Modeling of Complex Parts for Industrial WaterJet Cleaning

Industrial high-pressure waterjet cleaning is common to many industries. The modeling in this paper functions inside a collaborative robotic framework for high mix, low volume processes where human robot collaboration is beneficial. Automation of pressure washing is desirable for economic and ergonomic reasons. An automated cleaning system needs path simulation and analysis to give the operator insight into the predicted cleaning performance of the system. In this paper, ablation, the removal of a substrate coating by waterjet, is modeled for robotic cleaning operations. The model is designed to work with complex parts often found in spray cleaning operations, namely parts containing hidden portions, holes, or concavities. Experimentation is used to validate and calibrate the ablation model to yield accurate evaluations for how well every feature of a part is cleaned based on the cumulative effect of water affecting the part surface. The ablation model will provide the foundation for optimizing process parameters for robotic waterjet cleaning

Distributed OpenGL Rendering in Network Bandwidth Constrained Environments

Display walls made from multiple monitors are often used when very high resolution images are required. To utilise a display wall, rendering information must be sent to each computer that the monitors are connect to. The network is often the performance bottleneck for demanding applications, like high performance 3D animations. This paper introduces ClusterGL; a distribution library for OpenGL applications. ClusterGL reduces network traffic by using compression, frame differencing and multi-cast. Existing applications can use ClusterGL without recompilation. Benchmarks show that, for most applications, ClusterGL outperforms other systems that support unmodified OpenGL applications including Chromium and BroadcastGL. The difference is larger for more complex scene geometries and when there are more display machines. For example, when rendering OpenArena, ClusterGL outperforms Chromium by over 300% on the Symphony display wall at The University of Waikato, New Zealand. This display has 20 monitors supported by five computers connected by gigabit Ethernet, with a full resolution of over 35 megapixels. ClusterGL is freely available via Google Code

Evaluation of Ankom F58 Filter Bags Compared to Dacron Bags and Beakers for Analysis of Acid Detergent Fiber

Feed and fecal samples were analyzed to compare three methods of determining acid detergent fiber. Each sample was weighed into both Dacron and Ankom F58 fiber bags and then analyzed using an Ankom fiber analyzer. Results were then compared to the Van Soest beaker method. Ankom F58 bags helped reduce washout of small particles associated with Dacron bags, but fecal samples needed to be incubated in detergent for an extended amount of time to isolate acid detergent fiber material. Utilizing a technique that produces correct acid detergent fiber values is important for producers because these values are used as a proxy for calculating total digestible nutrients of feedstuffs

A deep learning framework for quality assessment and restoration in video endoscopy

Endoscopy is a routine imaging technique used for both diagnosis and minimally invasive surgical treatment. Artifacts such as motion blur, bubbles, specular reflections, floating objects and pixel saturation impede the visual interpretation and the automated analysis of endoscopy videos. Given the widespread use of endoscopy in different clinical applications, we contend that the robust and reliable identification of such artifacts and the automated restoration of corrupted video frames is a fundamental medical imaging problem. Existing state-of-the-art methods only deal with the detection and restoration of selected artifacts. However, typically endoscopy videos contain numerous artifacts which motivates to establish a comprehensive solution. We propose a fully automatic framework that can: 1) detect and classify six different primary artifacts, 2) provide a quality score for each frame and 3) restore mildly corrupted frames. To detect different artifacts our framework exploits fast multi-scale, single stage convolutional neural network detector. We introduce a quality metric to assess frame quality and predict image restoration success. Generative adversarial networks with carefully chosen regularization are finally used to restore corrupted frames. Our detector yields the highest mean average precision (mAP at 5% threshold) of 49.0 and the lowest computational time of 88 ms allowing for accurate real-time processing. Our restoration models for blind deblurring, saturation correction and inpainting demonstrate significant improvements over previous methods. On a set of 10 test videos we show that our approach preserves an average of 68.7% which is 25% more frames than that retained from the raw videos.Comment: 14 page

Practical Issues in Floodplain Mapping Over Large Regions

Flooding events are among the costliest and most frequent natural hazards occurring in Canada. Floodplain mapping is a non-structural flood management strategy that involves the formulation of hydrologic and hydraulic models to produce maps which predict extent and depth of floods. Practices and availability of floodplain mapping vary across Canada. The current state of floodplain mapping across Canada has been identified and reviewed. Vast areas of flood prone regions across Canada have been identified as not having floodplain maps or lacking updated ones. Large region floodplain maps have been recently introduced and can cover national and global regions. Limitations of spatial resolution exist in large region mapping efforts, which hinder their implementation for local scale floodplain management practices. A recent study at Western University produced a national floodplain map with a spatial resolution of 1 km x 1 km. This national floodplain map is highly accurate; however, spatial resolution needs to be improved to be implemented within local scale floodplain studies. The study presented in this thesis developed a downscaling methodology to further improve spatial resolution of the floodplain map. The downscaling methodology was implemented to produce floodplain maps at spatial resolutions of 20m, 40m, 60m, 80m, 100m, 200m, 300m, and 400m for two case study river basins: Bow and Elbow River Basin and St John River Basin. Analysis of the floodplain maps was completed, followed by volume conservation and computational time studies to assess the accuracy of the proposed downscaling methodology and to compare the sensitivity of the downscaling methodology

Vascular regeneration in a basal chordate is due to the presence of immobile, bi-functional cells.

The source of tissue turnover during homeostasis or following injury is usually due to proliferation of a small number of resident, lineage-restricted stem cells that have the ability to amplify and differentiate into mature cell types. We are studying vascular regeneration in a chordate model organism, Botryllus schlosseri, and have previously found that following surgical ablation of the extracorporeal vasculature, new tissue will regenerate in a VEGF-dependent process within 48 hrs. Here we use a novel vascular cell lineage tracing methodology to assess regeneration in parabiosed individuals and demonstrate that the source of regenerated vasculature is due to the proliferation of pre-existing vascular resident cells and not a mobile progenitor. We also show that these cells are bi-potential, and can reversibly adopt two fates, that of the newly forming vessels or the differentiated vascular tissue at the terminus of the vasculature, known as ampullae. In addition, we show that pre-existing vascular resident cells differentially express progenitor and differentiated cell markers including the Botryllus homologs of CD133, VEGFR-2, and Cadherin during the regenerative process

Evaluation of Ankom F58 Filter Bags Compared to Dacron Bags and Beakers for Analysis of Acid Detergent Fiber

Feed and fecal samples were analyzed to compare three methods of determining acid detergent fiber. Each sample was weighed into both Dacron and Ankom F58 fiber bags and then analyzed using an Ankom fiber analyzer. Results were then compared to the Van Soest beaker method. Ankom F58 bags helped reduce washout of small particles associated with Dacron bags, but fecal samples needed to be incubated in detergent for an extended amount of time to isolate acid detergent fiber material. Utilizing a technique that produces correct acid detergent fiber values is important for producers because these values are used as a proxy for calculating total digestible nutrients of feedstuffs

Analysis of potential for supplemental irrigation in southern Illinois

The aim of this study is to determine the potential for supplemental crop irrigation of the tight subsoil area of Southern Illinois with surface water impounded in small catchment reservoirs. The geographic area of the tight soils (mainly the southern 1/3 of Illinois includes almost 25 percent of the state. Random statistical sampling was used to select topographic quadrangles in this area for investigation of reservoir sites. Costs and water volume were then computed for sites with potential for reservoir siting. The results of the survey of potential reservoirs and cost analysis indicate about 1.2 million acres of land in the claypan area of Southern Illinois can be irrigated under current cost conditions depending on the price of corn and soybeans. From inspection of the best potential reservoir sites, watersheds, and irrigation areas, a specific site was selected for detailed analysis. Site analysis showed the most profitable management practice to be a corn-soybean rotation with reduced tillage, up-and-down slopes plowing, and irrigation. Further analysis was performed concerning the effect of sedimentation on reservoir capacity and, optimal land use. The results indicate that, over a thirty-year period, sedimentation will not have any appreciable effect on reservoir capacity and on land use practice. Finally, the supplemental irrigation system was analysed to determine its overall economic feasibility. A supply curve for irrigation from reservoirs was developed.U.S. Department of the InteriorU.S. Geological SurveyOpe

Vis-SPLIT: Interactive Hierarchical Modeling for mRNA Expression Classification

We propose an interactive visual analytics tool, Vis-SPLIT, for partitioning a population of individuals into groups with similar gene signatures. Vis-SPLIT allows users to interactively explore a dataset and exploit visual separations to build a classification model for specific cancers. The visualization components reveal gene expression and correlation to assist specific partitioning decisions, while also providing overviews for the decision model and clustered genetic signatures. We demonstrate the effectiveness of our framework through a case study and evaluate its usability with domain experts. Our results show that Vis-SPLIT can classify patients based on their genetic signatures to effectively gain insights into RNA sequencing data, as compared to an existing classification system.Comment: To be published in IEEE Visualization and Visual Analytics (VIS), 202

Incorporating Childhood Games Into the Memory Club Program

Alzheimer’s Care Armenia created the Memory Club to slow the progression of memory loss in the elderly. Our project aimed to incorporate participant\u27s childhood games into the Memory Club; to decrease anxiety and enhance their quality of life by improving their overall cognitive functioning. To accomplish our goal, we researched Armenian childhood games, evaluated each game for cognitive benefits, and assessed the results. The success of the program was measured using two standardized tests given to the participants and a comparison group: the Montreal Cognitive Assessment (MoCA) and Geriatric Anxiety Scale 10 Item (GAS-10). The test results were inconclusive, however, based on the changes seen in the participants’ behavior, emotions, and mental state, the Memory Club was deemed a success