Computer Graphics and Visualization based Analysis and Record System for Hand Surgery and Therapy Practice

In this thesis, we have designed and developed a computer graphics and visualization based analysis and record system for hand surgery and therapy practice. In particular, we have designed and developed three novel technologies: (i) model-based data compression for hand motion records (ii) model-based surface area estimation of a human hand and (iii) an emulated study of hand wound area estimation. First, we have presented a new data compression technique to better address the needs of electronic health record systems, such as file storage and privacy. In our proposed approach, we will extract the patient\u27s hand motion information and store the motion data in a binary format, and then we use a loss less data compression to further reduce the file size. To illustrate this idea, we have built a prototype, which demonstrates our entire work flow. Our experiment results have shown the effective compression performance as well as added benefit of 3-D review, enhanced privacy and review capability at different playback speeds and view angles. Next, we developed a new approach, to estimate the surface area of a patient\u27s hand accurately and quickly with a low-cost imaging sensor and a graphics based hand model. Through the image capturing device, we capture infrared images of the patient\u27s hand. Once we get the input images, we run them through the image analysis engine to extract the required information in order to obtain a customized graphics hand object. Once customized we use the graphics hand object to calculate the surface area of the patient\u27s hand. To illustrate this idea, we have built a prototype system, which demonstrate the entire work flow. Our experiment results have shown considerable reproducibility and consistency. Finally, we came up with a novel system, capable of identifying simulated wounds on a human hand and estimating their area. Through the imaging device, wound analysis engines, we are able to identify simulated wounds on a patient\u27s hand and measure their area using optical equations. To illustrate this idea, we have built a prototype system, which demonstrates our entire work flow. Our experiments show considerable reproducibility, accuracy and consistency. In summary, we have developed prototypes for each of the approaches to demonstrate its capabilities. Experiments and analysis are carried out to study their performance and complexity. We believe these new approaches can significantly improve the current practice in hand surgery analysis and therapy practice

Application of GIS for Estimation of Brightness Temperature using Landsat Data in Kilite Awulalo, Tigray Ethiopia

Put into practice of on Plantation and Domestic/home gardens, as an important component of both rural and urban green infrastructure, could make significant contributions to rural and urban biodiversity and which results to minimizing global warming in general and surface temperature in particular. There for this study investigates surface temperature estimation using Landsat Data in Kilite Awulalo, Tigray Ethiopia. The reason for selecting this area is due to the fact that, in the area there was afforestation and reforestation program have be done from 1980s. This initiates to assessing the works of the area especially on plantation programs for regulation of surface temperature. To do this, the specific objective of the study is to examine the application of GIS for Estimating surface Temperature using landsat data. The land surface temperature (LST) was retrieved from thermal infrared band of each LANDSAT images covering over a period 1984 (Landsat-5 TM band 6); 2000 (Landsat-7 ETM+ band 6) and 2014 (Landsat-8 OLI_TIRS band 11) was used and analyzed using Arc GIS 10.1. The surface temperature is then extracted from the surface radiance. Based on Landsat image, mean temperature of the 1984 TM of the area is 28.12°C, minimum temperature as 12.78°C and the maximum temperature is 36.72oC; mean temperature of the 2000 ETM+ of the area is 30.39°C, minimum temperature as 13.4°C and the maximum temperature is 41.92oC; and mean temperature of the 2014 OLI_TIRS of the area is 35.77°C, minimum temperature as 31.9°C and the maximum temperature is 43.26oC. From this we can understand that there is a significant change and increasing of brightness temperature between from year 1984, year 2000 and year 2014. Keywords: Landsat Data, RS, GIS, Brightness Temperatur

Performance of formulae based estimates of glomerular filtration rate for carboplatin dosing in stage 1 seminoma

<b>Background:</b> Single cycle carboplatin, dosed by glomerular filtration rate (GFR), is standard adjuvant therapy for stage 1 seminoma. Accurate measurement of GFR is essential for correct dosing. Isotopic methods remain the gold standard for the determination of GFR. Formulae to estimate GFR have improved the assessment of renal function in non-oncological settings. We assessed the utility of these formulae for carboplatin dosing.<p></p> <b>Methods:</b> We studied consecutive subjects receiving adjuvant carboplatin for stage 1 seminoma at our institution between 2007 and 2012. Subjects underwent 51Cr-ethylene diamine tetra-acetic acid (EDTA) measurement of GFR with carboplatin dose calculated using the Calvert formula. Theoretical carboplatin doses were calculated from estimated GFR using Chronic Kidney Disease-Epidemiology (CKD-EPI), Management of Diet in Renal Disease (MDRD) and Cockcroft–Gault (CG) formulae with additional correction for actual body surface area (BSA). Carboplatin doses calculated by formulae were compared with dose calculated by isotopic GFR; a difference <10% was considered acceptable.<p></p> <b>Results:</b> 115 patients were identified. Mean isotopic GFR was 96.9 ml/min/1.73 m2. CG and CKD-EPI tended to overestimate GFR whereas MDRD tended to underestimate GFR. The CKD-EPI formula had greatest accuracy. The CKD-EPI formula, corrected for actual BSA, performed best; 45.9% of patients received within 10% of correct carboplatin dose. Patients predicted as underdosed (13.5%) by CKD-EPI were more likely to be obese (p = 0.013); there were no predictors of the 40.5% receiving an excess dose.<p></p> <b>Conclusions:</b> Our data support further evaluation of the CKD-EPI formula in this patient population but clinically significant variances in carboplatin dosing occur using non-isotopic methods of GFR estimation. Isotopic determination of GFR should remain the recommended standard for carboplatin dosing when accuracy is essential.<p></p&gt

Adaptive online parameter estimation algorithm of PEM fuel cells

Since most of fuel cell models are generally nonlinearly parameterized functions, existing modeling techniques rely on the optimization approaches and impose heavy computational costs. In this paper, an adaptive online parameter estimation approach for PEM fuel cells is developed in order to directly estimate unknown parameters. The general framework of this approach is that the electrochemical model is first reformulated using Taylor series expansion. Then, one recently proposed adaptive parameter estimation method is further tailored to estimate the unknown parameters. In this method, the adaptive law is directly driven by the parameter estimation errors without using any predictors or observers. Moreover, parameter estimation errors can be guaranteed to achieve exponential convergence. Besides, the online validation of regressor matrix invertibility are avoided such that computation costs can be effectively reduced. Finally, comparative simulation results demonstrate that the proposed approach can achieve better performance than least square algorithm for estimating unknown parameters of fuel cells.Postprint (published version

Depth estimation of inner wall defects by means of infrared thermography

There two common methods dealing with interpreting data from infrared thermography: qualitatively and quantitatively. On a certain condition, the first method would be sufficient, but for an accurate interpretation, one should undergo the second one. This report proposes a method to estimate the defect depth quantitatively at an inner wall of petrochemical furnace wall. Finite element method (FEM) is used to model multilayer walls and to simulate temperature distribution due to the existence of the defect. Five informative parameters are proposed for depth estimation purpose. These parameters are the maximum temperature over the defect area (Tmax-def), the average temperature at the right edge of the defect (Tavg-right), the average temperature at the left edge of the defect (Tavg-left), the average temperature at the top edge of the defect (Tavg-top), and the average temperature over the sound area (Tavg-so). Artificial Neural Network (ANN) was trained with these parameters for estimating the defect depth. Two ANN architectures, Multi Layer Perceptron (MLP) and Radial Basis Function (RBF) network were trained for various defect depths. ANNs were used to estimate the controlled and testing data. The result shows that 100% accuracy of depth estimation was achieved for the controlled data. For the testing data, the accuracy was above 90% for the MLP network and above 80% for the RBF network. The results showed that the proposed informative parameters are useful for the estimation of defect depth and it is also clear that ANN can be used for quantitative interpretation of thermography data

Parameter estimation algorithm of H-100 PEM fuel cell

Best Oral Communication Award for Young Authors, atorgat pel comitè científic HYCELTEC 2019Polymer electrolyte membrane fuel cells (PEMFCs) have been recognized as one of the most promising eneygy conversion devices for commercial application due to their specific advantages, such as low operation temperature, zero pollutant emission, and high efficiency, etc. Since PEMFC is a highly nonlinear system and some parameters are related to the operation condition, most existing models are difficult to accurately predict the PEMFC characteristics. Thus, it is necessary to exploit parameter estimation methods for PEMFC to online determine the unknown model parameters by using easily measurable data to obtain concrete models. Most of the parameter estimations schemes for PEMFC have been designed based on intelligent optimization techniques. However, optimization methods cannot address the estimation problem online since they focus exclusively on offline searching procedure, which introduces heavy computational costs in the practical implementation and thus cannot be used in the real-time applications. Therefore, this paper aims to exploit real-time adaptive parameter estimation methods for a nonlinear parametric PEMFC system.Peer ReviewedAward-winningPostprint (author's final draft