Kompresi Citra Medis Menggunakan Alihragam Kosinus Diskret Dan Sistem Logika Fuzzy Adaptif

The required of bandwidth for communication of digital image data is increased. Limited channel capacity favors image compression techniques. These techniques attempt to minimize the number of bits needed to represent an image and to reconstruct it with little visible distortion. The image data compression techniques reduce memory of storage data and time needed to transmit data. One of the image data compression methods is using Discrete Cosine Transform and Adaptive Fuzzy Logic. The objective of this research is compressing medical image using Discrete Cosine Transform and Adaptive Fuzzy Logic System. Discrete Cosine Transform is applied to find the data will which be encoded and Adaptive Fuzzy Logic System is applied to classify sub image into certain class. The class classification of a sub image is according to their AC energy levels. The systems assign more bits to a sub image if the sub image contains much detail (large AC energy) and less bits if contains less detail (small AC energy). The result of the research shows that the accurate calculation of AC energy determines class classification of sub image and bitmaps used for image data compression must be matching with characteristic of image. Bitmaps used for image data compression determine compression ratio and reconstructed image quality. The medical image compression with ratio of 1:4.8028 result in a reconstruction image with SNR of 63.8197 dB, and visually shows that the image is similar to the original image without significant error

Estimation of Overhead Transmission Line Fault Distance Using Unsynchronized Two-Terminal Method

This paper presents the estimation of transmission line fault distance using unsynchronized two-terminal method. In operation, high or extra-high overhead voltage transmission lines can be interrupted. The disturbance can come from internal or external interference, which is permanent or temporary. For permanent interference, the network operator must visit the location of the disturbance in order to fix it. Because the transmission line is very long, while it takes quick time to find out the location of the disturbance so that it can be repaired immediately, then a method is needed to find out the location of the disturbance. This research proposes a method for determining the location of faults based on voltage and current data at the time of interference from both ends of the transmission line. The interference voltage and current data need not be synchronized. The use of this data makes this method very simple and easy to use. However, the accuracy of the estimation results can still be relied upon. In this study, a simulation was carried out on a two-end transmission line. The transmission line has a phase disturbance to the ground. The noise resistance applied in the simulation is 0 ohms, 10 ohms, 50 ohms, and 100 ohms. The results showed that the highest estimated error was 0.3%, which indicates that this method has a high degree of accuracy

Modeling of Wind Power Plant with Doubly-Fed Induction Generator

This paper presents the modeling and simulation of wind turbine driven by doubly-fed induction generator which feeds ac power to the distribution network. A stator flux oriented vector control is used for the variable speed doubly-fed induction generator operation. By controlling the generator excitation current the amplitude of the stator EMF is adjusted equal to the amplitude of the grid voltage. To set the generator frequency equal to the grid one, the turbine pitch angle controller accelerates the turbine/generator until it reaches the synchronous speed. The system is modeled and simulated in the Matlab Simulink environment in such a way that it can be suited for modeling of all types of induction generator configurations. The model makes use of rotor reference frame using dynamic vector approach for machine model. The system is also simulated when a fault occurs in 25 kV grid of distribution system. The results of a single line to ground fault and a symmetrical three-phase ground fault is analyzed. The results show that the wind energy conversion system can normally operate in fault conditions

A Neuro-Fuzzy Approach for Vehicle Fuel Consumption Prediction

This paper presents a neuro-fuzzy approach for predicting vehicle fuel consumption. The prediction of fuel consumption of a vehicle has become a strategic issue. This is because it is not only related to the problem of the availability of fuel which is getting thinner but also the problem of the environmental impact caused. In this study, the acquisition of the car parameter data was inputted, namely the number of cylinders, displacement, horsepower, weight, acceleration, and model year. The output variable that will be predicted is fuel consumption in miles per gallon (MPG). 'Weight' and 'Year' are chosen as the two best input variables. Training results and predictions are expressed in the three-dimensional input-output surface graph of the best two-input ANFIS model for MPG prediction. The graph shows a nonlinear and monotonic surface, where MPG is predicted to increase with an increase in 'Weight' and a decrease in 'Year'. The results of the RMSE training were 2.767 and the RMSE examination was 2.996. Based on the results of the study showed that the greater the weight of motor vehicles, the greater the amount of fuel needed to travel the same distance

Akuisisi, Pengolahan, dan Analisis Isyarat Suara Jantung (Heart Sound Signal Acquisition, Processing, and Analysis).

Different physicians may hear the same heart sound differently, and perhaps interpret them differently. The aim of this research is to realize a system that can aid the physicians to interpret objectively the heart sounds by analyzing the heart sound signals in time, spectral, and wavelet domain. The research was realized by constructing an acquisition circuit that amplifi and filter the signal detected by a stethoscope coupled with a microphone. The amplified signal is then digitalized and processed by computer besides amplifying its power to drive a loudspeaker. The processed signal is then analyzed using time, frequency, and wavelet techniques. The results show that the acquisition circuit can amplifi and filter the signal with the pass-band gain of 90 dB with a cut-of ffrequency of about 1 KHz and a transition-band slope of â40 dB/decade. The heart sounds interval and heart beat rate of the sample persons can be measured. The spectral bandwidth of the signal can be estimated and the time âfrequency pattern of the signal can be observed. Keywords: Heart sound, acquisition, processing, spectral, wavelet, analysi

Wavelet Based Feature Extraction for The Indonesian CV Syllables Sound

This paper proposes the combined methods of Wavelet Transform (WT) and Euclidean Distance (ED) to estimate the expected value of the possibly feature vector of Indonesian syllables. This research aims to find the best properties in effectiveness and efficiency on performing feature extraction of each syllable sound to be applied in the speech recognition systems. This proposed approach which is the state-of-the-art of the previous study consist of three main phase. In the first phase, the speech signal is segmented and normalized. In the second phase, the signal is transformed into frequency domain by using the WT. In the third phase, to estimate the expected feature vector, the ED algorithm is used. Th e result shows the list of features of each syllables can be used for the next research, and some recommendations on the most effective and efficient WT to be used in performing syllable sound recognition

Evaluasi Nilai Noise Sebelum Dan Sesudah Kalibrasi Sebagai Salah Satu Wujud Kinerja Pesawat CT-Scan

The noise has to be measured daily because it directly degrades image quality, which inturn it is dificult to define between normal and pathological tissues on a-CT image. Thisresearch’s aim was performed to examine noise differences between before and aftercalibrating of the CT-scanner system, and also to study the chance of noise deviated values day-by-day during 20 days of the two different periods of measurement.A callibrated head water phantom was scanned before and after equipment callibrations,using the head scanning parameter, and device measurement at ROI 228.2 mm2 to obtain thenoise data. Descriptive statistics was employed to present related information, and the T-testpaired-sample was the statistical tool to test the null hypothese (Ho) with level of significance(α) 0.05.The results showed most of noise values between before and after equipment calibrationsfall arround the base line or within two standard deviation (2SD). In before callibration of thenoise, the base line noise value is 4.76 HU whereas the upper limit and the lower limmit of thenoise values are 5.34 HU and 4.18 HU (respectively) with a-1.16 HU difference. In aftercallibration of the noise, the base line noise value is 4.35 HU whereas the upper limit and thelower limmit of the noise values are 5.29 HU and 3.41 HU with a-1.87 HU difference. However,there are two out of fourty noise values (± 5%) that fall outside of the 2SD limmit if a numberfalls outside of 2SD from the base line in the same direction (i.e., all high or all low) more thanfour days in a row, it is a shift that could be due to a machine malfunction and should beinvestigated before the outer control limit is exceeded. Statistical analyses with paired- sampleT-test showed p-value (0.005) < 0.05. By this meaning that, the noise between before and afterCT-Scanner callibrations are different in their values additonally most of the noise values aftercallibration seem to be low compared with that of the values before callibrations.Keywords: CT scan, evaluation, noise