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The present work represents a non contact, machine vision based method to estimate ripeness level of Guava fruit. The fruit under test is classified as green, ripe, overripe and spoiled using a web camera based computer vision system. This simple method uses a combination of digital web camera; computer and indigenously developed GUI based software to measure and analyze the surface color of the fruits...
Energy-mapping, the conversion of linear attenuation coefficients ( ) calculated at the effective computed tomography (CT) energy to those corresponding to 511 keV, is an important step in CT-based attenuation correction (CTAC) for positron emission tomography (PET) quantification. The aim of this study was to implement energy-mapping step by using curve fitting ability of artificial neural network...
Anomalous traffic detection on internet is a major issue of security as per the growth of smart devices and this technology. Several attacks are affecting the systems and deteriorate its computing performance. Intrusion detection system is one of the techniques, which helps to determine the system security, by alarming when intrusion is detected. In this paper performance of NSL-KDD dataset is evaluated...
Rainfall forecasting is one of the most imperative and demanding operational responsibilities carried out by meteorological services all over the world. The task is complicated since all decisions are to be taken in the visage of uncertainty. In this article, the traditional data pre-processing technique, moving average is coupled with Artificial Neural Network as MA - ANN to improve the prediction...
In this study the usability of routinely measured meteorological parameters to estimate the global solar radiation is investigated. The proposed models are in the form of polynomials. The parameters such as ratio of duration of sunshine to maximum sunshine hours, mean temperature and mean relative humidity are used. Different combinations of these parameter sets have been used in proposing the monthly...
This article presents a methodology for detection of high impedance faults (HIF). HIF occurs when e.g. a cable makes contact with objects of high electric resistance, resulting in a nonsignificant increase in current. Such faults cannot be detected by traditional protection devices that operate due to overcurrent. The developed methodology is based on making use of variables from a power quality meter...
Here we propose an artificial neural network (ANN) model for spectrum sensing in TV band specifically for identifying presence of audio signals. The ANN model is trained with parameters which are a combination of cyclostationary and SNR based features like channel capacity, bandwidth efficiency, autocorrelation. The ANN model is trained based on a new decision making factor termed as utilization factor...
Validation of high-speed interface performance in a given design space from a Signal Integrity (SI) perspective requires Bit Error Rate (BER) computation. Eye Height (EH) and Eye Width (EW) are used to determine the quality of an interface for a given set of design parameters and frequency of operation. EH, EW and BER estimation requires Time Domain (TD) simulation of complex channel models over billions...
The main objective of present study is to compare ANN model develop with neural network fitting tool (nftool), Radial Basis Function Neural Network (RBFNN) in predicting solar radiation for power generation. The three combinations of input variables are considered for prediction. The RBFNN utilizing input parameters as latitude, longitude, height above sea level and sunshine hours has mean absolute...
Smart meters are required to identify home appliances to fulfill various tasks in the smart grid environment. On the other hand, techniques using non-intrusive appliance load monitoring (NIALM) are yet to result in meaningful practical implementation. Our experimental setup, on the recommended specifications of the internal electrical wiring in Indian residences, used common household appliances'...
Pulmonary acoustic signal analysis provides essential information on the present state of the Lungs. In this paper, we intend to distinguish between normal, airway obstruction pathology and interstitial lung disease using pulmonary acoustic signal recordings. The proposed method extracts Mel frequency cepstral coefficients (MFCC) and AR Coefficients as features from pulmonary acoustic signals. The...
Vendor assessment is essential to banks for making an efficient service plan. This paper develops an evaluation fuzzy method based on the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and artificial neural network (ANN) for Vendor and performance evaluation in a fuzzy environment where the vagueness and subjectivity are handled with linguistic value parameterized by triangular...
Recently Pac-Man game has received some attention of AI researchers. Some artificial intelligence researches have been performed with the Pac-Man game. The Monte Carlo, UCT (Upper Confidence Bound for Tree) and DTS (Dynamically Expanding UCT Tree Search) method have some good performances when used in Pac-Man game. However, these methods are based on intensive computation and so they usually could...
This paper presents an intelligent system for the classification of ischemic stroke severity. The application of Artificial Neural Network (ANN) is proposed in this study to classify ischemic stroke severity using EEG sub bands Relative Power Ratio (RPR). There were 100 subjects from National Stroke Association of Malaysia NASAM, Petaling Jaya, Selangor, Malaysia divided into Early Group (EG), Intermediate...
This paper proposes ANN based method for fingerprint ROI (Region of Interest) segmentation. Proposed ANNs where trained with 10000 samples extracted from 20 fingerprint images (in grey-scale and binary modes). The experimental results, including three statistical performance indicators, shows very good performance of the proposed method on a test database of 200 fingerprint images.
One of the recent concerns in the photovoltaic (PV) system practice is solving the mismatching losses due to the partially shaded conditions. Mismatching problems mean that the I–V and P-V curves between the shaded and non-shaded parts of PV module are totally different. Under mismatching condition, multiple local peaks can be observed in the PV module characteristics which pose difficulties for controllers...
The differences between normal speech and whisper, particularly in terms of their acoustic characteristics, are serious problem of ASR (Automatic Speech Recognition) systems. This paper presents the preliminary results of the new way of speech signal pre-processing, which is based on inverse filtering. This method of signal pre-processing improves whisper recognition with ANNs (Artificial Neural Networks)...
Prognostic models for end-stage renal disease (ESRD) have been researched extensively as an increasing prevalence internationally. Different machine learning and statistic algorithms for the models were proposed in studies corresponding to different medical datasets including a quantity of missing values for optimal outcomes. We approached this issue by applying stepwise logistic regression, ANN,...
By the global warming and decreasing fossil fuel, alternative energy sources are looked for future and protecting environment. In the recent years, many studies are made about wind power whereby deteriorating environment will be regarded.
Signal speeds of high speed serial data links double almost every generation and with increasing speeds, simulation and modeling challenges are getting more complex. The present popular and widely accepted metric for simulating a high speed link from signal integrity (SI) perspective is Bit Error Rate (BER) testing. SI engineers look at eye-height and eye-width to determine the quality of an interface...
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