Masoud Mohammadian

RFID Technology and Crowded Event Management

Efficient management of large crowded events is always a challenge. Successful management of such events largely depends on the use of technologies. There are many business cases where the use of latest technology can vastly improve their management. In recent times, many types of identification and sensor devices, including RFID tags, have been developed. Such technologies, combined with appropriate backend database systems, can be used to improve the crowd and event management. Hajj, an annual pilgrimage to Mecca, is a very large and unique gathering, which attracts millions of pilgrims for two or more weeks. Despite tremendous advancement of technology and its availability, Hajj continues to be managed manually. There are many aspects of Hajj which are worth researching. The aim of this paper is to identify appropriate technologies which can be used to improve the management of large gatherings such as those of Hajj and Kumbh gatherings in India.

An adaptive hierarchical fuzzy logic system for modelling of financial systems

In this paper an intelligent hierarchical fuzzy logic system using genetic algorithms for the prediction and modelling of interest rates in Australia is developed. The proposed system uses a hierarchical fuzzy logic system in which a genetic algorithm is used as a training method for learning the fuzzy rules knowledge bases that are used for prediction of interest rates in Australia. A hierarchical fuzzy logic system is developed to model and predict three-month (quarterly) interest rate fluctuations. The system is further trained to model and predict interest rates for six-month and one-year periods. The proposed system is developed with first two, three, then four and finally five hierarchical knowledge bases to model and predict interest rates. A novel architecture called a feed forward fuzzy logic system using fuzzy logic and genetic algorithms is also developed to predict interest rates. A back-propagation hierarchical neural network system is also developed to predict interest rates for three-month, six-month and one-year periods. The results obtained from these two systems are then compared with the hierarchical fuzzy logic system results and conclusions are drown on the accuracy of all systems for prediction of interest rates in Australia. Copyright

Data classification process for security and privacy based on a fuzzy logic classifier

Data security and privacy are important issues in the success of a financial business operation. Implementing and applying policies related to data security and privacy, therefore, has become one of the core and important activities for large organisations. The data classification process can be laborious in large organisations with significant data to evaluate and categorise. By using a data classification process organisations can identify and apply appropriate policy and security settings such as private access control and encryption requirements. This paper explores the use of fuzzy logic in classification of data in organisations based on organisational data security and privacy needs and government policies imposed on data.

Multi-Agents Systems for Intelligent Control of Traffic Signals

In this paper the application of a multiagent system for controlling a set of traffic signals is considered. A fuzzy logic control scheme to regulate the flow of traffic approaching a set of three intersections is presented. The signal timing parameters, green phase splits and offset, are adjusted online based on the actual traffic approaching each intersection. An adaptive fuzzy logic traffic controller (FLTC) is used to adjust the green phase splits of the north-south and east-west approaches of each traffic signal. Each intersection is coordinated with its adjacent intersections by a multiagent system. The multiagent system uses a fuzzy rule based system for its decision making to coordinate all three intersections simultaneously. The effectiveness of the proposed control strategy is established through simulations.

Network Security Evaluation Method via Attack Graphs and Fuzzy Cognitive Maps

When presented with an attack graph, network administrator may raise question on how to harden the network. To defend his network, network administrator should be supplied with list of all attack paths that can compromise the network. With this list, he can decide which paths are worth paying attention to and defending against. In the event of limited resources, network administrator may only be interested in certain critical paths which cause worst network attack. Attack graph alone is not always helpful on its own and needs additional work for this purpose. In this paper we present the use of a Fuzzy Cognitive Map which is converted from attack graph with genetic algorithm to find attack scenarios causing worst impact on network security. The identified scenarios can then help network administrator to mitigate risks associated with the attack scenarios and improve his network security.

Development of a Fuzzy-based Multi-agent System for E-commerce Settings

Abstract In this paper we present our experience in developing a fuzzy-logic based multi-agent e-commerce system capable of achieving a mutually beneficial deal for the seller and buyer using a negotiation process. We use fuzzy logic to assist users to express their preferences about a product in fuzzy terms such as low, medium and high. Our system evaluates offers based on a fuzzy utility function and feeds utility scores to a fuzzy inference system which then computes its next counter offer. Our paper presents issues involved in the development of a multi-agent system for e-commerce settings using the JADE platform - a modern agent development environment. In this paper our focus is on implementing agents of different types/roles engaged in activities usually encountered with buying and selling in an e-commerce environment. Our concluding remarks and future research are presented.

A Framework for Teaching Mobile and Wireless Technology

Introduction Teaching the use of technology or the technology itself comes with a certain amount of inherent risks and drawbacks. Most technology is upgraded every 18 to 24 months. During any year the technology may have, patches, service packs, add-ons, etc ... New technology standards and related standards that affect the use of technology are being implemented and approved each year. In some technology areas new vendors are entering the market while some are leaving the market, and others are being amalgamated. Each of these modifications, changes, and standards, can slightly too dynamically affect the technology. These modifications and changes effect the way the technology works, can be used, is used, and its role as a business tool. The modifications potentially affect the way interactions between the human and the technology are dealt with, interactions between existing technologies, those begin used and considering to be used, and the user of the technology. In a teaching environment this means that the semester changes to the subject material might require some minor adjustments to the possibility that a massive overhaul of the teaching material is required. One technology area that is dynamically changing is mobile and wireless technology. The teaching of wireless and mobile technology brings about some inherent challenges and risks. This paper presents a framework for the teaching of mobile and wireless technology. The framework is based on the development of a subject where the teaching of the technology and feedback from a workshop presented at the International Conference on Intelligent Agents, Web Technology and Internet Commerce in Vienna, Austria February 2003. The framework is at a high level that will need to be reviewed for revisions on a periodic basis. The framework takes the perspective of the stakeholders in todays organizations that will have to and do deal with this technology on a day to day basis. These stakeholders require not only an understanding of the terminology, but how it is being used by modern organizations, and the potential to which mobile and wireless technology might be applied in an organizational and business context. Teaching Environment The teaching of mobile and wireless technology requires an environment that few universities have or are willing to commit to. This is understandable with the number of ongoing changes that continues to drive the mobile and wireless industry and the expense that is required in order to be technologically up to date in this area. However, it is not understandable from the market potential for the future skills and knowledge needed by many employees. Many universities have implemented wireless systems on their campuses providing an extensible service to the educational activities offered to students (Monash, 2002; UniWide, 2003; UTORcwn, 2003). These implementations are directed at teaching supporting not at the teaching of mobile and wireless technology. The objective of the development of a teaching framework for mobile and wireless technology is to first teach from an organizational perspective, particularly business organizations, and then from a technological perspective. The teaching needs to include the concepts and issues relating to the understanding of the use of mobile and wireless technology. The framework needs to consider how to react, within a reasonable timeframe, to the upgrades, patches, service packs, add-ons, standards, and business issues as they are discovered. The framework needs to provide a way to identify when each of these occurs and to be able to evaluate the potential affect that each could possible have on the business operations. A flow on affect is the ability to provide up to date information that would be integrated into the teaching material and the delivery method. For example an organization has recently installed a Wi-Fi local area network (WLAN) based on the 802. …

Rule based fuzzy cognitive maps and natural language processing in machine ethics

Purpose The developing academic field of machine ethics seeks to make artificial agents safer as they become more pervasive throughout society. In contrast to computer ethics, machine ethics is concerned with the behavior of machines toward human users and other machines. This study aims to use an action-based ethical theory founded on the combinational aspects of deontological and teleological theories of ethics in the construction of an artificial moral agent (AMA). Design/methodology/approach The decision results derived by the AMA are acquired via fuzzy logic interpretation of the relative values of the steady-state simulations of the corresponding rule-based fuzzy cognitive map (RBFCM). Findings Through the use of RBFCMs, the following paper illustrates the possibility of incorporating ethical components into machines, where latent semantic analysis (LSA) and RBFCMs can be used to model dynamic and complex situations, and to provide abilities in acquiring causal knowledge. Research limitations/implications This approach is especially appropriate for data-poor and uncertain situations common in ethics. Nonetheless, to ensure that a machine with an ethical component can function autonomously in the world, research in artificial intelligence will need to further investigate the representation and determination of ethical principles, the incorporation of these ethical principles into a system’s decision procedure, ethical decision-making with incomplete and uncertain knowledge, the explanation for decisions made using ethical principles and the evaluation of systems that act based upon ethical principles. Practical implications To date, the conducted research has contributed to a theoretical foundation for machine ethics through exploration of the rationale and the feasibility of adding an ethical dimension to machines. Further, the constructed AMA illustrates the possibility of utilizing an action-based ethical theory that provides guidance in ethical decision-making according to the precepts of its respective duties. The use of LSA illustrates their powerful capabilities in understanding text and their potential application as information retrieval systems in AMAs. The use of cognitive maps provides an approach and a decision procedure for resolving conflicts between different duties. Originality/value This paper suggests that cognitive maps could be used in AMAs as tools for meta-analysis, where comparisons regarding multiple ethical principles and duties can be examined and considered. With cognitive mapping, complex and abstract variables that cannot easily be measured but are important to decision-making can be modeled. This approach is especially appropriate for data-poor and uncertain situations common in ethics.

An Adaptive Intelligent Fuzzy Logic Classifier for Data Security and Privacy in Large Databases

Proper data protection facilities and services are very important in organizations. Data security and privacy issues needs to be considered and applied in organizations to provide a successful business operation. Large organizations have adapted the implementation and application of policies related to data security and privacy as one of their core and important activities. Data classification process allows financial organizations to organize their data according to their needs. However data classification is a laborious activity with significant data to evaluate and categorize. Data classification process is needed for organizations to identify and apply appropriate policy and security settings such as private access control and encryption requirements. In this paper a fuzzy logic based classification is used to classify data and suggests a method that can determine requirements for data security and privacy in organizations based on organizational needs and government policies imposed on data. A new method for data access authorization is also developed based on fuzzy logic, which will assist in preserving privacy and security of data. A Case study is considered to present the effectiveness of the proposed methods.

Fuzzy utility and inference system for bilateral negotiation

In this paper the development of a fuzzy logic based software agent for bilateral e-negotiation is considered. The developed fuzzy logic based intelligent agent is applied to a laptop purchasing model which allows users that have limited knowledge on different range of laptops available, to define the different attributes of laptop in human language such as low, medium or high price, speed, screen size and other attributes. The intelligent agent then performs an automatic evaluation on how close an item matches user preferences using fuzzy logic based decision-making built into the intelligent agent. We develop tactic for the intelligent agent so that it can change its decision making for example how much the agent should increase counter offer in its negotiation, depending on laptop utility score, offer price of the laptop and remaining negotiation time. Simulation results show that the buyer agent concedes more (i.e. raises its offer price) if laptop attributes being negotiated meets its client preferences better and concedes less if otherwise.