Search Results (3,017)

The integration of IoT and Ambient Assisted Living (AAL) enables discreet real-time health monitoring in home environments, offering significant potential for personalized and preventative care. However, challenges persist in balancing privacy, cost, usability, and system reliability. This paper provides an overview of recent advancements in sensor and IoT technologies for assisted living, with a focus on elderly individuals living independently. It categorizes sensor types and technologies that enhance healthcare delivery and explores an interdisciplinary framework encompassing sensing, communication, and decision-making systems. Through this analysis, this paper highlights current applications, identifies emerging challenges, and pinpoints critical areas for future research. This paper aims to inform ongoing discourse and advocate for interdisciplinary approaches in system design to address existing trade-offs and optimize performance. Full article

Background: Children with attention deficit hyperactivity disorder (ADHD) frequently encounter eating problems. However, qualitative research on the eating problems of these children and the strategies employed by their parents to manage these issues remains limited. This study aimed to explore the eating problems of school-age children with ADHD and the coping strategies used by parents in urban settings like Hong Kong. Methods: A descriptive qualitative design was utilized, employing semi-structured focus group interviews. Purposive sampling was used to recruit 12 parents who voluntarily participated in five focus group sessions. The interviews were conducted in Cantonese, audio-recorded, and transcribed verbatim. Data were analyzed using template thematic analysis to identify key themes and subthemes. Results: Two major themes emerged: challenges affecting ADHD children’s eating behaviors and parental coping strategies in Hong Kong. Children’s eating difficulties stemmed from ADHD-specific behaviors, compounded by Hong Kong’s demanding educational system and urban environmental constraints. In response, parents developed multifaceted coping approaches, ranging from dietary modifications and behavioral management strategies to healthcare resource utilization, while adapting their urban lifestyle to accommodate their children’s needs. Conclusions: Children with ADHD face eating challenges that intersect with Hong Kong’s sociocultural environment, where educational pressure, limited living spaces, and parents’ work schedules influence their eating patterns. Parents adopt integrated Eastern–Western approaches, supported by Hong Kong’s comprehensive healthcare resources spanning professional networks and community programs. Evidence-based dietary guidelines are essential to address ADHD-related nutritional misconceptions. Full article

The Enhanced 911 (E911) mandate of the Federal Communications Commission (FCC) drives the evolution of indoor three-dimensional (3D) location/positioning services for emergency calls. Many indoor localization systems exploit location-dependent wireless signaling signatures, often called fingerprints, and machine learning techniques for position estimation. In particular, received signal strength indicators (RSSIs) and Channel State Information (CSI) in Wireless Local Area Networks (WLANs or Wi-Fi) have gained popularity and have been addressed in the literature. While RSSI signatures are easy to collect, the fluctuation of wireless signals resulting from environmental uncertainties leads to considerable variations in RSSIs, which poses a challenge to accurate localization on a single floor, not to mention multi-floor or even three-dimensional (3D) indoor localization. Considering recent E911 mandate attention to vertical location accuracy, this study aimed to investigate CSI from Wi-Fi signals to produce baseline Z-axis location data, which has not been thoroughly addressed. To that end, we utilized CSI measurements and two representative machine learning methods, an artificial neural network (ANN) and convolutional neural network (CNN), to estimate both 3D and vertical-axis positioning feasibility to achieve E911 accuracy compliance. Full article

To ensure security and stable quality, deeper cybersecurity evaluations are essential for the development of safety features and functionalities in vehicles. Among these, the Autonomous emergency braking (AEB) system is the most relevant. This research presents a comprehensive Threat analysis and risk assessment (TARA) of the AEB system, emphasizing the identification, validation, and mitigation of major cybersecurity threats and risks. We systematically examine potential attack vectors by utilizing the STRIDE threat model. This approach enables a detailed analysis of each security threat associated with AEB systems, providing insights into how malicious actors could use the attack paths. The assessment aligns with ISO/SAE 21434, which offers a robust framework for risk management in automotive cybersecurity and IT security, ensuring a thorough evaluation of a system’s architecture. By assessing the AEB system’s architecture against these standards, we identify key components and communication pathways that may be particularly prone to cyberattacks. The results of this analysis highlight critical flaws within the AEB framework and propose corrective measures to enhance cybersecurity resilience. This article provides a structured methodology for assessing and mitigating automotive cybersecurity risks in compliance with industry standards, aiming to facilitate the safe implementation of AEB technology and ultimately improve overall vehicle security and safety. Full article

The rise of artificial intelligence (AI) necessitates ultra-fast computing, with on-chip terahertz (THz) communication emerging as a key enabler. It offers high bandwidth, low power consumption, dense interconnects, support for multi-core architectures, and 3D circuit integration. However, transitioning between different waveguides remains a major challenge in THz systems. In this paper, we propose a THz band mode converter that converts from a rectangular waveguide (RWG) (WR-0.43) in TE${}_{10}$ mode to a substrate-integrated waveguide (SIW) in TE${}_{20}$ mode. The converter comprises a tapered waveguide, a widened waveguide, a zigzag antenna, and an aperture coupling slot. The zigzag antenna effectively captures the electromagnetic (EM) energy from the RWG, which is then coupled to the aperture slot. This coupling generates a quasi-slotline mode for the electric field (E-field) along the longitudinal side of the aperture, exhibiting odd symmetry akin to the SIW’s TE${}_{20}$ mode. Consequently, the TE${}_{20}$ mode is excited in the symmetrical plane of the SIW and propagates transversely. Our work details the mode transition principle through simulations of the EM field distribution and model optimization. A back-to-back RWG TE${}_{10}$-to-TE${}_{10}$ mode converter is designed, demonstrating an insertion loss of approximately 5 dB over the wide frequency range band of 2.15–2.36 THz, showing a return loss of 10 dB. An on-chip antenna is proposed which is fed by a single higher-order mode of the SIW, achieving a maximum gain of 4.49 dB. Furthermore, a balun based on the proposed converter is designed, confirming the presence of the TE${}_{20}$ mode in the SIW. The proposed mode converter demonstrates its feasibility for integration into a THz-band high-speed circuit due to its efficient mode conversion and compact planar design. Full article

The gut–brain axis represents an important bidirectional communication network, with the vagus nerve acting as a central conduit for peripheral signals from the various gut organs to the central nervous system. Among the molecular mediators involved, serotonin (5-HT), synthesized predominantly by enterochromaffin cells in the gut, plays a pivotal role. Gut-derived serotonin activates vagal afferent fibers, transmitting signals to the nucleus tractus solitarius (NTS) and modulating serotonergic neurons in the dorsal raphe nucleus (DRN) as well as the norepinephrinergic neurons in the locus coeruleus (LC). This interaction influences emotional regulation, stress responses, and immune modulation. Emerging evidence also highlights the role of microbial metabolites, particularly short-chain fatty acids (SCFAs), in enhancing serotonin synthesis and vagal activity, thereby shaping gut–brain communication. This review synthesizes the current knowledge on serotonin signaling, vagal nerve pathways, and central autonomic regulation, with an emphasis on their implications for neuropsychiatric and gastrointestinal disorders. By elucidating these pathways, novel therapeutic strategies targeting the gut–brain axis may be developed to improve mental and physical health outcomes. Full article

Optoelectronic oscillators (OEOs) have emerged as indispensable tools for generating low-phase-noise microwave and millimeter-wave signals, which are critical for a variety of high-performance applications. These include radar systems, satellite links, electronic warfare, and advanced instrumentation. The ability of OEOs to produce signals with exceptionally low phase noise makes them ideal for scenarios demanding high signal purity and stability. In radar systems, low-phase-noise signals enhance target detection accuracy and resolution, while, in communication networks, such signals enable higher data throughput and improved signal integrity over extended distances. Furthermore, OEOs play a pivotal role in precision instrumentation, where even minor noise can compromise the performance of sensitive equipment. This review examines the progress in OEO technology, transitioning from classical designs relying on long optical fiber delay lines to modern integrated systems that leverage photonic integration for compact, efficient, and tunable solutions. Key advancements, including classical setups, hybrid designs, and integrated configurations, are discussed, with a focus on their performance improvements in phase noise, side-mode suppression ratio (SMSR), and frequency tunability. A 20-GHz oscillation with an SMSR as high as 70 dB has been achieved using a classical dual-loop configuration. A 9.867-GHz frequency with a phase noise of −142.5 dBc/Hz @ 10 kHz offset has also been generated in a parity–time-symmetric OEO. Additionally, integrated OEOs based on silicon photonic microring resonators have achieved an ultra-wideband tunable frequency from 3 GHz to 42.5 GHz, with phase noise as low as −93 dBc/Hz at a 10 kHz offset. The challenges in achieving fully integrated OEOs, particularly concerning the stability and phase noise at higher frequencies, are also explored. This paper provides a comprehensive overview of the state of the art in OEO technology, highlighting future directions and potential applications. Full article

The concept of Quality of Aquaculture Services (QoAS) is inspired by the Quality of Service (QoS) principle, originally developed in the field of networks and telecommunications, where it refers to the ability to guarantee the quality, availability, and priority of service in a communications system. Adapted to the aquaculture context, QoAS is fundamental to maximising the benefits of Integrated Multi-Trophic Aquaculture (IMTA). IMTA has emerged as a sustainable approach to meet the growing global demand for aquatic food products by combining species from different trophic levels in a single system, optimising resource use, improving environmental performance, and diversifying production. However, ensuring QoAS in these complex systems requires the implementation of advanced technologies to monitor, manage, and optimise every aspect of the aquaculture process. This article presents a comprehensive review of technologies applied at IMTA, focusing on IoT-based monitoring systems, resource management algorithms, water recirculation technologies, intelligent automation, biosecurity, and data management platforms. Our review finds that IoT and automation-based solutions significantly enhance real-time monitoring, increasing operational efficiency and environmental sustainability. Key challenges identified include integration complexity, high costs, and technical expertise requirements, but the ongoing development of modular, user-friendly solutions indicates a promising trajectory. This review highlights the transformative role of technological innovation in IMTA, providing a foundation for future research and advancements in QoAS management in aquaculture. Full article

Unmanned aerial vehicles (UAVs) have shown significant advantages in disaster relief, emergency communication, and Integrated Sensing and Communication (ISAC). However, the escalating demand for UAV spectrum is severely restricted by the scarcity of available spectrum, which in turn significantly limits communication performance. Additionally, the openness of the wireless channel poses a serious threat, such as wiretapping and jamming. Therefore, it is necessary to improve the security performance of the system. Recently, Reconfigurable Intelligent Surfaces (RIS), as a highly promising technology, has been integrated into Cognitive UAV Network. This integration enhances the legitimate signal while suppressing the eavesdropping signal. This paper investigates a RIS-assisted Cognitive UAV Network with multiple corresponding receiving users as cognitive users (CUs) in the presence of malicious eavesdroppers (Eav), in which the Cognitive UAV functions as the mobile aerial Base Station (BS) to transmit confidential messages for the users on the ground. Our primary aim is to attain the maximum secrecy bits by means of jointly optimizing the transmit power, access scheme of the CUs, the RIS phase shift matrix, and the trajectory. In light of the fact that the access scheme is an integer, the original problem proves to be a mixed integer non-convex one, which falls into the NP-hard category. To solve this problem, we propose block coordinate descent and successive convex approximation (BCD-SCA) algorithms. Firstly, we introduce the BCD algorithm to decouple the coupled variables and convert the original problem into four sub-problems for the non-convex subproblems to solve by the SCA algorithm. The results of our simulations indicate that the joint optimization scheme we have put forward not only achieves robust convergence but also outperforms conventional benchmark approaches. Full article

Cutaneous melanoma (CM) is an aggressive and metastatic tumor, resulting in high mortality rates. Despite significant advances in therapeutics, the available treatments still require improvements. Thus, purinergic signaling emerged as a potential pathway to cancer therapy due to its involvement in cell communication, proliferation, differentiation, and apoptosis. In addition, due to safety and acceptable clinical tolerability, carotenoids from microalgae have been investigated as adjuvants in anti-melanoma therapy. Then, this work aimed to investigate the in vitro anti-melanogenic effect of carotenoid extract (CA) and total biomass (BM) of the Scenedesmus obliquus microalgae on two cutaneous melanoma cell lines (A375 and B16F10). Cells were cultivated under ideal conditions and treated with 10, 25, 50, and 100 μM of CA or BM for 24 h. The effects of the compounds on viability, oxidant status, and purinergic signaling were verified. The IC50 cell viability results showed that CA and BM decreased B16F10 viability at 24.29 μM and 74.85 μM, respectively and decreased A375 viability at 73.93 μM and 127.80 μM, respectively. Carotenoid treatment for 24 h in B16F10 and A375 cells increased the release of reactive oxygen species compared to the control. In addition, CA and BM isolated or combined with cisplatin chemotherapy (CIS) modulated the purinergic system in B16F10 and A375 cell lines through P2X7, A2AR, CD39, and 5′-nucleotidase. They led to cell apoptosis and immunoregulation by activating A2A receptors and CD73 inhibition. The results disclose that CA and BM from Scenedesmus obliquus exhibit an anti-melanogenic effect, inhibiting melanoma cell growth. Full article

Smart fisheries are an important way to promote the sustainable development of fisheries, and efficient and reliable marine communication systems are the key to realizing smart fisheries. As an emerging marine communication technology, the VHF Data Exchange System (VDES) has the advantages of a high data transmission rate, large communication capacity, and wide coverage, providing new opportunities for the transformation and upgrading of smart fisheries. This paper introduces the technical architecture and functions of the VDES, compares it with existing marine communication technologies, analyzes the key requirements of a smart fishery, and assesses how the VDES meets these requirements. The potential application scenarios of the VDES in smart fishery fields such as fishing vessel monitoring, fishery resource management, and maritime security are discussed. The challenges faced by the VDES in the application of smart fisheries, such as technology, policies and regulations, and construction cost layout, are analyzed, and its future development trend is prospected. Suggestions such as its integration with emerging technologies, the realization of global seamless coverage, and the strengthening of international cooperation and data sharing are proposed. This paper aims to provide theoretical guidance and scientific reference for the promotion and application of the VDES in smart fisheries. Full article

As 6G development progresses, joint sensing and communication (JSC) is emerging as a transformative technology, promising enhanced spectrum and energy efficiency alongside innovative services. This paper delves into underexplored facets of JSC, particularly its role in vehicular technology and transportation systems. It discusses data fusion techniques that enable cooperative sensing in networked environments and underscores the critical role of resource management in balancing sensing and communication. It suggests modeling extended targets, such as vehicles, within a computationally feasible framework. Moreover, it proposes a novel integration of AI-based target recognition, allowing target-specific tracking parameters and target-based sensing resource allocation. Importantly, a case study is presented to underscore the real-world applicability of these concepts in vehicular scenarios, demonstrating how networked devices can achieve high sensing and communication performance. Full article

The exponential growth of Internet of Things (IoT) devices has led to massive volumes of data, challenging traditional centralized processing paradigms. The cloud–edge continuum computing model has emerged as a promising solution to address this challenge, offering a distributed approach to data processing and management and improved performances in terms of the overhead and latency of the communication network. In this paper, we present a novel resource allocation optimization solution in cloud–edge continuum architectures designed to support multiple heterogeneous mobile clients that run a set of applications in a 5G-enabled environment. Our approach is structured across three layers, mist, edge, and cloud, and introduces a set of innovative resource allocation models that addresses the limitations of the traditional bin-packing optimization problem in IoT systems. The proposed solution integrates task offloading and resource allocation strategies designed to optimize energy consumption while ensuring compliance with Service Level Agreements (SLAs) by minimizing resource consumption. The evaluation of our proposed solution shows a longer period of active time for edge servers because of the lower energy consumption. These results indicate that the proposed solution is viable and a sustainability model that prioritizes energy efficiency in alignment with current climate concerns. Full article

The measurement of image similarity represents a fundamental task within the domain of image processing, enabling the application of sophisticated computational techniques to ascertain the degree of similarity between two images. To enhance the performance of these similarity measurement algorithms, the academic community has investigated a range of quantum algorithms. Notably, the swap test-based quantum inner product algorithm (ST-QIP) has emerged as a pivotal method for computing image similarity. However, the inherent destructive nature of the swap test necessitates multiple quantum state evolutions and measurements, which leads to consumption of quantum resources and prolonged computational time, ultimately constraining its practical applicability. To address these limitations, this study introduces an advanced quantum inner product algorithm based on amplitude estimation (AE-QIP) designed to compute image similarity. This innovative approach circumvents the repetitive measurement processes associated with the swap test, thereby optimizing the utilization of quantum resources and substantially enhancing the algorithm’s performance. We conducted experiments using a quantum simulator to implement the AE-QIP algorithm and evaluate its effectiveness in the image retrieval tasks. It is found that the AE-QIP algorithm achieves comparable precision to the ST-QIP algorithm while exhibiting significant reductions in qubit consumption and average processing time. Additionally, our findings suggest that increasing the number of ancillary qubits can further enhance the accuracy of the AE-QIP algorithm. Overall, within the acceptable error thresholds, the AE-QIP algorithm exhibits enhanced efficiency relative to the ST-QIP algorithm. However, significant further research is needed to address the challenges involved in optimizing the performance of quantum retrieval systems as a whole. Full article

Underwater optical communication has emerged as an essential tool for exploring oceanography and marine resources for underwater vehicles or robots in recent years. Current techniques mostly rely on the paradigm of intensity modulation and direct detection, resorting to more powerful light sources on the transmitting side and more sensitive detectors on the receiving side, thus causing excess energy consumption and system costs. Here, a novel approach, namely, the optical differential communications method (ODCM), is proposed to extend the distance of underwater wireless optical communications in turbid water. The underlying physical reason is explained in theory and demonstrated in experiments. It is found that the stable propagation distance of ODCM could be further extended without relying on intensive light sources, in contrast to conventional methods, showing potential for longer communication ranges. Tests of underwater optical communications are conducted, and the results show that ODCM can significantly reduce the bit error rate (BER) at the same propagation distance or extend the propagation distance for the same BER level of optical signals. As such, this study provides an avenue for long-distance and stable underwater wireless optical communications in turbid environments. Full article