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21 – 30 of over 48000The purpose of this paper is to clarify the aims, monitoring methods and challenges of social media monitoring from the perspective of international companies. Trends in the…
Abstract
Purpose
The purpose of this paper is to clarify the aims, monitoring methods and challenges of social media monitoring from the perspective of international companies. Trends in the literature are also investigated.
Design/methodology/approach
Based on a systematic literature review, 30 key articles from 2008 to 2012 were further analysed.
Findings
International companies need real-time monitoring software, expertise and dynamic visualization to facilitate early detection and prognoses supporting strategy making. This is a costly affair, prompting questions about return on investment. A recent trend in the research literature concerns the development of models describing how issues spread in social media with the aim of facilitating prognoses.
Research limitations/implications
The online databases used comprised refereed peer-reviewed scientific articles. Books were not included in the search process.
Practical implications
Because information spreads fast in social media and affects international companies, they need to identify issues early, in order to monitor and predict their growth. This paper discusses the difficulties posed by this objective.
Originality/value
Social media monitoring is a young research area and research on the topic has been conducted from many different perspectives. Therefore, this paper brings together current insights geared towards corporate communication by international companies.
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This study aims to investigate the service performances of a new full-section asphalt concrete waterproof sealing structure (FSACWSS) for the high-speed railway subgrade through…
Abstract
Purpose
This study aims to investigate the service performances of a new full-section asphalt concrete waterproof sealing structure (FSACWSS) for the high-speed railway subgrade through on-site tracking, monitoring and post-construction investigation.
Design/methodology/approach
Based on the working state of the waterproof sealing structure, the main functional characteristics were analyzed, and a kind of roller-compacted high elastic modulus asphalt concrete (HEMAC) was designed and evaluated by several groups of laboratory tests. It is applied to an engineering test section, and the long-term performance monitoring and subgrade dynamic performance testing system were installed to track and monitor working performances of the test section and the adjacent contrast section with fiber-reinforced concrete.
Findings
Results show that both the dynamic performance of the track structure and the subgrade in the test section meet the requirements of the specification limits. The water content in the subgrade of the test section is maintained at 8–18%, which is less affected by the weather. However, the water content in the subgrade bed of the contrast section is 10–35%, which fluctuates significantly with the weather. The heat absorption effect of asphalt concrete in the test section makes the temperature of the subgrade at the shoulder larger than that in the contrastive section. The monitoring value of the subgrade vertical deformation in the test section is slightly larger than that in the contrastive section, but all of them meet the limit requirements. The asphalt concrete in the test section is in good contact with the base, and there are no diseases such as looseness or spalling. Only a number of cracks are found at the joints of the base plates. However, there are more longitudinal and lateral cracks in the contrastive section, which seriously affects the waterproof and sealing effects. Besides, the asphalt concrete is easier to repair, featuring good maintainability.
Originality/value
This research can provide a basis for popularization and application of the asphalt concrete waterproof sealing structure in high-speed railways.
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The activities using drum resources restrict the operation of multi-project systems. However, existing monitoring methods are not suitable for the characteristics of drum…
Abstract
Purpose
The activities using drum resources restrict the operation of multi-project systems. However, existing monitoring methods are not suitable for the characteristics of drum activities in the multi-project system. The authors therefore propose an adaptive capacity constraint buffer monitoring model based on the attributes of drum activities, aiming to build a high-efficiency progress control framework for multiple projects.
Design/methodology/approach
Considering the attributes and the interrelationship of drum activities, the monitoring reference points are determined on the basis of decentralized buffers. The authors next set action thresholds according to the relationship between the drum activities' interval margin and buffer consumption, and then the corresponding monitoring measures are taken.
Findings
The empirical results show that, compared to the classic methods, the proposed approach can effectively monitor the progress of the drum plan and realize the dual optimization of multi-project duration and cost.
Research limitations/implications
The buffer consumption at the follow-up monitoring time point is neglected when determining the action thresholds. Prediction methods can be introduced to present more all-sided monitoring.
Practical implications
This paper fulfils the dual optimization of multi-project duration and cost. It provides a reference guide for project managers.
Originality/value
A capacity constraint buffer monitoring method suitable for a multi-project environment is produced.
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Monika Kornacka, Anna Jaskulska, Kinga Skorupska, Marta Szastok, Małgorzata Nadziejko and Wiesław Kopeć
One of the recommendations in process-based cognitive therapies suggests that functional analysis created by the clinician should be supported by empirical data collected through…
Abstract
Purpose
One of the recommendations in process-based cognitive therapies suggests that functional analysis created by the clinician should be supported by empirical data collected through daily sampling. It enables the computing of a dynamic network of psychological processes and symptoms supporting clinical decisions but also therapeutic progress monitoring. However, the experience sampling solutions available in the market do not enable the automatic creation of this kind of network; thus, the use of this approach in clinical practice is practically impossible without advanced statistical skills and significant time investment. The purpose of the present paper is to describes a protocol of a research project based on a participatory approach aiming to create a solution enabling therapists not only to set up a personalized daily sampling for their patients and collect the data but also providing a fully automated visualization of the network adapted for therapeutic purposes.
Design/methodology/approach
The project will require creating a platform for therapists where they can set up monitoring and receive dynamic networks visualization, creating an experience sampling application for patients connected to the platform and creating an optimal data visualization system that will enable therapists to accurately and quickly interpret the network. A series of participatory workshops, qualitative and quantitative studies are described.
Findings
The presented studies will enable us to evaluate the ergonomy of use of both platform and app in laboratory and ecological settings along with the evaluation of network interpretation accuracy.
Originality/value
To the best of the authors’ knowledge, this is the first participatory design protocol for creating a solution that might enable clinicians to use a dynamic network approach in their everyday clinical practice. The challenges and opportunities of creating this kind of mHealth solution are discussed.
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Haiying Liu, Weisong Ye and Huinan Wang
The purpose of this paper is to develop an integrity monitoring method using ERAIM (Extended Receiver Autonomous Integrity Monitoring) for the integrated GNSS/Inertial (Global…
Abstract
Purpose
The purpose of this paper is to develop an integrity monitoring method using ERAIM (Extended Receiver Autonomous Integrity Monitoring) for the integrated GNSS/Inertial (Global Navigation Satellite System and inertial navigation system) of general aviation aircraft.
Design/methodology/approach
First the tightly integrated GNSS with Strapdown Inertial Navigation System (GNSS/SINS) and the Kalman filter is designed. Then the processing of ERAIM is presented, in which the least‐squares theory is used to calculate the best estimators by integrating the predicted states with measurement states of Kalman filter. Based on the new measurement model, the integrity monitoring for GNSS/inertial system is carried out, including the fault detection, identification, reliability and separability. Lastly, the simulation and analysis for ERAIM vs RAIM are performed to validate the proposed method.
Findings
Simulation results show that the ERAIM method is able to detect and identify effectively any type of failure including step failure and ramp failure. Compared to the RAIM method for only GNSS, the ERAIM increases the redundant information and reduces the correlation of test statistics, as well as enhancing the reliability and thus can significantly improve the performance of integrity monitoring.
Practical implications
In safety critical sectors such as aviation, stringent integrity performance requirements must be met. The ERAIM method cannot only be used in integrity monitoring for the integrated GNSS/Inertial system, but also can be applied to only GNSS or other integrated navigation systems for general aviation aircraft.
Originality/value
The paper presents a new integrity monitoring method of ERAIM, which is able to improve the fault detection and identification capabilities significantly by extending GNSS‐used RAIM method into the GNSS/Inertial integrated system.
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Abeer A. Zaki, Nesma A. Saleh and Mahmoud A. Mahmoud
This study aims to assess the effect of updating the Phase I data – to enhance the parameters' estimates – on the control charts' detection power designed to monitor social…
Abstract
Purpose
This study aims to assess the effect of updating the Phase I data – to enhance the parameters' estimates – on the control charts' detection power designed to monitor social networks.
Design/methodology/approach
A dynamic version of the degree corrected stochastic block model (DCSBM) is used to model the network. Both the Shewhart and exponentially weighted moving average (EWMA) control charts are used to monitor the model parameters. A performance comparison is conducted for each chart when designed using both fixed and moving windows of networks.
Findings
Our results show that continuously updating the parameters' estimates during the monitoring phase delays the Shewhart chart's detection of networks' anomalies; as compared to the fixed window approach. While the EWMA chart performance is either indifferent or worse, based on the updating technique, as compared to the fixed window approach. Generally, the EWMA chart performs uniformly better than the Shewhart chart for all shift sizes. We recommend the use of the EWMA chart when monitoring networks modeled with the DCSBM, with sufficiently small to moderate fixed window size to estimate the unknown model parameters.
Originality/value
This study shows that the excessive recommendations in literature regarding the continuous updating of Phase I data during the monitoring phase to enhance the control chart performance cannot generally be extended to social network monitoring; especially when using the DCSBM. That is to say, the effect of continuously updating the parameters' estimates highly depends on the nature of the process being monitored.
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Jafar Ali and Debasish Bandyopadhyay
Condition monitoring (CM) of structures is important from safety consideration. Damage detection techniques, using inverse dynamic approaches, are important tools to improve the…
Abstract
Purpose
Condition monitoring (CM) of structures is important from safety consideration. Damage detection techniques, using inverse dynamic approaches, are important tools to improve the mathematical models for monitoring the condition of structure. Uncertainties in the measured data might lead to unreliable identification of damage in structural system. Experimental validation is crucial for establishing its practical applicability. The measurement of dynamic responses at all degrees of freedom (DOFs) of a structure is also not feasible in practice. In addition the effect of these uncertainties and constraint of limited measurement are required to be studied based on experimental validation. This paper aims to discuss these issues.
Design/methodology/approach
Proposed numerical model based on measured natural frequencies and mode shapes is found suitable for CM of framed structures in the framework of finite element model with limited dynamic responses. The structural properties, namely, axial rigidity and bending rigidity are identified at the element level in the updated models of the system. Damage at the element level is identified by comparing the identified structural parameters of the updated model of the system with those of the undamaged state. Proposed numerical model is suitable for practical problem, as it is able to identify the structural parameters with limited modal data of first few modes, measured at selected DOFs.
Findings
The model is able to identify the structural damage with greater accuracy from the noisy dynamic responses even if the extent of damage is small. Experimental studies, on simple cantilever beams, establish the potential of the proposed methods for its practical implementation.
Research limitations/implications
The greater random noise will lead to unreliable identification of structural parameters as observed. Thus, filtering of noise technique may be required to be adopted prior to consideration of the measured data in the proposed identification approach.
Practical implications
Requirement of higher modal data seems to be difficult in case of real life practical problem. Thus, simulation technique like condensation or SEREP technique may be adopted.
Social implications
Structural health monitoring of infrastructural system is significantly important. CM of those structures from global response with limited measured data seems to be an effective tool to ensure safety and durability of structures.
Originality/value
The modal testing and subsequent extraction of modal data have been carried out at the authors’ laboratory. The numerical code based on inverse dynamic approach has been developed independently with original contribution.
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Michael V. Gangone, Matthew J. Whelan, Kerop D. Janoyan and Levon Minnetyan
The purpose of this paper is to further validate a wireless sensor system developed at Clarkson University for structural monitoring of highway bridges. The particular bridge…
Abstract
Purpose
The purpose of this paper is to further validate a wireless sensor system developed at Clarkson University for structural monitoring of highway bridges. The particular bridge monitored employs a fiber reinforced polymer (FRP) panel system which is fairly innovative in the field of civil engineering design. The superstructure was monitored on two separate occasions to determine a change in structural response and see how the structural system performs over time.
Design/methodology/approach
A series of wireless sensor units was deployed at various locations of the steel superstructure, to measure both the modal response from acceleration measurements as well as quasi‐static and dynamic strain response. Ambient and forced loading conditions were applied to measure the response. Data results were compared over two separate periods approximately nine months apart.
Findings
The first eight mode shapes were produced from output‐only system identification providing natural frequencies ranging from approximately 6 to 42 Hz. The strain response was monitored over two different testing periods to measure various performance characteristics. Neutral axis, distribution factor, impact factor and end fixity were determined. Results appeared to be different over the two testing periods. They indicate that the load rating of the superstructure decreased over the nine month period, possibly due to deterioration of the materials or composite action.
Research limitations/implications
The results from the two testing periods indicate that further testing needs to be completed to validate the change in response. It is difficult to say with certainty that the significant change in response is due to bridge deterioration and not other factors such as temperature effects on load rating. The sensor system, however, proved to provide high quality data and responses indicating its successful deployment for load testing and monitoring of highway infrastructure.
Originality/value
The paper provides a depiction of the change in structural behavior of a bridge superstructure using a wireless sensor system. The wireless system provided high‐rate data transmission in real time. Load testing at two different points in time, eight months apart, showed a significant change in bridge behavior. The paper provides a practical and actual physical load test and rating during these two periods for quantifiable change in response. It is shown that the wireless system is capable of infrastructure monitoring and that possible deterioration is expected with this particular bridge design. Additionally, the load testing occurred during different seasons, which could create cause for temperature effects in load rating. This can provide a basis for future performance monitoring techniques and structural health monitoring.
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Yinhua Liu, Rui Sun and Sun Jin
Driven by the development in sensing techniques and information and communications technology, and their applications in the manufacturing system, data-driven quality control…
Abstract
Purpose
Driven by the development in sensing techniques and information and communications technology, and their applications in the manufacturing system, data-driven quality control methods play an essential role in the quality improvement of assembly products. This paper aims to review the development of data-driven modeling methods for process monitoring and fault diagnosis in multi-station assembly systems. Furthermore, the authors discuss the applications of the methods proposed and present suggestions for future studies in data mining for quality control in product assembly.
Design/methodology/approach
This paper provides an outline of data-driven process monitoring and fault diagnosis methods for reduction in variation. The development of statistical process monitoring techniques and diagnosis methods, such as pattern matching, estimation-based analysis and artificial intelligence-based diagnostics, is introduced.
Findings
A classification structure for data-driven process control techniques and the limitations of their applications in multi-station assembly processes are discussed. From the perspective of the engineering requirements of real, dynamic, nonlinear and uncertain assembly systems, future trends in sensing system location, data mining and data fusion techniques for variation reduction are suggested.
Originality/value
This paper reveals the development of process monitoring and fault diagnosis techniques, and their applications in variation reduction in multi-station assembly.
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Ana Paula C. Larocca, Ricardo Ernesto Schaal and Edvaldo Simões da Fonseca
This paper aims to detect small dynamic displacements by analysis of L1 Global Positioning System carrier frequency using an improved method for collecting data and filtering…
Abstract
Purpose
This paper aims to detect small dynamic displacements by analysis of L1 Global Positioning System carrier frequency using an improved method for collecting data and filtering techniques on monitoring large structures. It is proposed to analyze the phase residuals directly from the raw phase observable data collected in a short baseline during a limited time span, in lieu of obtaining the residual data file from regular GPS processing programs.
Design/methodology/approach
The approach of this paper is an update on the method based on the interferometer idea for analyzing the Global Positioning Systems signals applying adaptive filtering techniques on the phase residuals computed through the double difference adjusted by the 3rd order polynomial. The method is based on the frequency domain analysis of the phase residuals resulted from the L1 double difference static data processing of only two satellites.
Findings
This research improves the ability to characterize the dynamic behavior of large structures though the detection of millimeter‐level data of structural amplitude oscillation response and its frequency value.
Practical implications
Support of Civil Engineers by collaboration on monitoring oscillations of spans and towers of large bridges; determination of amplitude oscillations value and low‐frequency modal values. The paper presents two trials to verify the proposed methodology for using GPS as a tool for monitoring large structures.
Originality/value
The paper presents a comprehensive framework and implementation approach to demonstrate the capabilities of Global Positioning System as a tool for monitoring large structures providing accurate response data at high levels of precision.
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