 65.18%, and 90.40%, respectively for 69-bus radial PDS. The impact of DG installation on the performance of radial PDS has been analyzed and a comparative study is also presented to examine the sovereignty of the proposed hybrid method. The comparative study report outlined that the proposed hybrid method can be a better choice for solving DG optimization in radial PDS.
Recomendaciones para el mes de Marzo
Authors:   Centro Nacional de Investigaciones de Café
Published: December 2024

El Instituto Internacional de Investigación para Clima y Sociedad, el Centro de Predicción Climática de la NOAA y demás centros de predicción climática internacional, prevén que el evento La Niña débil, presente actualmente en la cuenca del Océano Pacífico Tropical, continúe debilitándose y se espera que alcance la fase Neutra hacia el trimestre centrado en abril (marzo-abril-mayo) de 2018, con una probabilidad del 54%.
Édmond-Édouard Boissonnas and Édouard Chapuisat’s
Smyrne
(1919)
Authors: Wilson Colette
Published: December 2024

This article revisits the Mediterranean port city of Smyrna (today’s Izmir) in 1919 as it stood on the cusp of monumental change. Édmond-Édouard Boissonnas’s photographs and Édouard Chapuisat’s accompanying textual frames in the album
Smyrne
capture the city just as the Greek army landed there to begin their occupation of Asia Minor in a doomed bid to defeat the Ottoman Turks and create a new Byzantine empire. The article argues for the propagandist, transnationalistic aim of
Smyrne
in support of the Greek state’s irredentist agenda based on what Astrid Erll identifies as the ‘isomorphy between territory, social formation, mentalities and memories’. ‘Civilised’ Greeks are pitted against ‘backward’ Turks, and those who do not fit the narrative at all – Jews and Armenians – are excluded. The article concludes by reflecting on the afterlife of the album on a Greek heritage website which now offers the potential for reconciliatory nostalgia for both Greeks and Turks.
Integer divisor connectivity graph
Authors: Jorf M. , Oukhtite L.
Published: December 2024

UDC 512.5
Let

n

be a nonprime integer. We introduce a new simple undirected graph and denote it by

M
D

(
n
)

,

where the vertices are the proper divisors of

n

and two vertices

x

and

y

are adjacent if

x
y

divides

n
.

 We explore the connectedness of

M
D

(
n
)

and provide detailed calculations for the degree of each vertex. In addition, we focus on the special case where

n
=

p
α

,

where

p

is a prime positive integer and

α
≥
3

is a positive integer. For these instances, we explicitly determine the chromatic number

χ

and the clique number

ω

of

M
D

(
n
)

.

 Finally, we conclude that

χ

(
M
D
(
n
)
)

=
ω

(
M
D
(
n
)
)

.
CLASSY. XI. Tracing Neutral Gas Properties Using UV Absorption Lines and 21 cm Observations*
Authors: Parker Kaelee S. , Berg Danielle A. , Gazagnes Simon , Chisholm John , James Bethan L. , Hayes Matthew , Heckman Timothy , Henry Alaina , Berg Michelle A. , Arellano-Córdova Karla Z. , Xu Xinfeng , Erb Dawn K. , Martin Crystal L. , Hu Weida , Skillman Evan D. , McQuinn Kristen B. W. , Chen Zuyi , Stark Dan P.
Published: December 2024

Rest-frame far-ultraviolet (FUV) observations from JWST are revolutionizing our understanding of the high-z galaxies that drove reionization and the mechanisms by which they accomplished it. To fully interpret these observations, we must be able to diagnose how properties of the interstellar medium (ISM; e.g., column density, covering fraction, and outflow velocity) directly relate to the absorption features produced. Using the high-signal-to-noise and high-resolution FUV spectra of 45 nearby star-forming galaxies from the Cosmic Origins Spectrograph Legacy Spectroscopic Survey, we present the largest uniform, simultaneous characterization of neutral and low-ionization state (LIS) interstellar UV absorption lines (O i, Si ii, S ii, C ii, and Al ii) across a wide range of galaxy properties. We also present 21 cm H i observations for 35 galaxies, multiple of which are gas-poor or nondetected, possibly indicating the onset of a post-starburst phase. We find that our simultaneous one-component Voigt profile fits are capable of accurately modeling the LIS absorption for ∼75% of galaxies, mitigating challenges associated with saturation, infilling, and degeneracies. While the most massive galaxies require additional components, our one-component fits return average properties of the absorbing gas and follow the scaling relations described by a single gas cloud. We explore connections between LIS absorption and direct tracers of the neutral ISM (O i, Lyα, and H i 21 cm), finding that C ii most closely traces the neutral gas trends, while other ions exhibit weaker correlations. Given the challenges with directly observing H i at higher-z, we demonstrate that LIS absorption can be a powerful means to study the neutral ISM and present empirical relationships for predicting neutral gas properties.
Distribution and Anisotropy of the Energy Transfer Rate in the Solar Wind Turbulence
Authors: Wu Honghong , Huang Shiyong , Wang Xin , Yang Liping , Yuan Zhigang
Published: December 2024

The distribution of the energy transfer rate is critical for the interpretation of the intermittent energy cascade in the solar wind turbulence. However, the true observational distribution of the energy transfer rate in the solar wind and its anisotropy remain unknown. Here, we use a 7 day interval measured by Wind in the fast solar wind and investigate the distribution and anisotropy of the energy transfer rate based on the log-Poisson model. We find that the probability density distribution consists of two parts. The majority part locates at smaller values and is consistent with the log-normal distribution. The estimated mean value and standard deviation of the logarithmic energy transfer rate for the majority are both smaller in the direction parallel to the local mean magnetic field than in the perpendicular direction. The mean value displays a power-law shape with respect to the scale, with flatter index in the parallel direction and steeper index in the perpendicular direction. The minority part locates at larger values and expands as the scale decreases, indicating the growing intermittency toward smaller scales. The flatness for parallel logarithmic energy transfer rate is larger than that for perpendicular. And it rises as the scale decreases for all directions, demonstrating the relatively longer tail of the distribution with decreasing scale. Our results provide new insight to help interpret the intermittent energy cascade process in the solar wind turbulence.
On absolutely invertibles
Authors: García-Pacheco Francisco Javier , de los Ángeles Moreno-Frías María , Murillo-Arcila Marina
Published: December 2024

In this manuscript, the notion of absolutely invertible was extended consistently from semi-normed rings to the class of general topological rings. Then, the closure of the absolutely invertibles multiplied by a certain element was proved to be contained in the set of topological divisors of the element. Also, a sufficient condition for the closed unit ball of a complete unital normed ring to become a closed unit neighborhood of zero was found. Finally, two applications to classical operator theory were provided, i.e., every Banach space of dimension of at least $ 2 $ could be equivalently re-normed in such a way that the group of surjective linear isometries was not a normal subgroup of the group of isomorphisms, and every infinite-dimensional Banach space, containing a proper complemented subspace isomorphic to it, could be equivalently re-normed so that the set of surjective linear operators was not dense in the Banach algebra of bounded linear operators.
Research on bearing fault diagnosis based on a multimodal method
Authors: Chen Hao , Li Shengjie , Lu Xi , Zhang Qiong , Zhu Jixining , Lu Jiaxin
Published: December 2024

As an essential component of mechanical systems, bearing fault diagnosis is crucial to ensure the safe operation of the equipment. However, vibration data from bearings often exhibit non-stationary and nonlinear features, which complicates fault diagnosis. To address this challenge, this paper introduces a novel multi-scale time-frequency and statistical features fusion model (MTSF-FM). Specifically, the method first employs continuous wavelet transform to generate time-frequency images, capturing local and global features of the signal at different scales. Contrast enhancement techniques are then used to improve the visual quality of these images. Next, features are extracted from the time-frequency images using a visual geometry group network to obtain deep features of image modalities. In parallel, 13 key features are extracted from the original vibration data in the time-frequency domain. Convolutional neural networks are then employed for deep feature extraction. Experimental results demonstrate that MTSF-FM achieves accuracies of 98.5% and 95.1% on two public datasets. These findings highlight the effectiveness of MTSF-FM in analyzing complex vibration data and propose a novel method for bearing fault diagnosis.
STANOVANJE PRVO: DJELOTVORNOST U IZLASKU IZ BESKUĆNIŠTVA, UNAPREĐENJU ZDRAVLJA I KVALITETE ŽIVOTA
Authors: Knezić Dragana
Published: December 2024

Housing First is one of the best-researched and documented approaches to ending homelessness, grounded in the human right to adequate housing. It is precisely
because of this foundation and numerous evidence of effectiveness that Housing
First is supported by international and European policies on human rights and the
fight against poverty. This paper presents key evidence in support of the effectiveness of this approach related to the outcomes of exit from homelessness and housing
stability, improvement of mental health, quality of life and cost-effectiveness of interventions. The available research provides convincing evidence of the advantages
of the Housing First approach compared to traditional approaches in terms of the
effectiveness of exiting homelessness and the stability of housing, as well as the
improvement of the quality of life, assessed by various parameters. Regarding the
improvement of mental health and the cost-effectiveness of interventions, the results are mixed.
Key words: homelessness; Housing first; human right to adequate housing;
mental health; quality of life; cost-effectiveness of interventions; fight against
homelessness i social exclusion
De l'obéissance à la révolte ?
Authors: Martins Diana
Published: December 2024

Le soulèvement de l'héritier de la couronne portugaise, Alphonse, contre son père, le roi Denis du Portugal (1279-1325), entre 1317 et 1323, a profondément marqué le regard porté sur les relations existant entre le souverain, et son héritier et successeur. Le présent article s’efforce de contourner les limitations parfois imposées par les différentes sources en adoptant une approche de longue durée, en partant justement de la perspective du prince et en cherchant à comprendre, à l'aide de différents témoignages, la manière dont l'héritier a été engagé dans les actions diplomatiques menées par son père, en tentant ainsi de retracer les diverses phases de cette relation, tout en essayant de repérer les actes ou bien les moments où le prince a eu et a pu agir de manière indépendante, c'est-à-dire en évitant que son action soit conditionnée ou contrôlée par les intérêts de son père.
Aproximación a una tipología arquitectónica
Authors: Sánchez-Bordona María Dolores Campos , Teijeira María Dolores
Published: December 2024

El presente trabajo trata de estudiar los recintos de las bibliotecas catedralicias españolas durante la Baja Edad Media y comienzos de la Edad Moderna. El desconocimiento que sobre ellas se constata en la historiografía europea nos ha animado a definir sus características, cronología y tipologías, así como a desentrañar las razones de su creación, el modelo utilizado y el proceso evolutivo experimentado por estos espacios librarios en el reino de Castilla. El resultado del estudio ha sido alentador ya que ha puesto de manifiesto la analogía tipológica y funcional con otros ejemplos europeos, en especial con los franceses, alemanes e ingleses, de forma que hoy podemos constatar cómo las librerías catedralicias españolas también jugaron un importante papel en la historia de los espacios del saber, aunque no suficientemente valorado hasta la fecha.
Organizações internacionais na era da descolonização: introdução
Authors: Monteiro José Pedro
Published: December 2024

O estudo das intrsecções históricas que marcaram a história das organizações internacionais e a história da descolonização tem merecido renovado interesse historiográfico nas últimas décadas. Nesta introdução ao dossier temático sobre Organizações Internacionais na Era da Descolonização procura-se identificar alguns dos desenvolvimentos mais promissores neste campo de estudos, relacionando-os com fenómenos e processos históricos específicos. Conclui-se procurando apontar para as formas a partir das quais os artigos que compõem este dossier dialogam com essas interrogações e problemas historiográficos.
Ripple Effects
Authors: Karakuş Muhammed
Published: December 2024

The repercussions of the Russo-Ukrainian War continue to resonate across regions, shaping the geopolitical landscape. One remarkable phenomenon of war is the influx of foreign fighters drawn to the conflict due to a confluence of variegated motivations. However, this influx also injects an element of radicalization due to the presence of far-right and jihadist actors. The fluid and epochal nature of the conflict led powers to create multi-layered grotesque cooperations even with Islamic armed actors. Propelled by a confluence of reasons, these individuals represent a significant factor in the ongoing conflict. As the war grinds on, the study argues that Ukraine—for its survival—is obliged to recruit more and, especially from jihadist elements, to counterbalance fighters on the Russian side. Besides analyzing military strategies and capabilities on both sides, the study also explores the legal and ethical implications of foreign involvement in the war. It delves into the potential for knowledge transfer between armed groups taking sides in the conflict.
The War in Ukraine and the Limits of International Relations Theory
Authors: Pawłuszko Tomasz
Published: December 2024

The text presents possibilities for improving IR theory by increasing the importance of analytical competences in the process of scientific training and research. The war in Ukraine indicates that traditional IR concepts are no longer sufficient, and it is necessary to concretize them for the study of current political events. The author states that analytical training would allow for more effective research on international processes and strengthen the authority of science in the era of new technologies, where companies, think tanks, and the media already have advanced tools for assessing reality. The author believes that if scientists do not develop new ways of working, their work will potentially become redundant.
Optimizing Performance Metrics in Blockchain-Enabled AI/ML Data Analytics
Authors: Arockia Venice J. , Vettriselvan R. , Rajesh Deepa , Xavier Priya , Shanthi H. J.
Published: December 2024

The convergence of blockchain technology with artificial intelligence (AI) and machine learning (ML) has significantly transformed data analytics within Cognitive Internet of Things (CIoT) systems. This chapter investigates the critical performance metrics and evaluation methods necessary to assess the impact and effectiveness of AI/ML-enhanced blockchain analytics. It examines how blockchain contributes to data integrity, transparency, and security, while AI/ML algorithms enhance data processing and decision-making capabilities. The chapter outlines essential performance indicators, analytical approaches, and evaluation techniques for measuring the success of these integrated systems. By presenting case studies and practical examples, it addresses the challenges and benefits associated with deploying these technologies, offering guidance for optimizing performance and achieving reliable results. This analysis is aimed at professionals and researchers who seek to leverage blockchain and AI/ML technologies for advancing CIoT systems.
Automated Brain Tumor Detection From Magnetic Resonance Imaging Using AI-PSO-Based Deep Learning Models
Authors: Mishra Nilamadhab , Mamidi Abhishek , Rout Saroja Kumar , Thakur Amit , Alharbi Meshal
Published: December 2024

The proposed methodology begins with optimizing deep CNN parameters using Particle Swarm Optimization (PSO) to find an optimal configuration that maximizes the network's performance. PSO aids in the exploration of the high-dimensional parameter space, optimizing CNN's convolutional layers for feature extraction. Subsequently, the CNN is employed to automatically extract hierarchical features from magnetic resonance imaging (MRI) scans, capturing intricate patterns indicative of automated brain tumor detection. Healthcare practitioners can use the AI-PSO-Based Deep Learning Models for automated detection and diagnosis purposes.
Indian Legal Documents Corpus for Court Judgment Prediction and Summarization
Authors: Gautam Ayushi , Sharma Vishali , Saha Piyali , Patel Atul R. , Kanmani Sujithra
Published: December 2024

We propose the development of an automated system aimed at assisting judges in predicting case outcomes to streamline the judicial process. To ensure practical utility, this system should provide explanations for its predictions. To support research in this area, we introduce the Indian Legal Documents Corpus (ILDC), a substantial collection comprising 35,000 Indian Supreme Court cases, annotated with their original court decisions. Additionally, a subset of this corpus serves as a test set, annotated with expert-generated explanations for reference. Building upon the ILDC, we present the Court Judgment Prediction (CJP) task, which involves the automated prediction of case outcomes. We conduct experiments using various baseline models for case prediction and introduce a hierarchical occlusion analysis of explanations generated by our proposed algorithm. This analysis reveals a notable disparity between the algorithm's perspective and that of legal experts when explaining judgments, suggesting promising avenues for future research in this domain.
Navigating the Ethical Frontier-Human Oversight in AI-Driven Decision-Making System
Authors: Tariq Muhammad Usman
Published: December 2024

This chapter investigates the complicated harmony between utilising man-made reasoning (artificial intelligence) in an upgraded direction and the basis of maintaining human oversight to maintain moral principles. The potential for both significant benefits and ethical dilemmas grows as AI systems increasingly penetrate critical sectors, such as healthcare, law enforcement, and transportation. This chapter discusses the difficulties in encoding ethical standards in machine-readable formats and the necessity of incorporating human values into AI systems. It examines instances of both successful and flawed AI implementation through in-depth case studies, highlighting the significance of human intervention at crucial junctures for risk prevention and mitigation. In addition, the chapter discusses the significance of creating solid legal, ethical, and practical frameworks to direct the ethical use of AI technologies.
Introduction to Deepfake Technology and Its Early Foundations
Authors: Chataut Robin , Upadhyay Aadesh
Published: December 2024

The advent of deepfakes has revolutionized the digital landscape, presenting both innovative applications and significant challenges. This chapter will provide a comprehensive overview of deepfake technology, focusing on its creation, detection, and mitigation strategies. By examining the evolution, current state, and future prospects of deepfakes, the chapter aims to provide a thorough understanding of this rapidly advancing field. We will explore the origins and development of deepfake technology, tracing its journey from AI research labs to widespread use on social media and beyond. Additionally, we will delve into the technical foundations and early applications of deepfakes, with a focus on Generative Adversarial Networks (GANs), which are pivotal in synthesizing hyper-realistic audio and video content. The chapter will clarify the complex processes behind deepfakes, detailing how these technologies operate, the data they require, and the ethical dilemmas they raise. The rise of deepfakes has led to concerns about misinformation, privacy violations, and security threats.
Preventing Deepfakes From Being Used for Impersonation and Defamation
Authors: Solo Ashu M. G.
Published: December 2024

As technology advances, deepfakes have become a problem. Deepfakes can be used for impersonation and defamation, two of the major problems of the information age. Deepfakes for impersonation have been used to create fake intimate images. This research paper makes 9 recommendations for website policies, 17 recommendations for public policies, and 7 recommendations for public education to combat the use of deepfakes for impersonation and defamation. The author of this research paper previously proposed a field called misinformation identification engineering involving the development of algorithms and software to find, flag, or remove misinformation and disinformation on websites and in other documents.
Building Resilience
Authors: Singh Manjeet , Bhargava Deepshikha , Bhargava Amitabh , Singh Kirti
Published: December 2024

This chapter discusses deepfake and delves into its potential benefits and inherent risks. Contrary to the negative perception generally created about deepfake technology, the authors have given evidence to highlight its positive applications and advantages. This chapter also gives equal discussion to the associated dangers in its use, particularly violations which may arise from criminal activities. With that in view, a review of the networks and applications both utilized in the creation of deepfakes, while assessing state-of-the-art open-source tools presently available, has been performed. The chapter goes further to detail the actual process for creating a deepfake video; hence, this provides some first-hand overview of the technology. The main task of this work is to contribute to enhanced resilience against deepfake-related threats by critically reflecting on various factors, such as: relevant rules and regulations within the EU and North Macedonia; an overview of the regulatory landscape.
A Primer for Governance
Authors: Joshi Ankush , Kumar Vikash , Thakur Gesu , Chauhan Naman , Singh Ritik Kumar
Published: December 2024

This chapter explores the way machine learning is being used in governance, with a particular emphasis on how new AI technologies have the potential to completely transform public sector operations. Machine learning presents enormous potential for enhancing resource management, decision-making, and service delivery as governments throughout the world come under growing pressure to be more responsive, transparent, and efficient. The first part of the chapter identifies and examines major developments in artificial intelligence and their implications for governance, including automated decision systems, natural language processing, and predictive analytics. Recognizing that the adoption of AI in governance requires more than just technology, the chapter also emphasizes the need for developing new skills and competencies among public administrators. Public sector workers must adjust as AI changes workflows and decision-making procedures by gaining managerial, ethical, and technological skills in order to successfully navigate an AI-driven future. The chapter lists the fundamental skills that leaders and practitioners in governance will need, such as data literacy, algorithmic accountability, and an awareness of AI ethics. The chapter also offers a planned road map for incorporating machine intelligence into governance frameworks. It emphasizes how crucial it is to take a stepwise approach, beginning with small-scale pilot initiatives, fostering transparency to foster confidence, and maintaining a steady stream of updates to legal and regulatory frameworks to keep up with technology improvements. The objective of this strategy framework is to assist governments in the responsible adoption of artificial intelligence (AI), guaranteeing that the technology improves public services while upholding equity, responsibility, and public confidence. All things considered, the chapter provides a forward-looking viewpoint on how machine learning might change governance and lays out doable strategies for its morally sound and effective incorporation into public sector operations.
Cyber-Physical Systems for Enhancement in Security While Using Cyber
Authors: Bhatia Abhay , Kumar Anil , Sood Devendra
Published: December 2024

Advancements in affordable computing and communication technologies have led to the widespread proliferation of interconnected devices, giving rise to a new era characterized by devices that sense, compute, and share information, forming loosely connected Cyber-Physical Systems (CPS). Managing data and making intelligent decisions are the primary areas of research within CPS. Traditionally, cloud-based centralized computation has been the dominant architecture due to its ease of implementation and enhanced control. However, the explosion of data, scalability challenges, and privacy concerns are increasingly highlighting the limitations of such centralized systems. Therefore, there is a growing interest in decentralizing control and distributing computing tasks among the devices as a more promising approach for sharing intelligence. Investigating novel decentralization mechanisms is a central focus of this chapter.
Optimizing Image Encryption Efficiency Through Advanced Deep Learning Architectures and Techniques
Authors: Gundalwar Pravin Ramesh
Published: December 2024

Deep learning has significantly advanced image encryption, moving beyond traditional diffusion and confusion methods. This work explores three key methodologies: Encryption with Style Transfer uses neural networks to alter an image's visual style, enhancing security through aesthetic changes but potentially compromising cryptographic strength and efficiency. Style Transfer with Enhanced Diffusion builds on this by incorporating advanced diffusion techniques, improving attack resistance at the cost of increased computational complexity. Combining DNN with Chaotic Systems merges chaos theory with neural networks to produce highly unpredictable encryption patterns, enhancing robustness but adding design complexities and potential vulnerabilities. The work also addresses emerging threats such as Hidden Factors Leakage, involving exposure of internal model parameters, and Network Architecture Leakage.
Breaking Barriers
Authors: Ismail Laith Shlash , Ismail Osama A. Sh
Published: December 2024

Integration of Blue-Green Infrastructure could be considered a significant move towards transformation to a sustainable urban society. The present report specifies issues, and controversies relating to UBGI in the context of sustainable transformation along with solutions and recommendations relating to the same. It has been assessed that efficient utilization of urban space and sustainable development can be done only through compliance with BGI development. The main challenge assessed includes maintaining coordination and transparency between the stakeholders involved. Even various financial, economic and social constraints are dealt with for accomplishing specified projects. Real case studies have been discussed to evaluate the impact as well as the challenges faced while incorporating a specified framework. To reach an advanced level in context with transformation towards sustainable urban infrastructure it is necessary to explore integrated design approaches like Blue Green Architecture and interdisciplinary collaboration of engineering and ecological perspectives in future.
Integrating Artificial Intelligence in Blue-Green Infrastructure
Authors: Seelam Dhanunjay Reddy , Kidiyur Mridula Dileepraj , Whig Pawan , Gupta Shashi Kant , Balantrapu Siva Subrahmanyam
Published: December 2024

This chapter explores the transformative role of Artificial Intelligence (AI) in enhancing the design, implementation, and management of Blue-Green Infrastructure (BGI), a sustainable urban planning approach that integrates natural and engineered systems to address environmental challenges. The convergence of AI with BGI offers unprecedented opportunities to improve urban resilience, optimize resource management, and mitigate the impacts of climate change. Through advanced data analytics, predictive modeling, and real-time monitoring, AI-driven solutions can enhance the efficiency and effectiveness of BGI projects. This chapter delves into the various AI applications in BGI, including smart water management, flood prediction and prevention, urban heat island mitigation, and biodiversity conservation. Case studies and examples from global cities illustrate how AI is being leveraged to create more adaptive, sustainable, and resilient urban environments. The chapter also discusses the challenges and ethical considerations associated with the integration of AI in BGI, emphasizing the need for interdisciplinary collaboration and responsible AI deployment to ensure equitable and long-term benefits.
Integrating Green Infrastructure With AI-Driven Dynamic Workload Optimization for Sustainable Cloud Computing
Authors: Vemula Vamshidhar Reddy
Published: December 2024

The rapid growth of cloud computing has raised concerns about its environmental impact, particularly in terms of energy consumption and carbon emissions. This chapter explores the integration of green infrastructure with AI-driven dynamic workload optimization to promote sustainable cloud computing practices. By leveraging AI algorithms, cloud service providers can dynamically adjust resource allocation, optimize energy use, and enhance overall operational efficiency. The implementation of green infrastructure, including renewable energy sources and energy-efficient data centers, further supports the reduction of the ecological footprint associated with cloud services. This chapter examines the principles and strategies for achieving synergy between AI technologies and green infrastructure, presenting case studies that demonstrate successful implementations. The findings indicate that this integrated approach not only enhances sustainability but also improves cost-effectiveness and operational resilience, positioning organizations to meet both environmental goals and business objectives.
AI (Artificial Intelligence) Leveraging to Foster DEI (Diversity, Equity, and Inclusiveness) in Organizations
Authors: Karthikeyan C.
Published: December 2024

Artificial Intelligence (AI) has emerged as a transformative force across various sectors, with its potential to drive change in Diversity, Equity, and Inclusion (DEI) efforts becoming increasingly evident. This chapter explores recent developments in AI technology and its implications for enhancing DEI initiatives. It examines how AI can both support and challenge DEI goals, addressing issues such as algorithmic bias, representation, and accessibility. Through a review of current literature and case studies, the essay highlights the role of AI in promoting inclusivity while also identifying critical areas where AI-driven systems need refinement to avoid perpetuating existing disparities. By leveraging AI responsibly, organizations can create more equitable and diverse environments that reflect broader societal values.
Strengthening the Entrepreneurial Mindset With Artificial Intelligence in the Digitalization Process
Authors: Adiguzel Zafer
Published: December 2024

The intersection of entrepreneurship, digital technologies, and artificial intelligence (AI) is shaping the modern business landscape and future economic opportunities. It is important to examine entrepreneurial behavior patterns and entrepreneurial intent, the motivations, attitudes, and actions of contemporary entrepreneurs in terms of digital technology and AI. In the context of Industry 4.0, digitalization presents both challenges and opportunities, encouraging businesses to adapt to advanced technologies such as AI and automation while contributing to sustainable development goals. The chapter examines the evolving digital entrepreneurship ecosystem, emphasizing the role of infrastructures, policies, and funding that support innovation. The future of AI is assessed, discussing technological advances and the societal challenges that need to be addressed to ensure that AI serves as a force for sustainable growth and positive societal impact.
The importance of the cardiology observation unit in the management of patients with cardiovascular diseases: a pilot project
Authors: Monti Manuel , Cappannelli Simone , Cardile Marco , Cosmi Deborah , Di Pasquale Tania , Cappannelli Mariana , Fagotti Jacopo , Quadalti Pietro , Marvardi Michele , Marchetti Roberto , Capponi Euro
Published: December 2024

The intensive short observation (OBI) unit provides rapid diagnostic and therapeutic evaluations for patients in emergency-urgent conditions. Due to emergency department (ED) overcrowding, dedicated OBIs have been developed to improve care. As a pilot project, a cardiological OBI was established where specialist physicians manage patients, supported by nursing staff from the assigned unit. After observation, patients are discharged, hospitalized in cardiology, or transferred to other departments based on diagnostic needs. In 6 months, 107 patients were admitted to the cardiology OBI, with 85 (76%) discharged. Most admissions were for high-risk chest pain (55%), palpitations (30%), or suspected early-stage heart failure (15%). Notably, three patients were diagnosed with acute coronary syndrome after specialized evaluations for initially unclear symptoms. Preliminary results highlight the cardiological OBI’s effectiveness in reducing inappropriate hospitalizations, identifying complex cases early, and easing ED overcrowding. It met all performance goals, demonstrating the potential to optimize patient pathways and enhance diagnostic accuracy in challenging cases. Strengthening the cardiological OBI appears essential for addressing ED pressures and improving specialized patient care.
Ramadan Fasting Practice Trend in Muslim Patients with Diabetes: A Nationwide Survey in Bangladesh
Authors: Pathan Md. Faruque , Amin Mohammad Feroz , Afsana Faria , Saifuddin M. , Qureshi Nazmul Kabir , Mir Ahmed Salam , Rahman Muhammad Hafizur , Khan Laique Ahmed , Amin Ahsanul Haque , Haque Azizul , Ashrafuzzaman S. M. , Selim Shahjada
Published: December 2024

Background:

Despite health concerns, practicing Muslims with diabetes around the world observe fast during this month. This study aimed to explore the pattern of fasting behavior and associated factors among Muslim diabetic patients during Ramadan in Bangladesh.

Methods:

A cross-sectional survey was carried out among Muslim adult (>18 years) patients with diabetes attending in the private chamber of endocrinologists registered with Bangladesh Endocrine Society in different parts of Dhaka city, the Capital of Bangladesh between January 2022 and March 2022. A short pretested structured interviewer-administered survey questionnaire was used. Data from a total of 5324 patients were analyzed using SPSS (version 26).

Results:

Of all, 92% of patients observed fast during Ramadan. The mean age of the patients was 52.30 ± 11.26 (standard deviation) years and more than half were aged between 41 and 60 years. Those who did not fast were significantly older (P = 0.005). Approximately 51% were male and no sex difference exists in relation to fasting. The median duration of disease was 7 (0–65) years and those with longer duration were less likely to fast (P = 0.001). Among the diabetic patients, 54.5% had comorbidities and proportionately lower number of comorbid patients fasted (P = 0.006). 20.2% and 19.5% of patients experienced reduced and increased blood glucose level, respectively. Those who experienced such events were less likely to fast (P < 0.001). More than three-quarter of patients (77.2%) underwent checkup before Ramadan and 71.8% consulted doctors to modify their prescribed medicines before fasting has started. Nearly one-quarter of patients (24.8%) incorrectly believed that pricking their finger would break the fast (P < 0.001). Approximately 68% of patients believed that fasting will help them to control blood sugar. Nearly three-fourth (73.9%) of the participants believed they can fast in all days in the coming Ramadan.

Conclusions:

This study observed that a significant portion of Muslim adults with diabetes mellitus in Bangladesh tend to fast during Ramadan. Factors such as age, disease duration, and comorbidities influence their fasting behavior, whereas many of them believe fasting aids in blood sugar control and consult healthcare professionals to adjust medications.
Identifying Trends in Oncology Research through a Bibliographic Analysis of Cancer Research and Treatment
Authors: Lee Choong-kun , Choo Jeong Min , Ahn Yong Chan , Kim Jin , Rha Sun Young , Rim Chai Hong ,   On behalf of the 50th Anniversary Committee of the Korean Cancer Association
Published: December 2024

During the celebration of the 50th anniversary of the founding of the Korean Cancer Association, articles published in Cancer Research and Treatment from 2004 to 2023 were assessed based on the subject and design of each study. Based on this analysis, trends in domestic cancer research were inferred and directions were suggested for the future development of Cancer Research and Treatment.
Epsilon-regularity for almost-minimizers of anisotropic free interface problem with Hölder dependence on the position
Authors: Esposito Luca , Lamberti Lorenzo , Pisante Giovanni
Published: December 2024

We establish an

\varepsilon

-regularity result for almost-minimizers of a class of variational problems involving both bulk and interface energies. The bulk energy is of Dirichlet type. The surface energy exhibits anisotropic behavior and is defined by means of an ellipsoidal density that is Hölder continuous with respect to the position variable.
Technical Paper for 11
TH
SAE India International Mobility Conference Relevance of Autonomous Vehicles in the Indian Context
Authors: Mishra Adarsh , Mathur Gaurav
Published: December 2024

Autonomous vehicles (AVs) are positioned to revolutionize transportation, by eliminating human intervention through the use of advanced sensors and algorithms, offering improved safety, efficiency, and convenience. In India, where rapid urbanization and traffic congestion present unique challenges, AVs still hold a significant promise. This technical paper discusses the relevance of autonomous vehicles in the Indian context and the challenges that need to be addressed before the widespread adoption of autonomous vehicles in India. These challenges include the lack of infrastructure, concerns regarding road safety, software vulnerabilities, adaptability of change towards autonomous vehicles, and the management of traffic. The paper also highlights the government's initiatives to encourage the development and adoption of autonomous vehicles, ideology behind the legal framework and the required changes in terms of technological advancements, and urban planning. In a brief manner, this paper tends to mark up the factors impacting the economic and environmental aspects. The aim of this technical paper is to discuss about the adaptability of autonomous vehicles on Indian roads. Our vision for India incorporates autonomous vehicles (AVs) within a comprehensive mobility ecosystem. By seamlessly integrating AVs with public transportation and addressing last-mile connectivity, India has the opportunity to revolutionize its urban mobility while prioritizing inclusivity and sustainability. The paper concludes that while the adoption of autonomous vehicles in India faces significant challenges, the country's vast potential for road travel and the growing demand for sustainable transportation solutions make it a promising market for autonomous vehicles.
Multiple Pathways to Decarbonize India PV Sector
Authors: Sarna Nishant , Jaiswal Harsh , Rani Abha , Dwivedi Vipin , Vashisth Ajay , Bhat Anoop
Published: December 2024

The cumulative accumulation of greenhouse gases (GHGs) historically has resulted in the current problem of global warming. This is further compounded by developed nations, therefore, to fill this gap enhanced global actions are decided. Considering Country’s development need, available resources, government boost for agriculture, A holistic approach for 4W PVs is taken considering well to wheel emissions, as there are other ways to reduce tank to wheel emissions but may not be very effective for overall country’s GHG reduction. Major emissions in vehicle use are calculated based on Carbon intensity of various fuels & optimum pathway for Indian scenario is prepared & discussed in the paper considering all aspects CO2 reduction, development & motorization need. This paper explains multiple pathways for Passenger Vehicle (PV) Sector to be considered to meet country’s GHG needs.
Sustainable Storage & Transition from CNG to Hydrogen
Authors: Vora Kamalkishore Chhaganlal , Parasumanna Ajeet Babu Kumar , Shembekar Prashant Sharad
Published: December 2024

As the world becomes more environmentally conscious, a sustainable transition from Compressed Natural Gas (CNG) to a hydrogen economy is desirable. Hydrogen is a clean and abundant fuel that has the potential to replace fossil fuels and eliminate greenhouse gas emissions. This paper analyses the status of the hydrogen economy and the policies and incentives that government is implementing to promote its adoption, storage, dispensing and usage. The feasibility of a transition from CNG to a hydrogen economy through HCNG and the challenges that need to be overcome are explored. The paper discusses the advantages and disadvantages of CNG, HCNG and hydrogen and compares the fuels in terms of energy efficiency, infrastructure requirements and environmental impact.

Efforts have been made to develop Hydrogen storage cylinder (Type IV) to store hydrogen gas at high pressures, typically around 350 to 700 bar (5,000 to 10,000 psi), to ensure a sufficient range for the vehicle and ensure no risk against Hydrogen Embrittlement. The traditional approach to testing Type IV cylinders at pressures of 700 bar (and sometimes 1400 bar for a Factor of Safety 2) and under various environmental conditions is both expensive and time-consuming due to the lack of adequate facilities in India. To address this challenge, a novel test methodology leveraging the principles of Integrated Computational Materials Engineering (ICME) has been developed. This approach employs digital twin technology to simulate and analyse the performance of Type IV cylinders under conditions such as impact, extreme temperatures, and varying humidity levels. Burst pressure testing, a critical aspect of cylinder validation, is also incorporated into the simulation framework. The results of this study demonstrate a strong correlation between the simulated burst pressure and the outcomes of actual burst pressure tests. The test was carried out upto 700 bar successfully.