Association Rules Mining Based Clinical Observations

Healthcare institutes enrich the repository of patients' disease related information in an increasing manner which could have been more useful by carrying out relational analysis. Data mining algorithms are proven to be quite useful in exploring useful correlations from larger data repositories. In this paper we have implemented Association Rules mining based a novel idea for finding co-occurrences of diseases carried by a patient using the healthcare repository. We have developed a system-prototype for Clinical State Correlation Prediction (CSCP) which extracts data from patients' healthcare database, transforms the OLTP data into a Data Warehouse by generating association rules. The CSCP system helps reveal relations among the diseases. The CSCP system predicts the correlation(s) among primary disease (the disease for which the patient visits the doctor) and secondary disease/s (which is/are other associated disease/s carried by the same patient having the primary disease).Comment: 5 pages, MEDINFO 2010, C. Safran et al. (Eds.), IOS Pres

A Mathematical Model of Avian Influenza for Poultry Farm and its Stability Analysis

This paper aims to estimate the basic reproduction number for Avian Influenza outbreak in local and global poultry industries. In this concern, we apply the SEIAVR compartmental model which is developed based on the well-known SEIR model. The SEIAVR model provides the mathematical formulations of the basic reproduction number, final size relationship and a relationship between these two phenomena. The developed model Equations are solved numerically with the help of Range-Kutta method and the values of initial parameters are taken from the several literatures and reports. The calculated result of basic reproduction number shows that it is locally and globally stable if it is less than and greater than one at disease free equilibrium and at endemic equilibrium, respectively. Furthermore, we have compared among the calculated susceptive, expose, infective, removal, virus and asymptotic compartments where infection rate and expose period are observed very sensitive compared to other parameters. In addition, the model result of infective is compared with the field data and other’s model where the present model shows good performance against the field data

An Implementation of Intrusion Detection System Using Genetic Algorithm

Nowadays it is very important to maintain a high level security to ensure safe and trusted communication of information between various organizations. But secured data communication over internet and any other network is always under threat of intrusions and misuses. So Intrusion Detection Systems have become a needful component in terms of computer and network security. There are various approaches being utilized in intrusion detections, but unfortunately any of the systems so far is not completely flawless. So, the quest of betterment continues. In this progression, here we present an Intrusion Detection System (IDS), by applying genetic algorithm (GA) to efficiently detect various types of network intrusions. Parameters and evolution processes for GA are discussed in details and implemented. This approach uses evolution theory to information evolution in order to filter the traffic data and thus reduce the complexity. To implement and measure the performance of our system we used the KDD99 benchmark dataset and obtained reasonable detection rate

ONLY A SINGLE PROGRAMME IN RADIO CAN GIVE A FEELING OF BEING A MEMBER OF THE WORLD

ABSTRAC

Bonding mechanisms in the application of thermal barrier coatings to turbine blades.

Thermal barrier coatings (TBC's) are used to protect gas turbine blades from environmental degradation as well as to increase thermodynamic efficiency. Most TBC systems consist of a ceramic thermal barrier coating such as partially stabilized zirconia adhering to an oxidation resistant bond coat, which in turn is bonded to the turbine blade. This is required since partially stabilised zirconia will not readily bond to superalloys. However, the TBC can fail in service either by bond coat oxidation or thermal expansion mismatch between the bond coat and the TBC. A systematic literature survey has shown that the superalloy substrate material, type of bond coat selected, with the coating application techniques i.e. thermal spray or Electron Beam PVD (EBPVD) plays a fundamental role in determining the failure mechanisms involved. This program of work is concerned with the development of coatings with enhanced temperature capabilities for turbine blade applications by understanding the fundamental mechanisms responsible for adhesion between the nickel based turbine blade and zirconia based TBC. An understanding of the bonding mechanisms will allow the design of advanced coating systems with increased operating temperatures. This program of work introduces the Glow Discharge Optical Emission Spectroscopy (GDOES) technique, an atomic emission technique used for both bulk and depth profile analysis, which had not previously been applied to TBC's, and SEM and TEM in order to enhance understanding of failure modes in TBC systems and adhesion process. The results obtained from the studies indicate that the GDOES technique can be applied to depth profile bond coats and exposed TBC systems both qualitatively and semi-quantitatively. GDOES has been able to detect elements such as silicon and sodium that are in the ppm levels which are difficult / impossible to detect using EDX systems, and are very important in coating developments. In addition, as a preliminary guide GDOES has shown Ti diffusion from the superalloy substrate into the bond coat to be detrimental towards coating adhesion on most of the systems studied.The results of SEM and cross-sectional TEM on selected bond coat systems has shown the low cost Pt bond coat microstructure system to consist of TBC, Al2O3 bond coat and CMSX-4 superalloy substrate in all cases. The intermediate layer between the TBC and bond coat consists of Al2O3 which has been identified as responsible for maintaining the adhesion. Also identified is evidence of Ti segregation at the Al2O3 / bond coat interface, known to lead to decohesion in coatings. Failure in the low cost Pt bond coat system has been identified as the decohesion between the interfacial layer of Al2O3 and the bond coat.The program of studies has enabled failure mechanisms and factors affecting bonding to be identified in low cost Pt bond coat systems, so that in future better coating systems with enhanced properties can be designed This should also ensure that improved reliability in engines and increased service life of turbine blades be achieved

Pattern classification of cotton yarn neps

In this study, two types of cotton yarn neps, viz. seed coat and fibrous neps, have been classified by means of two standard classifiers, namely support vector machine and probabilistic neural network using the features extracted from the images of neps. At first, the region of interest is located in the captured images using k-means clustering algorithm, from which six features are extracted. These extracted features are used as dataset (both training and testing) for classifiers. A K-fold cross validation technique has been applied to assess the performance of the two classifiers. The results show that the neps classification accomplished by means of image recognition through these classifiers achieves nearly 96-97% accuracy for the test data set. Experimental results show that the required time for training probabilistic neural network is significantly less as compared to that of support vector machine

Impact of teachers’ professional development on school improvement—an analysis at Bangladesh standpoint

This study seeks to describe the teachers’ professional development activities in Bangladesh and explores the hypotheses about the relationship between teachers’ traditional professional development activities and school improvement. Data from a representative sample of City secondary schools from Bangladesh (n = 127) were gathered through questionnaires from 127 principals and 694 teachers. Hierarchical multiple regression analysis was used in this research. This study found significant impacts of some of teachers’ professional development activities on school improvement. Also found that the maximum school improvement can be achieved if schools put more emphasis on teachers’ collaboration, in-service training and classroom observation and less emphasis on individual action enquiry. The findings of this study provide important information for the policy makers, educational managers and especially for the headmasters and teachers concerned with the improvement of teachers’ quality in secondary schools of Bangladesh. This study adopts a concurrent approach of data collection and analysis

Premade Nanoparticle Films for the Synthesis of Vertically Aligned Carbon Nanotubes

Carbon nanotubes (CNTs) offer unique properties that have the potential to address multiple issues in industry and material sciences. Although many synthesis methods have been developed, it remains difficult to control CNT characteristics. Here, with the goal of achieving such control, we report a bottom-up process for CNT synthesis in which monolayers of premade aluminum oxide (Al2O3) and iron oxide (Fe3O4) nanoparticles were anchored on a flat silicon oxide (SiO2) substrate. The nanoparticle dispersion and monolayer assembly of the oleic-acid-stabilized Al2O3 nanoparticles were achieved using 11-phosphonoundecanoic acid as a bifunctional linker, with the phosphonate group binding to the SiO2 substrate and the terminal carboxylate group binding to the nanoparticles. Subsequently, an Fe3O4 monolayer was formed over the Al2O3 layer using the same approach. The assembled Al2O3 and Fe3O4 nanoparticle monolayers acted as a catalyst support and catalyst, respectively, for the growth of vertically aligned CNTs. The CNTs were successfully synthesized using a conventional atmospheric pressure-chemical vapor deposition method with acetylene as the carbon precursor. Thus, these nanoparticle films provide a facile and inexpensive approach for producing homogenous CNTs

Quality of Education in Bangladesh: A Survey on Private Business Schools

A survey was conducted to study the customers’ (students’) evaluation of private higher education sector in Bangladesh with special reference to the quality of business education. The sample was taken from business schools on a random basis from seven private universities of Bangladesh. The respondents (students) were asked to evaluate the quality of business education at private universities in light of sixty six variables and they ranked the attributes in a seven-point Likert’s summated scale. The result of this study shows that faculty credentials, intake (student) selection system, assessment system, campus facilities, research environment, leadership of university, market orientation, and corporate attachment are associated with quality of business education. Finally, the study suggests that the policymakers and administrators should address the identified factors for ensuring quality in their business schools. Keywords: Intake, Assessment, Leadership, Faculty, Market orientation