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This research proposes an innovative fault-tolerant media content list management technology applied to the smart robot domain.

A fault tolerant Content List Management Unit (CLMU) for real-time streaming systems focusing on smart robot claw machines is proposed to synchronize and manage the hyperlink stored on media servers. The fault-tolerant mechanism is realized by the self-healing method. A media server allows exchanging the hyperlink within the network through the CLMU mechanism.

Internet users can access the current multimedia information, and the multimedia information list can be rearranged appropriately. Furthermore, the service of the proposed multimedia system should be uninterrupted even when the master media server fails. Therefore, one of the slave media servers enables the Content List Service (CLS) of the proposed CLMU and replaces the defunct master media server.

The recovery time is less than 1.5 seconds. The multimedia transmission is not interrupted while any one of the media servers keeps functioning. The proposed method can serve to stabilize the system of media servers in a smart robot domain.

In today's e‐business, system downtime is an unacceptable option since each hour, even minute of downtime may generate negative financial effects. In order to stay competitive, e‐business must be continuous from a data availability perspective and agile with regard to data access. Therefore, there is a need for an information system which can support such a kind of business which will have high availability ratios. This study seeks to address this issue.

A systems approach has been used. Methodological framework is based on a MS/OR‐based definition of a system given by C.W. Churchman.

The paper presents a framework for the development of an e‐business‐oriented information system from business continuance perspective. It identifies high system availability and agile data access as two critical attributes in designing information systems for e‐business. In addition, it identifies two sets of information technologies (business continuity and business agility drivers) that are crucial in developing such information systems.

The presented framework can be used while selecting an appropriate operating platform in order to achieve higher levels of continuous computing.

Systems approach as defined by C.W. Churchman has been applied in the field of information systems for e‐business continuance.

Every company or manufacturing system is vulnerable to breakdowns. This research aims to analyze the role of Multi-Agent Technology (MAT) in minimizing breakdown probabilities in Manufacturing Industries.

This study formulated a framework of six factors and twenty-eight variables (explored in the literature). A hybrid approach of Multi-Criteria Decision-Making Technique (MCDM) was employed in the framework to prioritize, rank and establish interrelationships between factors and variables grouped under them.

The research findings reveal that the “Manufacturing Process” is the most essential factor, while “Integration Manufacturing with Maintenance” is highly impactful on the other factors to eliminate the flaws that may cause system breakdown. The findings of this study also provide a ranking order for variables to increase the performance of factors that will assist manufacturers in reducing maintenance efforts and enhancing process efficiency.

The ranking order developed in this study may assist manufacturers in reducing maintenance efforts and enhancing process efficiency. From the manufacturer’s perspective, this research presented MAT as a key aspect in dealing with the complexity of manufacturing operations in manufacturing organizations. This research may assist industrial management with insights into how they can lower the probability of breakdown, which will decrease expenditures, boost productivity and enhance overall efficiency.

This study is an original contribution to advancing MAT’s theory and empirical applications in manufacturing organizations to decrease breakdown probability.

The paper aims at identifying key information technology enablers for business continuance.

The paper provides an analysis of the issues surrounding communication technology downtime and business continuity.

To be competitive, today's business has to be continuous from a data availability perspective and agile with regard to data access. System and/or application downtime are not an option in modern business since each hour, even minute, of downtime may generate negative financial effects. A framework for the design and implementation of a server operating environment for business continuance is presented.

Analyses an important issue in the business environment.

The paper aims at defining a systemic framework for the implementation of business continuity management (BCM). The framework is based on the assertion that the implementation of BCM should be done through the systemic implementation of an “always-on” enterprise information system.

Systems approach is used in order to design a systemic framework for the implementation of continuous computing technologies within the concept of an always-on enterprise information system.

A conceptual framework has been proposed to develop a framework for a systemic implementation of several continuous computing technologies that enhance business continuity (BC) in the form of an “always-on” enterprise information system.

The paper identifies BC as a business pressure in internet era and suggests a systemic framework for implementation.

The objective of this study is to enhance the usage of teleoperation fields, such as in nuclear site decommissioning or nuclear waste disposal, by designing a stable, dependable and fault‐tolerant teleoperation system in the face of “extraordinary” conditions. These “extraordinary” conditions can be classified as variable time delays in communications lines, usage of different robotic systems, component failures and changes in the system parameters during task execution.

This paper first gives a review of teleoperation systems developed earlier. Later, fault tolerance is proposed for use in teleoperation systems at the processor, actuator, sub‐system, and system levels. Position/force control algorithms are recommended to address stability issues when there is a loss in communications. Various other controls are also introduced to overcome the instability experienced when there is a time delay in the communications line.

Finally, this work summarizes the teleoperation system architecture and controller design options in terms of a flowchart to help in the conceptual design of such systems.

The impact of these new designs and algorithms will be to expand the limits and boundaries of teleoperation and a widening of its utilization area. Enhanced operation of these systems will improve system reliability and even encourage their use in more critical and diverse applications.

To solve the above problems and ensure the stability of the ad hoc network node topology in the process of wireless signal transmission, this paper aims to design a robust adaptive sliding film fault-tolerant controller under the nonlinear distortion of signal transmission in an amorphous flat air-to-ground wireless ad hoc network system.

This paper designs a robust adaptive sliding film fault-tolerant controller under the nonlinear distortion of signal transmission in an amorphous flat air-to-ground wireless ad hoc network system.

The simulation results show that the amorphous flat wireless self-organizing network system has good nonlinear distortion fault-tolerant correction ability under the feedback control of the designed controller, and the system has the asymptotically stable convergence ability; the test results show: the node topology of the self-organizing network structural stability is significantly improved, which provides a foundation for the subsequent realization of long-distance transmission of ad hoc network nodes.

Because of the chosen research approach, the research results may lack generalizability. Therefore, researchers are encouraged to test the proposed propositions further.

The controller can extract the fault information caused by nonlinear distortion in the wireless signal transmission process, and at the same time, its feedback matrix K can gradually converge the generated wireless signal error to zero, to realize the stable transmission of the wireless signal.

Taking into consideration the current human need for agricultural produce such as rice that requires water for growth, the optimal consumption of this valuable liquid is important. Unfortunately, the traditional use of water by humans for agricultural purposes contradicts the concept of optimal consumption. Therefore, designing and implementing a mechanized irrigation system is of the highest importance. This system includes hardware equipment such as liquid altimeter sensors, valves and pumps which have a failure phenomenon as an integral part, causing faults in the system. Naturally, these faults occur at probable time intervals, and the probability function with exponential distribution is used to simulate this interval. Thus, before the implementation of such high-cost systems, its evaluation is essential during the design phase.

The proposed approach included two main steps: offline and online. The offline phase included the simulation of the studied system (i.e. the irrigation system of paddy fields) and the acquisition of a data set for training machine learning algorithms such as decision trees to detect, locate (classification) and evaluate faults. In the online phase, C5.0 decision trees trained in the offline phase were used on a stream of data generated by the system.

The proposed approach is a comprehensive online component-oriented method, which is a combination of supervised machine learning methods to investigate system faults. Each of these methods is considered a component determined by the dimensions and complexity of the case study (to discover, classify and evaluate fault tolerance). These components are placed together in the form of a process framework so that the appropriate method for each component is obtained based on comparison with other machine learning methods. As a result, depending on the conditions under study, the most efficient method is selected in the components. Before the system implementation phase, its reliability is checked by evaluating the predicted faults (in the system design phase). Therefore, this approach avoids the construction of a high-risk system. Compared to existing methods, the proposed approach is more comprehensive and has greater flexibility.

By expanding the dimensions of the problem, the model verification space grows exponentially using automata.

Unlike the existing methods that only examine one or two aspects of fault analysis such as fault detection, classification and fault-tolerance evaluation, this paper proposes a comprehensive process-oriented approach that investigates all three aspects of fault analysis concurrently.

To describe the architecture of iPOS (short for iPAQ positioning system), a novel fault‐tolerant and adaptive self‐positioning system with quality‐of‐service (QoS) guarantees for resource‐limited mobile devices.

The iPOS architecture is based on a novel sensor modelling technique in combination with a probabilistic data‐fusion engine, which is capable of efficiently combining the location information obtained from an arbitrary number of heterogeneous location sensors. As a proof of concept, the paper present a prototypical implementation for handheld devices, which was evaluated by means of practical experiments.

A major advantage of the iPOS positioning system is its extensibility and flexibility, which is achieved by means of an open plugin architecture and the support of global positioning coordinates according to the WGS‐84 standard. The iPOS system scales very well with respect to the number of sensor plugins that can be operated in parallel. The main limiting factor for the number of supported active plugins is the amount of available system resources on the MoD. With regard to recognition, the experimental results indicate a good accuracy of the fusion‐based positioning system in comparison to the accuracy of the individual sensing technologies. Thanks to the explicit modelling of reliable sensor events, the iPOS system is capable of providing QoS guarantees to applications with regard to the achieved positioning accuracy.

During the experiments, the author recognized time synchronisation as an important challenge that should be addressed as part of future work.

The system enables resource‐restricted mobile devices and computerised objects to exploit computing resources found in their immediate physical vicinity (locality).

The paper presents a novel lightweight sensor‐fusion architecture for fault‐tolerant and adaptive self‐positioning that performs well on resource‐limited mobile devices. A special feature of the developed data‐fusion architecture is the application of a novel event modelling technique that enables the positioning system to give QoS guarantees under certain conditions.

The objective of this paper is to provide a brief review of recent developments in the area of applications of ANN, Fuzzy Logic, and Wavelet Transform in fault diagnosis. The purpose of this work is to provide an approach for maintenance engineers for online fault diagnosis through the development of a machine condition‐monitoring system.

A detailed review of previous work carried out by several researchers and maintenance engineers in the area of machine‐fault signature‐analysis is performed. A hybrid expert system is developed using ANN, Fuzzy Logic and Wavelet Transform. A Knowledge Base (KB) is created with the help of fuzzy membership function. The triangular membership function is used for the generation of the knowledge base. The fuzzy‐BP approach is used successfully by using LR‐type fuzzy numbers of wavelet‐packet decomposition features.

The development of a hybrid system, with the use of LR‐type fuzzy numbers, ANN, Wavelets decomposition, and fuzzy logic is found. Results show that this approach can successfully diagnose the bearing condition and that accuracy is good compared with conventionally EBPNN‐based fault diagnosis.

The work presents a laboratory investigation carried out through an experimental set‐up for the study of mechanical faults, mainly related to the rolling element bearings.

The main contribution of the work has been the development of an expert system, which identifies the fault accurately online. The approaches can now be extended to the development of a fault diagnostics system for other mechanical faults such as gear fault, coupling fault, misalignment, looseness, and unbalance, etc.