Belief‐rule‐based expert systems for evaluation of e‐government: a case study

Little knowledge exists on the impact and results associated with e‐government projects in many specific‐use domains. Therefore, it is necessary to evaluate the efficiency and effectiveness of e‐government systems. Because the development of e‐government is a continuous process of improvement, it requires continuous evaluation of the overall e‐government system as well as evaluation of its various dimensions such as determinants, characteristics and results. E‐government development is often complex, with multiple stakeholders, large user bases and complex goals. Consequently, even experts have difficulties in evaluating these systems, especially in an integrated and comprehensive way, as well as on an aggregate level. Expert systems are a candidate solution to evaluate such complex e‐government systems. However, it is difficult for expert systems to cope with uncertain evaluation data that are vague, inconsistent, highly subjective or in other ways, challenging to formalize. This paper presents an approach that can handle uncertainty in e‐government evaluation: the combination of Belief Rule Base knowledge representation and Evidential Reasoning. This approach is illustrated with a concrete prototype, known as the Belief Rule Based Expert System (BRBES) and implemented in the local e‐government of Bangladesh. The results have been compared with a recently developed method of evaluating e‐government, and it is demonstrated that the results of the BRBES are more accurate and reliable. The BRBES can be used to identify the factors that need to be improved to achieve the overall aim of an e‐government project. In addition, various ‘what if’ scenarios can be generated, and developers and managers can obtain a foretaste of the outcomes. Thus, the system can be used to facilitate decision‐making processes under uncertainty.     

HEARTDROID—Rule engine for mobile and context‐aware expert systems

Building mobile context‐aware systems is inherently complex and non‐trivial task. It consists of several phases starting from acquisition of context, through modeling to execution of contextual models. Today, such systems are mostly implemented on mobile platforms, that introduce specific requirements, such as intelligibility, robustness, privacy, and efficiency. Over the last decade, along with the rapid development of mobile industry, many approaches were developed that unevenly support these requirements. This is mainly caused by the fact that current modelling and reasoning methods are not crafted to operate in mobile environments. We argue that the use of rule‐based reasoning tailored to mobile environments is an optimal solution. Rules are based on symbolic knowledge representation, as such they meet the general tendency to enforce understandability, intelligibility, and controllability of artificial intelligence software, as stated in the recent European Union General Data Protection Regulation. To this goal, we introduce a lightweight rule engine dedicated for Android platform called HEARTDROID. It executes models in the HMR+ rule language that are capable of expressing uncertainty of knowledge, capturing dynamics of mobile environment and provide high level of intelligibility. We present a qualitative and quantitative comparison of HEARTDROID with the most popular rule engines available.     

RuleSIM: a toolkit for simulating the operation and improving throughput of rule‐based spam filters

This paper introduces RuleSIM, a toolkit comprising different simulation tools specifically designed to aid researchers concerned about spam‐filtering throughput. RuleSIM allows easily designing, developing, simulating and comparing new scheduling heuristics using different filters and sets of e‐mails. Simulation results can be both graphically analysed, by using different complementary views, and quantitatively compared through several measures. Moreover, the underlying RuleSIM API can be easily integrated with third‐party Java optimization platforms to facilitate debugging and achieve better configurations for rule scheduling. RuleSIM is free software distributed under the terms of GNU Lesser General Public License, and both source code and documentation are publicly available at https://github.com/rulesim/v2.0 . Copyright © 2015 John Wiley & Sons, Ltd.     

Using new scheduling heuristics based on resource consumption information for increasing throughput on rule‐based spam filtering systems

The large increase of spam deliveries since the first half of 2013 entailed hard to solve troubles in spam filters. In order to adequately fight spam, the throughput of spam filtering platforms should be necessarily increased. In this context, and taking into consideration the widespread utilization of rule‐based filtering frameworks in the spam filtering domain, this work proposes three novel scheduling strategies for optimizing the time needed to classify new incoming e‐mails through an intelligent management of computational resources depending on the Central Processing Unit (CPU) usage and Input/Output (I/O) delays. In order to demonstrate the suitability of our approaches, we include in our experiments a comparative study in contrast to other successful heuristics previously published in the scientific literature. Results achieved demonstrated that one of our alternative heuristics allows time savings of up to 10% in message filtering, while keeping the same classification accuracy. Copyright © 2015 John Wiley & Sons, Ltd.     

用遗传算法改进基于专家系统的入侵检测系统

基于专家系统的入侵检测系统的检测性能很大程度依赖于专家系统的规则集.为了提高基于专家系统的入侵检测系统的检测能力,使用遗传算法来对专家系统的规则集进行动态更新.但是基本遗传算法并不能有效对规则集进行动态更新,所以从编码、适应度函数、交叉等几个方面对遗传算法进行了改进.对如何使用改进的遗传算法对专家系统的规则集进行动态更新提出了一种实现方案.     

Assessment of life insurance applications: an approach integrating neuro‐symbolic rule‐based with case‐based reasoning

Assessment of applications for life insurance is an important task in the insurance sector that concerns estimation of potential risks underlying an application, if accepted. This task is accomplished by specialized personnel of insurance companies. Because of recent financial crises, this task is more demanding, and intelligent computer‐based methods could be employed to assist. In this paper, we present an intelligent approach to assessment of life insurance applications, which is based on an integration of neurule‐based with case‐based reasoning. Neurules are a type of neuro‐symbolic rules that combine a symbolic (production rules) and a connectionist (adaline unit) representation. A characteristic of neurules is that in contrast to other hybrid neuro‐symbolic approaches, they retain the naturalness and modularity of symbolic rules. Neurules are produced from available symbolic rules that represent general knowledge, which however do not completely cover the domain. We use health condition, age, gender, annual income, profession, insurance type and primary life insurance benefit as assessment parameters used in rule conditions. The integration of neurules and cases employs different types of indices for the cases according to different roles they play in neurule‐based reasoning. This results in its accuracy improvement. Experimental results demonstrate the effectiveness of the approach.     

Authority updating: An expert authority evaluation algorithm considering post‐evaluation and power indices in social networks

In group assessment, the focus is on finding high‐authority experts to improve the reliability of assessment results. In this study, we propose an authority updating algorithm while considering the power and judgement reliability of an expert on the basis of social networks and post‐evaluations. A network power index is established and used to reflect the power of an expert while considering social networks. The measurement of the judgement reliability of an expert considers the post‐evaluation of the objects selected by experts, thereby more scientifically reflecting the reliability of experts. The analysis shows the following: although the social‐network structure influences the authority of experts, the influence weakens when the assessment group is a highly or even fully connected group; the network effect may increase the authority of some experts and reduce that of others, and it will weaken as the network connectivity increases; moreover, the judgement reliability and authority of an expert while considering post‐evaluation can encourage him/her to make fair assessments and strive to reduce his/her motivation and cognitive biases.     

Improving quality of software product line by analysing inconsistencies in feature models using an ontological rule‐based approach

In software product line engineering, feature models (FMs) represent the variability and commonality of a family of software products. The development of FMs may introduce inaccurate feature relationships. These relationships may cause various types of defects such as inconsistencies, which deteriorate the quality of software products. Several researchers have worked on the identification of defects due to inconsistency in FMs, but only a few of them have explained their causes. In this paper, FM is transformed to predicate‐based feature model ontology using Prolog. Further, first‐order logic is employed for defining rules to identify defects due to inconsistency, the explanations for their causes, and suggestions for their corrections. The proposed approach is explained using an FM available in Software Product Line Online Tools repository. It is validated using 26 FMs of discrete sizes up to 5,543 features, generated using the FeatureIDE tool and real‐world FMs. Results indicate that the proposed methodology is effective, accurate, and scalable and improves software product line.     

Toc‐Tum mini‐games: An educational game accessible for deaf culture based on virtual reality

Human hearing is an important sense, which complements the other senses, and is essential for children to begin to acquire basic concepts of the world; however, in severe cases of disability, children become marginalized from these benefits. An example of this is with music, a deaf individual is to be able to perceive it. With this in mind, we developed a novel medical expert system based on virtual reality, called Toc‐Tum mini‐games, applying basic concepts of music in an accessible way to the deaf culture. The intelligent proposed system is validated in two different tests: (a) with the target audience to evaluate the interest in the game and (b) with professionals knowledgeable in the field of music or who have had contact with the deaf, evaluate the impact of the game teaching music to the deaf. The tests with the target audience showed that the methods of interaction allowed the children to understand most of the stages and that they were animated during the test days. Regarding the professionals, they were interested in the possibility of using the proposed system in question, even if some modifications in the design had to be made. The results showed that the Toc‐Tum mini‐games is an intelligent tool capable of introducing music in a playful and manageable way using a virtual environment.     

Consensus of multi‐agent systems with time‐varying topology: An event‐based dynamic feedback scheme

The event‐based control strategy is an effective methodology for reducing the controller update and communication over the network. In this paper, the event‐based consensus of multi‐agent systems with linear dynamics and time‐varying topology is studied. For each agent, a state‐dependent threshold with an exponentially decaying bound is presented to determine the event times, and a new event‐based dynamic feedback scheme is proposed. It is shown that the controller update for each agent is only dependent on its own event times, which reduces significantly the controller update or computation for each agent. Moreover, based on the event‐based dynamic feedback scheme and the event triggering function presented in this paper, the continuous communication among neighboring agents is avoided, and the Zeno‐behavior of the closed‐loop systems is excluded. A numerical example is given to illustrate the effectiveness of theoretical results. Copyright © 2016 John Wiley & Sons, Ltd.     

An application of expert systems techniques to the on-line control and fault diagnosis of a mixing process

An application of expert hierarchical control is described in this paper. The control is implemented in a two-level configuration, where the lower layer performs direct regulation control and the upper layer performs supervisory functions. In the regulation layer, a rule-based controller performs the regulation task, where the controller is constructed upon causal relations between subsystems. The control action is inferred from the measurement of both controlled and noncontrolled variables. In the supervisory layer, the main function is a fault diagnosis system which diagnoses faults on-line. The diagnosis is based upon reasoning from the structure of the system and the functions of its components, and efficient diagnosis is achieved by dividing the system into several subsystems. The overall technique has been successfully implemented on a pilot scale mixing process under on-line computer control.     

Parallel implementation of rule-based expert systems for interactive applications

A novel approach to parallel implementation of rule-based expert systems is presented in this paper. This approach is tailored for expert systems in interactive applications. Rule-based expert systems are modeled by state space and AND/OR graphs. The interdependences among rules are analyzed to guide rule-base partitioning and memory bank assignment. Parallel execution of rule-based expert systems is investigated in the environment of closely coupled multiprocessors. Algorithms are developed for the parallel execution of rules and for the allocation of data to memory banks in interactive applications.     

Autonomic configuration and recovery in a mobile agent‐based distributed event monitoring system

In this paper we present a framework for building policy‐based autonomic distributed agent systems. The autonomic mechanisms of configuration and recovery are supported through a distributed event processing model and a set of policy enforcement mechanisms embedded in an agent framework. Policies are event‐driven rules derived from the system's functional and non‐functional requirements. Agents in the network monitor the system state for policy violation conditions, generate appropriate events, and communicate them to other agents for cooperative filtering, aggregation, and handling. A set of agents perform policy enforcement actions whenever events signifying any policy violation conditions occur. Policies are defined using a specification framework based on XML. The policy enforcement agents interpret the policies given in XML. We illustrate the utility of this framework in the context of an agent‐based distributed network monitoring application. We also present an experimental evaluation of our approach. Copyright © 2006 John Wiley & Sons, Ltd.     

An architecture for tuple‐based coordination of multi‐agent systems

Multi‐agent system development calls for powerful and expressive coordination models and languages, as well as for an effective coordination technology. A good deal of the current research effort focuses on tuple‐based coordination, exploiting its well‐known advantages, such as agent uncoupling and associative access to information, and addressing its limitations in terms of flexibility and control capabilities. In particular, the behaviour of a Linda‐like tuple space is fixed once and for all by the coordination model, and cannot be tailored to the specific application needs. Tuple centres are tuple spaces whose behaviour can be programmed by defining transactional reactions to the basic communication events, allowing coordination laws to be explicitly defined and embedded into the coordination medium. This paper presents the architecture of a run‐time system for tuple‐based coordination, where tuple centres work as an extensible kernel, around which multi‐agent systems can be designed and deployed. After sketching the implementation, the paper shows the advantages that can be achieved from both the design and the performance viewpoints. Copyright © 1999 John Wiley & Sons, Ltd.     

Observer‐based finite‐time stabilization for discrete‐time switched singular systems with quadratically inner‐bounded nonlinearities

This paper discusses the observer‐based finite‐time stabilization for discrete‐time switched singular systems with quadratically inner‐bounded nonlinear terms. Firstly, based on the Luenberger‐like observer, by using the average dwell time approach, sufficient conditions are proposed to make closed‐loop systems be regular, be causal, as having a unique solution, and be uniformly finite‐time bounded. Then, a new linear matrix inequality sufficient condition for the existence of an observer‐based controller is obtained by using certain matrix decoupling techniques, and the controller is designed. In this paper, the conditions proposed not only give the observer‐based controller design methods but also guarantee the existence and uniqueness of solution for the systems. Since the quadratically inner‐bounded nonlinearities are more general than Lipschitz nonlinearities and one‐sided Lipschitz nonlinearities, compared with previous works, the proposed controller design methods in this paper are also more general than the existing ones. Finally, numerical examples are provided to illustrate the effectiveness of the methods proposed in this paper.     

Decentralized control of network‐based interconnected systems: A state‐dependent triggering method

This paper investigates decentralized control for a class of interconnected system. Different from the traditional systems, the considered system has the following features: (i) its subsystems are connected through a communication network subject to transmission delays and packet losses; (ii) the subsystems' multi‐actuators are subjected to random faults; and (iii) the subsystems are subject to probabilistic nonlinear disturbances, the inner variation information of the nonlinearities, as well as their bounds information, is utilized to analyze the nonlinearities. Furthermore, in order to reduce the network bandwidth burden, a decentralized state‐dependent triggering scheme is proposed. Considering aforementioned characteristics and using the state‐dependent triggering scheme, new type of network‐based interconnected system model is built. By using the Lyapunov functional approach, sufficient conditions for the mean square stability and stabilization of the network‐based interconnected systems are obtained. Then reliable controllers, as well as the triggering matrices of the local subsystems, can be co‐designed by using a cone complementary linearization algorithm. Two simulation examples are given to illustrate the effectiveness and application of the proposed method. Copyright © 2013 John Wiley & Sons, Ltd.     

Observer‐based event‐triggered control for singularly perturbed systems with saturating actuator

This paper investigates an observer‐based event‐triggered control problem of singularly perturbed systems with saturating actuator. A strategy that consists of an observer‐based controller (OBC) and an event‐triggered mechanism (ETM) is considered. Firstly, sufficient conditions, which guarantee that the saturated SPSs are asymptotically stable excluding Zeno phenomenon, are derived via constructing an ε‐dependent Lyapunov‐Krasovskii functional. Then, the OBC and ETM are designed simultaneously based on the aforementioned criteria. Furthermore, an estimate of the basin of attraction and an ε‐bound are given by solving an optimization problem in the form of LMIs. Finally, an electric circuit system and a numerical example are presented to demonstrate the merits of the obtained method.     

Transparent adaptation of sharing granularity in MultiView‐based DSM systems

In this paper we propose a mechanism that provides distributed shared memory (DSM) systems with a flexible sharing granularity. The size of the shared memory units is dynamically determined by the system during runtime. This size can range from that of a single variable up to the size of the entire shared memory space. During runtime, the DSM transparently adapts the granularity to the memory access pattern of the application in each phase of its execution. This adaptation, called ComposedView, provides efficient data sharing in software DSM while preserving sequential consistency. Neither complex code analysis nor annotation by the programmer or the compiler are required. Our experiments indicate a substantial performance boost (up to 80% speed‐up improvement) when running a large set of applications using our method, compared to running these benchmark applications with the best fixed granularity. Copyright © 2001 John Wiley & Sons, Ltd.     

Network‐based robust performance analysis for uncertain systems interconnected over an undirected graph

This article aims at providing tractable conditions of robust performance (RP) analysis for interconnected uncertain system with networked communication, which is composed of heterogeneous uncertain subsystems connected over an undirected graph. Each subsystem communicates with its neighbors through local packet‐based communication network asynchronously and independently. First, the interconnected uncertain system with networked communication is modeled as a hybrid system. Then sufficient conditions in terms of linear matrix inequalities (LMIs), which are related to the interconnection structure and the maximum allowable transmission interval (MATI) of each local network, are derived such that the interconnected uncertain system is robustly asymptotically stable and achieves the desired RP. These conditions only depend on the parameters of individual subsystem and local network. Finally, an example of power system is given to demonstrate the applicability and effectiveness of our results.     

Drivers and export performance impacts of IT capability in ‘born‐global’ firms: a cross‐national study

Past research focusing on large firms has argued that information technology (IT) capability enhances firm performance. However, these studies have seldom explored why firms develop IT capability, and have also left a void the understanding of the role of IT capability in Small‐ and medium‐sized enterprises (SMEs). This study attempts to fill that void by examining the effect of relevant environmental and firm‐level factors on IT capability, and the effect of IT capability on the export performance of Chinese and US born‐global firms, a special breed of export‐focused SMEs. Results indicate that environmental factors such as information intensity, and firm‐level factors such as international entrepreneurial orientation, prompt born‐global firms to develop IT capability. Further, our results also strongly emphasise the positive role that IT capability plays on the performance of born‐global firms. Finally, a comparative analysis of the Chinese and US born‐global firms revealed a lack of a cross‐cultural difference in the factors leading these firms to develop IT capability, therefore supporting the ‘convergence’ perspective in cross‐cultural research.