In regions like the African equatorial region, where ground-based sensors like ionosondes and incoherent scatter radars are limited, satellite-based radio occultation (RO) observations offer a new alternative for ionospheric data collecting and optimization. Using RO measurements from the mostly newly launched COSMIC-2 (Constellation Observing System for Meteorology, Ionosphere, and Climate-2) mission, hence, the equatorial Africa,…

Ensuring the quality of higher education in Brazil presents a complex challenge, intensified by factors that directly affect students’ academic performance. The pervasive influence of social media and the overconsumption of superficial digital content undermine students’ ability to engage in deep comprehension, critical thinking, and the practical application of knowledge. Furthermore, inadequate preparation during the…

Understanding and responding to customer feedback is critical for business success. Customer response data offers valuable insights into preferences, behaviours, and sentiment. By analysing this data, businesses can optimize strategies, enhance customer experiences, and drive growth. Many analysis have been conducted in this field, while the review covers a broad range of AI and ML…

Persistent anomalies in modern photovoltaic (PV) systems present a formidable challenge, impeding optimal power output and system resilience. Artificial Intelligence (AI) has surfaced as a game-changing solution, yet existing research has merely scratched the surface of solar panel prognosis, leaving a critical void in leveraging AI’s explainable nature and active learning capabilities. This pioneering study…

This study presents a novel alternative to traditional Net Energy Metering (NEM) by proposing a set of innovative pricing schemes for solar customers participating in utility-led grid service programs through the aggregation of Distributed Energy Resources (DERs). Grounded in cooperative game theory, the proposed framework facilitates equitable and efficient value allocation among key stakeholders, namely…

This study aims to examine the impact of Gen AI utilization on students’ visual literacy skills using a quantitative approach and data instruments in the form of post-test scores of the control class and experimental class which are analyzed to measure the effectiveness of GEN AI in improving students’ visual literacy skills at four universities.…

The purpose of this paper is to explore the feasibility and development trend of utilizing smart medical technology for chronic disease health management in older people in the context of ageing at home. As the ageing society intensifies, the elderly population faces multiple health challenges, especially the management of chronic diseases. This paper analyzes the…

Natural language processing (NLP) techniques have transformed a number of tasks in the modern age of information explosion where millions of gigabytes of data are generated every day. Despite achieving state-of-the-art performance in high-resource languages, current techniques struggle with processing under-resourced languages which are characterized by data scarcity, linguistic diversity, computational limitations, ambiguity of language…

The rapid expansion of digital universities across Africa addresses the need for scalable higher education solutions, but challenges such as limited physical infrastructure and high dropout rates persist. In digital learning environments, effective interaction with educational content is crucial for student success. This article explores the transformative role of chatbots integrated into digital university platforms,…

Deep Neural Networks (DNNs) prove to be susceptible to synthetically generated samples, so-called adversarial examples. Such adversarial examples aim at generating misclassifications by specifically optimizing input data for a matching perturbation. With the increasing use of deep learning on embedded devices and the resulting use of quantization techniques to compress deep neural networks, it is…

In recent years, the utilization of tangible educational materials has attracted attention on educational settings. They provide hands-on learning experiences for beginners. This trend is especially notable in the field of programming education. Such educational materials are employed in many institutions worldwide. They liberate learners of programming from programming languages that are confined in a…

This manuscript offers an in-depth analysis of Explainable Artificial Intelligence (XAI), em- phasizing its crucial role in developing transparent and ethically compliant AI systems. It traces AI’s evolution from basic algorithms to complex systems capable of autonomous de- cisions with self-explanation. The paper distinguishes between explainability—making AI decision processes understandable to humans—and interpretability, which provides…

Insufficient information is often pointed out as one of the main problems with bug reports as most bugs are reported manually, they lack detailed information describing steps to reproduce the unexpected behavior, leading to increased time and effort for developers to reproduce and fix bugs. Current bug reporting systems lack support for self-hosted systems that…

SME big data maturity models will be reviewed in this study to identify systematic publications related to the subject. For SMEs to remain competitive, digitalization is essential. Due to limited resources, SMEs need to be more proactive in digitalization. Still, the benefits, such as operational efficiency, cost reduction, quality improvement, and innovative culture, make digitalization…

The Mind Monitoring System (MIMOSYS) is a novel voice analysis technique for mental health assessment that has been validated in some languages; however, no research has been conducted on the Vietnamese yet. This study aimed to examine the ability of the Vitality score extracted from the MIMOSYS system to assess depression status based on the…

This paper presents a system that combines speech and pointing gestures along with four distinct hand gestures to precisely identify both the object of interest and parameters for robotic tasks. We utilized skeleton landmarks to detect pointing gestures and determine their direction, while a pre-trained model, trained on 21 hand landmarks from 2D images, was…

This study addresses the need for improved prognostics in switch-mode power supplies (SMPS) that incorporate electromagnetic interference (EMI) filters, with a focus on aluminum electrolytic capacitors, which are critical for the reliability of these systems. The primary aim is to develop a robust model-based approach that can accurately predict the degradation and operational lifetime of…

This paper presents a method for automatic 3D segmentation of brain tumors in MRI using optical scanning holography. Automatic segmentation of tumors from 2D slices (coronal, sagittal and axial) enables efficient 3D reconstruction of the region of interest, eliminating the human errors of manual methods. The method uses enhanced optical scanning holography with a cylindrical…

Polyfluoroalkyl substances (PFAS) are persistent chemicals that accumulate in the body and environment. Although recent studies have indicated that PFAS may disrupt kidney function, the underlying mechanisms and overall effects on the organ remain unclear. Therefore, this study aims to elucidate the impact of PFAS on kidney health using machine learning techniques. Utilizing a dataset…

While Virtual reality is becoming more popular, 360-degree video transmission over the Internet is challenging due to the video bandwidth. Viewport Adaptive Streaming (VAS) was proposed to reduce the network capacity demand of 360-degree video by transmitting lower quality video for the parts of the video that are not in the current viewport. Understanding how…

Being known as an irreversible neurodegenerative disease which has no cure to date, detection and classification of Alzheimer’s disease (AD) in its early stages is significant so that the deterioration process can be slowed down. Generally, AD can be classified into three major stages, ranging from the “normal control” stage with no symptoms shown, the…

The integration of distributed energy resources has ushered in a host of complex challenges, significantly impacting power quality in distribution networks. This work studies these challenges, exploring issues such as voltage fluctuations and escalating power losses caused by the integration of solar systems and electric vehicle (EV) chargers. We present a robust methodology focused on…

Automated systems are increasingly exerting influence on our lives, evident in scenarios like AI-driven candidate screening for jobs or loan applications. These scenarios often rely on eXplainable Artificial Intelligence (XAI) algorithms to meet legal requirements and provide understandable insights into critical processes. However, a significant challenge arises when some XAI methods lack determinism, resulting in…

The navigation control of an autonomous vehicle can be determined by the coordinates of a GPS (Global Positioning System) positioning system, angular velocity, and acceleration with an INS (Inertial Navigation System). However, the errors associated with these devices do not allow it to be the only measurement system used in an autonomous vehicle. The need…

The integration of fluctuating renewable resources such as wind and solar into existing power systems poses challenges to grid reliability and the seamless incorporation of these resources. To address the inherent variability in renewable generation, direct load control emerges as a promising method for demand-side management. Thermostatically controlled appliances, like air conditioners, hold a significant…