Inferior canaliculi punctal granuloma of the lacrimal system: a case report

Pyogenic granuloma of the eyes usually occurs after ocular surgery or inflammation related to the eyes, itself. This lesion is commonly related to procedures associated with chalazia, strabismus, or even enucleation. However, the incidence of pyogenic granuloma that arises directly from the lower canaliculi of the nasolacrimal system is rare and not being extensively reported. We report a case of an elderly lady who presented with pyogenic granuloma post EDCR with silicone stenting for left nasolacrimal duct obstruction. She presented with persistent left eye epiphora following procedure. The unusual site for pyogenic granuloma and it occurrence after EDCR raise the possibility that the condition is related to previous procedure and the material being used

An Approach of Fuzzy Logic H∞ Filter in Mobile Robot Navigation Considering Non-Gaussian Noise

This chapter has presented an analysis of H∞ filter‐based mobile robot navigation with fuzzy logic to tolerate in non‐Gaussian noise conditions. The technique exploits the information obtained through H∞ filter measurement innovation to reduce the noises or the uncertainties during mobile robot observations. The simulation results depicted that the proposed technique has improved the mobile robot estimation as well as any landmark being observed. Different aspects such as γ values, noise parameters, intermittent measurement data lost and finite escape time issues are also analysed to investigate their effects in estimation. Different fuzzy logic design configurations were also studied to achieve better estimation results. As demonstrated in this work, fuzzy logic offers reliable estimation results compared to the conventional technique

A Solution to Partial Observability in Extended Kalman Filter Mobile Robot Navigation

Partial observability in EKF based mobile robot navigation is investigated in this paper to find a solution that can prevent erroneous estimation. By only considering certain landmarks in an environment, the computational cost in mobile robot can be reduced but with an increase of uncertainties to the system. This is known as suboptimal condition of the system. Fuzzy Logic technique is proposed to ensure that the estimation achieved desired performance even though some of the landmarks were excluded for references. The Fuzzy Logic is applied to the measurement innovation of Kalman Filter to correct the positions of both mobile robot and any observed landmarks during observations. The simulation results shown that the proposed method is capable to secure reliable estimation results even a number of landmarks being excluded from Kalman Filter update process in both Gaussian and non-Gaussian noise conditions

Improving Covariance Matrix Diagonalization in SLAM of Mobile Robot

Diagonalization of covariance matrix through eigenvalue approach in extended Kalman Filter (EKF)-based simultaneous localization and mapping (SLAM) of mobile robot has been studied, as one of the possible approaches in reducing complexity hence computational cost of the system. However, the estimation is seemed to be too optimistic, and further investigation need to be conducted. In this paper, the effect on addition of Pseudo elements in the diagonalization process is investigated. It is evaluated at the updated state covariance matrix of EKF-based SLAM. It is found that the additional of pseudo components in diagonal matrix can improve the covariance matrix and lower the computational complexity. This finding has been proved through simulation

Effect of Magnetic Graphene Oxide on Heavy Oil Demulsification

Chemical demulsification is the most efficient demulsification approach that can attain the desired separation efficiency and meet the environmental regulation standards whilst impose minimal economic burden on the petroleum industry. However, current demulsification methods using chemical demulsifiers suffer from significant secondary pollution, particularly after the demulsification process. Therefore, in this work, magnetic graphene oxide (MGO) was synthesized by a one-step co-precipitation method from graphene oxide (GO). The properties of MGO were then characterized by X-ray diffraction and Fourier transform infrared. MGO was successfully synthesized and used as the demulsifier for diluted heavy oil emulsions. Different MGO concentrations (40, 80, 120, 160, and 200 ppm) were used at different water cuts (20:80, 30:70, 40:60, 50:50, and 60:40 v/v%). Demulsification tests using the bottle test method indicated that MGO could separate the emulsions up to 99.98% efficiency due to the high surface area-to-volume ratio of nanoparticles and magnetic features, which enhanced the adsorptive capacity for separating water from the oil. The residual oil content in the separated water was then analyzed by an ultraviolet-visible spectrophotometer. The oil concentration in the separated water reduced to 398.8 mg/ml, corresponding to a demulsification efficiency of 99.98% observed at 40 ppm MGO concentration. The interfacial tension of the emulsions during demulsification was also analyzed, where the interfacial tension decreased with increasing MGO concentration

Effect of Magnetic Graphene Oxide on Heavy Oil Demulsification

Chemical demulsification is the most efficient demulsification approach that can attain the desired separation efficiency and meet the environmental regulation standards whilst impose minimal economic burden on the petroleum industry. However, current demulsification methods using chemical demulsifiers suffer from significant secondary pollution, particularly after the demulsification process. Therefore, in this work, magnetic graphene oxide (MGO) was synthesized by a one-step co-precipitation method from graphene oxide (GO). The properties of MGO were then characterized by X-ray diffraction and Fourier transform infrared. MGO was successfully synthesized and used as the demulsifier for diluted heavy oil emulsions. Different MGO concentrations (40, 80, 120, 160, and 200 ppm) were used at different water cuts (20:80, 30:70, 40:60, 50:50, and 60:40 v/v%). Demulsification tests using the bottle test method indicated that MGO could separate the emulsions up to 99.98% efficiency due to the high surface area-to-volume ratio of nanoparticles and magnetic features, which enhanced the adsorptive capacity for separating water from the oil. The residual oil content in the separated water was then analyzed by an ultraviolet-visible spectrophotometer. The oil concentration in the separated water reduced to 398.8 mg/ml, corresponding to a demulsification efficiency of 99.98% observed at 40 ppm MGO concentration. The interfacial tension of the emulsions during demulsification was also analyzed, where the interfacial tension decreased with increasing MGO concentration

Data Association Analysis In Simultaneous Localization And Mapping Problem

This paper examines the data association issues in Simultaneous Localization and Mapping Problem on two different techniques. Data association determines the system  efficiency and there are limited numbers of papers attempts to analyze the conditions. Two filters namely the Extended Kalman Filter(EKF) and H∞ Filters are considered in this paper to improved the estimation results of both mobile robot and the environment locations. The updated state covariance is modified to obtain better performance compared to its original state. The simulation results have shown consistency and lower percentage of errors for the proposed technique. However, there are certain cases that showing the updated state covariance becomes unstable and yields erroneous results especially for EKF. Hence, further works are expected to be carried for this matter

Investigation of the optimal sensor location and classifier for human motion classification

Human motion monitoring by means of wearable technologies is not uncommon nowadays. This demonstrates the growing awareness of the importance of healthy lifestyle. Human body motion involves the movement of multiple muscles and joints. However, the optimal location of sensor placement on the body to record the motion in daily activities has not been well understood. This study aims to find the best sensor location for this purpose among three locations on the body, that is on the back, shank, or wrist. In addition, this study seeks to find the best classification algorithm for human daily activities. The data recorded at these three locations were analysed using several classification algorithms in both Orange software and MATLAB. The results show that the sensor on the wrist provided the best classification result, thereby suggesting that wrist is the best place on the body to place the sensor for human motion monitoring. With regards to classification algorithm, we found that Neural Network provides the most accurate classification as compared to other algorithms. Future development of wearables should look into integrating classification algorithm in the system, thus the human motion monitoring will provide a richer information and not only limited to number of steps and calories burned

Beam Steering using the Active Element Pattern of Antenna Array

An antenna array is a set of a combination of two or more antennas in order to achieve improved performance over a single antenna. This paper investigates the beam steering technique using the active element pattern of dipole antenna array. The radiation pattern of the array can be obtain by using the active element pattern method multiplies with the array factor. The active element pattern is crucial as the mutual coupling effect is considered, and it will lead to an accurate radiation pattern, especially in determining direction of arrival (DoA) of a signal. A conventional method such as the pattern multiplication method ignores the coupling effect which is essential especially for closely spaced antenna arrays. The comparison between both techniques has been performed for better performance. It is observed that the active element pattern influenced the radiation pattern of antenna arrays, especially at the side lobe level. Then, the beam of the 3x3 dipole antenna array has been steered to an angle of 60° using three techniques; Uniform, Chebyshev and Binomial distribution. All of these are accomplished using CST and Matlab software

Beam steering using the active element pattern of antenna array

An antenna array is a set of a combination of two or more antennas in order to achieve improved performance over a single antenna. This paper investigates the beam steering technique using the active element pattern of dipole antenna array. The radiation pattern of the array can be obtain by using the active element pattern method multiplies with the array factor. The active element pattern is crucial as the mutual coupling effect is considered, and it will lead to an accurate radiation pattern, especially in determining direction of arrival (DoA) of a signal. A conventional method such as the pattern multiplication method ignores the coupling effect which is essential especially for closely spaced antenna arrays. The comparison between both techniques has been performed for better performance. It is observed that the active element pattern influenced the radiation pattern of antenna arrays, especially at the side lobe level. Then, the beam of the 3x3 dipole antenna array has been steered to an angle of 60° using three techniques; Uniform, Chebyshev and Binomial distribution. All of these are accomplished using CST and Matlab softwar