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In this era of web applications, web shopping portals have become increasingly popular as they allow customers to buy products from home. These websites often request the customers to rate their products and write reviews, which helps the manufacturers to improve the quality of their products and other customers in choosing the right product or service. The rapid increase in the popularity of e-commerce...
Epilepsy is a common neurological disorder which is difficult to treat because of its unpredictable and recurrent nature. The electroencephalogram (EEG) is a valuable tool for detecting epileptic seizures. With the aim of reducing the input feature dimensionality, a single median based feature called interquartile range (IQR) was used in this paper for the classification of normal and seizure EEG...
Millions of people die from Diabetes Mellitus every year. Recently, researchers have discovered that Diabetes Mellitus can be detected in a non-invasive manner through the analysis of human facial blocks. Although algorithms have been developed to detect Diabetes Mellitus using facial block color features, use of its texture features to detect this disease has not been fully investigated. In this...
We propose a robust diabetes prediction model by examining how predictions from several learning algorithms, performing the same task, can be exploited to yield a higher performance than the best individual learning algorithm. The task was to forecast the onset of non-insulin dependent diabetes within a five year period using previous vital sign examination information. Experimental data is a 768...
A micro array represents thousands of gene expression levels across a few samples. Determination of an optimal set of features from such a high dimensional dataset requires a good feature selection method. Based on statistical significance of the features, an elimination of insignificant genes can be performed. However such methods lack biological validation. In this paper we propose a method where...
Indonesia have a massive number of SMEs, but with a very low revenue. An alternative to increase revenue is by using internet. Some SMEs already develop their website, but they don't have same navigation. The websites confuse the potential buyers. So, a website's aggregator is essential. This aggregator is made without the owner of the SMEs to register their website, which means it can automatically...
In this paper, we propose a new image annotation method by combining content-based image annotation and tag-based image annotation techniques. Content-based image annotation technique is adopted to extract "loosely defined concepts" by analyzing pre-given images' features such as color moment (CM), edge orientation histogram (EOH), and local binary pattern (LBP), followed by constructing...
Digital image forgery is becoming easier to perform because of the rapid development of various manipulation tools. Image splicing is one of the most common image forgery techniques. To detect the spliced images several methods proposed utilizing the statistical features of the digital images. In this paper, a new image splicing detection approach proposed based on singular value decomposition (SVD)...
The aim of this study is to apply automatic speech recognition (ASR) mechanism to improve the amount of information extracted from the voice and to increase the accuracy of the system by using selective highly discriminative features among different types of acoustic features. For feature extraction, we applied three techniques which are Mel Frequency Cepstral Coefficient (MFCC), Linear Prediction...
This paper addresses two contributions for improving the accuracy and speed of preceding car detection systems. First, it proposes a feature description using Scalable Histogram of Oriented Gradient (SHOG) to solve scale problem of car region on the image. Without resizing the images to a fixed size, it is capable to extract a high-discriminated features with on the same feature space. Second, instead...
Large amount of medical data leads to the need of intelligent data mining tools in order to extract useful knowledge. Researchers have been using several statistical analysis and data mining techniques to improve the disease diagnosis accuracy in medical healthcare. Heart disease is considered as the leading cause of deaths worldwide over the past 10 years. Several researchers have introduced different...
Microarray studies and gene expression analysis have received tremendous attention over the last few years and provide many promising paths toward the understanding of fundamental questions in biology and medicine. High throughput biological data need to be processed, analyzed, and interpreted to address problems in life sciences. Feature selection (FS) and clustering are among the methods used in...
With the increase of colorectal cancer patients in recent years, the needs of quantitative evaluation of colorectal cancer are increased, and the computer-aided diagnosis (CAD) system which supports doctor's diagnosis is essential. In this paper, a hardware design of type identification module in CAD system for colorectal endoscopie images with narrow band imaging (NBI) magnification [1] is proposed...
Todays, feature selection is an active research in machine learning. The main idea of feature selection is to select a subset of available features, by eliminating features with little or no predictive information. This paper presents a hybrid model with a new local search technique based on reinforcement learning for feature selection. We combined the particle swarm optimization (PSO) with support...
In addition to provide charging service, Electric Vehicle (EV) charging station equipped with distributed energy storage system can also participate in the deregulate market to optimize the cost of operation. To support this function, it is necessary to achieve sufficient accuracy on the forecasting of energy resources and market prices. The deregulated market price prediction presents challenges...
Wrist pulse signal is believed to contain critical information of the patients' health condition. This project aims to analyze the time series wrist pulse signals in order to distinguish patients suffering from various symptoms with healthy people. In this paper, the four inflammation symptoms tackled in this project are Appendicitis (A), Acute Appendicitis (AA), Pancreatitis (P) and Duodenal Bulb...
In this paper, we propose a system of automatically classifying different types of dates from their images. Different dates have various distinguished features that can be useful to recognize a particular date. These features include color, texture, and shape. In the proposed system, a color image of a date is decomposed into its color components. Then, local texture descriptor in the form of local...
The ability to acquire Electroencephalogram (EEG) signals from the brain has led to the development of Brain Computer Interfaces (BCI), which capture signals generated by the physical processes in the brain and use them to control external devices. In this paper, we establish an application to control a robot on the Arduino platform by the use of a BCI system, which does not require training for individual...
Website response time is one of the most important performance parameter of website. It can be used to assess website performance to forecast the status of website. Large amounts of data are applied by a distributed monitoring system that monitoring a university website response time. Support vector machine with information granulation is studied to predict the response time. It can predict accurately...
Monitoring and classification of human activity has been an active area of research for the past few years due to the increasing demands in healthcare sector. Quick aid for falls in elderly persons and detecting emergency situations are few leading cause of such interest. In this paper, a human activity recognition system based on motion patterns on a smartphone is proposed for classification of activities...
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