36 research outputs found

    Social Networking Individual vs. Crowd Behavior (Connected Intelligence)

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    The study of Human behavior is much more complicated in various situations, especially on the spectrum of Social Networks. The study of individual behavior cannot be replicated for a group/crowd behavior which can have many social and behavioral dimensions. In the connected world where intelligence is shared among individuals and groups, there exists another kind of complexity which needs to be examined.The complexity of human behaviors as an individual or as a group on the social networks is much more versatile and erratic. The research work studies and analyzes these behaviors in a connected networked intelligent environment and as to how these behaviors are reflected towards Connected Intelligence. Consequently it defines how they can affect the intelligent analytical outcomes. Finally it comes up with a generic model which can be applied in any setup

    Direct velocity feedback versus a geometric controller design of remotely located vibration control systems

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    Proceedings of the 5th International Conference on Structural Engineering, Mechanics and Computation, SEMC 2013The mitigation of human induced vibrations in floors continues to be a key area of research particularly as a result of advancement in material and design technologies enabling the design of light, slender and more open plan structures. These floors are typically characterised by low and close natural frequencies as well as low modal damping ratios, and these combinations of factors contribute to their increased susceptibility to human induced vibrations. Amongst the remedial measures pursued to enhance their vibration serviceability performance, active vibration control (AVC) technologies are emerging as a viable technology and predominantly direct output feedback approaches have been pursued in past analytical studies and field trials. It has often been assumed that actuators and sensors can be located where vibration attenuation is desired and this may not always be feasible. The research work presented in this paper compares the vibration mitigation performances of the direct velocity feedback scheme that has been extensively used in past floor vibration control researches against a geometric controller design approach that has been developed to provide a design freedom for reducing vibration in both local and remote locations. The geometric controller design approach assumes the inability to locate the actuators and sensors at the remote location but acknowledges that this measurement can be obtained during the commissioning stage and used during the design phase to enhance both local and remote locations. All the analytical and experimental studies are based on a laboratory structure. The work demonstrates comparable vibration mitigation performances of the dominant mode of vibration of the laboratory structure for both approaches but also demonstrates potential for additional enhancement to the second vibration mode of the laboratory structure with the geometric controller design approach. Approximately 20-25 dB attenuation in the first and second vibration modes of the laboratory structure were achieved. © 2013 Taylor & Francis Group, London, UK.The authors would like to acknowledge the financial assistance provided by the UK Engineering and Physical Sciences Research Council (EPSRC) through a responsive mode grant entitled “Active Control of Human-Induced Vibration” (Ref: EP/H009825/1), Leadership Fellowship grant entitled “Advanced Technologies for Mitigation of Human-Induced Vibration” (Ref: EP/J004081/1) and Platform Grant entitled “Dynamic Performance of Large Civil Engineering Structures: An Integrated Approach to Management, Design and Assessment” (Ref: EP/G061130/1)

    IoT-Flock: An Open-source Framework for IoT Traffic Generation

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    Network traffic generation is one of the primary techniques that is used to design and analyze the performance of network security systems. However, due to the diversity of IoT networks in terms of devices, applications and protocols, the traditional network traffic generator tools are unable to generate the IoT specific protocols traffic. Hence, the traditional traffic generator tools cannot be used for designing and testing the performance of IoT-specific security solutions. In order to design an IoT-based traffic generation framework, two main challenges include IoT device modelling and generating the IoT normal and attack traffic simultaneously. Therefore, in this work, we propose an open-source framework for IoT traffic generation which supports the two widely used IoT application layer protocols, i.e., MQTT and CoAP. The proposed framework allows a user to create an IoT use case, add customized IoT devices into it and generate normal and malicious IoT traffic over a real-time network. Furthermore, we set up a real-time IoT smart home use case to manifest the applicability of the proposed framework for developing the security solutions for IoT smart home by emulating the real world IoT devices. The experimental results demonstrate that the proposed framework can be effectively used to develop better security solutions for IoT networks without physically deploying the real-time use case.Comment: 6 Pages, 2 Figures, 4 Tables. Accepted in IEEE International Conference on Emerging Trends in Smart Technologies(ICETST) 202

    Ultra-Low-Power, High-Accuracy 434 MHz Indoor Positioning System for Smart Homes Leveraging Machine Learning Models

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    Global navigation satellite systems have been used for reliable location-based services in outdoor environments. However, satellite-based systems are not suitable for indoor positioning due to low signal power inside buildings and low accuracy of 5 m. Future smart homes demand low-cost, high-accuracy and low-power indoor positioning systems that can provide accuracy of less than 5 m and enable battery operation for mobility and long-term use. We propose and implement an intelligent, highly accurate and low-power indoor positioning system for smart homes leveraging Gaussian Process Regression (GPR) model using information-theoretic gain based on reduction in differential entropy. The system is based on Time Difference of Arrival (TDOA) and uses ultra-low-power radio transceivers working at 434 MHz. The system has been deployed and tested using indoor measurements for two-dimensional (2D) positioning. In addition, the proposed system provides dual functionality with the same wireless links used for receiving telemetry data, with configurable data rates of up to 600 Kbauds. The implemented system integrates the time difference pulses obtained from the differential circuitry to determine the radio frequency (RF) transmitter node positions. The implemented system provides a high positioning accuracy of 0.68 m and 1.08 m for outdoor and indoor localization, respectively, when using GPR machine learning models, and provides telemetry data reception of 250 Kbauds. The system enables low-power battery operation with consumption of <200 mW power with ultra-low-power CC1101 radio transceivers and additional circuits with a differential amplifier. The proposed system provides low-cost, low-power and high-accuracy indoor localization and is an essential element of public well-being in future smart homes

    Umbilical cord blood DNA methylation in children who later develop type 1 diabetes

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    Aims/hypothesis: Distinct DNA methylation patterns have recently been observed to precede type 1 diabetes in whole blood collected from young children. Our aim was to determine whether perinatal DNA methylation is associated with later progression to type 1 diabetes.Methods: Reduced representation bisulphite sequencing (RRBS) analysis was performed on umbilical cord blood samples collected within the Finnish Type 1 Diabetes Prediction and Prevention (DIPP) Study. Children later diagnosed with type 1 diabetes and/or who tested positive for multiple islet autoantibodies (n = 43) were compared with control individuals (n = 79) who remained autoantibody-negative throughout the DIPP follow-up until 15 years of age. Potential confounding factors related to the pregnancy and the mother were included in the analysis.Results: No differences in the umbilical cord blood methylation patterns were observed between the cases and controls at a false discovery rate Conclusions/interpretation: Based on our results, differences between children who progress to type 1 diabetes and those who remain healthy throughout childhood are not yet present in the perinatal DNA methylome. However, we cannot exclude the possibility that such differences would be found in a larger dataset.</p

    Phenotypic characterisation of regulatory T cells in dogs reveals signature transcripts conserved in humans and mice

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    Regulatory T cells (Tregs) are a double-edged regulator of the immune system. Aberrations of Tregs correlate with pathogenesis of inflammatory, autoimmune and neoplastic disorders. Phenotypically and functionally distinct subsets of Tregs have been identified in humans and mice on the basis of their extensive portfolios of monoclonal antibodies (mAb) against Treg surface antigens. As an important veterinary species, dogs are increasingly recognised as an excellent model for many human diseases. However, insightful study of canine Tregs has been restrained by the limited availability of mAb. We therefore set out to characterise CD4+CD25high T cells isolated ex vivo from healthy dogs and showed that they possess a regulatory phenotype, function, and transcriptomic signature that resembles those of human and murine Tregs. By launching a cross-species comparison, we unveiled a conserved transcriptomic signature of Tregs and identified that transcript hip1 may have implications in Treg function

    NEOTROPICAL XENARTHRANS: a data set of occurrence of xenarthran species in the Neotropics

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    Xenarthrans – anteaters, sloths, and armadillos – have essential functions for ecosystem maintenance, such as insect control and nutrient cycling, playing key roles as ecosystem engineers. Because of habitat loss and fragmentation, hunting pressure, and conflicts with 24 domestic dogs, these species have been threatened locally, regionally, or even across their full distribution ranges. The Neotropics harbor 21 species of armadillos, ten anteaters, and six sloths. Our dataset includes the families Chlamyphoridae (13), Dasypodidae (7), Myrmecophagidae (3), Bradypodidae (4), and Megalonychidae (2). We have no occurrence data on Dasypus pilosus (Dasypodidae). Regarding Cyclopedidae, until recently, only one species was recognized, but new genetic studies have revealed that the group is represented by seven species. In this data-paper, we compiled a total of 42,528 records of 31 species, represented by occurrence and quantitative data, totaling 24,847 unique georeferenced records. The geographic range is from the south of the USA, Mexico, and Caribbean countries at the northern portion of the Neotropics, to its austral distribution in Argentina, Paraguay, Chile, and Uruguay. Regarding anteaters, Myrmecophaga tridactyla has the most records (n=5,941), and Cyclopes sp. has the fewest (n=240). The armadillo species with the most data is Dasypus novemcinctus (n=11,588), and the least recorded for Calyptophractus retusus (n=33). With regards to sloth species, Bradypus variegatus has the most records (n=962), and Bradypus pygmaeus has the fewest (n=12). Our main objective with Neotropical Xenarthrans is to make occurrence and quantitative data available to facilitate more ecological research, particularly if we integrate the xenarthran data with other datasets of Neotropical Series which will become available very soon (i.e. Neotropical Carnivores, Neotropical Invasive Mammals, and Neotropical Hunters and Dogs). Therefore, studies on trophic cascades, hunting pressure, habitat loss, fragmentation effects, species invasion, and climate change effects will be possible with the Neotropical Xenarthrans dataset

    Symbol Mapping Design for Bit-Interleaved Polar-Coded Modulation With Iterative Decoding

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