Iterative solution of a class of linear equations with application to reconstruction of three-dimensional object arrays

An iterative algorithm baaed on probabilistic estimation is described for obtaining the minimum-norm solution of a very large, consistent, linear system of equations AX = g where A is an (m times n) matrix with non-negative elements, x and g are respectively (n times 1) and (m times 1) vectors with positive components.

Naming ranges in Excel

When working with functions in Excel you can reference a range of cells by simply selecting the cells. For instance if you wanted to sum all your first month sales located in the range B3:B16, the function would be =SUM(B3:B16).

An object-centred approach to encourage online participation in the context of behaviour change

Online groups rely on contributions from their members to flourish, but in the context of behaviour change individuals are typically reluctant to participate actively before they have changed successfully. We took inspiration from CSCW research on objects to address this problem by shifting the focus of online participation from the exchange of personal experiences to more incidental interactions mediated by objects that offer support for change. In this article we describe how we designed, deployed and studied a smartphone application that uses different objects, called distractions and tips, to facilitate social interaction amongst people trying to quit smoking. A field study with 18 smokers revealed different forms of interaction: purely instrumental interactions with the objects, subtle engagement with other users through receptive and covert interactions, as well as explicit interaction with other users through disclosure and mutual support. The distraction objects offered a stepping-stone into interaction, whereas the tips encouraged interaction with the people behind the objects. This understanding of interaction through objects complements existing frameworks of online participation and adds to the current discourse on object-centred sociality. Furthermore, it provides an alternative approach to the design of online support groups, which offers the users enhanced control about the information they share with other users. We conclude by discussing how researchers and practitioners can apply the ideas of interaction around objects to other domains where individuals may have a simultaneous desire and reluctance to interact.

More than naming and shaming needed to stop corporate tax avoidance

The report of the Senate Economics References Committee inquiry into corporate tax avoidance comes with the subtitle – “You cannot tax what you cannot see”, with a strong focus on increased transparency. The majority of the 17 recommendations in the interim report relate to improved transparency of the tax affairs of corporate taxpayers. This is a significant step in the right direction. Recent experiences in the war on corporate tax avoidance both in Australia and overseas confirm that “information is power”. Most notably, we have seen increased transparency changing the behaviour of multinational enterprises as well as inducing governments to act.

A feedback-based algorithm forMotion analysis with application to object tracking

We present a motion detection algorithm which detects direction of motion at sufficient number of points and thus segregates the edge image into clusters of coherently moving points. Unlike most algorithms for motion analysis, we do not estimate magnitude of velocity vectors or obtain dense motion maps. The motivation is that motion direction information at a number of points seems to be sufficient to evoke perception of motion and hence should be useful in many image processing tasks requiring motion analysis. The algorithm essentially updates the motion at previous time using the current image frame as input in a dynamic fashion. One of the novel features of the algorithm is the use of some feedback mechanism for evidence segregation. This kind of motion analysis can identify regions in the image that are moving together coherently, and such information could be sufficient for many applications that utilize motion such as segmentation, compression, and tracking. We present an algorithm for tracking objects using our motion information to demonstrate the potential of this motion detection algorithm.

Stationary processes for object detection and non-rigid structure-from-motion

Stationary processes are random variables whose value is a signal and whose distribution is invariant to translation in the domain of the signal. They are intimately connected to convolution, and therefore to the Fourier transform, since the covariance matrix of a stationary process is a Toeplitz matrix, and Toeplitz matrices are the expression of convolution as a linear operator. This thesis utilises this connection in the study of i) efficient training algorithms for object detection and ii) trajectory-based non-rigid structure-from-motion.

Early and late electrophysiological effects of distractor frequency in picture naming: Reconciling input and output accounts

The “distractor-frequency effect” refers to the finding that high-frequency (HF) distractor words slow picture naming less than low-frequency distractors in the picture–word interference paradigm. Rival input and output accounts of this effect have been proposed. The former attributes the effect to attentional selection mechanisms operating during distractor recognition, whereas the latter attributes it to monitoring/decision mechanisms operating on distractor and target responses in an articulatory buffer. Using high-density (128-channel) EEG, we tested hypotheses from these rival accounts. In addition to conducting stimulus- and response-locked whole-brain corrected analyses, we investigated the correct-related negativity, an ERP observed on correct trials at fronto-central electrodes proposed to reflect the involvement of domain general monitoring. The wholebrain ERP analysis revealed a significant effect of distractor frequency at inferior right frontal and temporal sites between 100 and 300-msec post-stimulus onset, during which lexical access is thought to occur. Response-locked, region of interest (ROI) analyses of fronto-central electrodes revealed a correct-related negativity starting 121 msec before and peaking 125 msec after vocal onset on the grand averages. Slope analysis of this component revealed a significant difference between HF and lowfrequency distractor words, with the former associated with a steeper slope on the time windowspanning from100 msec before to 100 msec after vocal onset. The finding of ERP effects in time windows and components corresponding to both lexical processing and monitoring suggests the distractor frequency effect is most likely associated with more than one physiological mechanism.

Kernel-based spatial-color modeling for fast moving object tracking

Visual tracking has been a challenging problem in computer vision over the decades. The applications of Visual Tracking are far-reaching, ranging from surveillance and monitoring to smart rooms. Mean-shift (MS) tracker, which gained more attention recently, is known for tracking objects in a cluttered environment and its low computational complexity. The major problem encountered in histogram-based MS is its inability to track rapidly moving objects. In order to track fast moving objects, we propose a new robust mean-shift tracker that uses both spatial similarity measure and color histogram-based similarity measure. The inability of MS tracker to handle large displacements is circumvented by the spatial similarity-based tracking module, which lacks robustness to object's appearance change. The performance of the proposed tracker is better than the individual trackers for tracking fast-moving objects with better accuracy.

On the Benefits and Problems of the Object-Oriented Paradigm including a Finnish Study

Several researchers are of the opinion that there are many benefits in using the object-oriented paradigm in information systems development. If the object-oriented paradigm is used, the development of information systems may, for example, be faster and more efficient. On the other hand, there are also several problems with the paradigm. For example, it is often considered complex, it is often difficult to make use of the reuse concept and it is still immature in some areas. Although there are several interesting features in the object-oriented paradigm, there is still little comprehensive knowledge of the benefits and problems associated with it. The objective of the following study was to investigate and to gain more understanding of the benefits and problems of the object-oriented paradigm. A review of previous studies was made and twelve benefits and twelve problems were established. These benefits and problems were then analysed, studied and discussed. Further a survey and some case studies were made in order to get some knowledge on what benefits and problems with the object-oriented paradigm Finnish software companies had experienced. One hundred and four companies answered the survey that was sent to all Finnish software companies with five or more employees. The case studies were made with six large Finnish software companies. The major finding was that Finnish software companies were exceptionally positive towards the object-oriented information systems development and had experienced very few of the proposed problems. Finally two models for further research were developed. The first model presents connections between benefits and the second between problems.

Investigation on the Sources of Reflection at the Junction of Tall Grounded Object and Lightning Channel

During lightning strike to a tall grounded object (TGO), reflections of current waves are known to occur at either ends of the TGO. These reflection modify the channel current and hence, the lightning electromagnetic fields. This study aims to identify the possible contributing factors to reflection at a TGO-channel junction for the current waves ascending on the TGO. Possible sources of reflection identified are corona sheath and discontinuity of resistance and radius. For analyzing the contribution of corona sheath and discontinuity of resistance at the junction, a macroscopic physical model for the return stroke developed in our earlier work is employed. NEC-2D is used for assessing the contribution of abrupt change in radii at a TGO-channel junction. The wire-cage model adopted for the same is validated using laboratory experiments. Detailed investigation revealed the following. The main contributor for reflection at a TGO-channel junction is the difference between TGO and channel core radii. Also, the discontinuity of resistance at a TGO-channel junction can be of some relevance only for the first microsecond regime. Further, corona sheath does not play any significant role in the reflection.

Experiments on three-dimensional wire-frame object recognition

Some experimental results on the recognition of three-dimensional wire-frame objects are presented. In order to overcome the limitations of a recent model, which employs radial basis functions-based neural networks, we have proposed a hybrid learning system for object recognition, featuring: an optimization strategy (simulated annealing) in order to avoid local minima of an energy functional; and an appropriate choice of centers of the units. Further, in an attempt to achieve improved generalization ability, and to reduce the time for training, we invoke the principle of self-organization which utilises an unsupervised learning algorithm.

Object Tracking Using Motion Direction Detection

We present an algorithm for tracking objects in a video sequence, based on a novel approach for motion detection. We do not estimate the velocity �eld. In-stead we detect only the direction of motion at edge points and thus isolate sets of points which are moving coherently. We use a Hausdor� distance based matching algorithm to match point sets in local neighborhood and thus track objects in a video sequence. We show through some examples the e�ectiveness of the algo- rithm.

Covariance profiles: a signature representation for object sets

We consider the problem of extracting a signature representation of similar entities employing covariance descriptors. Covariance descriptors can efficiently represent objects and are robust to scale and pose changes. We posit that covariance descriptors corresponding to similar objects share a common geometrical structure which can be extracted through joint diagonalization. We term this diagonalizing matrix as the Covariance Profile (CP). CP can be used to measure the distance of a novel object to an object set through the diagonality measure. We demonstrate how CP can be employed on images as well as for videos, for applications such as face recognition and object-track clustering.

Analytical theory and stability analysis of an elongated nanoscale object under external torque

We consider the rotational motion of an elongated nanoscale object in a fluid under an external torque. The experimentally observed dynamics could be understood from analytical solutions of the Stokes equation, with explicit formulae derived for the dynamical states as a function of the object dimensions and the parameters defining the external torque. Under certain conditions, multiple analytical solutions to the Stokes equations exist, which have been investigated through numerical analysis of their stability against small perturbations and their sensitivity towards initial conditions. These experimental results and analytical formulae are general enough to be applicable to the rotational motion of any isolated elongated object at low Reynolds numbers, and could be useful in the design of non-spherical nanostructures for diverse applications pertaining to microfluidics and nanoscale propulsion technologies.

Fragment-based real-time object tracking: a sparse representation approach

Real-time object tracking is a critical task in many computer vision applications. Achieving rapid and robust tracking while handling changes in object pose and size, varying illumination and partial occlusion, is a challenging task given the limited amount of computational resources. In this paper we propose a real-time object tracker in l(1) framework addressing these issues. In the proposed approach, dictionaries containing templates of overlapping object fragments are created. The candidate fragments are sparsely represented in the dictionary fragment space by solving the l(1) regularized least squares problem. The non zero coefficients indicate the relative motion between the target and candidate fragments along with a fidelity measure. The final object motion is obtained by fusing the reliable motion information. The dictionary is updated based on the object likelihood map. The proposed tracking algorithm is tested on various challenging videos and found to outperform earlier approach.