Turkish Journal of Computer and Mathematics Education (TURCOMAT)
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Natural Origins I— Space Units, Hydrogen Scale, Probe, and Field Equations
No full textBased on the Unified Field Theory (SUF), this paper starts from the right-handed helical vortex structure of space itself and establishes the geometric origin of the system of natural constants. The core result is that all fundamental constants of nature are not independent experimental inputs, but are uniquely generated by the three-layer encapsulation structure and by the strict threefold duality among scale, frequency, and mass.
In addition, using the SUF three-parameter field, the paper makes experimentally testable predictions about the coupling between gravity and electromagnetism.
The final conclusion is that the system of natural constants, gravitational, electromagnetic, and quantum structures, and vacuum response all originate from the same SUF spatial field, through a three-layer encapsulation geometry. The probe scale, the encapsulation number, and the two fundamental constants constitute the minimal generating set of nature, from which all known fundamental constants are uniquely derived—no free degrees of freedom, no circular assumptions—realizing a genuine unification of the natural geometric origins of physics
DENSITY BASED SMART TRAFFIC CONTROL SYSTEM USING CANNY EDGE DETECTION
No full textThe need for state-of-the-art equipment and technology to enhance traffic management is become more pressing as the problem of urban traffic congestion deteriorates. empirical evidence has shown that the traditional methods, such as timers and human control, are inadequate in effectively tackling this problem. The present study introduces a traffic control system that employs digital image processing and intelligent edge identification to enable real-time measurement of vehicle density. In contrast to earlier systems, this high-performance traffic control system offers a significant improvement in response time, automation, vehicle management, reliability, and overall efficiency. Furthermore, the whole process, including picture collection, edge recognition, and green signal allocation, is documented with suitable schematics and validated by hardware implementation using four illustrative images of different traffic situations
AI-Powered Encryption Revolutionizing Cybersecurity with Adaptive Cryptographic Algorithms
No full textThis paper proposes a state-of-the-art encryption technique that integrates artificial intelligence into a dynamic, content-aware security system. We introduce an AI-powered encryption framework that automatically adjusts cryptographic parameters based on message sensitivity, effectively balancing security requirements and computational efficiency. The system combines a DistilBERT-based neural network for real-time content sensitivity analysis with a flexible encryption mechanism that adapts key lengths, iteration counts, and entropy levels on the fly.
Our implementation demonstrates significant adaptability, with a correlation of 0.974 between content sensitivity and security parameters. The system distinguishes between different security requirements, using 32-byte keys with millions of iteration rounds for high-sensitivity content (sensitivity score of 8.64) and 16-byte keys with reduced iterations for low-sensitivity messages (sensitivity score of 3.10). The processing time scales linearly with security requirements, ranging from 300 ms for low-sensitivity content to 732 ms for high-security encryption.
Performance evaluation was highly effective, with the system achieving an overall score of 8.64/10, including 9.87/10 for adaptability and 9.12/10 for performance efficiency. The security level rated high at 7.37/10 while maintaining manageable computational overhead. The framework effectively handled different types of content without sacrificing encryption-decryption accuracy across all levels of sensitivity.
This work signifies a significant leap forward in the field of adaptive cryptography, demonstrating the capabilities of AI-driven security systems that can automate and optimize encryption parameters without compromising security standards. These results suggest that this approach may well represent the future of encrypted communications, providing scaled security appropriately without human intervention
IMPERSONATION AND ADMINISTRATIVE MISCONDUCT AT THE ELECTION COMMISSION OF PAKISTAN
No full textThis study investigates the abuse of power and institutional vulnerability within Pakistan’s electoral system by analyzing the case of Mr. Karan Kumar, a private citizen summoned by the Election Commission of Pakistan (ECP) despite not being a registered candidate. After complying with the summons, Mr. Kumar faced misconduct by ECP officials, including verbal abuse and procedural manipulation by a Deputy Director, with no meaningful inquiry conducted despite tribunal direction. Although a legal petition was filed, the summons remained unrevoked, and harassment reportedly escalated through informal and extrajudicial means.
Methodologically, the paper draws on document analysis, comparative reviews of election oversight mechanisms in the UK and India, interviews with legal experts and civil society members, and prior academic literature. The findings expose a troubling pattern of bureaucratic impunity, overreach, and institutional failure within the ECP, consistent with earlier critiques of Pakistan’s administrative bodies raised in Siddiqui’s publications, including “Public Funds, Private Gains” (2022) [https://doi.org/10.61841/2s3kmv78], “Who Judges the Judges?” (2019) [https://doi.org/10.61841/txq2w096], and “Unlicensed Medical Practice and Institutional Silence” (2024) [https://cibgp.com/au/index.php/1323-6903/article/view/2876]. These works collectively reflect a broader scholarly trend in Siddiqui’s research, which critiques systemic weaknesses in public sector accountability and regulatory enforcement.
By extending the analytical scope to Pakistan’s electoral machinery, this paper identifies urgent accountability gaps, including lack of internal oversight, politicized appointments, and procedural opacity. Drawing on civic engagement theory and administrative law frameworks, the research recommends seven core reforms: nullification of the unconstitutional summons; an independent inquiry against the responsible officer; standardized conduct and grievance procedures for ECP officials; integration of public complaint systems; mandatory training in ethics and electoral integrity; digital grievance tracking; and amendment of the Elections Act of Pakistan to restrain unchecked administrative discretion.
This paper builds on the author’s prior publications such as “Liberalism in South Asia” [https://cibgp.com/au/index.php/1323-6903/article/view/2870], and the cross-jurisdictional critiques in “Surveillance Overreach and Judicial Apathy in Global Drone Policy” [Russian Law Journal, https://doi.org/10.52783/rlj.v9i2.4997], and “Constitutional Vulnerability in the Age of Digital Surveillance” [CRLSJ, https://doi.org/10.52783/crlsj.449], which address the fragility of state institutions in safeguarding citizens’ rights.
Ultimately, this research asserts that without transparency, rule-based enforcement, and civic accountability, democratic institutions in Pakistan risk functioning as instruments of coercion rather than justice. The paper calls for structural reforms that realign the ECP with constitutional principles and democratic norms
Analytical Solutions to a Nonlinear Fredholm Integral Equation Using Laplace-Series Techniques
No full textThis paper presents a comprehensive analytical investigation into solving a specific nonlinear Fredholm integral equation of the second kind, expressed as u(x)=x+λ∫01xtu2(t)dt. Utilizing the Laplace-series method, we derive explicit solutions and validate their accuracy through detailed mathematical procedures. The study focuses on the parameter λ , with particular emphasis on the case λ=0.7, where two distinct linear solutions emerge. We explore the derivation process, verify the solutions against special cases, and analyze their graphical representation using a MATLAB-based approach. The findings underscore the effectiveness of the Laplace-series method in addressing nonlinear integral equations and provide insights into the behavior of the solutions over the interval [0,1]. The results are further supported by numerical verification and a visual plot, offering a robust framework for understanding the equation’s solution space
Investigating the behavior of dynamic systems based on linear differential equations
No full textLinear differential equations are fundamental tools in the analysis and modeling of dynamical systems that are used in many physical and engineering phenomena. This paper examines the structure, properties, and applications of these linear equations in the analysis of mass-spring systems, RLC circuits, and heat transfer processes. By presenting mathematical models and analyzing the time responses of these systems, it is shown how linear equations can model complex behaviors in a simple, predictable, and robust manner. The results of this research show that linear differential equations, despite their simplicity, are effective tools for the analysis of physical systems, and are used to more accurately model more complex systems over time
Practical Applications of Homogeneous Coordinates in Image Transformations Using MATLAB
No full textHomogeneous coordinates offer a robust mathematical framework for representing and executing geometric transformations in image processing, computer vision, robotics, and computer graphics. By embedding Euclidean space into a higher-dimensional projective space, they provide a unified mechanism for handling affine transformations, such as translation, rotation, scaling, and shear, as well as projective transformations like perspective projection. This study explores the practical applications of homogeneous coordinates within the MATLAB environment, leveraging its matrix manipulation capabilities to implement these transformations efficiently. Homogeneous coordinates simplify complex transformation pipelines through matrix concatenation, enabling seamless execution of combined operations while preserving computational efficiency and accuracy. Key applications demonstrated include image registration, warping, rectification, 3D modeling, and camera calibration, emphasizing their critical role in medical imaging, virtual reality, and augmented reality. MATLAB\u27s intuitive programming environment and advanced visualization tools further enhance the accessibility and applicability of these techniques. This article provides detailed explanations, MATLAB code implementations, and visual demonstrations to bridge the gap between theoretical foundations and real-world applications, making it an invaluable resource for researchers, practitioners, and students in the fields of image processing and computer vision
Enhancing Healthcare Data Security: Mitigating Ransomware Threats to Network-Attached Storage (NAS) Systems for Real-Time Access and Compliance
No full textRansomware attacks have become one of the most significant cybersecurity threats in the healthcare sector, particularly targeting Network-Attached Storage (NAS) systems that store and manage critical patient data, including Electronic Health Records (EHRs) and medical imaging. As healthcare organizations increasingly rely on NAS devices to provide real-time access to healthcare data, vulnerabilities within these systems—such as outdated software, weak access controls, and insufficient encryption—have made them prime targets for cybercriminals. The consequences of such attacks include the loss or corruption of patient data, significant downtime, and disruptions in patient care, which can jeopardize lives and lead to non-compliance with regulations such as HIPAA. This paper proposes a comprehensive solution to mitigate ransomware threats to NAS systems in healthcare environments by implementing end-to-end encryption, regular system updates, and advanced intrusion detection systems (IDS). These measures ensure the protection of patient data, preserve real-time access to critical healthcare information, and minimize the operational impact of ransomware attacks. Additionally, this approach offers stronger cybersecurity, reduces downtime, and enhances the resilience of healthcare organizations to cyber threats. By adopting these strategies, healthcare providers can improve data security, ensure compliance with regulations like HIPAA, and safeguard patient care continuity. The implementation of encryption and IDS can not only prevent unauthorized access but also enhance the ability of organizations to detect and respond to ransomware attacks in real-time, ensuring that patient data remains available and intact. This solution provides healthcare organizations with an effective, proactive defense mechanism against evolving ransomware threats, thereby enhancing operational efficiency and improving service delivery
THE FUTURE OF REGULATED AI: SCALING LLMs WITH OVERSIGHT AND PRECISION
No full textLarge Language Models (LLMs) possess transformative generative capabilities; however, their large-scale deployment in regulated domains—specifically finance and healthcare—demands robust infrastructure, continuous monitoring, and rigorous safety guardrails. This paper investigates best practices for cloud-based LLM deployment, proposing architectures that prioritize scalability, compliance, and reliability. We delineate secure infrastructure designs incorporating container orchestration and hardware acceleration to satisfy high-performance requirements. Additionally, the study details real-time monitoring frameworks for anomaly detection and comprehensive guardrail mechanisms—ranging from prompt filtering to human-feedback fine-tuning—to ensure alignment with legal and ethical standards. Through an analysis of financial and clinical use cases and associated challenges such as data privacy and bias, this work demonstrates that strategic design and oversight enable the effective, compliant scaling of LLMs in sensitive industrie
Characteristic Mode Solution of Complex-Coefficient Complex-Solution Differential Equations
No full textComputation of complex-coefficient complex-solution differential equations is a problem that arises in various domains of science and engineering. This paper aims at applying the Theory of Characteristic Modes (TCM) approach along with the Method of Moments (MoM) in solving these problems with emphasis on procedures for higher differential equations. Several available methods, known in literatures, are available for solving the problem. The complexity of the available methods differs based on the accuracy of the solution. In this paper, the general method is first presented and then a simplified version of it is proposed to solve high order differential equations. Two examples are illustrated, a third and a fourth order complex-coefficients complex-solution differential equations, to show the simplicity of the proposed method. The proposed approach can be also introduced along with other methods to solve these special occurrences differential equations and other boundary value problems