Simulation of Filament Heater for Uniform Emission from Dispenser Cathode

This paper presents the design study of toroid shape filament heater for dispenser cathode.The filament heater will be used in cathode assembly of 200 kW 42 GHz gyrotron. A 3 D model of cathode assembly is designed using electromagnetic and thermal simulation software, ANSYS. The simulations are performed for optimizing the input filament heater power with respect to cathode surface temperature. The parametric study shows that the input power and cathode surface temperature depends strongly on the potting material, diameter of filament, number of turns, position and height of the filament heater with respect to cathode pellet. The design analyses are also carried out for two different filament heater materials i.e. tungsten and molybdenum. Further, the thermal, structural and transient analyses are also carried out to study the mechanical strength of the filament heater. It is concluded that the input heater power should be greater than 200 W to achieve cathode surface temperature greater than 1,000°C.     

Scandinavian Thins on Top of Cake: New and Improved Algorithms for Stacking and Packing

We show how to compute the smallest rectangle that can enclose any polygon, from a given set of polygons, in nearly linear time; we also present a PTAS for the problem, as well as a linear-time algorithm for the case when the polygons are rectangles themselves. We prove that finding a smallest convex polygon that encloses any of the given polygons is NP-hard, and give a PTAS for minimizing the perimeter of the convex enclosure. We also give efficient algorithms to find the smallest rectangle simultaneously enclosing a given pair of convex polygons.     

Reoptimization of the Shortest Common Superstring Problem

A reoptimization problem describes the following scenario: given an instance of an optimization problem together with an optimal solution for it, we want to find a good solution for a locally modified instance.     

Modelling water dynamics with DNDC and DAISY in a soil of the North China Plain: A comparative study

The performance of the DNDC and Daisy model to simulate the water dynamics in a floodplain soil of the North China Plain was tested and compared. While the DNDC model uses a simple cascade approach, the Daisy model applies the physically based Richard's equation for simulating water movement in soil. For model testing a three years record of the soil water content from the Dong Bei Wang experimental station near Beijing was used. There, the effect of nitrogen fertilization, irrigation and straw removal on soil water and nitrogen dynamics was investigated in a three factorial field experiment applying a split-split-plot design with 4 replications. The dataset of one treatment was used for model testing and calibration. Two other independent datasets from further treatments were employed for validating the models. For both models, the simulation results were not satisfying using default parameters. After parameter optimisation and the use of site-specific van Genuchten parameters, however, the Daisy model performed well. But, for the DNDC model, parameter optimisation failed to improve the simulation result. Owing to the fact that many biological processes such as plant growth, nitrification or denitrification depend strongly on the soil water content, our findings bring us to the conclusion that the site-specific suitability of the DNDC model for simulating the soil water dynamics should be tested before further simulation of other processes.     

Putting it all together – Formal verification of the VAMP

In the verified architecture microprocessor (VAMP) project we have designed, functionally verified, and synthesized a processor with full DLX instruction set, delayed branch, Tomasulo scheduler, maskable nested precise interrupts, pipelined fully IEEE compatible dual precision floating point unit with variable latency, and separate instruction and data caches. The verification has been carried out in the theorem proving system PVS. The processor has been implemented on a Xilinx FPGA. A shorter version of this article with the title “Instantiating uninterpreted functional units and memory system: functional verification of the VAMP” appeared in [8]. The work reported here was done while all the authors were with Saarland University.     

Kernel least-squares models using updates of the pseudoinverse

Sparse nonlinear classification and regression models in reproducing kernel Hilbert spaces (RKHSs) are considered. The use of Mercer kernels and the square loss function gives rise to an overdetermined linear least-squares problem in the corresponding RKHS. When we apply a greedy forward selection scheme, the least-squares problem may be solved by an order-recursive update of the pseudoinverse in each iteration step. The computational time is linear with respect to the number of the selected training samples.     

First-order and second-order statistical analysis of 3D and 2D image structure

In the first part of this article, we analyze the relation between local image structures (i.e., homogeneous, edge-like, corner-like or texture-like structures) and the underlying local 3D structure (represented in terms of continuous surfaces and different kinds of 3D discontinuities) using range data with real-world color images. We find that homogeneous image structures correspond to continuous surfaces, and discontinuities are mainly formed by edge-like or corner-like structures, which we discuss regarding potential computer vision applications and existing assumptions about the 3D world. In the second part, we utilize the measurements developed in the first part to investigate how the depth at homogeneous image structures is related to the depth of neighbor edges. For this, we first extract the local 3D structure of regularly sampled points, and then, analyze the coplanarity relation between these local 3D structures. We show that the likelihood to find a certain depth at a homogeneous image patch depends on the distance between the image patch and a neighbor edge. We find that this dependence is higher when there is a second neighbor edge which is coplanar with the first neighbor edge. These results allow deriving statistically based prediction models for depth interpolation on homogeneous image structures.