The dynamics and control of a remotely piloted plan-symmetric helicopter

Prior to the development of a production standard control system for ML Aviation's plan-symmetric remotely piloted helicopter system, SPRITE, optimum solutions to technical requirements had yet to be found for some aspects of the work. This thesis describes an industrial project where solutions to real problems have been provided within strict timescale constraints. Use has been made of published material wherever appropriate, new solutions have been contributed where none existed previously. A lack of clearly defined user requirements from potential Remotely Piloted Air Vehicle (RPAV) system users is identified, A simulation package is defined to enable the RPAV designer to progress with air vehicle and control system design, development and evaluation studies and to assist the user to investigate his applications. The theoretical basis of this simulation package is developed including Co-axial Contra-rotating Twin Rotor (CCTR), six degrees of freedom motion, fuselage aerodynamics and sensor and control system models. A compatible system of equations is derived for modelling a miniature plan-symmetric helicopter. Rigorous searches revealed a lack of CCTR models, based on closed form expressions to obviate integration along the rotor blade, for stabilisation and navigation studies through simulation. An economic CCTR simulation model is developed and validated by comparison with published work and practical tests. Confusion in published work between attitude and Euler angles is clarified. The implementation of package is discussed. dynamic adjustment of assessment. the theory into a high integrity software Use is made of a novel technique basing the integration time step size on error Simulation output for control system stability verification, cross coupling of motion between control channels and air vehicle response to demands and horizontal wind gusts studies are presented. Contra-Rotating Twin Rotor Flight Control System Remotely Piloted Plan-Symmetric Helicopter Simulation Six Degrees of Freedom Motion ( i i)

JenPep : a novel computational information resource for immunobiology and vaccinology

JenPep is a relational database containing a compendium of thermodynamic binding data for the interaction of peptides with a range of important immunological molecules:  the major histocompatibility complex, TAP transporter, and T cell receptor. The database also includes annotated lists of B cell and T cell epitopes. Version 2.0 of the database is implemented in a bespoke postgreSQL database system and is fully searchable online via a perl/HTML interface (URL:  http://www.jenner.ac.uk/JenPep).

Automatized Generation of Personalized Learning Paths through Aspects in Multidimensional Spaces

Report published in the Proceedings of the National Conference on "Education and Research in the Information Society", Plovdiv, May, 2016

An incentivized auction based group-selling approach for demand response management in V2G systems

Vehicle-to-Grid (V2G) system with efficient Demand Response Management (DRM) is critical to solve the problem of supplying electricity by utilizing surplus electricity available at EVs. An incentivilized DRM approach is studied to reduce the system cost and maintain the system stability. EVs are motivated with dynamic pricing determined by the group-selling based auction. In the proposed approach, a number of aggregators sit on the first level auction responsible to communicate with a group of EVs. EVs as bidders consider Quality of Energy (QoE) requirements and report interests and decisions on the bidding process coordinated by the associated aggregator. Auction winners are determined based on the bidding prices and the amount of electricity sold by the EV bidders. We investigate the impact of the proposed mechanism on the system performance with maximum feedback power constraints of aggregators. The designed mechanism is proven to have essential economic properties. Simulation results indicate the proposed mechanism can reduce the system cost and offer EVs significant incentives to participate in the V2G DRM operation.

An indexing structure and application model for vehicles moving on road networks

Moving objects database systems are the most challenging sub-category among Spatio-Temporal database systems. A database system that updates in real-time the location information of GPS-equipped moving vehicles has to meet even stricter requirements. Currently existing data storage models and indexing mechanisms work well only when the number of moving objects in the system is relatively small. This dissertation research aimed at the real-time tracking and history retrieval of massive numbers of vehicles moving on road networks. A total solution has been provided for the real-time update of the vehicles' location and motion information, range queries on current and history data, and prediction of vehicles' movement in the near future. ^ To achieve these goals, a new approach called Segmented Time Associated to Partitioned Space (STAPS) was first proposed in this dissertation for building and manipulating the indexing structures for moving objects databases. ^ Applying the STAPS approach, an indexing structure of associating a time interval tree to each road segment was developed for real-time database systems of vehicles moving on road networks. The indexing structure uses affordable storage to support real-time data updates and efficient query processing. The data update and query processing performance it provides is consistent without restrictions such as a time window or assuming linear moving trajectories. ^ An application system design based on distributed system architecture with centralized organization was developed to maximally support the proposed data and indexing structures. The suggested system architecture is highly scalable and flexible. Finally, based on a real-world application model of vehicles moving in region-wide, main issues on the implementation of such a system were addressed. ^

An exergy based engineering and economic analysis of sustainable building

To achieve the goal of sustainable development, the building energy system was evaluated from both the first and second law of thermodynamics point of view. The relationship between exergy destruction and sustainable development were discussed at first, followed by the description of the resource abundance model, the life cycle analysis model and the economic investment effectiveness model. By combining the forgoing models, a new sustainable index was proposed. Several green building case studies in U.S. and China were presented. The influences of building function, geographic location, climate pattern, the regional energy structure, and the technology improvement potential of renewable energy in the future were discussed. The building’s envelope, HVAC system, on-site renewable energy system life cycle analysis from energy, exergy, environmental and economic perspective were compared. It was found that climate pattern had a dramatic influence on the life cycle investment effectiveness of the building envelope. The building HVAC system energy performance was much better than its exergy performance. To further increase the exergy efficiency, renewable energy rather than fossil fuel should be used as the primary energy. A building life cycle cost and exergy consumption regression model was set up. The optimal building insulation level could be affected by either cost minimization or exergy consumption minimization approach. The exergy approach would cause better insulation than cost approach. The influence of energy price on the system selection strategy was discussed. Two photovoltaics (PV) systems—stand alone and grid tied system were compared by the life cycle assessment method. The superiority of the latter one was quite obvious. The analysis also showed that during its life span PV technology was less attractive economically because the electricity price in U.S. and China did not fully reflect the environmental burden associated with it. However if future energy price surges and PV system cost reductions were considered, the technology could be very promising for sustainable buildings in the future.

An Exergy Based Engineering and Economic Analysis of Sustainable Building

To achieve the goal of sustainable development, the building energy system was evaluated from both the first and second law of thermodynamics point of view. The relationship between exergy destruction and sustainable development were discussed at first, followed by the description of the resource abundance model, the life cycle analysis model and the economic investment effectiveness model. By combining the forgoing models, a new sustainable index was proposed. Several green building case studies in U.S. and China were presented. The influences of building function, geographic location, climate pattern, the regional energy structure, and the technology improvement potential of renewable energy in the future were discussed. The building’s envelope, HVAC system, on-site renewable energy system life cycle analysis from energy, exergy, environmental and economic perspective were compared. It was found that climate pattern had a dramatic influence on the life cycle investment effectiveness of the building envelope. The building HVAC system energy performance was much better than its exergy performance. To further increase the exergy efficiency, renewable energy rather than fossil fuel should be used as the primary energy. A building life cycle cost and exergy consumption regression model was set up. The optimal building insulation level could be affected by either cost minimization or exergy consumption minimization approach. The exergy approach would cause better insulation than cost approach. The influence of energy price on the system selection strategy was discussed. Two photovoltaics (PV) systems – stand alone and grid tied system were compared by the life cycle assessment method. The superiority of the latter one was quite obvious. The analysis also showed that during its life span PV technology was less attractive economically because the electricity price in U.S. and China did not fully reflect the environmental burden associated with it. However if future energy price surges and PV system cost reductions were considered, the technology could be very promising for sustainable buildings in the future.

An Indexing Structure and Application Model for Vehicles Moving on Road Networks

Moving objects database systems are the most challenging sub-category among Spatio-Temporal database systems. A database system that updates in real-time the location information of GPS-equipped moving vehicles has to meet even stricter requirements. Currently existing data storage models and indexing mechanisms work well only when the number of moving objects in the system is relatively small. This dissertation research aimed at the real-time tracking and history retrieval of massive numbers of vehicles moving on road networks. A total solution has been provided for the real-time update of the vehicles’ location and motion information, range queries on current and history data, and prediction of vehicles’ movement in the near future. To achieve these goals, a new approach called Segmented Time Associated to Partitioned Space (STAPS) was first proposed in this dissertation for building and manipulating the indexing structures for moving objects databases. Applying the STAPS approach, an indexing structure of associating a time interval tree to each road segment was developed for real-time database systems of vehicles moving on road networks. The indexing structure uses affordable storage to support real-time data updates and efficient query processing. The data update and query processing performance it provides is consistent without restrictions such as a time window or assuming linear moving trajectories. An application system design based on distributed system architecture with centralized organization was developed to maximally support the proposed data and indexing structures. The suggested system architecture is highly scalable and flexible. Finally, based on a real-world application model of vehicles moving in region-wide, main issues on the implementation of such a system were addressed.

The user's view level of the GOQL graphical query language

The paper addresses issues related to the design of a graphical query mechanism that can act as an interface to any object-oriented database system (OODBS), in general, and the object model of ODMG 2.0, in particular. In the paper a brief literature survey of related work is given, and an analysis methodology that allows the evaluation of such languages is proposed. Moreover, the user's view level of a new graphical query language, namely GOQL (Graphical Object Query Language), for ODMG 2.0 is presented. The user's view level provides a graphical schema that does not contain any of the perplexing details of an object-oriented database schema, and it also provides a foundation for a graphical interface that can support ad-hoc queries for object-oriented database applications. We illustrate, using an example, the user's view level of GOQL

In-situ formation of solidified hydrogen thin-membrane targets using a pulse tube cryocooler

An account is given of the Central Laser Facility's work to produce a cryogenic hydrogen targetry system using a pulse tube cryocooler. Due to the increasing demand for low Z thin laser targets, CLF (in collaboration with TUD) have been developing a system which allows the production of solid hydrogen membranes by engineering a design which can achieve this remotely; enabling the gas injection, condensation and solidification of hydrogen without compromising the vacuum of the target chamber. A dynamic sealing mechanism was integrated which allows targets to be grown and then remotely exposed to open vacuum for laser interaction. Further research was conducted on the survivability of the cryogenic targets which concluded that a warm gas effect causes temperature spiking when exposing the solidified hydrogen to the outer vacuum. This effect was shown to be mitigated by improving the pumping capacity of the environment and reducing the minimum temperature obtainable on the target mount. This was achieved by developing a two-stage radiation shield encased with superinsulating blanketing; reducing the base temperature from 14 0.5 K to 7.2 0.2 K about the coldhead as well as improving temperature control stability following the installation of a high-performance temperature controller and sensor apparatus. The system was delivered experimentally and in July 2014 the first laser shots were taken upon hydrogen targets in the Vulcan TAP facility.

Adaptive edge analytics for distributed networked control of water systems

Over the last decade, there has been a trend where water utility companies aim to make water distribution networks more intelligent in order to improve their quality of service, reduce water waste, minimize maintenance costs etc., by incorporating IoT technologies. Current state of the art solutions use expensive power hungry deployments to monitor and transmit water network states periodically in order to detect anomalous behaviors such as water leakage and bursts. However, more than 97% of water network assets are remote away from power and are often in geographically remote underpopulated areas, facts that make current approaches unsuitable for next generation more dynamic adaptive water networks. Battery-driven wireless sensor/actuator based solutions are theoretically the perfect choice to support next generation water distribution. In this paper, we present an end-to-end water leak localization system, which exploits edge processing and enables the use of battery-driven sensor nodes. Our system combines a lightweight edge anomaly detection algorithm based on compression rates and an efficient localization algorithm based on graph theory. The edge anomaly detection and localization elements of the systems produce a timely and accurate localization result and reduce the communication by 99% compared to the traditional periodic communication. We evaluated our schemes by deploying non-intrusive sensors measuring vibrational data on a real-world water test rig that have had controlled leakage and burst scenarios implemented.

Uso de dexmedetomidina como tratamiento coadyuvante de síndrome de abstinencia alcohólica: revisión sistemática

El objetivo de este estudio es establecer si la dexmedetomidina (DEX) es segura y efectiva para el manejo coadyuvante de síndrome de abstinencia a alcohol (SAA) a través de la búsqueda de evidencia científica. Metodología: se realiza una revisión sistemática de literatura publicada y no publicada desde enero de 1989 hasta febrero 2016 en PubMed, Embase, Scopus, Bireme, Cochrane library y en otras bases de datos y portales. Los criterios de inclusión fueron ensayos clínicos aleatorizados y no aleatorizados, estudios cuasi-experimentales, estudios de cohorte, y estudios de casos y controles; que incluyeron pacientes mayores de 18 años hospitalizados con diagnóstico de SAA y donde se usó DEX como terapia coadyuvante. Resultados: 7 estudios, 477 pacientes, se incluyeron en el análisis final. Se encontraron dos ensayos clínicos aleatorizados, tres estudios de casos y controles y dos estudios de cohorte retrospectivo. Solo uno de los estudios fue doble ciego y utilizó placebo como comparador. Análisis y conclusiones: en los estudios experimentales se determinan que el uso de DEX como terapia coadyuvante en el manejo de SAA tiene significancia clínica y estadística para disminuir dosis de BZD en las primeras 24 horas de tratamiento; pero no demostraron tener otros beneficios clínicos. En los estudios no aleatorizados existe consenso que relaciona el uso de DEX con menores dosis de BZD de forma temprana. Recomendaciones: no se recomienda el uso de DEX en SAA de forma rutinaria. Se recomienda usar DEX solo en casos en el que exista evidencia fallo terapéutico a BZD.

Database Independent Human Emotion Recognition with Meta-Cognitive Neuro-Fuzzy Inference System

Facial emotions are the most expressive way to display emotions. Many algorithms have been proposed which employ a particular set of people (usually a database) to both train and test their model. This paper focuses on the challenging task of database independent emotion recognition, which is a generalized case of subject-independent emotion recognition. The emotion recognition system employed in this work is a Meta-Cognitive Neuro-Fuzzy Inference System (McFIS). McFIS has two components, a neuro-fuzzy inference system, which is the cognitive component and a self-regulatory learning mechanism, which is the meta-cognitive component. The meta-cognitive component, monitors the knowledge in the neuro-fuzzy inference system and decides on what-to-learn, when-to-learn and how-to-learn the training samples, efficiently. For each sample, the McFIS decides whether to delete the sample without being learnt, use it to add/prune or update the network parameter or reserve it for future use. This helps the network avoid over-training and as a result improve its generalization performance over untrained databases. In this study, we extract pixel based emotion features from well-known (Japanese Female Facial Expression) JAFFE and (Taiwanese Female Expression Image) TFEID database. Two sets of experiment are conducted. First, we study the individual performance of both databases on McFIS based on 5-fold cross validation study. Next, in order to study the generalization performance, McFIS trained on JAFFE database is tested on TFEID and vice-versa. The performance The performance comparison in both experiments against SVNI classifier gives promising results.

Coupling ensemble weather predictions based on TIGGE database with Grid-Xinanjiang model for flood forecast

The incorporation of numerical weather predictions (NWP) into a flood forecasting system can increase forecast lead times from a few hours to a few days. A single NWP forecast from a single forecast centre, however, is insufficient as it involves considerable non-predictable uncertainties and lead to a high number of false alarms. The availability of global ensemble numerical weather prediction systems through the THORPEX Interactive Grand Global Ensemble' (TIGGE) offers a new opportunity for flood forecast. The Grid-Xinanjiang distributed hydrological model, which is based on the Xinanjiang model theory and the topographical information of each grid cell extracted from the Digital Elevation Model (DEM), is coupled with ensemble weather predictions based on the TIGGE database (CMC, CMA, ECWMF, UKMO, NCEP) for flood forecast. This paper presents a case study using the coupled flood forecasting model on the Xixian catchment (a drainage area of 8826 km2) located in Henan province, China. A probabilistic discharge is provided as the end product of flood forecast. Results show that the association of the Grid-Xinanjiang model and the TIGGE database gives a promising tool for an early warning of flood events several days ahead.

A Low Consumption Real Time Environmental Monitoring System for Smart Cities based on ZigBee Wireless Sensor Network

Nowadays, there is an increasing interest in wireless sensor networks (WSN) for environmental monitoring systems because it can be used to improve the quality of life and living conditions are becoming a major concern to people. This paper describes the design and development of a real time monitoring system based on ZigBee WSN characterized by a lower energy consumption, low cost, reduced dimensions and fast adaptation to the network tree topology. The developed system encompasses an optimized sensing process about environmental parameters, low rate transmission from sensor nodes to the gateway, packet parsing and data storing in a remote database and real time visualization through a web server.