53 research outputs found
An Intelligent Genetic Algorithm for Mining Classification Rules in Large Datasets
Genetic algorithm is a popular classification algorithm which creates a random population of candidate solutions and makes them to evolve into a suitable accurate solution for a given problem by processing them iteratively for several generations. During each generation the training data set is accessed by the genetic algorithm only for the population member's fitness calculation and no other extra knowledge about the problem domain is extracted from the training data set. Even the domain knowledge stored in the chromosome code of the population may be lost in the future generations due to genetic operations. All the genetic operations like crossover and mutation are probability based and they do not depend upon the domain knowledge. This phenomenon makes the genetic algorithm to converge slowly. This paper proposes a genetic algorithm which tries to gain maximum knowledge in between the generations and store them in the form of knowledge chromosomes. The gained knowledge is used to make predictions about the search space and to guide the search process to an area with potential solutions in the subsequent generations. This makes the genetic algorithm to converge quickly which in turn reduces the learning cost. The experiments show that the run time is reduced considerably when compared with the state-of-the-art evolutionary algorithm
Bronchial Colonisation and Inflammation in patients with clinically stable Bronchiectasis- Microbiological pattern and Risk factors
INTRODUCTION:
Bronchiectasis is a chronic pulmonary disease characterized by an abnormal irreversible dilatation of one or more bronchi often with wall thickening. The current view of the pathogenesis of Bronchiectasis considers initial colonization of the lower respiratory tract by different microorganisms as the first step leading to inflammatory response characterized by neutrophil migration within the airways and secondary secretion of variety of tissue
damaging oxidants and enzymes such as neutrophil elastase, myeloperoxidase and cytokines [interleukins]. Persistence of microorganisms in the airways because of impairment in mucus clearance may lead to a vicious circle of events
characterized by chronic bacterial colonization, persistent inflammatory reaction and progressive tissue damage and morbidity life.
In order to evaluate the Bacterial colonisation and level of bronchial inflammation in relation with bacterial colonisation; we did bronchoalveolor lavage of patients admitted with HRCT Chest[taken within 3 months] evidence
of bronchiectasis and fulfill with inclusion criteria of study. The obtained sample was divided into 3parts-One part was sent to microbiology for bacterial culture, second one was sent to pathology for Total and Differential cell count
estimation and third part was centrifuged and stored in 2 to 8'C temperature for IL-8 estimation.
METHOD OF STUDY:
Continuous prospective study.
Study Period:
This study was done for a period of 7 months from
February 2014 to August 2014.
Study Population: 90 patients.
Study Centre:
This study was done in Rajiv Gandhi Govt General Hospital,
Madras Medical College, Chennai-03.
INCLUSION CRITERIA:
1. Patients admitted with HRCT Chest diagnosis of Bronchiectasis {non cystic fibrosis},
2. Age >14 years,
3. SpO2> 90% in Room air.
EXCLUSION CRITERIA:
1. Patients with complications like Hemoptysis, Lung abscess and Amyloidosis.
2. Patients with Cystic fibrosis.
3. SPO2<90% in room air.
4. Patients with prior Hospitalisation within 2 months and had antibiotic within 4 weeks.
5. Patients with cardiac illness and Recent Myocardial infection 6. Patients with Renal failure.
RESULTS:
Among 90 study population analysis showed females were 58% and males were 42%. Cylindrical bronchiectasis 53%, followed by cystic bronchiectasis36% in predominance: and positive culture growth rate for sputum samples were 68% and BAL samples were 77%. The micro organisms isolated predominantly were H.influenza, Pseudomonas, Streptococci, Staphylocci and etc. Regarding airway inflammation, the total counts of BAL
fluid were increased in all the patients with slight higher level in positive culture growth patients with slight Neutrophilic predominance. [90-210X10*3 cells in range and 120x10*3 cells in median]. The IL-8 measured showed increased level in all three groups comparing control groups indicating earlier establishment of inflammation in bronchiectasis. [81-835pg/dl in range and 556pg/dl in median].
CONCLUSION:
A. The risk factors identified for increased colonisation were;
1.long duration of symptoms,
2.Cystic and Varicose bronchiectasis,
3. Presence of alcoholism and smoking.
B. Sputum culture is non invasive, alternative to broncho alveolar lavage fluid culture
Experimental Investigation of Catalytic Surface Reaction for Different Metal Surfaces
The use of a catalytic surface to enhance chemical reaction rates is a well established and common practice. However, its use in combustion devices for enhancing combustion reaction is somewhat less common and more recent. Catalytic combustors, because of their inherent ability to operate at very lean air fuel mixtures, can maintain a relatively low combustion temperature and hence reduce the formation of NOx significantly. Further the catalytic coating on the combustion chamber walls enhances the combustion process by increased rate of pre-flame reactions. This provides a basis for catalytic combustion in lean burn engine. A considerable amount of effort has been devoted in the present work to this experimental study and compares different catalyst reaction performance.A cylindrical chamber is fabricated and air-fuel mixture is passed through the chamber. A metal tube coated with the catalyst is placed inside the control volume and it is heated by an electric heater. The air-fuel mixture undergoes pre-flame combustion reaction and as a result of this, the miniature temperature increases. Various catalytic surfaces like mild steel, Nickel, Chromium and copper were tested. The activation temperatures of these catalytic surfaces were obtained from this experimental work. Keywords: catalytic reaction, LPG, activation energy, catalytic coatin
Heat release rate estimation in laminar premixed flames using laser-induced fluorescence of CH2O and H-atom
The present work demonstrates the feasibility of heat release rate imaging using the laser-induced fluorescence (LIF) of atomic hydrogen (H-atom) and formaldehyde (CH2O) in laminar premixed flames. The product of H-atom LIF and CH2O LIF signals is evaluated on a pixel-by-pixel basis and is compared with that of the OH × CH2O technique. These results for equivalence ratio ranging from 0.8 to 1.1 are compared with computations of one-dimensional freely-propagating flames. The performance of these markers is studied based on the following two aspects: the spatial accuracy of the local heat release rate and the trend in the total heat release rate with equivalence ratio. The measured trend in the spatial distribution of radicals and the deduced heat release rate agree well with the computational values. The variation in the spatially integrated heat release rate as a function of equivalence ratio is also investigated. The results suggest that the trend in the variation of the integrated heat release rate and the spatial location of heat release rate can be evaluated by either of these markers. The OH-based marker showed certain sensitivity to the chemical mechanism as compared to the H-atom based marker. Both the OH-based and H-atom based techniques provide close estimates of heat release rate. The OH based technique has practical advantage when compared to the H-atom based method, primarily due to the fact that the H-atom LIF is a two-photon process
Minig rules of concept drift using genetic algorithm
In a database the data concepts changes over time and this phenomenon is called as
concept drift. Rules of concept drift describe how the concept changes and sometimes
they are interesting and mining those rules becomes more important. CDR tree algorithm
is currently used to identify the rules of concept drift. Building a CDR tree becomes a
complex process when the domain values of the attributes get increased. Genetic Algorithms
are traditionally used for data mining tasks. In this paper, a Genetic Algorithm
based approach is proposed for mining the rules of concept drift, which makes the mining
task simpler and accurate when compared with the CDR-tree algorithm
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