A Study of the Effect of Electrode Dimensions on Scaling Up ERT Applications

Electrical Tomography is a versatile and non-invasive, and robust imaging technique that is vastly applied for both industrial and medical process imaging. One of the crucial factors that influence the quality of image reconstruction is the dimension of electrodes. When implementing ERT in a real industrial setting, the scaling-up procedure from lab-scaled model, is typically based on researchers' past experiences. This work investigates the effect of varying electrode dimensions with respect to the scaled-up dimension on ERT imaging. Sensitivity analysis was done to investigate the effect of the different widths of electrodes. However, the results were found to be inconclusive, as there are insignificant differences in sensitivity magnitudes, regardless of the widths of electrodes. A comparative study for the image reconstruction obtained using different width of a 16electrodes model is used as a platform for this illustration. Results show that images reconstructed produced from the wider electrodes provides better quality in terms of colour contrast and estimation of dimension of the imaged object, using image reconstructed from lab scale model as reference

3D tomographic imaging using ad hoc and mobile sensors

The aim of this research is to explore the integration of ad hoc and mobile sensors into a conventional Electrical Resistance Tomography (ERT) system. This is motivated by the desire to improve the spatial resolution of 3D reconstructed images that are produced using ERT. The feasibility of two approaches, referred to as the Extended Electrical Tomography (EET) and Augmented Electrical Tomography (AET) are considered. The approaches are characterized according to the functionality of the sensors on the ad hoc 'pills'. This thesis utilizes spectral and numerical analysis techniques, with the goal of providing a better understanding of reconstruction limitations, including quality of measurements, sensitivity levels and spatial resolution. These techniques are applied such that an objective evaluation can be made, without having to depend heavily on visual inspection of a selection of reconstructed images when evaluating the performance of different set-ups. In EET, the sensors on the pills are used as part of the ERT electrode system. Localized voltage differences are measured on a pair of electrodes that are located on an ad hoc pill. This extends the number of measurements per data set and provides information that was previously unobtainable using conventional electrode arrangements. A standalone voltage measurement system is used to acquire measurements that are taken using the internal electrodes. The system mimics the situation that is envisaged for a wireless pill, specifically that it has a floating ground and is battery-powered. For the present exploratory purposes, the electronic hardware is located remotely and the measured signal is transmitted to the PC through a cable. The instrumentation and data acquisition circuits are separated through opto-isolators which essentially isolates both systems. Using a single pill located in the centre of a vessel furnished with 16 electrodes arranged in a single plane, spectral analysis indicates that 15 of the 16 extended measurements acquired using the adjacent current injection strategy are unique. Improvement is observed for both the sensitivity and spatial resolution for the voxels in the vicinity of the ad hoc pill when comparing the EET approach with the conventional ERT approach. This shows the benefit of the EET approach. However, visual inspection of reconstructed images reveals no apparent difference between images produced using a regular and extended dataset. Similar studies are conducted for cases considering the opposite strategy, different position and orientation of the pill, and the effect of using multiple pills. In AET, the sensors on the ad hoc pills are used as conductivity probes. Localized conductivity measurements provide conductivity values of the voxels in a discretized mesh of the vessel, which reduces the number of unknowns to be solved during reconstruction. The measurements are incorporated into the inverse solver as prior information. The Gauss-Newton algorithm is chosen for implementation of this approach because of its non-linear nature. Little improvement is seen with the inclusion of one localized conductivity measurement. The effect on the neighbouring voxels is insignificant and there is a lack of control over how the augmented measurement influences the solution of its neighbouring voxels. This is the first time that measurements using ad hoc and 'wireless' sensors within the region of interest have been incorporated into an electrical tomography system.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

An adaptive data processing framework for cost- effective covid-19 and pneumonia detection

Medical imaging modalities have been showing great potentials for faster and efficient disease transmission control and containment. In the paper, we propose a costeffective COVID-19 and pneumonia detection framework using CT scans acquired from several hospitals. To this end, we incorporate a novel data processing framework that utilizes 3D and 2D CT scans to diversify the trainable inputs in a resource-limited setting. Moreover, we empirically demonstrate the significance of several data processing schemes for our COVID-19 and pneumonia detection network. Experiment results show that our proposed pneumonia detection network is comparable to other pneumonia detection tasks integrated with imaging modalities, with 93% mean AUC and 85.22% mean accuracy scores on generalized datasets. Additionally, our proposed data processing framework can be easily adapted to other applications of CT modality, especially for cost-effective and resource-limited scenarios, such as breast cancer detection, pulmonary nodules diagnosis, etc

Feasibility Study of Using Acoustic Signal for Material Identification in Underwater Application Using a Single Transceiver

Structural inspection is a process to evaluate the condition of a structure in order to determine whether cracks, flaws defects or damages occur in structural build. This work explores the feasibility study of using acoustic signal as a sensing modality for material identification in underwater application with a single transceiver. Using the measured reflected signal, a reflection coefficient for different material types is calculated and compared to that of an ideal or standard case. Various materials with different density and surface reflection properties were used as test objects with respect to the optimum operating frequency in this work. Early results indicate that there is potential for further exploration in utilizing acoustic signal for structural inspection underwater

Fingerprint Recognition Using a Hybrid of Minutiae- and Image-Based Matching Techniques

Biometrics recognition has been one of the standout research areas in the past decades as the demand for security systems increases. Fingerprint recognition remains as a popular choice for the ease of acquiring such data and it is universally accepted as a feature that is unique to all individuals. One of the limitations of existing fingerprint recognition techniques is that the systems tend to fall short when the available fingerprint is of low quality. This work describes a hybrid method that improves the performance of fingerprint recognition technique by using a combination of minutiae-based and image-based techniques, extracting features from both techniques to compensate the limitations of each of them. Results show that the proposed hybrid method is capable of achieving better recognition rate. Further analyses indicate that the percentage of similarity score and the Euclidean distance computation are both improved

Development of a self-sufficient Ad Hoc Sensor to Perform Electrical impedance tomography measurements from within imaged space

Electrical Impedance Tomography (EIT) is an ill-posed problem whereby there are insufficient measured data to solve for a large amount of unknowns (finite elements). Conventionally, EIT measurements are performed on the boundary of an object or a process vessel. This results in a lower spatial resolution in central regions far off the conventional periphery electrodes. This paper presents the development of a self-sufficient EIT sensor with an aim to obtain EIT measurements from any locality within the object or the process vessel. An ad hoc EIT sensor that performs the current injection and voltage measurement around two pairs of electrodes is developed. The sensor consists of a current source, voltage amplifier, multiplexers, and microcontroller. Tests were conducted on a phantom tank. The sensor successfully performs localized voltage measurements from the interior of the imaged space with channel SNR average of 15dB

Trajectory pattern mining via clustering based on similarity function for transportation surveillance

Recently, surveillance on moving vehicles for traffic flow monitoring has emerging in rapid rate. A comprehensive traffic data, that is vehicle trajectory, is selected as reliable data for discovering the underlying pattern via trajectory mining. As the task of monitoring moving vehicles via vehicle trajectory dataset can be tedious, researchers are keen to provide solutions that reducing the tedious task performed by the traffic operators. One of the solutions is to group the vehicle trajectory data according to the shape of the patterns. This grouping task is called as clustering. Each of the clusters formed represents a pattern. In this paper, the analysis of the implemented clustering algorithm on the trajectory data with similarity function is presented. Discussion on the issues concerning the trajectory clustering is also presented