Sharif Digital Repository

Business process reengineering (BPR) can help organisations to identify and improve their business processes. A major problem is the high volume of business process datasets with characteristics such as high dimensionality, noise, uncertainty in process datasets and complicated interactions among process variables. Data mining (DM) techniques facilitate the identification and analysis of business processes, and improve their performance by extracting the hidden knowledge in business process datasets. In this paper, we present the application of DM to BPR, based on two novel approaches. By a literature review, the first approach proposes DMbBPR model, mainly focuses on the applications of... 

In this paper, we use simulated annealing heuristics for constructing an intrusion detection system (IDS). The proposed IDS combines the learning ability of simulated annealing heuristics with the approximate reasoning method of fuzzy systems. The use of simulated annealing is an effort to effectively explore the large search space related to intrusion detection problems, and find the optimum set of fuzzy if-then rules. The aim of this paper is to present the capability of simulated annealing based fuzzy system to deal with intrusion detection classification problem as a new real-world application area. Experiments were performed with KDD-Cup99 intrusion detection benchmark data set. © 2008... 

The process of monitoring the events occurring in a computer system or network and analyzing them for sign of intrusions is known as intrusion detection system (IDS). The objective of this paper is to extract fuzzy classification rules for intrusion detection in computer networks. The proposed method is based on the iterative rule learning approach (IRL) to fuzzy rule base system design. The fuzzy rule base is generated in an incremental fashion, in that the evolutionary algorithm optimizes one fuzzy classifier rule at a time. The performance of final fuzzy classification system has been investigated using intrusion detection problem as a high-dimensional classification problem. Results show... 

The security of networked computers plays a strategic role in modern computer systems. This task is so complicated because the determination of normal and abnormal behaviors in computer networks is hard, as the boundaries cannot be well defined. One of the difficulties in such a prediction process is the generation of false alarms in many anomaly based intrusion detection systems. However, fuzzy logic is an important solution to reduce the false alarm rate in determining intrusive activities. This paper proposes a parallel genetic local search algorithm (PAGELS) to generate fuzzy rules capable of detecting intrusive behaviors in computer networks. The system uses the Michigan's approach,... 

In this paper, the use of simulated annealing (SA) metaheuristic for constructing a fuzzy classification system is presented. In several previous investigations, the capability of fuzzy systems to solve different kinds of problems has been demonstrated. Simulated annealing based fuzzy classification system (SAFCS), hybridizes the learning capability of SA metaheuristic with the approximate reasoning method of fuzzy systems. The objective of this paper is to illustrate the ability of SA to develop an accurate fuzzy classifier. The use of SA in classification is an attempt to effectively explore and exploit the large search space usually associated with classification problems, and find the... 

Fuzzy systems have demonstrated their ability to solve different kinds of problems in various applications domains. Currently, there is an increasing interest to augment fuzzy systems with learning and adaptation capabilities. Two of the most successful approaches to hybridize fuzzy systems with learning and adaptation methods have been made in the realm of soft computing. Neural fuzzy systems and genetic fuzzy systems hybridize the approximate reasoning method of fuzzy systems with the learning capabilities of neural networks and evolutionary algorithms. The objective of this paper is to describe a fuzzy genetics-based learning algorithm and discuss its usage to detect intrusion in a... 

In this paper, a novel classification approach is presented. This approach uses fuzzy if-then rules for classification task and employs a hybrid optimization method to improve the accuracy and comprehensibility of obtained outcome. The mentioned optimization method has been formulated by simulated annealing and genetic algorithm. In fact, the genetic operators have been used as perturb functions at the core of simulated annealing heuristic. Results of proposed approach have been compared with several well-known methods such as Naïve Bayes, Support Vector Machine, Decision Tree, k-NN, and GBML, and show that our method performs the classification task as well as other famous algorithms. ©... 

A real-time collision warning system based on TLC1 computation is proposed. Multi-frame lane detection and analysis are adopted to make the TLC calculation algorithm more reliable. The proposed system is robust because of its capability to calculate the TLC in different brightness. The presented system can be used in an intelligent vehicle for warning or lateral control. Experimental results show that the proposed algorithm, calculates TLC acceptably. © 2004 IFAC  

In this paper we investigated the structural properties of the ultra high voltage power transmission network of Iran. We modeled the power grid as a network with 105 nodes and 142 connection links. We found that the Iranian power grid displays a relatively moderate clustering coefficient-much larger than that of corresponding random networks-and small characteristics path length comparable to that of corresponding random networks; i.e. the power grid is a small-world network with exponential degree distribution. Global efficiency was considered as an indicator of grid's performance and the influence of random and intentional nodal failures on the efficiency was investigated. We also studied... 

The capability of fuzzy systems to solve different kinds of problems has been demonstrated in several previous investigations. Genetic fuzzy systems (GFSs) hybridize the approximate reasoning method of fuzzy systems with the learning capability of evolutionary algorithms. The objective of this paper is to design and analysis of various kinds of genetic fuzzy systems to deal with intrusion detection problem as a new real-world application area which is not previously tackled with GFSs. The resulted intrusion detection system would be capable of detecting normal and abnormal behaviors in computer networks. We have presented three kinds of genetic fuzzy systems based on Michigan, Pittsburgh and... 

In this paper we have proposed an evolutionary algorithm to induct fuzzy classification rules. The algorithm uses an ant colony optimization based local searcher to improve the quality of final fuzzy classification system. The proposed algorithm is performed on Intrusion Detection as a high-dimensional classification problem. Results show that the implemented evolutionary ACO-Based algorithm is capable of producing a reliable fuzzy rule based classifier for intrusion detection. © 2007 IEEE  

This paper presents a novel hybrid approach for intrusion detection in computer networks. The proposed approach combines an evolutionary based fuzzy system with an artificial immune system to generate high quality fuzzy classification rules. The performance of final fuzzy classification system has been investigated using the KDD-Cup99 benchmark dataset. The results indicate that in comparison to several traditional techniques, such as C4.5, Naïve Bayes, k-NN and SVM, the proposed hybrid approach achieves better classification accuracies for most of the classes of the intrusion detection classification problem. Therefore, the resulted fuzzy classification rules can be used to produce a... 

Real-time, fuzzy rule-based guidance systems for autonomous vehicles on limited-access highways are investigated. The goal of these systems is to plan trajectories that are safe, while satisfying the driver's requests based on stochastic information about the vehicle's state and the surrounding traffic. This paper presented a new method to implement an automated highway driving behaviour. The main advantage of the suggested system is its well-defined structure. To test the designed system, a simulation tool is implemented. By using the described tool, we can analyse the operation of the implemented decision making system in a simulated highway. Results show an acceptable performance of the... 

The increase in complexity and rate of technological changes in modern software development has led to a demand for systematic methods that raise the abstraction level for system maintenance and regression testing. Model-driven development (MDD) has promised to reduce extra coding efforts in software maintenance activities using traceable change management. The research described in this paper presents a Z-notation-based framework, called delta-based regression testing (DbRT), for formal modeling of regression testing in the context of MDD. The framework proposes to propagate the changes from a software specification to testing artifacts in order to preserve consistency after system... 

According to the increasing desire towards heat transfer rate enhancement with various methods in different industries, this has been an interesting topic of many researchers. The effects of adding TiO2 and Al2O3 nanoparticles to water on heat transfer and fluid flow characteristics are investigated with a semi-analytical method in this study. Two nanofluids flow and heat transfer in a microtube are studied in presence of slip boundary conditions and magnetic fields. The nanoparticles volume fraction, magnetic fields strength, slip parameter and NBT coefficient (the ratio of Brownian to thermophoretic diffusions) effects on the nanoparticle's distribution, velocity profile, temperature... 

Smart environments are complex systems encompassing multitude of devices with complex interconnections and interactions. User must not only be able to figure out the devices’ functionalities, but also understand the architectural and semantic relations between various components. Providing such information leads to better understanding and user satisfaction, if users get the appropriate mental models. One way to train users about such smart environments is Interactive Realistic Virtual Reality based Simulations (IRVRS): multimedia rich collaborative 3D virtual environments. IRVRS also facilitate easy and inexpensive access to population masses, thus they can be used for conducting large... 

Using multiple antennas at the transmit and receive sides of a passive radar brings both the benefits of MIMO radar and passive radar. However one of the obstacles arisen in such configuration is the receive antennas placement in proper positions so that the radar performance is improved. Here we just consider the case of positioning one receiver among multiple illuminators of opportunity. Indeed it is a start for the solution of optimizing the geometry of the multiple receivers in a passive radar  

SbCl3 supported on montmorillonite K-10 is an efficient catalyst for the ring opening of epoxides with aromatic amines under solvent-free conditions and microwave irradiation to give the corresponding b-amino alcohols in high yields with high regioselectivity  

In this paper, we consider an integrated sensing and communication (ISAC) system with wireless power transfer (WPT) where an unmanned aerial vehicle (UAV)-based radar serves a group of energy-limited communication users in addition to its sensing functionality. In this architecture, the radar senses the environment in phase 1 (namely sensing phase) and mean-while, the communications users (nodes) harvest and store the energy from the radar transmit signal. The stored energy is then used for information transmission from the nodes to UAV in phase 2, i.e., uplink phase. Performance of the radar system depends on the transmit signal as well as the receive filter; the energy of the transmit...