M. Marzuki Mustafa

Robust on-line control of hexavalent chromium reduction process using a Kalman filter

Abstract In waste water where toxic hexavalent chromium ions are present, it is essential that the hexavalent chromium ions are reduced to the less harmful trivalent chromium ions by dosing with reducing agent such as ferrous sulphate. The problem posed in controlling such a reduction process is that chromium ions cannot be easily measured on-line. In such a process, oxidation-reduction potential (ORP) is widely used. The ORP value, apart from being dependent on the concentration of chromium ions, is also dependent on other redox processes due the presence of other ion species, concentration of ions, temperature, etc. For this reason, the reduction process cannot be effectively controlled using conventional set-point control. The profiles of the ORP during the reduction process shows certain characteristic features which can be used as an indication of the completion of the process. In this paper we have successfully demonstrated a robust switching algorithm using a Kalman filter to control the dosing pump for this reduction process.

Black-box modeling of low dropout voltage regulator based on two-port network parameter identification

Low dropout (LDO) voltage regulator is used to produce regulated, constant and stable input supplies in most electronic systems. Information on the internal circuit of LDO regulator is required for the purpose of fault identification and manufacturing process analysis at the system level. However this information is not provided by the LDO regulator manufacturer in the product datasheet. Therefore this paper proposed a black-box modeling approach to model and identify the behavioral characteristic of the commercial LDO regulator. The proposed black-box modeling approach identified all g-parameter transfer function of two-port network which represent the LDO regulator. The derived transfer functions were validated and the results obtained show that the black-box model of LDO regulator can be utilized for fault diagnostic at the system level.

Characterization of voltage regulators by automated equivalent series resistance

A capacitor with a suitable equivalent series resistance (ESR) characteristic is typically connected to the output terminal of a voltage regulator. This ESR must be characterized during the manufacturing process to identify the range of ESR values and to stabilize voltage regulator operation. This ESR range is characterized manually in current manufacturing practice. However, it is tedious, time-consuming, and limits manufacturing productivity rate. Therefore, the ESR characterization process should be simplified and its effectiveness enhanced. In line with this objective, this work mainly aims to automate the ESR characterization process of voltage regulators. Simulation was performed as the reference for subsequent ESR characterization experiments. After investigating manual characterization outcomes, automated ESR characterization was conducted. A stepper motor controlled by the microcontroller was used to automatically change the ESR values. Results show that the automated ESR characterization approach is simple and can effectively reduce characterization time.

GLOBAL FEATURE FOR LEFT VENTRICULAR DYSFUNCTION DETECTION BASED ON SHAPE DEFORMATION TRACKING

Left ventricular (LV) shape alteration is closely correlated with cardiac disease and LV function. In this paper, we propose a feature to detect LV dysfunction globally by analyzing the LV shape deformation in systolic contraction. The feature is an index that is extracted from geometric measurement of LV shape such as the length of the long axis, the short axis, and the apical diameter. A framework for computing the features is also proposed that consists of shape model construction and motion estimation of myocardial boundary. The LV shape model is extracted from apical 2 and 4 chamber views of 2D echocardiography. The long axis, the short axis, and the apical diameter were redefined according to the LV shape constructed. An optical flow technique was used to estimate the position of the LV boundary in each frame. The classification of the LV dysfunction was performed using linear discriminant analysis (LDA) and neural networks (NNs). The 2D echocardiography dataset collected from routine clinical check-up were used to validate the proposed method by comparing the computation result and cardiac expert diagnose. Classification performance and statistical analysis, which was performed to discriminate between healthy and diseased data, indicated promising results. The global LV features would provide a strong basis for a global LV function diagnosis and a global cardiac pathology assessment.

Inter-rater reliability of accessing the intelligibility of band-limited transformed speech using nonlinear frequency compression

Speech intelligibility verification through a listening test session by human raters was conducted to assess the intelligibility of band-limited speech. The band-limited speech was generated using nonlinear frequency compression via spectral envelope transformation to assist individuals with high-frequency hearing loss. However, addressing the issue on the reliability of the assessment method is important because of the human factors that cause variability in the intelligibility test results. This study investigated the use of Cohens Kappa coefficient to measure the inter-rater reliability in the intelligibility test. The inter-rater reliability was found to be high when Cohens Kappa coefficient was over 0.6. The result indicates that the human raters showed a high level of agreement in assessing the intelligibility of the band-limited speech.

Shape deformation descriptor using Fourier analysis

Deformation analysis of left ventricle (LV) shape could provide a new quantitative understanding of its abnormality. Currently, there is established motion estimation that allows accurate tracking of every point on the 2D echocardiography (2DE). This method produces a precise movement vector of each point in 2DE sequence. Analyzing this data using Fourier analysis could produce a new pattern to determine normal and abnormal deformation of LV. Observation of this method was performed on dataset acquired from 10 normal subjects and 10 patients. Two standard views (apical 2 and 4 chamber) were analyzed using a proposed technique to determine a novel insight of deformation. The results obtained are very promising and could be used as reference for future cardiac abnormality detection.

Myocardial Motion Analysis Using Modified Radial Direction Distribution Based on Magnitude Criteria

Accurate information on myocardial motion is important in diagnosing cardiac abnormalities. In this research, the motion vectors are computed using an optical flow technique and further analyzed based on the magnitude and angle. We utilize a relative motion direction with respect to the center of the cavity, which is more useful for diagnosis because a physician can observe whether a segment is moving to the center or not more clearly. Instead of analizing individual vectors, it is more helpful to visualize the overall trend by performing their angular distribution. However, a common angular distribution considers motions with small and large magnitudes to have only an equal contribution and often fails to represent an accurate motion direction of a segment if there is a wide distribution of vector angles in the respective segment. In this paper, we propose a new method of providing an accurate radial direction profile by modifying the contribution of the motion vectors to the radial direction distribution based on a certain magnitude function. This method has been tested on clinical echocardiography sequences and shown to be successful in providing a more accurate radial direction profile compared with the common angular distribution.