Continuous Data Processing Research Articles

The Role Played and Opportunities Provided by IGP DMC of China National Seismic Network in Wenchuan Earthquake Disaster Relief and Researches

Abstract The seismological observation system in China achieved rapid development during the last five years. The Data Management Center (DMC) of the China Earthquake Network Center (CENC) of the China Earthquake Administration (CEA) now receives and archives waveform data from more than 1000 permanent seismic stations around China in real time. For operational, backup, and data security considerations, the DMC at the Institute of Geophysics (IGP), the CEA was established at the end of 2007. The IGPDMC is capable of receiving and processing continuous waveform data in real time from more than 1000 permanent seismic stations around China. Currently, the data processing and management mainly include data quality control, data format conversion, event data extraction at user’s request, and data download service via Internet. By now, the IGPDMC has supplied about 150 terabytes waveform data to over 120 researches of more than 30 academic institutions. More than 20 papers have been published in professional journals. After the great Wenchuan earthquake, the real-time waveform data from 56 portable stations deployed in the aftershock area were added to IGPDMC. All these data make the IGPDMC a critical platform for supporting relevant seismological research. This paper gives a detailed description of the permanent seismic stations of the CEA’s seismological observation system, the technical system construction of the IGPDMC, establishment of the near-real-time automatic event-extraction system for large earthquakes, as well as the prompt data support to Wenchuan earthquake-related researches.

Modeling Operating Speed and Deceleration on Two-Lane Rural Roads with Global Positioning System Data

In the road design process, speed variation along the road segment is an important issue to consider in adapting road geometry to drivers' expectations. To achieve this objective, speed criteria are used to evaluate road consistency. Being able to estimate the operating speed in the design phase can lead to safer road alignment. With this objective, several researchers have developed operating speed models. Most of these models are based on collected spot speed data. They assume constant speed on curves and, therefore, deceleration that occurs entirely on the approach tangent. According to these assumptions, spot speed data are collected at the center of the horizontal curve and at the midpoint of the preceding tangent to obtain operating speed models. This paper presents a new methodology based on the use of Global Positioning System devices that allow continuous collecting and processing of speed data. With this new methodology, not only can new and more accurate operating speed models be developed, but cited hypotheses can also be checked. Observed speed continuous profiles allow studies that previously could not be done, especially as related to deceleration and speed variations. This study calibrated new speed models, including three for horizontal curves with a radius curve and the curvature change rate of a single curve as explanatory variables, and one for tangents that incorporates the curve speed model. Tangent-curve speed variations are evaluated, with comparison of Δ85V and ΔV85, analysis of the deceleration length occurring on a curve, and development of two deceleration models.

南関東地域における微動の長期連続観測記録の地震波干渉法処理による表面波の群速度の推定

南関東地域において微動の長期連続観測を実施し, 地震波干渉法に基づくデータ処理によって２観測点間のグリーン関数の表面波成分の抽出を試み, 既往の深部地盤モデルの検証のための基礎的検討を行った。同地域の16地点における１年間以上の微動連続観測データを用いた地震波干渉法に基づく処理を行い, 周期２～６秒の帯域での相互相関関数を求めた。地震記録と比較することによって, 絶対振幅を議論しなければ, 得られた相互相関関数は地震記録の表面波と波形の山谷がよく一致しており, 地震波干渉法によって微動データからグリーン関数の表面波成分を抽出できることを実証的に確認した。得られた相互相関関数のマルチプルフィルター解析によって, 表面波の群速度の推定を得た。既存の深部地盤のS波速度構造モデルに対する理論値と観測値の比較を行った結果, 関東平野内部や相模湾の多くの地点では, 群速度の理論値と観測値がよく一致していた。しかし, 既存のモデルで地震基盤が露頭していると仮定されている伊豆半島や関東山地では, 観測された群速度は理論値よりも小さく, この地域のモデル修正の必要があることがわかった。これらの結果から深部地盤モデルの検証に地震波干渉法が有効に活用できることがわかった。

A multi-agent system for meteorological radar data management and decision support

The continuous processing and evaluation of meteorological radar data require significant efforts by scientists, both for data processing, storage, and maintenance, and for data interpretation and visualization. To assist meteorologists and to automate a large part of these tasks, we have designed and developed Abacus, a multi-agent system for managing radar data and providing decision support. Abacus' agents undertake data management and visualization tasks, while they are also responsible for extracting statistical indicators and assessing current weather conditions. Abacus agent system identifies potentially hazardous incidents, disseminates preprocessed information over the web, and enables warning services provided via email notifications. In this paper, Abacus' agent architecture is detailed and agent communication for information diffusion is presented. Focus is also given on the customizable logical rule-bases for agent reasoning required in decision support. The platform has been tested with real-world data from the Meteorological Service of Cyprus.

Epileptic Spike Recognition in Electroencephalogram Using Deterministic Finite Automata

This Paper presents an automated method of Epileptic Spike detection in Electroencephalogram (EEG) using Deterministic Finite Automata (DFA). It takes prerecorded single channel EEG data file as input and finds the occurrences of Epileptic Spikes data in it. The EEG signal was recorded at 256 Hz in two minutes separate data files using the Visual Lab-M software (ADLink Technology Inc., Taiwan). It was preprocessed for removal of baseline shift and band pass filtered using an infinite impulse response (IIR) Butterworth filter. A system, whose functionality was modeled with DFA, was designed. The system was tested with 10 EEG signal data files. The recognition rate of Epileptic Spike as on average was 95.68%. This system does not require any human intrusion. Also it does not need any short of training. The result shows that the application of DFA can be useful in detection of different characteristics present in EEG signals. This approach could be extended to a continuous data processing system.

Surface velocity field of the Ibero-Maghrebian segment of the Eurasia-Nubia plate boundary

SUMMARY We process continuous GPS data distributed over the Iberian Peninsula, complemented by a few stations in France and North Africa, to constrain the displacement field in the surrounding area. A surface velocity field is derived from the time-series of daily solutions for each station, whose observations span 3.5 yr or longer. We find that most of Iberia forms a stable block fixed relative to Eurasia in which residuals have a weighted rms value of 0.85 mm yr−1 and are all below the computed accuracy for each station. Stations in northern Morocco exhibit a motion close to what would be expected for stable Nubia, in which residuals have a weighted rms value of 0.70 mm yr−1 and are also all below computed accuracies. The most distinctive behaviour is found at stations along the southern coast of Spain and the northern coast of Morocco, where larger and more westward velocities are found. Three stations in southern Iberia show differences with respect to stable Eurasia that can reach 4.4 mm yr−1 and are distinctly larger than computed accuracies. We hypothesize that this peculiar behaviour is not only a consequence of the Nubian–Eurasian plate convergence, but also a result of a local lithospheric process, particularly the effect of the Gibraltar slab, as previously suggested by seismic tomography and geological modelling.

A computer system for continuous long-term recording, processing, and analysis of physiological data of brain injured patients in ICU settings

The objective of this project was to assemble and test a computer-based system for continuous long-term physiological data acquisition. The system would be used to study short-term (heart rate variability) and long-term (circadian rhythms) dynamics of physiological parameters in severely brain injured patients in ICU settings. A system has been built using open-source software and the Linux operating system as the platform. The system consists of three main parts: data acquisition, processing and analysis. The system was tested in ICU and experimental settings for long periods of time (up to 10 days of non-stop recording). The system appeared to function properly and accurately. Samples of the data according to the stages of acquisition-analysis process are presented in the paper. Avenues for the system use and development are discussed.

A Scalable Mutiprocessor for Real-Time Signal Processing Applications

We present a scalable multiprocessor for real-time signal processing applications. The basic building block is a node with eight processors. Nodes are connected by the switch-based network Switcherland [2]. Innovation highlights are: (a) a network with guaranteed transmission rates and bounded forwarding latencies, (b) a multiprocessor node based on RISC CPUs/DSPs and a communication infrastructure optimized for processing continuous data streams, and (c) an object-oriented programming model familiar from general-purpose systems. These properties make the described system a versatile platform for a wide range of signal processing applications.

Averaging and recording of digital deep-level transient spectroscopy transient signals

A new approach to the signal processing in digital deep-level transient spectroscopy (DLTS) systems is introduced. The problems of signal recovery from noise and efficient data storage are addressed separately from the transient signal analysis. As a result of this approach, an improved digital averaging scheme for DLTS signal recovery from noise and transient data storage is proposed. We have shown that the combined action of two complementary digital averaging techniques can improve the DLTS digital signal processing. Pseudologarithmic time averaging is efficient in reducing the number of processed data points and improving the signal-to-noise ratio for the high frequency noise components and in the transient tail. We demonstrate that the normalized errors in the magnitude measurements introduced by this type of averaging remain below 1% for pure logarithmic and below 0.1% provided that the logarithmic averaging intervals are further divided into five or more equal parts. Continuous time averaging is well suited for improving overall signal-to-noise ratio, for continuous display and processing of data, and it is more efficient in using the computer resources. The described combination of hardware and software tools for the implementation of these techniques supplies continuously fresh data and does not require any synchronization with the main computer program. Compared to other digital DLTS systems, this new approach offers an improved short delay time resolution, improved signal-to-noise ratio, and more efficient data storage. At the same time it offers real-time observation of essentially noise-free transients and, like analog systems, a real-time display of the DLTS scan. The real-time display means that the displayed transient and DLTS scan can be updated on the computer screen after each pulse even for a very large number of averaged pulses, and the result can be predicted well before the acquisition process reaches this number. The proposed techniques allow one to combine the powerful transient analysis of the digital DLTS methods with the sensitivity and the convenience of the analog methods. The described averaging and data reduction techniques are intended primarily for DLTS data processing, but the same principles can be useful for many other physical experiments involving transient data analysis.

Switcherland

Computer systems have become powerful enough to process continuous data streams such as video or animated graphics. While processing power and communication bandwidth of today's systems typically are sufficient, quality of service (QoS) guarantees as required for handling such data types cannot be provided by these systems in adequate ways.We present Switcherland, a scalable communication architecture based on crossbar switches that provides QoS guarantees for workstation clusters in the form of reserved bandwidth and bounded transmission delays. Similar to the ATM technology Switcherland provides QoS guarantees with the help of service classes, that is, data transfers are characterized as variable bit rate traffic or constant bit rate traffic. However, unlike LAN technologies, Switcherland is optimized for cluster computing in that (i) it serves as a backplane interconnection fabric as well as a LAN, (ii) it extends support for service classes by also covering the end nodes of the network, (iii) it provides low latency in the order of one microsecond per switch, and (iv) it uses a communication model based on a global memory to simplify programming.

Comparison between LDG-network and GERESS-array with respect to regional detection and location results

The design of a global seismic system to monitor compliance with a ban on underground nuclear testing considerably deviates from previous concepts of international seismic data exchange. The new concept relies on centralized processing of continuous data from a fixed station network (“alpha” stations) which provides the primary detection and location capability. This alpha station network is augmented by additional stations (“beta” stations) which send data on request to refine the hypocentres of events which were detected by the alpha network. To test this concept we have used the GERESS array in Germany as a prototype alpha station and investigated its regional detection and location capability for events in France and surrounding areas. For this region, data from the national French network operated by LDG provide an excellent reference data base. Within a 5 degree distance, GERESS showed an excellent performance in terms of detection and location down to magnitude M(LDG) = 3. Between a 5 degree and 10 degree distance, the detection capability is still high but very often it is not sufficient to locate events below M(LDG) = 4. Generalizing these results, we can conclude that either the maximum distance between alpha stations should be 10 degrees or the contribution of beta stations has to play a significant role in a future monitoring system.

新しい地下電気探査における逆解析過程とその評価

New electrical prospecting techniques utilizing effective surface and subsurface solid electrode arrays, large continuous data processing, high density computer simulation and visualization have become important useful exploration tools increasingly for detecting deeply located mineral or low mineralized deposit, energy and groundwater reservoirs, geological fracture zones and rock interior structures, and also for monitoring groundwater in rock mass and contermination, nuclear waste repository and various changes of underground structures.An important objective of electrical methods including resistivity tomography techniques, is to maximize, extract and enhance the response due to target inhomogeneities using surface electrodes on the various ground conditions and buried electrodes in boreholes, tunnels and other underground conditions. Recently, new computerized resistivity section construction techniques has been mainly developed with emphasis on improvement of the reliability to extract the subsurface informations for the domains of groundwater and environmental explorations. For an example, a future work in improving the reliability is to design effective surface and solid electrode array combinations under the restricted field conditions by new prediction and feedback techniques.This paper begins with a review of the recent activities about development of elements as an aid to new surface and subsurface electrode array techniques. Next, the basic concepts of resistivity array methods including high accuracy forward modeling, high resolution inversion, sensitivity distribution and image reconstruction from computerized tomography procedure, are reviewed. And also, some results on the improvement of reliability of electrical methods have been discussed by using the examples of subsurface signal extraction and enhancement, investigated by the authors.

The adaptive control of manipulator arms

This paper considers the control of the motion of an N-link manipulator arm using a hyperstable adaptive scheme. In order to clarify the exposition, the arm is specifically chosen to be an open polygon, with rotating joints, operating in one plane. However, this is not a significant restriction upon the control scheme that is developed, since the latter may be applied to spherical motions and grasping actions too. It is shown that an N-link arm satisfies all the conditions for perfect adaptive model following, even though the required reference model need only be of second order. The scheme is realised by simple analogue components, although this does not imply a restriction to continuous data processing, for parallel theories exist for digital systems. The latter have been omitted here so that the adaptive control concepts may be better emphasizedThe results of a simulation of the scheme as applied to a very simple arm are presented and recommendations are made for future research in this field.