The co-occurrence of autism and Williams syndrome: a case study report

This paper describes a longitudinal case study detailing the communication profile of one child with both Williams syndrome (WS) and autism. The participant was administered two standardized assessments of language and general cognitive abilities. His parents completed the Pre-Verbal Communication Schedule; and a sample of the child's spontaneous interaction was analyzed. The results show that this child presents with markedly delayed language and communication skills and that his communication profile is the opposite of the assumed 'typical' WS profile. The conclusion is that clinicians need to be aware of the co-occurrence of genetic disorders, such as WS and autism in order to facilitate accurate diagnosis and effective treatment.

Case Study: Interacting with Volumetric Medical Datasets in Networked CAVE Environments

Virtual Reality (VR) is widely used in visualizing medical datasets. This interest has emerged due to the usefulness of its techniques and features. Such features include immersion, collaboration, and interactivity. In a medical visualization context, immersion is important, because it allows users to interact directly and closelywith detailed structures in medical datasets. Collaboration on the other hand is beneficial, because it gives medical practitioners the chance to share their expertise and offer feedback and advice in a more effective and intuitive approach. Interactivity is crucial in medical visualization and simulation systems, because responsiveand instantaneous actions are key attributes in applications, such as surgical simulations. In this paper we present a case study that investigates the use of VR in a collaborative networked CAVE environment from a medical volumetric visualization perspective. The study will present a networked CAVE application, which has been built to visualize and interact with volumetric datasets. We will summarize the advantages of such an application and the potential benefits of our system. We also will describe the aspects related to this application area and the relevant issues of such implementations.

Case study: object and ground point separation on a river bank using airborne based LIDAR data

In the past decade, airborne based LIght Detection And Ranging (LIDAR) has been recognised by both the commercial and public sectors as a reliable and accurate source for land surveying in environmental, engineering and civil applications. Commonly, the first task to investigate LIDAR point clouds is to separate ground and object points. Skewness Balancing has been proven to be an efficient non-parametric unsupervised classification algorithm to address this challenge. Initially developed for moderate terrain, this algorithm needs to be adapted to handle sloped terrain. This paper addresses the difficulty of object and ground point separation in LIDAR data in hilly terrain. A case study on a diverse LIDAR data set in terms of data provider, resolution and LIDAR echo has been carried out. Several sites in urban and rural areas with man-made structure and vegetation in moderate and hilly terrain have been investigated and three categories have been identified. A deeper investigation on an urban scene with a river bank has been selected to extend the existing algorithm. The results show that an iterative use of Skewness Balancing is suitable for sloped terrain.

Rejoinder to 'Performance of different synchronisation measures in real data: A case study on electroencephalograhic signals

We agree with Duckrow and Albano [Phys. Rev. E 67, 063901 (2003)] and Quian Quiroga et al. [Phys. Rev. E 67, 063902 (2003)] that mutual information (MI) is a useful measure of dependence for electroencephalogram (EEG) data, but we show that the improvement seen in the performance of MI on extracting dependence trends from EEG is more dependent on the type of MI estimator rather than any embedding technique used. In an independent study we conducted in search for an optimal MI estimator, and in particular for EEG applications, we examined the performance of a number of MI estimators on the data set used by Quian Quiroga et al. in their original study, where the performance of different dependence measures on real data was investigated [Phys. Rev. E 65, 041903 (2002)]. We show that for EEG applications the best performance among the investigated estimators is achieved by k-nearest neighbors, which supports the conjecture by Quian Quiroga et al. in Phys. Rev. E 67, 063902 (2003) that the nearest neighbor estimator is the most precise method for estimating MI.

Comment on "Performance of different synchronization measures in real data: A case study on electroencephalographic signals"

We agree with Duckrow and Albano [Phys. Rev. E 67, 063901 (2003)] and Quian Quiroga [Phys. Rev. E 67, 063902 (2003)] that mutual information (MI) is a useful measure of dependence for electroencephalogram (EEG) data, but we show that the improvement seen in the performance of MI on extracting dependence trends from EEG is more dependent on the type of MI estimator rather than any embedding technique used. In an independent study we conducted in search for an optimal MI estimator, and in particular for EEG applications, we examined the performance of a number of MI estimators on the data set used by Quian Quiroga in their original study, where the performance of different dependence measures on real data was investigated [Phys. Rev. E 65, 041903 (2002)]. We show that for EEG applications the best performance among the investigated estimators is achieved by k-nearest neighbors, which supports the conjecture by Quian Quiroga in Phys. Rev. E 67, 063902 (2003) that the nearest neighbor estimator is the most precise method for estimating MI.

e-learning in project management using simulation models: a case study based on the replication of an experiment

Current e-learning systems are increasing their importance in higher education. However, the state of the art of e-learning applications, besides the state of the practice, does not achieve the level of interactivity that current learning theories advocate. In this paper, the possibility of enhancing e-learning systems to achieve deep learning has been studied by replicating an experiment in which students had to learn basic software engineering principles. One group learned these principles using a static approach, while the other group learned the same principles using a system-dynamics-based approach, which provided interactivity and feedback. The results show that, quantitatively, the latter group achieved a better understanding of the principles; furthermore, qualitatively, they enjoyed the learning experience

Pollen analysis and planted ancient woodland restoration strategies: a case study from the Wentwood, southeast Wales,UK

This paper considers the contribution of pollen analysis to conservation strategies aimed at restoring planted ancient woodland. Pollen and charcoal data are presented from organic deposits located adjacent to the Wentwood, a large planted ancient woodland in southeast Wales. Knowledge of the ecosystems preceding conifer planting can assist in restoring ancient woodlands by placing fragmented surviving ancient woodland habitats in a broader ecological, historical and cultural context. These habitats derive largely from secondary woodland that regenerated in the 3rd–5th centuries A.D. following largescale clearance of Quercus-Corylus woodland during the Romano-British period. Woodland regeneration favoured Fraxinus and Betula. Wood pasture and common land dominated the Wentwood during the medieval period until the enclosures of the 17th century. Surviving ancient woodland habitats contain an important Fagus component that probably reflects an earlier phase of planting preceding conifer planting in the 1880s. It is recommended that restoration measures should not aim to recreate static landscapes or woodland that existed under natural conditions. Very few habitats within the Wentwood can be considered wholly natural because of the long history of human impact. In these circumstances, restoration should focus on restoring those elements of the cultural landscape that are of most benefit to a range of flora and fauna, whilst taking into account factors that present significant issues for future conservation management, such as the adverse effects from projected climate change.

Activation of lower back muscles via FES for pressure sores prevention in paraplegia: a case study

The aim of this paper is to show the feasibility of the use of functional electrical stimulation (FES) applied to the lower back muscles for pressure sores prevention in paraplegia. The hypothesis under study is that FES induces a change in the pressure distribution on the contact area during sitting. Tests were conducted on a paraplegic subject (T5), sitting on a standard wheelchair and cushion. Trunk extensors (mainly the erector spinae) were stimulated using surface electrodes placed on the skin. A pressure mapping system was used to measure the pressure on the sitting surface in four situations: (a) no stimulation; (b) stimulation on one side of the spine only; (c) stimulation on both sides, at different levels; and (d) stimulation at the same level on both sides, during pressure-relief manoeuvres. A session of prolonged stimulation was also conducted. The experimental results show that the stimulation of the erector spinae on one side of the spine can induce a trunk rotation on the sagittal plane, which causes a change in the pressure distribution. A decrease of pressure on the side opposite to the stimulation was recorded. The phenomenon is intensified when different levels of stimulation are applied to the two sides, and such change can be sustained for a considerable time (around 5 minutes). The stimulation did not induce changes during pressure-relief manoeuvres. Finally, from this research we can conclude that the stimulation of the trunk extensors can be a useful tool for pressure sores prevention, and can potentially be used in a routine for pressure sores prevention based on periodical weight shifts.

Quantitative evaluation of three reconfiguration strategies on FPGAs: a case study

Reconfigurable computing is becoming an important new alternative for implementing computations. Field programmable gate arrays (FPGAs) are the ideal integrated circuit technology to experiment with the potential benefits of using different strategies of circuit specialization by reconfiguration. The final form of the reconfiguration strategy is often non-trivial to determine. Consequently, in this paper, we examine strategies for reconfiguration and, based on our experience, propose general guidelines for the tradeoffs using an area-time metric called functional density. Three experiments are set up to explore different reconfiguration strategies for FPGAs applied to a systolic implementation of a scalar quantizer used as a case study. Quantitative results for each experiment are given. The regular nature of the example means that the results can be generalized to a wide class of industry-relevant problems based on arrays.