60 research outputs found

    The Application of Fuzzy Logic Controller to Compute a Trust Level for Mobile Agents in a Smart Home

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    Agents that travel through many hosts may cause a threat on the security of the visited hosts. Assets, system resources, and the reputation of the host are few possible targets for such an attack. The possibility for multi-hop agents to be malicious is higher compared to the one-hop or two-hop boomerang agents. The travel history is one of the factors that may allow a server to evaluate the trustworthiness of an agent. This paper proposes a technique to define levels of trust for multi-hop agents that are roaming in a smart home environment. These levels of trust are used later to determine actions taken by a host at the arrival of an agent. This technique uses fuzzy logic as a method to calculate levels of trust and to define protective actions in regard to those levels

    Trust Level and Routing Selection for Mobile Agents in a Smart Home (Extended version)

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    The central security concern for systems where agents roam is how to establish trust in the agent. We present a Fuzzy Logic mechanism to calculate a level of trust and an optimal route for a mobile agent system in a smart home. The mechanism consists of two parts. The first part calculates a trust level at the platform side to decide which actions should be allowed by a visiting mobile agent. The second part calculates an optimal route at the mobile agent side to decide an alternative destination in the case of rejection by a platform. Examples are provided from smart home scenarios, showing how flexible the proposed mechanism is

    Enhanced nasopharyngeal infection and shedding associated with an epidemic lineage of emm3 group A Streptococcus

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    Background: A group A Streptococcus (GAS) lineage of genotype emm3, sequence type 15 (ST15) was associated with a six month upsurge in invasive GAS disease in the UK. The epidemic lineage (Lineage C) had lost two typical emm3 prophages, Φ315.1 and Φ315.2 associated with the superantigen ssa, but gained a different prophage (ΦUK-M3.1) associated with a different superantigen, speC and a DNAse spd1. Methods and Results: The presence of speC and spd1 in Lineage C ST15 strains enhanced both in vitro mitogenic and DNAse activities over non-Lineage C ST15 strains. Invasive disease models in Galleria mellonella and SPEC-sensitive transgenic mice, revealed no difference in overall invasiveness of Lineage C ST15 strains compared to non-Lineage C ST15 strains, consistent with clinical and epidemiological analysis. Lineage C strains did however markedly prolong murine nasal infection with enhanced nasal and airborne shedding compared to non-Lineage C strains. Deletion of speC or spd1 in two Lineage C strains identified a possible role for spd1 in airborne shedding from the murine nasopharynx. Conclusions: Nasopharyngeal infection and shedding of Lineage C strains was enhanced compared to nonLineage C strains and this was, in part, mediated by the gain of the DNase spd1 through prophage acquisition

    Emergence of a novel lineage containing a prophage in emm/M3 group A Streptococcus associated with upsurge in invasive disease in the UK

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    A sudden increase in invasive Group A Streptococcus (iGAS) infections associated with emm/M3 isolates during the winter of 2008/09 prompted the initiation of enhanced surveillance in England. In order to characterise the population of emm/M3 GAS within the UK and determine bacterial factors that might be responsible for this upsurge, 442 emm/M3 isolates from cases of invasive and non-invasive infections during the period 2001–2013 were subjected to whole genome sequencing. MLST analysis differentiated emm/M3 isolates into three sequence types (STs): ST15, ST315 and ST406. Analysis of the whole genome SNP-based phylogeny showed that the majority of isolates from the 2008–2009 upsurge period belonged to a distinct lineage characterized by the presence of a prophage carrying the speC exotoxin and spd1 DNAase genes but loss of two other prophages considered typical of the emm/M3 lineage. This lineage was significantly associated with the upsurge in iGAS cases and we postulate that the upsurge could be attributed in part to expansion of this novel prophage-containing lineage within the population. The study underlines the importance of prompt genomic analysis of changes in the GAS population, providing an advanced public health warning system for newly emergent, pathogenic strains

    Simulation of Concrete Slab Behavior to Explosion

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    Special structure prone to explosion requires special material. Identification of special material is required to find the right concrete properties. Researching material behavior using explosion test is costly. Therefore, prediction using simulation is needed. In this study, we use ANSYS Workbench as a simulation program. The explosion test model comprised a non-reinforced slab 500×500×50 mm and TNT cube. It was found that the compressive strength minimum of the concrete slab that withstand the explosion of 30 grams TNT was 20 MPa. The Young modulus affects to the concrete behavior using default RHT Concrete properties. It had instability against modified concrete properties when performing numerical analysis

    Enzyme classification with peptide programs: a comparative study

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    <p>Abstract</p> <p>Background</p> <p>Efficient and accurate prediction of protein function from sequence is one of the standing problems in Biology. The generalised use of sequence alignments for inferring function promotes the propagation of errors, and there are limits to its applicability. Several machine learning methods have been applied to predict protein function, but they lose much of the information encoded by protein sequences because they need to transform them to obtain data of fixed length.</p> <p>Results</p> <p>We have developed a machine learning methodology, called peptide programs (PPs), to deal directly with protein sequences and compared its performance with that of Support Vector Machines (SVMs) and BLAST in detailed enzyme classification tasks. Overall, the PPs and SVMs had a similar performance in terms of Matthews Correlation Coefficient, but the PPs had generally a higher precision. BLAST performed globally better than both methodologies, but the PPs had better results than BLAST and SVMs for the smaller datasets.</p> <p>Conclusion</p> <p>The higher precision of the PPs in comparison to the SVMs suggests that dealing with sequences is advantageous for detailed protein classification, as precision is essential to avoid annotation errors. The fact that the PPs performed better than BLAST for the smaller datasets demonstrates the potential of the methodology, but the drop in performance observed for the larger datasets indicates that further development is required.</p> <p>Possible strategies to address this issue include partitioning the datasets into smaller subsets and training individual PPs for each subset, or training several PPs for each dataset and combining them using a bagging strategy.</p

    Patient-provider interaction from the perspectives of type 2 diabetes patients in Muscat, Oman: a qualitative study

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    <p>Abstract</p> <p>Background</p> <p>Patients' expectations and perceptions of the medical encounter and interactions are important tools in diabetes management. Some problems regarding the interaction during encounters may be related to a lack of communication skills on the part of either the physician or the patient.</p> <p>This study aimed at exploring the perceptions of type 2 diabetes patients regarding the medical encounters and quality of interactions with their primary health-care providers.</p> <p>Methods</p> <p>Four focus group discussions (two women and two men groups) were conducted among 27 purposively selected patients (13 men and 14 women) from six primary health-care centres in Muscat, Oman. Qualitative content analysis was applied.</p> <p>Results</p> <p>The patients identified some weaknesses regarding the patient-provider communication like: unfriendly welcoming; interrupted consultation privacy; poor attention and eye contact; lack of encouraging the patients to ask questions on the providers' side; and inability to participate in medical dialogue or express concerns on the patients' side. Other barriers and difficulties related to issues of patient-centeredness, organization of diabetes clinics, health education and professional competency regarding diabetes care were also identified.</p> <p>Conclusion</p> <p>The diabetes patients' experiences with the primary health-care providers showed dissatisfaction with the services. We suggest appropriate training for health-care providers with regard to diabetes care and developing of communication skills with emphasis on a patient-centred approach. An efficient use of available resources in diabetes clinics and distributing responsibilities between team members in close collaboration with patients and their families seems necessary. Further exploration of the providers' work situation and barriers to good interaction is needed. Our findings can help the policy makers in Oman, and countries with similar health systems, to improve the quality and organizational efficiency of diabetes care services.</p
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