Application of cold filamentary microplasma pretreatment assisted by thermionic emission for potato drying

Cold filamentary microplasma (CFM) pretreatment assisted by thermionic emission (TE) is a promising, cold drying technology for agricultural products. Such novel pretreatment method based on local electroporation process in the air gap. Brief theory and treatment mechanism are explained. A fractional factorial design 3³ was used to determine the effect of CFM treatment assisted by TE parameters such as pulse frequency (F = 40, 80 and 120 Hz), pretreatment duration (D = 60, 120 and 180 s) and temperature of thermionic source (T = 700, 850 and 1000 °C) on drying time and drying rate of potato samples. Maximal CFM pretreatment effect was observed at frequency of 80 Hz, treatment duration of 120 s and temperature of thermionic source of 1000 °C, and the corresponding drying rate and drying time were 35·10⁻⁵ (kg/kg s⁻¹) and 130 min. The use of CFM treatment had minor effects on the main quality characteristics (total sugar and starch content) of potato samples. Fourier-transformed infrared spectroscopy confirmed the absence of any modifications of functional group composition of potato samples after CFM pretreatment. Results indicate that cold pulsed filamentary microplasma can enhance the drying rate and decrease drying time without changes in quality characteristics.Practical applicationsCold filamentary microplasma pretreatment assisted by thermionic emission can improve the efficiency of potato drying. Furthermore, it has potential application for reducing energy consumption in drying. CFM pretreatment could be potentially applied for agricultural products drying.     

Learning CPG-based biped locomotion with a policy gradient method

In this paper, we propose a learning framework for CPG-based biped locomotion with a policy gradient method. We demonstrate that appropriate sensory feedback to adjust the rhythm of the CPG (Central Pattern Generator) can be learned using the proposed method within a few hundred trials in simulations. We investigate linear stability of a periodic orbit of the acquired walking pattern considering its approximated return map. Furthermore, we apply the controllers acquired in numerical simulations to our physical 5-link biped robot in order to empirically evaluate the robustness of walking in the real environment. Experimental results demonstrate that the robot was able to successfully walk using the acquired controllers even in the cases of an environmental change by placing a seesaw-like metal sheet on the ground and a parametric change of the robot dynamics with an additional weight on a shank, which was not modeled in the numerical simulations.     

Multi-method learning and assimilation

Considering the wide range of possible behaviours to be acquired for domestic robots, applying a single learning method is clearly insufficient. In this paper, we propose a new strategy for behaviour acquisition for domestic robots where the behaviours are acquired using multiple differing learning methods that are subsequently incorporated into a common behaviour selection system, enabling them to be performed in appropriate situations. An example of the implementation of this strategy applied to the entertainment humanoid robot QRIO is introduced and the results are discussed.     

A technique for extracting behavioral sequence patterns from GPS recorded data

The mobile wireless market has been attracting many customers. Technically, the paradigm of anytime-anywhere connectivity raises previously unthinkable challenges, including the management of million of mobile customers, their profiles, the profiles-based selective information dissemination, and server-side computing infrastructure design issues to support such a large pool of users automatically and intelligently. In this paper, we propose a data mining technique for discovering frequent behavioral patterns from a collection of trajectories gathered by Global Positioning System. Although the search space for spatiotemporal knowledge is extremely challenging, imposing spatial and temporal constraints on spatiotemporal sequences makes the computation feasible. Specifically, the mined patterns are incorporated with synthetic constraints, namely spatiotemporal sequence length restriction, minimum and maximum timing gap between events, time window of occurrence of the whole pattern, inclusion or exclusion event constraints, and frequent movement patterns predictive of one ore more classes. The algorithm for mining all frequent constrained patterns is named cAllMOP. Moreover, to control the density of pattern regions a clustering algorithm is exploited. The proposed method is efficient and scalable. Its efficiency is better than that of the previous algorithms AllMOP and GSP with respect to the compactness of discovered knowledge, execution time, and memory requirement.     

基于红外原理的微型多气体检测系统的设计

为了解决目前煤矿瓦斯事故以及大量使用天然气的家庭安全、环境污染等问题,设计并开发了一种具有集成化、微型化的红外多气体检测系统,通过实验数据的测试对比和数据分析,这种系统达到了微功耗、微体积、宽量程、高分辨率等技术要求,且能集成多气体检测的微型检测系统.重点介绍了红外检测的光学原理,以及从单气体检测引入到集成多气体检测的设计思想和方法,并介绍了有关CAN总线的数据传输方式和无线数据通信方式在系统中的应用.     

Personal driving diary: Automated recognition of driving events from first-person videos

In this paper, we introduce the concept of personal driving diary. A personal driving diary is a multimedia archive of a person’s daily driving experience, describing important driving events of the user with annotated videos. This paper presents an automated system that constructs such multimedia diary by analyzing videos obtained from a vehicle-mounted camera. The proposed system recognizes important interactions between the driving vehicle and the other actors in videos (e.g., accident, overtaking, etc.), and labels them together with its contextual knowledge on the vehicle (e.g., mean velocity) to construct an event log. A decision tree based activity recognizer is designed, detecting driving events of vehicles and pedestrians from the first-person view videos by analyzing their trajectories and spatio-temporal relationships. The constructed diary enables efficient searching and event-based browsing of video clips, which helps the users when retrieving videos of dangerous situations. Our experiment confirms that the proposed system reliably generates driving diaries by annotating the vehicle events learned from training examples.     

Application of parallel mechanism in varistructured quadruped/biped human-carrying walking chair robot

For the existing problems of walking chair robot such as simple function,lower bearing capacity and not walking in complex environment,a novel varistructured quadruped / biped human-carrying walking chair robot is proposed.The proposed robot could be used as biped and quadruped walking chair robots.Considering the conversion of the walking chair robot from the quadruped to the biped or vice versa,6-UPS and 2-UPS+UP(U,P and S are universal joint,the prismatic pair,and sphere joint,respectively) parallel mechanisms are selected as the leg mechanism of the biped walking robot and quadruped walking robot,respectively.Combining the screw theory and theory of mechanism,the degrees of freedom of the leg mechanism and the body mechanism in diferent motion states are computed so as to meet the requirements of mechanism design.The motion characteristics of the 2-UPS+UP parallel mechanism which is the key part of the walking chair robot are analyzed.Then,the workspace of the moving platform is drawn and the efect of the structural parameters on the workspace volume is studied.Finally,it is found that the volume of the workspace of the moving platform is bigger when the side length ratio and the vertex angle ratio of the fxed platform and the moving platform which are isosceles triangles are close to 1.This study provides a theoretical foundation for the prototype development.     

一种针对特定密度检测的快速FBP算法

提出了一种针对特定密度检测的快速FBP算法。首先进行不完全数据投影重建,然后依据对密度的先验知识对初步重建图像进行聚类分割,最后找出感兴趣区域来精确重建。文末对该方法进行了实验,并将实验结果和传统FBP算法、几何参数表法做出主观、客观上的比较评价。结果表明,该算法不但能在很大程度上提高传统FBP算法的速度,而且对于感兴趣区域的重建质量上没有影响。     

基于主动视觉和超声的机器人目标跟踪系统

运动目标跟踪技术是未知环境下移动机器人研究领域的一个重要研究方向。该文提出了一种基于主动视觉和超声信息的移动机器人运动目标跟踪设计方法,利用一台SONY EV-D31彩色摄像机、自主研制的摄像机控制模块、图像采集与处理单元等构建了主动视觉系统。移动机器人采用了基于行为的分布式控制体系结构,利用主动视觉锁定运动目标,通过超声系统感知外部环境信息,能在未知的、动态的、非结构化复杂环境中可靠地跟踪运动目标。实验表明机器人具有较高的鲁棒性,运动目标跟踪系统运行可靠。