Free-living inferential modeling of blood glucose level using only noninvasive inputs

The goal of this work is to present a causation modeling methodology with the ability to accurately infer blood glucose levels using a large set of highly correlated noninvasive input variables over an extended period of time. These models can provide insight to improve glucose monitoring, and glucose regulation through advanced model-based control technologies. The efficacy of this approach is demonstrated using real data from a type 2 diabetic (T2D) subject collected under free-living conditions over a period of 25 consecutive days. The model was identified and tested using eleven variables that included three food variables as well as several activity and stress variables. The model was trained using 20 days of data and validated using 5 days of data. This gave a fitted correlation coefficient of 0.70 and an average absolute error (AAE) (i.e., the average of the absolute values for the measured glucose concentration minus modeled glucose concentration) of 13.3 mg/dL for the validation data. This AAE result was significantly better than the subject’s personal glucose meter AAE of 15.3 mg/dL for replicated measurements.     

Discovering and restoring changes in object positions using an autonomous robot with laser rangefinders

This paper describes an object rearrangement system for an autonomous mobile robot. The objective of the robot is to autonomously explore and learn about an environment, to detect changes in the environment on a later visit after object disturbances and finally, to move objects back to their original positions. In the implementation, it is assumed that the robot does not have any prior knowledge of the environment and the positions of the objects. The system exploits Simultaneous Localisation and Mapping (SLAM) and autonomous exploration techniques to achieve the task. These techniques allow the robot to perform localisation and mapping which is required to perform the object rearrangement task autonomously. The system includes an arrangement change detector, object tracking and map update that work with a Polar Scan Match (PSM) Extended Kalman Filter (EKF) SLAM system. In addition, a path planning technique for dragging and pushing an object is also presented in this paper. Experimental results of the integrated approach are shown to demonstrate that the proposed approach provides real-time autonomous object rearrangements by a mobile robot in an initially unknown real environment. Experiments also show the limits of the system by investigating failure modes.     

Formal analysis of human operator behavioural patterns in interactive surveillance systems

An important area of Human Reliability Assessment in interactive systems is the ability to understand the causes of human error and to model their occurrence. This paper investigates a new approach to analysis of task failures based on patterns of operator behaviour, in contrast with more traditional event-based approaches. It considers, as a case study, a formal model of an Air Traffic Control system operator’s task which incorporates a simple model of the high-level cognitive processes involved. The cognitive model is formalised in the CSP process algebra. Various patterns of behaviour that could lead to task failure are described using temporal logic. Then a model-checking technique is used to verify whether the set of selected behavioural patterns is sound and complete with respect to the definition of task failure. The decomposition is shown to be incomplete and a new behavioural pattern is identified, which appears to have been overlooked in the informal analysis of the problem. This illustrates how formal analysis of operator models can yield fresh insights into how failures may arise in interactive systems.

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Simulated train driving: fatigue, self-awareness and cognitive disengagement

Fatigue is a serious issue for the rail industry, increasing inefficiency and accident risk. The performance of 20 train drivers in a rail simulator was investigated at low, moderate and high fatigue levels. Psychomotor vigilance (PVT), self-rated performance and subjective alertness were also assessed. Alertness, PVT reaction times, extreme speed violations (>25% above the limit) and penalty brake applications increased with increasing fatigue level. In contrast, fuel use, draft (stretch) forces and braking errors were highest at moderate fatigue levels. Thus, at high fatigue levels, errors involving a failure to act (errors of omission) increased, whereas incorrect responses (errors of commission) decreased. The differential effect of fatigue on error types can be explained through a cognitive disengagement with the virtual train at high fatigue levels. Interaction with the train reduced dramatically, and accident risk increased. Awareness of fatigue-related performance changes was moderate at best. These findings are of operational concern.     

Gas particle industrial flow simulation using RANSTAD

A turbulent gas particle finite-volume flow simulation of a representative coal classifier is presented. Typical values of the loading ratio permit a one-way coupling analysis. As a case study, the computational fluid dynamics code,ranstad, and the modelling aspects are discussed in some detail. The simulation indicates that small (≈ 30 μm) coal particles pass through the classifier to the furnace but that large (≈ 300 μm) particles are captured and remilled. The computational simulation indicates that the classifier performance can be improved by internal geometric modification. The commitment of the Electricity Commission of New South Wales (Pacific Power) to the exploitation of Computational Engineering for the improvement of all aspects of electricity generation is acknowledged.     

Decision support aids with anthropomorphic characteristics influence trust and performance in younger and older adults

This study examined the use of deliberately anthropomorphic automation on younger and older adults' trust, dependence and performance on a diabetes decision-making task. Research with anthropomorphic interface agents has shown mixed effects in judgments of preferences but has rarely examined effects on performance. Meanwhile, research in automation has shown some forms of anthropomorphism (e.g. etiquette) have effects on trust and dependence on automation. Participants answered diabetes questions with no-aid, a non-anthropomorphic aid or an anthropomorphised aid. Trust and dependence in the aid was measured. A minimally anthropomorphic aide primarily affected younger adults' trust in the aid. Dependence, however, for both age groups was influenced by the anthropomorphic aid. Automation that deliberately embodies person-like characteristics can influence trust and dependence on reasonably reliable automation. However, further research is necessary to better understand the specific aspects of the aid that affect different age groups. Automation that embodies human-like characteristics may be useful in situations where there is under-utilisation of reasonably reliable aids by enhancing trust and dependence in that aid. Practitioner Summary: The design of decision-support aids on consumer devices (e.g. smartphones) may influence the level of trust that users place in that system and their amount of use. This study is the first step in articulating how the design of aids may influence user's trust and use of such systems.     

Preoperative radiotherapy for adenocarcinoma of the rectosigmoid

Ninety-seven patients with adenocarcinoma of the rectosigmoid have been treated with high dose (5000-6000 rad) preoperative irradiation from 1960 through 1972 at the University of Oregon Health Sciences Center. Fifty-seven were initially clinically resectable and 40 were initially inoperable. Forty of the 57 initially clinically resectable patients had "curative" resections and are at risk for more than 5 years. An increase in 5-year survival (from 38% to 53%) and an absence of pelvic recurrence have occurred in those patients receiving preoperative irradiation and "curative" resection. Four of the 40 initially inoperable patients are alive without tumor. Three of the four survivors had irradiation and surgery; one had irradiation only. An additional four patients had no evidence of tumor at death. Tumor was totally sterilized by irradiation and nine patients and reduced to microfocal extent in an additional three of the 97 patients. Incidence of complications was no greater than has been reported in a surgical series from the same institution.     

Vision in and out of vehicles

At the Australian National University's Intelligent Vehicle Project, we are developing subsystems for: driver fatigue or inattention detection; pedestrian spotting; blind-spot checking and merging assistance to validate whether sufficient clearance exists between cars; driver feedback for lane keeping; computer-augmented vision (that is, lane boundary or vehicle highlighting on a head-up display); traffic sign detection and recognition; and human factors research aids Systems that perform such supporting tasks are generally called driver assistance systems (DAS). We believe that implementing DAS could prevent similar accidents or at least reduce their severity.     

Deformable M-Reps for 3D Medical Image Segmentation

M-reps (formerly called DSLs) are a multiscale medial means for modeling and rendering 3D solid geometry. They are particularly well suited to model anatomic objects and in particular to capture prior geometric information effectively in deformable models segmentation approaches. The representation is based on figural models, which define objects at coarse scale by a hierarchy of figures—each figure generally a slab representing a solid region and its boundary simultaneously. This paper focuses on the use of single figure models to segment objects of relatively simple structure.A single figure is a sheet of medial atoms, which is interpolated from the model formed by a net, i.e., a mesh or chain, of medial atoms (hence the name m-reps), each atom modeling a solid region via not only a position and a width but also a local figural frame giving figural directions and an object angle between opposing, corresponding positions on the boundary implied by the m-rep. The special capability of an m-rep is to provide spatial and orientational correspondence between an object in two different states of deformation. This ability is central to effective measurement of both geometric typicality and geometry to image match, the two terms of the objective function optimized in segmentation by deformable models. The other ability of m-reps central to effective segmentation is their ability to support segmentation at multiple levels of scale, with successively finer precision. Objects modeled by single figures are segmented first by a similarity transform augmented by object elongation, then by adjustment of each medial atom, and finally by displacing a dense sampling of the m-rep implied boundary. While these models and approaches also exist in 2D, we focus on 3D objects.The segmentation of the kidney from CT and the hippocampus from MRI serve as the major examples in this paper. The accuracy of segmentation as compared to manual, slice-by-slice segmentation is reported.