Classification techniques using gray level co-occurrence matrix features for the detection of lung cancer using computed tomography imaging

Lung cancer, which causes the majority of fatalities worldwide each year, is one of the deadliest diseases. The survival rate of cancer patients could be improved with better cancer detection methods. Image processing and machine learning have both been used to aid in lung cancer detection, but a method that both increase accuracy and increases a patient’s survival rate has yet to be identified. In an effort to find the most effective method for the accurate lung cancer recognition, this paper analyses and compares several classification algorithms. Lung computed tomography (CT) images are enhanced by removing noise using a median filter. For filtered image, threshold segmentation is used to segment it into distinct parts. From the segmented image different features are extracted using the grey level co-occurrence matrix (GLCM). several classification strategies, including support vector machine (SVM), random forest (RF), k-nearest neighbor (KNN), and decision tree (DT) methods, are used to classify lung images as malignant or normal based on the extracted features. Methods are evaluated based on a number of various performance measures, like accuracy, a precision, the recall, and the F1-Score. Based on the experimental outcomes, SVM outperforms other classification methods in accurately detecting lung cancer with an accuracy of 99.32%

Design and Analysis of Dry Cylinder Liners Used in Diesel Engines

A Cylinder liner is a cylindrical part to be fitted  in to an engine block to form a cylindrical space in which the piston reciprocates very smoothly. It is one of the most important functional parts to make up the interior of an engine. Generally cylinder liners are made of Cast Iron, Cast steel, Nickel CI, Nickel chrome CI. The aim of this project is to design and analyze a dry cylinder liner for Hino-X diesel engines. A Hino – X engine cylinder dry liner used in one of Ashok Leyland model manufactured by  The amount of heat generated, heat transfer rate of the component, temperature produced inside the cylinder are to be calculated using ANSYS analysis package. Various surface coatings like ceramic, aluminum alloys and Nickel chrome alloy steel are used to study the, heat flux, , thermal stresses, thermal displacement, thermal gradient ,nodal temperatures of the cylinder liner. Modeling is done in Pro/Engineer and analysis is done coupled field analysis in ansys. After comparing the results, the best coated cylinder dry liner for this type of diesel engine can be suggested

Simulation of Surface Ozone Pollution in the Central Gulf Coast Region Using WRF/Chem Model: Sensitivity to PBL and Land Surface Physics

The fully coupled WRF/Chem (Weather Research and Forecasting/Chemistry) model is used to simulate air quality in the Mississippi Gulf coastal region at a high resolution (4 km) for a moderately severe summer ozone episode between 18 CST 7 and 18 CST 10 June 2006. The model sensitivity is studied for meteorological and gaseous criteria pollutants (O3, NO2) using three Planetary Boundary Layer (PBL) and four land surface model (LSM) schemes and comparison of model results with monitoring station observations. Results indicated that a few combinations of PBL and LSMs could reasonably produce realistic meteorological fields and that the combination of Yonsei University (YSU) PBL and NOAH LSM provides best predictions for winds, temperature, humidity and mixed layer depth in the study region for the period of study. The diurnal range in ozone concentration is better estimated by the YSU PBL in association with either 5-layer or NOAH land surface model. The model seems to underestimate the ozone concentrations in the study domain because of underestimation of temperatures and overestimation of winds. The underestimation of NO2 by model suggests the necessity of examining the emission data in respect of its accurate representation at model resolution. Quantitative analysis for most monitoring stations indicates that the combination of YSU PBL with NOAH LSM provides the best results for various chemical species with minimum BIAS, RMSE, and high correlation values

Inorganic molecular sieves: Preparation, modification and industrial application in catalytic processes

[EN] The increasing environmental concern and promotion of “green processes” are forcing the substitution of traditional acid and base homogeneous catalysts by solid ones. Among these heterogeneous catalysts, zeolites and zeotypes can be considered as real “green” catalysts, due to their benign nature from an environmental point of view. The importance of these inorganic molecular sieves within the field of heterogeneous catalysis relies not only on their microporous structure and the related shape selectivity, but also on the flexibility of their chemical composition. Modification of the zeolite framework composition results in materials with acidic, basic or redox properties, whereas multifunctional catalysts can be obtained by introducing metals by ion exchange or impregnation procedures, that can catalyze hydrogenation–dehydrogenation reactions, and the number of commercial applications of zeolite based catalysts is continuously expanding. In this review we discuss determinant issues for the development of zeolite based catalysts, going from zeolite catalyst preparation up to their industrial application. Concerning the synthesis of microporous materials we present some of the new trends moving into larger pore structures or into organic free synthesis media procedures, thanks to the incorporation of novel organic templates or alternative framework elements, and to the use of high-throughput synthesis methods. Post-synthesis zeolite modification and final catalyst conformation for industrial use are briefly discussed. In a last section we give a thorough overview on the application of zeolites in industrial processes. Some of them are well established mature technologies, such as fluid catalytic cracking, hydrocracking or aromatics alkylation. Although the number of zeolite structures commercially used as heterogeneous catalysts in these fields is limited, the development of new catalysts is a continuous challenge due to the need for processing heavier feeds or for increasing the quality of the products. The application of zeolite based catalysts in the production of chemicals and fine chemicals is an emerging field, and will greatly depend on the discovery of new or known structures by alternative, lower cost, synthesis routes, and the fine tuning of their textural properties. Finally, biomass conversion and selective catalytic reduction for conversion of NOx are two active research fields, highlighting the interest in these potential industrial applications.The authors acknowledge financial support from Ministerio de Ciencia e Innovacion (project Consolider-Ingenio 2010 MULTICAT).Martínez Sánchez, MC.; Corma Canós, A. (2011). Inorganic molecular sieves: Preparation, modification and industrial application in catalytic processes. Coordination Chemistry Reviews. 255(13-14):1558-1580. doi:10.1016/j.ccr.2011.03.014S1558158025513-1

Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans

Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci now explain ∼38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same regio