Volume 14 | Issue 5 |

 Abstract

The present study discusses the effects of colonialism and globalisation on the indigenous amaXhosa people of South Africa and their environment. it discussses how erasure of their space have occurred and how they have resisted the complete disruption.

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 Keywords

Colonialism, Globalisation, Space, Indigenous people

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India's new data protection law, the Digital Personal Data Protection Act of 2023, and its 2025 Rules, create a new kind of intermediary called the Consent Manager. The idea is that instead of every individual having to deal separately with hundreds of companies that collect their personal data, a single registered platform will let the user give, review, manage, and withdraw consent across all of them. This article examines whether the design of the Consent Manager will actually work for ordinary Indians, particularly those who are poor, less digitally literate, do not read English or Hindi well, share their phones with family members, or live in remote areas. It traces the legal architecture of the Consent Manager through the DPDP Act and the 2025 Rules, compares it with the existing Account Aggregator framework in the financial sector, and tests it against the constitutional standards of equality and proportionality laid down by the Supreme Court of India. The argument is that the present design assumes a data principal who is literate, English-speaking, smartphone-owning, and individually situated. Most data principals in India are not all of these things. The article concludes with five concrete reforms that can be brought in through delegated rules and regulatory guidance, without amending the Act itself, to make the Consent Manager genuinely accessible to the populations it most needs to protect.

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Creative Commons Attribution 4.0 and The Open Definition

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The ability to effectively ensure the safety of individuals within crowded public venues is one of the most challenging tasks in urban planning today. This area of concern rests at the intersection of urban infrastructure, public health, and emergency preparedness. Monitoring human security via video camera often results in staff losing concentration over time, and the ability to monitor multiple simultaneous video feeds becomes severely limited. We present a real-time crowd detection and social distance monitoring system built on YOLOv5x, the extra-large variant of Ultralytics' YOLOv5 family, running fully on GPU via PyTorch Hub. The system incorporates confidence-filtered COCO person detection, pairwise Euclidean proximity analysis with configurable thresholds, an OpenCV-based bird's-eye view perspective correction module to reduce foreshortening-induced false positives, and automated SMS alerts via the Twilio API when crowd count exceeds a defined threshold. At a confidence threshold of 0.5, the system achieves Precision 0.912, Recall 0.887, and F1-score 0.899. The bird's-eye transform improves violation detection accuracy by 10.3% and reduces false alerts by approximately 60%. The system sustains 31.4 FPS on an NVIDIA T4 GPU, with end-to-end SMS alert latency of 1.84 seconds over a 4G connection.

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Crowd Detection YOLOv5 Social Distance Monitoring Bird's-Eye View Perspective Transform Homography Twilio SMS Alert OpenCV PyTorch People Counting Public Safety Real-Time Video Analysis

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Nanoemulsions have emerged as advanced colloidal carriers capable of enhancing topical drug delivery by improving solubility, permeation, and therapeutic efficacy. Their nanoscale droplet size, high kinetic stability, and compatibility with diverse pharmaceutical actives make them ideal for dermatological and cosmeceutical applications. This review provides a comprehensive analysis of nanoemulsion formulation strategies, mechanistic insights into skin permeation, characterization techniques, and translational progress toward clinical use. Special emphasis is placed on nanoemulgels, surfactant/co-surfactant systems, droplet engineering, and therapeutic applications in inflammation, infection control, wound healing, and chronic skin diseases. Challenges related to scale-up, regulatory pathways, and long-term safety are critically evaluated. Future directions highlight personalized nanoemulsion therapy, multifunctional systems, and AI-driven formulation optimization.

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Nanoemulsion, Nanoemulgel, Topical drug delivery, Skin permeation, Dermatology, Clinical translation

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Creative Commons Attribution 4.0 and The Open Definition

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Abstract-- Finding reliable local skilled workers such as electricians, plumbers, carpenters, and appliance repair technicians remains a major challenge in urban and semi-urban regions. Existing methods primarily depend on informal referrals, which lack transparency, worker verification, and service quality assurance. This research proposes a secure digital labour marketplace that connects customers with verified local skilled workers through an AHP-weighted trust-aware recommendation system.

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Keywords: Digital Marketplace, Labour Platform, AHP Weight Derivation, Composite Trust Ranking, OTP Authentication, Worker Verification, XGBoost Validation, Location-Based Services

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Creative Commons Attribution 4.0 and The Open Definition

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As the popularity of digital devices and digital interactive systems has increased over the previous few years, the understanding of human emotions has become an important area of study. Emotion detection is important in various application domains, such as healthcare, education, and human-computer interaction. Accurately identifying emotions is a complex process, since various factors contribute to emotion detection, including facial expressions, behavior patterns, and context. This research project investigates the ability of deep learning techniques to detect emotion based on visual representations of people (e.g. images). This study explores various types of features used to categorize emotions (e.g. facial expressions, image-based cues) and assesses performance when different types of deep learning models are employed. In contrast to developing one type of deep learning model specifically to detect emotions, this research compares different approaches in order to establish models that perform well under similar conditions. The final goal is to generate an effective framework that can be applied and implemented in real-world practices with minimal effort and/or modification to the models.

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Creative Commons Attribution 4.0 and The Open Definition

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The rapid digitization of public services and everyday life under the 'Digital India' initiative has significantly increased citizens' exposure to cyber threats such as phishing, online fraud, identity theft, and social-media-based scams. In this context, social-awareness programs have emerged as a critical intervention to improve cyber-safety behavior among Indian digital citizens. This paper evaluates the effectiveness of existing cyber-safety awareness initiatives--launched by government bodies, educational institutions, and community organizations--using a mixed-method research design. Through structured surveys and focus-group discussions conducted across urban and semi-urban areas of Maharashtra (including Pune), the study examines citizens' awareness levels, perceived risk, and actual online behavior before and after exposure to cyber-safety campaigns. The findings reveal that while awareness of basic cyber-threats (such as password safety and public-Wi-Fi risks) has improved, critical gaps remain in understanding newer threats like deepfakes, ransomware-style extortion, and social-engineering attacks. The paper highlights that current awareness programs often emphasize generic messaging without tailoring content to specific user groups (e.g., students, elderly citizens, MSME owners). Based on the results, the study proposes a more targeted, participatory, and sustained model for cyber-awareness that integrates local context, role-based guidance, and continuous feedback mechanisms. The proposed framework aims to help transform the broader vision of 'Digital India' into a truly 'Secure India' by embedding cyber-safety awareness into everyday social practices and policy design.

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Creative Commons Attribution 4.0 and The Open Definition

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Cybersecurity awareness, social awareness programs, Digital India, cyber safety, phishing, online scams, behavior change, public-policy evaluation

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Creative Commons Attribution 4.0 and The Open Definition

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The internet plays an important role in the academic and personal lives of high school students. This study examines internet usage among high school students in relation to their location, particularly rural and urban areas. The study aims to identify the level and purpose of internet usage and to compare usage patterns based on students' location. A survey method was used, and data were collected through a questionnaire from high school students. The findings reveal that students use the internet mainly for education, communication, entertainment, and social networking. The study also shows significant differences between rural and urban students in internet access and usage, with urban students having better access and higher usage levels. The study highlights the need to improve digital facilities and promote effective and responsible internet usage among students.

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Internet Usage, High School Students, Student Location, Rural and Urban Students, Digital Learning, Educational Technology.

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Creative Commons Attribution 4.0 and The Open Definition

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- A worldwide increase in lifestyle-related diseases (such as diabetes, cardiovascular disease, hypertension and obesity) is associated with unhealthy lifestyles (e.g., sedentary behavior, poor dietary habits and increased stress levels). Early identification of these types of diseases can improve the outcomes of treatment and reduce long-term healthcare costs. Traditional diagnosis approaches use clinical testing as the primary means of identifying these diseases and generally, identify them after they have advanced or reached a More severe state based on symptoms. This research proposes an artificial intelligence (AI) and machine learning (ML) framework to assess and predict disease using lifestyle data. The application provides assessments of various parameters of an individual's lifestyle (such as physical activity, sleep, eating habits, stress levels and substance use) and finds patterns among those parameters that increase an individual's risk of developing a certain disease. Using predictive algorithms such as logistic regression, decision trees and random forest, predictive models are developed to classify individuals into categories. This approach is to create a preventative healthcare approach by delivering interventions before symptoms reach a severe state. Experimental results show that these predictive models using lifestyle data can generate highly accurate and reliable results, which makes them suitable for use in health care facilities or through wearable technologies .

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Artificial Intelligence, Machine Learning, Lifestyle Data, Disease Prediction, Preventive Healthcare

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Creative Commons Attribution 4.0 and The Open Definition

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This paper proposes a Mini Mobile Digital Radiography System integrating portable X-ray imaging, embedded processing, and telemedicine communication for efficient and real-time medical diagnosis. The system employs a Raspberry Pi-based architecture to perform on-device image acquisition, enhancement, and transmission. A hybrid image processing approach combining Contrast Limited Adaptive Histogram Equalization (CLAHE) and Wiener filtering is implemented to address challenges such as low contrast and noise in radiographic images. Performance evaluation using metrics such as Peak Signal-to-Noise Ratio (PSNR), Mean Square Error (MSE), and entropy demonstrates significant improvement in image quality compared to conventional methods. Furthermore, the system enables remote diagnosis through wireless data transmission using GSM/Wi-Fi networks, facilitating expert consultation in underserved and remote regions. The proposed system offers a cost-effective, portable, and scalable solution for modern healthcare applications, particularly in emergency and rural settings.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Digital Radiography, Portable Radiography System, Mobile Healthcare, Raspberry Pi, Embedded Systems, Medical Image Processing, Image Enhancement, Contrast Enhancement, Noise Reduction, CLAHE, Wiener Filter, Telemedicine.

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Creative Commons Attribution 4.0 and The Open Definition