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Identification Accuracy of Nonlinear System based on Volterra Model in Frequency Domain 基于频域Volterra模型的非线性系统辨识精度
Pub Date : 2013-01-01 DOI: 10.1016/j.aasri.2013.10.044
Pavlenko Vitaliy, Fomin Aleksandr, Pavlenko Sergey, Grigorenko Yuriy

The accuracy of the interpolation method for identification of nonlinear dynamical systems based on the Volterra model in the frequency domain is studied. To highlight the n-th partial component in the response of the system to the test signal the n-th partial derivative of the response using the test signal amplitude is found and its value is taken at zero. The polyharmonic signals are used as test ones. The algorithmic and software toolkit is developed for identification processes. This toolkit is used to construct the informational model of test system. The model is built as a first, second and third order amplitude–frequency characteristics and phase–frequency characteristics. The comparison of obtained characteristics with standard is given.

研究了基于频域Volterra模型的非线性动力系统辨识插值方法的精度。为了突出显示系统对测试信号的响应中的第n个偏分量,利用测试信号的振幅找到响应的第n个偏导数,并取其值为零。多谐信号作为测试信号。为识别过程开发了算法和软件工具包。该工具包用于构建测试系统的信息模型。建立了一阶、二阶和三阶幅频特性和相频特性模型。并将所得特性与标准进行了比较。
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引用次数: 6
A Distributed Variable Tap-length Algorithm within Diffusion Adaptive Networks 扩散自适应网络中的一种分布式变跳长算法[j]
Pub Date : 2013-01-01 DOI: 10.1016/j.aasri.2013.10.061
Leilei Li , Jingfeng Feng , Jianhui He , Jonathon A. Chambers

In this work, an adaptive algorithm with variable tap-length is proposed for diffusion networks, where all nodes exchange information with their connected group without a fusion center and utilize both exchanged information and their local observation to make their individual estimations. Based on a fractional tap-length solution and the fully distributed structure of networks, we propose the algorithm to resolve the estimation problems on both tap-length and tap-weights. The proposed algorithm with adaptive tap-length structure enables the networks to reduce communication energy and network resources. The convergence properties of this algorithm are confirmed by the simulation results.

本文提出了一种变跳长自适应扩散网络算法,在扩散网络中,所有节点在没有融合中心的情况下与其连接的群体交换信息,并利用交换的信息和各自的局部观测值进行各自的估计。基于分数阶接长解和全分布式网络结构,提出了一种解决接长和接权估计问题的算法。该算法采用自适应跳线长度结构,减少了网络的通信能量和网络资源。仿真结果验证了该算法的收敛性。
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引用次数: 4
The Research of the Transition from Traditional AVC to Smart AVC 传统AVC向智能AVC过渡的研究
Pub Date : 2013-01-01 DOI: 10.1016/j.aasri.2013.10.002
Huizhong Xu , Xiaoqun Ding , Jing Shi , Guangyu Chen

This paper first describes the relationship between the smart grid and smart AVC. By some problems of the conventional AVC's practical application connecting with the actual situation of the current grid development, this paper points out that the traditional AVC is unable to adapt to the development needs of the current grid and the tendency of intelligent AVC development.Through the research and the comprehensive exposition of the embedded Smart AVC, including intelligent AVC's new features, it points out that the future development direction of the Smart AVC and some features needs.

本文首先阐述了智能电网与智能AVC的关系。本文结合当前电网发展的实际情况,通过传统AVC在实际应用中存在的一些问题,指出传统AVC已不能适应当前电网的发展需要和智能化AVC发展的趋势。通过对嵌入式智能AVC的研究和综合阐述,包括智能AVC的新特性,指出了智能AVC未来的发展方向和一些特性需求。
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引用次数: 0
A Mobile Chinese Calligraphic Training System Using Virtual Reality Technology 基于虚拟现实技术的移动中国书法训练系统
Pub Date : 2013-01-01 DOI: 10.1016/j.aasri.2013.10.079
Yingfei Wu , Zhenming Yuan , Dibin Zhou , Yizhou Cai

Traditional method to learn Chinese calligraphy needs long hour's practice and the practice process often makes learners feel boring. And learners cannot get instant evaluation result during training. In this paper we introduce a new mobile Chinese Calligraphic training system based on virtual reality. The system is inspired by the way of tradition way to learn calligraphy which includes three main steps: a) learning stroke order of character; b) copying writing; c) real writing. Firstly the system demonstrates the right stroke order of calligraphic character with 2D and 3D mode. Secondly learner can write on iPad screen to practice copying writing. Meanwhile the leaner's writing track will be captured and evaluated according the similarity. The result of user studies shows that our system can successfully guide learners to improve their writing skills and motive them to learn calligraphy.

传统的学习中国书法的方法需要长时间的练习,练习的过程往往使学习者感到无聊。学习者在训练过程中无法得到即时的评价结果。本文介绍了一种基于虚拟现实的移动书法训练系统。该系统受传统书法学习方法的启发,包括三个主要步骤:1)学习汉字笔画顺序;B)抄写;C)真正的写作。该系统首先在二维和三维两种模式下对书法汉字的右笔画顺序进行了演示。其次,学习者可以在iPad屏幕上书写,练习抄写。同时捕捉学习者的写作轨迹,并根据相似度进行评价。用户研究结果表明,该系统能够成功地引导学习者提高写作水平,激发学习者学习书法的积极性。
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引用次数: 17
Transparency Issues in a Hybrid Reasoning Architecture for Assistive Healthcare 辅助医疗保健混合推理体系结构中的透明度问题
Pub Date : 2013-01-01 DOI: 10.1016/j.aasri.2013.10.040
Bingchuan Yuan, John Herbert

When pervasive computing is used to provide technology-driven assistive healthcare, there is a need for the system to be as sophisticated and adaptable as possible, while also being as transparent as possible for both subject and caregivers. A personalized, extensible hybrid reasoning framework has been implemented for the CARA (Context Aware Real-time Assistant) system which aims to satisfy these design goals. It provides context-aware sensor data fusion (including medical and environmental sensors) and incorporates anomaly detection mechanisms that support Activity of Daily Living (ADL) analysis and alert generation. The hybrid reasoning architecture incorporates both rule-based and case-based reasoning; this enables CARA to be more robust and to adapt to a changing environment by continuously retraining with new cases. The rules used for anomaly detection in a smart-home situation are given in a structured natural language, allowing subject or caregiver to inspect and, if appropriate, modify these rules; this supports the goal of transparency. For the case-based reasoning part, attention is drawn to the transparency issues that arise in the evaluation criteria used and interpretation of results.

当使用普适计算来提供技术驱动的辅助医疗保健时,系统需要尽可能复杂和适应性强,同时对受试者和护理人员都要尽可能透明。为了满足这些设计目标,为CARA(上下文感知实时助手)系统实现了一个个性化的、可扩展的混合推理框架。它提供上下文感知传感器数据融合(包括医疗和环境传感器),并集成了支持日常生活活动(ADL)分析和警报生成的异常检测机制。混合推理体系结构结合了基于规则和基于案例的推理;这使得CARA更加强大,并通过不断地对新案例进行再培训来适应不断变化的环境。在智能家居环境中用于异常检测的规则以结构化的自然语言给出,允许受试者或护理人员检查并在适当时修改这些规则;这支持了透明度的目标。对于基于案例的推理部分,注意在使用的评估标准和结果解释中出现的透明度问题。
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引用次数: 3
A Reputation-based Collaborative Approach for Spam Filtering 基于声誉的垃圾邮件过滤协同方法
Pub Date : 2013-01-01 DOI: 10.1016/j.aasri.2013.10.082
Wenxuan Shi , Maoqiang Xie

Spam and spam filters are contrarious components of a complex interdependent social ecosystem. Traditional spam filtering techniques or systems are usually designed and deployed individually that neglect the distributed and bulk characteristics of spam. This paper proposes a reputation-based collaborative anti-spam approach. This approach, adopting fingerprinting technique, evaluating reporters’ trust, achieved better performance and robustness than the state-of-the-art in comparison experiments on several known email corpora.

垃圾邮件和垃圾邮件过滤器是复杂的相互依赖的社会生态系统中相互矛盾的组成部分。传统的垃圾邮件过滤技术或系统通常是单独设计和部署的,忽略了垃圾邮件的分布式和批量特征。本文提出了一种基于信誉的协同反垃圾邮件方法。在几个已知的电子邮件语料库的对比实验中,该方法采用指纹技术来评估记者的信任,取得了比现有方法更好的性能和鲁棒性。
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引用次数: 9
The Method of Distribute Data Storage and Location on Weights of Jump Table 基于跳转表权值的分布式数据存储和定位方法
Pub Date : 2013-01-01 DOI: 10.1016/j.aasri.2013.10.067
Bi-lin Shao , Gen-qing Bian , Wei-qi Zhang

Focusing on the existing location technology limited the performance of the algorithm, distributed data location strategies DLPSL based on weights of jump table is presented to solve the efficiency problem. Weights are added to nodes of jump table, so that the high rate of location of the storage node priority is found to short the search path, and improve the storage and location efficiency. System analysis shows that, the node's insertion, deleting, and location on DLPSL are more efficient than single-linked list storage structure and skip graphic. Its time complexity is 0(log n), and space complexity is 0(n).

针对现有定位技术对算法性能的限制,提出了基于跳表权值的分布式数据定位策略DLPSL来解决算法的效率问题。对跳表节点增加权值,找到优先级较高的存储节点,缩短搜索路径,提高存储和定位效率。系统分析表明,节点在DLPSL上的插入、删除和定位比单链表存储结构和跳图更高效。其时间复杂度为0(log n),空间复杂度为0(n)。
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引用次数: 3
Large Distributed Arabic Handwriting Recognition System based on the Combination of FastDTW Algorithm and Map-reduce Programming Model via Cloud Computing Technologies 基于FastDTW算法和基于云计算的Map-reduce编程模型相结合的大型分布式阿拉伯手写识别系统
Pub Date : 2013-01-01 DOI: 10.1016/j.aasri.2013.10.072
Hamdi Hassen , Maher Khemakhem

This paper proposes a robust, efficient and scalable distributed Arabic handwriting OCR system based on a parallel FastDTW algorithm via cloud computing technologies. The three techniques Hadoop, MapReduce and Cascading are used to implement the parallel FastDTW algorithm. The experiments were deployed on Amazon EC2 Elastic Map Reduce and Amazon Simple Storage Service (S3) using a large scaled dataset built from the IFN/ENIT database.

基于并行FastDTW算法,利用云计算技术,提出了一种鲁棒、高效、可扩展的分布式阿拉伯手写OCR系统。采用Hadoop、MapReduce和Cascading三种技术实现并行FastDTW算法。实验部署在Amazon EC2 Elastic Map Reduce和Amazon Simple Storage Service (S3)上,使用从IFN/ENIT数据库构建的大型数据集。
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引用次数: 1
Computational Exploration of Theme-based Blog Data Using Topic Modeling, NERC and Sentiment Classifier Combine 结合主题建模、NERC和情感分类器的主题博客数据计算探索
Pub Date : 2013-01-01 DOI: 10.1016/j.aasri.2013.10.033
V.K. Singh , P. Waila , R. Piryani , A. Uddin

This paper presents findings of our exploratory research work on a novel combine of Topic Modeling, Named Entity Recognition and Sentiment Classification for sociological analysis of blog data. We have collected more than 500 blog posts on the broader theme of ‘Discrimination, Abuse and Crime against Women’. We employed topic discovery to identify top keywords and key themes and implemented the 7-entity model Named Entity Recognition process to identify the key persons, organizations and locations discussed in the blog posts. Thereafter we performed sentiment classification of the entire blog data into positive and negative categories using SentiWordNet. The results obtained are very interesting and validate the usefulness of our approach for computational analysis of social media data. The key contribution of the paper is to propose a novel Text Analytics combine and demonstrate its applicability for computational exploration of the social media data for sociological analysis purposes.

本文介绍了我们将主题建模、命名实体识别和情感分类结合起来进行博客数据社会学分析的探索性研究成果。我们收集了500多篇关于“对妇女的歧视、虐待和犯罪”这一更广泛主题的博客文章。我们使用主题发现来识别关键字和关键主题,并实施7实体模型命名实体识别流程来识别博客文章中讨论的关键人物、组织和地点。然后,我们使用SentiWordNet对整个博客数据进行情绪分类,分为积极和消极两类。获得的结果非常有趣,并验证了我们的方法在社交媒体数据计算分析中的实用性。本文的关键贡献是提出了一种新的文本分析组合,并展示了其在社会学分析目的的社交媒体数据计算探索中的适用性。
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引用次数: 2
Qualities of Interest for Spontaneous Networked Organizations 自发网络组织的兴趣性质
Pub Date : 2013-01-01 DOI: 10.1016/j.aasri.2013.10.019
Saad Alqithami, Henry Hexmoor

In spontaneous networked organizations, or any dynamic open organizations, autonomous agents must interact among themselves to achieve their goals. Agents usually interact, with which they have no experience, due to the scale and dynamism in these organizations. Each agent must, therefore, achieve certain qualities of interests in order to be capable of amalgamating fast. In light of this, we construct qualities of interest for a spontaneous networked organization. Theoretical aspects will be described including social harmony, coherence and spontaneity and their effect on the interaction process among agents inside such a collaborative organization. This study helps to improve the social capital of any networked organization.

在自发的网络组织或任何动态的开放组织中,自治代理必须相互作用以实现其目标。由于这些组织的规模和活力,代理通常与他们没有经验的人进行交互。因此,为了能够快速合并,每个代理人必须达到一定的利益品质。鉴于此,我们为一个自发的网络化组织构建了感兴趣的品质。理论方面将描述包括社会和谐,连贯性和自发性及其对这样一个协作组织内的代理人之间的互动过程的影响。本研究有助于提高任何网络化组织的社会资本。
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引用次数: 1
期刊
AASRI Procedia
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