Dataset Information

ARES: Automated Risk Estimation in Smart Sensor Environments.

ABSTRACT: Industry 4.0 adoption demands integrability, interoperability, composability, and security. Currently, integrability, interoperability and composability are addressed by next-generation approaches for enterprise systems integration such as model-based standards, ontology, business process model life cycle management and the context of business processes. Security is addressed by conducting risk management as a first step. Nevertheless, security risks are very much influenced by the assets that the business processes are supported. To this end, this paper proposes an approach for automated risk estimation in smart sensor environments, called ARES, which integrates with the business process model life cycle management. To do so, ARES utilizes standards for platform, vulnerability, weakness, and attack pattern enumeration in conjunction with a well-known vulnerability scoring system. The applicability of ARES is demonstrated with an application example that concerns a typical case of a microSCADA controller and a prototype tool called Business Process Cataloging and Classification System. Moreover, a computer-aided procedure for mapping attack patterns-to-platforms is proposed, and evaluation results are discussed revealing few limitations.

SUBMITTER: Dimitriadis A

PROVIDER: S-EPMC7472351 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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ARES: Automated Risk Estimation in Smart Sensor Environments.

Dimitriadis Athanasios A Flores Jose Luis JL Kulvatunyou Boonserm B Ivezic Nenad N Mavridis Ioannis I

Sensors (Basel, Switzerland) 20200817 16

Industry 4.0 adoption demands integrability, interoperability, composability, and security. Currently, integrability, interoperability and composability are addressed by next-generation approaches for enterprise systems integration such as model-based standards, ontology, business process model life cycle management and the context of business processes. Security is addressed by conducting risk management as a first step. Nevertheless, security risks are very much influenced by the assets that t ...[more]

PMID: 32824471

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Project description:IntroductionCardiac catheterization procedures result in high radiation doses and often multiple procedures are necessary for congenital heart disease patients. However, diagnostic reference levels (DRL) remain scarce. Our first goal was finding the optimal DRL parameter and determining appropriate DRLs. The second goal was to calculate organ doses (OD), effective doses (ED) and lifetime attributable risks (LAR) per procedure and to provide conversion factors based on dose area product (DAP).Materials and methodsDRLs are calculated for each procedure type, as the 75th percentile of the cumulative value per procedure from the corresponding parameter. All irradiation events in the DICOM Structured Reports were automatically processed and simulated using PCXMC, resulting in OD, ED and LAR. Using a Kruskal Wallis H test and subsequent pairwise comparisons, differences in median values of the DRL parameter between procedure types were assessed.ResultsLinear regression showed a strong correlation and narrow confidence interval between DAP and product of body weight and fluoroscopy time (BWxFT), even when all procedures (diagnostic and interventional) are combined. Only 15% of the pairwise comparisons were statistically significant for DAP normalized to BWxFT (DAPBWxFT). The latter pairs contained less frequent procedure types with significant outliers. For DAP normalized to BW (DAPBW), 38% of the pairwise comparisons showed statistically significant differences. Conversion factors from DAPBW to OD and ED were reported for various weight groups, due to the higher correlation between DAPBW and both OD and ED than between DAP and both OD and ED.ConclusionsThe P75 of DAPBWxFT for all procedures combined serves as an appropriate DRL value. This facilitates local DRL determination in smaller paediatric centres, which often have insufficient data to produce appropriate DRLs for different procedure types. Conversion factors are more reliable starting from DAPBW instead of DAP and should be used according to the appropriate BW group.

Project description:BACKGROUND:There is a lack of early (infant) mobility rehabilitation approaches that incorporate natural and complex environments and have the potential to concurrently advance motor, cognitive, and social development. The Grounded Early Adaptive Rehabilitation (GEAR) system is a pediatric learning environment designed to provide motor interventions that are grounded in social theory and can be applied in early life. Within a perceptively complex and behaviorally natural setting, GEAR utilizes novel body-weight support technology and socially-assistive robots to both ease and encourage mobility in young children through play-based, child-robot interaction. This methodology article reports on the development and integration of the different system components and presents preliminary evidence on the feasibility of the system. METHODS:GEAR consists of the physical and cyber components. The physical component includes the playground equipment to enrich the environment, an open-area body weight support (BWS) device to assist children by partially counter-acting gravity, two mobile robots to engage children into motor activity through social interaction, and a synchronized camera network to monitor the sessions. The cyber component consists of the interface to collect human movement and video data, the algorithms to identify the children's actions from the video stream, and the behavioral models for the child-robot interaction that suggest the most appropriate robot action in support of given motor training goals for the child. The feasibility of both components was assessed via preliminary testing. Three very young children (with and without Down syndrome) used the system in eight sessions within a 4-week period. RESULTS:All subjects completed the 8-session protocol, participated in all tasks involving the selected objects of the enriched environment, used the BWS device and interacted with the robots in all eight sessions. Action classification algorithms to identify early child behaviors in a complex naturalistic setting were tested and validated using the video data. Decision making algorithms specific to the type of interactions seen in the GEAR system were developed to be used for robot automation. CONCLUSIONS:Preliminary results from this study support the feasibility of both the physical and cyber components of the GEAR system and demonstrate its potential for use in future studies to assess the effects on the co-development of the motor, cognitive, and social systems of very young children with mobility challenges.

Project description:Root exudation is a key component of nutrient and carbon dynamics in terrestrial ecosystems. Exudation rates vary widely by plant species and environmental conditions, but our understanding of how root exudates affect soil functioning is incomplete, in part because there are few viable methods to manipulate root exudates in situ. To address this, we devised the Automated Root Exudate System (ARES), which simulates increased root exudation by applying small amounts of labile solutes at regular intervals in the field.The ARES is a gravity-fed drip irrigation system comprising a reservoir bottle connected via a timer to a micro-hose irrigation grid covering c. 1 m2; 24 drip-tips are inserted into the soil to 4-cm depth to apply solutions into the rooting zone. We installed two ARES subplots within existing litter removal and control plots in a temperate deciduous woodland. We applied either an artificial root exudate solution (RE) or a procedural control solution (CP) to each subplot for 1 min day-1 during two growing seasons. To investigate the influence of root exudation on soil carbon dynamics, we measured soil respiration monthly and soil microbial biomass at the end of each growing season.The ARES applied the solutions at a rate of c. 2 L m-2 week-1 without significantly increasing soil water content. The application of RE solution had a clear effect on soil carbon dynamics, but the response varied by litter treatment. Across two growing seasons, soil respiration was 25% higher in RE compared to CP subplots in the litter removal treatment, but not in the control plots. By contrast, we observed a significant increase in microbial biomass carbon (33%) and nitrogen (26%) in RE subplots in the control litter treatment.The ARES is an effective, low-cost method to apply experimental solutions directly into the rooting zone in the field. The installation of the systems entails minimal disturbance to the soil and little maintenance is required. Although we used ARES to apply root exudate solution, the method can be used to apply many other treatments involving solute inputs at regular intervals in a wide range of ecosystems.

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ARES: Automated Risk Estimation in Smart Sensor Environments.

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ARES: Automated Risk Estimation in Smart Sensor Environments.

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