Steady-State movement related potentials for brain–computer interfacing

An approach for brain-computer interfacing (BCI) by analysis of steady-state movement related potentials (ssMRPs) produced during rhythmic finger movements is proposed in this paper. The neurological background of ssMRPs is briefly reviewed. Averaged ssMRPs represent the development of a lateralized rhythmic potential, and the energy of the EEG signals at the finger tapping frequency can be used for single-trial ssMRP classification. The proposed ssMRP-based BCI approach is tested using the classic Fisher's linear discriminant classifier. Moreover, the influence of the current source density transform on the performance of BCI system is investigated. The averaged correct classification rates (CCRs) as well as averaged information transfer rates (ITRs) for different sliding time windows are reported. Reliable single-trial classification rates of 88%-100% accuracy are achievable at relatively high ITRs. Furthermore, we have been able to achieve CCRs of up to 93% in classification of the ssMRPs recorded during imagined rhythmic finger movements. The merit of this approach is in the application of rhythmic cues for BCI, the relatively simple recording setup, and straightforward computations that make the real-time implementations plausible

Evaluation of Growth Yield of Spirulina maxima in Photobioreactors

The paper deals with the evaluation of the parameters for the cultivation of Spirulina maxima in two reactors (large-laboratory scale (LL) and semi-technical scale (ST)), whose illuminated areas in respect of the illuminated volume are different, and with the operating costs. We evaluated the growth yield coefficients for Spirulina maxima cultures. In the LL, the following factors were identified: YO2/X – 65.5; YX/CO2 – 0.0806; YX/P2O5 – 0.0082, while in the ST: YO2/X – 583; YX/CO2 – 0.017; YX/P2O5 – 0.0023. Although the reactor in the ST was equipped with many devices that should have improved the efficiency of cultivation, the obtained result was lower compared to the culture conducted in the LL. It was proved that it was possible to perform the cultivation of Spirulina maxima under temperate climate conditions in simply constructed, low cost reactors

A Beam-Space Active Sensing Scheme for Integrated Communication and Sensing Applications

In this paper, we develop an active sensing strategy for a millimeter wave (mmWave) band Integrated Sensing and Communication (ISAC) system adopting a realistic hybrid digital-analog (HDA) architecture. To maintain a desired SNR level, initial beam acquisition (BA) must be established prior to data transmission. In the considered setup, a Base Station (BS) Tx transmits data via a digitally modulated waveform and a co-located radar receiver simultaneously performs radar estimation from the backscattered signal. In this BA scheme, a single common data stream is broadcast over a wide angular sector such that the radar receiver can detect the presence of not yet acquired users and perform coarse parameter estimation (angle of arrival, time of flight, and Doppler). As a result of the HDA architecture, we consider the design of multi-block adaptive RF-domain 'reduction matrices' (from antennas to RF chains) at the radar receiver, to achieve a compromise between the exploration capability in the angular domain and the directivity of the beamforming patterns. Our numerical results demonstrate that the proposed approach is able to reliably detect multiple targets while significantly reducing the initial acquisition time.Comment: 17 page

Vision-based techniques for gait recognition

Global security concerns have raised a proliferation of video surveillance devices. Intelligent surveillance systems seek to discover possible threats automatically and raise alerts. Being able to identify the surveyed object can help determine its threat level. The current generation of devices provide digital video data to be analysed for time varying features to assist in the identification process. Commonly, people queue up to access a facility and approach a video camera in full frontal view. In this environment, a variety of biometrics are available - for example, gait which includes temporal features like stride period. Gait can be measured unobtrusively at a distance. The video data will also include face features, which are short-range biometrics. In this way, one can combine biometrics naturally using one set of data. In this paper we survey current techniques of gait recognition and modelling with the environment in which the research was conducted. We also discuss in detail the issues arising from deriving gait data, such as perspective and occlusion effects, together with the associated computer vision challenges of reliable tracking of human movement. Then, after highlighting these issues and challenges related to gait processing, we proceed to discuss the frameworks combining gait with other biometrics. We then provide motivations for a novel paradigm in biometrics-based human recognition, i.e. the use of the fronto-normal view of gait as a far-range biometrics combined with biometrics operating at a near distance

Multi-cluster computing interconnection network performance modeling and analysis

The overall performance of a distributed system is often depends on the effectiveness of its interconnection network. Thus, the study of the communication networks for distributed systems is very important, which is the focus of this paper. In particular, we address the problem of fat-tree based interconnection networks performance modeling for multi-user heterogeneous multi-cluster computing systems. To this end, we present an analytical model and validate the model through comprehensive simulation. The results of the simulation demonstrated that the proposed model exhibits a good degree of accuracy for various system organizations and under different working conditions

Communication network analysis of the enterprise grid systems

This paper addresses the problem of performance analysis based on communication modelling of largescale heterogeneous distributed systems with emphases on enterprise grid computing systems. The study of communication layers is important because the overall performance of a distributed system is often critically hinged on the effectiveness of this part. This model considers processor as well as network heterogeneity of target system. The model is validated through comprehensive simulation, which demonstrates that the proposed model exhibits a good degree of accuracy for various system sizes and under different working conditions. The proposed model is then used to investigate the performance analysis of typical systems.<br /

Analysis of interconnection networks in heterogeneous multi-cluster systems

The study of interconnection networks is important because the overall performance of a distributed system is often critically hinged on the effectiveness of its interconnection network. In the mean time, the heterogeneity is one of the most important factors of such systems. This paper addresses the problem of interconnection networks performance modeling of large-scale distributed systems with emphases on heterogeneous multi-cluster computing systems. So, we present an analytical model to predict message latency in multi-cluster systems in the presence of cluster size heterogeneity. The model is validated through comprehensive simulation, which demonstrates that the proposed model exhibits a good degree of accuracy for various system organizations and under different working conditions.<br /

A novel semi-blind signal extraction approach incorporating parafac for the removal of eye-blink artifact from EEGs

In this paper, a novel iterative blind signal extraction (BSE) scheme for the removal of the eye-blink artifact from electroencephalogram (EEC) signals is proposed. In this method, in order to remove the artifact, the signal extraction algorithm is provided with a priori information, i.e., an estimation of the column of the mixing matrix corresponding to the eye- blink source. The a priori knowledge, namely the vector corresponding to the spatial distribution of the eye-blink factor, is identified by using the method of parallel factor analysis (PARAFAC). Hence, we call the BSE approach, semi- blind signal extraction (SBSE). The results demonstrate that the proposed algorithm effectively identifies and removes the eye-blink artifact from raw EEC measurements

Transport critical current density in Fe-sheathed nano-SiC doped MgB2 wires

The nano-SiC doped MgB2/Fe wires were fabricated using a powder-in-tube method and an in-situ reaction process. The depression of Tc with increasing SiC doping level remained rather small due to the counterbalanced effect of Si and C co-doping. The high level SiC co-doping allowed creation of the intra-grain defects and nano-inclusions, which act as effective pinning centers, resulting in a substantial enhancement in the Jc(H) performance. The transport Jc for all the wires is comparable to the magnetic Jc at higher fields despite the low density of the samples and percolative nature of current. The transport Ic for the 10wt% SiC doped MgB2/Fe reached 660A at 5K and 4.5T (Jc = 133,000A/cm2) and 540A at 20K and 2T (Jc = 108,000A/cm2). The transport Jc for the 10wt% SiC doped MgB2 wire is more than an order of magnitude higher than for the state-the-art Fe-sheathed MgB2 wire reported to date at 5K and 10T and 20K and 5T respectively. There is a plenty of room for further improvement in Jc as the density of the current samples is only 50%.Comment: 4 pages, 7 figures, presented at ASC 2002, Housto