Abstract: In conventional data acquisition, the delay time between the firing of one source and the next is such that the energy from the previous source has decayed to an acceptable level before data associated with the following source arrives. This minimum delay time imposes constraints on the data acquisition rate. For marine data, the minimum delay time also implies a minimum inline shot interval, because the vessel’s minimum speed is limited.

Abstract: The use of consumer digital cameras or webcams to characterize and monitor different features has become prevalent in various domains, especially in environmental applications. Despite some promising results, such digital camera systems generally suffer from signal aberrations due to the on-board image processing systems and thus offer limited quantitative data acquisition capability. The objective of this study was to test a series of radiometric corrections having the potential to reduce radiometric distortions linked to camera optics and environmental conditions, and to quantify the effects of these corrections on our ability to monitor crop variables. In 2007, we conducted a five-month experiment on sugarcane trial plots using original RGB and modified RGB (Red-Edge and NIR) cameras fitted onto a light aircraft. The camera settings were kept unchanged throughout the acquisition period and the images were recorded in JPEG and RAW formats. These images were corrected to eliminate the vignetting effect, and normalized between acquisition dates. Our results suggest that 1) the use of unprocessed image data did not improve the results of image analyses; 2) vignetting had a significant effect, especially for the modified camera, and 3) normalized vegetation indices calculated with vignetting-corrected images were sufficient to correct for scene illumination conditions. These results are discussed in the light of the experimental protocol and recommendations are made for the use of these versatile systems for quantitative remote sensing of terrestrial surfaces.

Abstract: Wireless Sensor Network (WSN) is increasingly popular in the field of micro-environmental monitoring due to its promising capability. However, most systems using WSN for environmental monitoring reported in the literature are developed for specific applications without functions for exploiting user's data processing methods. In this paper, a new system is designed in detail to perform micro-environmental monitoring taking the advantages of the WSN. The application-oriented hardware working style is designed, and the system platform for data acquisition, validation, processing and visualization is systematically presented. Several strategies are proposed to guarantee the system capability in terms of extracting useful information, visualizing events to their authentic time are also described. Moreover, a web-based surveillance subsystem is presented for remote control and monitoring. In addition, the system is extensible for engineers to carry their own data analysis algorithms. Experimental results are to show the path reliability and real-time characteristics, and to display the feasibility and applicability of the developed system into practical deployment.

Abstract: Reverse engineering (RE) is generally defined as a process of analysing an object or existing system (hardware and software) to identify its components and their interrelationships, and investigate how it works in order to redesign or produce a copy without access to the design from which it was originally produced [87,88]. In areas related to 3D graphics and modelling, RE technology is used for reconstructing 3D models of an object in different geometrical formats. RE hardware is used for RE data acquisition, which in the case of 3D modelling is the collection of geometrical data that represent a physical object. There are three main technologies for RE data acquisition: Contact, Non-Contact and Destructive. Outputs of the RE data acquisition process are 2D cross-sectional images and point clouds that define the geometry of an object. RE software is employed to transform the RE data produced by RE hardware into 3D geometrical models. The final outputs of the RE data processing chain can be one of two types of 3D data: (i) Polygons or (ii) NURBS (Non-Uniform Rational B Splines). Polygon models, which are normally in the STL, VRML or DXF format, are commonly used for rapid prototyping, laser milling, 3D graphics, simulation, and animations application. NURBS surfaces or solids are frequently used in Computer Aided Design, Manufacturing and Engineering (CAD-CAM-CAE) applications. In this chapter, hardware and software for RE are presented. Commercially available RE hardware based on different 3D data collection techniques is briefly introduced. The advantages and disadvantages of various data acquisition methods are outlined to help the selection of the right RE hardware for specific applications. In the RE software section, end-use RE applications are classified and typical commercialised RE packages are reviewed. The four RE phases used in a RE data processing chain are highlighted, in which the fundamental RE operations that are necessary for completing the RE data processing chain are presented and discussed in detail.

Abstract: A system for intelligent monitoring and management of an electrical system is disclosed. The system includes a data acquisition component, a power analytics server and a client terminal. The data acquisition component acquires real-time data output from the electrical system. The power analytics server is comprised of a real-time energy pricing engine, virtual system modeling engine, an analytics engine, a machine learning engine and a schematic user interface creator engine. The real-time energy pricing engine generates real-time utility power pricing data. The virtual system modeling engine generates predicted data output for the electrical system. The analytics engine monitors real-time data output and predicted data output of the electrical system. The machine learning engine stores and processes patterns observed from the real-time data output and the predicted data output to forecast an aspect of the electrical system.

Abstract: A system and method for intelligent monitoring and management of an electrical system is disclosed. The system includes a data acquisition component, a power analytics server and a client terminal. The data acquisition component acquires real-time data output from the electrical system. The power analytics server is comprised of a real-time electrical system security index engine that calculates real-time system security index values from stability indices data generated from a virtual system model of the electrical system. The client terminal displays the system security index values to assess the security and stability of the electrical system.

Abstract: Embedded logic analysis has emerged as a powerful technique for identifying functional bugs during post-silicon validation, as it enables at-speed acquisition of data from the circuit nodes in real-time. Nonetheless, the amount of data that is observed is limited by the capacity of the on-chip trace buffers. This paper introduces an automated method for improving the utilization of the on-chip storage, by identifying a small set of trace signals from which a large number of states can be restored using a compute-efficient algorithm. This enlarged set of data can then be used to aid the search of functional bugs in the fabricated circuit.

Abstract: Machine condition plays an important role in machining performance. A machine condition monitoring system will provide significant economic benefits when applied to machine tools and machining processes. Development of such a system requires reliable machining data that can reflect machining processes. This study demonstrates a tool condition monitoring approach in an end-milling operation based on the vibration signal collected through a low-cost, microcontroller-based data acquisition system. A data acquisition system has been built through interfacing a microcontroller with a signal transducer for collecting cutting vibration. The examination tests of this developed system have been carried out on a CNC milling machine. Experimental studies and data analysis have been performed to validate the proposed system. The onsite tests show the developed system can perform properly as proposed.

Abstract: A system for utilizing a neural network to make real-time predictions about the health, reliability, and performance of a monitored system are disclosed. The system includes a data acquisition component, a power analytics server and a client terminal. The data acquisition component acquires real-time data output from the electrical system. The power analytics server is comprised of a virtual system modeling engine, an analytics engine, an adaptive prediction engine. The virtual system modeling engine generates predicted data output for the electrical system. The analytics engine monitors real-time data output and predicted data output of the electrical system. The adaptive prediction engine can be configured to forecast an aspect of the monitored system using a neural network algorithm. The adaptive prediction engine is further configured to process the real-time data output and automatically optimize the neural network algorithm by minimizing a measure of error between the real-time data output and an estimated data output predicted by the neural network algorithm.

Abstract: An optical imaging system includes an optical radiation source ( 410, 510 ), a frequency clock module outputting frequency clock signals ( 420 ), an optical interferometer ( 430 ), a data acquisition (DAQ) device ( 440 ) triggered by the frequency clock signals, and a computer ( 450 ) to perform multi-dimensional optical imaging of the samples. The frequency clock signals are processed by software or hardware to produce a record containing frequency-time relationship of the optical radiation source ( 410, 510 ) to externally clock the sampling process of the DAQ device ( 440 ). The system may employ over-sampling and various digital signal processing methods to improve image quality. The system further includes multiple stages of routers ( 1418, 1425 ) connecting the light source ( 1410 ) with a plurality of interferometers ( 1420 a- 1420 n) and a DAQ system ( 1450 ) externally clocked by frequency clock signals to perform high-speed multi-channel optical imaging of samples.

Abstract: Methods and devices for providing diabetes management including automatic time acquisition protocol is provided.

Abstract: Wireless sensor networks have rapidly matured in recent years to offer data acquisition capabilities on par with those of traditional tethered data acquisition systems. Entire structural monitoring systems assembled from wireless sensors have proven to be low cost, easy to install, and accurate. However, the functionality of wireless sensors can be further extended to include actuation capabilities. Wireless sensors capable of actuating a structure could serve as building blocks of future generations of structural control systems. In this study, a wireless sensor prototype capable of data acquisition, computational analysis and actuation is proposed for use in a real-time structural control system. The performance of a wireless control system is illustrated using a full-scale structure controlled by a semi-active magnetorheological (MR) damper and a network of wireless sensors. One wireless sensor designated as a controller automates the task of collecting state data, calculating control forces, and issuing commands to the MR damper, all in real time. Additional wireless sensors are installed to measure the acceleration and velocity response of each system degree of freedom. Base motion is applied to the structure to simulate seismic excitations while the wireless control system mitigates inter-storey drift response of the structure. An optimal linear quadratic regulation solution is formulated for embedment within the computational cores of the wireless sensors. Copyright © 2007 John Wiley & Sons, Ltd.

Abstract: A photoacoustic imaging apparatus is provided for medical or other imaging applications and also a method for calibrating this apparatus. The apparatus employs a sparse array of transducer elements and a reconstruction algorithm. Spatial calibration maps of the sparse array are used to optimize the reconstruction algorithm. The apparatus includes a laser producing a pulsed laser beam to illuminate a subject for imaging and generate photoacoustic waves. The transducers are fixedly mounted on a holder so as to form the sparse array. A photoacoustic (PA) waves are received by each transducer. The resultant analog signals from each transducer are amplified, filtered, and converted to digital signals in parallel by a data acquisition system which is operatively connected to a computer. The computer receives the digital signals and processes the digital signals by the algorithm based on iterative forward projection and back-projection in order to provide the image.

Abstract: A method of generating post-mission position and orientation data comprises generating position and orientation data representing positions and orientations of a mobile platform, based on global navigation satellite system (GNSS) data and inertial navigation system (INS) data acquired during a data acquisition period by the mobile platform, using a network real-time kinematic (RTK) subsystem to generate correction data associated with the data acquisition period, and correcting the position and orientation data based on the correction data. The RTK subsystem may implement a virtual reference station (VRS) technique to generate the correction data.

Abstract: A main difference between Magnetic Resonance (MR) imaging and other medical imaging modalities is the control over the data acquisition and how it can be managed to finally show the adequate reconstructed image. With some basic programming adjustments, the user can modify the spatial resolution, field of view (FOV), image contrast, acquisition velocity, artifacts and so many other parameters that will contribute to form the final image. The main character and agent of all this control is called k-space, which represents the matrix where the MR data will be stored previously to a Fourier transformation to obtain the desired image.This work introduces 'k-Space tutorial', a MATLAB-based educational environment to learn how the image and the k-space are related, and how the image can be affected through k-space modifications. This MR imaging educational environment has learning facilities on the basic acceleration strategies that can be encountered in almost all MR scanners: scan percentage, rectangular FOV and partial Fourier imaging. It also permits one to apply low- and high-pass filtering to the k-space, and to observe how the contrast or the details are selected in the reconstructed image. It also allows one to modify the signal-to-noise ratio of the acquisition and create some artifacts on the image as a simulated movement of the patient - with variable intensity level - and some electromagnetic spikes on k-space occurring during data acquisition.

Abstract: With widespread availability of digital images and easy-to-use image editing softwares, the origin and integrity of digital images has become a serious concern. This paper introduces the problem of image acquisition forensics and proposes a fusion of a set of signal processing features to identify the source of digital images. Our results show that the devices' color interpolation coefficients and noise statistics can jointly serve as good forensic features to help accurately trace the origin of the input image to its production process and to differentiate between images produced by cameras, cell phone cameras, scanners, and computer graphics. Further, the proposed features can also be extended to determining the brand and model of the device. Thus, the techniques introduced in this work provide a unified framework for image acquisition forensics.

Abstract: A system for automatically generating a schematic user interface of an electrical system is disclosed. The system includes a data acquisition component, a power analytics server and a client terminal. The data acquisition component acquires real-time data output from the electrical system. The power analytics server is comprised of a virtual system modeling engine, an analytics engine, a machine learning engine and a schematic user interface creator engine. The virtual system modeling engine generates predicted data output for the electrical system. The analytics engine monitors real-time data output and predicted data output of the electrical system. The machine learning engine stores and processes patterns observed from the real-time data output and the predicted data output to forecast an aspect of the electrical system. The schematic user interface creator engine is configured to create a schematic user interface that is representative of the virtual system model and link the schematic user interface to the data acquisition component.

Abstract: Hands-On Introduction to LabVIEW for Scientists and Engineers takes a "learn-by-doing" approach to acquiring the computer-based skills used in daily experimental work Ideal as a course textbook or a self-study supplement, the text explores practical programming solutions for carrying out interesting and relevant projects Readers--who are assumed to have no prior computer programming or LabVIEW background--will begin writing meaningful programs in the first few pages Instructors adopting the book as a classroom text can easily choose the desired depth of coverage for their courses The first four chapters focus on the fundamentals of LabVIEW programming and the basics of computer-based experimentation using a National Instruments data acquisition (DAQ) device; these chapters provide the instructional materials necessary for a three-week introduction to LabVIEW-based data acquisition A full-featured course that uses most of the text's chapters will bring students to an intermediate skill level in computer-based data acquisition and analysis Features *Flexible modular structure The text's unique organization makes it suitable as either a short introduction to LabVIEW or a guide to more in-depth programming *Easy-to-implement Express VIs enable introduction of data acquisition in early chapters *"Do It Yourself" projects at the end of each chapter Each project poses an interesting "real-world" problem and loosely directs readers in applying the chapter's material to find a solution *Homework problems at the end of each chapter A wide selection of homework-style problems allows interested students to test their understanding and further develop their computer-based experimentation skills

Abstract: With the rapid development of the embedded computer technology, the new generation of industrial automation data acquisition and monitoring system, which takes the high performance of embedded microprocessor as its core, adapts well to the application system. It meets the strict requests of the function, reliability, cost, size and power consumption, etc. In the industrial automation application system, the Modbus communication protocol is widespread industrial standard and is used in massive industrial equipments, including DCS, PLC, RTU and the intelligent instrument, etc. In order to reach the demand of the embedded data acquisition monitoring system of the industrial automation application, an embedded data acquisition monitoring platform based on Modbus protocol under the Linux environment is designed in this paper. The serial port Modbus master protocol is realized, which includes two kinds of communication mode: ASCII and RTU. As a result, communicating with various serial Modbus salve protocol equipments can be satisfied. The Modbus master realized by this embedded platform is stable and reliable. It has excellent prospect in the embedded data acquisition monitoring system of new automation applications.

Abstract: Using three different short-period electromagnetic sensors with resonance frequencies of 1 Hz (Mark L4C-3D), 2 Hz (Mark L-22D), and 4.5 Hz (I/O SM-6), coupled with three digital acquisition system, the portable data acquisition system (PDAS) Teledyne Geotech, the refraction technology (REFTEK) 72A, and the Earth Data Logger PR6-24 (EDL), the effect of the seismic instruments on the horizontal-to-vertical spectral ratio (H/V) using seismic noise for frequencies less than 1 Hz has been evaluated. For all possible sensors–acquisition system pairs, the background seismic signal and instrumental self-noise power spectral densities have been calculated and compared. The results obtained when coupling the short-period sensors with different acquisition systems show that the performance of the considered instruments at frequencies <1 Hz strongly depends upon the sensor–acquisition system combination and the gain used, with the best performance obtained for sensors with the lowest resonance frequency. For all acquisition systems, it was possible to retrieve correctly the H/V peak down to 0.1–0.2 Hz by using a high gain and a 1-Hz sensor. In contrast, biased H/V spectral ratios were retrieved when low-gain values were considered. Particular care is required when using 4.5-Hz sensors, because they may not even allow the fundamental resonance frequency peak to be reproduced.

Abstract: To address modern molecular imaging requirements, a digital positron emission tomography (PET) scanner for small animals has been developed at Universite de Sherbrooke. Based on individual readout of avalanche photodiodes (APD) coupled to LYSO/LGSO phoswich detectors, the scanner supports up to 4608 channels in a 16.2 cm diameter, 11.25 cm axial field of view with an isotropic ~ 1.2 mm FWHM intrinsic spatial resolution at the center of the field of view. Custom data acquisition boards preprocess and sample APD signals at 45 MHz and compute in real time crystal identification, energy and timing information of detected events at an average sustained rate of up to 1250 raw counts per second per mm2 (10 000 cps/channel). Real time digital signal analysis also filters out events outside the pre-selected energy window with crystal granularity to eliminate Compton events and electronic noise. Retained events are then merged into a single stream through a real-time sorting tree, at which end prompt and delayed coincidences are extracted. A single Firewire link handles both control and data transfers with a host computer. The LabPET features four data recording modes, giving the user the choice to retain data for research or to minimize file size for high coincidence count rate and imaging purposes. The electronic system also supports time synchronized data insertion for flags such as vital signs used in gated image reconstruction. Aside from data acquisition, hardware can generate live energy and discrimination spectra suitable for fast, automatic channel calibration.

Abstract: Increasingly, we must deal with complex subsurface structures in seismic exploration, often resulting in poor illumination and, therefore, poor image quality. Consequently, it is desirable to take into consideration the effects of wave propagation in the subsurface structure when designing an acquisition geometry. We developed a new, model-based implementation of the previously introduced focal-beam analysis method. The method's objective is to provide quantitative insight into the combined influence of acquisition geometry, overburden structure, and migration operators on image resolution and angle-dependent amplitude accuracy. This is achieved by simulation of migrated grid-point responses using focal beams. Note that the seismic response of any subsurface can be composed of a linear sum of grid-point responses. The focal beams have been chosen because any migration process represents double focusing. In addition, the focal source beam and focal detector beam relate migration quality to illumination properties of the source geometry and sensing properties of the detector geometry, respectively. Wave-equation modeling ensures that frequency-dependent effects in the seismic-frequency range are incorporated. We tested our method by application to a 3D salt model in the Gulf of Mexico. Investigation of well-sampled, all-azimuth, long-offset acquisition geometries revealed fundamental illumination and sensing limitations. Further results exposed the shortcomings of narrow-azimuth data acquisition. The method also demonstrates how acquisition-related amplitude errors affect seismic inversion results.

Abstract: Wireless sensor networks are increasingly being used in environmental monitoring applications. Collecting raw data from these networks can lead to excessive energy consumption. This is especially true when the application requires specialized sensors that have very high energy consumption, e.g. hydrological sensors for monitoring marine environments. We describe an adaptive sensor sampling scheme where nodes change their sampling frequencies autonomously based on the variability of the measured parameters. The sampling scheme also meets the user's sensing coverage requirements by using information provided by the underlying MAC protocol. This allows the scheme to automatically adapt to topology changes. Our results based on real and synthetic data sets, indicate a reduction in sensor sampling by up to 93%, reduction in message transmissions by up to 99% and overall energy savings of up to 87%. We also show that generally more than 90% of the collected readings fall within the user-defined error threshold.

Abstract: A mobile geophysical instrument produces geophysical data sets each associated with a position computed by use of a position sensor. A variable time delay results between a time when data for each geophysical data set is collected and a time when a position associated with each geophysical data set is recorded. A module receives distance transducer data and includes circuitry configured to generate a module signal based on trigger signals from the distance transducer and a calibration value. A data acquisition system (DAS) receives geophysical data sets from the geophysical instrument, positioning data from the positioning sensor, and the module signals. The DAS generates a DAS timestamp in response to each module signal and associates the DAS timestamp with each geophysical data set and a position associated with the geophysical data set, so as to substantially eliminate the variable time delay.

Abstract: In a data acquisition system a sensor module includes a motion sensor and a communication controller. The motion sensor and communication controller are prepared in a form factor adapted to be received within, or otherwise readily used with, the user appliance. A data signal produced by the motion sensor is adaptable for compliance validation.

Abstract: This paper presents recent developments in the use of electromagnetic induction tomography (EMT) for steel flow visualization. Several aspects are reported. First, results are shown from an 8-coil, single-frequency, EMT system from tests using liquid steel. The results are consistent with video recordings of an exposed section of the steel flow passing through a submerged entry nozzle, in terms of flow size and position, providing a good representation of the steel flow profile changes during trials. The second part describes the development of a system with a C-shaped sensor, which is capable of being slotted in place for practical deployment as well as being rapidly removed during nozzle changes. The effects of reducing the number of coils in this configuration were also studied. Finally, the development of a multiple-frequency system for plant use is reported. The system is designed based on a commercial data acquisition board, which can provide three sinusoidal signals with target frequencies for excitation simultaneously. This paper describes the new hardware electronics and software. Experimental results show that the system is able to identify a variety of test samples. Instead of imaging the cross-section of the steel flow profiles, the current system is developed for checking signal levels at different operation frequencies, which are of more interest for industrial use. Nevertheless, the work demonstrates a significant step forward to develop a multiple-frequency EMT system for practical use in this industrial process application.