Alternate Data Acquisition and Real-time Monitoring System on HT-7 Tokamak

A new system called alternate data acquisition and real-time monitoring system has been developed for long-time discharge in tokamak operation. It can support continuous on-line data acquisition at a high sampling rate and a graphic display of the plasma parameters during the discharge. Thus operators can monitor and control the plasma state in real time. An application of this system has been demonstrated on the HT-7 tokamak.

Applied Research of the Inner Timer of General Microcomputer in High-Speed and Real-Time Data Acquisition System

The real-time data acquisition system controlled by microcomputer is applied widely. It is very important how to use the inner timer of microcomputer to realize accurate timing of sampling-interval in the application of data acquisition. This paper discusses in detail the procedure that we use the inner timer of microcomputer to realize real-time data acquisition with high timing-accuracy, and analyze the error of timing-accuracy. It also gives us a relevant routine programmed in assembly language.

Sentiment Drift Detection and Analysis in Real Time Twitter Data Streams

Handling sentiment drifts in real time twitter data streams are a challen-ging task while performing sentiment classifications,because of the changes that occur in the sentiments of twitter users,with respect to time.The growing volume of tweets with sentiment drifts has led to the need for devising an adaptive approach to detect and handle this drift in real time.This work proposes an adap-tive learning algorithm-based framework,Twitter Sentiment Drift Analysis-Bidir-ectional Encoder Representations from Transformers(TSDA-BERT),which introduces a sentiment drift measure to detect drifts and a domain impact score to adaptively retrain the classification model with domain relevant data in real time.The framework also works on static data by converting them to data streams using the Kafka tool.The experiments conducted on real time and simulated tweets of sports,health care andfinancial topics show that the proposed system is able to detect sentiment drifts and maintain the performance of the classification model,with accuracies of 91%,87%and 90%,respectively.Though the results have been provided only for a few topics,as a proof of concept,this framework can be applied to detect sentiment drifts and perform sentiment classification on real time data streams of any topic.

Cyber Resilience through Real-Time Threat Analysis in Information Security

This paper examines how cybersecurity is developing and how it relates to more conventional information security. Although information security and cyber security are sometimes used synonymously, this study contends that they are not the same. The concept of cyber security is explored, which goes beyond protecting information resources to include a wider variety of assets, including people [1]. Protecting information assets is the main goal of traditional information security, with consideration to the human element and how people fit into the security process. On the other hand, cyber security adds a new level of complexity, as people might unintentionally contribute to or become targets of cyberattacks. This aspect presents moral questions since it is becoming more widely accepted that society has a duty to protect weaker members of society, including children [1]. The study emphasizes how important cyber security is on a larger scale, with many countries creating plans and laws to counteract cyberattacks. Nevertheless, a lot of these sources frequently neglect to define the differences or the relationship between information security and cyber security [1]. The paper focus on differentiating between cybersecurity and information security on a larger scale. The study also highlights other areas of cybersecurity which includes defending people, social norms, and vital infrastructure from threats that arise from online in addition to information and technology protection. It contends that ethical issues and the human factor are becoming more and more important in protecting assets in the digital age, and that cyber security is a paradigm shift in this regard [1].

Real-time crash prediction on freeways using data mining and emerging techniques

Recent advances in intelligent transportation system allow traffic safety studies to extend from historic data-based analyses to real-time applications. The study presents a new method to predict crash likelihood with traffic data collected by discrete loop detectors as well as the web-crawl weather data. Matched case-control method and support vector machines （SVMs） technique were employed to identify the risk status. The adaptive synthetic over-sampling technique was applied to solve the imbalanced dataset issues. Random forest technique was applied to select the contributing factors and avoid the over-fitting issues. The results indicate that the SVMs classifier could successfully classify 76.32% of the crashes on the test dataset and 87.52% of the crashes on the overall dataset, which were relatively satisfactory compared with the results of the previous studies. Compared with the SVMs classifier without the data, the SVMs classifier with the web-crawl weather data increased the crash prediction accuracy by 1.32% and decreased the false alarm rate by 1.72%, showing the potential value of the massive web weather data. Mean impact value method was employed to evaluate the variable effects, and the results are identical with the results of most of previous studies. The emerging technique based on the discrete traffic data and web weather data proves to be more applicable on real- time safety management on freeways.

Data Transfer Over the Internet for Real Time Applications

Efficient real time data exchange over the Internet plays a crucial role in the successful application of web-based systems. In this paper, a data transfer mechanism over the Internet is proposed for real time web based applications. The mechanism incorporates the eXtensible Markup Language （XML） and Hierarchical Data Format （HDF） to provide a flexible and efficient data format. Heterogeneous transfer data is classified into light and heavy data, which are stored using XML and HDF respectively; the HDF data format is then mapped to Java Document Object Model （JDOM） objects in XML in the Java environment. These JDOM data objects are sent across computer networks with the support of the Java Remote Method Invocation （RMI） data transfer infrastructure. Client＇s defined data priority levels are implemented in RMI, which guides a server to transfer data objects at different priorities. A remote monitoring system for an industrial reactor process simulator is used as a case study to illustrate the proposed data transfer mechanism.

Impact of GPS Almanac Broadcast Strategy on the Signal Acquisition Time

This paper investigates the problem of almanac affecting the signal acquisition time with two constraints: different age of data and multi-sets of almanac. The contributions made in this paper include: 1) the exploiting of signal acquisition concept to extend well-known almanac function of predicting visible satellite and initializing signal acquisition to minimizing the signal acquisition time; 2) a model based on code phase and Doppler frequency to reflect the impact of multi-sets of almanac on the signal acquisition time; 3) the evaluation of the existing GPS almanac with different broadcast strategy. The theoretical analyses and simulations conducted on three sets of almanac show that the model proposed in this paper is general and efficient for almanac design and application.

Quality control of marine big data——a case study of real-time observation station data in Qingdao

Offshore waters provide resources for human beings,while on the other hand,threaten them because of marine disasters.Ocean stations are part of offshore observation networks,and the quality of their data is of great significance for exploiting and protecting the ocean.We used hourly mean wave height,temperature,and pressure real-time observation data taken in the Xiaomaidao station(in Qingdao,China)from June 1,2017,to May 31,2018,to explore the data quality using eight quality control methods,and to discriminate the most effective method for Xiaomaidao station.After using the eight quality control methods,the percentages of the mean wave height,temperature,and pressure data that passed the tests were 89.6%,88.3%,and 98.6%,respectively.With the marine disaster(wave alarm report)data,the values failed in the test mainly due to the influence of aging observation equipment and missing data transmissions.The mean wave height is often affected by dynamic marine disasters,so the continuity test method is not effective.The correlation test with other related parameters would be more useful for the mean wave height.

FPGA SoC Based Multichannel Data Acquisition System with Network Control Module

Normally, Data acquisition (DAQ) is used to acquire the signals from different devices like sensors, transducers, actuators etc. The data acquisition is also used to analyze the signals, digitizing the signals and acquiring the signals from different inputs. The main drawbacks in data acquisition system are data storage, hardware size and remote monitoring. The System-on-Chip Field Programmable Gate Array (SoC-FPGA) is used in the proposed system in the aim to reduce the hardware and memory size. Further to provide remote monitoring with Ethernet/Wi-Fi, the Network Control Module (NCM) is integrated with Data acquisition and processing module for the communication between the systems. This developed system achieves high resolution with memory reduction, reduced hardware size, fast remote monitoring and control. It is used for real time processing in DAQ and signal processing. For fault tolerance and portability, the full system reconfigurability based FPGA acts as the best solution and the system can be reused with different configurations. The control of data acquisition and the subsequent management of data are coded in LabVIEW. LabVIEW tool is used to design and develop a four-channel Data Acquisition and Processing (DAQP) unit. National Instruments Data Acquisition (NIDAQ) and National Instruments Field Programmable Gate Array (NIFPGA) are used to test and implement the design for real time processing. This is designed to provide high accuracy, storage and portability.

Design and FPGA verification of a novel reliable real-time data transfer system

Considering the increasing use of information technology with established standards, such as TCP/IP and XML in modern industrial automation, we present a high cost performance solution with FPGA (field programmable gate array) imple-mentation of a novel reliable real-time data transfer system based on EPA (Ethernet for plant automation) protocol and IEEE 1588 standard. This combination can provide more predictable and real-time communication between automation equipments and precise synchronization between devices. The designed EPA system has been verified on Xilinx Spartan3 XC3S1500 and it consumed 75% of the total slices. The experimental results show that the novel industrial control system achieves high synchro-nization precision and provides a 1.59-μs standard deviation between the master device and the slave ones. Such a real-time data transfer system is an excellent candidate for automation equipments which require precise synchronization based on Ethernet at a comparatively low price.

Data Acquisition System for Electron Energy Loss Coincident Spectrometers

A Data Acquisition System （DAQ） for electron energy loss coincident spectrometers （EELCS） has been developed. The system is composed of a Multiplex Time-Digital Converter （TDC） that measures the flying time of positive and negative ions and a one-dimension positionsensitive detector that records the energy loss of scattering electrons. The experimental data are buffered in a first-in-first-out（FIFO） memory module, then transferred from the FIFO memory to PC by the USB interface. The DAQ system can record the flying time of several ions in one collision, and allows of different data collection modes. The system has been demonstrated at the Electron Energy Loss Coincident Spectrometers at the Laboratory of Atomic and Molecular Physics, USTC. A detail description of the whole system is given and experimental results shown.

Screening and reconstruction of real-time traffic data

The quality of real time traffic information is of the great importance, therefore the factors having effect on traffic characteristics are analyzed in general, and the necessities of real time data processing are summarized. The identification and reconstruction of real time traffic data are analyzed using Kalman filter equation and statistical approach. Four methods for ITS (Intelligent transportation system) detector data screening in traffic management systems are discussed in detail. Meanwhile traffic data examinations are discussed with solutions formulated through analysis, and recommendations are made for information collection and data management in future.

Design and development of real-time query platform for big data based on hadoop

This paper designs and develops a framework on a distributed computing platform for massive multi-source spatial data using a column-oriented database(HBase).This platform consists of four layers including ETL(extraction transformation loading) tier,data processing tier,data storage tier and data display tier,achieving long-term store,real-time analysis and inquiry for massive data.Finally,a real dataset cluster is simulated,which are made up of 39 nodes including 2 master nodes and 37 data nodes,and performing function tests of data importing module and real-time query module,and performance tests of HDFS's I/O,the MapReduce cluster,batch-loading and real-time query of massive data.The test results indicate that this platform achieves high performance in terms of response time and linear scalability.

The development of real time data driving multi-axis linkage and synergic movement control system of 3D variable cross-section roll forming machine

The three dimensional variable cross-section roll forming is a kind of new metal forming technology which combines large forming force,multi-axis linkage movement and space synergic movement,and the sequential synergic movement of the ganged roller group is used to complete the metal sheet forming according to the shape of the complicated and variable forming part data.The control system should meet the demands of quick response to the test requirements of the product part.A new kind of real time data driving multi-axis linkage and synergic movement control strategy of 3D roll forming is put forward in the paper.In the new control strategy,the forming data are automatically generated according to the shape of the parts,and the multi-axis linkage movement together with cooperative motion among the six stands of the 3D roll forming machine is driven by the real-time information,and the control nodes are also driven by the forming data.The new control strategy is applied to a 48axis 3D roll forming machine developed by our research center,and the control servo period is less than 10ms.A forming experiment of variable cross section part is carried out,and the forming precision is better than±0.5mm by the control strategy.The result of the experiment proves that the control strategy has significant potentiality for the development of 3D roll forming production line with large scale,multi-axis ganged and synergic movement.

Real Time Data Analysis of West Rapti River Basin of Nepal

Floods are the most widespread climate-related hazards in the world, and they impact more people globally than any other type of natural disasters. It causes over one third of the total economic loss from natural catastrophes and is responsible for two thirds of people affected by natural disasters. On the other hand, studies and analysis have shown that damage reductions due to forecasts improvements can range from a few percentage points to as much as 35% of annual flood damages. About 300 people lose their lives each year due to floods and landslides in Nepal with property damage exceeding 626 million NPR on average. The West Rapti River basin is one of the most flood prone river basins in Nepal. The real-time flood early warning system together with the development of water management and flood protection schemes plays a crucial role in reducing the loss of lives and properties and in overall development of the basin. The non-structural mitigating measure places people away from flood. This method is designed to reduce the impact of flooding to society and economy. This paper presents an overview of flood problems in the West Rapti River basin, causes and consequences of recent floods and the applicability and effectiveness of the real time data to flood early warning in Nepal.

Web-based GIS System for Real-time Field Data Collection Using Personal Mobile Phone

Recently, use of mobile communicational devices in field data collection is increasing such as smart phones and cellular phones due to emergence of embedded Global Position System GPS and Wi-Fi Internet access. Accurate timely and handy field data collection is required for disaster management and emergency quick responses. In this article, we introduce web-based GIS system to collect the field data by personal mobile phone through Post Office Protocol POP3 mail server. The main objective of this work is to demonstrate real-time field data collection method to the students using their mobile phone to collect field data by timely and handy manners, either individual or group survey in local or global scale research.

Real-time performance of periodic data transmission in EPA industrial Ethernet

To evaluate and improve the real-time performance of Ethernet for plant automation（EPA） industrial Ethernet,the real-time performance of EPA periodic data transmission was theoretically and experimentally studied.By analyzing information transmission regularity and EPA deterministic scheduling mechanism,periodic messages were categorized as different modes according to their entering-queue time.The scheduling characteristics and delivery time of each mode and their interacting relations were studied,during which the models of real-time performance of periodic information transmission in EPA system were established.On this basis,an experimental platform is developed to test the delivery time of periodic messages transmission in EPA system.According to the analysis and the experiment,the main factors that limit the real-time performance of EPA periodic data transmission and the improvement methods were proposed.

Integrated Real-Time Big Data Stream Sentiment Analysis Service

Opinion (sentiment) analysis on big data streams from the constantly generated text streams on social media networks to hundreds of millions of online consumer reviews provides many organizations in every field with opportunities to discover valuable intelligence from the massive user generated text streams. However, the traditional content analysis frameworks are inefficient to handle the unprecedentedly big volume of unstructured text streams and the complexity of text analysis tasks for the real time opinion analysis on the big data streams. In this paper, we propose a parallel real time sentiment analysis system: Social Media Data Stream Sentiment Analysis Service (SMDSSAS) that performs multiple phases of sentiment analysis of social media text streams effectively in real time with two fully analytic opinion mining models to combat the scale of text data streams and the complexity of sentiment analysis processing on unstructured text streams. We propose two aspect based opinion mining models: Deterministic and Probabilistic sentiment models for a real time sentiment analysis on the user given topic related data streams. Experiments on the social media Twitter stream traffic captured during the pre-election weeks of the 2016 Presidential election for real-time analysis of public opinions toward two presidential candidates showed that the proposed system was able to predict correctly Donald Trump as the winner of the 2016 Presidential election. The cross validation results showed that the proposed sentiment models with the real-time streaming components in our proposed framework delivered effectively the analysis of the opinions on two presidential candidates with average 81% accuracy for the Deterministic model and 80% for the Probabilistic model, which are 1% - 22% improvements from the results of the existing literature.

Scheduling transactions in mobile distributed real-time database systems

A DMVOCC-MVDA(distributed multiversion optimistic concurrency control with multiversion dynamic adjustment)protocol was presented to process mobile distributed real-time transaction in mobile broadcast environments.At the mobile hosts,all transactions perform local pre-validation.The local pre-validation process is carried out against the committed transactions at the server in the last broadcast cycle.Transactions that survive in local pre-validation must be submitted to the server for local final validation.The new protocol eliminates conflicts between mobile read-only and mobile update transactions,and resolves data conflicts flexibly by using multiversion dynamic adjustment of serialization order to avoid unnecessary restarts of transactions.Mobile read-only transactions can be committed with no-blocking,and respond time of mobile read-only transactions is greatly shortened.The tolerance of mobile transactions of disconnections from the broadcast channel is increased.In global validation mobile distributed transactions have to do check to ensure distributed serializability in all participants.The simulation results show that the new concurrency control protocol proposed offers better performance than other protocols in terms of miss rate,restart rate,commit rate.Under high work load(think time is 1s)the miss rate of DMVOCC-MVDA is only 14.6%,is significantly lower than that of other protocols.The restart rate of DMVOCC-MVDA is only 32.3%,showing that DMVOCC-MVDA can effectively reduce the restart rate of mobile transactions.And the commit rate of DMVOCC-MVDA is up to 61.2%,which is obviously higher than that of other protocols.

If real-time route and high-speed data is important,GoTa is vital.

GoTaTM from ZTE is the world’s first CDMA-based system. Now, ZTE proudly introduces its third-generation digital trunking system featuring a centralized dispatch,