Acceleration of the Presenter Detection Algorithms Using FPGA as a Coprocessor for Effective Video Recording

In a video recording of a presentation session, presenter detection is required in order for the camera to have the ability to track the face of the presenter. High computation power is required to perform video processing for the detection of the presenter. Instead of using a normal embedded to perform real time video processing, Field Programmable Gate Array (FPGA) can be used as a coprocessor to perform complex computation algorithm. FGPA coprocessors can be used with standard microprocessor or microcontroller to handle complex tasks and subsequently improve the performance

Optimization of building-integrated photovoltaic thermal air system combined with thermal storage

Photovoltaic (PV) combined with phase change material (PV/PCM) system is a hybrid solar system that uses a PCM to reduce the PV temperature and to store energy for other applications. This study aims to increase the integrated PV efficiency of buildings by incorporating PCM while utilizing the stored heat in PCM for controlling indoor conditions. Experiments have been carried out on a prototype PV/PCM air system using monocrystalline PV modules. Transient simulations of the system performance have also been performed using a commercial computational fluid dynamics package based on the finite volume method. The results from simulation were validated by comparing it with experimental results. The results indicate that PCM is effective in limiting temperature rise in PV device and the heat from PCM can enhance night ventilation and decrease the building energy consumption to achieve indoor thermal comfort for certain periods of time

Attention Clusters: Purely Attention Based Local Feature Integration for Video Classification

Recently, substantial research effort has focused on how to apply CNNs or RNNs to better extract temporal patterns from videos, so as to improve the accuracy of video classification. In this paper, however, we show that temporal information, especially longer-term patterns, may not be necessary to achieve competitive results on common video classification datasets. We investigate the potential of a purely attention based local feature integration. Accounting for the characteristics of such features in video classification, we propose a local feature integration framework based on attention clusters, and introduce a shifting operation to capture more diverse signals. We carefully analyze and compare the effect of different attention mechanisms, cluster sizes, and the use of the shifting operation, and also investigate the combination of attention clusters for multimodal integration. We demonstrate the effectiveness of our framework on three real-world video classification datasets. Our model achieves competitive results across all of these. In particular, on the large-scale Kinetics dataset, our framework obtains an excellent single model accuracy of 79.4% in terms of the top-1 and 94.0% in terms of the top-5 accuracy on the validation set. The attention clusters are the backbone of our winner solution at ActivityNet Kinetics Challenge 2017. Code and models will be released soon.Comment: The backbone of the winner solution at ActivityNet Kinetics Challenge 201

Unconventional Superconducting Symmetry in a Checkerboard Antiferromagnet

We use a renormalized mean field theory to study the Gutzwiller projected BCS states of the extended Hubbard model in the large $U$ limit, or the $t$-$t'$-$J$-$J'$ model on a two-dimensional checkerboard lattice. At small $t'/t$, the frustration due to the diagonal terms of $t'$ and $J'$ does not alter the $d_{x^2-y^2}$-wave pairing symmetry, and the negative (positive) $t'/t$ enhances (suppresses) the pairing order parameter. At large $t'/t$, the ground state has an extended s-wave symmetry. At the intermediate $t'/t$, the ground state is $d+id$ or $d+is$-wave with time reversal symmetry broken.Comment: 6 pages, 6 figure

A Symbolic Model Checking Approach to Verifying Satellite Onboard Software

This paper discusses the use of symbolic model checking technology to verify the design of an embedded software control system called attitude and orbit control system (AOCS). This system is mission-critical because it is responsible for maintaining the attitude of the satellite and for performing fault detection, isolation, and recovery decisions of the satellite. An executable AOCS implementation by Space Systems Finland has been provided to us in Ada source code form. In order to use symbolic model checking methods, the Ada implementation of the system was modeled at a quite detailed implementation level using the input language of the symbolic model checker NuSMV 2. We describe the modeling techniques and abstractions used to alleviate the state explosion problem due to handling of timers and the large number of system components controlled by AOCS. The specification of the required system behavior was also provided to us in a form of extended state machine diagrams with prioritized transitions. These diagrams have been translated to a set of temporal logic properties, allowing the piecewise checking of the system behavior one extended state machine transition at a time. We also report on the scalability of symbolic model checking tools for the case study at hand as well as discuss potential topics for future work