Study on the Interactivity of Controlled and Automatic Information Processing in L2 Reading

L2 reading is not only an important channel for people to obtain information and knowledge,but also the main way for people to learn a foreign language.Reading information processing can be divided into controlled processing and automatic processing.Controlled information processing is a conscious and resource-intensive processing model,while automatic information processing is an unconscious and automatic processing model.This study investigates the characteristics and interactivity of controlled and automatic information processing in L2 reading,and explores the roles of controlled and automatic information processing strategies in improving L2 reading ability.The findings are as follows:(a)controlled and automatic information processing is interactive in L2 reading;and(b)the uses of controlled and automatic information processing strategies are beneficial to the improvement of the reading ability of L2 learners.This study has important theoretical and practical value in improving the efficiency of L2 reading teaching and learning.

结合地理信息与AIS数据的海上航道自适应提取方法

海上航道对于海上态势感知具有重要意义。然而,现有的航道提取方法存在航道航路点易丢失、提取准确性不高等问题,本文依据船舶航路点数量与其途经岛屿、港口等地理区域数量相等的准则,提出了一种结合地理信息与自动识别系统(Automatic Identification System, AIS)数据的海上航道自适应提取方法。首先,构建港口之间往返船只AIS航迹数据集,将每条AIS航迹等间距分段并计算每段航迹的平均航速,设置航速差初始阈值,计算相邻航段平均航速差超过阈值的数量作为初始船只转弯次数。其次,统计AIS航迹途经岛屿、港口等地理区域的数量,若其与利用AIS航迹提取的船舶转弯次数不相等,则根据两者的差异自适应调整航速差阈值,重新提取船舶航路点,直至其与途经地理区域的数量相等,将平均航速差超出最终阈值的航迹段的连接点作为船舶航路点。然后,利用基于密度的聚类算法将所有船舶的航路点聚类为航路点集合,计算航路点集合的质心作为航道的航路点。最后,以航道航路点为顶点、航路点之间的连线为边构建有向图,并删除落在陆地上的连线后得到最终的航道提取结果。利用潍坊港—连云港港之间行驶的20条船舶的AIS数据开展了海上航道提取实验,结果表明,与基于交通路径异常检测的航道提取方法相比,本文方法得到的船舶航路点的平均虚检率降低了9.1%,平均漏检率降低了16.7%,显著提升了航道航路点位置提取的准确性。

基于2比特判决反馈的改进AIS非相干解调算法

针对星载接收机接收到的船舶自动识别系统(Automatic Identification System,AIS)信号信噪比低、高斯最小频移键控调制采用的高斯成形滤波器产生码间干扰(Inter-Symbol Interference,ISI)以及非相干解调鲁棒性差等问题,提出了一种基于2比特判决反馈的改进AIS非相干解调算法。首先,接收信号通过匹配滤波器、鉴频器和自适应检测滤波器获得基带信号;其次,构造判决反馈,补偿鉴频噪声与ISI;最后,设计一种基于长短时记忆(Long-short Term Memory,LSTM)与注意力机制(Attention)的相位路径预测模型,获取2比特反馈补偿,改进判决反馈补偿能力。仿真与实测结果表明,改进方法较1比特判决反馈法对自适应滤波器的适应能力更强,在信噪比为7.2 dB时,误码率降低至10-5;较传统方法,真实场景下AIS信号的循环冗余校验通过率提升了9.5%。

船舶自动识别系统(AIS)数据在海洋渔业中研究应用现状

在全球海洋主要经济渔业资源衰退的背景下,如何保护和可持续开发利用海洋渔业资源受到全球各国、地区和组织高度重视,一直是研究热点。受传统海洋渔业数据的制约,一直难以全面了解远洋渔船的捕捞足迹,因此,无法对其实行有效监控和管理。船舶自动识别系统(automatic identification system,AIS)提供的全球远洋渔船轨迹数据可以用于量化分析从单艘到全球渔船行为,挖掘的历史捕捞强度空间信息可为海洋捕捞活动的监测管理和生态压力评估提供良好的可替代数据来源,成为近年海洋信息和海洋渔业研究的新热点。为促进AIS数据在我国海洋渔业中的研究应用,对AIS近年的研究内容和应用现状进行总结,指出AIS数据目前研究的不足和未来潜在的研究方法,以期为AIS在海洋渔业中的研究和应用提供参考。

悬空波导环境下AIS信号超视距传播特性分析

大气波导可陷获无线电波信号,使其发生超视距传播现象,影响无线电系统信号传播预测和性能评估应用。本文针对由探空数据诊断的悬空波导个例,利用对流层电波传播确定性方法模拟岸-船自动识别系统(automatic identification system,AIS)传播链路,定量研究了不同悬空波导环境影响下AIS信号的超视距传播特性。结果表明:波导强度50 M单位且底高约7 m的悬空波导环境下,AIS信号发生明显超视距传播现象;波导底高约700 m且强度较大的悬空波导环境也会对AIS信号传播产生影响;相比于单一悬空波导模型,复合悬空波导(文中指两个悬空波导层结构组成)环境对AIS信号传播影响更大。本文研究成果可为大气波导监测反演、无线电系统设计、装备效应评估等应用提供重要理论参考。

基于联邦学习的船舶AIS轨迹预测算法

联邦学习是一种可以在弱通信环境下有效解决数据孤岛问题的分布式机器学习方法。针对海上船舶轨迹实时预测问题,提出基于Fedves联邦学习框架与卷积神经网络-门控循环单元(CNN-GRU)模型的船舶轨迹预测算法(E-FVTP)。根据Fedves联邦学习框架,通过规范客户端数据集规模以及客户端正则项,在保持原有客户端数据特征的前提下,减小数据非独立同分布特征对全局模型的影响,加快收敛速度。面向海洋通信资源短缺场景,建立基于船舶自动识别系统(AIS)数据的CNN-GRU船舶轨迹预测模型,解决了船舶终端设备计算能力不足的问题。在MarineCadastre开源和舟山海洋船舶航行AIS数据集上的实验结果表明,E-FVTP在预测误差比集中式训练降低40%的情况下,收敛速度提升67%、通信代价降低76.32%,可实现复杂海洋环境中船舶轨迹的精确预测,保障海上交通安全。

A Heterogeneous Information Fusion Method for Maritime Radar and AIS Based on D-S Evidence Theory

Maritime radar and automatic identification systems (AIS), which are essential auxiliary equipment for navigation safety in the shipping industry, have played significant roles in maritime safety supervision. However, in practical applications, the information obtained by a single device is limited, and it is necessary to integrate the information of maritime radar and AIS messages to achieve better recognition effects. In this study, the D-S evidence theory is used to fusion the two kinds of heterogeneous information: maritime radar images and AIS messages. Firstly, the radar image and AIS message are processed to get the targets of interest in the same coordinate system. Then, the coordinate position and heading of targets are chosen as the indicators for judging target similarity. Finally, a piece of D-S evidence theory based on the information fusion method is proposed to match the radar target and the AIS target of the same ship. Particularly, the effectiveness of the proposed method has been validated and evaluated through several experiments, which proves that such a method is practical in maritime safety supervision.

System Supporting Automatic Generation of Finite Element Using Image Information

A mesh generating system has been developed in orde r to prepare large amounts of input data which are needed for easy implementation of a finite element analysis. This system consists of a Pre-Mesh Generator, an Automatic Mesh Generator and a Mesh Modifier. Pre-Mesh Generator produces the shape and sub-block information as input data of Automatic Mesh Generator by c arrying out various image processing with respect to the image information of th e drawing input using scanner. Automatic Mesh Generator generates mesh of trian gular elements in the arbitrarily shaped and multiple connected planar domain by using minimum necessary information. This generator has 3 methods of mesh gene ration for each sub-block, A) Regular Mesh Generation, B) Semi-Regular Mesh Ge neration and C) Irregular Mesh Generation. Any of them can be selected automati cally according to the external form of sub-block or the state of domain. Mesh Modifier projects and modifies the pattern of generated mesh by Automatic Mesh Generator as required. This system simplifies the user’s task while saving manp ower in carrying out the finite element analysis.

Unlocking the Potential:A Comprehensive Systematic Review of ChatGPT in Natural Language Processing Tasks

As Natural Language Processing(NLP)continues to advance,driven by the emergence of sophisticated large language models such as ChatGPT,there has been a notable growth in research activity.This rapid uptake reflects increasing interest in the field and induces critical inquiries into ChatGPT’s applicability in the NLP domain.This review paper systematically investigates the role of ChatGPT in diverse NLP tasks,including information extraction,Name Entity Recognition(NER),event extraction,relation extraction,Part of Speech(PoS)tagging,text classification,sentiment analysis,emotion recognition and text annotation.The novelty of this work lies in its comprehensive analysis of the existing literature,addressing a critical gap in understanding ChatGPT’s adaptability,limitations,and optimal application.In this paper,we employed a systematic stepwise approach following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses(PRISMA)framework to direct our search process and seek relevant studies.Our review reveals ChatGPT’s significant potential in enhancing various NLP tasks.Its adaptability in information extraction tasks,sentiment analysis,and text classification showcases its ability to comprehend diverse contexts and extract meaningful details.Additionally,ChatGPT’s flexibility in annotation tasks reducesmanual efforts and accelerates the annotation process,making it a valuable asset in NLP development and research.Furthermore,GPT-4 and prompt engineering emerge as a complementary mechanism,empowering users to guide the model and enhance overall accuracy.Despite its promising potential,challenges persist.The performance of ChatGP Tneeds tobe testedusingmore extensivedatasets anddiversedata structures.Subsequently,its limitations in handling domain-specific language and the need for fine-tuning in specific applications highlight the importance of further investigations to address these issues.

Type WYZ-97 Eighteen information Noninsulate Frequency shift Automatic Blocking System

Type WYZ 97 eighteen information noninsulate frequency shift automatic blocking system is the most advanced railroad signaling system in China nowadays.The article introduced its principles,technical targets,features and the applications.

AIS航标在遥测遥控系统中的定位跳变问题探究

文章以汕头港5号船舶自动识别系统(Automatic Identification System,AIS)航标为例,对AIS航标在遥测遥控系统中发生定位跳变的现象进行探讨,并简单阐述规范AIS航标管理和避免类似情况再次发生的一些工作思路。

Factors Influencing the Success of Agricultural Information System （AIS）： A Factor Analysis

This study aims at investigating the AIS （Agricultural Information System） in Hamedan province, Iran, benefiting from the list of criteria for well functioning AISs that were identified in earlier researches. For this purpose, a survey method with multi-stage stratified random sampling technique was used to select 31 agricultural researchers, and 62 extension workers in the province. The data were acquired by questionnaire and structured interviews. The instrument for data collection was subjected to pre-testing, validation and reliability tests. The results of the factor analysis revealed that the criteria could be categorized into four overarching groups based on their inter-correlation. The analysis of mentioned criteria in Hamedan province AIS showed less efficiency and effectiveness than studies conducted in other areas. But among these, two desirable criteria existed. It is recommended that the ecological knowledge system （EKS） should be integrated with AIS, and some ecological and sustainable development criteria should be added to the existing ones.

基于AIS+GSM的小型船舶动态监管终端设计

我国近海小型船舶数量众多、海域环境复杂、航线繁忙,而小型船舶一般没有安装船舶自动识别系统,因此给近海船舶航行安全带来威胁,也为渔船管理带来困难。基于AIS+GSM设计了小型船舶动态监管终端,采用太阳能供电、北斗与GPS双模定位、AIS和GSM双网通信,实现终端防拆防移、信息可视化、航程航线记录查询、自动报警、身份识别等功能,很好地满足近海小型船舶的管理需要,能有效保障船舶航行的安全。

基于AIS信号的低空大气波导监测试验分析

鉴于低空大气波导对海上工作的雷达、通信系统的显著影响,提出了基于实测船舶自动识别系统(automatic identification system, AIS)信号的海上低空大气波导遥感新方法.首先讨论了不同大气折射环境下的AIS信号传播特性,验证了低空大气波导尤其表面波导对海上实际VHF频段AIS信号的显著影响;然后给出了2018年4月20日以及22日岸基AIS接收机接收功率平面位置分布图结果,利用接收站附近探空站的修正大气折射率剖面验证了大气波导是形成AIS信号远距离传播的主要原因;最后给出了基于AIS信号反演低空大气波导的步骤,采用粒子群优化算法得到根据单一方位接收功率的反演结果.该方法具有被动接收、时空分辨率高的优点,是当前雷达海杂波、卫星导航信号遥感探测大气波导的有益补充.

Real-time Monitoring of Subsea Gas Pipelines,Offshore Platforms,and Ship Inspection Scores Using an Automatic Identification System

The aim of this research is to develop an algorithm and application that can perform real-time monitoring of the safety operation of offshore platforms and subsea gas pipelines as well as determine the need for ship inspection using data obtained from automatic identification system(AIS).The research also focuses on the integration of shipping database,AIS data,and others to develop a prototype for designing a real-time monitoring system of offshore platforms and pipelines.A simple concept is used in the development of this prototype,which is achieved by using an overlaying map that outlines the coordinates of the offshore platform and subsea gas pipeline with the ship’s coordinates(longitude/latitude)as detected by AIS.Using such information,we can then build an early warning system(EWS)relayed through short message service(SMS),email,or other means when the ship enters the restricted and exclusion zone of platforms and pipelines.The ship inspection system is developed by combining several attributes.Then,decision analysis software is employed to prioritize the vessel’s four attributes,including ship age,ship type,classification,and flag state.Results show that the EWS can increase the safety level of offshore platforms and pipelines,as well as the efficient use of patrol boats in monitoring the safety of the facilities.Meanwhile,ship inspection enables the port to prioritize the ship to be inspected in accordance with the priority ranking inspection score.

Exploring the Potentialities of Automatic Extraction of University Webometric Information

Purpose:The main objective of this work is to show the potentialities of recently developed approaches for automatic knowledge extraction directly from the universities’websites.The information automatically extracted can be potentially updated with a frequency higher than once per year,and be safe from manipulations or misinterpretations.Moreover,this approach allows us flexibility in collecting indicators about the efficiency of universities’websites and their effectiveness in disseminating key contents.These new indicators can complement traditional indicators of scientific research(e.g.number of articles and number of citations)and teaching(e.g.number of students and graduates)by introducing further dimensions to allow new insights for“profiling”the analyzed universities.Design/methodology/approach:Webometrics relies on web mining methods and techniques to perform quantitative analyses of the web.This study implements an advanced application of the webometric approach,exploiting all the three categories of web mining:web content mining;web structure mining;web usage mining.The information to compute our indicators has been extracted from the universities’websites by using web scraping and text mining techniques.The scraped information has been stored in a NoSQL DB according to a semistructured form to allow for retrieving information efficiently by text mining techniques.This provides increased flexibility in the design of new indicators,opening the door to new types of analyses.Some data have also been collected by means of batch interrogations of search engines(Bing,www.bing.com)or from a leading provider of Web analytics(SimilarWeb,http://www.similarweb.com).The information extracted from the Web has been combined with the University structural information taken from the European Tertiary Education Register(https://eter.joanneum.at/#/home),a database collecting information on Higher Education Institutions(HEIs)at European level.All the above was used to perform a clusterization of 79 Italian universities based on structural and digital indicators.Findings:The main findings of this study concern the evaluation of the potential in digitalization of universities,in particular by presenting techniques for the automatic extraction of information from the web to build indicators of quality and impact of universities’websites.These indicators can complement traditional indicators and can be used to identify groups of universities with common features using clustering techniques working with the above indicators.Research limitations:The results reported in this study refers to Italian universities only,but the approach could be extended to other university systems abroad.Practical implications:The approach proposed in this study and its illustration on Italian universities show the usefulness of recently introduced automatic data extraction and web scraping approaches and its practical relevance for characterizing and profiling the activities of universities on the basis of their websites.The approach could be applied to other university systems.Originality/value:This work applies for the first time to university websites some recently introduced techniques for automatic knowledge extraction based on web scraping,optical character recognition and nontrivial text mining operations(Bruni&Bianchi,2020).

基于L-System的土族盘绣规则纹样生成方法

盘绣作为土族刺绣艺术的主体,具有鲜明的民族和地域特色。针对其传统手工制法存在工艺复杂且效率低,耗时长,质量参差不齐等问题,提出了一种基于L系统(L-System)的土族盘绣规则纹样图案快速生成方法。先分析土族盘绣的结构特征并归纳规律,基于L-System定义了指令符号集、相应的公理以及路径规则。然后提出并设计了规则纹样位置约束函数。最后用turtle控制指令根据约束函数按照路径规则对生成的纹样进行重组,实现土族盘绣图案的自动生成。实验评价采用图像信息熵对比以及专业、非专业人士评判打分的方法,结果表明上述方法所生成的图案能达到与原始绣片高度相似的效果,所提方法能快速自动生成土族盘绣图案,为艺人制作底稿节约了时间,提高了效率。

Design and Application of the Automatic Monitoring System for Wastewater Source in Shandong Province

In order to realize real-time online monitoring of the wastewater source enterprises,manage and issue monitoring information,this paper comprehensively uses automatic control,embedded data acquisition and transmission,distributed computing and data processing,geographic information system,etc.to develop automatic monitoring system of the wastewater source in Shandong Province.This system incorporates automatic monitoring information acquisition,transmission and daily work as an organic whole.The system realizes not only the continuous online monitoring of wastewater source enterprise,but also the deep excavation and utilization on monitoring information.It provides scientific and objective basis for energy saving,consumption reduction,carbon emission reduction,total amount control and other environmental management works,and meets the requirements of environmental management and related departments to wastewater source management.

基于AIS数据的敏感水域船舶异常行为检测

为了检测敏感水域中船舶的异常行为,提出了基于船舶自动识别系统(AIS)数据的敏感水域船舶异常行为检测框架。首先,选定3个敏感水域,将进出次数、停留时间和速度比值3个指标作为异常因子并建立检测框架;然后,采用专家调查法构造判断矩阵,进而确定异常因子权重;接着,基于AIS数据确定异常因子值及其评分,综合异常因子权重并利用层次加权计算得到船舶异常得分;最后,利用南海、东京湾和琉球3个敏感水域近2年的AIS数据进行了试验分析。试验结果表明,该框架可有效检测出敏感水域中行为异常的船舶,具有可行性。

基于全球AIS的多源航迹关联数据集

数据、算法和算力是当前人工智能技术发展的3大推力,考虑到智能关联算法研究的迫切需求和多雷达协同观测航迹数据获取困难,针对航迹关联数据集缺失问题,该文公开了多源航迹关联数据集(MTAD),其由全球AIS航迹数据经栅格划分、自动中断和噪声添加处理步骤构建。该数据集包括训练集和测试集两大部分,共有航迹百万余条,其中训练集包含5000个场景样本,测试集包含1000个场景样本,每一个场景样本由几个到几百个数量不等的航迹构成,涵盖多种运动模式、多种目标类型和长度不等的持续时间。同时,进一步对构造的MTAD数据集进行可视化分析,详细研究了各个栅格内航迹的特点,证明了该数据集的丰富性、合理性和有效性。最后,作为参考,给出了关联评价指标和关联基线结果。该数据集目前已被用作海军“金海豚”杯竞赛科目专用数据集。