An intelligent approach to design three-dimensional aircraft sheet metal part model for manufacture

Aircraft sheet metal part manufacturing is a knowledge-intensive process, and the manufacturability and manufacturing information are required to be considered in three-dimensional (3D) model by knowledge reuse. This paper presents a 3D model structure of the aircraft sheet metal part and an intelligent approach to design the model for manufacture combining intelligent manufacturability analysis with manufacturing information definition. Processability of part, formability of material and cost of fabrication are proposed to analyse the manufacturability of the part. Knowledge base for manufacturability analysis is established, and knowledge is reused to evaluate the part’s manufacturability intelligently to meet the constraints of manufacturing conditions. Non-geometric information is defined in the 3D model to meet the needs of digital manufacturing and inspection using model-based technology. An example is given to describe the process of design for manufacture, which shows that the approach can realize the concurrent design and digital manufacturing of aircraft sheet metal

A digital definition method for manufacturing model of aircraft integral panel

The manufacturing model of aircraft integral panel is presented based on the analysis of its structure and manufacturing process. The manufacturing model for each key process consists of model for processing and model for workpiece to bridge digital design and fabricating. Model for workpiece is used to express the target part information at the end of some operation. Model for processing is used to describe the intermediate state information, and it aims to attain but is different the workpiece because of process factors. The definition flow of the manufacturing model is given. The modeling approach of integral panel part blank from shot peen forming part model orienting to NC cutting is proposed and exemplified. It is analyzed that the approaches above can define the models accurately and totally to meet the needs of process planning , NC fabricating and inspecting

Charge-Density-Wave Transitions of Dirac Fermions Coupled to Phonons

The spontaneous generation of charge-density-wave order in a Dirac fermion system via the natural mechanism of electron-phonon coupling is studied in the framework of the Holstein model on the honeycomb lattice. Using two independent and unbiased quantum Monte Carlo methods, the phase diagram as a function of temperature and coupling strength is determined. It features a quantum critical point as well as a line of thermal critical points. Finite-size scaling appears consistent with fermionic Gross-Neveu-Ising universality for the quantum phase transition, and bosonic Ising universality for the thermal phase transition. The critical temperature has a maximum at intermediate couplings. Our findings motivate experimental efforts to identify or engineer Dirac systems with sufficiently strong and tunable electron-phonon coupling.Comment: 4+3 pages, 4+2 figure

VQS: Linking Segmentations to Questions and Answers for Supervised Attention in VQA and Question-Focused Semantic Segmentation

Rich and dense human labeled datasets are among the main enabling factors for the recent advance on vision-language understanding. Many seemingly distant annotations (e.g., semantic segmentation and visual question answering (VQA)) are inherently connected in that they reveal different levels and perspectives of human understandings about the same visual scenes --- and even the same set of images (e.g., of COCO). The popularity of COCO correlates those annotations and tasks. Explicitly linking them up may significantly benefit both individual tasks and the unified vision and language modeling. We present the preliminary work of linking the instance segmentations provided by COCO to the questions and answers (QAs) in the VQA dataset, and name the collected links visual questions and segmentation answers (VQS). They transfer human supervision between the previously separate tasks, offer more effective leverage to existing problems, and also open the door for new research problems and models. We study two applications of the VQS data in this paper: supervised attention for VQA and a novel question-focused semantic segmentation task. For the former, we obtain state-of-the-art results on the VQA real multiple-choice task by simply augmenting the multilayer perceptrons with some attention features that are learned using the segmentation-QA links as explicit supervision. To put the latter in perspective, we study two plausible methods and compare them to an oracle method assuming that the instance segmentations are given at the test stage.Comment: To appear on ICCV 201

CEBus demonstration system

A CEBus demonstration system is constructed and applied to aspects of home automation security. Two M68HC16Z1 evaluation boards are used as CEBus nodes. Two CEBus spread spectrum power line modems (SSC PLCEMS) interconnect the nodes. An SSC PLCEMS handles all spread spectrum signal generation and reception. The application programs in the two boards are written in assembly language based upon CAL (Common Application Language), a CEBus standard. The standard CEBus frame format and FCS (Frame Check Sequence) are implemented by software in the Data Link Layer. Encoding and decoding binary information into UST format are implemented in the Physical Layer. The system responsiveness of 30 millisec was measured experimentally for a case with 3 information bytes. The noise sensitivity was measured experimentally with a straight 3-wire connection of the modems with and without AC power. The distorted AC line caused a packet error rate of 2%, a higher rate than obtained by injecting broadband random noise