Parameter Estimation of K-Distributed Clutter Based on Fuzzy Inference and Gustafson-Kessel Clustering

The detection performance of maritime radars is restricted by the unwanted sea echo or clutter which is the vector sum of scattering from the sea surface. The echo is noise-like and is expected from a set of randomly moving scatters. Although the number of these target-like data is small, they may cause false alarm in maritime radar and perturb the target detection. K-distribution is known as the best fitted probability density function for the radar sea clutter. The accurate and fast parameter estimation of K-distribution for small number of sea clutter radar data is crucial task to avoid irreparable disasters. A novel approach to estimate the parameters of K-distribution based on fuzzy inference has been proposed in the thesis. Takagi-Sugeno Kang (TSK) model has been chosen since human knowledge is unavailable to be captured, whereas the sea clutter for specific parameter can be easily generated. GK- clustering has been used in order to identify the membership function of the antecedent parts. Least Square Method has been utilized to estimate the parameter of the K-distribution, which is represented in the consequent part of the fuzzy inference system. For a real-time implementation of the proposed method, vectorized programming technique has been implemented. In comparison with the conventional methods, this technique has less computational complexity, needs lesser time to train and estimates faster than any existing methods. Since the method is clustering based, some kind of pre-knowledge (rough estimation) is naturally stored in the structure of the TSK-fuzzy system and Least Square provides a mechanism to fine tune the consequent parameters. The novelty of the proposed method is the incorporation of the clustering (as a pre-estimator) with the estimation process. The resultant estimator then overcomes the bottleneck of the existing methods and is capable of handling even a small number of data

Parameter estimation of K-distributed sea clutter based on fuzzy inference and Gustafson-Kessel clustering

The detection performance of maritime radars is restricted by the unwanted sea echo or clutter. Although the number of these target-like data is small, they may cause false alarm and perturb the target detection. K-distribution is known as the best fit probability density function for the radar sea clutter. This paper proposes a novel approach to estimate the parameters of K-distribution, based on fuzzy Gustafson–Kessel clustering and fuzzy Takagi–Sugeno Kang modelling. The main contribution of the proposed method is the ability to estimate the parameters, given a small number of data which will usually be the case in practical applications. This is achieved by a pre-estimation using fuzzy clustering that provides a prior knowledge and forms a rough model to be fine tuned using the least square method. The algorithm also improves the calculations of shape and width of membership functions by means of clustering in order to improve the accuracy. The resultant estimator then acts to overcome the bottleneck of the existing methods in which it achieves a higher performance and accuracy in spite of small number of data

Universal controller for monotone systems inspired from fuzzy logic control

This paper starts with formulation of monotone fuzzy system and then proposes a formula based universal controller for class of monotone systems which is inspired from fuzzy logic control by extending the number of fuzzy sets into infinity. After taking the limit, the fuzzy rule table is replaced by an explicit formula and consequently the needed memory space is minimized. It is shown that this controller can be approximated by a linear state feedback controller followed by a nonlinear saturation function. Furthermore, the optimal control solution and global asymptotic stability for a monotone control system are shown. The experimental results show that the crisp fuzzy-inspired controllers have the same or in some cases better performance and stability with extra merit of lower memory space and cycle time

Minimum rule-based parallel structure fuzzy controller

One of the most important issues in fuzzy logic controller design is the number of fuzzy subsets for inputs and outputs. The number of fuzzy terms should be big enough to achieve sufficient approximation and must be small enough to save the space of memory. There is a trade off between approximation and memory space (algorithm cycle time). This paper proposes a simple parallel structure of fuzzy controllers where simulation is performed on a real temperature model. It can be shown that the proposed parallel structure fuzzy controllers has the same performance and stability compared with the conventional fuzzy controller, with an advantage of significantly lower number of rules. This can save memory space and reduces cycle time which is an important element in practical implementation problems

Association between Occupational Exposure to Mineral Dust and Blood Lipid Parameters

Background: Epidemiological studies have shown a change in blood biochemical parameters due to short and long exposure to airborne particles. Long Exposure to airborne particles can increase the risk of blood lipid disorders through oxidative stress. Therefore, this study was conducted to evaluate the relationship between respiratory exposure with inhaled particles and blood lipid parameters in workers of a ceramic tile factory. Methods: In this descriptive-analytical study, a sample size based on similar studies and Cochran formula, 128 healthy workers (77 exposed and 51 unexposed) were estimated in the age range of 24-40 years and randomly selected from among the factory workers. Sampling of the breathing region of all individuals was performed to determine the concentration of respirable particles based on the NIOSH_0600 method. Blood lipid parameters of people having cholesterol, triglyceride, HDL, and LDL were measured using standard methods. The data were analyzed using SPSS version 20 software. Results: The Mean of exposure to respirable particles in different units were 73.29 ± 7.75 mg / m3 and lower than standard (3 mg / m3). In this study, the levels of triglyceride and HDL were higher in the exposed group and the mean of these two parameters were statistically different. There was no correlation between lipid parameters and density of respirable particles and work experience (P value> 0.05); however, the body mass index had a positive correlation with cholesterol, triglyceride and HDL. Moreover, cholesterol and triglycerides showed a positive correlation with systolic hypertension. Conclusion: Exposure to particles has relationship with levels of lipid-related markers factors and can change the level of some of the lipid parameters. Therefore, protecting workers in units with high levels of dust and constant efforts to train and supervise workers to enhance safety and monitoring the proper and consistent use of these equipment is essential

Performance of Pregnant Women on Folic Acid Intake

The cause of neural tube defects (NTDs) is multifactorial and in this case folic acid has an important role. Since the neural tube is closed during 21-28 days of pregnancy, most of women are not informed about their pregnancy at this time, and as a result the golden time of folic acid consumption is missed. The aim of this study was evaluating the performance of pregnant women attending to Tehran Women's Hospital in regard to folic acid intake during pre-conceptional period between 2011 and 2012. This cross-sectional study was conducted in 370 pregnant women attending the prenatal clinic of a hospital affiliate to Tehran University of Medical Sciences between 2011 and 2012. Data were collected through interview using a questionnaire. Although 70% of the pregnancies were planned, but 70.5% of pregnant women had not taken folic acid before conception or in necessary time. There was found a significant relationship between level of education, history of abnormalities in children and the number of abortions and taking folic acid before pregnancy (P=0.005, P=0.000 and P=0.000, respectively)