Generating State-Based Testing Models for Object-Oriented Framework Interface Classes

An application framework provides a reusable design and implementation for a family of software systems. Application developers extend the framework to build their particular applications using hooks. Hooks are the places identified to show how to use and customize the framework. Hooks define the Framework Interface Classes (FICs) and the specifications of their methods. As part of the development life cycle, it is required to test the implementations of the FICs. Building a testing model to express the behavior of a class is an essential step for the generation of the class-based test cases. The testing model has to be consistent with the specifications provided for the hooks. State-based models consisting of states and transitions are testing models well suited to objectoriented software. Typically, hand-construction of a state-based model of a class behavior is expensive, error-prone, and may result in constructing an inconsistent model with the specifications of the class methods, which misleads verification results. In this paper, a technique is introduced to automatically synthesize a state-based testing model for FICs using the specifications provided for the hooks. A tool that supports the proposed technique is introduced.

Electronic Commerce: Costumer Protection In Electronic Payments

As a by-product of its "cyberspace" status, electronic commerce is global, encompassing a whole range of B2C relationships which need to be approached with solutions provided at a local level while remaining viable when applied to global issues. Today, the European Union seems to be endowed with a reliable legal framework for consumer protection. A question which remains, however, is enforcement of this protection. This is probably a matter of time and awareness from both parties in the B2C relationship. Business should realize that enhancing trust in the minds of consumers is more than a question of technology; it is a question of best practice. Best practice starts with the online service of high street banks as well as with the existence of a secure, user-friendly and cost-effective payment system. It also includes the respect of privacy and the use of smart cards as well as enhancing privacy technologies and fair information practice. In sum, only by offering this guarantee of privacy and security will the consumer be assured that, in cyberspace, his/her interests will be protected in the same manner as in a traditional commercial environment.

Nonlinear Sensitive Control of Centrifugal Compressor

In this work, we treat the problems related to chemical and petrochemical plants of a certain complex process taking the centrifugal compressor as an example, a system being very complex by its physical structure as well as its behaviour (surge phenomenon). We propose to study the application possibilities of the recent control approaches to the compressor behaviour, and consequently evaluate their contribution in the practical and theoretical fields. Facing the studied industrial process complexity, we choose to make recourse to fuzzy logic for analysis and treatment of its control problem owing to the fact that these techniques constitute the only framework in which the types of imperfect knowledge can jointly be treated (uncertainties, inaccuracies, etc..) offering suitable tools to characterise them. In the particular case of the centrifugal compressor, these imperfections are interpreted by modelling errors, the neglected dynamics, no modelisable dynamics and the parametric variations. The purpose of this paper is to produce a total robust nonlinear controller design method to stabilize the compression process at its optimum steady state by manipulating the gas rate flow. In order to cope with both the parameter uncertainty and the structured non linearity of the plant, the proposed method consists of a linear steady state regulation that ensures robust optimal control and of a nonlinear compensation that achieves the exact input/output linearization.

Optimizing Dialogue Strategy Learning Using Learning Automata

Modeling the behavior of the dialogue management in the design of a spoken dialogue system using statistical methodologies is currently a growing research area. This paper presents a work on developing an adaptive learning approach to optimize dialogue strategy. At the core of our system is a method formalizing dialogue management as a sequential decision making under uncertainty whose underlying probabilistic structure has a Markov Chain. Researchers have mostly focused on model-free algorithms for automating the design of dialogue management using machine learning techniques such as reinforcement learning. But in model-free algorithms there exist a dilemma in engaging the type of exploration versus exploitation. Hence we present a model-based online policy learning algorithm using interconnected learning automata for optimizing dialogue strategy. The proposed algorithm is capable of deriving an optimal policy that prescribes what action should be taken in various states of conversation so as to maximize the expected total reward to attain the goal and incorporates good exploration and exploitation in its updates to improve the naturalness of humancomputer interaction. We test the proposed approach using the most sophisticated evaluation framework PARADISE for accessing to the railway information system.

Internet Bandwidth Network Quality Management: The Case Study of Telecom Organization of Thailand

This paper addresses a current problem that occurs among Thai internet service providers with regard to bandwidth network quality management. The IPSTAR department of Telecom Organization of Thailand public company (TOT); the largest internet service provider in Thailand, is the case study to analyze the problem that exists. The Internet bandwidth network quality management (iBWQM) framework is mainly applied to the problem that has been found. Bandwidth management policy (BMP) and quality of service (QoS) are two antecedents of iBWQM. This paper investigates internet user behavior, marketing demand and network operation views in order to determine bandwidth management policy (e.g. quota management, scheduling and malicious management). The congestion of bandwidth is also analyzed to enhance quality of service (QoS). Moreover, the iBWQM framework is able to improve the quality of service and increase bandwidth utilization, minimize complaint rate concerns to slow speed, and provide network planning guidelines through Thai Internet services providers.

Discrete Polynomial Moments and Savitzky-Golay Smoothing

This paper presents unified theory for local (Savitzky- Golay) and global polynomial smoothing. The algebraic framework can represent any polynomial approximation and is seamless from low degree local, to high degree global approximations. The representation of the smoothing operator as a projection onto orthonormal basis functions enables the computation of: the covariance matrix for noise propagation through the filter; the noise gain and; the frequency response of the polynomial filters. A virtually perfect Gram polynomial basis is synthesized, whereby polynomials of degree d = 1000 can be synthesized without significant errors. The perfect basis ensures that the filters are strictly polynomial preserving. Given n points and a support length ls = 2m + 1 then the smoothing operator is strictly linear phase for the points xi, i = m+1. . . n-m. The method is demonstrated on geometric surfaces data lying on an invariant 2D lattice.

The Theoretical Framework of the Necessity of Conducting Operational Auditing in Iran

Nowadays, efficiency, effectiveness and economy are regarded as the main objectives of managers and the secret of the continuity of an organization in competing economy. In such competing settings, it is essential that the management of an organization has not been neglected and been obliged to identify quickly the opportunities for improving the operation of organization and remove the shortcomings of their managed system in order to use the opportunities for development. Operational auditing is a useful tool for system adjustment and leading an organization toward its objectives. Operational auditing is indeed a viewpoint which identifies the causes of insufficiencies, weaknesses and deficiencies of system and plans to eliminate them. Operational auditing is useful in the effectiveness and optimization of executive managers- decisions and increasing the efficiency and economy of their performance in the future and prevents the waste and incorrect use of resources. Evidence shows that operational auditing is used at a limited level in Iran. This matter raises some questions like the following ones in the minds. Why do a limited number of corporations use operational auditing? Which factors can guarantee its full implementation? What obstacles are there in its implementation? The purpose of this article is to determine executive objectives, the operation domain of operational auditing, the components of operational auditing and the executive obstacles to operational auditing in Iran.

Household Indebtedness Risks in the Czech Republic

In the past 20 years the economy of the Czech Republic has experienced substantial changes. In the 1990s the development was affected by the transformation which sought to establish the right conditions for privatization and creation of elementary market relations. In the last decade the characteristic elements such as private ownership and corresponding institutional framework have been strengthened. This development was marked by the accession of the Czech Republic to the EU. The Czech Republic is striving to reduce the difference between its level of economic development and the quality of institutional framework in comparison with other developed countries. The process of finding the adequate solutions has been hampered by the negative impact of the world financial crisis on the Czech Republic and the standard of living of its inhabitants. This contribution seeks to address the question of whether and to which extent the economic development of the transitive Czech economy is affected by the change in behaviour of households and their tendency to consumption, i.e. in the sense of reduction or increase in demand for goods and services. It aims to verify whether the increasing trend of household indebtedness and decreasing trend of saving pose a significant risk in the Czech Republic. At a general level the analysis aims to contribute to finding an answer to the question of whether the debt increase of Czech households is connected to the risk of "eating through" the borrowed money and whether Czech households risk falling into a debt trap. In addition to household indebtedness risks in the Czech Republic the analysis will focus on identification of specifics of the transformation phase of the Czech economy in comparison with the EU countries, or selected OECD countries.

Loss of P16/INK4A Protein Expression is a Common Abnormality in Hodgkin's Lymphoma

P16/INK4A is tumor suppressor protein that plays a critical role in cell cycle regulation. Loss of P16 protein expression has been implicated in pathogenesis of many cancers, including lymphoma. Therefore, we sought to investigate if loss of P16 protein expression is associated with lymphoma and/or any specific lymphoma subtypes (Hodgkin-s lymphoma (HL) and nonHodgkin-s lymphoma (NHL)). Fifty-five lymphoma cases consisted of 30 cases of HL and 25 cases of NHL, with an age range of 3 to 78 years, were examined for loss of P16 by immunohistochemical technique using a specific antibody reacting against P16. In total, P16 loss was seen in 33% of all lymphoma cases. P16 loss was identified in 47.7% of HL cases. In contrast, only 16% of NHL showed loss of P16. Loss of P16 was seen in 67% of HL patients with 50 years of age or older, whereas P16 loss was found in only 42% of HL patients with less than 50 years of age. P16 loss in HL is somewhat higher in male (55%) than in female (30%). In subtypes of HL, P16 loss was found exclusively in all cases of lymphocyte depletion, lymphocyte predominance and unclassified cases, whereas P16 loss was seen in 39% of mixed cellularity and 29% of nodular sclerosis cases. In low grade NHL patients, P16 loss was seen in approximately one-third of cases, whereas no or very rare of P16 loss was found in intermediate and high grade cases. P16 loss did not show any correlation with age or gender of NHL patients. In conclusion, the high rate of P16 loss seen in our study suggests that loss of P16 expression plays a critical role in the pathogenesis of lymphoma, particularly with HL.

Evolutionary Eigenspace Learning using CCIPCA and IPCA for Face Recognition

Traditional principal components analysis (PCA) techniques for face recognition are based on batch-mode training using a pre-available image set. Real world applications require that the training set be dynamic of evolving nature where within the framework of continuous learning, new training images are continuously added to the original set; this would trigger a costly continuous re-computation of the eigen space representation via repeating an entire batch-based training that includes the old and new images. Incremental PCA methods allow adding new images and updating the PCA representation. In this paper, two incremental PCA approaches, CCIPCA and IPCA, are examined and compared. Besides, different learning and testing strategies are proposed and applied to the two algorithms. The results suggest that batch PCA is inferior to both incremental approaches, and that all CCIPCAs are practically equivalent.

Optimal Maintenance Policy for a Partially Observable Two-Unit System

In this paper, we present a maintenance model of a two-unit series system with economic dependence. Unit#1 which is considered to be more expensive and more important, is subject to condition monitoring (CM) at equidistant, discrete time epochs and unit#2, which is not subject to CM has a general lifetime distribution. The multivariate observation vectors obtained through condition monitoring carry partial information about the hidden state of unit#1, which can be in a healthy or a warning state while operating. Only the failure state is assumed to be observable for both units. The objective is to find an optimal opportunistic maintenance policy minimizing the long-run expected average cost per unit time. The problem is formulated and solved in the partially observable semi-Markov decision process framework. An effective computational algorithm for finding the optimal policy and the minimum average cost is developed, illustrated by a numerical example.

A Framework to Support the Design of Mobile Applications

This paper introduces a framework that aims to support the design and development of mobile services. The traditional innovation process and its supporting instruments in form of creativity tools, acceptance research and user-generated content analysis are screened for potentials for improvement. The result is a reshaped innovation process where acceptance research and usergenerated content analysis are fully integrated within a creativity tool. Advantages of this method are the enhancement of design relevant information for developers and designers and the possibility to forecast market success.

The Effect of Correlated Service and Inter-arrival Times on System Performance

In communication networks where communication nodes are connected with finite capacity transmission links, the packet inter-arrival times are strongly correlated with the packet length and the link capacity (or the packet service time). Such correlation affects the system performance significantly, but little attention has been paid to this issue. In this paper, we propose a mathematical framework to study the impact of the correlation between the packet service times and the packet inter-arrival times on system performance. With our mathematical model, we analyze the system performance, e.g., the unfinished work of the system, and show that the correlation affects the system performance significantly. Some numerical examples are also provided.

Generating Class-Based Test Cases for Interface Classes of Object-Oriented Black Box Frameworks

An application framework provides a reusable design and implementation for a family of software systems. Application developers extend the framework to build their particular applications using hooks. Hooks are the places identified to show how to use and customize the framework. Hooks define the Framework Interface Classes (FICs) and their possible specifications, which helps in building reusable test cases for the implementations of these classes. This paper introduces a novel technique called all paths-state to generate state-based test cases to test the FICs at class level. The technique is experimentally evaluated. The empirical evaluation shows that all paths-state technique produces test cases with a high degree of coverage for the specifications of the implemented FICs comparing to test cases generated using round-trip path and all-transition techniques.

A Probabilistic Reinforcement-Based Approach to Conceptualization

Conceptualization strengthens intelligent systems in generalization skill, effective knowledge representation, real-time inference, and managing uncertain and indefinite situations in addition to facilitating knowledge communication for learning agents situated in real world. Concept learning introduces a way of abstraction by which the continuous state is formed as entities called concepts which are connected to the action space and thus, they illustrate somehow the complex action space. Of computational concept learning approaches, action-based conceptualization is favored because of its simplicity and mirror neuron foundations in neuroscience. In this paper, a new biologically inspired concept learning approach based on the probabilistic framework is proposed. This approach exploits and extends the mirror neuron-s role in conceptualization for a reinforcement learning agent in nondeterministic environments. In the proposed method, instead of building a huge numerical knowledge, the concepts are learnt gradually from rewards through interaction with the environment. Moreover the probabilistic formation of the concepts is employed to deal with uncertain and dynamic nature of real problems in addition to the ability of generalization. These characteristics as a whole distinguish the proposed learning algorithm from both a pure classification algorithm and typical reinforcement learning. Simulation results show advantages of the proposed framework in terms of convergence speed as well as generalization and asymptotic behavior because of utilizing both success and failures attempts through received rewards. Experimental results, on the other hand, show the applicability and effectiveness of the proposed method in continuous and noisy environments for a real robotic task such as maze as well as the benefits of implementing an incremental learning scenario in artificial agents.

RANFIS : Rough Adaptive Neuro-Fuzzy Inference System

The paper presents a new hybridization methodology involving Neural, Fuzzy and Rough Computing. A Rough Sets based approximation technique has been proposed based on a certain Neuro – Fuzzy architecture. A New Rough Neuron composition consisting of a combination of a Lower Bound neuron and a Boundary neuron has also been described. The conventional convergence of error in back propagation has been given away for a new framework based on 'Output Excitation Factor' and an inverse input transfer function. The paper also presents a brief comparison of performances, of the existing Rough Neural Networks and ANFIS architecture against the proposed methodology. It can be observed that the rough approximation based neuro-fuzzy architecture is superior to its counterparts.

Design Process and Real-Time Validation of an Innovative Autonomous Mid-Air Flight and Landing System

This paper describes the design process and the realtime validation of an innovative autonomous mid-air flight and landing system developed by the Italian Aerospace Research Center in the framework of the Italian national funded project TECVOL (Technologies for the Autonomous Flight). In the paper it is provided an insight of the whole development process of the system under study. In particular, the project framework is illustrated at first, then the functional context and the adopted design and testing approach are described, and finally the on-ground validation test rig on purpose designed is addressed in details. Furthermore, the hardwarein- the-loop validation of the autonomous mid-air flight and landing system by means of the real-time test rig is described and discussed.

Estimation of Attenuation and Phase Delay in Driving Voltage Waveform of a Digital-Noiseless, Ultra-High-Speed Image Sensor

Since 2004, we have been developing an in-situ storage image sensor (ISIS) that captures more than 100 consecutive images at a frame rate of 10 Mfps with ultra-high sensitivity as well as the video camera for use with this ISIS. Currently, basic research is continuing in an attempt to increase the frame rate up to 100 Mfps and above. In order to suppress electro-magnetic noise at such high frequency, a digital-noiseless imaging transfer scheme has been developed utilizing solely sinusoidal driving voltages. This paper presents highly efficient-yet-accurate expressions to estimate attenuation as well as phase delay of driving voltages through RC networks of an ultra-high-speed image sensor. Elmore metric for a fundamental RC chain is employed as the first-order approximation. By application of dimensional analysis to SPICE data, we found a simple expression that significantly improves the accuracy of the approximation. Similarly, another simple closed-form model to estimate phase delay through fundamental RC networks is also obtained. Estimation error of both expressions is much less than previous works, only less 2% for most of the cases . The framework of this analysis can be extended to address similar issues of other VLSI structures.

Traffic Flow on Road Junctions

The paper deals with a mathematical model for fluid dynamic flows on road networks which is based on conservation laws. This nonlinear framework is based on the conservation of cars. We focus on traffic circle, which is a finite number of roads that meet at some junctions. The traffic circle with junctions having either one incoming and two outgoing or two incoming and one outgoing roads. We describe the numerical schemes with the particular boundary conditions used to produce approximated solutions of the problem.

Scientific Workflow Interoperability Evaluation

There is wide range of scientific workflow systems today, each one designed to resolve problems at a specific level. In large collaborative projects, it is often necessary to recognize the heterogeneous workflow systems already in use by various partners and any potential collaboration between these systems requires workflow interoperability. Publish/Subscribe Scientific Workflow Interoperability Framework (PS-SWIF) approach was proposed to achieve workflow interoperability among workflow systems. This paper evaluates the PS-SWIF approach and its system to achieve workflow interoperability using Web Services with asynchronous notification messages represented by WS-Eventing standard. This experiment covers different types of communication models provided by Workflow Management Coalition (WfMC). These models are: Chained processes, Nested synchronous sub-processes, Event synchronous sub-processes, and Nested sub-processes (Polling/Deferred Synchronous). Also, this experiment shows the flexibility and simplicity of the PS-SWIF approach when applied to a variety of workflow systems (Triana, Taverna, Kepler) in local and remote environments.