VFAST - Virtual Foundation for Advancement of Science and Technology (Pakistan)
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Prayer Rulings in the Manuscript Ganj al-Hadi by Shaykh al-Qur’an Qazi Abdul Hadi Rustami: An Analytical and Referential Exploration
Full text linkThis research paper explores the jurisprudential rulings on prayer (Ahkām al-Ṣalāh) as presented in the manuscript Ganj al-Hadi authored by Shaykh al-Qur’an Qazi Abdul Hadi Rustami (RA). The study involves critical editing, scholarly referencing (takhrīj), and Urdu translation of the manuscript’s relevant sections. Topics examined include prayer times, prerequisites, integrals and obligations of prayer, prostration of forgetfulness (sajdah al-sahw), prayer for the ill and the traveller, as well as invalidators and disliked acts during prayer. The research highlights the manuscript\u27s classical legal reasoning and its relevance to Hanafi jurisprudence.Through analytical commentary and source-based validation, the paper evaluates how Ganj al-Hadi presents structured guidance for common and exceptional prayer cases. The research contributes to Islamic legal heritage by reviving an important but lesser-known manuscript. It is hoped that this work facilitates future scholars and jurists in understanding traditional legal discourse, particularly within the South Asian Hanafi context
5G and AI: Addressing Security Challenges in Next-Generation Wireless Networks Through Machine Learning and Cryptographic Solutions
Full text linkModern wireless communication technologies are progressing very fast making it possible to deploy fifth-generation (5G) networks that have high speed with low delay and great connectivity. However, these innovative technologies also bring significant security risks as these are based on distributed environments, network slicing, and software-defined networking. Considering these threats, this research aims to examine the application of artificial intelligence and cryptographic approaches towards mitigating these risks. The use of AI in security has been highlighted to one of the best security features of current computer and network systems, especially in the case of machine learning. The Convolutional Neural Network (CNN) based detection models like GANs and Auto encoders show good detection rates but have issues of high computational load and energy consumption. Reinforcement learning models provide clients with adaptive solutions for security to change their approach as threats change. Moreover, five advanced solutions include post-quantum cryptography, homomorphic encryption, and blockchain-based authentication to enhance the security of the 5G network from unauthorized parties and data loss. These approaches are then assessed for their performance and effectiveness through experiment in enhancing aspects such as network security, performance, and efficiency in terms of energy use. However, adversarial AI attacks, block chain scalability, and the computational overhead associated with quantum-resistant encryption are still hurdles towards large-scale adoption. This paper revealed that there is the necessity to further refine the AI methods used, set standardization across the regulatory bodies, and employ highly secure cryptographic techniques for better protection of the 5G network. AI security frameworks, together with cryptographic improvements for the future generation wireless networks, can significantly improve security while maintaining efficiency and scalability, which will promote more secure future networks
AGRITECH: A Smart System for Sustainable Farming
Full text linkConventional agriculture, which requires human labor and does not use any kind of mechanism, is proved to be very less efficient and cannot meet the growing food requirements of the world. The application of IoT as a means of implementing change toward precision agriculture is presented below. The following paper describes the design of a smart agricultural system using IoT devices, Raspberry Pi, and a set of sensors: soil moisture, humidity, gas, flame, and motion sensors to improve farming. High technologies like drone and image processing are used to check the health of the plant and increase the production during the farming process.The smart system substantially enhances the productivity and utilization of resources by making smart choices. A mobile application can expand the system’s capabilities, data protection, low energy consumption and high reliability. This specific use of IoT makes farming more efficient to enable farmers to grow more crops and make more profits as a positive step towards sustainable farming. From the research, the authors have been able to show how IoT can be implemented in agriculture to facilitate better yield, resource utilization, and its sustainable utilization.The implementation of IoT-based smart agriculture systems significantly enhanced farming efficiency, resource utilization, and crop yield. Results indicate improved decision-making, reduced manual labor, and increased productivity through automated monitoring and mobile-based control
Integrating Behavior Driven Testing Approach with Cypress and Cucumber
Full text linkSoftware testing is integral to ensuring the functionality and quality of applications. This study highlights the implementation of Cypress and Node.js by the Nokia RON team to address the challenges of GUI testing. The adoption of Cypress enabled comprehensive and targeted testing, alongside efficient resolution of dependency and third-party package issues through selective installation. By integrating Cypress with Cucumber, an easy-to-use interface was developed to transform smoke test checklists into Gherkin syntax, enhancing readability and adaptability. Additionally, the use of Mochawesome Reporter provided detailed HTML reports, facilitating issue tracking and quick resolutions. This methodology, supported by a structured questionnaire, fostered stakeholder satisfaction and collaboration, resulting in an interactive and effective testing environment. The findings emphasize the role of Behavior Driven Development (BDD) in streamlining automated testing, improving communication among stakeholders, and ensuring higher software quality
Lightweight Cryptographic Algorithm Development Using Fundamental Cryptographic Techniques
Full text linkCryptography is used to make data and information transmission and computational systems secure over the networks by using mathematical and scientific techniques. The cryptographic algorithm should fulfil the conditions of authentication, confidentiality, integrity and reliability. In today’s era, where digital communication and data storage is increasing day by day and the data leakage, breaches and attacks are continuously rising. The increase in need of strong and secure cryptography algorithms to protect user information that ensures the integrity and confidentiality of data. The existing symmetric cryptographic algorithms like AES or DES, can provide strong security but they have very complex implementations and requires high computational resources. The aim of this paper is to provide a study for the research done in the field of cryptography, cryptographic techniques and to propose and developed a light weight symmetric cryptographic algorithm using different fundamental cryptographic techniques that is secure and fulfils the conditions of authentication, confidentiality, integrity and reliability
Supervised Learning Approach for Intrusion Detection in Unbalanced Network Traffic
Full text linkIntrusion detection systems (IDS) serve as critical sentinels in network security, assuming a paramount role in identifying and mitigating potential threats. With the evolution of our digital landscape, robust and productive intrusion detection mechanisms have become increasingly imperative. The significance of IDS lies in their ability to safeguard network resources’ integrity, confidentiality, and availability. In an era where cyber threats constantly evolve in complexity and scale, IDS serves as the front line of defence, tirelessly monitoring network traffic to pinpoint suspicious activities and mitigate potential security breaches. To address the class imbalance problem, the Synthetic Minority Over-sampling Technique (SMOTE) was applied to pre-process the CIC-IDS 2017 and NSL-KDD 2009 datasets. Advanced machine learning technique is harnessed to enhance IDS capabilities, specifically through utilising Support Vector Machines (SVM) for subsequent classification tasks. The experimental outcomes on both datasets unveil exceptional accuracy of 99% and performance across multiple intrusion types, underscoring the effectiveness of our SVM-based approach in strengthening IDS
Exploring IIoT: Wireless Control Systems with ESP8266 as a Web-ServerController— Basic Experimentation
Full text linkThis research presents the design and implementation of a low-cost, modular Industrial Internet of Things training kit aimed at enhancing hands-on IIoT education in academic and experimental settings. The primary goal was to bridge the gap between theoretical learning and practical industrial automation through the development of a WiFi-enabled educational trainer based on the ESP8266 microcontroller. The system integrated DC and AC loads to simulate real-world electromechanical components commonly found in flexible manufacturing systems and computer integrated manufacturing. A web-based graphical user interface was developed using HTML, CSS and C++ within the Arduino IDE, facilitates wireless control. Seven different basic and fundamental experiments were conducted focusing on hardware architecture, device interfacing, wireless communication, and internet network connectivity. Results demonstrated effective control of resistor connected LED, DC, and three-phase AC loads, with a control response time of less than 250±2 ms and a wireless range up to approximately 30±2 meters. The uniqueness of the work is its scalable design that is accessible and IIoT literate, particularly in the developing countries, such as Pakistan. Although the limitations are limited to basic analytics and absence of encryption, the limitations are to be improved eventually. The kit provides a viable basis of IIoT skill building and helps in smart manufacturing projects that are in line with Industry 4.0
Advancing NLP for Shahmukhi Punjabi: Word Embedding and Text Classification with a Novel Dataset
Full text linkThe Punjabi language occupies a large pool in today’s era; millions speak it. Only in Pakistan, 80 million people speak the Punjabi language in the province of Punjab. However, with this Big Market Cap, there has yet to be any proper research available. This research focuses on the Punjabi Language, especially the Shahmukhi Punjabi language, famous in Pakistan and Asia. However, it needs to be given more attention in the existing research. There needs to be an adequately supervised established dataset available with large data. Till now, there has yet to be any proper research on Word Embedding and Classification. This paper introduced the crafted dataset for the Shahmukhi Punjabi language dataset. It is also based on advanced NLP techniques like Word2Vec and SDfasttext for Word Embedding to capture the semantic relation within the language. In addition, we investigated the applications of six distinct classification models to analyze four different categories: News, Ghazal, Dohra, and Poetry. The notable success of the Naive Bayes classifier with other classification models lays the groundwork for future research and applications in natural language processing for the Punjabi language. The study encourages further exploration and the development of tailored solutions to meet the linguistic diversity in digital environments and apply deep learning models
Automated Fetal Femur Segmentation and Length Measurement in Ultrasound Images: A Key Tool for Accurate Gestational Age Assessment
Full text linkAccurate gestational age (GA) estimation in the second and third trimesters is crucial for effective prenatal care. It is typically determined by measuring fetal femur length (FL) in ultrasound (US) images. However, manual FL measurements are time-consuming and require expertise, leading to the need for automation. This study aims to develop an automated multi-step approach to improve FL measurement accuracy while addressing common US challenges such as speckle noise, shadows, and low signal-to-noise ratio (SNR). The proposed method includes image acquisition, preprocessing for contrast enhancement, speckle noise reduction using a bilateral filter, k-means clustering for initial femur segmentation, and morphological analysis to isolate the femur for precise FL measurement. The approach achieved a Dice similarity coefficient of 93.18±9.54% and a mean measurement difference of 0.062 cm compared to manual assessments, with 95% limits of agreement from -1.06 cm to 1.19 cm, confirming its accuracy and clinical reliability. These results demonstrate that the proposed method enhances FL measurement accuracy, reduces manual workload, and contributes to more reliable GA estimation, making it a valuable tool for prenatal care
On the Sources of the Sirah of the Prophet Muhammad (ﷺ): An Analytical Study of Harald Motzki’s Book, The Biography of Muhammad: The Issue of Sources, from the Perspective of Islamic Teachings
No full textThe biography of Prophet Muhammad (SAW) has been the subject of numerous writings. Without the constraints and restrictions of time and space, scholars illuminated every aspect of the Prophet\u27s life. They brought the economic, social, political, and individual facets into discussion. They thoroughly studied the numerous sources discussing the prophet\u27s life. Westerners actively participated in this competition and played a significant role in the development of important Sira literature. The study of Hadith of Goldziher and Schacht etc., also sparked a debate about the reliability of the Sources of Sira in the West. They reexamined the issues of the Prophet\u27s biography\u27s sources in the latter half of the 20th century. Some orientalists, such as Cook and Crone, blatantly dispute the validity of Islamic sources. Others are attempting to rebuild the Sira tradition while considering them somewhat credible. The problems pertaining to Sira\u27s sources are also addressed in the work under examination: The Biography of Muhammad: The Issue of Sources. It is an assortment of studies written by various academics that address the problems. This collection of essays, compiled by Harald Motzki, is the outcome of a colloquium that was convened in October 1997 at the University of Nijmegen in the Netherlands to address the challenge of reconstructing the life of the Islamic prophet using the primary Arabic sources. The work is critically examined and analyzed in brief in this article