Volume 14 | Issue 4 |

 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.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

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.

Licence: creative commons attribution 4.0

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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.

Licence: creative commons attribution 4.0

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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.

Licence: creative commons attribution 4.0

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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.

Licence: creative commons attribution 4.0

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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

 Abstract

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Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This paper introduces Mini-ROS, a lightweight, cloud-edge hybrid framework built on ROS 2 that enables smarter and more efficient robotic control. The system combines AI-driven perception--powered by a Hybrid CNN-Regression model for object and face detection--with predictive runtime estimation that uses voltage data to anticipate performance. Mini-ROS is designed to balance computation between the cloud and the robot: heavy processing tasks are handled by cloud microservices managed through Kubernetes, while a ROS 2 edge client takes care of real-time sensing and actuation. To make monitoring easier, a web dashboard provides live updates on telemetry and AI events. Compared to other ROS frameworks Mini-ROS really shines as it runs faster with lower delays, scales easily as your system grows, and uses resources more efficiently. This makes it a perfect fit for affordable robots and setups that involve multiple robots working together.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

ROS 2, Cloud Robotics, Edge Computing, Hybrid Architecture, Microservices, gRPC, WebSockets, Object Detection, Runtime Prediction, Artificial Intelligence, Kubernetes, Real-Time Control

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Adolescence is the period of transition between childhood and adulthood. It is a time of new challenges and new opportunities. Adjustment implies a satisfactory adaptation to the demands of day-to-day life. Adolescents are confused and anxious regarding the biological, psychological and social challenges they have confronted. The present study is an attempt to study adjustment problems of adolescents and its impact on their academic achievement. It is a descriptive survey study comprising of 300 adolescents taken from High schools of Davangere district. Adolescent Problem Inventory was used to collect data. The marks secured by the students in the examination of previous semester / year were obtained from school records and they were considered as the academic achievement of the students. The mean, percentage, t-test and co-efficient of correlation were used to analyse the data and interpret the result. Results showed that adolescent boys and girls posses adjustment problems in various areas like family, school, social and personal. It was revealed that the adolescent boys and girls of High schools in Davangere district differ significantly on adjustment problems and in academic achievements. It was found that adjustment problems of the adolescents influence on their academic achievements.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Adolescent, Adjustment, Academic Achievement,Turbulent.

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Creative Commons Attribution 4.0 and The Open Definition