A virtual head-stick rehabilitation robot system

For individuals with upper-extremity motor disabilities, the head-stick is a simple and intuitive means of performing manipulations because it provides direct proprioceptive information to the user. Through practice and use of inherent proprioceptive cues, users may become quite adept at using the head-stick for a number of different tasks. The traditional head-stick is limited, however, to the user's achievable range of head motion and force generation, which may be insufficient for many tasks. The authors describe an interface to a robot system which emulates the proprioceptive qualities of a traditional head-stick while also allowing for augmented end-effector ranges of force and motion. The design and implementation of the system in terms of coordinate transforms, bilateral telemanipulator architecture, safety systems, and system identification of the master is described, in addition to preliminary evaluation results.

A normative approach to multi-agent systems for intelligent buildings

Building Management Systems (BMS) are widely adopted in modern buildings around the world in order to provide high-quality building services, and reduce the running cost of the building. However, most BMS are functionality-oriented and do not consider user personalization. The aim of this research is to capture and represent building management rules using organizational semiotics methods. We implement Semantic Analysis, which determines semantic units in building management and their relationship patterns of behaviour, and Norm Analysis, which extracts and specifies the norms that establish how and when these management actions occur. Finally, we propose a multi-agent framework for norm based building management. This framework contributes to the design domain of intelligent building management system by defining a set of behaviour patterns, and the norms that govern the real-time behaviour in a building.

Intelligent agents enabling negotiated control of pervasive environments

One of the important goals of the intelligent buildings especially in commercial applications is not only to minimize the energy consumption but also to enhance the occupant’s comfort. However, most of current development in the intelligent buildings focuses on an implementation of the automatic building control systems that can support energy efficiency approach. The consideration of occupants’ preferences is not adequate. To improve occupant’s wellbeing and energy efficiency in intelligent environments, we develop four types of agent combined together to form a multi-agent system to control the intelligent buildings. Users’ preferential conflicts are discussed. Furthermore, a negotiation mechanism for conflict resolution, has been proposed in order to reach an agreement, and has been represented in syntax directed translation schemes for future implementation and testing. Keywords: conflict resolution, intelligent buildings, multi-agent systems (MAS), negotiation strategy, syntax directed translation schemes (SDTS).

Virtual reality Post Traumatic Stress Disorder (PTSD) exposure therapy results with active duty OIF/OEF service members

Posttraumatic stress disorder (PTSD) is reported to be caused by exposure to traumatic events including (but not limited to) military combat, violent personal assault, being kidnapped or taken hostage and terrorist attacks. Initial data suggest that at least 1 out of 6 Iraq War veterans are exhibiting symptoms of depression, anxiety and PTSD. Virtual reality (VR) delivered exposure therapy for PTSD has been used with reports of positive outcomes. The aim of the current paper, is to present the rationale and brief description of a Virtual Iraq/Afghanistan PTSD VR therapy application and present initial findings from its use with PTSD patients. Thus far, Virtual Iraq/Afghanistan consists of a series of customizable virtual scenarios designed to represent relevant Middle Eastern VR contexts for exposure therapy, including a city and desert road convoy environment. User-centered design feedback, needed to iteratively evolve the system, was gathered from returning Iraq War veterans in the USA and from a system deployed in Iraq and tested by an Army Combat Stress Control Team. Results from an open clinical trial at San Diego Naval Medical Center of the first 20 treatment completers indicate that 16 no longer met PTSD screening criteria at post-treatment, with only one not maintaining treatment gains at 3 month follow-up.

Causal volumes in distributed virtual reality

Research to date has tended to concentrate on bandwidth considerations to increase scalability in distributed interactive simulation and virtual reality systems. This paper proposes that the major concern for latency in user interaction is that of the fundamental limit of communication rate due to the speed of light. Causal volumes and surfaces are introduced as a model of the limitations of causality caused by this fundamental delay. The concept of virtual world critical speed is introduced, which can be determined from the causal surface. The implications of the critical speed are discussed, and relativistic dynamics are used to constrain the object speed, in the same way speeds are bounded in the real world.

Improvement of 3D protein models using multiple templates guided by single-template model quality assessment

Motivation: Modelling the 3D structures of proteins can often be enhanced if more than one fold template is used during the modelling process. However, in many cases, this may also result in poorer model quality for a given target or alignment method. There is a need for modelling protocols that can both consistently and significantly improve 3D models and provide an indication of when models might not benefit from the use of multiple target-template alignments. Here, we investigate the use of both global and local model quality prediction scores produced by ModFOLDclust2, to improve the selection of target-template alignments for the construction of multiple-template models. Additionally, we evaluate clustering the resulting population of multi- and single-template models for the improvement of our IntFOLD-TS tertiary structure prediction method. Results: We find that using accurate local model quality scores to guide alignment selection is the most consistent way to significantly improve models for each of the sequence to structure alignment methods tested. In addition, using accurate global model quality for re-ranking alignments, prior to selection, further improves the majority of multi-template modelling methods tested. Furthermore, subsequent clustering of the resulting population of multiple-template models significantly improves the quality of selected models compared with the previous version of our tertiary structure prediction method, IntFOLD-TS.

Surface chemistry of glycine on Pt{111} in different aqueous environments

Adsorption of glycine on Ptf111g under UHV conditions and in different aqueous environments was studied by XPS (UHV and ambient pressure) and NEXAFS. Under UHV conditions, glycine adsorbs in its neutral molecular state up to about 0.15 ML. Further deposition leads to the formation of an additional zwitterionic species, which is in direct contact with the substrate surface, followed by the growth of multilayers, which also consist of zwitterions. The neutral surface species is most stable and decomposes at 360 K through a multi-step process which includes the formation of methylamine and carbon monoxide. When glycine and water are co-adsorbed in UHV at low temperatures (< 170 K) inter-layer diffusion is inhibited and the surface composition depends on the adsorption sequence. Water adsorbed on top of a glycine layer does not lead to significant changes in its chemical state. When glycine is adsorbed on top of a pre-adsorbed chemisorbed water layer or thick ice layer, however, it is found in its zwitterionic state, even at low coverage. No difference is seen in the chemical state of glycine when the layers are exposed to ambient water vapor pressure up to 0.2 Torr at temperatures above 300 K. Also the decomposition temperature stays the same, 360 K, irrespective of the water vapor pressure. Only the reaction path of the decomposition products is affected by ambient water vapor.

ATD: a multiplatform for semiautomatic 3-D detection of kidneys and their pathology in real time

This research presents a novel multi-functional system for medical Imaging-enabled Assistive Diagnosis (IAD). Although the IAD demonstrator has focused on abdominal images and supports the clinical diagnosis of kidneys using CT/MRI imaging, it can be adapted to work on image delineation, annotation and 3D real-size volumetric modelling of other organ structures such as the brain, spine, etc. The IAD provides advanced real-time 3D visualisation and measurements with fully automated functionalities as developed in two stages. In the first stage, via the clinically driven user interface, specialist clinicians use CT/MRI imaging datasets to accurately delineate and annotate the kidneys and their possible abnormalities, thus creating “3D Golden Standard Models”. Based on these models, in the second stage, clinical support staff i.e. medical technicians interactively define model-based rules and parameters for the integrated “Automatic Recognition Framework” to achieve results which are closest to that of the clinicians. These specific rules and parameters are stored in “Templates” and can later be used by any clinician to automatically identify organ structures i.e. kidneys and their possible abnormalities. The system also supports the transmission of these “Templates” to another expert for a second opinion. A 3D model of the body, the organs and their possible pathology with real metrics is also integrated. The automatic functionality was tested on eleven MRI datasets (comprising of 286 images) and the 3D models were validated by comparing them with the metrics from the corresponding “3D Golden Standard Models”. The system provides metrics for the evaluation of the results, in terms of Accuracy, Precision, Sensitivity, Specificity and Dice Similarity Coefficient (DSC) so as to enable benchmarking of its performance. The first IAD prototype has produced promising results as its performance accuracy based on the most widely deployed evaluation metric, DSC, yields 97% for the recognition of kidneys and 96% for their abnormalities; whilst across all the above evaluation metrics its performance ranges between 96% and 100%. Further development of the IAD system is in progress to extend and evaluate its clinical diagnostic support capability through development and integration of additional algorithms to offer fully computer-aided identification of other organs and their abnormalities based on CT/MRI/Ultra-sound Imaging.

Haplotype analysis of vernalization loci in European barley germplasm reveals novel VRN-H1 alleles and a predominant winter VRN-H1/VRN-H2 multi-locus haplotype

In barley, variation in the requirement for vernalization (an extended period of low temperature before flowering can occur) is determined by the VRN-H1, -H2 and -H3 loci. In European cultivated germplasm, most variation in vernalization requirement is accounted for by alleles at VRN-H1 and VRN-H2 only, but the range of allelic variation is largely unexplored. Here we characterise VRN-H1 and VRN-H2 haplotypes in 429 varieties representing a large portion of the acreage sown to barley in Western Europe over the last 60 years. Analysis of genotype, intron I sequencing data and growth habit tests identified three novel VRN-H1 alleles and determined the most frequent VRN-H1 intron I rearrangements. Combined analysis of VRN-H1 and VRN-H2 alleles resulted in the classification of seventeen VRN-H1/VRN-H2 multi-locus haplotypes, three of which account for 79% of varieties. The molecular markers employed here represent powerful diagnostic tools for prediction of growth habit and assessment of varietal purity. These markers will also allow development of germplasm to test the behaviour of individual alleles with the aim of understanding the relationship between allelic variation and adaptation to specific agri-environments.

3D digital elevation model generation

This chapter presents techniques used for the generation of 3D digital elevation models (DEMs) from remotely sensed data. Three methods are explored and discussed—optical stereoscopic imagery, Interferometric Synthetic Aperture Radar (InSAR), and LIght Detection and Ranging (LIDAR). For each approach, the state-of-the-art presented in the literature is reviewed. Techniques involved in DEM generation are presented with accuracy evaluation. Results of DEMs reconstructed from remotely sensed data are illustrated. While the processes of DEM generation from satellite stereoscopic imagery represents a good example of passive, multi-view imaging technology, discussed in Chap. 2 of this book, InSAR and LIDAR use different principles to acquire 3D information. With regard to InSAR and LIDAR, detailed discussions are conducted in order to convey the fundamentals of both technologies.

Educational simulation in construction: the virtual construction simulator

Students in the architecture, engineering, and construction disciplines are often challenged with visualizing and understanding the complex spatial and temporal relationships involved in designing and constructing three-dimensional (3D) structures. An evolving body of research traces the use of educational computer simulations to enhance student learning experiences through testing real-world scenarios and the development of student decision-making skills. Ongoing research at Pennsylvania State University aims to improve engineering education in construction through interactive construction project learning applications in an immersive virtual reality environment. This paper describes the first- and second-generation development of the Virtual Construction Simulator (VCS), a tool that enables students to simultaneously create and review construction schedules through 3D model interaction. The educational value and utility of VCS was assessed through surveys, focus group interviews, and a student exercise conducted in a construction management class. Results revealed VCS is a valuable and effective four-dimensional (4D) model creation and schedule review application that fosters collaborative work and greater student task focus. This paper concludes with a discussion of the findings and the future development steps of the VCS educational simulation

Multi-site evaluation of an urban land-surface model: intra-urban heterogeneity, seasonality and parameter complexity requirements

An extensive off-line evaluation of the Noah/Single Layer Urban Canopy Model (Noah/SLUCM) urban land-surface model is presented using data from 15 sites to assess (1) the ability of the scheme to reproduce the surface energy balance observed in a range of urban environments, including seasonal changes, and (2) the impact of increasing complexity of input parameter information. Model performance is found to be most dependent on representation of vegetated surface area cover; refinement of other parameter values leads to smaller improvements. Model biases in net all-wave radiation and trade-offs between turbulent heat fluxes are highlighted using an optimization algorithm. Here we use the Urban Zones to characterize Energy partitioning (UZE) as the basis to assign default SLUCM parameter values. A methodology (FRAISE) to assign sites (or areas) to one of these categories based on surface characteristics is evaluated. Using three urban sites from the Basel Urban Boundary Layer Experiment (BUBBLE) dataset, an independent evaluation of the model performance with the parameter values representative of each class is performed. The scheme copes well with both seasonal changes in the surface characteristics and intra-urban heterogeneities in energy flux partitioning, with RMSE performance comparable to similar state-of-the-art models for all fluxes, sites and seasons. The potential of the methodology for high-resolution atmospheric modelling application using the Weather Research and Forecasting (WRF) model is highlighted. This analysis supports the recommendations that (1) three classes are appropriate to characterize the urban environment, and (2) that the parameter values identified should be adopted as default values in WRF.

Visual sensor fusion for active security in robotic industrial environments

This work presents a method of information fusion involving data captured by both a standard CCD camera and a ToF camera to be used in the detection of the proximity between a manipulator robot and a human. Both cameras are assumed to be located above the work area of an industrial robot. The fusion of colour images and time of light information makes it possible to know the 3D localization of objects with respect to a world coordinate system. At the same time this allows to know their colour information. Considering that ToF information given by the range camera contains innacuracies including distance error, border error, and pixel saturation, some corrections over the ToF information are proposed and developed to improve the results. The proposed fusion method uses the calibration parameters of both cameras to reproject 3D ToF points, expressed in a common coordinate system for both cameras and a robot arm, in 2D colour images. In addition to this, using the 3D information, the motion detection in a robot industrial environment is achieved, and the fusion of information is applied to the foreground objects previously detected. This combination of information results in a matrix that links colour and 3D information, giving the possibility of characterising the object by its colour in addition to its 3D localization. Further development of these methods will make it possible to identify objects and their position in the real world, and to use this information to prevent possible collisions between the robot and such objects.

Cost function for sub-agent elements in multi-agent energy management system

Distributed generation plays a key role in reducing CO2 emissions and losses in transmission of power. However, due to the nature of renewable resources, distributed generation requires suitable control strategies to assure reliability and optimality for the grid. Multi-agent systems are perfect candidates for providing distributed control of distributed generation stations as well as providing reliability and flexibility for the grid integration. The proposed multi-agent energy management system consists of single-type agents who control one or more gird entities, which are represented as generic sub-agent elements. The agent applies one control algorithm across all elements and uses a cost function to evaluate the suitability of the element as a supplier. The behavior set by the agent's user defines which parameters of an element have greater weight in the cost function, which allows the user to specify the preference on suppliers dynamically. This study shows the ability of the multi-agent energy management system to select suppliers according to the selection behavior given by the user. The optimality of the supplier for the required demand is ensured by the cost function based on the parameters of the element.

Visual sensor fusion for active security in robotic industrial environments

This work presents a method of information fusion involving data captured by both a standard charge-coupled device (CCD) camera and a time-of-flight (ToF) camera to be used in the detection of the proximity between a manipulator robot and a human. Both cameras are assumed to be located above the work area of an industrial robot. The fusion of colour images and time-of-flight information makes it possible to know the 3D localization of objects with respect to a world coordinate system. At the same time, this allows to know their colour information. Considering that ToF information given by the range camera contains innacuracies including distance error, border error, and pixel saturation, some corrections over the ToF information are proposed and developed to improve the results. The proposed fusion method uses the calibration parameters of both cameras to reproject 3D ToF points, expressed in a common coordinate system for both cameras and a robot arm, in 2D colour images. In addition to this, using the 3D information, the motion detection in a robot industrial environment is achieved, and the fusion of information is applied to the foreground objects previously detected. This combination of information results in a matrix that links colour and 3D information, giving the possibility of characterising the object by its colour in addition to its 3D localisation. Further development of these methods will make it possible to identify objects and their position in the real world and to use this information to prevent possible collisions between the robot and such objects.