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Electrical capacitance tomography (ECT) and electrical resistance tomography (ERT) are promising techniques for multiphase flow measurement due to their high speed, low cost, non-invasive and visualization features. There are two major difficulties in image reconstruction for ECT and ERT: the “soft-field”effect, and the ill-posedness of the inverse problem, which includes two problems: under-determined problem and the solution is not stable, i.e. is very sensitive to measurement errors and noise. This paper aims to summarize and evaluate various reconstruction algorithms which have been studied and developed in the word for many years and to provide reference for further research and application.

In the past 10 years, various image reconstruction algorithms have been developed to deal with these problems, including in the field of industrial multi-phase flow measurement and biological medical diagnosis.

This paper reviews existing image reconstruction algorithms and the new algorithms proposed by the authors for electrical capacitance tomography and electrical resistance tomography in multi-phase flow measurement and biological medical diagnosis.

The authors systematically summarize and evaluate various reconstruction algorithms which have been studied and developed in the word for many years and to provide valuable reference for practical applications.

In some developing countries, vehicles are often over‐loaded, which causes road accidents and damage to road surfaces. Currently, large measuring facilities are used to measure the vehicle‐loading on highways. A major limitation is that they can measure vehicle‐loading at fixed locations only. This paper seeks to present an on‐vehicle loading measurement system with capacitance and acceleration transducers.

A description and analysis of the system are presented.

The capacitance transducers sense the variation in distance between electrodes, using the on‐vehicle leaf springs as weighing elastomers. The acceleration transducers deal with the influence of acceleration to vehicle‐loading measurement. The major advantage of this system over the existing systems is that both static and dynamic loading can be measured.

This system is simple and easy to install.

The paper shows that with this system both a driver and an inspector can check vehicle‐loading at any time and any location through radio communication, thus identifying over‐loaded vehicles on highways.

The purpose of this paper is to present the sensing mechanism, design issues, performance evaluation and applications for planar capacitive sensors. In the context of characterisation and imaging of a dielectric material under test (MUT), a systematic study of sensor modelling, features and design issues is needed. In addition, the influencing factors on sensitivity distribution, and the effect of conductivity on sensor performance need to be further studied for planar capacitive sensors.

While analytical methods can provide accurate solutions to sensors of simple geometries, numerical modelling is preferred to obtain sensor response to different design parameters and properties of MUT, and to derive the sensitivity distributions of various electrode designs. Several important parameters have been used to evaluate the response of the sensors in different sensing modes. The designs of different planar capacitive sensor arrays are presented and experimentally evaluated.

The response features and design guidelines for planar capacitive sensors in different sensing modes have been summarised, showing that the sensor in the transmission mode or the single‐electrode mode is suitable for material characterisation and imaging, while the sensor in the shunt mode is suitable for proximity/displacement measurement. The sensitivity distribution of the sensor depends largely on the geometry of the electrodes. Conductivity causes positive changes for the sensor in the transmission and single‐electrode mode, but negative changes for the sensor in the shunt mode. Experimental results confirm that sensing depths of the sensor arrays and the influence of buried conductor on capacitance measurements are in agreement with simulations.

Experimental verification is needed when a sensor is designed.

This paper provides a comprehensive study for planar capacitive sensors in terms of sensor design, evaluation and applications.

The purpose of this paper is to present an analytical model and implementation of a prototype electro‐magnetic tomography (EMT) sensor system. Sensitivity maps for an EMT sensor are usually calculated using a numerical approach, such as the finite element method (FEM). While FEM can produce accurate results for any geometrical layout, intensive computation is needed to solve the forward problem and to obtain the sensitivity maps. An alternative approach is to develop an analytical model for the same purpose.

Although the applicability of the analytical model is limited to certain geometrical cases, it provides a much faster means, in particular for calculating sensitivity maps, than FEM. The paper gives brief insight into the calculations and some details on its implementation. The results obtained with the analytical model are compared with FEM.

The results having been obtained with the analytical model and compared with FEM, it has been shown that the differences are as small as 6 per cent and that the prototype EMT sensor system can reconstruct images with an error under 10 per cent (of the object size) in the true position.

This is the first time an analytical model has been used to calculate sensitivity maps for EMT.

In the context of multi-sided platforms (MSPs), the authors address the evaluation of search- and experience-based information and the effect on different components of user satisfaction.

The instrument was developed by either modifying previous measures or developing new scales. The authors collected the sample of experienced 300 TripAdvisor users via online questionnaire survey of a customer panel. The structural equation modeling (SEM) package (AMOS) with the maximum likelihood estimation method was used to test the sample data.

Attitudes toward search-based information can foster user satisfaction with information interaction rather than user satisfaction with social interaction. Attitudes toward experience-based information can foster user satisfaction with information interaction and user satisfaction with social interaction. The motivation for information interaction is stronger than the motivation for social interaction to enhance user satisfaction with information quality.

The distinction between search- and experience-based information provides different route messages to develop the attitude-driven framework of platform-enabled interactions.

The support for platform-enabled interactions to enhance the motivation for information and social interactions should be aligned with the evaluation of information quality.

The satisfaction-driven framework has been widely used to examine the post-adoption of information technologies (IT). In contrast, the attitude-driven framework was less examined in the literature. The authors develop a research model based on the attitude-driven framework to examine the platform-enabled interactions that can foster repeated intention.

Circular pipelines are mostly used for pneumatic conveyance in industrial processes. For optimum and efficient production in industries that use a pipeline for conveyance, tomographic image of the transport particles is paramount. Sensing mechanism plays a vital role in process tomography. The purpose of this paper is to present a two‐dimensional (2‐D) model for sensing the characteristics of electrostatic sensors for electrical charge tomography system. The proposed model uses the finite‐element method.

The domain is discretized into discrete shapes, called finite elements, by using a MATLAB. Each of these elements is taken as image pixels, on which the electric charges carried by conveyed particles are transformed into equations. The charges' interaction and the sensors installed around the circumference, at the sensing zone of the conveying pipeline are related by the proposed model equations. A matrix compression technique was also introduced to solve the problem of unevenly sensing characteristics of the sensors due to elements' number's concentration. The model equations were used to simulate the modeled electrostatic charge distribution carried by the particles moving in the pipeline.

The simulated results show that the proposed sensors are highly sensitive to electrostatic charge at any position in the sensing zone, thereby making it a good candidate for tomographic image reconstruction.

Tomographic imaging using finite element method is found to be more accurate and reliable compared to linear and filtered back projection method.