Judul: Iris Recognition Using Fuzzy Support Vector Machine With Several Kernels
Abstrak: Authentikasi dengan menggunakan salah satu bagian tubuh manusia akhir-akhir ini mengalami perkembangan yang pesat. Salah satunya authentikasi dengan menggunakan bagian tubuh manusia adalah iris yaitu selaput pelangi pada mata. Iris setiap orang mempunyai pola yang berbeda-beda. Hal ini dapat dimungkinkan karena iris mempunyai struktur yang unik.
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Judul: Pengenalan Iris Mata dengan Support Vector Machine Menggunakan Ekstraksi Ciri Log-Gabor Filter
Abstrak: The human eye is one of the identifying characteristics of an individual, especially the iris part. Human iris has a consistent pattern and more reliable than the other biometric subjects such as face and fingerprint which change over time. This research uses the CASIA iris image data. The system uses an automatic segmentation based on threshold to localize the iris collarette and normalize the results to constant dimension using Daugmans rubber sheet model by remapping each point within the iris region to a pair of polar coordinates. The features are extracted using the 1D log-Gabor filter produce a template which will be used as features for the classification process. The template data will be classified by using One-against-all Support Vector Machine (SVM) method. The data are split into five subsets and then alternately used for training data and testing data. These method used three kinds of kernel: Linear kernel, Polynomial kernel, and Radial Basis Function (RBF) kernel. The tests are performed on a dataset of the left eye, a dataset of the right eye, and the combination of both eyes. The best iris recognition accuracy of the dataset for the right eye is at 99%, for the left eye is at 100%, and for the combination of both eyes is at 100%. According to these results, it can be concluded that if there is only one iris image for each individual, then the SVM method is appropriate to be used for iris recognition. The training time required for the dataset of the left eye, the dataset of the right eye, and the combination of both eyes are 0.3368 seconds, 0.3366 seconds and 0.6857 seconds, respectively, while testing time required for a dataset of the left eye, a dataset of the right eye, and the combination of both eyes are 0.0361 seconds, 0.0364 seconds and 0.0638 seconds, respectively.
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Judul: Thermal Characteristics and Dynamics of Tropical Cyclone over Western North Pacific Ocean: A Case Study of Typhoon Songda (Chedeng) 2011
Abstrak: The frequent occasion of Tropical Cyclone (TC) over Western North Pacific (WNP) Ocean lies from 10˚N to 26˚N and 121˚E to 170˚E. Sources of TC development come from warm ocean temperature where latent heat is released during condensation processes and subsequently concentrated in the boundary layer. Relative humidity at 850-700 hPa is responsible to produce the most intense storm. Meanwhile, weak vertical wind shear between 850-200 hPa is one of the dynamical factors that lead to the development of TC. Pressure level of 850-200 hPa is chosen to minimize the thermodynamic effect in the lower troposphere. Typhoon Songda (Chedeng in the Philippines) or TSC lasted from May 18th to 30th, 2011 and strengthened into powerful Super Typhoon stage between May 24th and 27th. Long curving track and the exhibition of all sequences of TC life cycle, TSC is then considered as an ideal case of TC. The objective of the study with case of TSC is to investigate the role of thermal characteristics and dynamics on TC intensity. The research is carried out by using Advanced Research of Weather Research and Forecasting model (WRF ARW model) version 3.3. Two domains are employed in the model. The first domain situate from 02˚N to 40˚N and 118˚E to 149˚E and cover spatial resolution () of 33.1 km. The second domain situate from 09˚N to 27˚N and 119˚E to 132˚E with of 11 km. Timestep of the model () is 120 seconds. The model is supported by the following physical parameterization, i.e., Yonsei University Scheme (YSU) in the boundary layer, Kain-Fritsch scheme (KF) in the cumulus, and WRF Single-Moment 3-class scheme in the microphysics. Initial meteorological condition prior to the formation of the cyclone is generated using WRF ARW standard-release model. Sensitivity of the model output is obtained from a selected single-parameter change scenarios, namely, 10 % to 20 % decrease and increase of wind shear initial data at 850-200 hPa, and by 10 % to 20 % decrease of relative humidity initial data at 850-700 hPa. The result showed that the negative correlations between wind shear and intensity are found in wind shear scenarios. Wind shears of 10 ms-1 which lead to strengthening of the wind intensity in the early period of Typhoon development are found in wind shear scenarios. The effect of wind shear changes on wind intensity is statistically significant in the 20 % wind shear scenarios. During mature stage, weak wind intensity occurred when wind shear increase as given in the WRF standard-release and the 20 % decreasing scenario. Different situation is found in the 20 % increasing scenario where wind shear tend to weak and lead to strong wind intensity at this stage. Meanwhile, the reduction of moisture supply at 850-700 hPa resulting from 20 % decreasing relative humidity play a major role in the weakening of wind intensity and reduces mechanical energy of the cycle process as much as 300 J kg-1.
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