A deformation transformer for real-time cloth animation

Achieving interactive performance in cloth animation has significant implications in computer games and other interactive graphics applications. Although much progress has been made, it is still much desired to have real-time high-quality results that well preserve dynamic folds and wrinkles. In this paper, we introduce a hybrid method for real-time cloth animation. It relies on datadriven models to capture the relationship between cloth deformations at two resolutions. Such data-driven models are responsible for transforming low-quality simulated deformations at the low resolution into high-resolution cloth deformations with dynamically introduced fine details. Our data-driven transformation is trained using rotation invariant quantities extracted from the cloth models, and is independent of the simulation technique chosen for the lower resolution model. We have also developed a fast collision detection and handling scheme based on dynamically transformed bounding volumes. All the components in our algorithm can be efficiently implemented on programmable graphics hardware to achieve an overall real-time performance on high-resolution cloth models. © 2010 ACM.postprin

The mechanical and material properties of elderly human articular cartilage subject to impact and slow loading

Copyright © 2013 IPEM. Published by Elsevier Ltd. All rights reserved.Peer reviewedPostprin

Simple and fast damage identification on 6061 aluminium based on mode shape curvature

This paper presents a simple and fast approach for the identification of damage to isotropic steel structures. The main contribution of this work is a simplified approach using cubic polynomial regression, unlike previously developed damage identification models that use two specimens. This was achieved by differentiating the mode shape displacement from the mode shape curvature using a central finite difference equation to determine the damaged curve, and subsequently, computing the undamaged curve using a Cubic Polynomial Regression (CPR) model. To validate the accuracy of the model, five specimens with different types of damage (single and double notch) at various depths were simulated. The performance of the model was evaluated against the experimental modal test results. It was found that the presented model was capable of detecting the type of damage (whether single or double notch) in a 6061 Aluminium beam structure. However, when compared to the experimental results, the average difference could reach up to 17% due to external factors. In particular, the performance of the presented model in detecting the location of the damage was inaccurate and imprecise for both the FEA simulation and experimental cases. The CPR model is useful for operators and engineers who require a simple and fast approach to detect damage, but, in terms of accuracy, different techniques must be considered, especially those that are capable of removing and clearing out noise signals

Optimization of the drying process of edible film-based cassava starch using response surface methodology

Most food packaging consists of plastic which is difficult to degrade. One strategy for addressing this issue is the development of biodegradable polymers from cassava starch, a known of raw material easily produced at low cost and biologically to degrade, hence becoming a low-cost for edible film production. The edible film was prepared by gelatinization method using cassava starch and glycerol as plasticizers. The study was subjected to determine the optimum drying process for cassava starch-based edible film based on the drying condition process with two independent variables: drying temperature (40, 50, and 60°C) and drying time (4, 5, and 6 h) on the mechanical properties. The response surface methodology approach with a central composite design was used for optimization. The experimental data for the optimum drying condition were analyzed to obtain the optimized variables using plots and contours. The optimized edible film occurred at a drying temperature of 63.28 °C and drying time of 3.58 h resulting in a tensile strength of 6640.24 Pa, elongation at break of 1.051%, and water solubility of 55.575%. The study concluded that the optimized drying condition process significantly affected the tensile strength, elongation at break, and water solubility

Stereoscopic viewing, roughness and gloss perception

This thesis presents a novel investigation into the effect stereoscopic vision has upon the strength of perceived gloss on rough surfaces. We demonstrate that in certain cases disparity is necessary for accurate judgements of gloss strength. We first detail the process we used to create a two-level taxonomy of property terms, which helped to inform the early direction of this work, before presenting the eleven words which we found categorised the property space. This shaped careful examination of the relevant literature, leading us to conclude that most studies into roughness, gloss, and stereoscopic vision have been performed with unrealistic surfaces and physically inaccurate lighting models. To improve on the stimuli used in these earlier studies, advanced offline rendering techniques were employed to create images of complex, naturalistic, and realistically glossy 1/fβ noise surfaces. These images were rendered using multi-bounce path tracing to account for interreflections and soft shadows, with a reflectance model which observed all common light phenomena. Using these images in a series of psychophysical experiments, we first show that random phase spectra can alter the strength of perceived gloss. These results are presented alongside pairs of the surfaces tested which have similar levels of perceptual gloss. These surface pairs are then used to conclude that naïve observers consistently underestimate how glossy a surface is without the correct surface and highlight disparity, but only on the rougher surfaces presented

Processing remotely sensed data for geological content over a part of the Barberton Greenstone Belt, Republic of South Africa.

Various methods and techniques developed by researchers worldwide for enhancement and processing ATM, MSS· and TM remotely sensed data are tested. on LANDSAT 5 Thematic Mapper data from a part of the Barberton Greenstone Belt straddling the border between the Republic of South Africa and the Kingdom of Swaziland. Various enhancement techniques employed to facilitate the extraction of structural features and lineaments, and the findings Of the ensuing photogeologlcal interpretation are compared with existing geological maps~ Methods for the detection of zones of hydrothermal alteration. are also considered. The reflectance from vegetation, both natural and cultivated, and the possible reduction of the interference caused by this reflectance, are considered in detail. Partial unmixing of reflectances through the use of various methods and techniques, some of which are readily available from the literature, are performed and its effectiveness tested. Since large areas within the study area are covered by plantations, the interfereiice from the two types of vegetation present (i.e. natural and cultivated), were initially considered separately. In an attempt to isolate the forested areas from the natural vegetation, masks derived through image classification were used to differentially enhance the various features. Results indicate that the use of any particular method to the exclusion of all others will seriously limit the scope of conclusions possible through interpretation of the information present. Enhancement of information in one domain will inadvertently lead to the suppression of information from one or more of the coexisting domains. A series of results from a sequence of procedures interpreted in parallel will in every case produce information of a higher decision making quality.AC201

Wearable Technology For Healthcare And Athletic Performance

Wearable technology research has led to advancements in healthcare and athletic performance. Devices range from one size fits all fitness trackers to custom fitted devices with tailored algorithms. Because these devices are comfortable, discrete, and pervasive in everyday life, custom solutions can be created to fit an individual\u27s specific needs. In this dissertation, we design wearable sensors, develop features and algorithms, and create intelligent feedback systems that promote the advancement of healthcare and athletic performance. First, we present Magneto: a body mounted electromagnet-based sensing system for joint motion analysis. Joint motion analysis facilitates research into injury prevention, rehabilitation, and activity monitoring. Sensors used in such analysis must be unobtrusive, accurate, and capable of monitoring fast-paced dynamic motions. Our system is wireless, has a high sampling rate, and is unaffected by outside magnetic noise. Magnetic noise commonly influences magnetic field readings via magnetic interference from the Earth\u27s magnetic field, the environment, and nearby ferrous objects. Magneto uses the combination of an electromagnet and magnetometer to remove environmental interference from a magnetic field reading. We evaluated this sensing method to show its performance when removing the interference in three movement dimensions, in six environments, and with six different sampling rates. Then, we localized the electromagnet with respect to the magnetic field reader, allowing us to apply Magneto in two pilot studies: measuring elbow angles and calculating shoulder positions. We calculated elbow angles to the nearest 15â—¦ with 93.8% accuracy, shoulder position in two-degrees of freedom with 96.9% accuracy, and shoulder positions in three-degrees of freedom with 75.8% accuracy. Second, we present TracKnee: a sensing knee sleeve designed and fabricated to unobtrusively measure knee angles using conductive fabric sensors. We propose three models that can be used in succession to calculate knee angles from voltage. These models take an input of voltage, calculate the resistance of our conductive fabric sensor, then calculate the change in length across the front of the knee and finally to the angle of the knee. We evaluated our models and our device by conducting a user study with six participants where we collected 240 ground truth angles and sensor data from our TracKnee device. Our results show that our model is 94.86% accurate to the nearest 15th degree angle and that our average error per angle is error per angle is 3.69 degrees. Third, we present ServesUp: a sensing shirt designed to monitor shoulder and elbow motion during the volleyball serve. In this project, we will designed and fabricated a sensing shirt that is comfortable, unobtrusive, and washable that an athlete can wear during and without impeding volleyball play. To make the shirt comfortable, we used soft and flexible conductive fabric sensors to monitor the motion of the shoulder and the elbow. We conducted a user study with ten volleyball players for a total of 1000 volleyball serves. We classified serving motion using a KNN with a classification accuracy of 89.2%. We will use this data provide actionable insights back to the player to help improve their serving skill. Fourth, we present BreathEZ, the first smartwatch application that provides both choking first aid instruction and real-time tactile and visual feedback on the quality of the abdominal thrust compressions. We evaluated our application through two user studies involving 20 subjects and 200 abdominal thrust events. The results of our study show that BreathEZ achieves a classification accuracy of 90.9% for abdominal thrusts. All participants that used BreathEZ in our study were able to improve their performance of abdominal thrusts. Of these participants, 60% were able to perform within the recommended range with the use of BreathEZ. Comparatively no participants trained with a video only reached that range. Finally, we present BBAid: the first smartwatch based system that provides real-time feedback on the back blow portion of choking first aid while instructing the user on first aid procedure. We evaluated our application through two user studies involving 26 subjects and 260 back blow events. The results of our study show that BBAid achieves a classification accuracy of 93.75% for back blows. With the use of BBAid, participants in our study were able to perform back blows within the recommended range 75% of the time. Comparatively the participants trained with a video only reached that range 12% of the time. All participants in the study, after receiving training were much more willing to perform choking first aid

Interface électronique et logicielle pour la surveillance de la respiration en temps réel en utilisant des vêtements intelligents sans fils

Dans ce mémoire, on présente une nouvelle architecture d’un chandail intelligent pour surveiller la respiration en temps réel. Ce vêtement intelligent comporte une architecture qui offre une méthode de détection innovante assurant une suivie de l’activité respiratoire en continue. Tout d’abord le chandail détecte la déformation du haut du thorax pendant la respiration à l’aide d’une antenne intégrée dans le chandail. L’antenne a été conçue dans les laboratoires du centre d’optique, photonique et laser de l’université Laval. Un capteur Bluetooth intégré dans le même chandail détecte par la suite la variation du signal RSSI (indicateur d’intensité du signal reçu) et l’envoie à une unité de traitement et d’analyse de données sans fils (un ordinateur ou une tablette). Une interface d’analyse des données a été crée pour permettre la détermination du rythme respiratoire et le caractériser selon le signal de respiration reçu. En plus, le chandail intelligent est alimenté par une source d’énergie sans fils et hybride fonctionnant avec une batterie rechargeable ou par un lien inductif. Deux versions de chandail ont été testées. La première contient un seul capteur alors que la deuxième possède six capteurs positionnés sur la partie frontal du vêtement. En plus, différents paramètres ont été pris en considération durant les tests citant entre autres la morphologie, l’âge et le sexe des utilisateurs. Des tests ont démontré une détection réussie de plusieurs informations pertinentes comme les cycles de respiration (inspiration, expiration), la fréquence respiratoire et d’autres mesures statistiques pour les diagnostics.In this thesis, we present a new architecture of a smart T-shirt to monitor breathing in real time. This smart garment has an architecture that offers an innovative detection method ensuring continuous monitoring of respiratory activity. First the T-shirt detects deformation of the upper chest during breathing using an antenna built into the T-shirt. The antenna was designed in the laboratories of the optics, photonics and laser center of Laval University. A Bluetooth sensor integrated in the same T-shirt subsequently detects the variation of the RSSI signal (indicator of received signal strength) and sends it to a wireless data processing and analysis unit (a computer or tablet). A data analysis interface has been created to allow determination of the respiratory rate and characterization according to the received breathing signal. In addition, the smart T-shirt is powered by a wireless, hybrid power source powered by a rechargeable battery or by an inductive link. Two versions of the T-shirt were tested. The first contains a single sensor while the second has six sensors positioned on the front of the garment. In addition, different parameters were taken into account during the tests, citing among others the morphology, age and sex of the users. Tests have demonstrated successful detection of several relevant information such as breathing cycles (inspiration, expiration),respiratory rate and other statistical measures for diagnosis

Continuum Mechanical Models for Design and Characterization of Soft Robots

The emergence of ``soft'' robots, whose bodies are made from stretchable materials, has fundamentally changed the way we design and construct robotic systems. Demonstrations and research show that soft robotic systems can be useful in rehabilitation, medical devices, agriculture, manufacturing and home assistance. Increasing need for collaborative, safe robotic devices have combined with technological advances to create a compelling development landscape for soft robots. However, soft robots are not yet present in medical and rehabilitative devices, agriculture, our homes, and many other human-collaborative and human-interactive applications. This gap between promise and practical implementation exists because foundational theories and techniques that exist in rigid robotics have not yet been developed for soft robots. Theories in traditional robotics rely on rigid body displacements via discrete joints and discrete actuators, while in soft robots, kinematic and actuation functions are blended, leading to nonlinear, continuous deformations rather than rigid body motion. This dissertation addresses the need for foundational techniques using continuum mechanics. Three core questions regarding the use of continuum mechanical models in soft robotics are explored: (1) whether or not continuum mechanical models can describe existing soft actuators, (2) which physical phenomena need to be incorporated into continuum mechanical models for their use in a soft robotics context, and (3) how understanding on continuum mechanical phenomena may form bases for novel soft robot architectures. Theoretical modeling, experimentation, and design prototyping tools are used to explore Fiber-Reinforced Elastomeric Enclosures (FREEs), an often-used soft actuator, and to develop novel soft robot architectures based on auxetic behavior. This dissertation develops a continuum mechanical model for end loading on FREEs. This model connects a FREE’s actuation pressure and kinematic configuration to its end loads by considering stiffness of its elastomer and fiber reinforcement. The model is validated against a large experimental data set and compared to other FREE models used by roboticists. It is shown that the model can describe the FREE’s loading in a generalizable manner, but that it is bounded in its peak performance. Such a model can provide the novel function of evaluating the performance of FREE designs under high loading without the costs of building and testing prototypes. This dissertation further explores the influence viscoelasticity, an inherent property of soft polymers, on end loading of FREEs. The viscoelastic model developed can inform soft roboticists wishing to exploit or avoid hysteresis and force reversal. The final section of the dissertations explores two contrasting styles of auxetic metamaterials for their uses in soft robotic actuation. The first metamaterial architecture is composed of beams with distributed compliance, which are placed antagonistic configurations on a variety of surfaces, giving ride to shape morphing behavior. The second metamaterial architecture studied is a ``kirigami’’ sheet with an orthogonal cut pattern, utilizing lumped compliance and strain hardening to permanently deploy from a compact shape to a functional one. This dissertation lays the foundation for design of soft robots by robust physical models, reducing the need for physical prototypes and trial-and-error approaches. The work presented provides tools for systematic exploration of FREEs under loading in a wide range of configurations. The work further develops new concepts for soft actuators based on continuum mechanical modeling of auxetic metamaterials. The work presented expands the available tools for design and development of soft robotic systems, and the available architectures for soft robot actuation.PHDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/163236/1/asedal_1.pd