Understanding Iconography: a method to allow rich picture interpretation to improve.

Information Systems for complex situations often fail to adequately deliver quality and suitability. One reason for this failure is an inability to identify comprehensive user requirements. Seldom do all stakeholders, especially those "invisible‟ or "back room‟ system users, have a voice when systems are designed. If this is a global problem then it may impact on both the public and private sectors in terms of their ability to perform, produce and stay competitive. To improve upon this, system designers use rich pictures as a diagrammatic means of identifying differing world views with the aim of creating shared understanding of the organisation. Rich pictures have predominantly been used as freeform, unstructured tools with no commonly agreed syntax. This research has collated, analysed and documented a substantial collection of rich pictures into a single dataset. Attention has been focussed on three main research areas; how the rich picture is facilitated, how the rich picture is constructed and how to interpret the resultant pictures. This research highlights the importance of the rich picture tool and argues the value of adding levels of structure, in certain cases. It is shown that there are considerable benefits for both the interpreter and the creator by providing a pre-drawing session, a common key of symbols and a framework for icon understanding. In conclusion, it is suggested that there is some evidence that a framework which aims to support the process of the rich picture and aid interpretation is valuable.

'Cloak Without Dagger': How the Information Research Department Fought Britain's Cold War in the Middle East, 1948-1956

Vaughn, James, ''Cloak Without Dagger': How the Information Research Department Fought Britain's Cold War in the Middle East, 1948-1956', Cold War History (2004) 4(3) pp.56-84 RAE2008

I Cannot Tell: Edward Thomas's Uncertainties

Poster, Jeremy, 'I Cannot Tell: Edward Thomas's Uncertainties', In: 'Branch-Lines: Edward Thomas and Contemporary Poetry', Guy Cuthbertson & Lucy Newlyn (eds), (London: Enitharmon Press), pp.264, 2007 RAE2008

Steady-state motion of a Mode-III crack on imperfect interfaces

Mishuris, Gennady; Movchan, N.V.; Movchan, A.B., (2006) 'Steady-state motion of a Mode-III crack on imperfect interfaces', Quarterly Journal of Mechanics and Applied Mathematics 59(4) pp.487-516 RAE2008

(O)znaki śmierci w polskiej poezji po roku 1956

Wydział Filologii Polskiej i Klasycznej: Instytut Filologii Polskiej

Analiza struktury przestrzennej i czasoprzestrzennej maksymalnych opadów dobowych w Polsce w latach 1956-1980

Jednym z wyników prognoz wykonywanych z zastosowaniem globalnych i regionalnych modeli klimatycznych jest odkrycie wysokiego prawdopodobieństwa wzrostu częstości oraz natężenia ekstremalnych opadów. Poznanie prawidłowości ich powtarzalności i zasięgu przestrzennego ma oczywiście bardzo duże znaczenie gospodarcze i społeczne. Dlatego, niezależnie od wprowadzania nowych technik pomiarowych należy dokonywać analizy i reinterpretacji archiwalnych danych, korzystając z możliwości stwarzanych przez rozwój GIS. Głównym celem opracowania jest analiza prawidłowości przestrzennej i czasowej zmienności miesięcznych oraz rocznych maksymalnych dobowych sum opadów (MSDO) z lat 1956-1980, z obszaru Polski. W pracy wykorzystano nowe w geografii polskiej metody geostatystyczne. Do publikacji dołączono dysk DVD ze źródłową bazą danych i najważniejszymi wynikami w postaci numerycznej i kartograficznej.

First ten annual reports of the American Board of Commissioners for Foreign Missions : with other documents of the Board.

http://www.archive.org/details/firsttenannualre00amerrich

Dynamical Instabilities and Deterministic Chaos in Ballistic Electron Motion in Semiconductor Superlattices

We consider the motion of ballistic electrons within a superlattice miniband under the influence of an alternating electric field. We show that the interaction of electrons with the self-consistent electromagnetic field generated by the electron current may lead to the transition from regular to chaotic dynamics. We estimate the conditions for the experimental observation of this deterministic chaos and discuss the similarities of the superlattice system with the other condensed matter and quantum optical systems.

Camera Canvas: Image Editing Software for People with Disabilities

Poster is based on the following paper: C. Kwan and M. Betke. Camera Canvas: Image editing software for people with disabilities. In Proceedings of the 14th International Conference on Human Computer Interaction (HCI International 2011), Orlando, Florida, July 2011.

Physically-Based Combinations of Views: Representing Rigid and Nonrigid Motion

Nonrigid motion can be described as morphing or blending between extremal shapes, e.g., heart motion can be described as transitioning between the systole and diastole states. Using physically-based modeling techniques, shape similarity can be measured in terms of forces and strain. This provides a physically-based coordinate system in which motion is characterized in terms of physical similarity to a set of extremal shapes. Having such a low-dimensional characterization of nonrigid motion allows for the recognition and the comparison of different types of nonrigid motion.

EVALUATION OF HARMONIC MOTION ELASTOGRAPHY AND ACOUSTO-­OPTIC IMAGING FOR MONITORING LESION FORMATION BY HIGH INTENSITY FOCUSED ULTRASOUND

Malignant or benign tumors may be ablated with high‐intensity focused ultrasound (HIFU). This technique, known as focused ultrasound surgery (FUS), has been actively investigated for decades, but slow to be implemented and difficult to control due to lack of real‐time feedback during ablation. Two methods of imaging and monitoring HIFU lesions during formation were implemented simultaneously, in order to investigate the efficacy of each and to increase confidence in the detection of the lesion. The first, Acousto‐Optic Imaging (AOI) detects the increasing optical absorption and scattering in the lesion. The intensity of a diffuse optical field in illuminated tissue is mapped at the spatial resolution of an ultrasound focal spot, using the acousto‐optic effect. The second, Harmonic Motion Imaging (HMI), detects the changing stiffness in the lesion. The HIFU beam is modulated to force oscillatory motion in the tissue, and the amplitude of this motion, measured by ultrasound pulse‐echo techniques, is influenced by the stiffness. Experiments were performed on store‐bought chicken breast and freshly slaughtered bovine liver. The AOI results correlated with the onset and relative size of forming lesions much better than prior knowledge of the HIFU power and duration. For HMI, a significant artifact was discovered due to acoustic nonlinearity. The artifact was mitigated by adjusting the phase of the HIFU and imaging pulses. A more detailed model of the HMI process than previously published was made using finite element analysis. The model showed that the amplitude of harmonic motion was primarily affected by increases in acoustic attenuation and stiffness as the lesion formed and the interaction of these effects was complex and often counteracted each other. Further biological variability in tissue properties meant that changes in motion were masked by sample‐to‐sample variation. The HMI experiments predicted lesion formation in only about a quarter of the lesions made. In simultaneous AOI/HMI experiments it appeared that AOI was a more robust method for lesion detection.

Discovering Clusters in Motion Time-Series Data

A new approach is proposed for clustering time-series data. The approach can be used to discover groupings of similar object motions that were observed in a video collection. A finite mixture of hidden Markov models (HMMs) is fitted to the motion data using the expectation-maximization (EM) framework. Previous approaches for HMM-based clustering employ a k-means formulation, where each sequence is assigned to only a single HMM. In contrast, the formulation presented in this paper allows each sequence to belong to more than a single HMM with some probability, and the hard decision about the sequence class membership can be deferred until a later time when such a decision is required. Experiments with simulated data demonstrate the benefit of using this EM-based approach when there is more "overlap" in the processes generating the data. Experiments with real data show the promising potential of HMM-based motion clustering in a number of applications.

Robust Tracking of Human Motion

This technical report presents a combined solution for two problems, one: tracking objects in 3D space and estimating their trajectories and second: computing the similarity between previously estimated trajectories and clustering them using the similarities that we just computed. For the first part, trajectories are estimated using an EKF formulation that will provide the 3D trajectory up to a constant. To improve accuracy, when occlusions appear, multiple hypotheses are followed. For the second problem we compute the distances between trajectories using a similarity based on LCSS formulation. Similarities are computed between projections of trajectories on coordinate axes. Finally we group trajectories together based on previously computed distances, using a clustering algorithm. To check the validity of our approach, several experiments using real data were performed.

Extraction and Clustering of Motion Trajectories in Video

A system is described that tracks moving objects in a video dataset so as to extract a representation of the objects' 3D trajectories. The system then finds hierarchical clusters of similar trajectories in the video dataset. Objects' motion trajectories are extracted via an EKF formulation that provides each object's 3D trajectory up to a constant factor. To increase accuracy when occlusions occur, multiple tracking hypotheses are followed. For trajectory-based clustering and retrieval, a modified version of edit distance, called longest common subsequence (LCSS) is employed. Similarities are computed between projections of trajectories on coordinate axes. Trajectories are grouped based, using an agglomerative clustering algorithm. To check the validity of the approach, experiments using real data were performed.

Periodic Motion Detection and Estimation via Space-Time Sampling

A novel technique to detect and localize periodic movements in video is presented. The distinctive feature of the technique is that it requires neither feature tracking nor object segmentation. Intensity patterns along linear sample paths in space-time are used in estimation of period of object motion in a given sequence of frames. Sample paths are obtained by connecting (in space-time) sample points from regions of high motion magnitude in the first and last frames. Oscillations in intensity values are induced at time instants when an object intersects the sample path. The locations of peaks in intensity are determined by parameters of both cyclic object motion and orientation of the sample path with respect to object motion. The information about peaks is used in a least squares framework to obtain an initial estimate of these parameters. The estimate is further refined using the full intensity profile. The best estimate for the period of cyclic object motion is obtained by looking for consensus among estimates from many sample paths. The proposed technique is evaluated with synthetic videos where ground-truth is known, and with American Sign Language videos where the goal is to detect periodic hand motions.