The majority of the analyzed calculi from patients are composed of calcium oxalate (CaOx) monohydrate whewellite (Wh) and CaOx dihydrate wedellite (Wd). The urinary calculi were identified by chemical and morphological analysis based on106 urine samples from human voluntary. The Crystalluria made by an optical polarized light microscopy. The oxaluria and urinary calcium were determined by conventional volumetric assays. The aim of this paper was to develop a simple system to predict and classify the type of crystalluria using Artificial Neural Networks (ANNs) algorithm.
The goal of this study is to develop a simple intelligent urolithiasis diagnosis system. The accuracy of the system was determined by comparing the recognition rates of the Artificial Neural Networks (ANNs)-, k-nearest Neighbor (kNN)-, and Support Vector Machines (SVM) algorithms. The results showed that the ANN model was superior to SVM and KNN models in prediction. We aimed through this work to classify the subjects in three classes according to the chemical concentrations of variables (Ca, Ox, pCaOx, Ca/ Ox) using and according to their clinical status. The ANN model, used to determine the first class that contains the subjects presenting their urine a calcium oxalate monohydrate (CaC2O4,H2O : whewellite (Wh)) crystal type. This ANN model reached a correct prediction rate of 85.3%. Using SVM- and KNN model the correct prediction rate reached 82.6% and 65.55% respectively. The second class contains the subjects presenting a calcium oxalate dihydrate (CaC2O4,2H2O wedellite (Wd)) crystal type. The ANN-, SVM- and KNN model reached a 93.4%-, 94.2%- and 77.25% correct prediction rate, respectively. In third class that corresponds to the subjects who have negative crystalluria (NC), ANN-, SVM- and KNN model reached a 91.7%-, 87.8%- and 69.77% correct prediction rate, respectively. Compared to SVM- and KNN models, the developed system using ANN model has allowed us to discriminate the subjects. This system is important in clinical laboratories since it could be a helpful tool for provide information about the development, formation of urinary stones crystals and the determination of their crystal type.
This paper presents the project "edugame" whose objective is to provide an educational game which introduces a series of activities such as the construction of words, the recognition of letters or mathematical operations for teaching children. We chose to follow, for this project, a methodological approach which begins with a design phase, using UML, followed by an implementation phase using the Android platform. This allowed us to make available to children of 3 to 7 years an interactive game for independent learning.
In this article, we defined the steps to create a web service based on an example that relates to the field of e-Learning. In addition, it cited the components and the basic functionality of a web service. In determining the concepts on which is based the web services namely SOAP and WSDL (a description in XML Schema web service) and UDDI, these three elements constitute the life cycle of use of a web service architecture in a distributed client / server.