cardiovascular diseases are one of the most common diseases that cause a large number of deaths each year. coronary artery disease (cad) is the most common type of these diseases worldwide and is the main reason of heart attacks. thus early diagnosis of cad is very essential and is an important field of medical studies. many methods are used to diagnose cad so far. these methods reduce cost and...

background: breast cancer is currently one of the leading causes of death among women worldwide. the diagnosis and separation of cancerous tumors in mammographic images require accuracy, experience and time, and it has always posed itself as a major challenge to the radiologists and physicians. objective: this paper proposes a new algorithm which draws on discrete wavelet transform and adaptive...

One of the main features of High Throughput Computing systems is the availability of high power processing resources. Cloud Computing systems can offer these features through concepts like Pay-Per-Use and Quality of Service (QoS) over the Internet. Many applications in Cloud computing are represented by workflows. Quality of Service is one of the most important challenges in the context of sche...

In recent years, production of text documents has seen an exponential growth, which is the reason why their proper classification seems necessary for better access. One of the main problems of classifying text documents is working in high-dimensional feature space. Feature Selection (FS) is one of the ways to reduce the number of text attributes. So, working with a great bulk of the feature spa...

The main aim is to generate a frequent itemset. Big Data analytics is the process of examining big data to uncover hidden patterns. Association Rule Learning is a technique which is used to implement big data. It finds the frequent items in the dataset. Frequent itemsets are those items which occur frequently in the database. To find the frequent itemsets, we are using three algorithms APRIORI ...

We present a new fast algorithm for calculating the growth rate of complexity for regular languages. Using this algorithm we develop a space and time efficient method to approximate growth rates of complexity of arbitrary power-free languages over finite alphabets. Through extensive computer-assisted studieswe sufficiently improve all known upper bounds for growth rates of such languages, obtai...

This paper presents a Genetic Algorithm Fuzzy Data Envelopment Analysis (GA-FDEA) model that caters for optimal selecting of economic indicators for the measurement of relative productivity and performance of financial institutions. Imprecise or uncertain data of financial institutions due to varying monetary policies and market risk were retrieved from Nigeria Stock Exchange Commission and eva...

Recently there has been a growing interest in designing differentially private data mining algorithms. A variety of algorithms have been proposed for mining frequent itemsets. Frequent itemset mining (FIM) is one of the most fundamental problems in data mining. It has practical importance in a wide range of application areas such as decision support, web usage mining, bioinformatics, etc. In th...

evolutionary algorithms are some of the most crucial random approaches tosolve the problems, but sometimes generate low quality solutions. on the otherhand, learning automata are adaptive decision-making devices, operating onunknown random environments, so it seems that if evolutionary and learningautomaton based algorithms are operated simultaneously, the quality of results willincrease sharpl...