The current study focuses on the short-term effect of MARIO, a social robot, on quality of life, depression, and perceived social support in persons with dementia (PWD) and evaluates their acceptability of MARIO. Ten PWD in one nursing home took part in a 4-week pilot study, where each participant had up to 12 sessions with MARIO. Sessions comprised engagement in music, news, reminiscence, games, and calendar applications. Standardized questionnaires were administered before and after the 4-week period. Participants had a sustained interest in MARIO during their interactions and an acceptance of MARIO's appearance, sound, and applications. Consequently, participants spent more time socially engaged. No statistically significant differences were found in quality of life, depression, and perceived social support.PWD can engage with a social robot in a real-world nursing home. Future research should incorporate a larger sample and longer intervention period. connect them with their family, their pastimes and the outside world. The initial design of MARIO's applications was also based on four key principles: (i) the applications are individualised, (ii) the applications offer choice, (iii) the applications can prompt the individual and (iv) the applications are simple and intuitive to use. The applications underwent an iterative process of user-driven development, which involved testing several iterations of the applications with PLWD and using their feedback to further refine the applications. This paper presents the results of the final evaluation of MARIO carried out in the X (identifying information) nursing home setting. The aims of the pilot study were (i) to evaluate the acceptability, functionality and usability of MARIO to PLWD in a nursing home, as well as any potential ethical issues, from the perspective of the PLWD interacting with MARIO and the researcher observing the interactions and (ii) to explore the short-term effect of MARIO on quality of life, depression and perceived social support of PLWD. Methods DesignThis study was a single group, pre-post, pilot study. It was carried out in one purposively selected nursing home, containing 100 beds, in rural X (identifying information). Quantitative data was collected from PLWD, on quality of life, depression and social support, at baseline and directly after a four-week intervention period. These outcomes were established to be important for measuring the effect of psychosocial interventions for PLWD (Moniz-Cook et al., 2008). The study received ethical approval from the Research Ethics Committee of X (identifying information).
Abstract. Smart grid security has many facets, ranging over a spectrum from resisting attacks aimed at supervisory and control systems, to end user privacy concerns while monitored by the utility enterprise. This multi-faceted problem also includes vulnerabilities that arise from deployment of local cyber-physical attacks at a smart metering location, with a potential to a) manipulate the measured energy consumption, and b) being massively deployed aiming at destabilisation. In this paper we study a smart metering device that uses a trusted platform for storage and communication of metering data, and show that despite the hard core security, there is still room for deployment of a second level of defence as an embedded real-time anomaly detector that can cover both the cyber and physical domains.
Abstract-Reconfigurable Radio Systems (RRS), based on Software Defined Radio (SDR) and Mobile Ad-hoc Network (MANET) technologies, offer considerable advantages for military operations, such as increased network survivability and interoperability. The RRS-based Common Tactical Radio System (GTRS), currently in development by the Swedish Armed Forces, is designed for use in diverse geographical settings and for purposes varying from international combat missions to national contingency operations. However, protecting these networks from attacks and safeguarding the carried information against leaks is an ongoing research challenge, especially in combined scenarios where tactical data may flow across organizational boundaries. This paper presents a best-effort approach to Data Leakage Prevention (DLP) for inter-organizational RRS-based networks.The proposed architecture makes use of data mining techniques and an efficient n-dimensional clustering algorithm which has previously been successfully used for real-time anomaly detection in critical infrastructure protection. The DLP architecture is developed as an extension to the GTRS system, modeled and simulated in OPNET™ Modeler. Our results show that common data leaks can be efficiently identified by the proposed scheme, while keeping the important false positive rate at a very low level.
The need for an efficient Water Management System (WMS) is strongly felt by water utilities, municipalities and by medium to large scale corporates that have to face every day with problems dealing with water usage and supply Leveraging a sensor data network, an automated system to implement fault detection in a water network at an early stage can be a valuable tool that saves water, energy, time and money. This paper introduces a novel FDD (fault detection and diagnosis) approach for water networks developed within the FP7 Waternomics Project by modeling a water network in the simulation environment EPANET and applying an anomaly detection algorithm named ADWICE (Anomaly Detection With fast Incremental ClustEring) to real time data of water flow and pressure to infer performance and operational anomalies. The method is currently being implemented at the Linate Airport water network in Milan, and initial results are presented in this paper.
The paper will present an overview of one of the Fault Detection and Diagnosis (FDD) systems developed within the Waternomics project. The FDD system has been developed basing on the hydraulic modeling of the water network, the real time values of flow and pressure obtained from installation of innovative ICT and commercial smart meters and the application of the Anomaly Detection with fast Incremental ClustEring (ADWICE) algorithm adapted for the drinking water network. The FDD system developed is useful when we have to consider more than one parameter at the same time to determine if an anomaly or fault is in place in a complex water network and the system is designed on purpose to cope with a larger features set. The new FDD system will be implemented in an Italian demo site, the Linate Airport Water network in Milan, where a large water distribution network is in place and where, due the many variables coming into play, it could be very difficult to detect anomalies with a low false alarm rate.
Abstract-Mobile wireless handheld devices can support ad hoc communication when infrastructure systems are overloaded or not available. Unfortunately, the constrained capacity of their batteries and the energy inefficiency inherent to the ad hoc communication poses a challenge causing a short lifetime. Protocols and application layer services, such as security, can be designed (offline) to do an efficient use of the resources. Realtime adaptation can further minimise their impact on the energy consumption, increasing the network lifetime thus extending the availability of network communication.In this paper, we propose an energy-aware adaption component for an Intrusion Detection System (IDS) in mobile ad hoc networks (MANET). The component is in charge of adjusting the parameters of the IDS based on the current energy level, using the trade-off between the node's response to attacks and the energy consumption induced by the IDS. The approach is based on a model for accounting CPU energy consumption in network simulation, which has been implemented in an existing IDS in ns-3. Simulations demonstrate that the adaption has a positive impact on the battery life time, increasing it by 14%, without deteriorating the network-wide performance of the IDS.
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