An improved 2D optical flow sensor for motion segmentation

A functional focal-plane implementation of a 2D optical flow system is presented that detects an preserves motion discontinuities. The system is composed of two different network layers of analog computational units arranged in a retinotopical order. The units in the first layer (the optical flow network) estimate the local optical flow field in two visual dimensions, where the strength of their nearest-neighbor connections determines the amount of motion integration. Whereas in an earlier implementation \cite{Stocker_Douglas99} the connection strength was set constant in the complete image space, it is now \emph{dynamically and locally} controlled by the second network layer (the motion discontinuities network) that is recurrently connected to the optical flow network. The connection strengths in the optical flow network are modulated such that visual motion integration is ideally only facilitated within image areas that are likely to represent common motion sources. Results of an experimental aVLSI chip illustrate the potential of the approach and its functionality under real-world conditions

Integrated 2-D Optical Flow Sensor

I present a new focal-plane analog VLSI sensor that estimates optical flow in two visual dimensions. The chip significantly improves previous approaches both with respect to the applied model of optical flow estimation as well as the actual hardware implementation. Its distributed computational architecture consists of an array of locally connected motion units that collectively solve for the unique optimal optical flow estimate. The novel gradient-based motion model assumes visual motion to be translational, smooth and biased. The model guarantees that the estimation problem is computationally well-posed regardless of the visual input. Model parameters can be globally adjusted, leading to a rich output behavior. Varying the smoothness strength, for example, can provide a continuous spectrum of motion estimates, ranging from normal to global optical flow. Unlike approaches that rely on the explicit matching of brightness edges in space or time, the applied gradient-based model assures spatiotemporal continuity on visual information. The non-linear coupling of the individual motion units improves the resulting optical flow estimate because it reduces spatial smoothing across large velocity differences. Extended measurements of a 30x30 array prototype sensor under real-world conditions demonstrate the validity of the model and the robustness and functionality of the implementation

Compact Integrated Transconductance Amplifier Circuit for Temporal Differentiation

A compact integrated CMOS circuit for temporal differentiation is presented. It consists of a high-gain inverting amplifier, an active non-linear transconductance and a capacitor and requires only 4 transistors in its minimal configuration.The circuit provides two rectified current outputs that are proportional to the temporal derivative of the input voltage signal. Besides the compactness of its design, the presented circuit is not dependent on the DC-value of the input signal, as compared with known integrated differentiator circuits. Measured chip results show that the circuit operates on a large input frequency range for which it provides nearideal temporal differentiation. The circuit is particularly suited for focal-plane implementations of gradient-based visual motion systems

Computation of Smooth Optical Flow in a Feedback Connected Analog Network

In 1986, Tanner and Mead \cite{Tanner_Mead86} implemented an interesting constraint satisfaction circuit for global motion sensing in aVLSI. We report here a new and improved aVLSI implementation that provides smooth optical flow as well as global motion in a two dimensional visual field. The computation of optical flow is an ill-posed problem, which expresses itself as the aperture problem. However, the optical flow can be estimated by the use of regularization methods, in which additional constraints are introduced in terms of a global energy functional that must be minimized. We show how the algorithmic constraints of Horn and Schunck \cite{Horn_Schunck81} on computing smooth optical flow can be mapped onto the physical constraints of an equivalent electronic network

Multifragmentation, Clustering, and Coalescence in Nuclear Collisions

Nuclear collisions at intermediate, relativistic, and ultra-relativistic energies offer unique opportunities to study in detail manifold fragmentation and clustering phenomena in dense nuclear matter. At intermediate energies, the well known processes of nuclear multifragmentation -- the disintegration of bulk nuclear matter in clusters of a wide range of sizes and masses -- allow the study of the critical point of the equation of state of nuclear matter. At very high energies, ultra-relativistic heavy-ion collisions offer a glimpse at the substructure of hadronic matter by crossing the phase boundary to the quark-gluon plasma. The hadronization of the quark-gluon plasma created in the fireball of a ultra-relativistic heavy-ion collision can be considered, again, as a clustering process. We will present two models which allow the simulation of nuclear multifragmentation and the hadronization via the formation of clusters in an interacting gas of quarks, and will discuss the importance of clustering to our understanding of hadronization in ultra-relativistic heavy-ion collisions.Comment: 10 pages, 8 figure

Inter-professional in-situ simulated team and resuscitation training for patient safety: Description and impact of a programmatic approach

© 2015 Zimmermann et al.Background: Inter-professional teamwork is key for patient safety and team training is an effective strategy to improve patient outcome. In-situ simulation is a relatively new strategy with emerging efficacy, but best practices for the design, delivery and implementation have yet to be evaluated. Our aim is to describe and evaluate the implementation of an inter-professional in-situ simulated team and resuscitation training in a teaching hospital with a programmatic approach. Methods: We designed and implemented a team and resuscitation training program according to Kerns six steps approach for curriculum development. General and specific needs assessments were conducted as independent cross-sectional surveys. Teamwork, technical skills and detection of latent safety threats were defined as specific objectives. Inter-professional in-situ simulation was used as educational strategy. The training was embedded within the workdays of participants and implemented in our highest acuity wards (emergency department, intensive care unit, intermediate care unit). Self-perceived impact and self-efficacy were sampled with an anonymous evaluation questionnaire after every simulated training session. Assessment of team performance was done with the team-based self-assessment tool TeamMonitor applying Van der Vleutens conceptual framework of longitudinal evaluation after experienced real events. Latent safety threats were reported during training sessions and after experienced real events. Results: The general and specific needs assessments clearly identified the problems, revealed specific training needs and assisted with stakeholder engagement. Ninety-five interdisciplinary staff members of the Childrens Hospital participated in 20 in-situ simulated training sessions within 2 years. Participant feedback showed a high effect and acceptance of training with reference to self-perceived impact and self-efficacy. Thirty-five team members experiencing 8 real critical events assessed team performance with TeamMonitor. Team performance assessment with TeamMonitor was feasible and identified specific areas to target future team training sessions. Training sessions as well as experienced real events revealed important latent safety threats that directed system changes. Conclusions: The programmatic approach of Kerns six steps for curriculum development helped to overcome barriers of design, implementation and assessment of an in-situ team and resuscitation training program. This approach may help improve effectiveness and impact of an in-situ simulated training program

Reversible Peg Solitaire on Graphs

The game of peg solitaire on graphs was introduced by Beeler and Hoilman in 2011. In this game, pegs are initially placed on all but one vertex of a graph G. If xyz forms a path in G and there are pegs on vertices x and y but not z, then a jump places a peg on z and removes the pegs from x and y. A graph is called solvable if, for some configuration of pegs occupying all but one vertex, some sequence of jumps leaves a single peg. We study the game of reversible peg solitaire, where there are again initially pegs on all but one vertex, but now both jumps and unjumps (the reversal of a jump) are allowed. We show that in this game all non-star graphs that contain a vertex of degree at least three are solvable, that cycles and paths on n vertices, where n is divisible by 2 or 3, are solvable, and that all other graphs are not solvable. We also classify the possible starting hole and ending peg positions for solvable graphs

Combinatorial Proofs of Identities of Alzer and Prodinger and Some Generalizations

We provide combinatorial proofs of identities published by Alzer and Prodinger. These identities include that for integers b, n, and r with b ≥ 1 and n − 1 ≥ r ≥ 0 we have and for integers b, n, and r with b ≥ 0 and n − 1 ≥ r ≥ 0 we have Our combinatorial proofs generalize squares to sth powers, and involve generalized Eulerian numbers and generalized Delannoy numbers