Rapid Fabrication of Large-sized Solid Shape using Variable Lamination Manufacturing and Multi-functional Hotwire Cutting System

Rapid prototyping (RP) technologies have been widely used to reduce the lead-time and development cost of new products. The VLM-ST process has been developed to overcome the currently developed RP technologies such as a large building time, a high building cost, an additional post-processing and a large apparatus cost. However, the VLM-ST process has the limitation of fabricated model size (VLM300: 297×210 mm, VLM400: 420×297 mm) and the limitation of slope angle when the large-sized model more than 600 × 600 × 600 mm or axisymmetric shape is fabricated. The objective of this paper is to develop a multi-functional hotwire cutting system (MHC) using EPS-foam block or sheet as the working material in order to fabricate a large-sized shape more than 600 × 600 × 600 mm. Because the MHC apparatus employs a four-axis synchronized hotwire cutter with the structure of two XY movable heads and a turn-table, it allows the easy fabrication of various 3D shapes, such as (1) an axisymmetric shape or a sweeping cross-sectioned pillar shape using the hot-strip in the form of sweeping surface and EPS foam block on the turn-table, (2) a polyhedral complex shape using the hotwire and EPS foam block on the turn-table, and (3) a ruled surface approximated freeform shape using the hotwire and EPS foam sheet. In order to examine the applicability of the developed MHC apparatus, an axisymmetric shape, a polyhedral shape and a large-sized freeform shape were fabricated by the apparatus.Mechanical Engineerin

Deep Virtual Networks for Memory Efficient Inference of Multiple Tasks

Deep networks consume a large amount of memory by their nature. A natural question arises can we reduce that memory requirement whilst maintaining performance. In particular, in this work we address the problem of memory efficient learning for multiple tasks. To this end, we propose a novel network architecture producing multiple networks of different configurations, termed deep virtual networks (DVNs), for different tasks. Each DVN is specialized for a single task and structured hierarchically. The hierarchical structure, which contains multiple levels of hierarchy corresponding to different numbers of parameters, enables multiple inference for different memory budgets. The building block of a deep virtual network is based on a disjoint collection of parameters of a network, which we call a unit. The lowest level of hierarchy in a deep virtual network is a unit, and higher levels of hierarchy contain lower levels' units and other additional units. Given a budget on the number of parameters, a different level of a deep virtual network can be chosen to perform the task. A unit can be shared by different DVNs, allowing multiple DVNs in a single network. In addition, shared units provide assistance to the target task with additional knowledge learned from another tasks. This cooperative configuration of DVNs makes it possible to handle different tasks in a memory-aware manner. Our experiments show that the proposed method outperforms existing approaches for multiple tasks. Notably, ours is more efficient than others as it allows memory-aware inference for all tasks.Comment: CVPR 201

Geometrically Induced Phase Transitions at Large N

Utilizing the large N dual description of a metastable system of branes and anti-branes wrapping rigid homologous S^2's in a non-compact Calabi-Yau threefold, we study phase transitions induced by changing the positions of the S^2's. At leading order in 1/N the effective potential for this system is computed by the planar limit of an auxiliary matrix model. Beginning at the two loop correction, the degenerate vacuum energy density of the discrete confining vacua split, and a potential is generated for the axion. Changing the relative positions of the S^2's causes discrete jumps in the energetically preferred confining vacuum and can also obstruct direct brane/anti-brane annihilation processes. The branes must hop to nearby S^2's before annihilating, thus significantly increasing the lifetime of the corresponding non-supersymmetric vacua. We also speculate that misaligned metastable glueball phases may generate a repulsive inter-brane force which stabilizes the radial mode present in compact Calabi-Yau threefolds.Comment: 47 pages, 7 figure