A low-complexity flight controller for Unmanned Aircraft Systems with constrained control allocation

In this paper, we propose a framework for joint allocation and constrained control design of flight controllers for Unmanned Aircraft Systems (UAS). The actuator configuration is used to map actuator constraint set into the space of the aircraft generalised forces. By constraining the demanded generalised forces, we ensure that the allocation problem is always feasible; and therefore, it can be solved without constraints. This leads to an allocation problem that does not require on-line numerical optimisation. Furthermore, since the controller handles the constraints, and there is no need to implement heuristics to inform the controller about actuator saturation. The latter is fundamental for avoiding Pilot Induced Oscillations (PIO) in remotely operated UAS due to the rate limit on the aircraft control surfaces.

Task modeling for collaborative authoring

Motivation ?Task analysis for designing modern collaborative work needs a more fine grained approach. Especially in a complex task domain, like collaborative scientific authoring, when there is a single overall goal that can only be accomplished only by collaboration between multiple roles, each requiring its own expertise. We analyzed and re-considered roles, activities, and objects for design for complex collaboration contexts. Our main focus is on a generic approach to design for multiple roles and subtasks in a domain with a shared overall goal, which requires a detailed approach. Collaborative authoring is our current example. This research is incremental: an existing task analysis approach (GTA) is reconsidered by applying it to a case of complex collaboration. Our analysis shows that designing for collaboration indeed requires a refined approach to task modeling: GTA, in future, will need to consider tasks at the lowest level that can be delegated or mandates. These tasks need to be analyzed and redesigned in more in detail, along with the relevant task object.

Treatment plan complexity metrics for predicting IMRT pre-treatment quality assurance results

The planning of IMRT treatments requires a compromise between dose conformity (complexity) and deliverability. This study investigates established and novel treatment complexity metrics for 122 IMRT beams from prostate treatment plans. The Treatment and Dose Assessor software was used to extract the necessary data from exported treatment plan files and calculate the metrics. For most of the metrics, there was strong overlap between the calculated values for plans that passed and failed their quality assurance (QA) tests. However, statistically significant variation between plans that passed and failed QA measurements was found for the established modulation index and for a novel metric describing the proportion of small apertures in each beam. The ‘small aperture score’ provided threshold values which successfully distinguished deliverable treatment plans from plans that did not pass QA, with a low false negative rate.

Distinguishing between task and contextual performance for nurses : development of a job performance scale

Aim. This paper is a report of a development and validation of a new job performance scale based on an established job performance model. Background. Previous measures of nursing quality are atheoretical and fail to incorporate the complete range of behaviours performed. Thus, an up-to-date measure of job performance is required for assessing nursing quality. Methods. Test construction involved systematic generation of test items using focus groups, a literature review, and an expert review of test items. A pilot study was conducted to determine the multidimensional nature of the taxonomy and its psychometric properties. All data were collected in 2005. Findings. The final version of the nursing performance taxonomy included 41 behaviours across eight dimensions of job performance. Results from preliminary psychometric investigations suggest that the nursing performance scale has good internal consistency, good convergent validity and good criterion validity. Conclusion. The findings give preliminary support for a new job performance scale as a reliable and valid tool for assessing nursing quality. However, further research using a larger sample and nurses from a broader geographical region is required to cross-validate the measure. This scale may be used to guide hospital managers regarding the quality of nursing care within units and to guide future research in the area.

The stress-buffering effects of control on task satisfaction and perceived goal attainment : an experimental study of the moderating influence of desire for control

The purpose of the present study was to examine the extent to which Desire for Control (DFC) interacts with experimental manipulations of demand and control, and the consequences of these interactions on task satisfaction and perceived goal attainment (i.e. task performance and task mastery). It was expected that the proposed stress-buffering effects of control would be evident only for individuals high in DFC. Moreover, it was anticipated that control may have a stress-exacerbating effect for those low in DFC. These hypotheses were tested on a sample of 137 first year psychology students who participated in an in-basket activity under low and high conditions of demand and control. Results revealed that the proposed stress-buffering effect of control was found only for those high in DFC and a stress-exacerbating effect of increased control was evident for those low in DFC on task performance and task mastery perceptions. Future research directions and the implications of these findings to applied settings are discussed.

Task-relationship-self : a framework for understanding service encounter behaviors

Research conducted over past decades has investigated selected service encounter behaviors from either a customer or service provider perspective. However, a comprehensive, dual-perspective framework is lacking. Such a framework is needed to organize knowledge of these behaviors, and thereby provide structure, clarity, and parsimony to the field. This paper describes a three-tier framework of service encounter behavior that was developed by applying grounded theory principles to interviews with customers, service employees, and other stakeholders. These informants described many ways in which they behave when executing service exchanges, dealing with service difficulties, and managing themselves in the process. Using an iterative inductive approach, a conceptual framework was developed in which specific (Tier 1) behaviors were placed within broader (Tier 2) categories, and these lower classification levels were, in turn, interpreted within a conceptual space defined by the (Tier 3) dimensions of task, relationship, and self. This framework was then elaborated and refined by reference to the psychology and marketing literature, a set of 157 audio-recorded service interactions, and an expert panel study. The paper includes comparisons between the framework and those previously proposed, propositions regarding service encounter processes and outcomes, and implications for future research and practice.

General self-efficacy influences affective task reactions during a work simulation : the temporal effects of changes in workload at different levels of control

This study investigated the effects of workload, control, and general self-efficacy on affective task reactions (i.e., demands-ability fit, active coping, and anxiety) during a work simulation. The main goals were: (1) to determine the extent general self-efficacy moderates the effects of demand and control on affective task reactions, and; (2) to determine if this varies as a function of changes in workload. Participants (N=141) completed an inbox activity under conditions of low or high control and within low and high workload conditions. The order of trials varied so that workload increased or decreased. Results revealed individuals with high general self-efficacy reported better demands-abilities fit and active coping as well as less anxiety. Three interactive effects were found. First, it was found that high control increased demands-abilities fit from trial 1 to trial 2, but only when workload decreased. Second, it was found that low efficacious individuals active coping increased in trial 2, but only under high control. Third, it was found that high control helped high efficacious individuals manage anxiety when workload decreased. However, for individuals with low general self-efficacy, neither high nor low control alleviated anxiety (i.e., whether workload increased or decreased over time).

Image-guided sampling reveals increased stroma and lower glandular complexity in mammographically dense breast tissue

Mammographic density (MD) adjusted for age and body mass index (BMI) is a strong heritable breast cancer risk factor; however, its biological basis remains elusive. Previous studies assessed MD-associated histology using random sampling approaches, despite evidence that high and low MD areas exist within a breast and are negatively correlated with respect to one another. We have used an image-guided approach to sample high and low MD tissues from within individual breasts to examine the relationship between histology and degree of MD. Image-guided sampling was performed using two different methodologies on mastectomy tissues (n = 12): (1) sampling of high and low MD regions within a slice guided by bright (high MD) and dark (low MD) areas in a slice X-ray film; (2) sampling of high and low MD regions within a whole breast using a stereotactically guided vacuum-assisted core biopsy technique. Pairwise analysis accounting for potential confounders (i.e. age, BMI, menopausal status, etc.) provides appropriate power for analysis despite the small sample size. High MD tissues had higher stromal (P = 0.002) and lower fat (P = 0.002) compositions, but no evidence of difference in glandular areas (P = 0.084) compared to low MD tissues from the same breast. High MD regions had higher relative gland counts (P = 0.023), and a preponderance of Type I lobules in high MD compared to low MD regions was observed in 58% of subjects (n = 7), but did not achieve significance. These findings clarify the histologic nature of high MD tissue and support hypotheses regarding the biophysical impact of dense connective tissue on mammary malignancy. They also provide important terms of reference for ongoing analyses of the underlying genetics of MD.

Automatic inference of driving task demand from visual cues of emotion and attention

Sensing the mental, physical and emotional demand of a driving task is of primary importance in road safety research and for effectively designing in-vehicle information systems (IVIS). Particularly, the need of cars capable of sensing and reacting to the emotional state of the driver has been repeatedly advocated in the literature. Algorithms and sensors to identify patterns of human behavior, such as gestures, speech, eye gaze and facial expression, are becoming available by using low cost hardware: This paper presents a new system which uses surrogate measures such as facial expression (emotion) and head pose and movements (intention) to infer task difficulty in a driving situation. 11 drivers were recruited and observed in a simulated driving task that involved several pre-programmed events aimed at eliciting emotive reactions, such as being stuck behind slower vehicles, intersections and roundabouts, and potentially dangerous situations. The resulting system, combining face expressions and head pose classification, is capable of recognizing dangerous events (such as crashes and near misses) and stressful situations (e.g. intersections and way giving) that occur during the simulated drive.

Plasma nanoscience : from controlled complexity to practical simplicity

Plasma Nanoscience is a multidisciplinary research field which aims to elucidate the specific roles, purposes, and benefits of the ionized gas environment in assembling and processing nanoscale objects in natural, laboratory and technological situations. Compared to neutral gas-based routes, in low-temperature weakly-ionized plasmas there is another level of complexity related to the necessity of creating and sustaining a suitable degree of ionization and a much larger number of species generated in the gas phase. The thinner the nanotubes, the stronger is the quantum confinement of electrons and more unique size-dependent quantum effects can emerge. Furthermore, due to a very high mobility of electrons, the surfaces are at a negative potential compared to the plasma bulk. Therefore, there are non-uniform electric fields within the plasma sheath. The electric field lines start in the plasma bulk and converge to the sharp tips of the developing one-dimensional nanostructures.

A control theoretic paradigm for cell signaling networks : a simple complexity for a sensitive robustness

The fields of molecular biology and cell biology are being flooded with complex genomic and proteomic datasets of large dimensions. We now recognize that each molecule in the cell and tissue can no longer be viewed as an isolated entity. Instead, each molecule must be considered as one member of an interacting network. Consequently, there is an urgent need for mathematical models to understand the behavior of cell signaling networks in health and in disease.

Workflow patterns as a means to model task succession in games – a preliminary case study

Over about the last decade, people involved in game development have noted the need for more formal models and tools to support the design phase of games. It is argued that the present lack of such formal tools is currently hindering knowledge transfer among designers. Formal visual languages, on the other hand, can help to more effectively express, abstract and communicate game design concepts. Moreover, formal tools can assist in the prototyping phase, allowing designers to reason about and simulate game mechanics on an abstract level. In this paper we present an initial investigation into whether workflow patterns – which have already proven to be effective for modeling business processes – are a suitable way to model task succession in games. Our preliminary results suggest that workflow patterns show promise in this regard but some limitations, especially in regard to time constraints, currently restrict their potential.

Controlling current and voltage type interfaces in power-hardware-in-the-loop simulations

The usual practice to study a large power system is through digital computer simulation. However, the impact of large scale use of small distributed generators on a power network cannot be evaluated strictly by simulation since many of these components cannot be accurately modelled. Moreover, the network complexity makes the task of practical testing on a physical network nearly impossible. This study discusses the paradigm of interfacing a real-time simulation of a power system to real-life hardware devices. This type of splitting a network into two parts and running a real-time simulation with a physical system in parallel is usually termed as power-hardware-in-the-loop (PHIL) simulation. The hardware part is driven by a voltage source converter that amplifies the signals of the simulator. In this paper, the effects of suitable control strategy on the performance of PHIL and the associated stability aspects are analysed in detail. The analyses are validated through several experimental tests using an real-time digital simulator.

Development of gas sensing technology for ground and airborne applications powered by solar energy : methodology and experimental results

Monitoring gases for environmental, industrial and agricultural fields is a demanding task that requires long periods of observation, large quantity of sensors, data management, high temporal and spatial resolution, long term stability, recalibration procedures, computational resources, and energy availability. Wireless Sensor Networks (WSNs) and Unmanned Aerial Vehicles (UAVs) are currently representing the best alternative to monitor large, remote, and difficult access areas, as these technologies have the possibility of carrying specialised gas sensing systems, and offer the possibility of geo-located and time stamp samples. However, these technologies are not fully functional for scientific and commercial applications as their development and availability is limited by a number of factors: the cost of sensors required to cover large areas, their stability over long periods, their power consumption, and the weight of the system to be used on small UAVs. Energy availability is a serious challenge when WSN are deployed in remote areas with difficult access to the grid, while small UAVs are limited by the energy in their reservoir tank or batteries. Another important challenge is the management of data produced by the sensor nodes, requiring large amount of resources to be stored, analysed and displayed after long periods of operation. In response to these challenges, this research proposes the following solutions aiming to improve the availability and development of these technologies for gas sensing monitoring: first, the integration of WSNs and UAVs for environmental gas sensing in order to monitor large volumes at ground and aerial levels with a minimum of sensor nodes for an effective 3D monitoring; second, the use of solar energy as a main power source to allow continuous monitoring; and lastly, the creation of a data management platform to store, analyse and share the information with operators and external users. The principal outcomes of this research are the creation of a gas sensing system suitable for monitoring any kind of gas, which has been installed and tested on CH4 and CO2 in a sensor network (WSN) and on a UAV. The use of the same gas sensing system in a WSN and a UAV reduces significantly the complexity and cost of the application as it allows: a) the standardisation of the signal acquisition and data processing, thereby reducing the required computational resources; b) the standardisation of calibration and operational procedures, reducing systematic errors and complexity; c) the reduction of the weight and energy consumption, leading to an improved power management and weight balance in the case of UAVs; d) the simplification of the sensor node architecture, which is easily replicated in all the nodes. I evaluated two different sensor modules by laboratory, bench, and field tests: a non-dispersive infrared module (NDIR) and a metal-oxide resistive nano-sensor module (MOX nano-sensor). The tests revealed advantages and disadvantages of the two modules when used for static nodes at the ground level and mobile nodes on-board a UAV. Commercial NDIR modules for CO2 have been successfully tested and evaluated in the WSN and on board of the UAV. Their advantage is the precision and stability, but their application is limited to a few gases. The advantages of the MOX nano-sensors are the small size, low weight, low power consumption and their sensitivity to a broad range of gases. However, selectivity is still a concern that needs to be addressed with further studies. An electronic board to interface sensors in a large range of resistivity was successfully designed, created and adapted to operate on ground nodes and on-board UAV. The WSN and UAV created were powered with solar energy in order to facilitate outdoor deployment, data collection and continuous monitoring over large and remote volumes. The gas sensing, solar power, transmission and data management systems of the WSN and UAV were fully evaluated by laboratory, bench and field testing. The methodology created to design, developed, integrate and test these systems was extensively described and experimentally validated. The sampling and transmission capabilities of the WSN and UAV were successfully tested in an emulated mission involving the detection and measurement of CO2 concentrations in a field coming from a contaminant source; the data collected during the mission was transmitted in real time to a central node for data analysis and 3D mapping of the target gas. The major outcome of this research is the accomplishment of the first flight mission, never reported before in the literature, of a solar powered UAV equipped with a CO2 sensing system in conjunction with a network of ground sensor nodes for an effective 3D monitoring of the target gas. A data management platform was created using an external internet server, which manages, stores, and shares the data collected in two web pages, showing statistics and static graph images for internal and external users as requested. The system was bench tested with real data produced by the sensor nodes and the architecture of the platform was widely described and illustrated in order to provide guidance and support on how to replicate the system. In conclusion, the overall results of the project provide guidance on how to create a gas sensing system integrating WSNs and UAVs, how to power the system with solar energy and manage the data produced by the sensor nodes. This system can be used in a wide range of outdoor applications, especially in agriculture, bushfires, mining studies, zoology, and botanical studies opening the way to an ubiquitous low cost environmental monitoring, which may help to decrease our carbon footprint and to improve the health of the planet.

Predicting sense convergence with distributional semantics : an application to the CogALex-IV 2014 shared task

This paper presents our system to address the CogALex-IV 2014 shared task of identifying a single word most semantically related to a group of 5 words (queries). Our system uses an implementation of a neural language model and identifies the answer word by finding the most semantically similar word representation to the sum of the query representations. It is a fully unsupervised system which learns on around 20% of the UkWaC corpus. It correctly identifies 85 exact correct targets out of 2,000 queries, 285 approximate targets in lists of 5 suggestions.