Proceeding of the Electrical Engineering Computer Science and Informatics
Not a member yet
649 research outputs found
Sort by
A Combination of the Evolutionary Tree Miner and Simulated Annealing
Get PDFIn recent years, process mining is important to discover process model from event logs; however the existing methods have not achieved good in overall fitness. In this context, this paper proposes a combination of the Evolutionary Tree Miner (ETM) and Simulated Annealing (SA). The ETM aims to reduce randomness of population so that it can improved the quality of individuals. SA aims to increase overall fitness in the population. The results of the proposed method which was compared to other approaches show that the proposes method had better in overall fitness and better quality of individuals
Feature Extraction and Classification of Thorax X-Ray Image in the Assessment of Osteoporosis
Get PDFPrevious studies showed that it was possible to have a prediction or an early detection of osteoporosis by measuring the thickness of the cortex of the clavicle of thorax x-ray image. The drawback of this system was that it was still dependent on the operator of subjective vision applications in the measurement. In addition, the accuracy of the system very much relied on the x-ray image quality. Therefore, it is in urgent need of another system which can automatically classify x-ray image and another method of image processing to identify and acknowledge a certain texture of the based image using a set of classes or texture classification given. In this paper, calculation and analysis of a series of image processing algorithms to perform x-ray image classification are done using the K-Nearest Neighbor (KNN) and feature extraction techniques Gray Level Co-occurrence Matrix (GLCM) on small sample size data of 46. Thorax x-ray images of 44 females and 2 males with the average age of 63 years old. T-score of these images had been measured using DEXA scan before as a justification. The proposed method shows that the clavicle cortex thickness measurement using GLCM and KNN method as feature extraction and image classification has its sensitivity of 100% and specificity of 90%. Furthermore, the accuracy which is obtained from the entire implementation capability in correctly assessing osteoporosis is 97.83%. Thus, it is evident that it is significantly correlated with predetermined T-score of DEXA in the assessment of osteoporosis.
The Successful Elements Implementing the eLearning using Cloud Services Data Centre at Private Institution of Higher Learning in Malaysia
Get PDFThere are a few network environment used for institutions of higher learning for eLearning application. The world financial crises cause institution of higher learning struggling to maintain and update the technologies and infrastructures and try to provide the sufficient budget allocation for the network infrastructure. Cloud Services Data Centre network environment is one of the solution where they does not used physical network technology and infrastructure and cost saving. The purpose of this paper is to identify the success factor elements in implementing the eLearning using Cloud Services Data Centre at Private Institution of Higher Learning in Malaysia. The literature was reviewed and base on the preliminary study a few elements was identified for the success factor elements. The elements are perception, business needs, strategy planning, cost saving, security and vendor capability. Base on the finding the propose framework and hypothesis was derived. To validate the success factor elements of Cloud Services Data Centre the pilot test was been done
Variance Analysis of Photoplethysmography for Blood Pressure Measurement
Get PDFThe emergence of photoplethysmography for blood pressure estimation is offering a more convenient method. The elements of photoplethysmography waveform is crucial for blood pressure measurement. Several photoplethysmography elements are still not completely understood. The purpose of this study was to investigated corelation of photoplethysmography elements with blood pressure using statistical approach. Analysis of variance test (ANOVA) was conducted to see if there are any correlation between elements of photoplethysmography with blood pressure. This study used 10 volunteers without an ethical clearance. Photoplethysmography waveform and blood pressure measurements were taken through the patient monitor equipment DatascopeTM. As the result, value factor from the arithmetic is 35.67 and value factor from the table is 3.14. The value of F arithmetic (35.67) > F table (3.14). The correlation of diastolic time (Td) is negative with systolic arterial pressure (SAP) and the correlation of systolic amplitude (As) is positive with diastolic arterial pressure (DAP). The results showed elements of photoplethysmography can be used to estimation blood pressure. The emergence of photoplethysmography for blood pressure estimation is offering a more convenient method. The elements of photoplethysmography waveform is crucial for blood pressure measurement. Several photoplethysmography elements are still not completely understood. The purpose of this study was to investigated corelation of photoplethysmography elements with blood pressure using statistical approach. Analysis of variance test (ANOVA) was conducted to see if there are any correlation between elements of photoplethysmography with blood pressure. This study used 10 volunteers without an ethical clearance. Photoplethysmography waveform and blood pressure measurements were taken through the patient monitor equipment DatascopeTM. As the result, value factor from the arithmetic is 35.67 and value factor from the table is 3.14. The value of F arithmetic (35.67) > F table (3.14). The correlation of diastolic time (Td) is negative with systolic arterial pressure (SAP) and the correlation of systolic amplitude (As) is positive with diastolic arterial pressure (DAP). The results showed elements of photoplethysmography can be used to estimation blood pressure
Task-Technology Fit for Textile Cyberpreneur’s Intention to Adopt Cloud-based M-Retail Application
Get PDFTask-Technology Fit (TTF) model has been widely used in many researches for understanding the compatibility of task characteristics and technology characteristics. Applying TTF in mobile retail (m-retail) context from the perspectives of retailers might give the insights of their intention to adopt mobile cloud application technology for online business operations. Since it is currently common for retailers such as textile cyberpreneurs to conduct m-retail via the uses of certain mobile applications and devices, it is essential to investigate the usage intention based on task-related factors. Therefore, the objective of this study is to examine the compatibility of textile cyberpreneurs’ tasks and characteristics of cloud-based m-retail application (CBMA) along with their usage intention to adopt the technology for their online business transactions. This research model surveyed 348 Malaysian textile cyberpreneurs. The results show that both task characteristics and technology characteristics have positive significant effects on task-technology fit. Further analysis also suggests the fitness between task and technology has positively influenced textile cyberpreneurs’ intention to adopt cloud-based m-retail application. The findings contributed in acknowledging the usage intention among textile cyberpreneurs based on task-related factors which might be useful for service providers in delivering the right services for end-users. The directions for future research are also discussed
Design of Automatic Switching Bio-Impedance Analysis (BIA) for Body Fat Measurement
Get PDFBioelectrical impedance analysis (BIA) is one method of measuring body fat levels by distinguishing the fat mass and non-fat mass based on body composition assessment. This research designs a system to measure the body fat percentage by BIA method. The system is capable of measuring BIA with automatic switching between four different electrode schemes, i.e cross-sectional, hand-to-hand, hand-to-foot, and foot-to-foot. Two electrodes are to conduct current into the body, while other two electrodes are utilized to measure the voltage from the body. The alternating current is injected with frequency of 50 kHz. Automatic switch in the form of multiplexers and demultiplexers controls the sequence of BIA measurement methods. Microcontroller process the data and the result is displayed on LCD. A keypad is used to input related body parameters, i.e height, weight, age, and gender. The measurement tests shows that the BIA works as intended, while the comparison with commercial BIA reveals maximum relative error of 4.6 % and the highest standard deviation of 2.2%
Measurement of Maximum Value of Dental Radiograph to Predict the Bone Mineral Density
Get PDFPost-menopausal woman has a high risk to have osteoporosis. The condition of osteoporosis is characterized by the bone mineral density. The gold standard of BMD examination is using DEXA scan, but it has a problem in high cost and limited availability. So the study about the alternative to overcome the problem is necessary. The objective of this study is to measure the maximum value of periapical radiograph and determine its ability to be a predictor for bone mineral density of lumbar spine and hip.Image processing method was applied to 37 data subject that involved periapical radiograph and DEXA scan. The grayscale image was converted into binary image to observe the connectivity of the pixels. Measurement of maximum value for each radiograph has been done and continued by linier regression method between the maximum value with the BMD of lumbar spine and hip.The result of this study showed that the maximum value has a weak correlation with the BMD of lumbar spine and hip. The maximum value also cannot be the predictor for BMD of lumbar spine and hip as the significant of F is larger than 0,05 in the linier regression test
The Ontology-Based Methodology Phases To Develop Multi-Agent System (OmMAS)
Get PDFSemantic aspect on methodology phase is a significant issue to develop multi-agent system in the current days. There are a lot of methodologies to develop multi-agent system, but the current problem is how to choose the best methodology phase to develop current multi-agent system. The development of multi-agent system currently is to be more complex and difficult. Many aspects that contains on multi-agent system, the one of the famous issue now is about semantic aspect on multi-agent system. The old methodology phases are not suitable to develop current multi-agent system. Nowadays, many researchers start to improve and customize the obsolete methodology to adjust with the current needed. There are two research steps contains in this paper, the first step is to review and criticize previous methodologies especially about MOMA (Methodology for Developing Ontology-Based Multi-Agent System) was introduced in 2013. The second step is the main contribution of this paper is to improve previous methodology phases with the new methodology phases named OmMas (The Ontology-Based Methodology phases to Develop Multi-Agent System), and using semantic aspect as the main focus of this methodology. The result of this research is improved ontology- based methodology phases as a representation of semantic aspect on the ontology development process.
Toward a New Approach in Fruit Recognition using Hybrid RGBD Features and Fruit Hierarchy Property
Get PDFWe present hierarchical multi-feature classification (HMC) system for multiclass fruit recognition problem. Our approach to HMC exploits the advantages of combining multimodal features and the fruit hierarchy property. In the construction of hybrid features, we take the advantage of using color feature in the fruit recognition problem and combine it with 3D shape feature of depth channel of RGBD (Red, Green, Blue, Depth) images. Meanwhile, given a set of fruit species and variety, with a preexisting hierarchy among them, we consider the problem of assigning images to one of these fruit variety from the point of view of a hierarchy. We report on computational experiment using this approach. We show that the use of hierarchy structure along with hybrid RGBD features can improve the classification performance
Sketch Plus Colorization Deep Convolutional Neural Networks for Photos Generation from Sketches
Get PDFIn this paper, we introduce a method to generate photos from sketches using Deep Convolutional Neural Networks (DCNN). This research proposes a method by combining a network to invert sketches into photos (sketch inversion net) with a network to predict color given grayscale images (colorization net). By using this method, the quality of generated photos is expected to be more similar to the actual photos. We first artificially constructed uncontrolled conditions for the dataset. The dataset, which consists of hand-drawn sketches and their corresponding photos, were pre-processed using several data augmentation techniques to train the models in addressing the issues of rotation, scaling, shape, noise, and positioning. Validation was measured using two types of similarity measurements: pixel- difference based and human visual system (HVS) which mimics human perception in evaluating the quality of an image. The pixel- difference based metric consists of Mean Squared Error (MSE) and Peak Signal-to-Noise Ratio (PSNR) while the HVS consists of Universal Image Quality Index (UIQI) and Structural Similarity (SSIM). Our method gives the best quality of generated photos for all measures (844.04 for MSE, 19.06 for PSNR, 0.47 for UIQI, and 0.66 for SSIM)