The accumulation and analysis of large-scale patient data have led to breakthrough discoveries in potential flags for diseases based on pattern recognition, highlight medication efficacy, and local population health trends that would be impossible with traditional paper-based records. However, these benefits come with unique challenges posed by the application of data sharing for research and…

Service-oriented architecture has attracted attention in automotive development. The Automotive Open System Architecture (AUTOSAR) specifies Scalable Service-Oriented Middleware over IP (SOME/IP) as a key middleware for service-oriented communication in-vehicles. However, SOME/IP-based networks are vulnerable to server spoofing during the service discovery phase, enabling attackers to cause man-in-the-middle attacks by impersonating legitimate services. This paper proposes…

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,…

Complex networked systems provide a cornucopia of network statistics, many of which relate to the temporal behaviour of subsystems, devices, or even individual protocol layers. Different and flexible visualizations can play a crucial role in discovering and making patterns, relations, and trends tangible. We developed PerfVis, a tool that visualizes timestamp data to aid in…

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…

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…

In this work, we present CIRB-Edge, a novel integer compression method designed specifically to overcome the limitations of traditional techniques such as Huffman coding, Delta encoding, and dictionary-based algorithms. These legacy methods often fall short in meeting the stringent requirements of secure, energy-efficient, and real-time edge computing due to their high computational overhead, memory demands,…

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…

Establishing an environment that allows for the quantitative evaluation of the ability of autonomous driving systems to respond to real-world adverse conditions is crucial to ensuring their safety and reliability. This study proposes a dynamic scenario-based simulation framework that simulates complex and sequential hazardous scenarios frequently encountered in actual road environments. The proposed scenarios are…

The importance of MMF space harmonics in squirrel-cage induction motors has been recognized in the literature since the beginning. Their details have been analyzed over the years, but only partly systematized. In this article, however, not only the origin and the entire system of that harmonics are described, but also their interaction causing the asynchronous…

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…

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…

Gallium nitride (GaN) is expected to be used as a material for power semiconductor devices. However, it is crucial to focus on the dielectric properties of GaN. In this study, we investigated the transient response of the drain current during high-frequency application after intentionally maintaining the current collapse in the AlGaN/GaN high electron mobility transistors.…

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…

This article enhances discussions on Generative Artificial Intelligence (GenAI) and prompt engineering by exploring critical pitfalls and industry-specific advantages. It begins with a foundational overview of AI evolution, emphasizing how generative models such as GANs, VAEs, and Transformers have revolutionized language processing, image generation, and drug discovery. Prompt engineering is highlighted as a key methodology…

With the spread of inverters, the attention of designers naturally turned to 5-phase motors, due to their advantageous properties. In this regard, perhaps the most important issue in the design of such machines is the selection of the correct rotor slot number. Many articles have been published on multiphase machines, however, only few of them…

Despite the development of the Internet and wired networks such as fiber optics, mobile networks remain the most used thanks to the mobility they offer to the user. However, data protection in these networks is more complex because of the radio channels they use for transmission. Hence,there is a need to find more sophisticated data…