Particle-in-cell and weak turbulence simulations of plasma emission

The plasma emission process, which is the mechanism for solar type II and type III radio bursts phenomena, is studied by means of particle-in-cell and weak turbulence simulation methods. By plasma emission, it is meant as a loose description of a series of processes, starting from the solar flare associated electron beam exciting Langmuir and ion-acoustic turbulence, and subsequent partial conversion of beam energy into the radiation energy by nonlinear processes. Particle-in-cell (PIC) simulation is rigorous but the method is computationally intense, and it is difficult to diagnose the results. Numerical solution of equations of weak turbulence (WT) theory, termed WT simulation, on the other hand, is efficient and naturally lends itself to diagnostics since various terms in the equation can be turned on or off. Nevertheless, WT theory is based upon a number of assumptions. It is, therefore, desirable to compare the two methods, which is carried out for the first time in the present paper with numerical solutions of the complete set of equations of the WT theory and with two-dimensional electromagnetic PIC simulation. Upon making quantitative comparisons it is found that WT theory is largely valid, although some discrepancies are also found. The present study also indicates that it requires large computational resources in order to accurately simulate the radiation emission processes, especially for low electron beam speeds. Findings from the present paper thus imply that both methods may be useful for the study of solar radio emissions as they are complementary.Comment: 21 pages, 9 figure

Meta-Learning for Phonemic Annotation of Corpora

We apply rule induction, classifier combination and meta-learning (stacked classifiers) to the problem of bootstrapping high accuracy automatic annotation of corpora with pronunciation information. The task we address in this paper consists of generating phonemic representations reflecting the Flemish and Dutch pronunciations of a word on the basis of its orthographic representation (which in turn is based on the actual speech recordings). We compare several possible approaches to achieve the text-to-pronunciation mapping task: memory-based learning, transformation-based learning, rule induction, maximum entropy modeling, combination of classifiers in stacked learning, and stacking of meta-learners. We are interested both in optimal accuracy and in obtaining insight into the linguistic regularities involved. As far as accuracy is concerned, an already high accuracy level (93% for Celex and 86% for Fonilex at word level) for single classifiers is boosted significantly with additional error reductions of 31% and 38% respectively using combination of classifiers, and a further 5% using combination of meta-learners, bringing overall word level accuracy to 96% for the Dutch variant and 92% for the Flemish variant. We also show that the application of machine learning methods indeed leads to increased insight into the linguistic regularities determining the variation between the two pronunciation variants studied.Comment: 8 page

Development of Navigation Control Algorithm for AGV Using D* Search Algorithm

In this paper, we present a navigation control algorithm for Automatic Guided Vehicles (AGV) that move in industrial environments including static and moving obstacles using D* algorithm. This algorithm has ability to get paths planning in unknown, partially known and changing environments efficiently. To apply the D* search algorithm, the grid map represent the known environment is generated. By using the laser scanner LMS-151 and laser navigation sensor NAV-200, the grid map is updated according to the changing of environment and obstacles. When the AGV finds some new map information such as new unknown obstacles, it adds the information to its map and re-plans a new shortest path from its current coordinates to the given goal coordinates. It repeats the process until it reaches the goal coordinates. This algorithm is verified through simulation and experiment. The simulation and experimental results show that the algorithm can be used to move the AGV successfully to reach the goal position while it avoids unknown moving and static obstacles. [Keywords— navigation control algorithm; Automatic Guided Vehicles (AGV); D* search algorithm

Uji Patogenitas Bacillus Thuringiensis Var. Israelensis Terhadap Larva Nyamuk Aedes SP. Sebagai Biokontrol Penyebab Penyakit Demam Berdarah Dengue Di Denpasar Tahun 2014

The Dengue Hemorrhagic Fever (DHF) in Indonesia increases every year. In 2008, cases of DHF in Indonesia accounted 137,469 cases (IR: 59.02 per 100,000 population, CFR 0.86%). This increased in 2009 to 154,855 DHF cases (IR: 66.48 per 100,000, CFR 0.89%). In 2010, Indonesia experienced the highest DHF case in ASEAN, namely 156,086 cases with 1,358 deaths (Kemenkes, 2011). Many preventive efforts had been carried out to eradicate Aedes sp. The bioinsecticide vector control using Bacillus thuringiensis is safe for the environment and humans compared to the synthetic insecticides. This study evaluated the pathogenicity of B. thuringiensis against larvae of Aedes sp. in Denpasar city. This study conducted Quasy Experimental Design of 6 treatments, concentrations of 50 µL, 40 µL, 30 µL, 20 µL, 10 µL and 1 control, with 4 repetitions. The number of cells and spores of B. thuringiensis used in this study was 11.2 x 109 cfu/ml and 7.43 x 109 cfu/ml, respectively. The highest mean score difference compared to the control was the 50 µL concentration with average larvae mortality at 6 hours of 96%, increasing to 100% in 12 and 24 hours. LC50 concentration within 6 hours was 4 µl/L, and LC90 concentration was 16 µl/L. Using statistical test, average mortality of larvae Aedes sp. at all concentrations were similar (p ? 0.005). The greater concentration of B. thuringiensis and the longer exposure time leads to a greater mortality of Aedes sp. larvae

Characteristics of switching plasma in an inverse-pinch switch

Characteristics of the plasma that switches on tens of giga volt-ampere in an inverse-pinch plasma switch (INPIStron) have been made. Through optical and spectroscopic diagnostics of the current carrying plasma, the current density, the motion of current paths, dominant ionic species have been determined in order to access their effects on circuit parameters and material erosion. Also the optimum operational condition of the plasma-puff triggering method required for azimuthally uniform conduction in the INPIStron has been determined

Bending and Breaking of Stripes in a Charge-Ordered Manganite

In complex electronic materials, coupling between electrons and the atomic lattice gives rise to remarkable phenomena, including colossal magnetoresistance and metal-insulator transitions. Charge-ordered phases are a prototypical manifestation of charge-lattice coupling, in which the atomic lattice undergoes periodic lattice displacements (PLDs). Here we directly map the picometer scale PLDs at individual atomic columns in the room temperature charge-ordered manganite Bi$_{0.35}$Sr$_{0.18}$Ca$_{0.47}$MnO$_3$ using aberration corrected scanning transmission electron microscopy (STEM). We measure transverse, displacive lattice modulations of the cations, distinct from existing manganite charge-order models. We reveal locally unidirectional striped PLD domains as small as $\sim$5 nm, despite apparent bidirectionality over larger length scales. Further, we observe a direct link between disorder in one lattice modulation, in the form of dislocations and shear deformations, and nascent order in the perpendicular modulation. By examining the defects and symmetries of PLDs near the charge-ordering phase transition, we directly visualize the local competition underpinning spatial heterogeneity in a complex oxide.Comment: Main text: 20 pages, 4 figures. Supplemental Information: 27 pages, 14 figure