Intangible resources are ever-increasingly vital to individual businesses' success and competitiveness in today's emerging knowledge economy. Against this background, this study explores and empirically models the influence of Intellectual Capital on Sales Growth, with Corporate Governance as a moderator, in the Information Technology industry of Karachi. In this research, Intangible Resources comprise three dimensions of Intellectual Capital-Human Capital, Structural Capital and Relationship Capital; and three theoretical perspectives-Resource Based View, Knowledge Based View and Agency Theory. Knowledge resources are accumulated through the process of knowledge integration resulting in revenue growth through increased efficiency and effectiveness, while effective Corporate Governance determines alignment [...]

Recognition of faces with partial occlusions poses an exceptionally difficult challenge for contemporary researchers working on biometric identification tasks. Various real-life use cases in areas such as border crossings, healthcare services, smart surveillance, etc., usually require performing face identification despite masks, sunglasses, scarfs, and similar accessories blocking parts of the face, causing poor recognition performance. In this study, we conduct a systematic analysis of occluded face recognition research works that have been carried out between 2021 and 2026. After the application of inclusion/exclusion criteria to our initial database consisting of relevant peer-reviewed articles in IEEE Xplore, ScienceDirect, Springer, and arXiv [...]

The retail fuel price forecasting of emerging economies is important for the energy policy, fiscal planning and consumer welfare. Pakistan, where petrol and diesel prices are periodically revised (twice every fortnight) using an Import Parity Pricing (IPP) mechanism, is strongly influenced by changes in the international crude oil benchmarks (Brent and WTI) and Pakistani Rupee (PKR) to US dollar exchange rate. The paper presents a hybrid machine learning model that combines an autoregressive integrated moving average (ARIMA) model for trend extraction with a Random Forest (RF) regressor of nonlinear residual patterns. With real-time crude prices, historical PKR/USD weekly data (2026), [...]

The rapid urbanisation is putting pressure on city infrastructures around the world, and the Internet of Things (IoT) is the main technological layer that municipalities are using to respond. However, the literature on IoT-enabled smart cities remains fragmented: architectural frameworks, application domain studies, and challenge analyses are usually reported in isolation, with little cross comparison to guide implementation decisions. This paper addresses that fragmentation through a structured review of 61 peer-reviewed studies (2022–2024, plus select foundational works from 2013–2019) from IEEE Xplore, Elsevier, and SpringerLink. A direct comparison of three dominant IoT architectural paradigms: layered, distributed (edge/fog), and service-oriented; on [...]

Intrusion Detection Systems (IDS) are important for protecting modern the networks against increasingly known cyber-attacks. However, the traditional IDS methods are also characterized by high dimensional data, low detection accuracy and the interpretability, this research is aimed at providing an explainable intrusion detection framework to combine the ExtraTrees-based feature selection with the ensemble ML models based on UNSW-NB15 dataset. The introduced methodology will start with the in-depth of the data preprocessing, such as the handling missing values, categorical attributes, and feature normalization to improve the quality of data and model performance. ExtraTrees feature selection is subsequently performed in order to [...]