The increasing complexity of modern networks has amplified the challenges associated with ensuring robust and scalable security. With the rapid evolution of cyber threats, traditional methods of network security management are often inadequate, leading to inefficiencies and vulnerabilities. Automation has emerged as a transformative approach to streamline network operations, enhance security postures, and reduce the margin of human error. This study explores the integration of Ansible, a powerful open-source automation tool, into network security workflows to deliver a (...) comprehensive framework for secure network automation. This research begins by examining the limitations of conventional network security management, emphasizing the time-intensive and error-prone nature of manual configurations. It highlights how automation, specifically using Ansible, addresses these issues by enabling consistent, repeatable, and scalable processes. Ansible’s ability to seamlessly integrate with diverse networking devices and platforms makes it an ideal choice for automating complex network environments. The methodology involves the development of automated playbooks for various security tasks, including firewall rule management, vulnerability scanning, configuration compliance checks, and incident response. By leveraging Ansible's declarative language, these playbooks are designed to be user-friendly and adaptable, ensuring ease of deployment across networks of varying sizes and complexities. The study also incorporates real-world use cases to demonstrate the tool's effectiveness in mitigating security risks while significantly reducing administrative overhead. Furthermore, the paper evaluates the impact of automation on key performance metrics such as response time to security incidents, accuracy of configurations, and overall system uptime. The findings indicate that integrating Ansible into network security workflows not only enhances operational efficiency but also fortifies security by minimizing misconfigurations and improving threat response times. These results underscore the importance of adopting automation as a critical component of modern network security strategies. In addition to technical insights, the study addresses potential challenges, such as initial implementation costs, skill gaps, and the need for continuous updates to automation scripts to align with evolving security requirements. It provides recommendations for organizations to overcome these obstacles, including investing in employee training and adopting iterative implementation strategies. The research concludes by affirming the transformative potential of automation tools like Ansible in revolutionizing network security management. By reducing reliance on manual processes, organizations can focus their efforts on proactive threat hunting and strategic planning, thereby fostering a more resilient security infrastructure. This paper serves as a comprehensive guide for network administrators and IT professionals seeking to leverage Ansible for secure network automation, providing both theoretical insights and practical solutions to enhance network security in an increasingly dynamic cyber landscape. (shrink)

We introduce the Bias Network Approach (BNA) as a sociotechnical method for AI developers to identify, map, and relate biases across the AI development process. This approach addresses the limitations of what we call the "isolationist approach to AI bias," a trend in AI literature where biases are seen as separate occurrence linked to specific stages in an AI pipeline. Dealing with these multiple biases can trigger a sense of excessive overload in managing each potential bias individually or promote (...) the adoption of an uncritical approach to understanding the influence of biases in developers’ decision-making. The BNA fosters dialogue and a critical stance among developers, guided by external experts, using graphical representations to depict biased connections. To test the BNA, we conducted a pilot case study on the "waiting list” project, involving a small AI developer team creating a healthcare waiting list NPL model in Chile. The analysis showed promising findings: (i) the BNA aids in visualizing interconnected biases and their impacts, facilitating ethical reflection in a more accessible way; (ii) it promotes transparency in decision-making throughout AI development; and (iii) more focus is necessary on professional biases and material limitations as sources of bias in AI development. (shrink)

This Open Access book explains the philosophy, design principles, and community organization of Decidim and provides essential insights into how the platform works. Decidim is the world leading digital infrastructure for participatory democracy, built entirely and collaboratively as free software, and used by more than 500 institutions with over three million users worldwide. -/- The platform allows any organization (government, association, university, NGO, neighbourhood, or cooperative) to support multitudinous processes of participatory democracy. In a context dominated by corporate-owned digital platforms, (...) in the era of increasing social structuring via Artificial Intelligence, Decidim stands as a public or community owned platform for collective human intelligence. Yet, the project is much more than its technological features. Decidim is in itself a crossroad of the various dimensions of the networked society, a detailed practical map of its complexities and conflicts. Theauthors distinguish three general dimensions of the project: (1) the political - shedding light on the democratic model that Decidim promotes and its impact on public policies and organizations, (2) the technopolitical - explaining how this technology is democratically designed and managed to produce and protect certain political effects, and (3) the technical - presenting the conditions of production, operation, and success of the project. This book systematically covers those three levels in an academically sound, technologically consistent, and politically innovative manner. Serving as a useful resource and handbook for the use of Decidim, it will not only appeal to students and scholars interested in participatory and digital democracy but also to professionals, policy-makers, and a wider audience interested in learning more about the Decidim platform. (shrink)

In the era of data-driven enterprises, efficient and reliable storage networking is paramount for ensuring seamless data access and management. Cisco MDS Fabric Switches have emerged as a cornerstone in modern storage networking, offering robust performance, scalability, and advanced features tailored to meet the demands of diverse enterprise environments. This research article provides an in-depth exploration of Cisco MDS Fabric Switches, examining their architectural design, core components, and integration capabilities within storage networks. Through a comprehensive methodology that includes data collection, (...) preprocessing, feature engineering, and machine learning model training, the study evaluates the performance and reliability of these switches in real-world scenarios. The implementation workflow outlines the initial setup, sentiment analysis for user feedback, automated response generation, and real-time transaction verification, ensuring a holistic assessment of the switches’ operational efficacy. Results indicate significant improvements in data throughput, reduced latency, and enhanced user satisfaction, positioning Cisco MDS Fabric Switches as a superior choice for enterprise storage solutions. The discussion highlights the advantages of adopting Cisco MDS Fabric Switches, addresses potential limitations, and outlines the challenges faced during integration. Conclusively, this guide serves as an essential resource for IT professionals and storage network architects seeking to optimize their storage infrastructure through informed decision-making and strategic deployment of Cisco MDS Fabric Switches. (shrink)

This mixed methods study investigates whether technology mediated collaborative practices during a professional development (PD) session led to growth in the collective efficacy of 21 special education teachers at an independent 1-12 school in Southeastern Virginia. This school specializes in individualized instruction for students with learning differences not limited to Autism Spectrum Disorder, Attention Deficit Hyperactivity Disorder, Specific Learning Disability, and their comorbidities. Teacher collective efficacy, which subsumes cohesive perceptions of classroom learning and behavior management, has been shown as (...) strongly related to student achievement and healthy school culture. Mastery experiences with specific tasks related to teaching and learning can spur collective efficacy. Cutting-edge technologies (Vibe and Newline collaborative all-in-one hardware and software interfaces) were used to engage teachers in an interdisciplinary vision boarding activity to outline academic, social, and technological goals within and across subject areas. Teachers also engaged in a behavior management reflection exercise. Pre- and post-survey analysis was conducted using a paired samples t-test, showing overall growth in collective efficacy after the brief PD session. Regression analyses revealed that technology savvy teachers grew most in collective efficacy. Network analysis of vision board output and a descriptive analysis of the behavior management surveys showed that teachers became united in interdisciplinary goals for learning, and in strategies for behavior management through conversational practices. (shrink)

Modernizing workflows is imperative to address labor-intensive tasks that hinder productivity and efficiency. Convolutional Neural Networks (CNNs), a prominent technique in Artificial Intelligence, offer transformative potential for automating complex processes and streamlining operations. This study explores the application of CNNs in building accurate classification models for diverse datasets, demonstrating their ability to significantly enhance decision-making processes and operational efficiency. By leveraging a dataset of images, an optimized CNN model has been developed, showcasing high accuracy and reliability in classification tasks. The (...) findings underscore the ability of AI-powered approaches to reduce manual efforts, improve productivity, and support sustainable modernization across various domains. This study is relevant to professionals seeking to embed AI solutions into conventional workflows, offering a pathway to enhanced innovation and efficiency. (shrink)

In 2024, the convergence of AI-driven operations (AIOps), intent-based networking (IBN), and cloud- native infrastructure gave rise to autonomous cloud networking—a paradigm where networks adapt, secure, and optimize themselves with minimal human intervention. This research explores the design and deployment of self- managing networks across hybrid and multi-cloud environments. It investigates how AI/ML models are integrated into network control planes to enable predictive fault detection, adaptive traffic engineering, and dynamic policy enforcement. Using a survey of IT professionals and cloud (...) architects, this study captures industry readiness, adoption barriers, and expectations surrounding autonomous networking technologies. It also examines architectural challenges, including observability, configuration drift, and real-time compliance. Through statistical analysis, the paper identifies the maturity level of autonomous networking deployments and proposes an architectural blueprint to guide implementation. (shrink)

In an era of increasing cyber threats, ethical hacking has emerged as a pivotal practice in strengthening network security. Ethical hacking, also known as penetration testing, involves authorized attempts to breach a network or system to uncover vulnerabilities before malicious actors can exploit them. This research paper delves into the role of ethical hacking in assessing and mitigating network vulnerabilities to fortify defenses against cyberattacks. It emphasizes the strategic importance of ethical hacking in the context of evolving (...) cybersecurity challenges and explores its practical application in organizational security frameworks. The study begins by defining ethical hacking and its ethical and legal boundaries, distinguishing it from malicious hacking activities. It examines the methodologies and tools used by ethical hackers to identify vulnerabilities, simulate attacks, and provide actionable recommendations for remediation. By mimicking the tactics of cybercriminals, ethical hackers play a critical role in uncovering weaknesses in network configurations, software applications, and hardware systems. A core focus of the research is on the importance of integrating ethical hacking into a proactive cybersecurity strategy. The paper highlights how ethical hacking helps organizations stay ahead of potential threats by identifying vulnerabilities in real time and enabling swift mitigation. Case studies from various industries, such as healthcare, finance, and technology, are analyzed to demonstrate the tangible benefits of ethical hacking in preventing data breaches, minimizing downtime, and safeguarding sensitive information. The paper also explores the challenges associated with ethical hacking, including the need for skilled professionals, the potential for system disruptions during testing, and the importance of maintaining strict compliance with legal and regulatory standards. It discusses the ethical implications of penetration testing, particularly in balancing the need for security with respect for privacy and data protection. Advancements in tools and techniques used by ethical hackers are another significant aspect of this research. The paper investigates the use of artificial intelligence (AI) and machine learning (ML) to enhance vulnerability detection and streamline testing processes. It also addresses the rise of automated penetration testing tools and their role in increasing the efficiency and accuracy of ethical hacking efforts. The findings of this research underscore the necessity of ethical hacking as an essential component of modern cybersecurity frameworks. Organizations that adopt ethical hacking as part of their security strategy gain valuable insights into their vulnerabilities and can build resilient defenses against an everevolving threat landscape. By fostering a culture of continuous testing and improvement, ethical hacking contributes to the creation of a robust and secure network environment. This paper aims to serve as a comprehensive resource for cybersecurity professionals, IT managers, and policymakers, offering insights into the best practices, tools, and techniques of ethical hacking. By leveraging the principles of ethical hacking, organizations can effectively assess vulnerabilities, enhance their security posture, and protect critical assets in the face of mounting cyber threats. (shrink)

As organizations increasingly adopt cloud computing to enhance scalability, efficiency, and costeffectiveness, securing cloud-based applications and data storage has become a paramount concern. This shift has redefined the role of network engineers, who are now at the forefront of implementing and managing secure cloud infrastructures. This research paper examines the critical responsibilities of network engineers in safeguarding cloud environments, focusing on the challenges, strategies, and tools they employ to mitigate risks and ensure data integrity. The paper identifies key (...) challenges associated with cloud security, including data breaches, misconfigured systems, insecure interfaces, and insider threats. These vulnerabilities are further exacerbated by the dynamic and decentralized nature of cloud ecosystems, which often involve multi-tenant architectures and complex integrations. The study underscores the need for network engineers to adapt to these complexities by acquiring specialized skills in cloud security protocols and emerging technologies. A significant focus is placed on the implementation of robust network security frameworks, such as zero-trust architecture, which emphasizes the principle of "never trust, always verify." Network engineers play a crucial role in deploying access control measures, encryption mechanisms, and intrusion detection systems to safeguard sensitive data. Additionally, the research highlights the importance of continuous monitoring and threat intelligence to identify and address vulnerabilities proactively. The integration of automation and artificial intelligence (AI) in cloud security is another critical area explored in this study. Automation tools enable network engineers to streamline routine tasks, such as patch management and configuration audits, thereby reducing human error and response time. AI-driven solutions, on the other hand, enhance threat detection capabilities by analyzing large datasets for anomalous patterns and potential attacks. The paper also discusses the collaborative responsibilities of network engineers, who must work closely with developers, cloud providers, and organizational stakeholders to align security measures with business objectives. This includes implementing secure DevOps practices, ensuring compliance with industry regulations, and conducting regular security audits. Case studies of successful cloud security implementations are presented to illustrate the effectiveness of these collaborative approaches. In conclusion, this research emphasizes the evolving role of network engineers as pivotal defenders of cloud-based systems. It calls for continuous professional development to stay abreast of emerging threats and technologies, as well as fostering a culture of shared responsibility for security within organizations. By adopting a proactive and comprehensive approach, network engineers can significantly enhance the resilience of cloud infrastructures, ensuring the confidentiality, integrity, and availability of critical data and applications. This study aims to provide actionable insights and a strategic framework for network engineers and organizations striving to navigate the complexities of securing cloud environments. Through a combination of technological expertise, innovative tools, and collaborative practices, network engineers are positioned to address the unique challenges posed by cloud computing and play a central role in shaping the future of secure digital ecosystems. (shrink)

Recreational Drugs European Network (ReDNet) project aims to use the Psychonaut Web Mapping Project database (Psychonaut Web Mapping Group, 2009) containing novel psychoactive compounds usually not mentioned in the scientific literature and thus unknown to clinicians as a unique source of information. The database will be used to develop an integrated ICT prevention approach targeted at vulnerable individuals and focused on novel synthetic and herbal compounds and combinations. Particular care will be taken in keeping the health professionals working directly (...) with young people showing problematic behaviors regularly updated in terms of novel compounds and combinations as well. A user-friendly project website will be developed aimed primarily at delivering the information/prevention approaches, but will also be a way of communicating with project partners and relevant stakeholders (e.g. thematic forum facilities, instant messages, blogs, video chat, wikiblog, newsletters distributed via mailing list). The website will support various ICT prevention tools, including an SMS alert service. Different areas and sections will be aimed specifically at the different target groups. -/- . (shrink)

The Internet has revolutionized the way knowledge is currently produced, stored and disseminated. A few finger clicks on a keyboard can save time and many hours of search in libraries or shopping in stores. Online trademarks with an prefix such as e-library, e-business, e-health etc., are increasingly part of our daily professional vocabularies. However, the Internet has also produced multiple negative side effects, ranging from an unhealthy dependency to a dehumanization of human relationships. Fraudulent, unethical and scam practices are (...) also flourishing through for example misleading online advertising methods. Some social and professional networks gather users’ profiles for selling and advertising purposes, sometimes by making it technically difficult to unsubscribe. Here, I discuss some of these unethical aspects and propose some potential solutions to reduce them. (shrink)

Abstract: Heart attacks, or myocardial infarctions, are a leading cause of mortality worldwide. Early prediction and accurate analysis of potential risk factors play a crucial role in preventing heart attacks and improving patient outcomes. In this study, we conduct a comprehensive review of datasets related to heart attack analysis and prediction. We begin by examining the various types of datasets available for heart attack research, encompassing clinical, demographic, and physiological data. These datasets originate from diverse sources, including hospitals, research institutions, (...) and public health agencies. Our analysis aims to identify common features, data quality, and potential biases in these datasets. Next, we explore the predictive modeling techniques employed in heart attack prediction. Machine learning algorithms, such as decision trees, support vector machines, and deep neural networks, have gained prominence in predicting heart attacks. We discuss the strengths and limitations of these methods and highlight recent advancements in predictive modeling. Furthermore, we delve into the critical risk factors associated with heart attacks. Factors such as age, gender, hypertension, diabetes, and cholesterol levels are examined for their significance in predicting cardiac events. We also investigate the role of lifestyle factors, including smoking, diet, and physical activity, in heart attack risk assessment. Additionally, this review addresses the importance of data preprocessing and feature engineering in improving prediction accuracy. Feature selection methods, missing data handling, and data scaling techniques are discussed to enhance the robustness of heart attack prediction models. In conclusion, this comprehensive dataset review provides valuable insights into the state of heart attack analysis and prediction. It serves as a resource for researchers and healthcare professionals seeking to better understand the datasets available for heart attack research and the methods employed for accurate prediction. Ultimately, our efforts in dataset analysis and predictive modeling contribute to the advancement of preventive cardiology and the reduction of heart attack-related morbidity and mortality. (shrink)

In this paper, we propose a new hybrid neutrosophic multi criteria decision making (MCDM) framework that employs a collection of neutrosophic analytical network process (ANP), and order preference by similarity to ideal solution (TOPSIS) under bipolar neutrosophic numbers. The MCDM framework is applied for chief executive officer (CEO) selection in a case study at the Elsewedy Electric Group, Egypt. The proposed approach allows us to assemble individual evaluations of the decision makers and therefore perform accurate personnel selection. The outcomes (...) of the proposed method are compared with those of the related works such as weight sum model (WSM), weight product model (WPM), analytical hierarchy process (AHP), multiobjective optimization based on simple ratio analysis (MOORA) and ANP methods to prove and validate the results. (shrink)

The International Network of Critical Studies of Tourism, Territory and Self-Determination invites to the: -/- III International Meeting of REESCRITA Research Network Reflections for a Sustainable and Inclusive Tourism -/- to be held from January 29th to February 2nd, 2024 at the facilities of the Monterrey Institute of Technology and Higher Education, Campus Cuernavaca -/- Purposes To analyze the current situation of tourism and territoriality studies, in governmental, legislative, business and social sectors; To identify theoretical and methodological contributions (...) and empirical research results of specialists in various disciplines that converge around tourism studies, such as Anthropology, Organizational Sciences, Legal Sciences, Political Science, Communication, Demography, Economy, Geography, History, Social Psychology, International Relations and Sociology, as well as interdisciplinary areas that imply a vision of sustainability around territory and tourism, such as water, education, environment and sustainability, public health, social work, among others; To publicize research results FOR understanding tourism and its implications in community life, territoriality and environment. -/- Topics: Tourism from the community perspective Governance, territory and sustainability Tourism and health International perspectives for sustainable tourism -/- Participants Researchers Teachers Tourism professionals Public and private institutions related to tourism Academic institutions. (shrink)

This study seeks to explore Israeli senior teacher educators’ retrospective interpretations of their early career experiences, while addressing a special emphasis on cultural and contextual characteristics of the academic colleges of education (ACEs). In order to study in depth the attraction factors of career choices among teacher educators, who have outstanding academic skills and background in university teaching, 10 semi-structured interviews were conducted. The findings pointed to the 'balancing between different fields of work' as a major attraction in choosing both (...) the profession and the academic home among teacher educators. Moreover, three balancing points of utmost importance in career choices are identified as significant: a balance between theory and practice toward educational change; a balance between self-worth and production-based worth; and a balance between social relevance and professional networks. The study concludes with a handful of recommendations for ACE administrators on the strategies of recruiting and retaining new teacher educators with impressive academic achievement. (shrink)

In this comprehensive exploration of Artificial Intelligence, The AI Renaissance: Innovations, Ethics, and the Future of Intelligent Systems takes readers on a captivating journey through the foundations, applications, and ethical dimensions of this groundbreaking technology. Divided into three insightful parts, the book begins with a deep dive into the evolution of AI, from early symbolic intelligence to the rise of deep learning, and examines the intersection of neuroscience and artificial general intelligence (AGI). Part two highlights AI’s transformative role across various (...) industries, from fintech to cybersecurity. Explore how AI is revolutionizing finance through fraud detection, automated trading, and personalized financial services. Dive into the world of computer networking, where AI is optimizing connectivity, enhancing predictive maintenance, and enabling ultra-fast 5G networks. Learn how AI is strengthening cybersecurity defenses with cutting-edge threat detection, automated responses, and advanced security policies. The final section delves into the critical discussions surrounding AI’s ethical, social, and philosophical challenges, such as algorithmic bias, human-AI collaboration, and the potential future of AGI. With speculation on the role of quantum computing and the ethical landscape ahead, this book offers a thorough, thought-provoking analysis of how AI will shape our world in the years to come. Ideal for anyone interested in understanding the current state and future potential of AI, this Book is a must-read for technology enthusiasts, industry professionals, and thinkers concerned with the intersection of innovation and ethics. (shrink)

We propose a qualitatively new kind of governance for the emerging need to efficiently guide the densely interconnected, ever more complex world development, which is based on explicit and openly presented problem solutions and their interactive implementation practice within the versatile, but unified professional analysis of complex real-world dynamics, involving both the powerful central units and the attached creative worldwide network of professional representatives. We provide fundamental and rigorous scientific arguments in favour of introduction of just that (...) kind of governance at the modern development stage, after the complexity threshold in the real world dynamics evolution (sometimes intuitively designated as "globalisation"), where the traditional spontaneous-empirical kind of development and related administrative governance lose dramatically and inevitably their efficiency and the necessity of explicit consistent understanding and guidance of complex real-world dynamics becomes evident. (shrink)

This article presents a comprehensive framework for building a strong foundation in blockchain technology and data analytics, two rapidly evolving fields that are increasingly intertwined in today's digital landscape. We propose a structured approach that combines theoretical knowledge acquisition with practical skill development, designed to equip aspiring professionals with the necessary tools to succeed in this dynamic sector. The framework encompasses key areas such as blockchain fundamentals, smart contracts, cryptography, data analysis techniques, and advanced machine learning concepts including neural networks, (...) deep learning, and artificial intelligence. We emphasize the importance of leveraging diverse educational resources while highlighting the critical role of hands-on projects in reinforcing learning outcomes. By detailing strategies for developing blockchain applications and conducting advanced data analytics, this article bridges the gap between academic understanding and practical application. We explore real-world use cases demonstrating the synergy between blockchain and AI in areas such as financial crime prevention, supply chain management, and healthcare. Our findings suggest that this integrated approach not only enhances technical proficiency but also cultivates the problem-solving and analytical skills essential for advancing towards professional roles in blockchain and data analytics. This research contributes to the growing body of literature on technology education and provides a roadmap for individuals seeking to establish a robust foundation in these interconnected fields. (shrink)

How the Profit Motive Influences Media’s Role in Politics and Product Innovation -/- Introduction -/- Media plays a crucial role in shaping public opinion, influencing political discourse, and driving consumer behavior. Ideally, journalism should serve as a watchdog, holding power accountable and informing the public with accurate, unbiased information. Similarly, the media’s role in promoting products should focus on genuine innovation that benefits society. However, the profit motive has significantly altered these dynamics. Instead of prioritizing public welfare, media institutions often (...) focus on financial gain, leading to political bias, misinformation, and consumer culture driven by unnecessary product upgrades rather than true innovation. -/- Despite these challenges, the profit motive remains essential in sustaining economic growth, creating jobs, and driving technological progress. Businesses, including media and technology firms, must continue to generate profit to support their employees, invest in innovation, and maintain financial stability. This essay explores how media’s pursuit of profit has shaped politics and product innovation—sometimes leading to manipulation and overconsumption—while also highlighting the necessity of profit for economic stability and job creation. -/- The Profit Motive In Political Influence -/- Media companies operate as businesses, and their financial survival depends on maximizing profits. This has led to the prioritization of sensationalism, bias, and political influence over objective journalism. -/- 1. Sensationalism and Misinformation -/- To attract more viewers, readers, and online engagement, media companies rely on dramatic headlines, fear-mongering, and emotionally charged content. Instead of presenting balanced perspectives, media outlets choose narratives that generate more engagement, regardless of accuracy. -/- Example: During election cycles, media outlets often focus on scandals and controversies rather than discussing real policy issues. In the 2016 U.S. presidential election, much of the media coverage fixated on the “Clinton emails” rather than substantive discussions about economic policy, healthcare, or climate change. -/- 2. Corporate Ownership and Political Bias -/- Many mainstream media companies are owned by large corporations with vested interests in certain political outcomes. This ownership structure influences editorial decisions, leading to biased reporting that serves corporate and elite interests rather than public welfare. -/- Example: Billionaire-owned media companies, such as The Washington Post (owned by Jeff Bezos) and Fox News (controlled by Rupert Murdoch), have been accused of pushing narratives that align with their owners' political and business interests. -/- 3. Political Advertising and Pay-to-Play Journalism -/- Political campaigns and corporations pay large sums to media companies for favorable coverage. This financial dependency can lead to biased reporting or the suppression of critical stories. -/- Example: In the Philippines, politicians often use paid news segments and political ads disguised as news reports, creating the illusion of widespread public support while suppressing dissenting voices. -/- 4. Media-Driven Political Polarization -/- To maximize audience loyalty, many media organizations take strong partisan positions, reinforcing ideological divisions. This leads to echo chambers where people only consume content that aligns with their preexisting beliefs, further polarizing society. -/- Example: In the U.S., Fox News caters primarily to conservative audiences, while MSNBC leans toward liberal perspectives. This divide reinforces political tribalism, making constructive dialogue difficult. -/- The Profit Motive In Product Innovation -/- Beyond politics, media also plays a significant role in shaping consumer behavior and perceptions of innovation. While technological advancements and new products can improve lives, media-driven marketing often prioritizes unnecessary upgrades and exaggerated benefits over true innovation. -/- 1. The Role of Media in Shaping Consumer Demand -/- Since advertising revenue is a primary income source for most media companies, they prioritize content that appeals to advertisers rather than educating or informing the public. this leads to an emphasis on promoting new products, sometimes regardless of their necessity or actual innovation. -/- Example: Tech companies use media partnerships to generate excitement about new product releases, even when the changes are minimal. A major smartphone manufacturer, for instance, may introduce minor camera improvements or design tweaks and market them as groundbreaking innovations. -/- 2. Social Media and Influencer-Driven Product Hype -/- The rise of social media has intensified product marketing, making influencers a key force in driving demand. Many influencers, backed by corporate sponsors, promote products without critically evaluating their real impact or necessity. -/- Example: Luxury brands and smartphone companies pay influencers to showcase their products as status symbols. This creates an artificial perception of exclusivity and necessity, leading consumers to purchase items they might not truly need. -/- 3. The Illusion of Innovation Through Frequent Upgrades -/- Many industries, particularly technology and fashion, rely on planned obsolescence—introducing frequent but minor updates to create the illusion of innovation. This strategy encourages consumers to upgrade their products regularly, even when older models remain functional. -/- Example: A leading electronics company releases new smartphone models annually, often with only minor feature enhancements. Many devices slow down over time due to software updates, subtly pressuring users to replace their devices sooner than necessary. -/- 4. Psychological Manipulation in Advertising -/- Media uses psychological tactics to influence consumer behavior. Limited-time offers, aspirational advertising, and fear-based marketing create artificial demand for new products. -/- Example: Beauty magazines and social media ads promote anti-aging products by associating youth with success and attractiveness. This fosters insecurity, encouraging unnecessary spending on skincare and cosmetic treatments. -/- Why the Profit Motive Must Continue -/- Despite these challenges, the profit motive remains essential to economic stability, job creation, and continuous innovation. Businesses, including media companies, rely on profits to sustain their operations and support employees. -/- 1. Job Creation and Economic Growth -/- Profitable businesses provide stable employment, allowing workers to earn wages, support their families, and contribute to economic growth. Media companies, for example, employ journalists, editors, graphic designers, marketers, and IT professionals. The same is true for product innovation, where research and development teams, factory workers, and sales professionals all benefit from profitable enterprises. -/- Example: The global tech industry supports millions of jobs, from engineers developing new products to retail workers selling them. Without profit incentives, companies would have little motivation to expand, invest, and hire more employees. -/- 2. Funding for Innovation and Technological Advancements -/- Profit enables companies to invest in research and development, leading to technological breakthroughs that improve quality of life. Whether in medicine, transportation, or communication, businesses reinvest earnings into innovation that benefits society. -/- Example: The telecommunications industry continually advances due to profits that fund research into faster internet speeds, better security features, and more efficient network infrastructure. -/- 3. Stability and Business Sustainability -/- Without profit, businesses cannot survive in the long term. Media companies, for instance, require revenue to pay journalists and produce high-quality content. Similarly, manufacturers must generate income to continue developing new products. A balanced approach—where profitability coexists with ethical responsibility—ensures economic stability while minimizing harm. -/- Conclusion -/- The profit motive has significantly shaped the media’s role in both politics and product innovation. While it sometimes leads to sensationalism, misinformation, and excessive consumerism, it remains essential for job creation, economic stability, and technological progress. The key challenge is finding a balance—ensuring that media and businesses remain profitable while also prioritizing truth, sustainability, and genuine innovation. Addressing these issues requires policy reforms, media literacy education, and a shift toward more responsible journalism and marketing practices. By fostering ethical profit-driven growth, society can benefit from stable incomes, continuous innovation, and an informed public. -/- . (shrink)

This chapter explores Nagel’s polemics. It shows these have a two-fold character: (i) to defend liberal civilization against all kinds of enemies. And (ii) to defend what he calls ‘contextual naturalism.’ And the chapter shows that (i-ii) reinforce each other and undermine alternative political and philosophical programs. The chapter’s argument responds to an influential argument by George Reisch that Nagel’s professional stance represents a kind of disciplinary retreat from politics. In order to respond to Reisch the relationship between Nagel’s (...) philosophy of science and his politics is explored and this chapter shows how both are anchored in what Nagel once called his ‘contextual naturalism’—a metaphysics that resists imposing the unity of the world and treats all entities as embedded in a wider network of entities. Part of the argument traces out how Nagel’s views on responsible speech and professionalism reflect a distinct understanding of the political role of philosophers of science. (shrink)

The healthcare sector is undergoing a transformative shift towards smart healthcare, driven by advancements in technology, including Artificial Intelligence (AI) and Blockchain. As healthcare systems generate vast amounts of data from multiple sources, such as electronic health records (EHRs), medical imaging, wearable devices, and sensor-based monitoring, the challenge lies in securely integrating and analyzing this data for real-time, actionable insights. Blockchain technology, with its decentralized, immutable, and transparent framework, offers a robust solution for securing data integrity, privacy, and sharing across (...) healthcare networks. AI, on the other hand, enables advanced data analytics, providing healthcare professionals with predictive insights, early diagnosis, and personalized treatment plans. This paper explores the integration of Blockchain and AI for advanced data management in smart healthcare. We propose a system that utilizes Blockchain for secure and transparent data storage, ensuring that healthcare data from various sources is tamper-proof and can be shared across multiple stakeholders. AI algorithms, particularly machine learning and deep learning models, are applied to the integrated data to detect patterns, predict disease progression, and optimize treatment plans. By leveraging Blockchain, healthcare data can be securely shared across providers and patients, ensuring privacy and regulatory compliance, while AI technologies provide the intelligence required for enhancing clinical decision-making. This integrated system not only addresses the growing concerns surrounding data security and privacy but also promotes interoperability and collaboration within the healthcare ecosystem. The paper discusses the challenges, opportunities, and future directions of Blockchain and AI integration in smart healthcare systems, highlighting how this convergence can lead to more efficient, secure, and personalized healthcare services. (shrink)

When information on a coma patient’s expected outcome is uncertain, a moral dilemma arises in clinical practice: if life-sustaining treatment is continued, the patient may survive with unacceptably poor neurological prospects, but if withdrawn a patient who could have recovered may die. Continuous electroencephalogram-monitoring is expected to substantially improve neuroprognostication for patients in coma after cardiac arrest. This raises expectations that decisions whether or not to withdraw will become easier. This paper investigates that expectation, exploring cEEG’s impacts when it becomes (...) part of a socio-technical network in an Intensive Care Unit. Based on observations in two ICUs in the Netherlands and one in the USA that had cEEG implemented for research, we interviewed 25 family members, healthcare professionals, and surviving patients. The analysis focuses on the way patient outcomes are constructed, the kind of decision support these outcomes provide, and how cEEG affects communication between professionals and relatives. We argue that cEEG can take away or decrease the intensity of the dilemma in some cases, while increasing uncertainty for others. It also raises new concerns. Since its actual impacts furthermore hinge on how cEEG is designed and implemented, we end with recommendations for ensuring responsible development and implementation. (shrink)

Philosophy has been a public endeavor since its origins in ancient Greece, India, and China. However, recent years have seen the development of a new type of public philosophy conducted by both academics and non- professionals. The new public philosophy manifests itself in a range of modalities, from the publication of magazines and books for the general public to a variety of initiatives that exploit the power and flexibility of social networks and new media. In this paper we examine the (...) phenomenon of public philosophy in its several facets, and investigate whether and in what sense it is itself a mix of philosophical practice and teaching. We conclude with a number of suggestions to academic colleagues on why and how to foster further growth of public philosophy for the benefit of society at large and of the discipline itself. (shrink)

Abstract The values of the healthcare sector are fairly ubiquitous across the globe, focusing on caring and respect, patient health, excellence in care delivery, and multi-stakeholder collaboration. Many individual pharmacists embrace these core values. But their ability to honor these values is significantly determined by the nature of the system they work in. -/- The paper starts with a model of the prevailing pharmacist workforce model in Scotland, in which core roles are predominantly separated into hierarchically disaggregated jobs focused on (...) one professional ‘pillar’: Clinician /Practice Provider; Educator; Leader/Manager; and Researcher. This is the ‘Atomistic’ Model. This skills-segregation yields a workforce of individuals working in isolation rather than collaborating together, and lacking a shared information flow, purpose and identity. Key strategic flaws include suboptimal responsiveness to population and subpopulation needs, inconsistency and inequity of care, an erosion of professional agency, and lower job satisfaction. It is conjectured that this results from a lack of congruence between values, professional ethos, and organizational structure. ‘Atomism’ culminates in a syndrome of widespread professional-level cognitive dissonance. -/- The paper contrasts this with a new emerging workforce vision, The Collaborative Care Model. This new model defines a systems-first-approach, built on the principle that all jobs must include all four professional ‘pillars’. Vertical skills integration, involving education and task sharing, will support sustainability and succession planning. Horizontal skills integration (across practice, leadership and research) is included to improve responsiveness to population need and individual professional agency. The working conditions, supportive ethos, and career structure needed to make the model work are described. Moral theory and workforce theory are used to justify why the model may be more effective for population health, delivering greater job satisfaction for individuals and ultimately helping systematically realize and honor healthcare values. Finally, the paper sketches the first steps needed to implement the model at the national level, starting with the operationalization of new multi-pillar professional curricula across the career spectrum. Potential pitfalls and challenges are also discussed. -/- Co-Authors: 1. Paul Forsyth (PF) Lead Pharmacist Clinical Cardiology, Pharmacy, NHS Greater Glasgow & Clyde. Contribution: Conceptualization; Model Curation; Model Theory; Model Visualization; Writing - original draft (lead author), Writing - review & editing (lead author) 2. Andrew Radley (AR), Consultant in Public Health Pharmacy, NHS Tayside. Contribution: Conceptualization; Model curation; Model Theory; Writing - review & editing 3. Gordon Rushworth (GR), MPharm MSc FFRPS FRPharmS (Consultant). Programme Director, Highland Pharmacy Education & Research Centre, NHS Highland, Inverness. Contribution: Model curation; Writing - review & editing 4. Fiona Marra (FM) National Lead Clinician Scottish Infection and Immunology Network (SPAIIN) / Advanced Pharmacist HCV / HIV, NHS Greater Glasgow & Clyde. Contribution: Model curation; Writing - review & editing 5. Susan Roberts (SR) Associate Postgraduate Pharmacy Dean, NHS Education for Scotland. Contribution: Model curation; Writing - review & editing 6. Roisin O’Hare (RO) Lead Teacher Practitioner Pharmacist, Northern Ireland University Network, Southern Health and Social Care Trust. Contribution: Model curation; Writing - review & editing 7. Catherine Duggan (CD) Chief Executive Officer, International Pharmaceutical Federation (FIP). Contribution: Model curation; Writing - review & editing 8. Barry Maguire (BM) Senior Lecturer, School of Philosophy, Psychology and Life Sciences, The University of Edinburgh. Contribution: Conceptualization; Model Curation; Model Theory; Model Visualization; Supervision; Writing - original draft (senior academic supervisor), Writing - review & editing (senior academic supervisor) -/- . (shrink)

This chapter explores Nagel’s polemics. It shows these have a two-fold character: to defend liberal civilization against all kinds of enemies. And to defend what he calls ‘contextual naturalism.’ And the chapter shows that reinforce each other and undermine alternative political and philosophical programs. The chapter’s argument responds to an influential argument by George Reisch that Nagel’s professional stance represents a kind of disciplinary retreat from politics. In order to respond to Reisch the relationship between Nagel’s philosophy of science (...) and his politics is explored and this chapter shows how both are anchored in what Nagel once called his ‘contextual naturalism’—a metaphysics that resists imposing the unity of the world and treats all entities as embedded in a wider network of entities. Part of the argument traces out how Nagel’s views on responsible speech and professionalism reflect a distinct understanding of the political role of philosophers of science. (shrink)

The supervision of teachers is essential for ensuring effective teaching methods, ongoing professional growth, and student success. This study explored the experiences of program heads in supervising teachers. It was conducted in a local college in Tangub City, Misamis Occidental. The phenomenological design was used in the study. Eleven program heads served as the participants selected through the purposive sampling technique. The Interview Guide was used as the research instrument. Moustakas' transcendental phenomenology of data analysis was utilized to analyze (...) the data gathered. Results revealed the following main themes: the critical role of supervision in advancing teacher development and educational excellence, mutual learning and growth, the role of program heads in teacher supervision, overcoming challenges in teacher supervision, and effective communication strategies. Supervision improves teaching and learning quality, which supports professional development. The complex nature of supervisory roles requires adaptive strategies and strong support networks. It is recommended for program heads and teachers to establish open communication to help address the challenges encountered during supervision. (shrink)

A number of the men who would become the 9/11 hijackers were stopped for minor traffic violations. They were pulled over by police officers for speeding or caught by random inspection without a driver’s license. For United States government commissions and the press, these brushes with the law were missed opportunities. For some police officers though, they were of personal and professional significance. These officers replayed the incidents of contact with the 19 men, which lay bare the uncertainty of (...) every encounter, whether a traffic stop, or with someone taking photos of a landmark. Representatives from law enforcement began to design policies to include local police in national intelligence, with the idea of capitalizing on what patrol officers already do in dealing with the general public. Several initiatives were launched, among these, the Suspicious Activity Reporting Initiative. Routine reporting of suspicious activity was developed into steps for gathering, assessing and sharing terrorism-related information with a larger law enforcement and intelligence network. Through empirical analysis of counterterrorism efforts and recent scholarship on it, this chapter discusses prevention, preemption, and anticipation as three technologies of security, focusing on how each deals with uncertainty. The Suspicious Activity Reporting Initiative, this analysis suggests, is an anticipatory technology which constitutes police officers and intelligence analysts as subjects who work in a mode of uncertainty. (shrink)

This article investigates the role of television on the structure and organization of political parties in the post – communist Albania. The existing literature on political parties links the structure of mass parties with the written press, and the structure of electoral- professional and cartel parties with the increasing influence of television. The mass party is based on the principle of membership. Among many tasks that members had to carry out, the dissemination of party’s declarations, statements, opinions and ideology, (...) through the distribution of party press is one of the most important. The studies on political parties have observed the emergence of the catch-all, electoral-professional and cartel party, in which the party leaders have substituted the membership organizational network with television, and thus minimized the role of intermediate party organs. In difference from their counterparts in Western Europe, in the new established democracies of post-communist countries, political parties were born in a period characterized by a modern and developed media which was accessible to everyone. Therefore, the immediate access to modern means of communication has distanced the parties from the society since the early phases of their inceptions, without giving them the opportunity and necessity to organize territorially. This article analysed the techniques that have used the Albanian political parties to communicate with their electorate, concluding that in the moment of their creation, television could not serve to the opposition parties as a means of information. That is why they had to rely heavily on the written press and their membership. The opening of some broadcasting channels, after 2000, made possible the access on modern techniques of communication, leading to a minor role of the press and membership. As a result we could say that at the early phase of democratic process, the political parties in Albania shared features of the mass party with a strong territorial penetration, features that started to fade out when television gained a more prominent role in the organization of electoral campaigns by influencing thus a more contemporary western alike model of party organization. (shrink)

This article derives from data collected over a six-month period between February and August 2022. Its sampling pertains to members of two general Twitter Lists of philosophy professionals: “Philosophers on Twitter”, limited to a maximum of 4500 active accounts, and “Philosophers”, restricted to accounts surpassing 1000 followers and currently including over 1,100 individuals. The totality of members of these two Lists is referenced in this article as “Philosophy Twitter”. -/- Data was collected in five principal ways from members of these (...) two Lists: 1) Monitoring the List streams, 2) addressing members, including following, retweeting, liking, endorsing, asking, commenting, and replying, 3) probing members’ Twitter activities in their Profiles (“Tweets & replies”), 4) reviewing members’ Twitter Bios, CVs, professional profiles, and websites, and 5) network analysis of members’ quantitative and qualitative association and interaction profiles. -/- The study of this material aimed at revealing interpersonal social structures and processes of philosophy professionals by their Twitter conduct. Its personal purview focused on creators, teachers, researchers, and students and thus excepted schools, colleges, universities, formal associations, and publishers. Particular attention was given to gaining insights on substantive orientation, cooperation, and constructive dialogue versus hierarchic and tribal characteristics. (shrink)

Every school needs an advocate leader who can influence others to address issues, concerns, and problems that affect education, its quality, access, and the welfare of the stakeholders, especially that of the learners. This leader needs to subscribe to the redefined roles and nature of leadership. Advocacy leadership challenges educational leaders to take a progressive stance on pressing educational issues and problems. The next in line leaders need to awaken in themselves a specific advocacy and tune-in to this new trend. (...) With this, a qualitative inquiry explored the educational advocacies of twenty graduate students involved in focus group discussions and interviews. Using the thematic network as an analytical framework, the inquiry identified 46 keywords, 51 basic themes, and 6 organizing themes. Thus, a new thematic network of educational advocacies was generated. Learners’ welfare was the most dominant educational advocacy of graduate students, while leadership and governance, professional development, culture and religion, safety and environmental protection, and community development were considered as developing and noteworthy advocacies. These educational advocacies were deemed interconnected and interdependent to each other. Also, the study comes up with relevant propositions, while it makes recommendations for further research and utilization of the new framework. The results have implications for revisiting the educational administration curriculum by mapping out the subjects that contribute to the development of educational advocacy. (shrink)

Generative Artificial Intelligence (AI) has emerged as a powerful force at the intersection of technology and imagination, enabling machines to create novel content across diverse domains such as art, music, design, and literature. This technology is shifting the paradigm of creativity, allowing AI systems to not only automate tasks but also contribute to the creative process by generating original content that mirrors or transcends human imagination. Generative models, such as Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Transformer-based models, are (...) at the forefront of this revolution. These models are redefining how creativity is perceived, empowering both professional and amateur creators to explore new creative territories. This paper explores the role of generative AI in creative industries, examining its potential, challenges, and ethical implications. Through case studies and real-world applications, we demonstrate how generative AI is influencing various creative fields and shaping the future of human creativity. (shrink)

How to participate proactively in a process of change and transformation, to shape our path within an uncertain future? With this publication, the State Of The Art Network marks a waypost on a journey which started in 2018, when like-minded Nordic and Baltic art organisations and professionals initiated this network as a multidisciplinary collaboration facing the Anthropocene. Over five years, ten organisations and around 80 practitioners from different disciplines, like the arts, natural sciences and humanities came together, online (...) and in person, for workshops, seminars and discussions. The aim was to find ways to create resilience and concrete actions on how to live through the change in culture, economy and the environment and to find concrete, hands-on methods to deal with the Anthropocene and the environmental crisis. As an outcome of this process, this publication takes a closer look at how we as practising artists, researchers and cultural actors can create elements for critical thinking and doing which can assist us in navigating the complexities of the present. -/- Edited for the State Of The Art Network by Erich Berger, Mari Keski-Korsu, Marietta Radomska and Line Thastum. -/- Produced and published by Bioart Society 2023. (shrink)

This chapter explores the personal and professional obstacles faced by Humanities and Social Science scholars contemplating pre-publication of their scholarly work in an on-line network. Borrowing a theoretical framework from the radical educational theorist Ivan Illich, it also develops the idea that pre-publication networks offer higher education a bottom-up, decentralized alternative to business-modeled e-learning. If learners would only embrace this more anarchical medium, appreciating writing for pre-publication as a process of open-ended discovery rather than product delivery, then the (...) prospect of deinstitutionalizing e-learning could become an exciting new reality. The chapter’s methodology is a combination of normative-theoretical analysis and small sample (n=2) case study based on the author’s personal and professional experiences. While the generalizability (or external validity) of the conclusions is limited, the author hopes to motivate further inquiry into the connection between on-line pre-publication and e-learning. (shrink)

This article reflects on the skills required in trades services to people dedicated to coordinate services in complex clinical situations because of their multidimensionality and chronicity. All human activity requires for its proper effectuation, the coordination of interdependencies between actors. Coordination of interdependencies is done in ordinary mode, in everyday activities, but also in dedicated mode, that is to say, through a practice that has a primary mandate to manage them in a conscious, voluntary and accountable for intervention situations whose (...) complexity is high. This passage from the ordinary form in the form of dedicated coordination undertakes a transformation of skills and professional knowledge mobilized in the professional gesture. Further skills and knowledge relating to the disciplinary control of clinical objects, the case manager or professional figure who best embodies this form of coordination, should mobilize expertise and procedural knowledge (assessment, planning, communication, negotiation, activation networks, etc..) required to control the interfaces between technical systems and professional and organizational actors, posing as the interdependence of actants primary purpose in work. For this he must do it in a time of temporality combining organizational project in clinical time. e présent article réfléchit aux compétences requises dans les métiers de services aux personnes dédiés à coordonner les services dans les situations cliniques complexes en raison de leur multi-dimensionnalité et leur chronicité. Toute activité humaine exige, pour sa bonne effectuation, la coordination des interdépendances entre les acteurs concernés. La coordination des interdépendances se réalise en mode ordinaire, dans les activités de tous les jours, mais aussi en mode dédié, c’est-à-dire à travers une pratique qui a pour mandat principal de les gérer de manière consciente, volontaire et imputable pour les situations d’intervention dont la complexité est grande. Ce passage de la forme ordinaire à la forme dédiée de coordination engage une transformation des compétences et savoirs professionnels mobilisés dans le geste professionnel. En outre des compétences et savoirs relatifs à la maîtrise des objets cliniques disciplinaires, le gestionnaire de cas, soit la figure professionnelle qui incarne le mieux cette modalité de coordination, doit mobiliser des compétences et savoirs procéduraux (évaluation, planification, communication, négociation, activation de réseaux, etc.) requis à la maîtrise des interfaces entre systèmes techniques et acteurs professionnels et organisationnels, en posant l’interdépendance des actants comme objet premier de son action professionnelle. Pour cela, il doit effectuer cette dernière dans une temporalité conjuguant le temps du projet organisationnel au temps clinique. (shrink)

This book is a new scholarly edition of Lincoln Steffensâ classic, â oemuck-rakingâ account of Gilded Age corruption in America. It provides the broader political background, theoretical and historical context needed to better understand the social and political roots of corruption in general terms: the social and moral nature of corruption and reform. Steffens enjoyed the support of a multitude of journalists with first-hand knowledge of their localities. He interviewed and came to know political bosses, crusading district attorneys and indicted (...) corruptionists spanning a cast of hundreds. He also benefited from the support of a large-scale, nationally prominent network of anti-corruption specialists and luminaries, including President Theodore Roosevelt. Steffens explored in detail the high Gilded Age corruption of New York City, Chicago, â oecorrupt and contentedâ Philadelphia, Pittsburgh, St. Louis and Minneapolis. His work culminated in a well-documented record of Gilded Age corruption in the cities; and, with the addition of the editorial annotations, Chronology and Introduction of this edition, the reader is placed in a position to gain an overview and considerable insight into the general, moral and social-political phenomenon of corruption. This book will be of interest for students and professionals in political philosophy, political science, American history and American studies. (shrink)

To improve oneself and grow professionally, career development has been found to be crucial, as it serves as a roadmap for the professional growth of employees. However, a barrier, known as the glass ceiling, hinders the progress of employees, especially those in the LGBTQIA+ community. This study explores the impact of the glass ceiling on the career development of selected LGBTQIA+ individuals, shedding light on the barriers faced by this community in the workplace. The researchers used a qualitative multiple-case (...) study and selected ten (10) LGBTQIA+ participants from large enterprises via the judgmental sampling technique. Through thematic analysis, psychological impact, workplace discomfort, lack of recognition, and career progress challenges emerged as the impacts of the glass ceiling on the participants. Strategies for overcoming glass ceiling barriers, such as resilience, self-reflection, and community support, are identified. Thus, the study found that glass ceilings are really evident in the context of businesses. With this, the proposed advocacy plan in the study suggests interventions like workplace inclusion training, mentorship networks, and seminars on employee rights. Furthermore, it emphasizes the call for ongoing research and advocacy efforts to dismantle barriers and cultivate workplaces that not only embrace diversity but also provide equitable opportunities for career growth. (shrink)

Existing studies show that when Hollywood professionals develop and produce films and television series, they consult experts in social and political issues. These experts may be private individuals or representatives of various governmental, social movement, or research organisations. Drawing on ethnography and interviews, I focus on organisational experts and explore how they provide their expertise to Hollywood. I argue that these organisations form a peculiar social space surrounding Hollywood, which I refer to as ‘the relational space of organisational expertise provision’, (...) which demonstrates some field effects like similar practices and habitus, but does not show overt competition. I argue that the provision of organisational expertise in Hollywood is undertaken by organisational boundary spanners who operate within this relational space through the enactment of expertise networks, the construction of connecting interfaces, and the trading of expertise as short-lived, or proxy, capital. These findings contribute to the Bourdieusian field analysis and sociology of expertise by elucidating how social spaces interact, how social agents gain power through the inter-field exchange of expertise, and what happens in the field of power. (shrink)

Generative Artificial Intelligence (AI) has emerged as a powerful force at the intersection of technology and imagination, enabling machines to create novel content across diverse domains such as art, music, design, and literature. This technology is shifting the paradigm of creativity, allowing AI systems to not only automate tasks but also contribute to the creative process by generating original content that mirrors or transcends human imagination. Generative models, such as Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Transformer-based models, are (...) at the forefront of this revolution. These models are redefining how creativity is perceived, empowering both professional and amateur creators to explore new creative territories. This paper explores the role of generative AI in creative industries, examining its potential, challenges, and ethical implications. Through case studies and real-world applications, we demonstrate how generative AI is influencing various creative fields and shaping the future of human creativity. (shrink)

This study aims to investigate some aspects that contribute to the growing popularity of conspiracy theories in the 21st century. They have gained so much popularity among the public in recent years that an age of conspiracies. Conspiracy theories are increasingly responding to several socially significant events occurring around us, coming up with an alternative explanation, especially for those political, social, tragic, or other events that concern a more significant number of people. Thanks to the rapid expansion of access to (...) the Internet and rapid development in information and communication technologies, systems, and means, conspiracy theories are significantly penetrating the mass media and especially the sphere of new media. Currently, social networks are the medium with the most incredible spread of various conspiracy theories. It is one of the primary reasons why conspiracy theories have become the subject of our scientific interest. Using relevant methods of qualitative theoretical scientific research, in this work, we present our research findings and a view on some selected aspects contributing to the growing popularity of conspiracy theories to readers from the professional and lay public. (shrink)

Integrating medical imaging with computing technologies, such as Artificial Intelligence (AI) and its subsets: Machine learning (ML) and Deep Learning (DL) has advanced into an essential facet of present-day medicine, signaling a pivotal role in diagnostic decision-making and treatment plans (Huang et al., 2023). The significance of medical imaging is escalated by its sustained growth within the realm of modern healthcare (Varoquaux and Cheplygina, 2022). Nevertheless, the ever-increasing volume of medical images compared to the availability of imaging experts. Biomedical experts (...) and radiologists have resulted in a widening disparity, causing an excess and overwhelming workload on these healthcare professionals (Chen et al., 2021). Several studies indicate that the present-day biomedical radiologist is now saddled with the daunting task of interpreting an image almost every 10 seconds to keep pace with the burgeoning clinical demands (McDonald et al., 2015; Hosny et al., 2018; Lantsman et al., 2022). This cognitive drain has invariably led to inevitable consequences such as delays in diagnosis and an amplified risk of diagnostic errors – thus, the biomedical imaging aspect is in dire need of methods that would aid accurate diagnostics and analytics for improved decision making. In this review, the importance of AI-related technologies such as ML and/or DL methods are reviewed in relation to the processing of medical or biomedical images along with their potentials, challenges, and possible suggestions for future studies in the health landscape. The focus will be on machine learning methods associated with the medical field of image classification. (shrink)

Thyroid disorders are common endocrine conditions that affect millions of people worldwide. Accurately identifying these disorders is essential for effective treatment and management. Traditional diagnostic methods, such as laboratory tests and clinical evaluations, are reliable but can be time-consuming and sometimes affected by human error. With advancements in artificial intelligence and machine learning (ML), automated systems are now being developed to improve diagnostic accuracy and efficiency. This study aims to build a machine learning model that classifies thyroid disorders using the (...) thyroidDF.csv dataset. Several ML algorithms, including Random Forest, Artificial Neural Networks (ANN), and XGBoost, are applied to analyze patient data. Various data preprocessing techniques, such as feature selection, data balancing, and hyperparameter tuning, are used to enhance model performance. Among these models, XGBoost performs the best, showing higher accuracy, recall, and precision compared to others. Beyond classification, this research also addresses challenges like data imbalance and the need for model interpretability in medical applications. The proposed system is designed to be practical and reliable for clinical use, helping healthcare professionals make informed decisions for early detection and diagnosis. Future improvements could include expanding the dataset, incorporating explainable AI techniques, and developing real-time monitoring features to further improve accuracy and usability in real-world settings. This report is structured into chapters covering the motivation, methodology, experimental results, and future directions of this research. By integrating AI with medical diagnostics, this study contributes to improving healthcare solutions, enabling more precise diagnoses and better treatment strategies for thyroid disorders. (shrink)

Ear diseases, if not diagnosed and treated promptly, can lead to severe health complications, including chronic pain, infection, and permanent hearing loss. Early detection is crucial to preventing these outcomes and ensuring effective treatment. However, traditional diagnostic methods for ear diseases typically depend on manual examination of the ear by experienced medical professionals using otoscopes. These methods are not only timeconsuming and resource-intensive but can also be highly subjective, often leading to inconsistent or inaccurate diagnoses, especially in under-resourced or remote (...) areas. To address these challenges, this project introduces an automated, deep learning-based system for the detection of ear infections. By leveraging the power of Convolutional Neural Networks (CNNs), the system is capable of analyzing medical images of the ear and classifying them into two categories: Normal or Infected. The approach involves training a CNN model on a labeled dataset of ear images, allowing it to learn complex patterns and features associated with various ear conditions. Once trained, the system can accept new ear images as input, process them through the CNN model, and output a diagnosis within seconds. This not only significantly reduces the time required for diagnosis but also enhances accuracy and consistency, minimizing the risk of human error. The proposed system is designed to support medical professionals by acting as a diagnostic aid, particularly in regions with limited access to specialized healthcare services. Ultimately, this project aims to demonstrate how artificial intelligence and deep learning can be harnessed to improve medical diagnostics, reduce workload for healthcare workers, and contribute to better patient outcomes by facilitating early and accurate detection of ear infections. (shrink)

The study aims to identify the impact of the use of artificial intelligence techniques in improving the outputs of higher education in Business Administrative Colleges in the universities under study that formed the research community. As for the sample, it consisted of (130) academic respondents in these universities under study. The research concluded that there is a statistically significant effect of using artificial intelligence techniques (expert systems, neural networks) in improving the outputs of higher education in Business Administrative Colleges under (...) study. It was found that artificial intelligence technologies contribute to finding graduates who are able to carry out the process of modernization and professional development in various fields of work. These technologies also contribute to improving and developing the skills of graduates in the labor market and providing them with new skills and characteristics to perform their duties. The research recommended increasing interest in the expert systems technology by the universities under study because of its scientific importance in improving the outputs of higher education by reformulating them in the form of programs embraced by computers. (shrink)

Every year, approximately 800,000 people lose their lives to suicide, underscoring the urgent need to identify individuals at risk. With the widespread use of social media, many individuals openly share their thoughts, including expressions of suicidal ideation, providing an opportunity for timely intervention. This study introduces an advanced system for detecting suicidal content on social media platforms using a combination of Natural Language Processing (NLP), Deep Learning, and Machine Learning techniques. The system leverages keyword-based detection, sentiment analysis, and contextual NLP (...) methods to identify posts indicative of suicidal ideation. A hybrid approach is adopted, integrating Logistic regression,Random Forest, Support Vector Machine, Naive Bayes and Artificial Neural Networks (ANNs) to enhance text classification performance and improve detection accuracy. The model is trained on a carefully curated dataset of labeled posts and evaluated using metrics such as precision, recall, and F1-score, demonstrating significant improvements in the accurate detection of concerning content. This automated system is designed for deployment by social media platforms to flag potentially harmful posts, allowing mental health professionals to review and provide timely support. By enhancing early identification and intervention efforts, this system offers a valuable tool for reducing suicide risks and potentially saving lives. In cases where suicidal content is identified, the system prompts the user with a supportive questionnaire, text box, or chatbot interface to offer immediate assistance or guidance. This project contributes to mental health awareness by providing an automated, accurate, and accessible tool for early detection of suicidal ideation, facilitating timely intervention and support. (shrink)

The study of a person existence in Internet space is certainly an actual task, since the Internet is not only a source of innovation, but also the cause of society's transformations and the social and cultural problems that arise in connection with this. Computer network is global. It is used by people of different professions, age, level and nature of education, living around the world and belonging to different cultures. It complicates the problem of developing common standards of behavior, (...) a system of norms and rules that could be widely accepted by all users. On the other hand, the Internet space can be viewed as a new form of existence where physical laws do not work, and in connection with this, social ones are often questioned. This paper focuses on how social norms regulate relations in Internet space. The authors represents the typology of deviant behavior in the network. The empirical basis of the research includes the sociological survey of students of the senior courses in the Institute of Computer Science and Technology of Peter the Great St. Petersburg Polytechnic University. Sociological survey allows to identify students’ understanding of Internet space. The selection of students is conditioned by the fact that IT professionals are considered simultaneously as ordinary users of the network and as future professionals in this field. (shrink)

This research paper presents an in-depth analysis of advanced artificial intelligence (AI) algorithms designed to automate data preprocessing in the healthcare sector. The automation of data preprocessing is crucial due to the overwhelming volume, diversity, and complexity of healthcare data, which includes medical records, diagnostic imaging, sensor data from medical devices, genomic data, and other heterogeneous sources. These datasets often exhibit various inconsistencies such as missing values, noise, outliers, and redundant or irrelevant information that necessitate extensive preprocessing before being analyzed (...) by machine learning or statistical models. Traditional data preprocessing methods, which are largely manual and time-consuming, can result in errors that affect the quality of the data and, subsequently, the performance of predictive and diagnostic models. Thus, there is a growing need for intelligent, automated systems that can enhance data quality, streamline the preprocessing pipeline, and reduce the time and effort required by healthcare professionals and data scientists. The study begins by outlining the specific challenges associated with healthcare data, including its high dimensionality, incompleteness, and variability across different data sources and formats. These issues not only complicate the preprocessing stage but also hinder the ability to develop robust models capable of making accurate predictions or diagnoses. The paper then explores how AI algorithms—particularly those based on machine learning (ML), deep learning (DL), and reinforcement learning (RL)—can automate key data preprocessing tasks such as data cleaning, feature selection, normalization, and transformation. These algorithms are designed to identify patterns in data, detect anomalies, and automatically apply corrections or transformations based on predefined rules or learned behaviors, thereby minimizing human intervention. The paper also delves into specific AI techniques that have been successfully applied to healthcare data preprocessing. For instance, supervised learning models, such as decision trees and support vector machines (SVMs), have been utilized to perform imputation of missing data by predicting the most likely values based on the available information. Similarly, unsupervised learning methods, such as clustering algorithms, have been employed to group similar data points and remove outliers that could distort the performance of analytical models. Moreover, deep learning techniques, particularly autoencoders and generative adversarial networks (GANs), have demonstrated remarkable effectiveness in transforming high-dimensional medical data into lower-dimensional representations, enabling more efficient and accurate model training. In addition to the discussion of these algorithms, the paper emphasizes the role of natural language processing (NLP) in automating the preprocessing of unstructured healthcare data, such as clinical notes and diagnostic reports. NLP techniques, including named entity recognition (NER) and word embeddings, are instrumental in extracting relevant information from unstructured text, standardizing terminologies, and converting textual data into structured formats suitable for downstream analysis. Furthermore, AI-based feature selection algorithms are explored, which aim to identify the most relevant features in the dataset, thereby reducing its dimensionality and improving the computational efficiency of predictive models. The study goes on to highlight the significant reduction in processing time achieved by AIdriven automation of preprocessing tasks. In conventional settings, data preprocessing accounts for a substantial portion of the time spent on building healthcare models, often requiring expert intervention to manually inspect and clean the data. By employing AI algorithms, not only can this process be expedited, but the accuracy of the resulting data is also enhanced, which translates into better model performance. The paper provides a detailed comparative analysis of manual preprocessing methods versus automated AI-driven approaches, demonstrating the substantial time savings and improvements in data quality brought about by automation. (shrink)

This richly illustrated book offers new perspectives and research on how digital culture is transforming museums in the 21st century, as they strive to keep pace with emerging technologies driving cultural and social change, played out not only in today’s pervasive networked environment of the Internet and Web, but in everyday life, from home to work and on city streets. In a world where digital culture has redefined human information behavior as life in code and digits, increasingly it dominates human (...) activity and communication. These developments have radically changed the expectations of the museum visitor, real and virtual, the work of museum professionals and, most prominently, the nature of museum exhibitions, while digital art and life in a digitally saturated world is changing our ways of seeing, doing, our senses and aesthetics. -/- Overall, this book creates a new picture of the 21st-century museum field. As museums become shared spaces with their communities, local, national and global and move from collection-centered to user-/visitor-centered institutions, they are assuming new roles and responsibilities tied to new goals for engaging their audience, conveying meaning through collections, creating learning experiences and importantly, connecting to daily digital life and culture integral to the museum ecosystem. Our studies of recent exhibitions at museums leading change are used to exemplify new directions, while they point to a reimagined vision for museums of the future at the heart of which is the integration of digital culture and visitor experience and participation in real and virtual space. (shrink)

The Internet of Things (IoT) is rapidly revolutionizing industries and everyday life through the integration of smart devices, sensors, and networks. The ability to connect and communicate between these devices is vital for the effective functioning of IoT systems. As IoT devices vary widely in terms of their power, connectivity, and computational capabilities, communication protocols play a crucial role in ensuring seamless, efficient, and reliable communication. Among the most widely used protocols in IoT are MQTT (Message Queuing Telemetry Transport) and (...) CoAP (Constrained Application Protocol), designed to address the specific requirements of IoT, including low power consumption, minimal bandwidth usage, and scalability. This paper surveys the key communication protocols used in IoT, with a specific focus on MQTT and CoAP. It discusses their architecture, characteristics, advantages, and limitations. Furthermore, the paper explores other emerging protocols that complement or extend the capabilities of MQTT and CoAP, such as HTTP/2, LwM2M, and AMQP, providing a broad perspective on the evolving IoT communication landscape. The primary objective of this paper is to evaluate the suitability of these protocols for different IoT applications, ranging from home automation and healthcare to industrial IoT (IIoT). We also highlight the security challenges associated with these protocols and suggest potential solutions. Lastly, we discuss future trends and the need for interoperability between different IoT communication protocols as IoT continues to scale and evolve. By analyzing the strengths and weaknesses of these communication protocols, this paper aims to provide IoT developers, researchers, and industry professionals with valuable insights into selecting the most appropriate communication framework for their IoT systems. (shrink)

In the constantly evolving landscape of Artificial Intelligence (AI), programming language selection has a defining role in the generation of innovation. This paper examines the harmonious dance between Python and AI, a language that has emerged to be the spine of intelligent systems. In a comprehensive review, we bring forth Python's heterogeneity and dominance in AI design, with applications in real life in machine learning, deep learning, natural language processing, robotics, and more. A deeper look into the strengths of Python—simplicity, (...) rich libraries, and supportive community—offers a sufficient reason why it is now the choice of AI researchers and developers. No technology is flawless, though; hence, we also mention the shortcomings of Python, such as performance bottlenecks and runtime issues, to present an overall picture. Since a tremendous amount of programming languages are used in AI, the paper also provides a comparative summary of popular AI-guided languages in terms of their efficiency, scalability, and usability for various AI applications. By providing an overview of Python's prevalence and placement among other AI languages, the research seeks to offer developers, researchers, and professionals decision-making information for AI-project deployment. (shrink)

This systematic literature review aims to address some critical questions in interdisciplinary STEM education. Specifically, this study endeavors to determine how STEM education has been implemented in the K-12 and higher education settings, which are the major target of this review, in the time range of 2016 to 2024. Within this time frame, I will utilize PRISMA’S systematic review procedures to conduct an analysis of peer-reviewed articles databases such as ERIC, Web of Science, Scopus, IEEE Xplore Digital Library, Science Direct (...) and Google Scholar. Articles from these databases would be analyzed through the use of Boolean oppositions of texts connected to education 5.0, STEM education as well as interdisciplinary approaches. There are tangible outcomes on student participation, improved retention, and development of timely necessary and relevant skills such as advanced ICT understands, intricate problem solving, and teamwork. Inadequate curriculum development policies, lack of curriculum policies, trained personnel and poor resource provision limited the development of the said framework. The review concludes that while interdisciplinary STEM education effectively prepares students for contemporary challenges and aligns with UN Sustainable Development Goals, successful implementation requires systematic institutional support and robust infrastructure. Recommendations include developing age-appropriate integrated curricula, establishing teacher collaboration networks, and conducting longitudinal research to assess long-term program impacts on student outcomes and career readiness. (shrink)