Ravi Kumar

This paper explores the philosophical relationship between Immanuel Kant's transcendental idealism and Ludwig Wittgenstein's linguistic philosophy, particularly focusing on the echoes of Kant's ideas in Wittgenstein's work. Kant's Critique of Pure Reason argues that human cognition is shaped by a priori categories, which structure our experience of phenomena but leave the noumenal realm unknowable. Wittgenstein, in his Tractatus Logico-Philosophicus, similarly examines the limits of what can be known; suggesting that language mirrors reality but also has its limits in expressing what lies beyond logic. In his later work, Philosophical Investigations, Wittgenstein emphasizes the social and contextual nature of meaning, developed through "language games" and "forms of life". This paper argues that while Wittgenstein shifts from Kant’s universal transcendental structures to a more pragmatic view of language, both philosophers share a concern with the limits of human knowledge and expression. Furthermore, both thinkers acknowledge the ineffable about Kant’s noumenal world and Wittgenstein’s mystical realm as crucial yet unreachable domains. This comparative analysis contributes to contemporary discussions in epistemology and philosophy of language, demonstrating the enduring relevance of Kant’s transcendental insights in Wittgenstein’s linguistic turn.

The question of whether human rights are natural, universal, or socially constructed remains central in contemporary philosophy. This paper examines John Searle’s theory of social ontology as a framework for understanding the ontological status of rights. Searle’s account of institutional facts, collective intentionality, and deontic powers offers a distinctive perspective on how rights emerge from shared linguistic and social practices. Within this framework, human rights are conceived not as metaphysical absolutes but as status functions grounded in collective recognition and maintained through institutional structures. This analysis highlights the strengths of Searle’s approach in explaining the social reality of rights while also engaging with its limitations, particularly regarding the universal validity of human rights and the challenges posed by cultural relativism and power asymmetries. By situating human rights within the ontology of social reality, the paper contributes to ongoing debates in philosophy and political theory about the foundations, legitimacy, and future of human rights discourse.

The Heart of the Matter: Development, Identity and Violence - Reconfiguring the Debate The Volume addresses the complex relationship betweenDevelopment, Identity and Violence from different dimensions. Itexplores the ideas of development beyond its appearances anddevlves deeper into its essence. India has been a site oftumultuous changes in recent times as a consequence of its shifttowards neoliberalism. This shift has not only introduced a newframework of development but has also produced its side effects.Chapters in this volume make an effort to critically engage withthese issues trying to reconfigure the ongoing debates ondevelopment. Contents Acknowledgements Introduction 1. Thinking Through Urban Debris: Violence, Terror and theState 2. Through an Beyond: Identities and class Struggle 3. " No rehabilitation" is Ecocide and Genocide: Is TherePossibility of Hope? 4. Ventilating Predicament of Development: New Economic Enclavesand Structural Violence in India 5. The Artifice of Modernity in Nation- Building: Analyzing thecase of "Postcolonial" Northeast India 6. Developing Bastar: The Dandakaranya Project Contributor Ravi Kumar Ravi Kumar teaches at the Development of Sociology, Jamia MilliaIslamia. His works include Ghetto and within; Class, Identity,State and politics of Mobilization (2010, Delhi: Aakar Books);Global Neoliberalism and education and its Consequences (2009, NewYork& London: Roultledge); The Crisis of Elementary Educationin India (2006, New Delhi: sage Publications); The Politics ofImperialism and Counterstrategies (2004, New Delhi: Aakar books).He is in Process of Co-editing a series on social movements,Dissent and Transformative. He has written extensively oneducation, media and social movements and is on the advisory boardof Journal of Critical Education Policy Studies and co-editsRadical Notes.

Data mining technology for healthcare purposes transforms basic medical information into useful insights which helps doctors predict diseases along with diagnosing patients while tailoring personalized treatment plans. A successful healthcare analytics process requires a complete data pipeline which includes data preprocessing followed by extraction then selection after optimization until classification. Data preprocessing implements the Z-Score Method together with Isolation Forest along with Interquartile Range (IQR) Method to detect outliers which would potentially harm model performance. The Principal Component Analysis (PCA) serves as an extraction method to reduce dimensions alongside log transformation which addresses data skewness to establish data stability. Wrapper methods Recursive Feature Elimination (RFE) together with Genetic Algorithms build predictive accuracy by continuously refining the selected feature subsets. Model performance enhancement relies on the Adam optimizer together with other optimization methods that aid in achieving high accuracy during medical outcome predictions. Adam Optimization optimization achieved a maximum training accuracy of 1.0 while validation accuracy reached 0.9 as the optimal value. Improvements in loss functionality decreased it from 45 to almost zero levels proving successful learning takes place. Analysis showed that the model demonstrated a positive trend in both validation accuracy levels despite periodic accuracy difficulties because the pipeline functioned well for predicting CKD conditions. Future work will direct its attention towards adjusting model performance by fine-tuning along with regularization techniques and additional data acquisition for enhancing generalization capabilities

Data mining technology for healthcare purposes transforms basic medical information into useful insights which helps doctors predict diseases along with diagnosing patients while tailoring personalized treatment plans. A successful healthcare analytics process requires a complete data pipeline which includes data preprocessing followed by extraction then selection after optimization until classification. Data preprocessing implements the Z-Score Method together with Isolation Forest along with Interquartile Range (IQR) Method to detect outliers which would potentially harm model performance. The Principal Component Analysis (PCA) serves as an extraction method to reduce dimensions alongside log transformation which addresses data skewness to establish data stability. Wrapper methods Recursive Feature Elimination (RFE) together with Genetic Algorithms build predictive accuracy by continuously refining the selected feature subsets. Model performance enhancement relies on the Adam optimizer together with other optimization methods that aid in achieving high accuracy during medical outcome predictions. Adam Optimization optimization achieved a maximum training accuracy of 1.0 while validation accuracy reached 0.9 as the optimal value. Improvements in loss functionality decreased it from 45 to almost zero levels proving successful learning takes place. Analysis showed that the model demonstrated a positive trend in both validation accuracy levels despite periodic accuracy difficulties because the pipeline functioned well for predicting CKD conditions. Future work will direct its attention towards adjusting model performance by fine-tuning along with regularization techniques and additional data acquisition for enhancing generalization capabilities

The development of cultural heritage tourism (CHT) frequently encounters obstacles pertaining to community support, as the attitudes of the local populace typically dictate the outcome of tourism endeavors. The community's influence on these perceptions has been undervalued in traditional approaches, which has resulted in low levels of engagement and support for cultural preservation. This study aims to bridge this gap by investigating how different degrees of community involvement impact local perceptions of the advantages of tourism, the preservation of culture, and general satisfaction with the results. Data was gathered from 300 participants who were actively involved in many heritages sites' tourism planning. The connections between perceptions of the advantages of tourism and community involvement (CI) were evaluatedby utilizing Partial Least Squares Structural Equation Modeling (PLS-SEM). The results demonstrated that the perceptions of economic benefits (PEB), perceptions of cultural preservation (PCP), and community satisfaction (CS) are all positively impacted by greater CI. The aforementioned results underscore the significance of adopting participatory methodologies, implying that cultivating community engagement is vital for the sustainable growth of CHT.