Texture Feature Extraction by Using Local Binary Pattern

Local Binary Pattern (LBP) is a method that used to describe texture characteristics of the surfaces. By applying LBP, texture pattern probability can be summarised into a histogram. LBP values need to be determined for all of the image pixels. Texture regularity might be determined based on the distribution shape of the LBP histogram. The implementation results of LBP on two texture types - synthetic and natural textures - shows that extracted texture feature can be used as input for pattern classification. Euclidean distance method is applied to classify the texture pattern obtained from LBPcomputation

Optimasi Kinerja Protokol Aodv Dengan Static Intersection Node

VANET adalah sebuah pengembangan teknologi yang memungkinkan komunikasi antar kendaraan meskipun tidak terdapat koneksi secara langsung antara kendaraan yang berkomunikasi. Untuk meningkatkan performa protokol routing, maka pada penelitian ini akan ditambahkan SIN (Static Intersection Node). Static Intersection Node adalah RSU (Road Side Unit) yang diletakkan di persimpangan jalan (intersection). Fungsi dari Static Intersection Node pada penelitian ini adalah sebagai repeater untuk membantu mengirimkan paket data ke kendaraan lain yang berada disekitarnya sehingga dapat meningkatkan Packet Delivery Ratio serta meminimalkan Packet Loss dan End to End Delay

Aplikasi Secure E-election dengan Memanfaatkan Fungsi Kriptografi dan Teknologi Fingerprint untuk Mendukung E-democracy

Proses Pemilihan Umum (Pemilu) seperti Pemilihan Kepala Daerah (Pilkada), Pemilihan Legislatif (Pileg), dan Pemilihan Presiden (Pilpres) di Indonesia dewasa ini masih rawan kecurangan untuk kepentingan salah satu golongan, seperti yang terindikasi kuat terjadi pada beberapa Pilkada yang telah dilaksanakan. Hal ini terjadi karena terdapat beberapa titik dalam tahapan Pemilu yang berpotensi besar bisa dilakukan berbagai macam kecurangan. Kecurangan ini bisa berupa manipulasi data pada saat proses pengiriman hasil penghitungan suara di Tempat Pemungutan Suara (TPS) untuk direkapitulasi di tingkat Panitia Pemilihan Kecamatan (PPK). Hal lain yang dapat dimanfaatkan adalah adanya sisa kertas suara yang juga berpotensi menimbulkan praktik curang. Secara sistem juga belum dapat dibuktikan seorang pemilih benar-benar melakukan pemilihan di sebuah TPS. Sistem yang berlaku sekarang, petugas KPPS-lah yang mencatat kehadiran seorang pemilih. Dengan berbagai potensi kecurangan tersebut, sudah saatnya kita berupaya untuk mengatasi dan mencegah hal-hal tersebut terjadi pada pemilihan yang akan datang. Pemerintah telah membentuk Panitia Pengawas Pemilu (Panwaslu) untuk meminimalisir terjadinya berbagai kecurangan dalam Pemilu. Namun demikian, tetap harus ada perbaikan terkait dengan sistem pemilihan yang selama ini digunakan dan masih dilakukan secara manual (by paper). Dengan memanfaatkan kemajuan teknologi, sistem Pemilu di Indonesia dapat dilakukan secara elektronik. Penerapan sistem Pemilu secara elektronik dapat memberikan berbagai kemudahan dan keuntungan dibandingkan dengan pemilihan secara manual. Namun, dibalik kemudahan dan keuntungan yang diberikan belum tentu sistem pemilihan secara elektronik itu aman. Dengan demikian harus ada suatu jaminan keamanan terhadap sistem tersebut. Salah satu cara untuk memberikan jaminan keamanan sistem adalah dengan menerapkan fungsi kriptografi pada sistem pemilihan elektronik tersebut sehingga mampu mengatasi kerawanan kecurangan yang mungkin terjadi. Aplikasi Secure e-election merupakan konsep Pemilu secara elektronik yang menerapkan fungsi kriptografi dan mendukung azas Pemilu yaitu Langsung, Umum, Bebas, Rahasia, Jujur, dan Adil (LUBER JURDIL). Aplikasi ini terdiri dari aplikasi pendaftaran pemilih, aplikasi pemungutan suara, aplikasi pengecekan pilihan serta aplikasi web untuk mengakses daftar pemilih dan hasil pemilu. Fitur yang terdapat dalam aplikasi ini adalah database online yang memuat daftar pemilih se-Indonesia dan hasil pemilihan serta otentikasi pemilih dilakukan dengan menggunakan fingerprint sehingga memungkinkan pemilih melakukan pemilihan di TPS manapun

The Effects of Rootone-F Plant Growth Regulators on the Growth of Duabanga mollucana. Blume Cuttings

Wood shortage supply from natural forest effected the running of wood-based industry. Therefore forestry entrepreneurs began to switch from also growing tree species to fast growing tree species. Duabanga moluccana Blume is one type of native tree in Indonesia who can growing  fast and have good characteristics for industrial raw materials. Multiplication of Duabanga mollucana can be planting by seeds and also by vegetative propagation. Shoot and stem cuttings is one alternative was to obtain plantation in sufficient quantities and in sort time. The addition of plant growth regulators (Rootone - F) was expected to increase the percentage of rooted materials cuttings and the survival percentage

Energy spectrum and the absolute flux of various celestial X-ray sources

The results on the flux of low energy X-rays in the range 2-18 Kev from Sco-X1, Tau-X1 and Cen-X2 celestial sources observed during two rocket flights, flown from the Thumba Equatorial Rocket Launching Station (TERLS), Trivandrum, India, are presented. The absolute flux and the energy spectrum obtained for these sources are compared with other similar observations. The results indicate a long-term exponential decrease in the energy flux of X-rays from Sco-X1 over the period 1965-1968. The X-ray source Cen-X2, which showed a remarkable outburst of X-rays in April 1967, had ceased to be active after May 1967. We present here the first evidence of the rediscovery of the low energy, X-ray flux from Cen-X2 since May 1967. These short-lived X-ray out-bursts may be attributed to a shock wave from the nova outburst expanding into the circumstellar medium

Nitrogen and potassium nutrition of French basil (Ocimum basilicum Linn.)

Studies were undertaken on red sandy loam soil (Kandiustalf) in a semi-arid tropical climateat Bangalore (Karnataka) to find out the effect of fertilizer application in influencing oilproduction, quality and soil fertility in French basil (Ocimum basilicum). The study showedthat application of nitrogen (up to 100 kg ha-1) increased herb and essential oil yields in themain crop, first ratoon and second crop while potassium application (up to 80 kg ha-1)increased the yields in the second ratoon and second crop suggesting that soil potassiumdepletion occurred with time.  Nitrogen application increased methyl chavicol (by 4.1%) anddecreased linalool (by 14.2%) contents in basil oil. Yield increases were accompanied by higherremoval of nitrogen, phosphorus and potassium from soil (by 247%, 23% and 94%,respectively) by the crop and lower amounts of exchangeable potassium (by 37.8 %) in soil.Due to the depletion of soil potassium, interactions between nitrogen and potassium weresignificant in the second crop of basil. Application of 100 kg nitrogen ha-1 and 80 kg potassiumha-1 gave optimum yield and quality of oil. &nbsp

Data-driven coarse graining in action: Modeling and prediction of complex systems

In many physical, technological, social, and economic applications, one is commonly faced with the task of estimating statistical properties, such as mean first passage times of a temporal continuous process, from empirical data (experimental observations). Typically, however, an accurate and reliable estimation of such properties directly from the data alone is not possible as the time series is often too short, or the particular phenomenon of interest is only rarely observed. We propose here a theoretical-computational framework which provides us with a systematic and rational estimation of statistical quantities of a given temporal process, such as waiting times between subsequent bursts of activity in intermittent signals. Our framework is illustrated with applications from real-world data sets, ranging from marine biology to paleoclimatic data

Efficient Density Estimation via Piecewise Polynomial Approximation

We give a highly efficient "semi-agnostic" algorithm for learning univariate probability distributions that are well approximated by piecewise polynomial density functions. Let $p$ be an arbitrary distribution over an interval $I$ which is $\tau$-close (in total variation distance) to an unknown probability distribution $q$ that is defined by an unknown partition of $I$ into $t$ intervals and $t$ unknown degree-$d$ polynomials specifying $q$ over each of the intervals. We give an algorithm that draws \tilde{O}(t\new{(d+1)}/\eps^2) samples from $p$, runs in time \poly(t,d,1/\eps), and with high probability outputs a piecewise polynomial hypothesis distribution $h$ that is (O(\tau)+\eps)-close (in total variation distance) to $p$. This sample complexity is essentially optimal; we show that even for $\tau=0$, any algorithm that learns an unknown $t$-piecewise degree-$d$ probability distribution over $I$ to accuracy \eps must use \Omega({\frac {t(d+1)} {\poly(1 + \log(d+1))}} \cdot {\frac 1 {\eps^2}}) samples from the distribution, regardless of its running time. Our algorithm combines tools from approximation theory, uniform convergence, linear programming, and dynamic programming. We apply this general algorithm to obtain a wide range of results for many natural problems in density estimation over both continuous and discrete domains. These include state-of-the-art results for learning mixtures of log-concave distributions; mixtures of $t$-modal distributions; mixtures of Monotone Hazard Rate distributions; mixtures of Poisson Binomial Distributions; mixtures of Gaussians; and mixtures of $k$-monotone densities. Our general technique yields computationally efficient algorithms for all these problems, in many cases with provably optimal sample complexities (up to logarithmic factors) in all parameters