Real-time removal of ocular artifacts from EEG based on independent component analysis and manifold learning

Frequent occurrence of ocular artifacts leads to serious problems in interpreting and analyzing the electroencephalogram (EEG). In the present paper, a novel and robust technique is proposed to eliminate ocular artifacts from EEG signals in real time. Independent Component Analysis (ICA) is used to decompose EEG signals. The features of topography and power spectral density of those components are extracted. Moreover, we introduce manifold learning algorithm, a recently popular dimensionality reduction technique, to reduce the dimensionality of initial features, and then those new features are fed to a classifier to identify ocular artifacts components. A k-nearest neighbor classifier is adopted to classify components because classification results show that manifold learning with the nearest neighbor algorithm works best. Finally, the artifact removal method proposed here is evaluated by the comparisons of EEG data before and after artifact removal. The results indicate that the method proposed could remove ocular artifacts effectively from EEG signals with little distortion of the underlying brain signals and be satisfied the real-time application.     

Design and implementation of look-ahead linear jerk filter for a computerized numerical controlled machine

In this study, an open programmable logic controller (PLC) from Fuji electric prescribed in the Structured Text program was applied to develop a look-ahead linear jerk filter (LALJF) for a computerized numerically controlled (CNC) machine. To ensure the smooth and accurate motion of a tool with a linear change in jerk during real-time machining, the proposed filter was formed by combining a look-ahead algorithm with three modified moving average filters (3MMAF). The look-ahead algorithm performed a single look-ahead step-change in the speed of the speed curve. Based on a step-changing speed profile, given maximal acceleration/deceleration and maximum jerk, the speed curve was modified before it was passed through a linear jerk filter to reduce machining time. The speed commands filtered by the proposed filter stabilize machine table at the beginning and end of its motion, and at any point at which its speed exhibits a step-change. The theoretical and computational aspects of the LALJF are presented together with experimental results of its implementation on an X–Y table. The multiple-step-changing speed curve of a CNC machine and the speed curve of a high-speed measurement system were constructed in order to verify the feasibility and precision of the proposed method.     

VLSM技术在IP地址管理中的应用

现阶段IPV4网络,由于Internet用户的飞速增长,接入点大量增加而造成了IP地址相对匮乏,同时由于分级地址管理,IP地址存在严重的浪费。本文针对这个问题在大型网络设计中使用VLSM和路由汇总等高级IP编址技术,可以有效减少IP地址的浪费,减小路由选择表,提高网络性能。     

UTM技术浅析

随着网络应用越来越广泛,安全问题日益突出,单一的安全产品已经难以应对复杂多变的网络攻击,在这种背景下UTM应运而生。     

Cross‐talk acceptability in natural still images for different (auto)stereoscopic display technologies

Abstract— One of the most annoying distortions in (auto)stereoscopic displays is probably cross‐talk, visible as double edges, which is mainly caused by an imperfect separation of left‐ and right‐eye images. For different types of three‐dimensional (3‐D) displays, cross‐talk is caused by different origins, which could result in different levels of perceived image distortion. To evaluate the influence of (auto)stereoscopic display technology on cross‐talk perception, optical measurements and subjective assessments were performed with three different types of 3‐D displays. It is shown with natural still images that the 3‐D display technology with the lowest luminance and contrast level tolerates the highest level of cross‐talk, while still maintaining an acceptable image‐quality level.     

Unified multi-domain modelling and simulation of space robot for capturing a moving target

Space robotic systems are expected to play an increasingly important role in the future on-orbit service. The applications include repairing, refueling or de-orbiting of a satellite, or removal of the space debris. The dynamical performances of space robotic system result from the multi-physics interactions between mechanical, electrical, electronic, control, etc. In this paper, we developed a unified multi-domain modelling and simulation system. The system is composed of the following modules: the path planner, joint controllers, motor and its driver, gearing mechanism of the space manipulators, the Guidance, Navigation, and Control (GNC) system, the actuators of the base, and the orbital environment, orbital dynamic and the multi-body dynamic of the whole system, etc. Based on this system, the operation during different stages, including far range rendezvous, close range rendezvous (is usually divided into two sub-phases: closing and final approach) and target capturing can be studied from the view of multi-physics domains. The key algorithms, such as pose (position and attitude) measurement, GNC of the base, path planning and control of the space manipulator, and so on, can be validated using the system. As examples, the capturing processes of a moving target under free-floating and attitude-controlled modes are simulated and the simulation results are given.     

A tree-based particle swarm optimization for multicast routing

QoS multicast routing is a non-linear combinatorial optimization problem. It tries to find a multicast routing tree with minimal cost that can satisfy constraints such as bandwidth, delay, and delay jitter. This problem is NP-complete. The solution to such problems is often to search first for paths from the source node to each destination node and then integrate these paths into a multicast tree. Such a method, however, is slow and complex. To overcome these shortcomings, we propose a new method for tree-based optimization. Our algorithm optimizes the multicast tree directly, unlike the conventional solutions to finding paths and integrating them to generate a multicast tree. Our algorithm also applies particle swarm optimization to the solution to control the optimization orientation of the tree shape. Simulation results show that our algorithm performs well in searching, converging speed and adaptability scale.     

Video analysis based on volumetric event detection

During the past decade, feature extraction and knowledge acquisition based on video analysis have been extensively researched and tested on many applications such as closed-circuit television(CCTV)data analysis, large-scale public event control, and other daily security monitoring and surveillance operations with various degrees of success. However, since the actual video process is a multi-phased one and encompasses extensive theories and techniques ranging from fundamental image processing, computational geometry and graphics, and machine vision, to advanced artificial intelligence, pattern analysis, and even cognitive science, there are still many important problems to resolve before it can be widely applied. Among them, video event identification and detection are two prominent ones. Comparing with the most popular frame-to-frame processing mode of most of today's approaches and systems, this project reorganizes video data as a 3D volume structure that provides the hybrid spatial and temporal information in a unified space. This paper reports an innovative technique to transform original video frames to 3D volume structures denoted by spatial and temporal features. It then highlights the volume array structure in a so-called "pre-suspicion" mechanism for a later process. The focus of this report is the development of an effective and efficient voxel-based segmentation technique suitable to the volumetric nature of video events and ready for deployment in 3D clustering operations. The paper is concluded with a performance evaluation of the devised technique and discussion on the future work for accelerating the pre-processing of the original video data.