IUB Journals (Islamia University of Bahawalpur)
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خلافتِ راشدہ کا زرعی نظام اور جدید ریاستی پالیسیاں: The Agricultural System of the Rashidun Caliphate and Modern State Policies
No full textThe period of the Rashidun Caliphate (11–40 AH / 632–661 CE) occupies a central place in the history of Islamic civilization. It represents the formative era in which the foundations of Islamic governance, economy, and social justice were practically implemented under the leadership of the Rightly Guided Caliphs — Abu Bakr al-Ṣiddīq, ʿUmar ibn al-Khaṭṭāb, ʿUthmān ibn ʿAffān, and ʿAlī ibn Abī Ṭālib (may Allah be pleased with them all). Among the various administrative and economic developments of this era, the agricultural system stands out as a cornerstone of economic stability, food security, and social welfare. Agriculture was not only a means of livelihood but also a manifestation of the Qur’ānic vision of productive labor, justice in resource distribution, and the ethical stewardship of land. The Rashidun Caliphs introduced policies that balanced ownership rights with social responsibility. Through instruments such as ‘ushr (tithe), kharāj (land tax), fay’ (state revenue from non-military sources), and the establishment of public lands, the state ensured a fair and sustainable management of agricultural resources. These measures reflected the Caliphs’ commitment to equity, efficiency, and public interest (maṣlaḥah)
Regulating Halal in Cosmetics Ingredients: A Comparative Study of Pakistan and International Standards
No full textThe global cosmetics industry has undergone rapid expansion, accompanied by increasing regulatory scrutiny and ethical concerns regarding product safety, ingredient sourcing, and consumer transparency. In Pakistan, cosmetic products are regulated under the Drug Regulatory Authority of Pakistan (DRAP) Act and associated rules, while internationally, frameworks such as the European Union Cosmetics Regulation (EC No. 1223/2009), the U.S. Food and Drug Administration (FDA) guidelines, and ISO standards govern formulation, labeling, and safety assessment. This study critically examines cosmetic ingredients within the context of national and international regulatory standards, with special attention to substances derived from animal, microbial, or synthetic sources that may raise concerns regarding halal status, impurity (Najāsah), and transformation. By integrating contemporary cosmetic science with classical and modern Islamic jurisprudence, the research evaluates how Sharia principles such as the prohibition of harm, the avoidance of intoxicants and impure substances, and the objectives of Islamic law (maqāṣid al-sharīʿah) can coexist with modern cosmetic regulations.
This study aims to critically evaluate the sharia permissibility of cosmetics ingredients particularly those derived from human, animals, aquatic animals, insects, plants and biotechnological sources by comparing Pakistan standard and international standards. The study further highlights gaps in ingredient source disclosure and halal certification within Pakistan’s cosmetic market, emphasizing the need for harmonization between regulatory compliance and religious ethics. The findings suggest that while international and Pakistani standards effectively address safety and quality, incorporating Sharia based guidelines particularly regarding ingredient sourcing and transparency can enhance consumer trust and ethical accountability. The study concludes that a multidisciplinary framework combining scientific regulation, legal governance, and Islamic ethical oversight is essential for the sustainable development of the cosmetics industry in Muslim societies
Factors Affecting Behavioural Intention to Visit Tourist Attractions in Pakistan: Evidence from Social Media Users in Pakistan
No full textSocial media is rapidly evolving across every field worldwide, with tourism being no exception. Pakistan has enormous potential in its tourism industry, which can be augmented through promotion on social media. This research aims to determine the role of social media in affecting the behavioural intent to visit tourist attractions in Pakistan. The data for this study were collected from 225 participants, all active social media users living in major cities across Pakistan. Data acquisition for this study employed convenience and snowball sampling methodologies, and SPSS software was utilised for multiple regression and reliability analysis. Our results of the hypothesis test showed that the positive experiences of travellers, information search regarding travel and tourism promotion play a significant and positive role in building their behavioural intention to travel to the tourism venues or sites in Pakistan. Despite recent negative influences from social media, we aim to promote Pakistani tourist sites through social media by actively requesting visitors to share positive and uplifting reviews. In parallel, we seek to empower the public with greater knowledge about the worth and basic structure of the tourism industry, to achieve a renewed and enduring growth in tourism
Book Review: Zia-un-Nabi by Justice Muhammad Karam Shah al-Azhari
No full textZia-un-Nabi by Justice Muhammad Karam Shah al-Azhari (1918-1998) represents one of the most comprehensive Urdu Seerah works of the modern era. Spanning seven volumes published between 1972 and the 1990s, it traces the Prophet Muhammad’s PBUH life from pre-Islamic Arabia to the final years in Madinah, integrating Qur’anic exegesis, Hadith scholarship, and historical analysis. Distinctively, Karam Shah grounds his narrative in the Qur’an and authentic Hadith, employing rigorous methodologies of isnād evaluation and tarjīḥ to reconcile classical sources. The concluding volume addresses and refutes major Orientalist critiques, particularly those of Goldziher, Muir, and Watt, by highlighting methodological biases and affirming the Qur’an’s divine coherence as ultimate evidence of prophethood. Combining devotional reverence with scholarly precision, Zia-un-Nabi stands as both an intellectual defense of Islamic tradition and a spiritually enriching contribution to modern Seerah literature
Enhancing Business Cycle Forecasting in Pakistan: A Composite Leading Indicator Approach with PLS-SEM
No full textObjective: This study aims to forecast the business cycles in Pakistan by developing Composite Leading Indicators (CLI) that capture multi-dimensional interactions between real, monetary, and external sectors of the economy.
Research Gap: Although the econometric techniques, like OLS, VAR, and ARIMA, proved to be valuable but they failed to capture more complex and multi-dimensional interactions between real, monetary and external sectors. This paper fills that gap by constructing Composite Leading indicators to forecast business cycles for Pakistan’s economy
Design/Methodology/Approach: Based on quarterly data between 2011 and 2025, the model incorporates major indicators like narrow money, export volumes, household debt, household prices, policy rates, real effective exchange rates, and global economic conditions and constructs a CLI model through Partial Least Squares Structural Equation Modeling (PLS-SEM).
The Main Findings: The findings indicate that the short-run liquidity and export performance have the highest direct impact on the volatility of GDP whereas the medium-run financial imbalances, such as household debt and household prices, have a key countercyclical role in spurring downturns provided they are not sufficiently reduced. The model captures a considerable proportion of the variance of GDP growth, as non-linear.
Theoretical / Practical Implications of the Findings: This study demonstrates the practicality of a multi-horizon framework of CLI estimation using PLS-SEM in that it can be used to construct more efficient early warning mechanisms and can aid policymakers in the smarter macroeconomic planning against domestic and external shocks.
Originality/Value: This research offers a novel application of PLS-SEM in business cycle forecasting for a developing economy, providing new insights into non-linear macro-financial linkages rarely explored in Pakistan’s context.
 
Role of Earnings Management and Digitalization in Explaining the Relationship Between Audit Quality and Value Addition: Insights from China
No full textThis study examines the complex relationship of audit quality and value addition, considering the mediating roles of access to finance and ESG performance, and moderating roles of digitalization and earnings management in Chinese non-financial firms. Seemingly Unrelated Regression (SUR) system is used for unbalanced panel data to test the parallel mediation and double moderation proposed. Our findings show that the relationship between audit quality and value addition is in fact quite complex. Where ESG performance and capital constraints show a full, parallel, and negative mediating role between audit fees and value addition. Similarly, digitization positively moderates the association of audit fees and capital constraints, and earnings management negatively moderates the association between audit fees and both mediators. Given China’s unique institutional environment, characterized by state-influenced financing structures and rapid digital transformation, these findings offer valuable insights into how audit quality interacts with technology and sustainability in adding value for firms. Our findings suggest that Chinese firms need to integrate digitalization with ESG metrices, to ensure value addition. Finally, policymakers in China also need to consider the consequence of improved audit quality on capital access of firms and promote transparency in ESG reporting that may help support firms in value addition without being penalized by overly conservative investor reactions
Optimizing Blockchain Scalability: Enhancing Consensus Mechanisms with Nodetovector Algorithms
No full textBlockchain technology has revolutionized industries with its decentralized and secure data management and transaction capabilities. However, scalability remains a critical challenge as blockchain networks expand. This study investigates the integration of TensorFlow with Node2Vec embeddings to optimize consensus mechanisms, focusing on enhancing blockchain scalability. Using the Hyperledger Fabric framework, experiments simulated and analyzed system performance metrics including block size, timeout, arrival rate, and probability of timeout. Data analysis revealed significant variability and trends critical for machine learning modeling. The study shows that using the model with embeddings and Principal Component Analysis (PCA) for visualization, for feature reduction performed better than traditional Linear Regression. The Mean Squared Error (MSE) was 0.0341 compared to 0.0658 highlighting the effectiveness of AI techniques in improving abilities and addressing scalability challenges in networks. This research aims to advance analytics in technology by showcasing how integrating TensorFlow with Node2Vec embeddings can enhance network efficiency and scalability bridging the gap between theory and practice to drive innovation, in decentralized data management and secure transaction processing
Advanced Malicious Behavior Classification Using a Refined ANN-CNN Model : A Hybrid Deep Learning Approach for Enhanced Cybersecurity Threat Detection
No full textThe rapid growth of the internet has led to an overwhelming increase in online data. Activities such as data transfer, online banking, and business transactions are now conducted over the internet, which, while providing convenience, also presents opportunities for malware developers to exploit vulnerabilities. Cybercriminals use sophisticated methods to bypass security measures, stealing personal data and demanding ransom from victims. To address these growing threats, there is a critical need for more advanced AI-based methods to detect and prevent malware attacks.
In this paper, we propose an improved hybrid ANN-CNN sequential model designed to enhance malware classification performance. Class imbalance is addressed using the SMOTE technique, which ensures that all classes are equally represented. Additionally, Principal Component Analysis (PCA) is employed for feature selection, enabling the model to focus on the most meaningful features and improving both training efficiency and model accuracy.
The model is evaluated on three multiclass datasets: WSN (Wireless Sensor Network), Microsoft Malware, and Virus Malware Digit. The proposed model achieved 98.1%, 99.6%, and 99.0% accuracy, respectively, demonstrating its effectiveness in handling complex, imbalanced, and diverse malware datasets
Multi-Scale Human Pose Estimation Using Morphological Segmentation and Deep Learning
No full textThe intersection of computer vision, computer graphics, and machine learning leads to human modeling and pose estimation. Human pose estimation has been and continues to be a challenging issue in computer vision because of occlusions, differences in sizes of bodies, and intricate joint movements. Even with recent breakthroughs in deep learning, correctly identifying salient events in real-world settings remains a major challenge. To solve these problems, we introduce a new approach to accurate human pose estimation that combines morphological segmentation with deep learning. Morphological operations help segment the input images, and Convolutional Neural Network (CNN) architecture like VGG16 is utilized to extract significant features from the segmented images, which are then classified using classifiers. The model, which is proposed, is trained on two publicly shared datasets, MPII and LSP, to capture diverse human poses with varying conditions and scales. We emphasize the success of our approach in attaining sophisticated results in human pose estimation tasks by engaging in extensive testing and evaluation. Our method effectively deals with occlusions and intricate poses along with accurately detecting key points. We also highlight the model's interpretability and generalizability, presenting its strength in numerous real-life scenarios
ڈاکٹر محمد اقبال نسلِ نو کے لیے ایک پُراُمید شاعر و راہنما : Dr. Muhammad Iqbal: An Optimistic Poet and Guide for the New Generation
No full textAbstract
Muhammad Iqbal was a prominent Muslim leader, thinker, philosopher, and a poet full of hope in the last century. He was well-versed in Western sciences and philosophy, as well as in Quranic knowledge, which is evident in his poetry. He had a deep understanding of Islamic history, which enabled him to identify the causes of the rise and fall of Muslims. He sought to connect the younger generation with their ancestors, emphasizing that they achieved greatness by following the guidance of the Quran. However, he lamented that despite being part of that legacy, they were living in subjugation due to their unfamiliarity with Quranic teachings.
The study of history reveals that the Muslim community has experienced many ups and downs. During the final period of British rule; Muslims were once again on the path of revival and renewal. For this reason, Dr Iqbal not only encouraged the youth of the Muslim community to rise again but also announced to them the promise of superiority in the world.
Iqbal fundamentally sought a complete revolution, placing his hopes on the Muslim community, which he believed could bring about such a change by establishing a new system in the contemporary era. His concept of "Khudi" was the essence of this revolution, through which he anticipated the revival of Islam. This paper will discuss the revival of Islam and Iqbal's comprehensive philosophy, focusing on his role as a guide and symbol of hope for the younger generation, as well as his expectations for them.
Keywords: Iqbal, Poetry, Khudi, Youth, Islam, Muslims, Leader, Thinker