Implementation of Objects Recognition in Seismic Image via Artificial Neural Network (ANN)

Seismic image processing is necessary in oil and gas exploration to identify the existence of potential reservoir by classifying the seismic image into different sections. These sections, also known as objects made up of different patterns which portraying the structure of subsurface. This project aims to develop a data mining algorithm embedded in a system that has ability to recognize the objects of channel and fault in seismic image. The method chosen is artificial neural network (ANN) which consists of input layer, hidden layer and output layer. Each layer is made up of numbers of neuron nodes to receive input data from preceding layers and output value to next layer until final output is determined from output layer. The ANN is trained and tested via MATLAB Neural Network Pattern Recognition Toolbox (nprtool) and MATLAB Neural Network Toolbox (nntool). 2-dimension (2D) seismic image is converted into gray scale image via MATLAB Image Processing Toolbox (imtool) and Grey-level co-occurrence matrix (GLCM) which serve as input to the ANN is retrieved from the gray scale image. Result is displayed by the system informing user whether the input image is channel, fault or neither both

One-Way Random Effects Model For Asymmetric Trimmed Means

There are two very important concerns for the random effects model. The first concern being the assumption of equal variances of groups and the second concern is assuming normality. Violations of these result in unsatisfactory Type I errors and considerable loss of power. Jeyaratnam-Othman (1985) addresses the first concern in dealing with unequal variances while assuming normality. Wilcox in 1994 continued the study by suggesting a generalization on Jeyaratnam-Othman’s procedure based on symmetric trimmed means. The procedure resulted in significant gain in power but was unsatisfactory for skewed distributions with unequal group sizes. This research replaces Wilcox’s symmetric trimmed means with asymmetric ones aiming to obtain good, if not, better Type I errors. Two hinge estimators by Reed and Stark (1996), Q1 and Q2, were employed to obtain the asymmetric trimmed means for this research. Simulations were carried out for Jeyaratnam-Othman (1985), Wilcox (1994) and the two proposed procedures for a four-group design subjected to different data distributions. Good control of Type I errors was evident for both proposed procedures for balanced designs with values ranging from 0.026 to 0.082. Good power averaging 0.782 was also obtained. However, power and Type I errors for the unbalanced design were very unsatisfactory

Flavor Profiles of Oklahoma-Grown Peanuts

The main objective of this study is to examine flavor characteristics of peanut varieties developed through traditional breeding and genetic engineering. Traditional varieties, NC 7, Jupiter, Florunner, Tamrun 96, Tamrun OL 01, Tamrun OL 02, Tamspan 90, and OLin were grown at Fort Cobb, Oklahoma. The genetically modified peanut (GMP) varieties, 188, 540 and 654 were from the USDA-ARS in Stillwater, Oklahoma. Variety Okrun was examined as a control for the genetically engineered peanut lines. The flavor analysis was performed using sensory evaluation and a gas chromatograph/mass spectrometer (GC/MS) equipped with an olfactory sniff-port. Traditional varieties were evaluated by a trained sensory panel for 18 attributes. The peanut samples were also analyzed for their moisture, ash, protein, sugar, and oil composition. Experimental results showed that the variations in nutritional composition of peanut varieties examined in this study were minimal. There were minor differences in flavor attributes among the samples.Department of Plant and Soil Science

Implementation of Objects Recognition in Seismic Image via Artificial Neural Network (ANN)

Seismic image processing is necessary in oil and gas exploration to identify the existence of potential reservoir by classifying the seismic image into different sections. These sections, also known as objects made up of different patterns which portraying the structure of subsurface. This project aims to develop a data mining algorithm embedded in a system that has ability to recognize the objects of channel and fault in seismic image. The method chosen is artificial neural network (ANN) which consists of input layer, hidden layer and output layer. Each layer is made up of numbers of neuron nodes to receive input data from preceding layers and output value to next layer until final output is determined from output layer. The ANN is trained and tested via MATLAB Neural Network Pattern Recognition Toolbox (nprtool) and MATLAB Neural Network Toolbox (nntool). 2-dimension (2D) seismic image is converted into gray scale image via MATLAB Image Processing Toolbox (imtool) and Grey-level co-occurrence matrix (GLCM) which serve as input to the ANN is retrieved from the gray scale image. Result is displayed by the system informing user whether the input image is channel, fault or neither both

Adventurism: Singapore adventure tourists in the new economy

Master'sMASTER OF SOCIAL SCIENCE

Quality of care for adult Type 2 diabetes mellitus at a University Primary Care Centre in Malaysia.

Background: Type 2 Diabetes Mellitus (T2D) with its concurrent cardiovascular risk factors such as hypertension and dyslipidaemia and its complications has now accounted for the majority of national and global morbidity and mortality. Aims & Objective: The study aimed to determine the prevalence of complications appearing in diabetic patients despite therapy, addressing to an urban academic primary care centre. Methods: This was a sub-analysis of a cross-sectional study on 212 patients with Type 2 diabetes mellitus (T2D) conducted from June to September 2006. Patients aged ≥ 30 years, non-smokers and under follow-up care of senior doctors were recruited. The average of the three most recent readings of fasting plasma sugar, HbA1c, systolic and diastolic blood pressure, and lipid profiles was taken as measures of respective disease control. Results: Two thirds of the patients were female. The mean age was 62.7 (SD± 10.8) years and the duration of T2D was 11.74 (SD± 6.7) years. A total of 23.6% achieved HbA1c ≤ 7.0%, 26.2% attained LDL-C ≤ 2.6 mmol/L and 24.5% achieved target blood pressure < 130/ 80 mmHg. The most prevalent co-morbid condition was hypertension (77.3%). A total of 27.2% patients had diabetic complications, out of which 86.5% had one complication. Proteinuria < 1gm/L and coronary artery disease were the two most common complications. There were only 16% on subcutaneous insulin and this was significantly associated with fasting plasma glucose (t = 5.38, df= 204, p < 0.0001) and HbA1c (t = 4.31, df= 206, p < 0.0001). Conclusions: Many T2D patients at this centre did not achieve treatment goals. Insulin and lipid-lowering drugs use should be optimized to improve control rates. More structured care processes are urgently needed in order to achieve good glycaemic control

The relationship between gold price and exchange rate of Asean currencies (Ringgit Malaysia , Singapore Dollar, Thai Baht) against U.S. Dollar

The empirical study is to examine relationship between gold price and exchange rate of ASEAN currencies such as Malaysian Ringgit (MYR/USD), Singapore Dollar (SGD/USD), and Thai Baht (THB/USD) against U.S. dollar. After the end of the Bretton Woods System and Gold Standard, the floating exchange rate has been adopted by most of the countries. Many have argued that the adoption of the floating exchange rate has been a major cause for the instability of world gold price. Currently, the gold price is dominated in U.S. dollar in which the change in dollar will influence the gold price in other currencies. The Augmented Dickey-Fuller (ADF) Unit Root Test, Johansen Cointegration Test, Granger Causality Test with Vector Error Correction Model (VECM) and Ordinary Least Square (OLS) Method are applied to examine the relationship between gold price and exchange rate of MYR/USD, SGD/USD and THB/USD on a monthly basis from January 1981 to December 2010. The result shows that long-term relationship exists between gold price and exchange rate of MYR/USD, SGD/USD and THB/USD. Nevertheless, there is no short-term relationship among them. Moreover, the result also indicates that gold price has positive relationship with MYR/USD but has inverse relationship with SGD/USD and THB/USD

Physico-chemical compositions of the red seedless watermelons (Citrullus Lanatus)

Changes of physico-chemical properties such as size, weight, moisture content, total soluble solid (TSS), colour, pH, total acidity and sugar content of red seedless watermelon during storage at room temperature (± 28°C; 70-80% RH) were investigated. The average weight, diameter and length of red seedless watermelon were 5.94 kg, 22.0 cm and 21.8 cm respectively. The length to diameter ratio was 1.02. The statistical analysis indicated that total soluble solids of fruit decreased significantly (p<0.01), but no significant changes were found in pH and total acidity during ripening. Weight loss, moisture content and freezing point was found to be increased significantly (p<0.01) during ripening. Colour L* was found no significant changes but colour a* and b* increased significantly (p<0.1) throughout the ripening process. For sugar analysis, significant changes (p<0.1) in fructose and glucose were obtained, but no significant changes were observed in sucrose content during storage time. From the observation, the optimum eating quality of watermelon stored in room temperature (± 28°C; 70-80% RH) was within one week after harvest, although they can be stored up to 2 weeks. The data obtained is vital in order to apply in different field, purpose and application

A case study: the knowledge and awareness levels of copyright infringement among learners utilising digital technologies in Sunway College Johor Bahru

Technologies especially Web 2.0 tools and mobile devices are transforming the way education is delivered. As such higher education institutions are experiencing an emerging pedagogical trend that may cause copyright infringement. The Copyright Act 1987 was legislated to inspire continuing creative work among academicians. Hence, the knowledge and awareness of Copyright Law and its infringement becomes increasingly significant in protecting the academicians’ work. Unawareness of the law can cause students to infringe the law and it can affect academicians’ work. An initial survey was conducted on 127 first year students from all nine programmes of Sunway College Johor Bahru. The results reveal that although the respondents have a relatively high awareness level and claim to understand the infringement; their actual knowledge level is only approximately 50% of the law. Also, the knowledge and awareness levels have very little correlation with the attitude level towards the Copyright Law