Jurnal Ilmu Komputer dan Informasi
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A CHANGE DETECTION AND RESOURCE-AWARE DATA SENSING APPROACHES FOR IMPROVING THE REPORTING PROTOCOL MECHANISM FOR MOBILE USER
Get PDFUpdate mechanism is an important process that relays information to the end-user by sending the data from the client to the server. There are several kinds of update mechanism that are used, one of them is reporting protocol. Reporting protocol sends the data from the client to the server continuously in a certain time interval. Reporting protocol occasionally sends the same information repeatedly to the end-user and sometimes the data aren’t needed by the end-user. This is an issue, because it can cause a large amount of bandwidth usage. In this research, we have developed an improvement of the reporting protocol mechanism for mobile user using change detection and resource-aware data sensing to minimize the bandwidth and resource usage. The improvement of reporting protocol that is implemented reduces frequency of data transfer with the prediction of the changes in user activity and position. The prediction is used as a trigger when the data is about to be sent. The results have shown that the adaptive reporting protocol could improve the performance of the overall reporting protocol. This is shown by the improvement of the bandwidth efficiency up to 36-97%, memory efficiency at 1.5-6% and battery efficiency at 7-13%
LOCAL LINE BINARY PATTERN FOR FEATURE EXTRACTION ON PALM VEIN RECOGNITION
Get PDFIn recent years, palm vein recognition has been studied to overcome problems in conventional systems in biometrics technology (finger print, face, and iris). Those problems in biometrics includes convenience and performance. However, due to the clarity of the palm vein image, the veins could not be segmented properly. To overcome this problem, we propose a palm vein recognition system using Local Line Binary Pattern (LLBP) method that can extract robust features from the palm vein images that has unclear veins. LLBP is an advanced method of Local Binary Pattern (LBP), a texture descriptor based on the gray level comparison of a neighborhood of pixels. There are four major steps in this paper, Region of Interest (ROI) detection, image preprocessing, features extraction using LLBP method, and matching using Fuzzy k-NN classifier. The proposed method was applied on the CASIA Multi-Spectral Image Database. Experimental results showed that the proposed method using LLBP has a good performance with recognition accuracy of 97.3%. In the future, experiments will be conducted to observe which parameter that could affect processing time and recognition accuracy of LLBP is neede
STUDY COMPARISON BACKPROPOGATION, SUPPORT VECTOR MACHINE, AND EXTREME LEARNING MACHINE FOR BIOINFORMATICS DATA
Get PDFA successful understanding on how to make computers learn would open up many new uses of computers and new levels of competence and customization. A detailed understanding on information- processing algorithms for machine learning might lead to a better understanding of human learning abilities and disabilities. There are many type of machine learning that we know, which includes Backpropagation (BP), Extreme Learning Machine (ELM), and Support Vector Machine (SVM). This research uses five data that have several characteristics. The result of this research is all the three investigated models offer comparable classification accuracies. This research has three type conclusions, the best performance in accuracy is BP, the best performance in stability is SVM and the best performance in CPU time is ELM for bioinformatics data
ORBITAL TRAJECTORY SIMULATION ON TWIN STARS SYSTEM IN IFS FRACTAL MODEL BASED ON HYBRID ANIMATION METHOD
No full textIFS (Iterated Function Systems) is a method to model fractal object based on affine transformation functions. The star-like object rotation effect in the IFS fractal model could be exhibited by using metamorphical method, as a replacement to the affine rotation method on a non metamorphic animation. The advantage of a metamorphic animation method over the metamorphic animation method is that the object's relative position to the fixed point as an absolute centroid is absolute. Therefore, the rotational effect can be exhibited at any positions. In addition, it can also be combined with rotational effect of the local centroid itself around the absolute centroid as a fixed point by the primitive rotational operation to form an interesting behavior of orbital trajectory Based on the hybrid of both animation methods, the animation simulation could be done on orbital trajectory on a twin stars rotating to each other as a system. Both objects are rotated in the same angular direction, but started in the opposite position around two closely different fixed points. So, the orbital trajectory yielded forms an elliptical path. The two similar objects can be created efficiently by cloning-scaling technique. In general, the animation method can be modeled as an animation framework
COMPARATIVE STUDY OF RTOS AND PRIMITIVE INTERRUPT IN EMBEDDED SYSTEM
Get PDFMultitasking is one of the most challenging issues in the automation industry which is highly depended on the embedded system. There are two methods to perform multitasking in embedded system: RTOS and primitive interrupt. The main purpose of this research is to compare the performance of R¬TOS with primitive method while concurrently undertaking multiple tasks. The system, which is able to perform various tasks, has been built to evaluate the performance of both methods. There are four tasks introduced in the system: servo task, sensor task, LED task, and LCD task. The performance of each method is indicated by the success rate of the sensor task detection. Sensor task detection will be compared with the true value which is calculated and measured manually during observation time. Observation time was varied after several iterations and the data of the iteration are recorded for both RTOS and primitive interrupt methods. The results of the conducted experiments have shown that, RTOS is more accurate than interrupt method. However, the data variance of the primitive interrupt method is narrower than RTOS. Therefore, to choose a better method, an optimization is needed to be done and each product has its own standard
PARAMETER SIGMOID TRANSFORM CONTRAST ENHANCEMENT FOR DENTAL RADIOGRAPH CLASSIFICATION AND NUMBERING SYSTEM
Get PDFDental record is a method that is used to identify a person. The identification process needs a system that could recognize each individual tooth automatically. The similar intensity level between the teeth and the gums is one of the main problem in tooth identification in a dental radiograph. The intensity problem could influence the segmentation process of the system. In this paper, we proposed a new contrast enhancement by using parameter sigmoid transform to increase the segmentation accuracy. There are five main steps in this method. The first step is to fix the contrast of the image with the proposed method. The next steps are to segment the teeth using horizontal and vertical integral projection, feature extraction, and classification using Support Vector Machine (SVM). The last step is teeth numbering. The experiment result using the proposed method have an accuracy rate of 88% for classification and 73% for teeth numbering
IMAGE SPLICING DETECTION BASED ON DEMOSAICKING AND WAVELET TRANSFORMATION
Get PDFImage splicing is a form of digital image manipulation by combining two or more image into a new image. The application was developed through a passive approach using demosaicking and wavelet transformation method. This research purposed a method to implement the demosaicking and wavelet transform for digital image forgery detection with a passive approach. This research shows that (1) demosaicking can be used as a comparison image in forgery detection; (2) the application of demosaicking and wavelet transformation can improve the quality of the input image (3) demosaicking and wavelet algorithm are able to estimate whether the input image is real or fake image with a passive approach and estimate the manipulation area from the input image
PREFERENCE BASED TERM WEIGHTING FOR ARABIC FIQH DOCUMENT RANKING
Get PDFIn document retrieval, besides the suitability of query with search results, there is also a subjective user assessment that is expected to be a deciding factor in document ranking. This preference aspect is referred at the fiqh document searching. People tend to prefer on certain fiqh methodology without rejecting other fiqh methodologies. It is necessary to investigate preference factor in addition to the relevance factor in the document ranking. Therefore, this research proposed a method of term weighting based on preference to rank documents according to user preference. The proposed method is also combined with term weighting based on documents index and books index so it sees relevance and preference aspect. The proposed method is Inverse Preference Frequency with α value (IPFα). In this method, we calculate preference value by IPF term weighting. Then, the preference values of terms that is equal with the query are multiplied by α. IPFα combined with the existing weighting methods become TF.IDF.IBF.IPFα. Experiment of the proposed method uses dataset of several Arabic fiqh documents. Evaluation uses recall, precision, and f-measure calculations. Proposed term weighting method is obtained to rank the document in the right order according to user preference. It is shown from the result with recall value reach 75%, precision 100%, and f-measure 85.7% respectively
STUDY COMPARISON OF SVM-, K-NN- AND BACKPROPAGATION-BASED CLASSIFIER FOR IMAGE RETRIEVAL
Get PDFClassification is a method for compiling data systematically according to the rules that have been set previously. In recent years classification method has been proven to help many people’s work, such as image classification, medical biology, traffic light, text classification etc. There are many methods to solve classification problem. This variation method makes the researchers find it difficult to determine which method is best for a problem. This framework is aimed to compare the ability of classification methods, such as Support Vector Machine (SVM), K-Nearest Neighbor (K-NN), and Backpropagation, especially in study cases of image retrieval with five category of image dataset. The result shows that K-NN has the best average result in accuracy with 82%. It is also the fastest in average computation time with 17,99 second during retrieve session for all categories class. The Backpropagation, however, is the slowest among three of them. In average it needed 883 second for training session and 41,7 second for retrieve session
SIMULATION OF LANDMARK APPROACH FOR WALL FOLLOWING ALGORITHM ON FIRE-FIGHTING ROBOT USING V-REP
Get PDFAutonomous mobile robot has been implemented to assist humans in their daily activity. Autonomous robots have also contributed significantly in human safety. Autonomous mobile robot have been implemented to assist humans in their daily activity. Autonomous robots Have also contributed significantly in human safety. An example of the autonomous robot in the human safety sector is the fire fighting robot, which is the main topic of this paper. As an autonomous robot, the fire fighting robot needs a robust navigation ability to execute a given task in the shortest time interval. Wall-following algorithm is one of several navigating algorithm that simplifies this autonomous navigation problem. As a contribution, we propose two methods that could be combined to make the existing wall-following algorithm more robust. The combined wall-flowing algorithm will be compared to the original wall-following algorithm. By doing so, we could determine which method has more impact on the robot’s navigation robustness. Our goal is to see which method is more effective when combined with the wall-following algorithm