Volume 14 | Issue 4 |

 Abstract

Franz Kafka's novel "The Metamorphosis" presents an unexplainable transformation of the main character of the novel, Gregor Samsa into a "monstrous vermin." This paper conveys that Gregor's physical change is not a random occurrence but the ultimate expression of his pre-existing self-alienation rooted in oppressive familial and financial duties. Even before his physical transformation, Gregor's psyche had been eroded by a mechanical, soul-crushing routine, effectively reducing him to a mindless machine serving a system and a family that valued his labour over his humanity.

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 Keywords

Beyond the Bug: A Study of Psychological Setback and Self-Alienation in Franz Kafka's novel "The Metamorphosis."

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Indigenous Knowledge Systems (IKS) represent a vital component of cultural heritage embedded in local communities and transmitted through generations via social practices and lived experiences. This study examines the continuity, preservation, and representation of IKS from a social science perspective. It explores the influence of socio-cultural transformations such as globalization, modernization, and environmental change on the sustainability of IKS, revealing that while these factors contribute to knowledge erosion, community resilience, adaptive practices, and the role of cultural custodians support its continuity. The study further assesses the availability of institutional policies for long-term preservation of IKS in selected repositories, highlighting the absence of comprehensive frameworks despite emerging efforts in digital curation, ethical governance, and community-centered approaches, alongside challenges such as financial constraints and linguistic loss. Additionally, it evaluates the representation of IKS within educational curricula, indicating gradual inclusion with increasing recognition of its cultural and social significance, although limitations persist due to lack of teacher preparedness, standardization issues, and loss of contextual depth. The study concludes that effective preservation and promotion of IKS require strong community participation, supportive policy frameworks, and pedagogical transformation to ensure its relevance for cultural identity and sustainable development.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Indigenous Knowledge Systems (IKS), Knowledge Preservation, Value-Based Education, Cultural Heritage Education

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Domestic violence is a major public health and psychological concern that affects not only intimate partners but also children who witness or directly experience violence within the home. Exposure to domestic violence during childhood has profound consequences for emotional, cognitive, behavioral, and social development. Children living in violent households frequently experience chronic stress, fear, insecurity, and trauma, which may contribute to long-term psychopathology. This paper reviews the psychological effects of domestic violence on children, including anxiety, depression, post-traumatic stress disorder (PTSD), attachment disturbances, behavioral problems, academic difficulties, and intergenerational patterns of violence. It also discusses developmental differences in response to violence exposure and highlights the importance of early intervention, school-based support, and trauma-informed therapeutic approaches.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Domestic violence,Children,Psychological Effects,Anxiety,Trauma,Attachment

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Visually impaired people often find it difficult to read everyday printed materials like books, newspapers, or documents. To address this problem, we built a simple and affordable automatic reading system using a Raspberry Pi 3 Model B, a 5MP camera, basic speakers with a 3.5 mm jack, and a standard 5V power supply. The entire setup is compact and easy to carry, making it practical for daily use.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Raspberry Pi 3, Smart Reader, Optical Character Recognition (OCR), Text-to-Speech (TTS), Assistive Technology, Pi Camera, USB Speakers, Image Processing, Visually Impaired.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Road transportation in hilly regions poses significant safety challenges due to steep gradients, sharp curves, and varying road conditions. Conventional braking systems rely heavily on driver response, which may be insufficient in critical situations, leading to accidents such as vehicle rollback or loss of control during descent. This paper presents a Safety Auto Brake System (SABS) based on a Micro-Electro-Mechanical System (MEMS) sensor for real-time slope detection and automatic braking control. The MEMS sensor, acting as an accelerometer, continuously measures tilt and acceleration along multiple axes and transmits data to a microcontroller for processing. Based on predefined threshold values, the system automatically activates the braking mechanism under unsafe conditions. The proposed system effectively prevents rollback during uphill starts and controls vehicle speed during downhill motion, thereby enhancing stability and safety. The integration of MEMS technology offers advantages such as high sensitivity, fast response, compact size, and low power consumption. Additionally, the system reduces driver workload and can be implemented using cost-effective components, making it suitable for both new vehicles and retrofitting applications. Experimental analysis indicates that the proposed system significantly improves vehicle control and reduces accident risks in hilly terrain. Future work may include integration with advanced driver assistance systems and adaptive control techniques for improved performance.

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Creative Commons Attribution 4.0 and The Open Definition

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Safety Auto Brake System on Hill Station by Using MEMS Sensor

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The convergence of DevOps practices and cybersecurity imperatives has given rise to the DevSecOps paradigm, demanding security processes that are as agile and automated as the pipelines they protect. Conventional security assessment methodologies -- manual penetration testing, rule-based static analysis, and fragmented dynamic scanning -- are unable to keep pace with the velocity, scale, and complexity of modern software delivery. This paper proposes and evaluates AI-ASAP (AI-driven Automated Security Assessment Pipeline), a comprehensive framework that embeds artificial intelligence at every stage of the security assessment lifecycle within CI/CD workflows. AI-ASAP integrates static application security testing (SAST) enhanced by natural language processing (NLP), reinforcement-learning-based dynamic fuzzing, graph neural network (GNN) dependency risk analysis, large language model (LLM) powered remediation generation, and continuous threat intelligence correlation. Evaluation across simulated enterprise environments demonstrates a 94.3% vulnerability detection rate, a 6.7% false positive rate, and a reduction in mean assessment time from days to under 45 minutes, with automated pull-request remediation capabilities. The proposed framework represents a significant advancement toward autonomous, continuous, and intelligent security assessment in modern software engineering.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

DevSecOps, AI Security, SAST, DAST, CI/CD Pipeline, Vulnerability Assessment, LLM Remediation, Reinforcement Learning, Graph Neural Networks, Threat Intelligence.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

MiDAS is a cost-effective and scalable automation platform developed to enhance the operational efficiency of small and medium-sized manufacturing enterprises (SMEs). Many SMEs still rely on manual methods for monitoring machine performance, which often leads to delayed maintenance, unexpected equipment failures, and suboptimal production efficiency. Although conventional industrial automation solutions such as PLC and SCADA systems provide robust capabilities, their high cost and implementation complexity make them less accessible to smaller industries. To address this gap, MiDAS integrates affordable Internet of Things (IoT) technologies with practical industrial monitoring needs. The system utilizes low-cost hardware components, including ESP32 microcontrollers, sensors, and a Raspberry Pi functioning as a local server. It captures real-time machine parameters such as punch count, vibration, and energy consumption, and transmits the data wirelessly using the MQTT protocol. The collected data is processed using analytical techniques such as aggregation, threshold-based anomaly detection, moving averages, and linear regression to generate predictive maintenance insights. A web-based dashboard, developed using React, provides real-time visualization of machine status, health metrics, and predictive alerts. By enabling continuous monitoring, early fault detection, and data-driven decision-making at a significantly lower cost than traditional systems, MiDAS empowers SMEs to reduce downtime, improve productivity, and adopt Industry 4.0 practices effectively.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Predictive maintenance, IIoT, ESP32, Raspberry Pi 4, proximity sensor, edge computing, real time monitoring, machine health, production output, maintenance notifications, industrial automation

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This paper examines Mary Shelley's Frankenstein (1818) and Octavia Butler's Dawn (1987) as science-fictional thought experiments that interrogate the ethical, social, and ecological consequences of scientific intervention in life. Drawing on the interdisciplinary framework of Science, Technology, and Society (STS), along with concepts from bioethics and ecofeminism, the study explores how both texts critique scientific rationality when it operates without ethical responsibility. Shelley's Frankenstein, often regarded as the foundational work of modern science fiction, exposes the dangers of unchecked ambition and irresponsible experimentation, anticipating contemporary debates on cloning, artificial life, and bioengineering. Butler's Dawn, situated in a post-apocalyptic and posthuman context, extends this critique by examining genetic manipulation, hybridity, colonisation, and ecological symbiosis. While Shelley foregrounds individual responsibility and the moral limits of scientific inquiry, Butler complicates ethical judgment by framing survival as contingent upon compromise, interdependence, and the redefinition of the human. Together, these texts demonstrate how science fiction functions as a critical and pedagogical space for reflecting on ethical science, environmental sustainability, and the future of human and non-human life in an age of technological acceleration and ecological crisis.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Science fiction; thought experiment; STS; bioethics; ecofeminism; hybridity; Anthropocene; posthumanism

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The rapid advancement of technology and the explosion of biological data have led to the emergence of bioinformatics, a field that integrates biology with data science. Bioinformatics utilizes computational tools, statistical models, and machine learning techniques to analyze complex biological data. This paper explores how data science has become indispensable in modern biology, the applications of bioinformatics, its challenges, and future prospects. The study highlights how bioinformatics is transforming healthcare, genomics, and drug discovery.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Bioinformatics

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Digital evidence forms the cornerstone of modern investigations but poses significant challenges for maintaining integrity and a verifiable chain-of-custody. This paper proposes a multi-layered evidence protection system that combines cryptographic hashing, and role-based access control (RBAC) to secure evidence from ingestion to analysis. The architecture allows authenticated users (investigators, officers, administrators, etc.) to upload evidence via a secure portal. Each file is split into chunks and hashed; SHA-256 hashes are aggregated into a MongoDB database stored with the evidence. RBAC enforces permissions for each role. An audit log records all actions. Experimental estimates indicate that hashing overhead is low, while modern hash functions are collision-resistant. Finally, we discuss future directions(e.g. Blockchain timestamping, explainable AI for forgery detection) and conclude that this framework greatly enhances evidence integrity and traceability.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Keywords-- Digital Evidence Management, Chain of Custody, Cryptographic Hash, SHA-256, Role-Based Access Control, Evidence Integrity.

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Creative Commons Attribution 4.0 and The Open Definition