Proceeding of the Electrical Engineering Computer Science and Informatics
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High Performance Direct Torque Control of Induction Motor Drives: Problems and Improvements
Get PDFThis paper presents some of the main problems, as well as their root causes, of Direct Torque Control (DTC) 3-phase induction motor drive. The high torque ripple in DTC drive due to the hysteresis controller inevitably becomes worst with the discrete implementation of the drive system. The hysteresis controller also causes variable switching frequency that depends on operating conditions, especially the speed. The simplification used in stator flux expression for voltage vectors selection in flux control results in a poor flux regulation at low speed. To overcome these problems, techniques that have been implemented at UTM- PROTON Future Drive Laboratory (UPFDL) are presented and described. Some experimental results obtained from the previous works are also presented and discussed.
Implementation of K-Means Clustering Method to Distribution of High School Teachers
Get PDFCurrently, the government is still having difficulties in distributing teachers. The current problem is not just about less teachers, but also more teachers in some cities. The problem of unequal distribution of teachers then became dependent on local government. The distribution of teachers now can not be centralized because of the decentralization system implemented in Indonesia. Clustering in data mining is useful for finding distribution patterns within a dataset that is useful for data analysis processes. Using clustering, identifiable densely populated areas, overall distribution patterns and attractive associations between data attributes. The purpose of this research is to apply k-means clustering algorithm to analyze distribution of high school teachers in Indonesia. This research uses three steps, namely dataset selection, preprocessing data, and application of k-means clustering. Testing is done by using k cluster, that is k = 12. The cluster results are analyzed to classify clusters into 3 categories, namely less, enough, and more teachers. Testing results obtained data Sum of Squared Error (SSE) with percentage 87.15%. While the clustering results produce clusters 3 and 5 in the category of less teachers. Cluster 1 and 9 in the category of enough teachers. While cluster 2,4,6,7,8,10,11,12 in the category of more teachers. Based on the results obtained it can be concluded that the accuracy of the algorithm used with 12 clusters is very high. The results of this clustering analysis can also be used as a reference for the distribution of teachers to region with less teachers, so as to solve the issue of uneven distribution of teachers
Empirical Investigation on Factors Related to Individual of Impact Performance Information System
Get PDFToday, many Information System Success studies are performed however only a few studies which focused on the impact of a personal user to succeed of applying IS. The aim of this study is to investigate and to measure the effect of End User Computing Satisfaction into Individual of Impact Performance, with regard the successful implementation of Information system at higher education. Random sampling technique is conducted offline on 100 IS college users and Structural Equation Model technique is used to analyze survey data based on Information System Success model. Our result show that IOIP is influenced by EUCS
Reconfigurable Logic Embedded Architecture of Support Vector Machine Linear Kernel
Get PDFSupport Vector Machine (SVM) is a linear binary classifier that requires a kernel function to handle non-linear problems. Most previous SVM implementations for embedded systems in literature were built targeting a certain application; where analyses were done through comparison with software im- plementations only. The impact of different application datasets towards SVM hardware performance were not analyzed. In this work, we propose a parameterizable linear kernel architecture that is fully pipelined. It is prototyped and analyzed on Altera Cyclone IV platform and results are verified with equivalent software model. Further analysis is done on determining the effect of the number of features and support vectors on the performance of the hardware architecture. From our proposed linear kernel implementation, the number of features determine the maximum operating frequency and amount of logic resource utilization, whereas the number of support vectors determines the amount of on-chip memory usage and also the throughput of the system
2D-Sigmoid Enhancement Prior to Segment MRI Glioma Tumour
Get PDFTumour identification has always been a topic that interested researchers around the world. The most challenging phase in tumour identification based on brain MR image is the segmentation of the tumour contour which may contain many unwanted details. Intensity inhomogeneities often occur in real world images and may cause the difficulties in image segmentation. In order to overcome the difficulties caused by intensity inhomogeneity, the study presented pre-processing prior to a region based active contour model with modification of Region Scalable Fitting (MRF) method for image segmentation. Region based active contour model that draw upon intensity information in local regions. The pre-processing is a kind of image enhancement which applies the 2D-sigmoid function at tumour boundary. 2D-sigmoid function enhances the contrast in the brain MRI image for pre-processing steps. Enhanced pixel value, F(x, y), is the ‘S’ shape function of intensity I (x, y) of the image at the point (x, y), width of the gradient magnitude around brain image (α) and gradient magnitude around brain image (β). Experimental results show desirable of MRF method in terms of computation efficiency
Automated Post-Trabeculectomy Bleb Assesment by Using Image Processing
Get PDFGlaucoma is a second leading cause of blindness after cataract. Glaucoma caused by unbalance absorption of aqueus humour so it increase intraocular pressure. As a result, it surpresses nerve cells so that nerve cells can not get enough blood flow as nutrition intake and can lead to permanent blindness. One of the treatment for glaucoma is by surgical procedure, called trabeculectomy. After the surgery a slightly lifted tissue due to passing fluid, called bleb, should appears. Bleb assesment is necessary to examine the successful of trabeculectomy surgery. One of standard assesment is Indiana Bleb Appearance Grading Scale (IBAGS). Ophthalmologist used this standard to grade the bleb images manually so the result is subjective. This work offered a new approach to standardize the system of bleb assessment by computer software. Features related to bleb height, width and vascularity were extracted from the bleb image by using image processing algorithm. The KNN algorithm then used to classify the image according the IBAGS. The proposed method has successfully increased the Cohen’s kappa coefficient from 0.56 to 0.63. Therefore, it potentially reduced the subjectivity of the bleb grading
Precise Wide Baseline Stereo Image Matching for Compact Digital Cameras
Get PDFNumerous image matching methods for wide range of applications have been invented in the last decade. When high precision and reliability of the object space point coordinates is highly demanding, a stereo image matching method which can produce conjugate point of images and a standard deviation of the matched point is examined. In this approach, image gradients are used locally to seek a conjugate patch. The normalized cross correlation is first utilized to estimate an approximate location of the conjugate patch between two normalized images. Then the location of conjugate patch is further refined by using Gaussian-Newton least squares image matching. Both radiometric and geometric parameters of least squares models are used selectively in seeking the best possible accuracy. Iterative computation is conducted to incrementally refine the geometric location of the conjugate point. After a matched patch has been found, a variant-covariant matrix of the parameter is analyzed to inform the precision of the conjugate points both on images and object space. This method can compute high precision object space points and some examples demonstrate the insight of the approach
Compressed Natural Gas (CNG) Technology for Fuel Power Plants
Get PDFGas has great potential to be converted into electrical energy. Indonesia has natural gas reserves up to 50 years in the future, but the optimization of the gas to be converted into electricity is low and unable to compete with coal. Gas is converted into electricity has low electrical efficiency (25%), and the raw materials are more expensive than coal. Steam from a lot of wasted gas turbine, thus the need for utilizing exhaust gas results from gas turbine units. Combined cycle technology (Gas and Steam Power Plant) be a solution to improve the efficiency of electricity. Among other Thermal Units, Steam Power Plant (Combined Cycle Power Plant) has a high electrical efficiency (45%). Weakness of the current Gas and Steam Power Plant peak burden still using fuel oil. Compressed Natural Gas (CNG) Technology may be used to accommodate the gas with little land use. CNG gas stored in the circumstances of great pressure up to 250 bar, in contrast to gas directly converted into electricity in a power plant only 27 bar pressure. Stored in CNG gas used as a fuel to replace loadbearing peak. Lawyer System on CNG conversion as well as the power plant is generally only used compressed gas with greater pressure and a bit of land
Neural Network on Mortality Prediction for the Patient Admitted with ADHF (Acute Decompensated Heart Failure)
Get PDFPatient admitted with acute decompensated heart failure (ADHF) facing with high risk of mortality where 30 day mortality rates are reaching 10%. Identifying patient with high and low risk of mortality could improve clinical outcomes and hospital resources allocation. This paper proposed the use of artificial neural network to predict mortality for the patient admitted with ADHF. Results show that artificial neural network can predict mortality for ADHF patient with good prediction accuracy of 94.73% accuracy for training dataset and 91.65% for test dataset
Improving E-Book Learning Experience by Learning Recommendation
Get PDFTechnology Enhanced Learning is one of the most dynamic areas of inquiry in education. One form of TELs, that is on-screen learning, has become the topic of interest of many works. It is popular mainly with young people despite all findings, which undoubtedly suggest that it is detrimental to learning. The method hinders learning experience due to the reading spatial instability, difficulties in establishing mental map, and poor visual ergonomics. Currently, many textbooks are available in electronic form and a majority of the students in Bina Nusantara University in Indonesia, for example, consider the form to be more convenient and preferable. In the electronic form, the textbooks are much more affordable. They can be obtained easier than the printed books. This work intends to explore a method of improving the learning quality of the electronic textbooks. The improvement is expected to be achieved by enriching the electronic textbook with cues in the form of margin notes, highlights, markers, lines and arrows, and navigation tools provided by the subject matter expert. The idea is implemented on a class at the university and its effects are assessed. The participants are divided into two groups having the same distribution of the past academic performance where one group is assigned to learn using the recommendation system and the other is without the system. After the learning, their understandings are assessed systematically by qualitative and quantitative methods. The participants with the recommendation system outperform those without significantly, which is marked by the values of the Cohen’s effect size d larger than 1.20 with the standard deviation about 0.563