Pedestrian Flow Simulation Validation and Verification Techniques

For the verification and validation of microscopic simulation models of pedestrian flow, we have performed experiments for different kind of facilities and sites where most conflicts and congestion happens e.g. corridors, narrow passages, and crosswalks. The validity of the model should compare the experimental conditions and simulation results with video recording carried out in the same condition like in real life e.g. pedestrian flux and density distributions. The strategy in this technique is to achieve a certain amount of accuracy required in the simulation model. This method is good at detecting the critical points in the pedestrians walking areas. For the calibration of suitable models we use the results obtained from analyzing the video recordings in Hajj 2009 and these results can be used to check the design sections of pedestrian facilities and exits. As practical examples, we present the simulation of pilgrim streams on the Jamarat bridge. The objectives of this study are twofold: first, to show through verification and validation that simulation tools can be used to reproduce realistic scenarios, and second, gather data for accurate predictions for designers and decision makers.Comment: 19 pages, 10 figure

Collaborative Surgical Robots:Optical Tracking During Endovascular Operations

Endovascular interventions usually require meticulous handling of surgical instruments and constant monitoring of the operating room workspace. To address these challenges, robotic- assisted technologies and tracking techniques are increasingly being developed. Specifically, the limited workspace and potential for a collision between the robot and surrounding dynamic obstacles are important aspects that need to be considered. This article presents a navigation system developed to assist clinicians with the magnetic actuation of endovascular catheters using multiple surgical robots. We demonstrate the actuation of a magnetic catheter in an experimental arterial testbed with dynamic obstacles. The motions and trajectory planning of two six degrees of freedom (6-DoF) robotic arms are established through passive markerguided motion planning. We achieve an overall 3D tracking accuracy of 2.3 ± 0.6 mm for experiments involving dynamic obstacles. We conclude that integrating multiple optical trackers with the online planning of two serial-link manipulators is useful to support the treatment of endovascular diseases and aid clinicians during interventions

Restoration of the cantilever bowing distortion in Atomic Force Microscopy

Due to the mechanics of the Atomic Force Microscope (AFM), there is a curvature distortion (bowing effect) present in the acquired images. At present, flattening such images requires human intervention to manually segment object data from the background, which is time consuming and highly inaccurate. In this paper, an automated algorithm to flatten lines from AFM images is presented. The proposed method classifies the data into objects and background, and fits convex lines in an iterative fashion. Results on real images from DNA wrapped carbon nanotubes (DNACNTs) and synthetic experiments are presented, demonstrating the effectiveness of the proposed algorithm in increasing the resolution of the surface topography. In addition a link between the flattening problem and MRI inhomogeneity (shading) is given and the proposed method is compared to an entropy based MRI inhomogeniety correction method

Vision-based haptic feedback for remote micromanipulation in-SEM environment.

International audienceThis paper presents an intuitive environment for remote micromanipulation composed of both haptic feedback and virtual reconstruction of the scene. To enable non expert users to perform complex teleoperated micromanipulation tasks it is of utmost importance to provide them with information about the 3D relative positions of the objects and the tools. Haptic feedback is an intuitive way to transmit such information. Since position sensors are not available at this scale, visual feedback is used to derive information about the scene. In this work, three different techniques are implemented, evaluated and compared to derive the object positions from scanning electron microscope images. The modified correlation matching with generated template algorithm is accurate and provides reliable detection of objects. To track the tool, a marker based approach is chosen since fast detection is required for stable haptic feedback. Information derived from these algorithms is used to propose an intuitive remote manipulation system, that enables users situated in geographically distant sites to benefit from specific equipments such as SEMs. Stability of the haptic feedback is ensured by the minimization of the delays, the computational efficiency of vision algorithms and the proper tuning of the haptic coupling. Virtual guides are proposed to avoid any involuntary collisions between the tool and the objects. This approach is validated by a teleoperation involving melamine microspheres with a diameter of less than 2 m between Paris, France and Oldenburg, Germany

SiMPLISTIC: A Novel Pairwise Potential for Implicit Solvent Lipid Simulations with Single-site Models

Implicit solvent, coarse-grained models with pairwise interactions can access the largest length and time scales in molecular dynamics simulations, owing to the absence of interactions with a huge number of solvent particles, the smaller number of interaction sites in the model molecules, and the lack of fast sub-molecular degrees of freedom. In this paper, we describe a maximally coarse-grained model for lipids in implicit water. The model is called SiMPLISTIC, which abbreviates for Single-site Model with Pairwise interaction for Lipids in Implicit Solvent with Tuneable Intrinsic Curvature. SiMPLISTIC lipids rapidly self-assemble into realistic non-lamellar and lamellar phases such as inverted micelles and bilayers, the spontaneous curvature of the phase being determined by a single free parameter of the model. Model membrane simulations with the lamellar lipids show satisfactory fluid and gel phases with no interdigitation or tilt. The model lipids follow rigid body dynamics suggested by empirical studies, and generate bilayer elastic properties consistent with experiments and other simulations. SiMPLISTIC can also simulate mixtures of lipids that differ in their packing parameter or length, the latter leading to the phenomenon of hydrophobic mismatch driven domain formation. The model has a large scope due to its speed, conceptual and computational simplicity, and versatility. Applications may range from large-scale simulations for academic and industrial research on various lipid-based systems, such as lyotropic liquid crystals, biological and biomimetic membranes, vectors for drug and gene delivery, to fast, lightweight, interactive simulations for gaining insights into self-assembly, lipid polymorphism, biomembrane organization etc.Comment: 17 pages, 11 figure

Model and Appearance Based Analysis of Neuronal Morphology from Different Microscopy Imaging Modalities

The neuronal morphology analysis is key for understanding how a brain works. This process requires the neuron imaging system with single-cell resolution; however, there is no feasible system for the human brain. Fortunately, the knowledge can be inferred from the model organism, Drosophila melanogaster, to the human system. This dissertation explores the morphology analysis of Drosophila larvae at single-cell resolution in static images and image sequences, as well as multiple microscopy imaging modalities. Our contributions are on both computational methods for morphology quantification and analysis of the influence of the anatomical aspect. We develop novel model-and-appearance-based methods for morphology quantification and illustrate their significance in three neuroscience studies. Modeling of the structure and dynamics of neuronal circuits creates understanding about how connectivity patterns are formed within a motor circuit and determining whether the connectivity map of neurons can be deduced by estimations of neuronal morphology. To address this problem, we study both boundary-based and centerline-based approaches for neuron reconstruction in static volumes. Neuronal mechanisms are related to the morphology dynamics; so the patterns of neuronal morphology changes are analyzed along with other aspects. In this case, the relationship between neuronal activity and morphology dynamics is explored to analyze locomotion procedures. Our tracking method models the morphology dynamics in the calcium image sequence designed for detecting neuronal activity. It follows the local-to-global design to handle calcium imaging issues and neuronal movement characteristics. Lastly, modeling the link between structural and functional development depicts the correlation between neuron growth and protein interactions. This requires the morphology analysis of different imaging modalities. It can be solved using the part-wise volume segmentation with artificial templates, the standardized representation of neurons. Our method follows the global-to-local approach to solve both part-wise segmentation and registration across modalities. Our methods address common issues in automated morphology analysis from extracting morphological features to tracking neurons, as well as mapping neurons across imaging modalities. The quantitative analysis delivered by our techniques enables a number of new applications and visualizations for advancing the investigation of phenomena in the nervous system

Creating landscapes with simulated colliding plates

The creation of realistic virtual terrain has been a longstanding computer graphics problem, as terrain will form the backdrop of any virtual world. Approaches to this problem to date have taken one of two approaches: either fractally generating landscapes, or simulating the processes of water and thermal erosion. I have developed a new method to synthesize virtual landscapes, by simulating some of the geological forces that create real-world landscapes I model the collision and deformation of simulated tectonic plates, and create features that mimic those found along real-world plate boundaries. This is achieved through the use of a meshless object representation subjected to physically-based forces, using existing techniques for accurately modeling stress and strain in solid objects