Pakistan agricultural sector forms the backbone of its economy, with wheat being the staple crop, processed predominantly through small-scale flour grinders (Aata Chakkis). Alongside wheat, other grains such as maize (corn), barley, millet, rice, and chickpeas are also ground in these mills for daily consumption. However, these mills consume significant electricity, increasing operational costs and pressuring Pakistans fragile power grid. With rising power costs and frequent outages, mill owners are adopting solar-powered solutions. This study explores how Variable Frequency Drives (VFDs) can optimize the efficiency of solar-powered flour grinders by providing grain-specific motor speed control, reducing electricity consumption, and maintaining [...]

Web application security reports are usually ordered by technical severity but low-resourced organizations want to know which vulnerability will become the most expensive security debt to repay? This paper presents SECURE-DEBT a model used to rank the 2025 OWASP web application risks to prioritize the remediation of web applications in resource-constrained healthcare-style organizations and small to medium enterprises (SMEs)? SECURE-DEBT considers the unresolved vulnerabilities as security debt thus incurring future risk based on evidence, exposure, sensitive information, exploitability, operational impact and time considerations for a fix? The study follows an empirically-driven, framework-based conceptual research article? The scoring considers mapping to [...]

Upper-limb amputations are a significant source of disability, especially in resource-limited environments where expensive commercial-grade prosthetics (often costing over USD 70,000) are unaffordable. This paper describes the design, optimisation and pilot testing of a 7-degree of freedom (DOF) transhumeral motorised prosthesis controlled by TinyML-based myoelectric decoding. The gesture-recognition accuracy (F1-score) of 95.5% across five able-bodied participants (gesture-level accuracy: approximately 92.3% for the most difficult gesture) with an end-to-end response time of 100ms is achieved using an affordable ESP32 microcontroller and a Cost-Complexity Pruned (CCP) Random Forest (RF) classifier. This paper outlines the hardware-software co-design, mathematical formulation of [...]

This paper presents a multilingual spam email classification framework capable of processing both German and English texts using classical machine learning models combined with a translation-enhanced pipeline. The system integrates TF-IDF vectorization, Logistic Regression, Multinomial Naive Bayes, and a probability-calibrated Linear Support Vector Classifier (SVC). A key contribution is the incorporation of an automatic German-to-English translation layer using MarianMT, allowing cross-lingual evaluation and robustness analysis. Multiple models are trained on a manually curated dataset of 3,790 emails, achieving up to 98.55% accuracy and 0.9860 AUC-ROC on the evaluated dataset. A Streamlit-based application is implemented for real-time inference, [...]

Transformer architectures have become a central foundation of modern artificial intelligence because of their scalability, parallel computation, and representation learning across language, vision, code, and multimodal domains. Since the original Transformer, the architecture has evolved into encoder-only, decoder-only, encoder-decoder, efficient attention, vision, multimodal, sparse Mixture-of-Experts, open-weight, state-space, recurrent, and hybrid model families. This review presents a structured and benchmark-informed comparison of Transformer architectures using a defined literature selection protocol, inclusion and exclusion criteria, model-family coding dimensions, and source-verification rules. The paper compares major architectures with respect to training objective, attention or sequence-modeling mechanism, computational complexity, scalability, context length, modality support, [...]

As we can see, different people are addicted to mobile and computer games nowadays and rejected the famous ancient games like chess. This paper depicts design and construction of smart electronic chess system using electronic circuits which change the playing ability of human chess game to a non-idealized behavior, it’s up to difficult mode. Chess Board environment and its searching methodology are given by to use of openly sourced chess game engine the "STOCK FISH ". It will be restructured by using python ide. When user play its move, the spawn’s original location and its current location are fed into [...]

This study explores blockchain consensus algorithms, emphasizing their theoretical foundations, advancements, and security implications. It begins with an overview of key consensus mechanisms, including Proof of Work (PoW), Proof of Stake (PoS), and Byzantine Fault Tolerance,and examines their respective strengths and limitations. The study also investigates scalability and feasibility in real-world applications, highlighting innovations that enhance energy efficiency and fault tolerance. Furthermore, the research addresses potential vulnerabilities, such as Sybil attacks and centralization risks, proposing mitigation strategies to ensure robust network security. The findings contribute to the understanding and development of secure, efficient, and scalable blockchain systems,fostering innovation [...]

The digital era has revolutionized the way we live, work, and interact, yet it has also exposed us to a new frontier of vulnerabilities. As the world becomes increasingly connected, the complexity and frequency of cyber threats have grown exponentially. Cybersecurity has emerged as a critical field, demanding innovative and adaptable solutions to protect sensitive data, safeguard infrastructure, and maintain trust in digital systems. Artificial Intelligence and Machine Learning stand at the forefront of this transformation, offering tools that are not only reactive but also predictive. Unlike traditional cybersecurity measures that often rely on predefined rules, AI and ML leverage [...]

The natural language processing (NLP) sector re- quires sentiment analysis as its essential capability because deep learning advancements keep happening. Textual sentiment analysis capability allows automatic understanding of both positive and negative emotions found in movie titles which can help various industries perform better social media monitoring and marketing and customer feedback analysis. This paper investigates the implementation of a Bi-LSTM (Bidirectional Long Short-Term Memory) model that integrates GloVe (Global Vectors for Word Representation) embeddings as a solution for movie title sentiment classification. A Bi-LSTM model analyzes data sequences from start to end and back again which increases its ability [...]

The project is based on Google Map is formally known as Google Local, which is a Web mapping service application and technology provides by Google. The fundamental objective of this project is to plan an actual tour and to provide the best route and pictures of the place’s tourists are willing to visit. It includes the information about the places and snaps taken, but the people who had visited the places and they can also mark on Google maps. It will help other people to get information about places which they are planning their visit. Secondly, People will come to [...]

It is through the lens of the Open Systems Interconnection (OSI) model that we can begin to manage the complexity that is present with modern network communications. All the seven layers starting from the Physical layer all the way to the Application Layer have different functional roles and their respective security vulnerabilities, and if there is no fix, it becomes a target for cybercriminals. This documentation provides a comprehensive analysis of the implementation of OSI principles based layered security strategies through appropriate protocol management and sophisticated cybersecurity techniques. Port and protocol management should be employed as a first line of [...]

In this study, we present the development of a novel, automated solar photovoltaic (PV) panel cleaning system designed to address the challenges of dust accumulation and water scarcity, particularly in arid and semi-arid regions. The proposed system integrates a hybrid cleaning mechanism that utilizes a combination of water sprinkles, a wiper, and a brush to effectively remove dust and debris from the surface of solar panels. Unlike conventional cleaning systems that consume large volumes of water, our design employs only three controlled sprinkles, significantly minimizing water usage without compromising cleaning efficiency. A key feature of the system is its autonomous [...]

Blockchain technology offers transformative potential for healthcare through its decentralized, immutable ledger system. When it combined with federated learning, which allows the models to trained collaboratively without sharing data these technologies address the critical challenges in medical, data privacy and security. Our architecture demonstrates how this combined implementation (1) secures patient records via cryptographic hashing, (2) maintains data integrity across distributed nodes, and (3) preserves confidentiality during processes, while specifically addressing three key implementation challenges: computational overhead from dual-layer encryption, and evolving regulatory compliance requirements. Through comparative evaluation of blockchain types (public, private, consortium), we identify trade-offs in scalability versus [...]

Screen time refers to the duration spent on digital devices and digital media, including online gaming, smartphones, tablets, computers, televisions, and wearable technologies such as smartwatches, as well as internet browsing across various devices. To analyze parents' perceptions of screen practices among young children under six, highlighting their behaviors and the impact on early development, including a lack of interaction, cognitive development, and behavioral issues. This study employed a quantitative, cross-sectional design, collecting data from 74 participants via convenience sampling, and analyzed the data using SPSS software for descriptive statistics (percentages, frequencies, and a chi-square test of parental perceptions of [...]

Dust accumulation on solar panels, commonly referred to as soiling, significantly reduces the energy conversion performance of Photo Voltaic (PV) systems. Dust deposition on the panel surface obstructs sunlight from reaching the cells, and combined with elevated panel temperatures and deterioration of glass optical properties, this results in substantial efficiency losses. Previous studies have reported efficiency reductions ranging from 5% to 40%, depending on dust characteristics, particle size, and environmental conditions. Such losses not only reduce total energy output but also cause considerable economic impact, particularly for large-scale solar power plants. To mitigate these effects, the scientific community has actively [...]