The processes of reflection of three-dimensional electromagnetic waves by locally irregular media interfaces are investigated. The problem under study is mathematically reduced to the solution of a boundary value problem for the Maxwell equations in an infinite space with an irregular boundary. In order to develop a numerical algorithm, the potential theory and a special…

In urban, rural and indoor applications, diffraction mechanism is very important to predict the field strength and calculate the coverage accurately. The diffraction mechanism takes place on NLOS (non-line-of-sight) cases like rooftop, vertex, corner, edge and sharp surfaces. S-UTD-CH model computes three type of electromagnetic wave incidence such as direct, reflected and diffracted waves, respectively.…

Hasty software development can produce immediate implementations with source code unnecessarily complex and hardly readable. These small kinds of software decay generate a technical debt that could be big enough to seriously affect future maintenance activities. This work presents an analysis technique for identifying architectural technical debt related to non-uniformity of naming patterns; the technique…

This paper extends some of our research results disseminated in the most recent awarded international conference paper concerning the implementation in real time of a sliding mode observer state estimator. For the same case study developed in the conference paper, more precisely a DC servomotor angular speed control system, we extend the proposed concept of…

We explore the dependency of MIMO performance on azimuthal spread (AS) and elevation spread (ES) using correlated-based stochastic models (CBSMs). We represent the transmitter as uniform rectangular array (URA), and derive an analytical function for spatial correlation, in terms of maximum power when phase gradient of the incident wave follows a Student’s t-distribution. We model…

In learning environment, portfolio is used as a tool to keep track of learner’s progress. Particularly, when it comes to e-learning, continuous assessment allows greater customization and efficiency in learning process and prevents students lost interest in their study. Also, each student has his own characteristics and learning skills that must be taken into account…

Fair allocation of risks in conditions of contract is pivotal for coordination, unhindered execution, dispute resolution and maintenance of positive relationship among the parties executing the contract. Pakistani construction industry despite subcontracting a large percentage of construction projects lacks standard conditions of subcontract and they are primarily based on the will of the prime contractor…

Developments in power electronics have enabled the widespread application of Pulse Width Modulation (PWM) inverters, notably for obtaining electricity from renewable systems. This paper critical review the previous studies in designing stand-alone inverter and modelling the inverter with two control loops to improve and provide a high-quality power of a stand-alone inverter. Multi-loop control techniques…

In this paper, an application of artificial neural network (ANN) using bayesian regularization (BR) learning algorithm  based on multilayer perceptron (MLP) model is presented for computing the operating frequency of C-shaped patch antennas (CPAs) in UHF band.  Firstly, the operating frequencies of 144 CPAs having varied dimensions and electrical parameters were simulated by the XFDTD…

Security Operations Centers (SOCs) require intrusion detection systems that achieve high detection accuracy while maintaining a low false-positive rate and robustness to evolving attack patterns. However, most existing machine learning-based approaches primarily focus on detecting known threats and often overlook distribution shifts and the reliability of generated alerts. In this paper, we propose TL-SOC, a…

Forecasting and assessing student performance are crucial for allowing educators to pinpoint deficiencies and promote grade improvement. A thorough comprehension of feature contributions is crucial for improving model interpretability and facilitating informed decision-making in academic institutions. Explainable artificial intelligence encompasses methodologies and strategies designed to deliver transparent and accessible rationales for the decisions rendered by…

This study investigated the influence of a biomass additive on the thermal performance of the inner liner of fired-clay cook-stoves. Fired-clay cook-stoves are essential cooking devices, particularly in areas with limited access to modern energy resources. The study aimed to enhance the thermal efficiency of the cook-stoves by incorporating rice husk into the inner liner…

Neural Networks derives intelligent systems and modern autonomous applications. With the complexity introduced in today’s systems, designing architectures remains open research problem in all fields. Despite many efforts to generalize, the resources required by neural architectures remain challenge. Robots design, Smart cities, IoTs …etc. become the leading industry and driving the fourth industrial revolutions. All…

Skin cancer stands among some of the fastest growing and fatal malignancies of the world as a result early and accurate diagnosis of skin cancer is essential in order to enhance patient survival and treatment prognosis. Conventional methods of diagnosis including dermoscopy and histopathological examinations are expensive and time consuming also subject to inter-observer error.…

This paper presents the design and fabrication of an electromagnetically actuated PCB-based resonating scanning micro-mirror for LiDAR applications, with optimization targeted towards low-cost fabrication and a high scanning angle. Traditional silicon MEMS-based micro-mirrors, while offering high precision and compatibility with CMOS processing, are limited by fragility at low scanning frequencies and costly fabrication processes. To…

The rapid proliferation of drones across various industries has introduced significant challenges related to privacy, security, and noise pollution. Current drone detection systems, primarily based on visual and radar technologies, face limitations under certain conditions, highlighting the need for effective acoustic-based detection methods. This paper presents a unique and comprehensive dataset of drone acoustic signatures,…

The growing integration of the Internet of Medical Things (IoMT) into healthcare has amplified the need for secure and privacy-preserving artificial intelligence. Federated Learning (FL) has emerged as a pivotal paradigm for decentralized medical data processing; however, it still faces challenges concerning data confidentiality, trust management, and scalability. This review presents an extended theoretical comparison…

Achieving targeted reliability for complex products in real-world field environments remains a persistent challenge, even when laboratory validation suggests high performance. A significant reliability gap often emerges during the initial deployment phase, typically within the first one to five years where field failure rates can be up to twice those predicted in controlled settings. Compounding…

This study establishes a method for determining whether learners have an understanding of data science. Data science requires knowledge in various fields, which makes many learners give up. To prevent learners from being discouraged, it is necessary to judge the comprehension of the principles in each specified skill. It is important to assess not only…

Deep neural networks (DNNs) have demonstrated remarkable success across a wide range of machine learning tasks. However, determining an effective network architecture, particularly the sizes of the hidden layers, remains a significant challenge and often relies on inefficient trial-and-error experimentation. In this paper, we propose an automated architecture design approach based on structurally adaptive DNNs,…

Zero Trust Architecture offers a transformative approach to network security by emphasizing ”never trust, always verify.” IoT devices, while increasingly integral to modern ecosystems, pose unique challenges for identity management and access control due to their constrained processing power, memory, and energy capabilities. In a Zero Trust framework, every IoT device is treated as a…

We address irregular polygon nesting on sheet materials with a lightweight evolutionary framework that operates directly in the layout space. The method formalizes multi-term fitness combining utilization, overlap penalties, spacing regularity, and local alignment, with all components normalized before aggregation. Feasibility is enforced by an AABB– SAT pipeline and validated via analytic ground-truth cases, degenerate…

Investment decision-making plays a pivotal role in shaping both individual and institutional economic outcomes. Given the increasing complexity and uncertainty in global markets, optimizing investment decisions has become essential for maximizing returns while managing risks. This work explores modern optimization approaches in investment decision-making, focusing on mathematical modeling techniques such as linear programming (LP), mixed-integer…

While prior research has focused on siloed approaches to equipment replacement, this study introduces an integrated decision-making framework that synergizes predictive maintenance (IoT/M), dynamic multi-criteria analysis (MCDM), and sustainability-driven material selection. By validating this model through cross-sector case studies and strategic operational planning across various industrial sectors. We demonstrate a 30% improvement in replacement timing…

As models based in artificial intelligence increase in sophistication, there is a higher demand for the integration of hardware components to heighten real-world implementations. Both facial feature tracking and shape-from-focus are known techniques in computer vision. However, the combination of these two elements, particularly in a cost-effective configuration, has not been extensively explored. In this…