The method of processing two algorithms within a single workflow, and hence the combined method, is called as hybrid computing. We propose a data mining framework comprising of two stages, namely clustering and classification. The first stage employs k-means algorithm on data and generates two clusters, namely cluster-0 and cluster-1. Instances in cluster-0 do not have disease symptoms and cluster-1 consists of instances with disease symptoms. The verification of valid grouping is then carried out by referring to the association of class labels in original datasets. Incorrectly classified instances are removed and remaining instances are used to build the classifier using C4.5 decision-tree algorithm with k-fold cross validation method. The framework was tested using eight datasets from the machine learning repository of the UCI. The proposed framework was evaluated for accuracy, sensitivity and specificity measures. Our framework obtained promising classification accuracy as compared to other methods found in the literature.
- Inderscience Publishers
- Effective framework for prediction of disease outcome using ...
Release Announcement – SymphoniePRO Desktop Application V.3.0
We are excited to share the latest version of software for the SymphoniePRO Data Logger. This release, version 3.0, introduces exciting new functionality as well as performance improvements. Below are some of the highlights: Utility Enhancements Like POPAuto, which was included in SymphoniePRO Desktop Application version 2.0, version 3.0 of SymphoniePRO Desktop now installs a similar productivity-boosting lightweight utility called OutAuto. OutAuto can be used to extract hundreds of raw logger data files from...
Interview with Senior Vice President, Jordi Verdés, at iWater, Barcelona 2016
Kurita has attended to the first edition of iWater in Barcelona between 15th and 17th of November. Take a look at the interview with Jordi Verdés, Senior Vice President of Kurita Europe GmbH. He highlighted Kurita´s contribution to the environment through water and paper applications. Interview with Senior Vice President of Kurita Europe, Jordi Verdés, at iWater, Barcelona 2016
Toxicological and Environmental Safety Data - Case Study
IntroductionAGRAGEL is a cross-linked copolymer of acrylic acid and acrylamide partially neutralized as potassium/ ammonium salt. The polymer is in its dry form a granulate and forms a gel-like material upon addition of water or aqueous solutions. Due to the cross-linking it is insoluble in water. Uptake of water is facilitated mainly by the negative carboxylic groups of the polymer and their hydration with water molecules. Complete solubilization is hindered because of the cross-linking of different polymer...
Arsenic adsorption using Fe(III)-loaded porous amidoximated acrylonitrile/itaconic copolymers
A highly selective polymeric ligand exchanger was developed for the removal of trace As(V) from aqueous solution. This adsorbent was prepared by loading Fe(III) onto porous amidoximated polyacrynitrile (AN)/itaconic acid (IA) copolymers (Fe(III)-AO AN/IA). Negligible ferric ion dissolution was observed from Fe(III)-AO AN/IA in solution of acidic pHs up to 2. As(V) adsorption by Fe(III)-AO AN/IA is a pH-dependent process with maximum capacity of 1.32 mg/g at pH 2–3. The adsorption process was found to be governed...
Alkaline fermentation of waste activated sludge stimulated by saponin: volatile fatty acid ...
Volatile fatty acid (VFA) production stimulated by saponin (SP), an environmentally friendly bio-surfactant, was investigated during sludge alkaline fermentation in laboratory studies and pilot applications. The combined use of SP and pH 9 condition significantly enhanced VFA production to approximately 425 mg COD/g VSS, which was 4.7-fold of raw sludge and 1.5-fold of sole pH 10 adjustment (the optimum pH for alkaline fermentation). Further results indicated that SP & pH 9 condition provided sufficient...