ANGELAH: A Framework for Assisting Elders At Home

The ever growing percentage of elderly people within modern societies poses welfare systems under relevant stress. In fact, partial and progressive loss of motor, sensorial, and/or cognitive skills renders elders unable to live autonomously, eventually leading to their hospitalization. This results in both relevant emotional and economic costs. Ubiquitous computing technologies can offer interesting opportunities for in-house safety and autonomy. However, existing systems partially address in-house safety requirements and typically focus on only elder monitoring and emergency detection. The paper presents ANGELAH, a middleware-level solution integrating both ”elder monitoring and emergency detection” solutions and networking solutions. ANGELAH has two main features: i) it enables efficient integration between a variety of sensors and actuators deployed at home for emergency detection and ii) provides a solid framework for creating and managing rescue teams composed of individuals willing to promptly assist elders in case of emergency situations. A prototype of ANGELAH, designed for a case study for helping elders with vision impairments, is developed and interesting results are obtained from both computer simulations and a real-network testbed

Stochastic simulation of destruction processes in self-irradiated materials

Self-irradiation damages resulting from fission processes are common phenomena observed in nuclear fuel containing (NFC) materials. Numerous $\alpha$-decays lead to local structure transformations in NFC materials. The damages appearing due to the impacts of heavy nuclear recoils in the subsurface layer can cause detachments of material particles. Such a behaviour is similar to sputtering processes observed during a bombardment of the material surface by a flux of energetic particles. However, in the NFC material, the impacts are initiated from the bulk. In this work we propose a two-dimensional mesoscopic model to perform a stochastic simulation of the destruction processes occurring in a subsurface region of NFC material. We describe the erosion of the material surface, the evolution of its roughness and predict the detachment of the material particles. Size distributions of the emitted particles are obtained in this study. The simulation results of the model are in a qualitative agreement with the size histogram of particles produced from the material containing lava-like fuel formed during the Chernobyl nuclear power plant disaster.Comment: 11 pages, 8 figure

REFWA: An Efficient and Fair Congestion Control Scheme for LEO Satellite Networks

科研費報告書収録論文(課題番号:17500030/研究代表者:加藤寧/インターネットと高親和性を有する次世代低軌道衛星ネットワークに関する基盤研究

A Dynamic Service Level Negotiation Mechanism for QoS Provisioning in NGEO Satellite Networks

科研費報告書収録論文(課題番号:17500030/研究代表者:加藤寧/インターネットと高親和性を有する次世代低軌道衛星ネットワークに関する基盤研究

On how to Mitigate the Packet Reordering Issue in the Explicit Load Balancing Scheme

科研費報告書収録論文(課題番号:17500030/研究代表者:加藤寧/インターネットと高親和性を有する次世代低軌道衛星ネットワークに関する基盤研究

A Stable Routing Protocol to Support ITS Services in VANET Networks

科研費報告書収録論文(課題番号:17500030/研究代表者:加藤寧/インターネットと高親和性を有する次世代低軌道衛星ネットワークに関する基盤研究

Empowering Patient Similarity Networks through Innovative Data-Quality-Aware Federated Profiling

Continuous monitoring of patients involves collecting and analyzing sensory data from a multitude of sources. To overcome communication overhead, ensure data privacy and security, reduce data loss, and maintain efficient resource usage, the processing and analytics are moved close to where the data are located (e.g., the edge). However, data quality (DQ) can be degraded because of imprecise or malfunctioning sensors, dynamic changes in the environment, transmission failures, or delays. Therefore, it is crucial to keep an eye on data quality and spot problems as quickly as possible, so that they do not mislead clinical judgments and lead to the wrong course of action. In this article, a novel approach called federated data quality profiling (FDQP) is proposed to assess the quality of the data at the edge. FDQP is inspired by federated learning (FL) and serves as a condensed document or a guide for node data quality assurance. The FDQP formal model is developed to capture the quality dimensions specified in the data quality profile (DQP). The proposed approach uses federated feature selection to improve classifier precision and rank features based on criteria such as feature value, outlier percentage, and missing data percentage. Extensive experimentation using a fetal dataset split into different edge nodes and a set of scenarios were carefully chosen to evaluate the proposed FDQP model. The results of the experiments demonstrated that the proposed FDQP approach positively improved the DQ, and thus, impacted the accuracy of the federated patient similarity network (FPSN)-based machine learning models. The proposed data-quality-aware federated PSN architecture leveraging FDQP model with data collected from edge nodes can effectively improve the data quality and accuracy of the federated patient similarity network (FPSN)-based machine learning models. Our profiling algorithm used lightweight profile exchange instead of full data processing at the edge, which resulted in optimal data quality achievement, thus improving efficiency. Overall, FDQP is an effective method for assessing data quality in the edge computing environment, and we believe that the proposed approach can be applied to other scenarios beyond patient monitoring

ELB: An Explicit Load Balancing Routing Protocol for Multi-Hop NGEO Satellite Constellations

科研費報告書収録論文(課題番号:17500030/研究代表者:加藤寧/インターネットと高親和性を有する次世代低軌道衛星ネットワークに関する基盤研究

Design Guidelines for a Global and Self-Managed LEO Satellites-Based Sensor Network

科研費報告書収録論文(課題番号:17500030/研究代表者:加藤寧/インターネットと高親和性を有する次世代低軌道衛星ネットワークに関する基盤研究