Performance of Lung Carcinoma in Classification Neural Network with Pre Processing Using WEGA

Data pre processing ease the mining procedure by removing the insignificant information and errors that may arise while entering the data manually. The data collection method is not strict so there accompanies missing and incorrect values, irrelevant variables, data with out of range etc. These have significant impact and minimize the accuracy of the mining process. Generally accuracy in the case of medical research must reach to the extent. There are many factors affect the analysis on the given task. The precise representation and quality of the dataset is vital. If there exists more irrelevant and redundant information the meaningful discovery of knowledge is a big question. Pre processing is a prominent way for the data preparation and thus it the earlier stage in mining. It includes many variant procedures according to the problem of the set. The output is taken as the direct training set for further research. This research analyse the Lung cancer dataset with fifteen attributes by applying pre processing method attribute evaluation. This method reduce the dimensionality, file size and time taken for the analysis by considering only on the most relevant variables. The work is carried in the WEKA tool as it has enormous procedures for data preparation. The performance before and after pre processing is discussed with suitable metrics

Hydrothermal assisted morphology designed MoS2 material as alternative cathode catalyst for PEM electrolyser application

In this work, we developed a simple and cost-effective hydrothermal route to regulate the formation of molybdenum disulfide (MoS2) in different morphologies, like, nano-sheet, nano-capsule and nano-flake structure by controlling the reaction temperature and sulphur precursor employed. Such a fine tuning of different morphologies yields a leverage to obtain novel shapes with high surface area to employ them as suitable candidates for hydrogen evolution catalysts. Moreover, we report here the first time observation of MoS2 nano-capsule formation via environmentally benign hydrothermal route and characterized them by X-ray diffraction (XRD), nitrogen adsorption and desorption by Brunaer–Emmett–Teller (BET) method, scanning electron microscopy (SEM), transmission electron microscopy (TEM), high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) and X-ray photo-electron spectroscopy (XPS) techniques. MoS2 nano-capsules exhibits superior activity towards hydrogen evolution reaction (HER) with a low over-potential of 120 mV (RHE), accompanied by large exchange current density and excellent stability in 0.5 M H2SO4 solution. MoS2 nano-capsule catalyst was coated on solid proton conducting membrane (Nafion) and IrO2 as anode catalyst. The performance of the catalyst was evaluated in MEA mode for 200 h at 2 V without any degradation of electrocatalytic activity

Microsoft Word - 52-225.doc

Abstract: Quantum dot Cellular Automata (QCA) offers a new transistorless computing paradigm in nanotechnology. It has the potential for attractive features such as faster speed , smaller size and low power consumption than transistor based technology .By taking the advantages of QCA we are able to design interesting computational architecture. The basic logic elements used in this technology are the inverter and the majority gate (MG). The majority gate is not a universal gate .Hence another important logic gate introduced in this technology is And-Or-Inverter (AOI).In this paper, we propose design of different logical structures using AOI. The rules are introduced in this paper for easy implementation of AOI circuits for different functions and characteristics of AOI is also defined and analyzed. Design implementations using the AOI gate are compared with the conventional CMOS and majority gate based QCA methodology

Hardware Implementation of Road Network Extraction Using Simplified Gabor Wavelet in Field Programmable Gate Array

Automatic detection of road networks from the satellite and aerial images is the most demanded research area, and it is used for various remote sensing applications. The Simplified Gabor Wavelet based approaches are used to extract the road network automatically. In this paper, a field programmable gate array architecture designed for automatic extraction of road network using Simplified Gabor Wavelet is proposed. The hardware implementation results are compared with software implementation results. The performance measures such as completeness, correctness and quality are calculated. In the software implementation, the average value of completeness, correctness, and quality of various images are 91%, 98%, and 89% respectively. In the hardware implementation, the average value of completeness, correctness, and quality are 89%, 97%, and 87% respectively. The performance of the proposed algorithm is also proved in noisy images. These measures prove that the proposed work yields road network very resembling to reference road map.

Hardware Implementation of Road Network Extraction Using Simplified Gabor Wavelet in Field Programmable Gate Array

Automatic detection of road networks from the satellite and aerial images is the most demanded research area, and it is used for various remote sensing applications. The Simplified Gabor Wavelet based approaches are used to extract the road network automatically. In this paper, a field programmable gate array architecture designed for automatic extraction of road network using Simplified Gabor Wavelet is proposed. The hardware implementation results are compared with software implementation results. The performance measures such as completeness, correctness and quality are calculated. In the software implementation, the average value of completeness, correctness, and quality of various images are 91%, 98%, and 89% respectively. In the hardware implementation, the average value of completeness, correctness, and quality are 89%, 97%, and 87% respectively. The performance of the proposed algorithm is also proved in noisy images. These measures prove that the proposed work yields road network very resembling to reference road map.

Transmission Dynamics of Japanese Encephalitis, with Emphasis on Gaps in Understanding and Priority Areas for Research on Japanese Encephalitis and Other Acute Encephalitis Syndromes in India

Japanese encephalitis (JE), a vector-borne zoonotic viral disease, is endemic to large parts of Asia and the Pacific, but has potential to spread to other parts of the world. An estimated 3 billion people are at risk, and about 67,000 cases being reported annually, most of which are from India. The disease is transmitted by mosquitoes mostly belonging to Culex vishnui subgroup. It is considered vaccine preventable and, with the help of vector control, is largely kept under check notwithstanding periodic outbreaks. Vaccination programmes, increased living standards, and mechanization of agriculture are the key factors in the decline of incidence of this disease in Japan and South Korea, and in some other countries, including India (667 cases and 200 deaths in 1981 to 33 in 2013 without a death); Japanese encephalitis is on the decline since mid-1990s. However, transmission of JE is likely to increase in Bangladesh, Cambodia, Indonesia, Laos, Myanmar, North Korea and Pakistan because of population growth, intensified rice farming, failure of vector control in vast stretches of paddy ecosystems, unorganized pig rearing and the lack of effective vaccination programs and disease surveillance. A leading cause of acute encephalitis syndrome (AES), the JE coupled with an ever increasing trend in AES cases, recently poses many challenges as the infection is not only involving an array of animals as amplifiers, but is also transmitted by an overwhelmingly high number of mosquito species belonging to varied genera as Culex, Anopheles, Monsonia and Armigeres