2,188 research outputs found
PERFORMANCE ANALYSIS OF BREAST CANCER CLASSIFICATION USING DECISION TREE CLASSIFIERS
Breast cancer is one of the dangerous cancers among world's women above 35 y. The breast is made up of lobules that secrete milk and thin milk ducts to carry milk from lobules to the nipple. Breast cancer mostly occurs either in lobules or in milk ducts. The most common type of breast cancer is ductal carcinoma where it starts from ducts and spreads across the lobules and surrounding tissues. According to the medical survey, each year there are about 125.0 per 100,000 new cases of breast cancer are diagnosed and 21.5 per 100,000 women due to this disease in the United States. Also, 246,660 new cases of women with cancer are estimated for the year 2016. Early diagnosis of breast cancer is a key factor for long-term survival of cancer patients. Classification plays an important role in breast cancer detection and used by researchers to analyse and classify the medical data. In this research work, priority-based decision tree classifier algorithm has been implemented for Wisconsin Breast cancer dataset. This paper analyzes the different decision tree classifier algorithms for Wisconsin original, diagnostic and prognostic dataset using WEKA software. The performance of the classifiers are evaluated against the parameters like accuracy, Kappa statistic, Entropy, RMSE, TP Rate, FP Rate, Precision, Recall, F-Measure, ROC, Specificity, Sensitivity
DECISION TREE CLASSIFIERS FOR CLASSIFICATION OF BREAST CANCER
Objective: Breast cancer is one of the dangerous cancers among world's women above 35 y. The breast is made up of lobules that secrete milk and thin milk ducts to carry milk from lobules to the nipple. Breast cancer mostly occurs either in lobules or in milk ducts. The most common type of breast cancer is ductal carcinoma where it starts from ducts and spreads across the lobules and surrounding tissues. Survey: According to the medical survey, each year there are about 125.0 per 100,000 new cases of breast cancer are diagnosed and 21.5 per 100,000 women due to this disease in united states. Also, 246,660 new cases of women with cancer are estimated for the year 2016.Methods: Early diagnosis of breast cancer is a key factor for long-term survival of cancer patients. Classification is one of the vital techniques used by researchers to analyze and classify the medical data.Results: This paper analyzes the different decision tree classifier algorithms for seer breast cancer dataset using WEKA software. The performance of the classifiers are evaluated against the parameters like accuracy, Kappa statistic, Entropy, RMSE, TP Rate, FP Rate, Precision, Recall, F-Measure, ROC, Specificity, Sensitivity.Conclusion: The simulation results shows REPTree classifier classifies the data with 93.63% accuracy and minimum RMSE of 0.1628 REPTree algorithm consumes less time to build the model with 0.929 ROC and 0.959 PRC values. By comparing classification results, we confirm that a REPTree algorithm is better than other classification algorithms for SEER dataset
Regeneration of the proboscis of cymatiid Cymatium pileare (Gastropoda: Proso branchia)
Cymatiids cause considerable damage to bivalve stock in molluscan culture. Bivalves are preyed upon by
cymatiids with insertion of proboscis and interaction of radula and jaws. Rate of regeneration of proboscis in
cymatiid was faster than predatory thiasid and muricid gastropods
Effect of temperature on the feeding rate of cymatiid Cymatium (Monoplex) pileare (Gastropoda:Prosobranchia)
Influence of temperature (24┬░, 28┬░, 31┬░ or 34┬░C) was studied on the feeding rate of predatory
cymatiid. Cymatium (Manop/ex) pileare fed with edible oyster.The rate of feeding increased from 2 to
5.3 oysters/gastropod/month as temperature increased from 24┬░ to 31┬░C. Increase in temperature
decreased the days of feeding interval from 6.3 days at 24┬░C to 3.7 days at 34┬░C. All test animals
courted mortality at 34┬░C on 17th day suggesting it as the upper tolerable limit of temperature
Determination of Optimal Double Sampling Plan using Genetic Algorithm
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In this paper a genetic algorithm has been designed for the selection of optimal acceptance numbers and sample sizes for the specified producer’s risk and consumer’s risk. Implementation of the algorithm has been illustrated numerically for different choices of quantities involved in a double sampling plan<span> </span><span> </span></span> <script type="text/javascript"><!--\ud
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Evaluation of Anti-Diabetic Activity of Isolated Fractions of Allium Sativum
The present study focuses the determination of the anti-diabetic activity of the extracted fractions of Allium sativum in rats with diabetes induced through STZ. The 20 mg/kg and 40 mg/kg doses of Allium sativum were given to the rats for 28 days. Using the accu-chek active test meter, blood glucose levels were measured to assess the anti-diabetic effects of the isolated fractions. Additionally, a comparison was made with the standard anti-diabetic medication, Pioglitazone, was given to another group of rats at a normal dose of 2.7 mg/kg. The results revealed that Allium sativum had significant anti-diabetic activity. Also, the Allium sativum remained safe till 300 mg/kg in acute toxic and 1000 mg/kg in sub-acute toxic studies and had photochemically. From these findings it can be inferred that Allium sativum has lowered FBG in experimentally induced diabetic rats
Clinical and angiographic profile of symptomatic patients undergoing percutaneous transluminal coronary angioplasty and drug-eluting stent implantation
Background: There are limited number of studies in India which have looked at this clinical and angiographic characteristic of the disease. Thus, this study was conducted to assess the clinical and angiographic profile of symptomatic patients who underwent percutaneous transluminal coronary angioplasty (PTCA) and drug-eluting stent (DES) implantation.Methods: This was an observational study conducted at a tertiary-care center in India between November 2014 and November 2015. A total of 106 consecutive patients who received either Cypher/Xience/BioMime stent presented with anginal symptoms were included in the study. Based on the type of stent received, patients were divided into two groups: (A) Limus group; (B) Paclitaxel group. Coronary angiogram was done in all the patients. Angioplasty data were collected from patient records. Angiographic profiles of the two groups were compared and analysed.Results: Among the 106 patients, 54 patients were included in the Limus group and 52 patients were included in the Taxus stent. De novo lesions were found to be significantly higher in the Limus group (40(74%), p = 0.06) whereas the in-stent restenosis was found to be significantly higher in the paclitaxel group (22(42.3%), p = 0.08). At follow-up, the incidence of death was 0% and no patients suffered by myocardial infarction. One (1.8%), two (3.8%) patients from the Limus and Paclitaxel groups had target vessel revascularization, respectively.Conclusions: Development of lesions in new areas rather than in-stent restenosis is the cause for angina in the majority of patients who underwent angioplasty presenting with anginal symptoms
Formal Design of Asynchronous Fault Detection and Identification Components using Temporal Epistemic Logic
Autonomous critical systems, such as satellites and space rovers, must be
able to detect the occurrence of faults in order to ensure correct operation.
This task is carried out by Fault Detection and Identification (FDI)
components, that are embedded in those systems and are in charge of detecting
faults in an automated and timely manner by reading data from sensors and
triggering predefined alarms. The design of effective FDI components is an
extremely hard problem, also due to the lack of a complete theoretical
foundation, and of precise specification and validation techniques. In this
paper, we present the first formal approach to the design of FDI components for
discrete event systems, both in a synchronous and asynchronous setting. We
propose a logical language for the specification of FDI requirements that
accounts for a wide class of practical cases, and includes novel aspects such
as maximality and trace-diagnosability. The language is equipped with a clear
semantics based on temporal epistemic logic, and is proved to enjoy suitable
properties. We discuss how to validate the requirements and how to verify that
a given FDI component satisfies them. We propose an algorithm for the synthesis
of correct-by-construction FDI components, and report on the applicability of
the design approach on an industrial case-study coming from aerospace.Comment: 33 pages, 20 figure
Recovery on non-ferrous metallic values from metallurgical wastes
WITH the increased tempo of industrial expansion and ever-increasing consumption of common nonferrous metals like Al, Cu, Pb, Zn, Sri in India, conservation, substitution and reclamation from waste products and substandard raw materials are of paramount importance for the country, not only to tide over the present crisis but also in the larger interests of economic growth and self-sufficiency. Self-sufficiency can be attained by developing processes for the utilization of low grade and complex ores,recovery of metals from waste products, like slags, ashes, drosses, apart from conservation of the non-ferrous metals not available in the country, by their judicious use and also by substitution wherever possible
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