Data-driven classification of low-power communication signals by an unauthenticated user using a software-defined radio

Many large-scale distributed multi-agent systems exchange information over low-power communication networks. In particular, agents intermittently communicate state and control signals in robotic network applications, often with limited power over an unlicensed spectrum, prone to eavesdropping and denial-of-service attacks. In this paper, we argue that a widely popular low-power communication protocol known as LoRa is vulnerable to denial-of-service attacks by an unauthenticated attacker if it can successfully identify a target signal's bandwidth and spreading factor. Leveraging a structural pattern in the LoRa signal's instantaneous frequency representation, we relate the problem of jointly inferring the two unknown parameters to a classification problem, which can be efficiently implemented using neural networks.Comment: Accepted for presentation at Asilomar Conference on Signals, Systems, and Computers, 202

Maximal Dissent: a State-Dependent Way to Agree in Distributed Convex Optimization

Consider a set of agents collaboratively solving a distributed convex optimization problem, asynchronously, under stringent communication constraints. In such situations, when an agent is activated and is allowed to communicate with only one of its neighbors, we would like to pick the one holding the most informative local estimate. We propose new algorithms where the agents with maximal dissent average their estimates, leading to an information mixing mechanism that often displays faster convergence to an optimal solution compared to randomized gossip. The core idea is that when two neighboring agents whose distance between local estimates is the largest among all neighboring agents in the network average their states, it leads to the largest possible immediate reduction of the quadratic Lyapunov function used to establish convergence to the set of optimal solutions. As a broader contribution, we prove the convergence of max-dissent subgradient methods using a unified framework that can be used for other state-dependent distributed optimization algorithms. Our proof technique bypasses the need of establishing the information flow between any two agents within a time interval of uniform length by intelligently studying convergence properties of the Lyapunov function used in our analysis

Avaliação da cultura de segurança do paciente na Amazônia Ocidental

Introdução: A cultura de segurança do paciente é fator contribuinte para a manutenção do bem-estar do usuário no sistema de saúde, pois por meio dela obtém-se uma sistematização organizada e de qualidade do cuidado ao paciente, prevenindo possíveis intercorrências que possam trazer danos. Objetivo: Analisar a Cultura de Segurança do Paciente (CSP) na perspectiva dos profissionais de saúde no Hospital de Referência do Alto Rio Juruá, na Amazônia Ocidental Brasileira. Método: Trata-se de um estudo transversal desenvolvido em um hospital público de médio porte em um município da Amazônia Ocidental. O questionário Hospital Survey on Patient Safety Culture, da Agency for Healthcare Research and Quality foi aplicado em 280 profissionais, no período dezembro de 2016 a fevereiro de 2017. Foi realizada a análise descritiva dos dados e a consistência interna do instrumento. Resultados: Os resultados apontam as melhores avaliações nas dimensões de Trabalho em equipe nos âmbitos das unidades (60%) e Aprendizado organizacional (60%). Os aspectos com os piores resultados foram as dimensões de Respostas não punitivas aos erros (18%) e Frequência de eventos relatados (32%). A análise de confiabilidade interna (Alpha de Cronbach) das dimensões variou entre 0,35 a 0,90. Conclusão: A cultura do medo parece predominar nesse hospital, contudo o estudo demonstrou que há possibilidades de melhoria em todas as dimensões da CSP. Os valores do Alpha de Cronbach apresentaram semelhança com os resultados obtidos pelo processo de validação.Introduction: The safety culture of the patient is a contributing factor for the maintenance of the user’s well-being in the health system because, through it, an organized systematization and quality of patient care are obtained, preventing possible intercurrences that can cause damages. Objective: To analyze the Patient Safety Culture (PSC) from the perspective of health professionals at the Reference Hospital of the Upper Juruá River, in the Brazilian Western Amazon. Methods: This is a cross-sectional study developed in a medium-sized public hospital in a municipality in Western Amazonia. The Survey for Patient Safety Culture survey of the Agency for Healthcare Research and Quality was applied to 280 professionals from December 2016 to February 2017. Descriptive analysis of the data and the internal consistency of the instrument were performed. Results: The results indicate the best evaluations in the dimensions of Teamwork in the scopes of the units (60%) and Organizational learning (60%). The aspects with the worst results were the dimensions of non-punitive responses to errors (18%) and frequency of events reported (32%). The internal reliability (Cronbach’s Alpha) analysis of the dimensions ranged from 0.35 to 0.90. Conclusion: The "culture of fear" seems to predominate in this hospital, however, the study showed that there is scope for improvement in all dimensions of CSP. The values of Cronbach’s Alpha presented similarity to the results obtained by the validation process