Security protection design for deception and real system regimes: A model and analysis

In this paper, we model a possible deception system with the explicit purpose of enticing unauthorized users and restricting their access to the real system. The proposed model represents a system designer’s defensive actions against intruders in a way that maximizes the difference between the intruders’ cost and the system designer’s cost of system protection. Under the assumption of a dual entity system, the proposed model shows that intruders differ in behavior depending on the system’s vulnerability at the time of intrusion as well as depending on their own economic incentives. The optimal results of the proposed model provide the system designer with insights on how to configure the level of protection for the two systems.     

A general approach to fuzzy concepts

The paper proposes a flexible way to build concepts within fuzzy logic and set theory. The framework is general enough to capture some important particular cases, with their own independent interpretations, like “antitone” or “isotone” concepts constructed from fuzzy binary relations, but also to allow the two universes (of objects and attributes) to be equipped each with its own truth structure. Perhaps the most important feature of our approach is that we do not commit ourselves to any kind of logical connector, covering thus the case of a possibly non‐commutative conjunction too. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

A partition-based approach towards constructing Galois (concept) lattices

Galois lattices and formal concept analysis of binary relations have proved useful in the resolution of many problems of theoretical or practical interest. Recent studies of practical applications in data mining and software engineering have put the emphasis on the need for both efficient and flexible algorithms to construct the lattice. Our paper presents a novel approach for lattice construction based on the apposition of binary relation fragments. We extend the existing theory to a complete characterization of the global Galois (concept) lattice as a substructure of the direct product of the lattices related to fragments. The structural properties underlie a procedure for extracting the global lattice from the direct product, which is the basis for a full-scale lattice construction algorithm implementing a divide-and-conquer strategy. The paper provides a complexity analysis of the algorithm together with some results about its practical performance and describes a class of binary relations for which the algorithm outperforms the most efficient lattice-constructing methods.     

A fuzzy approach for selecting project membership to achieve cognitive style goals

Decision makers select employees for a project to match a particular set of goals pertaining to the multiple criteria mix of skills and competencies needed. Cognitive style influences how a person gathers and evaluates information and consequently, provides skills and competencies toward problem solving. The proposed fuzzy set-based model facilitates the manager’s selection of employees who meet the project goal(s) for the preferred cognitive style. The paper presents background information on cognitive styles and fuzzy logic with an algorithm developed based on belief in the fuzzy probability of a cognitive style fitting a defined goal. An application is presented with analysis and conclusions stated.     

A model of interim information sharing under incomplete information

We propose a two-person game-theoretical model to study information sharing decisions at an interim stage when information is incomplete. The two agents have pieces of private information about the state of nature, and that information is improved by combining the pieces. Agents are both senders and receivers of information. There is an institutional arrangement that fixes a transfer of wealth from an agent who lies about her private information. In our model, we show that (1) there is a positive relation between information revelation and the amount of the transfers, and (2) information revelation has a collective action structure, in particular, the incentives of an agent to reveal decrease with respect to the amount of information disclosed by the other.     

A novel cognitive transformation algorithm based on Gaussian cloud model and its application in image segmentation

The representation and processing of uncertain concepts are key issue for both the study of artificial intelligence with uncertainty and human knowledge processing. The intension and extension of a concept can be transformed automatically in the human cognition process, while it is difficult for computers. A Gaussian cloud model (GCM) is used to realize the cognitive transformation between intension and extension of a concept through computer algorithms, including forward Gaussian cloud transformation (FGCT) algorithms and backward Gaussian cloud transformation (BGCT) algorithms. A FGCT algorithm can transform a concept’s intension into extension, and a BGCT algorithm can implement the cognitive transformation from a concept’s extension to intension. In this paper, the authors perform a thorough analysis on the existing BGCT algorithms firstly, and find that these BGCT algorithms have some drawbacks. They cannot obtain the stable intension of a concept sometimes. For this reason, a new backward Gaussian cloud cognitive transformation algorithm based on sample division is proposed. The effectiveness and convergence of the proposed method is analyzed in detail, and some comparison experiments on obtaining the concept’s intension and applications to image segmentation are conducted to evaluate this method. The results show the stability and performance of our method.     

A numerical approach to solve the model of an electromechanical system

In this paper, the model of an electromechanical system, which is a system of linear differential equations, is studied. Haar wavelet collocation method (HWCM) is applied for finding the approximate solution of the model. HWCM reduces the system of the model into a matrix‐vector form that contains the unknown Haar coefficients, and these coefficients are easily calculated. To demonstrate the validity and applicability of HWCM, numerical solutions of the system for different parameter values in the system are presented. The obtained results demonstrate the efficiency and accuracy of the method. All of the computations are performed via a program written in Mathematica.     

A method based on PSO and granular computing of linguistic information to solve group decision making problems defined in heterogeneous contexts

Group decision making is a type of decision problem in which multiple experts acting collectively, analyze problems, evaluate alternatives, and select a solution from a collection of alternatives. As the natural language is the standard representation of those concepts that humans use for communication, it seems natural that they use words (linguistic terms) instead of numerical values to provide their opinions. However, while linguistic information is readily available, it is not operational and thus it has to be made usable though expressing it in terms of information granules. To do so, Granular Computing, which has emerged as a unified and coherent framework of designing, processing, and interpretation of information granules, can be used. The aim of this paper is to present an information granulation of the linguistic information used in group decision making problems defined in heterogeneous contexts, i.e., where the experts have associated importance degrees reflecting their ability to handle the problem. The granulation of the linguistic terms is formulated as an optimization problem, solved by using the particle swarm optimization, in which a performance index is maximized by a suitable mapping of the linguistic terms on information granules formalized as sets. This performance index is expressed as a weighted aggregation of the individual consistency achieved by each expert.     

From fractions to proportional reasoning: a cognitive schemes of operation approach

Four seventh grade students participated in a constructivist teaching experiment in which manipulatives within a computer microworld were used to solve fractional reasoning tasks followed by tasks that involve concepts of rate, ratio and proportion. Through a retrospective analysis of video tapes, their thinking processes were analyzed from the perspective of the types of cognitive schemes of operation used as they engaged in the given problem situations. One result of the study indicates that the modifications of the students’ available schemes of operation when solving the fractional reasoning tasks formed a basis for the cognitive schemes of operation used in their solutions of tasks involving proportionality.     

Discriminant versus rough sets approach to vague data analysis

This paper presents a comparative study of the use of two different methods of data analysis on a common set of data. The first is a method based on rough sets theory and the second is the location model method from the field of discriminant analysis. To investigate the comparative performance of these methods, a set of real medical data has been used. The data considered are of both discrete and continuous character. During the comparison, particular attention is paid to data reduction and to the derivation of decision rules and classification functions from the reduced set.     

A framework for incremental generation of closed itemsets

Association rule mining from a transaction database (TDB) requires the detection of frequently occurring patterns, called frequent itemsets (FIs), whereby the number of FIs may be potentially huge. Recent approaches for FI mining use the closed itemset paradigm to limit the mining effort to a subset of the entire FI family, the frequent closed itemsets (FCIs). We show here how FCIs can be mined incrementally yet efficiently whenever a new transaction is added to a database whose mining results are available. Our approach for mining FIs in dynamic databases relies on recent results about lattice incremental restructuring and lattice construction. The fundamentals of the incremental FCI mining task are discussed and its reduction to the problem of lattice update, via the CI family, is made explicit. The related structural results underlie two algorithms for updating the set of FCIs of a given TDB upon the insertion of a new transaction. A straightforward method searches for necessary completions throughout the entire CI family, whereas a second method exploits lattice properties to limit the search to CIs which share at least one item with the new transaction. Efficient implementations of the parsimonious method is discussed in the paper together with a set of results from a preliminary study of the method's practical performances.     

An analytic network process approach to operationalization of five forces model

The five forces model has been one of the most influential frameworks for strategic management. In contrast to its importance as a centerpiece of textbooks, however, it has attracted less attention from both academic researchers and practicing managers. This is due to its innate weakness, difficulty in operationalization. The vital requisites for operationalizing the five forces model are to deal with it as a complex system composed of interrelated forces and their sub-forces, and to prioritize them with consideration of their interdependency. The tenet of this study is the requisites can be achieved through the analytic network process (ANP). The ANP, which is a generalization of the analytic hierarchy process (AHP), produces priorities of elements in a complex network model with consideration of interdependency among elements. The five forces model is transformed into a network model of the ANP. The ANP procedure is then carried out to obtain the priority weights of the forces. Combining the derived weights and ratings on the forces produces the state-of-industry-competition index (SICI) values that represent the overall competitive condition of a given industry. The working of the proposed approach is provided with the help of a case study example of the Web portal Industry of Korea. The proposed ANP approach is expected to expand the five forces model into a workable system of analysis by improving its analytical power.     

Nonequivalence transformation of λ‐matrix eigenproblems and model embedding approach to model tuning

In this paper we present some theory for a non‐equivalence transformation of matrix eigenvalues for λ‐matrix polynomials. Application of this transformation to eigenvalue embedding for model tuning on a realistic industry problem is illustrated. The new approach has several advantages such as flexibility, efficiency, and structure‐preservation. A numerical experiment on a pseudosimulation data set from The Boeing Company is reported. Copyright © 2001 John Wiley & Sons, Ltd.     

A novel approach to obtain analytical-numerical solutions of nonlinear Lorenz system

In this research we apply an analytic approach to solve the well-known Lorenz system in the non-chaotic regime. The proposed approach is based on modal expansion by infinite series. The analytical-numerical results show that for real initial conditions and under the non-convective regime the modal expansion series reproduce correctly the dynamical behavior of the solution of the Lorenz system. The validity and reliability of the proposed analytical approach with few terms is tested by its application to the convective and non-convective regime with various parameter values. The main advantage is that the obtained solution is global and is presented in analytical form.     

A new discrete mechanics approach to swing-up control of the cart-pendulum system

This paper develops a new swing-up control method for the cart-pendulum system via discrete mechanics. The swing-up control law consists of two parts: the swing-up stage and the stabilization one. In the swing-up stage, we use a controller based on a discrete Lyapunov function and it can swing up the pendulum. Then, in the stabilization stage, we utilize a stabilizing controller based on the linearized system and discrete-time optimal regulator theory. In addition, transformation methods from discrete control inputs into continuous zero-order hold inputs are introduced. From some simulation results, we can confirm that the cart-pendulum system is swung up and stabilized by our new method.     

A stochastic model to evaluate performance of testing and taping processes on an LSI production system

An automated testing and taping process on a LSI production system is modelled as a variant of M/G/1 finite capacity queue with multiple transactions, where each package receives either a normal service or normal service plus postservice. The system has N spaces for waiting. We successfully define states of system to regard as those of a Markov renewal process even though some time points are not regeneration points. Using the model, we derive properties of stochastic behaviour of the system, in particular, throughput, process of overflows, busy period, and idle period as cost-effective tools for system evaluation.     

A new approach to fuzzy wavelet system modeling

In this paper, we propose simple but effective two different fuzzy wavelet networks (FWNs) for system identification. The FWNs combine the traditional Takagi–Sugeno–Kang (TSK) fuzzy model and discrete wavelet transforms (DWT). The proposed FWNs consist of a set of if–then rules and, then parts are series expansion in terms of wavelets functions. In the first system, while the only one scale parameter is changing with it corresponding rule number, translation parameter sets are fixed in each rule. As for the second system, DWT is used completely by using wavelet frames. The performance of proposed fuzzy models is illustrated by examples and compared with previously published examples. Simulation results indicate the remarkable capabilities of the proposed methods. It is worth noting that the second FWN achieves high function approximation accuracy and fast convergence.     

A statistical approach to crosslingual natural language tasks

The existence of huge volumes of documents written in multiple languages on Internet leads to investigate novel algorithmic approaches to deal with information of this kind. However, most crosslingual natural language processing (NLP) tasks consider a decoupled approach in which monolingual NLP techniques are applied along with an independent translation process. This two-step approach is too sensitive to translation errors, and in general to the accumulative effect of errors. To solve this problem, we propose to use a direct probabilistic crosslingual NLP system which integrates both steps, translation and the specific NLP task, into a single one. In order to perform this integrated approach to crosslingual tasks, we propose to use the statistical IBM 1 word alignment model (M1). The M1 model may show a non-monotonic behaviour when aligning words from a sentence in a source language to words from another sentence in a different, target language. This is the case of languages with different word order. In English, for instance, adjectives appear before nouns, whereas in Spanish it is exactly the opposite. The successful experimental results reported in three different tasks - text classification, information retrieval and plagiarism analysis - highlight the benefits of the statistical integrated approach proposed in this work.     

A four-input three-stage queuing network approach to model an industrial system

An industrial system is represented as a four-input, three-stage queuing network in this paper. The four-input queuing network receives orders from clients, and the orders are waiting to be served. Each order comprises (i) time of occurrence of the orders, and (ii) quantity of items to be delivered in each order. The objective of this paper is to compute the optimal path which produces the least response time for the delivery of items to the final destination along the three stages of the network. The average number of items that can be delivered with this minimum response time constitute the optimum capacity of the queuing network. After getting serviced by the last node (a queue and its server) in each stage of the queuing network, a decision is made to route the items to the appropriate node in the next stage which can produce the least response time. Performance measures such as average queue lengths, average response times, average waiting times of the jobs in the four-input network are derived and plotted. Closed-form expressions for the equivalent service rate, equivalent average queue lengths, equivalent response and waiting times of a single equivalent queue with a server representing the entire four-input queuing network are also derived and plotted.