ABC-CNN: An Attention Based Convolutional Neural Network for Visual Question Answering

We propose a novel attention based deep learning architecture for visual question answering task (VQA). Given an image and an image related natural language question, VQA generates the natural language answer for the question. Generating the correct answers requires the model's attention to focus on the regions corresponding to the question, because different questions inquire about the attributes of different image regions. We introduce an attention based configurable convolutional neural network (ABC-CNN) to learn such question-guided attention. ABC-CNN determines an attention map for an image-question pair by convolving the image feature map with configurable convolutional kernels derived from the question's semantics. We evaluate the ABC-CNN architecture on three benchmark VQA datasets: Toronto COCO-QA, DAQUAR, and VQA dataset. ABC-CNN model achieves significant improvements over state-of-the-art methods on these datasets. The question-guided attention generated by ABC-CNN is also shown to reflect the regions that are highly relevant to the questions

Design of a Six-Swing-Arm Wheel-Legged Chassis for Forestry and Simulation Analysis of its Obstacle-Crossing Performance

Obstacle-crossing performance is an important criterion for evaluating the power chassis of forestry machinery. In this paper, a new six-swing-arm wheel-legged chassis (SWC&F) is designed according to the characteristics of forest terrain, using herringbone legs to control the ride comfort and stability of the chassis in the process of crossing obstacles. First, the kinematic model of the SWC&F is established, the coordinate analytical expression of each wheel centre position is derived, and the swing angle range of each wheel leg of the chassis is calculated according to the installation position of the hydraulic cylinder. Next, the control model of the system is constructed, and the obstacle-crossing performance of the SWC&F is analyzed by ADAMS/Simulink co-simulation using the PID control method and conventional control method, respectively. The results show that the maximum obstacle crossing height of the SWC&F can reach 411.1 mm, and the chassis with PID control system has good dynamic response characteristics and smooth motion, which meets the requirements of forest chassis obstacle crossing design. The study can provide the foundation for the practical laws of the physical prototype of the forest vehicle chassis

On the Uniqueness of Balanced Complex Orthogonal Design

Complex orthogonal designs (CODs) play a crucial role in the construction of space-time block codes. Their real analog, real orthogonal designs (or equivalently, sum of squares composition formula) have a long history. Adams et al. (2011) introduced the concept of balanced complex orthogonal designs (BCODs) to address practical considerations. BCODs have a constant code rate of $1/2$ and a minimum decoding delay of $2^m$, where $2m$ is the number of columns. Understanding the structure of BCODs helps design space-time block codes, and it is also fascinating in its own right. We prove, when the number of columns is fixed, all (indecomposable) balanced complex orthogonal designs (BCODs) have the same parameters $[2^m, 2m, 2^{m-1}]$, and moreover, they are all equivalent