Inventions

The increasing number of Base Stations (BSs) and connected devices, coupled with their mobility, poses significant challenges and makes mobility management even more pressing. Therefore, advanced handover (HO) management technologies are required to address this issue. This paper focuses on the ping-pong HO problem. To address this issue, we propose an algorithm using Reinforcement Learning (RL) based on the Double Deep Q-Network (DDQN). The novelty of our approach is to assign specialized RL agents to users based on their mobility patterns. The use of specialized RL agents simplifies the learning process. The effectiveness of the proposed algorithm is demonstrated in tests on the ns-3 platform due to its ability to replicate real-world scenarios. To compare the results of the proposed approach, the baseline handover algorithm based on Events A2 and A4 is used. The results show that the proposed approach reduces the number of HO by more than four times on average, resulting in a more stable data rate and increasing it up to two times in the best case.

Additive manufacturing (AM) has emerged as a key enabling technology in contemporary dental manufacturing, driven by its capacity for customization, geometric complexity, and seamless integration with digital design workflows. This article presents a technology-oriented narrative review of additive manufacturing in dental implant production, focusing on dominant processing routes, material systems, and emerging research trends rather than a systematic or critical appraisal of the literature. An indicative descriptive analysis of publications indexed in the Web of Science and Scopus databases between 2014 and 2024 was used to contextualize the technological development of the field and identify major research directions. Emphasis was placed on metal powder bed fusion technologies, specifically Selective Laser Melting (SLM) and Direct Metal Laser Sintering (DMLS), which enable the fabrication of titanium implants with controlled porosity and enhanced osseointegration. Ceramic AM approaches, including SLA, DLP, and PBF, are discussed in relation to their potential for aesthetic dental restorations and customized prosthetic components. The publication trend overview indicates a growing interest in ceramic AM after 2020, an increasing focus on hybrid and functionally graded materials, and persistent challenges related to standardization and the availability of long-term clinical evidence. Key technological limitations—including manufacturing accuracy, material stability, validated metrology, and process reproducibility—are highlighted alongside emerging directions such as artificial intelligence-assisted workflows, nanostructured surface modifications, and concepts enabling accelerated or immediate clinical use of additively manufactured dental restorations.

This pilot study evaluated the visionMC system, a low-cost artificial intelligence system integrating HOG-based facial recognition and voice notifications, for workflow optimization in a family medicine practice. Implemented on a Raspberry Pi 4, the system was tested over two weeks with 50 patients. It achieved 85% recognition accuracy and an average detection time of 3.4 s. Compared with baseline, patient waiting times showed a substantial reduction in waiting time and administrative workload, and the administrative workload decreased by 5–7 min per patient. A satisfaction survey (N = 35) indicated high acceptance, with all scores above 4.5/5, particularly for usefulness and waiting time reduction. These results suggest that visionMC can improve efficiency and enhance patient experience with minimal financial and technical requirements. Larger multicenter studies are warranted to confirm scalability and generalizability. visionMC demonstrates that effective AI integration in small practices is feasible with minimal resources, supporting scalable digital health transformation. Beyond biometric identification, the system’s primary contribution is streamlining practice management by instantly displaying the arriving patient and enabling rapid chart preparation. Personalized greetings enhance patient experience, while email alerts on motion events provide a secondary security benefit. These combined effects drove the observed reductions in waiting and administrative times.