The paper describes a symmetric encryption algorithm based on bit permutations and using an iterative process combined with a chaotic function. The main advantages of such a cryptosystem is its ability to encrypt securely bit sequences and assuring confusion, diffusion and indistinguishability properties in the cipher. The algorithm is applied on the image encryption where the plain-image is vi...

The binary steering process is a heuristic designed to intervene between consecutive steps of a nonbinary iterative image reconstruction algorithm in order to gradually steer the iterates towards a binary solution. We present computational results which show that a strongly overrelaxed simultaneous nonbinary iterative algorithm performs in our experiments better than a strongly underrelaxed seq...

The advantages of FCM algorithm are that it is mainly applied in point data cluster and can't directly process relational data, for which the paper proposes a clustering algorithm in data mining based on web log. Firstly, the paper improves FCM algorithm which makes it can process relational data, and makes robustness improvement on the algorithm. Then, the traditional FCM algorithm needs to de...

Supervised clustering is a data mining technique that assigns a set of data to predefined classes by analyzing dataset attributes. It is considered as an important technique for information retrieval, management, and mining in information systems. Since customer satisfaction is the main goal of organizations in modern society, to meet the requirements, 137 call center of Tehran city council is ...

One of the most important data mining problems is discovery of sequential patterns. Sequential pattern mining consists in discovering all frequently occurring subsequences in a collection of data sequences. This paper discusses several issues concerning possible extensions to traditional database management systems required to support sequential pattern discovery: a sequential pattern query lan...

There is an increase in the demand for data mining applications on the web. With the increase in the size of data sets there is also a demand for scalable generic solutions. Scalability and generic data mining models can be provided with the use of distributed computing. In this paper we propose the use of a multilayered framework for a distributed data mining system. A multi-layered architectu...

Sequential access pattern mining discovers interesting and frequent user access patterns from web logs. Most of the previous studies have adopted Apriori-like sequential pattern mining techniques, which faced the problem on requiring expensive multiple scans of databases. More recent algorithms that are based on the Web Access Pattern tree (or WAP-tree) can achieve an order of magnitude faster ...

Proposing efficient techniques for discovery of useful information and valuable knowledge from very large databases and data warehouses has attracted the attention of many researchers in the field of data mining. The wellknown Association Rule Mining (ARM) algorithm, Apriori, searches for frequent itemsets (i.e., set of items with an acceptable support) by scanning the whole database repeatedly...

Abstract Process mining, which aims to mine a high-quality process model from event log, provides powerful tool support the design, enactment, management, and analysis of operational business processes. However, task is not easy because algorithm needs discover various complex structures, handle noisy incomplete logs balance multiple performance indicators. In this paper, novel (called PSOMiner...