Application of probability models to Malaysian sunshine data

A 10-year Malaysian sunshine data of four stations were fitted to three models, namely the Bendt, Hollands and Huget and Saunier models. Distribution parameters of the models were determined from the values of the observed mean of the sunshine data. The Kolmogorov–Smirnov test was applied to determine the goodness of fit. It was found that the Saunier model was suitable for the Petaling Jaya and Subang stations while the Hollands and Huget model well suited the Bayan Lepas and Kota Bharu stations. The Bendt model did not give a good fit for all stations. It was also found that for the months that have the same observed mean but different observed standard deviations the distribution models were able to fit well only if the estimated standard deviations were close in value to the observed standard deviations. © 1998 John Wiley & Sons, Ltd.     

Detection and Classification of Hemorrhages in Retinal Images

Damage of the blood vessels in retina due to diabetes is called diabetic retinopathy (DR). Hemorrhages is the first clinically visible symptoms of DR. This paper presents a new technique to extract and classify the hemorrhages in fundus images. The normal objects such as blood vessels, fovea and optic disc inside retinal images are masked to distinguish them from hemorrhages. For masking blood vessels, thresholding that separates blood vessels and background intensity followed by a new filter to extract the border of vessels based on orientations of vessels are used. For masking optic disc, the image is divided into sub-images then the brightest window with maximum variance in intensity is selected. Then the candidate dark regions are extracted based on adaptive thresholding and top-hat morphological techniques. Features are extracted from each candidate region based on ophthalmologist selection such as color and size and pattern recognition techniques such as texture and wavelet features. Three different types of Support Vector Machine (SVM), Linear SVM, Quadratic SVM and Cubic SVM classifier are applied to classify the candidate dark regions as either hemorrhages or healthy. The efficacy of the proposed method is demonstrated using the standard benchmark DIARETDB1 database and by comparing the results with methods in silico. The performance of the method is measured based on average sensitivity, specificity, F-score and accuracy. Experimental results show the Linear SVM classifier gives better results than Cubic SVM and Quadratic SVM with respect to sensitivity and accuracy and with respect to specificity Quadratic SVM gives better result as compared to other SVMs.     

Simultaneous and sequential estimation of kinetic parameters in a starch viscosity model

A modified Brookfield viscometer equipped with a data acquisition system was used to study gelatinizing behavior of native corn starch. Data for the dependent variable (continuous torque), and independent variables were collected. The independent variables were time–temperature history, shear history, and temperature, corresponding to the three main regions in a pasting curve. Parameters were estimated simultaneously using both ordinary least squares, and the sequential method. The model fit well as shown by RMSE of approximately 2% of full scale, and relative standard error of all parameters estimated less than 11%. Scaled sensitivity coefficients showed that the most important parameters were time–temperature history, followed by shear history, and the temperature parameter was the least important. This work is the first to show that starch-pasting curve parameters can be estimated simultaneously and sequentially, and can be used to predict pasting curves in other systems (RVA) well.     

On the Performance of Various 5G Signals Sensing Based on Hybrid Filter

International Journal of Wireless Information Networks - The 5G wireless communication system is promised to exploit many kinds of waveform for satisfying various requirements to transmit huge size...     

A design framework of a smartphone user interface for elderly users

Universal Access in the Information Society - Most smartphones currently in the market have complicated user interfaces (UIs) that elderly users find difficult to use. Such difficulties often lead...     

Fuzzy expert system for troubleshooting of the deodorizer unit in a palm oil refining plant

In this paper, a troubleshooting technique is developed to provide a sequence of necessary actions during deodorizer unit failure in a palm oil refinery. This paper introduces a fuzzy expert system that incorporates the knowledge of experienced plant workers in dealing with the complex problems of the palm oil deodorizer. The presented methodology uses both qualitative and quantitative data. Qualitative data are collected from several interview sessions with the technical staff in a palm oil refinery. Quantitative data are gathered from various sources, such as control and monitoring systems. The qualitative data are analyzed to discover the possible pattern of faults in the deodorizer failure. This tool can diagnose possible faults and provide a sequence of necessary actions when deodorizer failure occurs. The obtained results show the developed deodorizer troubleshooting tool is useful to guide plant workers/operators in diagnosing the possible faults and abnormalities during the troubleshooting process, as well as to provide field training for inexperienced staff.     

Offshore Software Maintenance Outsourcing Process Model Validation: A Case Study Approach

The successful execution and management of Offshore Software Maintenance Outsourcing (OSMO) can be very beneficial for OSMO vendors and the OSMO client. Although a lot of research on software outsourcing is going on, most of the existing literature on offshore outsourcing deals with the outsourcing of software development only. Several frameworks have been developed focusing on guiding software system managers concerning offshore software outsourcing. However, none of these studies delivered comprehensive guidelines for managing the whole process of OSMO. There is a considerable lack of research working on managing OSMO from a vendor’s perspective. Therefore, to find the best practices for managing an OSMO process, it is necessary to further investigate such complex and multifaceted phenomena from the vendor’s perspective. This study validated the preliminary OSMO process model via a case study research approach. The results showed that the OSMO process model is applicable in an industrial setting with few changes. The industrial data collected during the case study enabled this paper to extend the preliminary OSMO process model. The refined version of the OSMO process model has four major phases including (i) Project Assessment, (ii) SLA (iii) Execution, and (iv) Risk.     

The Correlation of Device Parameters with Illumination Energy to Explore the Performance of a Monocrystalline Silicon Solar Module

Silicon - The effect of illumination energy on the electrical parameters of a monocrystalline silicon solar module was investigated and results used to reveal the effective spectrum which can help...     

Effect of support structure design toward residual stress of part build using selective laser melting

Selective laser melting process required post-processing of support structure and it is compulsory to use it at overhanging part. There is certain condition where support structure cannot be remove using wire cut machine because of limited access to part and need to be remove manually. This is where the removability of support structure plays important role because support structure needed to be design so that it can be easily remove using manual way. In addition, when comparing contour type of support structure with the most commonly use block type of support structure it shows that contour type is easier to be remove. Furthermore, no research has been done on optimizing the contour type of support structure. A research experiment is conducted in this work to optimize the parameter of contour support structure which is contour offset, teeth height, teeth top length and teeth base length. The result indicates amount of residual stress and the time required for support removal are significantly influenced by contour offset, while all parameters are significant for support volume. The optimum parameter to get low residual stress is contour offset is 0.6 mm, teeth height is 1.4 mm, teeth top length is 0.75 mm and teeth base length is 1.55 mm.