EMITTER International Journal of Engineering Technology
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160 research outputs found
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Differential Spatio-temporal Multiband Satellite Image Clustering using K-means Optimization With Reinforcement Programming
No full textDeforestration is one of the crucial issues in Indonesia because now Indonesia has world's highest deforestation rate. In other hand, multispectral image delivers a great source of data for studying spatial and temporal changeability of the environmental such as deforestration area. This research present differential image processing methods for detecting nature change of deforestration. Our differential image processing algorithms extract and indicating area automatically. The feature of our proposed idea produce extracted information from multiband satellite image and calculate the area of deforestration by years with calculating data using temporal dataset. Yet, multiband satellite image consists of big data size that were difficult to be handled for segmentation. Commonly, K- Means clustering is considered to be a powerfull clustering algorithm because of its ability to clustering big data. However K-Means has sensitivity of its first generated centroids, which could lead into a bad performance. In this paper we propose a new approach to optimize K-Means clustering using Reinforcement Programming in order to clustering multispectral image. We build a new mechanism for generating initial centroids by implementing exploration and exploitation knowledge from Reinforcement Programming. This optimization will lead a better result for K-means data cluster. We select multispectral image from Landsat 7 in past ten years in Medawai, Borneo, Indonesia, and apply two segmentation areas consist of deforestration land and forest field. We made series of experiments and compared the experimental results of K-means using Reinforcement Programming as optimizing initiate centroid and normal K-means without optimization process.Keywords: Deforestration, Multispectral images, landsat, automatic clustering, K-means
CFD Analysis of Nozzle Exit Position Effect in Ejector Gas Removal System in Geothermal Power Plant
No full textThe single stage ejector is used to extract the Non CondensableGas (NCG) in the condenser using the working principle of the Venturi tube. Three dimensional computational simulation of the ejector according to the operating conditions was conducted to determine the flow in the ejector. Motive steam entering through the convergent – divergent nozzle with increasing flow velocity so that the low pressure exist around the nozzle. Comparison is done also in a two dimensional simulation to know the differences occurring phenomena and flow inside ejector. Different simulation results obtained between two dimensional and three dimensional simulation. Reverse flow which occurs in the mixing chamber made the static pressure in the area has increased dramatically. Then the variation performed on Exit Nozzle Position (NXP) to determine the changes of the flow of the NCG and the vacuum level of the ejector.Keywords: Ejector, NCG, CFD, Compressible flow
Centronit: Initial Centroid Designation Algorithm for K-Means Clustering
No full textClustering performance of the K-means highly depends on the correctness of initial centroids. Usually initial centroids for the K- means clustering are determined randomly so that the determined initial centers may cause to reach the nearest local minima, not the global optimum. In this paper, we propose an algorithm, called as Centronit, for designation of initial centroidoptimization of K-means clustering. The proposed algorithm is based on the calculation of the average distance of the nearest data inside region of the minimum distance. The initial centroids can be designated by the lowest average distance of each data. The minimum distance is set by calculating the average distance between the data. This method is also robust from outliers of data. The experimental results show effectiveness of the proposed method to improve the clustering results with the K-means clustering.Keywords: K-means clustering, initial centroids, Kmeansoptimization
PID Controller Design of Nonlinear System using a New Modified Particle Swarm Optimization with Time-Varying Constriction Coefficient
No full textThe proportional integral derivative (PID) controllers have been widely used in most process control systems for a long time. However, it is a very important problem how to choose PID parameters, because these parameters give a great influence on the control performance. Especially, it is difficult to tune these parameters for nonlinear systems. In this paper, a new modified particle swarm optimization (PSO) is presented to search for optimal PID parameters for such system. The proposed algorithm is to modify constriction coefficient which is nonlinearly decreased time-varying for improving the final accuracy and the convergence speed of PSO. To validate the control performance of the proposed method, a typical nonlinear system control, a continuous stirred tank reactor (CSTR) process, is illustrated. The results testify that a new modified PSO algorithm can perform well in the nonlinear PID control system design in term of lesser overshoot, rise-time, settling-time, IAE and ISE.Keywords: PID controller, Particle Swarm Optimization (PSO),constriction factor, nonlinear system
Performance Analysis of an OFDM PHY Scheme with Zero Forcing Equalizer Using Software Defined Radio Platform and USRP
No full textWe present an implementation of Zero Forcing (ZF) equalizer in OFDM scheme using Software Defined Radio platform whereas NI USRP-2920 as the Radio Frequency (RF) front-end. ZF equalizer is employed to achieve reliable system at the receiver. Center frequency used for data transmission is 915 MHz. The reliability transmission and the performance of ZF equalizer are measured in term of different symbol mapping (i.e., M-PSK and M-QAM). The IQ rate determines the bandwidth available, whereas good performance is achieved with IQ rate less than 1 MHz.ZF equalizer achieves good performance when using BPSK, QPSK and 16-QAM modulation techniques. By applying ZF equalizer, bit error on BPSK and QPSK modulations can be reduced from 29,16% and 39,06% into 0%. This advantage of ZF equalizer also is able to press the bit error on 16- QAM and 64-QAM modulations into 3,125% and 8,85%, respectively.Keywords: OFDM,SDR, USRP,Zero Forcing Equalize
Automatic Backup System for Virtualization Environment
No full textVirtualization is a technology lately much discussed and considered as the proper way to cut costs in the construction of a data center. One example of the implementation of virtualization technologies is to using VMware. Another tools for virtualization are Xen and OpenVZ, but VMware is more flexible than Xen or OpenVZ because VMware can run a variety of operating systems. Although it has the advantage, virtualization technology also has a vital weakness, virtualization technologies could be analogous by putting all the eggs in a basket. This means that if the master server problem, all systems inside the virtual machine can not be used. However, it can be anticipated by provide backup facilities that run continually and automatically. VMware itself has had an application to backup/replicate virtual machines. However, that application is not free yet.This research has been design and creates a web-based software forbacking up virtual machines on VMware. So it made easier for users and admins to perform periodic backups of virtual machines. From the test results has been done, it can be seen that used disk type thin or zeroed thick make process backup faster, system can’t work well when virtual machine has snapshot, scheduling system and restoring system has worked well, physical ability data storage influence system.Keywords: Virtual machine, virtualization, Vmware, Backup, Data Center
A Combination of PD Controller and PIAFC for Stabilization of “x†Configuration Quadcopter
No full textThis paper presents a stabilization control method for “x†configuration quadcopter. The control method used the combination of PD (Proportional Derivative) controller and PIAFC (Proportional Integral Active Force Control). PD is used to stabilize quadcopter, and PIAFC is used to reject uncertainty disturbance (e.g. wind) by estimating disturbance torque value of quadcopter. The PD with PIAFC provided better result where PIAFC could minimize uncertain disturbance effect. The simulation has successfully give comparation about controller performance (PD, PD-AFC, PD-PIAFC) by calculate RMS (Root Mean Square) value. PD with AFC gives better result than PD. AFC optimization using PI (PD-PIAFC) give best result if compared with PD or PD-AFC. PD-PIAFC has lowest RMS value of result control signal, 0.0389 for constant disturbance and 0.1008 for fluctuated disturbance.Keywords:“x†configuration quadcopter, stability, PD, PIAFC
Combination Adaptive Traffic Algorithm and Coordinated Sleeping in Wireless Sensor Network
No full textWireless sensor network (WSN) uses a battery as its primary power source, so that WSN will be limited to battery power for long operations. The WSN should be able to save the energy consumption in order to operate in a long time.WSN has the potential to be the future of wireless communications solutions. WSN are small but has a variety of functions that can help human life. WSN has the wide variety of sensors and can communicate quickly making it easier for people to obtain information accurately and quickly. In this study, we combine adaptive traffic algorithms and coordinated sleeping as powerâ€efficient WSN solution. We compared the performance of our proposed ideas combination adaptive traffic and coordinated sleeping algorithm with nonâ€adaptive scheme. From the simulation results, our proposed idea has goodâ€quality data transmission and more efficient in energy consumption, but it has higher delay than that of nonâ€adaptive scheme.Keywords:WSN,adaptive traffic,coordinated sleeping,beacon order,superframe order
Indonesian Automatic Speech Recognition For Command Speech Controller Multimedia Player
No full textThe purpose of multimedia devices development is controlling through voice. Nowdays voice that can be recognized only in English. To overcome the issue, then recognition using Indonesian language model and accousticc model and dictionary. Automatic Speech Recognizier is build using engine CMU Sphinx with modified english language to Indonesian Language database and XBMC used as the multimedia player. The experiment is using 10 volunteers testing items based on 7 commands. The volunteers is classifiedd by the genders, 5 Male & 5 female. 10 samples is taken in each command, continue with each volunteer perform 10 testing command. Each volunteer also have to try all 7 command that already provided. Based on percentage clarification table, the word “Kanan†had the most recognize with percentage 83% while “pilih†is the lowest one. The word which had the most wrong clarification is “kembali†with percentagee 67%, while the word “kanan†is the lowest one. From the result of Recognition Rate by male there are several command such as “Kembaliâ€, “Utamaâ€, “Atas “ and “Bawah†has the low Recognition Rate. Especially for “kembali†cannot be recognized as the command in the female voices but in male voice that command has 4% of RR this is because the command doesn’t have similar word in english near to “kembali†so the system unrecognize the command. Also for the command “Pilih†using the female voice has 80% of RR but for the male voice has only 4% of RR. This problem is mostly because of the different voice characteristic between adult male and female which male has lower voice frequencies (from 85 to 180 Hz) than woman (165 to 255 Hz).The result of the experiment showed that each man had different number of recognition rate caused by the difference tone, pronunciation, and speed of speech. For further work needs to be done in order to improving the accouracy of the Indonesian Automatic Speech Recognition system.Keywords: Automatic Speech Recognizer, Indonesian Acoustic Model, CMU Sphinx, indonesian Language Model, Recognition Rate, XBMC
Optimizing Fuzzy Rule Base for Illumination Compensation in Face Recognition using Genetic Algorithms
No full textFuzzy rule optimization is a challenging step in the development of a fuzzy model. A simple two inputs fuzzy model may have thousands of combination of fuzzy rules when it deals with large number of input variations. Intuitively and trialâ€error determination of fuzzy rule is very difficult. This paper addresses the problem of optimizing Fuzzy rule using Genetic Algorithm to compensate illumination effect in face recognition. Since uneven illumination contributes negative effects to the performance of face recognition, those effects must be compensated. We have developed a novel algorithmbased on a reflectance model to compensate the effect of illumination for human face recognition. We build a pair of model from a single image and reason those modelsusing Fuzzy.Fuzzy rule, then, is optimized using Genetic Algorithm. This approachspendsless computation cost by still keepinga high performance. Based on the experimental result, we can show that our algorithm is feasiblefor recognizing desired person under variable lighting conditions with faster computation time.Keywords: Face recognition, harsh illumination, reflectance model, fuzzy, genetic algorith