Intelligent Data Acquisition Technology Based on Agents

In this paper we use the wireless Android smart network to control data collection network of wireless sensor networks, and establish the wireless sensor network data acquisition model based on particle swarm layout algorithm, and design the data signal receiving algorithm by introducing wireless fence monitoring method. In order to verify the reliability and applicability of the algorithm, we compare the particle swarm layout algorithm with PSO, random distribution and genetic algorithm. Through experiments, data gathering integrity of particle swarm layout algorithm reaches 96%, the time of data acquisition is 1258 seconds, the iterative number is 12587 times. It is the best of the three algorithms. It provides a theoretical reference for the research on data acquisition and control technology of wireless sensor network.

Recently, a novel data acquisition method has been proposed and experimentally implemented for differential phase‐contrast computed tomography (DPC‐CT), in which a conventional X‐ray tube and a Talbot‐Lau‐type interferometer were utilized in data acquisition. The divergent nature of the data acquisition system requires a divergent‐beam image reconstruction algorithm for DPC‐CT. This paper focuses on addressing this image reconstruction issue. We have developed a filtered backprojection algorithm to directly reconstruct the DPC‐CT images from acquired fan‐beam data. The developed algorithm allows one to directly reconstruct the decrement of the real part of the refractive index from the measured data. In order to accurately reconstruct an image, the data need to be acquired over an angular range of at least 180∘ plus the fan angle. As opposed to the parallel beam data acquisition and reconstruction methods, a 180∘‐rotation angle for the data acquisition system does not provide sufficient data for an accurate reconstruction of the entire field of view. Numerical simulations have been conducted to validate the image reconstruction algorithm.

Data acquisition for automated processing is a central aspect of clinical trials with large numbers of cases because of their extensive demand for manpower. Scientific data can be collected using data forms, which are created in Hypertext Markup Language and published on the Internet. The completed data form can be returned via E-mail or Common Gateway Interface-Script and forwarded into a study database. For the Internet-based data acquisition of a prospective multicenter trial (e.g., on endophthalmitis incidence after cataract extraction), we developed two special HTML forms that can be opened in the ophthalmology department's homepage. A large number of acquired anonymous data has been collected via Internet and automatically transferred into the trial database. The Internet provides a fast and easy avenue for the acquisition of scientific data. This method of data acquisition and data processing will become more common place in multicenter clinical trials.

Data Acquisition and Interface Technology is a compulsory course for the major of measurement and control technology and instrument in Southwest Petroleum University, and it is a basic course combining theory and practice closely. The traditional experiment teaching is limited by various conditions. Students can only complete the specific experiment content with limited experiment equipment in limited time and place. It is an effective way to solve the above problems by introducing virtual simulation technology to construct the remote measure and control experiment platform to carry on the reform of the traditional experiment teaching mode. The remote measurement and control platform uses virtual technology to form the test function into a software module with image-realistic panel controls, to complete the test and processing tasks as if doing experiments in the laboratory, to move the experiment teaching into the classroom, to move into the network and life, and to realize the perfect fusion of theory and practice. It has been proved that the application of the remote measurement and control platform in the experimental teaching of the course of Data Acquisition and Interface Technology can improve the teaching effect. Moreover, the cost is low and the efficiency is high, so that students cannot be limited by time and space, improve their self-learning ability and practical innovation ability, which is of great significance in the teaching of the course of measurement and control technology.

The rate of development of open government data (OGD) portals has been fast in recent years due to potential benefits of the utilization of OGD. However, scholars have emphasized lack of use as a key problem in the realization of these benefits. Although studies have been carried out to understand decisive factors in OGD utilization from the aspects of either portals or users, they failed to consider the interaction between the two. Therefore, our study carried out an analysis of the interaction between users and OGD portals during users’ data acquisition process from three aspects: data acquisition methods, data quality requirements, and helping functions. We carried out a survey in a Chinese population to collect data for analysis. Results show users’ high acceptance of keyword search as their method for data acquisition through OGD portals but browsing showed higher usage frequency and was a more stable data acquisition behavior. Females show better acceptance of regular recommendations (e.g. RSS) based on their visiting histories than males. Users’ age, education background and occupation affect their demands of different data quality attributes. Our analysis also shows positive relationship between users’ data acquisition habits with their demands of data quality, users’ need of help with their feelings of difficulties in using the portal, and users’ need of help with their demands of data quality. We suggest promoting OGD utilization by offering better helping functions and improving data qualities in future development of OGD portals.

In the context of the development of intelligent education, the assessment of teachers' cognitive skills in information technology has been paid more and more attention by researchers. Therefore, this study carried out the assessment and research on the micro-ability of teachers' cognitive skills in information technology. Based on the loop model of analyzing the internal process of learning activities put forward by Romisosky, the study firstly divided the task dimension of teachers' cognitive skills into pre-knowledge assessment and applied pre-knowledge assessment. Secondly, different data acquisition indicators, data acquisition methods, data scoring methods and scoring standards are used for evaluation. Data acquisition and analysis are carried out according to multiple-choice answers and platform automatic saving. In the final result report section, not only the overall result of the evaluation, but also the comparison table of expert design scheme is given, so that teachers can understand the similarities and differences between their own design and expert design, and make timely adjustments and Suggestions for teachers' problems in the evaluation. The research shows that the platform-based cognitive skills assessment of teachers can measure the ability of teachers to explore learning activities, push personalized teaching design resources, and provide references for improving teachers' cognitive skills of information technology.

This paper will explore the dynamics of integrating data acquisition technology into a university level course.The complete process from instructor training and competence, to end delivery of materials in a digital format, will be explored.The equipment necessary, the supporting material development required, and the costs will be shown.This paper will be based upon my experiences at Purdue University.I implemented a complete unit of instruction related to data acquisition and diagnostics into my aircraft powerplant technologies course.I prepared digital classroom materials, developed supporting laboratory projects, and programmed the equipment to support our specific needs.The result has been a comprehensive introduction to data acquisition and diagnostics for our students.

PurposeTo develop data acquisition and image reconstruction methods to enable high‐resolution 1H MR spectroscopic imaging (MRSI) of the brain, using the recently proposed subspace‐based spectroscopic imaging framework called SPICE (SPectroscopic Imaging by exploiting spatiospectral CorrElation).Theory and MethodsSPICE is characterized by the use of a subspace model for both data acquisition and image reconstruction. For data acquisition, we propose a novel spatiospectral encoding scheme that provides hybrid data sets for determining the subspace structure and for image reconstruction using the subspace model. More specifically, we use a hybrid chemical shift imaging /echo‐planar spectroscopic imaging sequence for two‐dimensional (2D) MRSI and a dual‐density, dual‐speed echo‐planar spectroscopic imaging sequence for three‐dimensional (3D) MRSI. For image reconstruction, we propose a method that can determine the subspace structure and the high‐resolution spatiospectral reconstruction from the hybrid data sets generated by the proposed sequences, incorporating field inhomogeneity correction and edge‐preserving regularization.ResultsPhantom and in vivo brain experiments were performed to evaluate the performance of the proposed method. For 2D MRSI experiments, SPICE is able to produce high‐SNR spatiospectral distributions with an approximately 3 mm nominal in‐plane resolution from a 10‐min acquisition. For 3D MRSI experiments, SPICE is able to achieve an approximately 3 mm in‐plane and 4 mm through‐plane resolution in about 25 min.ConclusionSpecial data acquisition and reconstruction methods have been developed for high‐resolution 1H‐MRSI of the brain using SPICE. Using these methods, SPICE is able to produce spatiospectral distributions of 1H metabolites in the brain with high spatial resolution, while maintaining a good SNR. These capabilities should prove useful for practical applications of SPICE. Magn Reson Med 76:1059–1070, 2016. © 2015 Wiley Periodicals, Inc.

Much emphasis has been given to research and development of manufacturing systems to produce machine products, such as automotive and machine tools, with high accuracy and quality since the first industrial revolution in 18th Centuries. Industry 4.0 initiated by Germany also deals with the advanced manufacturing systems, which have the capability called “Plug and Produce”, by applying such recent information and communication technologies as CPS (Cyber Physical Systems) and IoTs (Internet of Things) . The paper deals with the new manufacturing systems called HMS (Holonic Manufacturing Systems), which was proposed by an international collaborations for the advanced manufacturing systems under the recent ICT (Information and Communication Technologies) environment.

A review on technologies and their usage in solid waste monitoring and management systems: Issues and challenges

Rapid development of modern science and technology drives the development of data acquisition technology. Data mining technology in the digital display instrument, site acquisition, and other fields has a broad demand. This paper studies the intelligent meter data acquisition method based on OPC communication. It proposes the calculation method of the operation time for key equipment based on the distributed control system and the data obtained from the comprehensive analysis are shown in DCS. It achieves real-time interaction and improved management efficiency and automation management level while reducing the workload of engineers.

Towards an automated image-based estimation of building age as input for Building Energy Modeling (BEM)

This paper overviews various methods of data acquisition from GEM detectors. Presented are currently working systems in tokamaks. The data acquisition methods are divided into two parts. First part, devoted to analog signal processing , describes different approaches for signals acquisition, i.e. pulse amplifying and shaping, ASIC use, delay lines. Digital data acquisition part describes presently used high speed interfaces and system standards. Described are also different approaches for data handling, i.e. online analysis, data reduction, system topologies.

The breadth of ion-beam nanoscience methods discussed in the proceeding chapters implies that the control and readout systems also span a wide range of techniques. For many nanoscience and technology applications the need to process or characterise a batches of samples has lead to a convergence of data acquisition systems and control systems. This coupled with the development of high-performance lowcost computing over the past decades has lead to a progressive evolution in data acquisition technology. Historically, much of the electronics used in nanoscience and technology using ion beams is based on nuclear analogue pulse counting and spectrometry where NIM (Nuclear Instrumentation Modules) have been a standard tool for some decades.

This paper presents the methods for power system transient signal data acquisition, it includes two key technologies, the first is high-precision GPS-based remote synchronization for data acquisition, and the second is high-speed sampling and storage technologies. For the first problem, a single variable linear regression model is established for the GPS PPS signal and a UCT on-line estimation algorithm is developed to generate accurate and steady PPS (pulse per second). The sampling pulse which is synchronized with the corrected second pulse is generated simultaneously. For the second problem, a high-speed data acquisition system with a two level circulating storage scheme specialized for transient signal recording is developed in this paper.