Provisioning of health services such as care, monitoring, and remote surgery is being improved thanks to fifth-generation cellular technology (5G). As 5G expands globally, more smart healthcare applications have been developed due to its extensive eMBB (Enhanced Mobile Broadband) and URLLC (Ultra-Reliable Low Latency Communications) features that can be used to generate healthcare systems that allow minimizing the face-to-face assistance of patients at hospital centers. This powerful network provides high transmission speeds, ultra-low latency, and a network capacity greater than that of 4G. Fifth-generation cellular technology is expected to be a means to provide excellent quality of medical care, through its technological provision to the use of IoMT (Internet of Medical Things) devices. Due to the numerous contributions in research on this topic, it is necessary to develop a review that provides an orderly perspective on research trends and niches for researchers to use as a starting point for their work. In this context, this article presents a systematic review based on PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses), with article selection based on inclusion and exclusion criteria that avoid bias. This research was based on research questions that were answered from the included works. These questions focus on technical characteristics, health benefits, and security protocols necessary for the development of smart healthcare applications. We have identified that a high percentage of existing works in the literature are proposals (56.81%, n = 25) and theoretical studies (22.73%, n = 10); few implementations (15.91%, n = 7) and prototypes (4.55%, n = 2) exist, due to the limited global deployment of 5G. However, the panorama looks promising based on proposals and future work that these technological systems allow, all based on improving healthcare for people.

This document presents the design, simulation and measurement of a new fractal ultra-wideband CPW-fed antenna (UWB). The antenna uses a basic hexagonal shape, in which different modifications are made applying concepts of fractal geometry and Notch filters to obtain the optimal model. The simulation process is detailed until obtaining the ideal structure according to the UWB characteristics. The optimal structure generated presents the Koch fractal in the first iteration, additionally, smaller hexagonal slots are strategically placed to acquire the UWB characteristics. To reject the frequency band considered for IEEE 802.11a and WLAN-HIPERLAN/2 from 5.1 to 5.9GHz, the implementation of a Notch filter in U is made in the patch. The technique used for the design of the grooves of the ground plane allows to improve the reflection in the entire range of 3.1 to 10 GHz, specifically at low frequencies. To improve reflection at high frequencies, hexagonal filters are attached to the upper corners of the patch. The dimensions optimized for this fractal antenna are 25 × 25 mm2 designed in a substrate FR4 with dielectric constant εr = 4.4, a thickness of h = 1.5 and a tangent of losses of δ = 0.02, obtaining a bandwidth of 2.38 a 9.82Ghz with a VSWR <; 2 over the entire frequency range except for the rejected frequencies for WLAN. The compact antenna has a nearly omnidirectional radiation pattern with an adequate impedance and good return loss less than -10dB over the entire UWB range, these features offer several applications within telecommunications.

In this article, the up-to-date design of an antenna in the shape of Chakana, “Andes Cross” or “Inka Cross” will be presented and meticulously analyzed. The design base-structure is a planar monopole that goes along with different modifications related to fractal geometry concepts due to its main properties miniaturization, operability, self-similarity, and space-filling. The utilization of the second iteration of Koch fractal in the ground plane and Sierpinski second iteration in the patch allows an improvement of the Ultra-Wideband (UWB)characteristics by acquiring reflection in all of the 3.1 to 10.6 GHz range designated by the Federal Communications Commission (FCC). In order to improve the reflection present in high frequencies a ground-plane Notch is used; furthermore, so as to reject the frequency band considered for IEEE 802.11A, WLAN-HIPERLAN/2 and the Industrial, Scientific and Medical band (ISM band)located between 5.15 and 5.82 GHz, the implementation of an H-shaped Notch filter on the patch is carried out. The dimensions optimized for this fractal antenna are 30mm×33mm, mounted on an FR4 substrate with dielectric constant εr=4.4, a thickness of h=1.5 and a tangent of losses of δ=0.02, obtaining a bandwidth of 3.25 to 11.36 GHz with a VSWR<;2 over the entire frequency range except for the rejected frequencies for ISM. Also, the H-Shaped Notch filter with an effective length of approximately 23.14 mm is positioned around of 4 mm from the feed line to ensure an optimal rejection of -4.85 dB at the center frequency of 5.41 GHz. Therefore, based on the combination of the fractal geometries Koch and Sierpinski proposed, a new Hybrid Fractal Antenna Design for UWB application with a nearly omnidirectional radiation pattern, adequate 50 impedance and good return loss less than -10dB over the entire UWB range is presented.

Neural network quantization has become established as a key strategy for transitioning medical imaging models from research environments to clinical devices and resource-constrained edge platforms; however, the available evidence remains fragmented and focused on highly heterogeneous use cases. This study presents a systematic review of 72 studies on quantization applied to medical images, following PRISMA guidelines, with the aim of characterizing the relationship among quantization technique, network architecture, imaging modality, and execution environment, as well as their impact on latency, memory footprint, and clinical deployment. Based on a structured variable matrix, we analyze—through tailored visualizations—usage patterns of Post-Training Quantization (PTQ), Quantization-Aware Training (QAT), mixed precision, and binary/low-bit schemes across frameworks such as PyTorch V 2.6.0, TensorFlow 2.19.0, and TensorFlow Lite, executed on server-class GPUs, edge/embedded devices, and specialized hardware. The results reveal a strong concentration of evidence in PyTorch/TensorFlow pipelines using INT8 or mixed precision on GPUs and edge platforms, contrasted with limited attention to PACS/RIS interoperability, model lifecycle management, energy consumption, cost, and regulatory traceability. We conclude that, although quantization can approximate real-time performance and reduce memory footprint, its clinical adoption remains constrained by integration challenges, model governance requirements, and the maturity of the hardware–software ecosystem.

Cultural heritage is one of many fields that has seen a significant digital transformation in the form of digitization and asset annotations for heritage preservation, inheritance, and dissemination. However, a lack of accurate and descriptive metadata in this field has an impact on the usability and discoverability of digital content, affecting cultural heritage platform visitors and resulting in an unsatisfactory user experience as well as limiting processing capabilities to add new functionalities. Over time, cultural heritage institutions were responsible for providing metadata for their collection items with the help of professionals, which is expensive and requires significant effort and time. In this sense, crowdsourcing can play a significant role in digital transformation or massive data processing, which can be useful for leveraging the crowd and enriching the metadata quality of digital cultural content. This paper focuses on a very important challenge faced by cultural heritage crowdsourcing platforms, which is how to attract users and make such activities enjoyable for them in order to achieve higher-quality annotations. One way to address this is to offer personalized interesting items based on each user preference, rather than making the user experience random and demanding. Thus, we present an image annotation recommendation system for users of cultural heritage platforms. The recommendation system design incorporates various technologies intending to help users in selecting the best matching images for annotations based on their interests and characteristics. Different classification methods were implemented to validate the accuracy of our work on Egyptian heritage.

In this article a process of animation of 3D models is proposed to transform them into virtual agents or avatars with the possibility of being used in Human-Computer interaction processes. The resulting virtual agents have been adapted as tools that serve as a starting point for the development of real-time interaction algorithms. The characteristics of the generated tools allows to deepen in techniques of machine learning and artificial intelligence, endowing to the virtual agents of movements with natural and real characteristics. It is possible to use them as puppets, capturing the movements of a person and transferring them to the animation; it is also possible to program specific sequences whose interaction processes are completely determined. Finally, the idea of developing algorithms involving artificial intelligence combined with human intelligence to improve interaction processes is proposed.