Photoelastic force measurements in granular materials

Photoelastic techniques are used to make both qualitative and quantitative measurements of the forces within idealized granular materials. The method is based on placing a birefringent granular material between a pair of polarizing filters, so that each region of the material rotates the polarization of light according to the amount of local of stress. In this review paper, we summarize past work using the technique, describe the optics underlying the technique, and illustrate how it can be used to quantitatively determine the vector contact forces between particles in a 2D granular system. We provide a description of software resources available to perform this task, as well as key techniques and resources for building an experimental apparatus

Computational intelligence approaches to robotics, automation, and control [Volume guest editors]

No abstract available

Optimisation of Mobile Communication Networks - OMCO NET

The mini conference “Optimisation of Mobile Communication Networks” focuses on advanced methods for search and optimisation applied to wireless communication networks. It is sponsored by Research & Enterprise Fund Southampton Solent University. The conference strives to widen knowledge on advanced search methods capable of optimisation of wireless communications networks. The aim is to provide a forum for exchange of recent knowledge, new ideas and trends in this progressive and challenging area. The conference will popularise new successful approaches on resolving hard tasks such as minimisation of transmit power, cooperative and optimal routing

Speeding Up Particle Filter Algorithm for Tracking Multiple Targets Using CUDA Programming

This thesis proposes to work on a parallelization method to speed up the computational runtime of the particle filter algorithm for multiple targets tracking. CUDA programming is utilized to execute the original implementation of the particle filter algorithm on GPU. The thesis provides a detailed discussion of the background information on the relevant topics. And then a presentation of the code architecture changes is followed. The detailed CUDA-based implementation is illustrated and discussed, which is followed by a discussion andcomparison of the results obtained from a series of tests.In this thesis, the introduction and description of the basic particle filter are presented first. Detailed illustrations of each step in the original implementation of the particle filter algorithm, which is executed sequentially on CPU, are provided. Then, background information of parallel programming technologies is provided, such as GPGPU and CUDA programming. The new design of the CUDA based implementation of the particle filter algorithm is proposed to speed up the execution of the original implementation, which is executed on CPU. Moreover, a detailed explanation of the CUDA-based implementation is given.Finally, the thesis will demonstrate the test results for both CPU and CUDA implementation as a comparison. The experiments indicate that the CUDA implementation can obtain a maximum of 7.5x speedup over the original implementation. After implementing more results and comparison, it was concluded that the CUDA implementation was significantly faster than the CPU version. Furthermore, the CUDA version still has much space for future optimizations to increase its performance

Survey of location-centric target tracking with mobile elements in wireless sensor networks

介绍目标跟踪的过程以及移动跟踪的特点;通过区分目标定位为主的方法和目标探测为主的方法,介绍定位为主的移动式目标跟踪方法(称为目标的移动式定位跟踪; )的研究现状;分析和比较不同方法的特点和应用领域,发现现有方法虽然可以提高跟踪质量、降低网络整体能耗,但是还存在一些问题。基于此,总结目标的移动; 式定位跟踪方法在方法类型、网络结构和节点模型等方面可能存在的研究热点,指出其研究和发展趋势。The basic process of target tracking and the properties of tracking; solutions with mobile elements were introduced. By distinguishing; location-centric methods and detection-centric methods, the current; research status of the location-centric target tracking methods were; reviewed. The properties and application fields of different solutions; were analyzed and compared. Although the existing solutions can; significantly improve tracking quality and reduce energy consumption of; the whole network, there are also some problems. Based on these; discoveries, some possible research hotspots of mobile solutions were; summarized in many aspects, such as method types, network architecture,; node model, and so on, indicating the future direction of research and; development.国家自然科学基金资助项目; 国家科技支撑计划项

Event-based Vision: A Survey

Event cameras are bio-inspired sensors that differ from conventional frame cameras: Instead of capturing images at a fixed rate, they asynchronously measure per-pixel brightness changes, and output a stream of events that encode the time, location and sign of the brightness changes. Event cameras offer attractive properties compared to traditional cameras: high temporal resolution (in the order of microseconds), very high dynamic range (140 dB vs. 60 dB), low power consumption, and high pixel bandwidth (on the order of kHz) resulting in reduced motion blur. Hence, event cameras have a large potential for robotics and computer vision in challenging scenarios for traditional cameras, such as low-latency, high speed, and high dynamic range. However, novel methods are required to process the unconventional output of these sensors in order to unlock their potential. This paper provides a comprehensive overview of the emerging field of event-based vision, with a focus on the applications and the algorithms developed to unlock the outstanding properties of event cameras. We present event cameras from their working principle, the actual sensors that are available and the tasks that they have been used for, from low-level vision (feature detection and tracking, optic flow, etc.) to high-level vision (reconstruction, segmentation, recognition). We also discuss the techniques developed to process events, including learning-based techniques, as well as specialized processors for these novel sensors, such as spiking neural networks. Additionally, we highlight the challenges that remain to be tackled and the opportunities that lie ahead in the search for a more efficient, bio-inspired way for machines to perceive and interact with the world