Prototypicality Gradient and Similarity Measure: A Semiotic-Based Approach Dedicated to Ontology Personalization

This paper introduces a new approach dedicated to the Ontology Personalization. Inspired by works in Cognitive Psychology, our work is based on a process which aims at capturing the user-sensitive relevance of the categorization process, that is the one which is really perceived by the end-user. Practically, this process consists in decorating the Specialization/Generalization links (i.e. the is-a links) of the hierarchy of concepts with 2 gradients. The goal of the first gradient, called Conceptual Prototypicality Gradient, is to capture the user-sensitive relevance of the categorization process, that is the one which is perceived by the end-user. As this gradient is defined according to the three aspects of the semiotic triangle (i.e. intentional, extensional and expressional dimension), we call it Semiotic based Prototypicality Gradient. The objective of the second gradient, called Lexical Prototypicality Gradient, is to capture the user-sensitive relevance of the lexicalization process, i.e. the definition of a set of terms used to denote a concept. These gradients enrich the initial formal semantics of an ontology by adding a pragmatics defined according to a context of use which depends on parameters like culture, educational background and/or emotional context of the end-user. This paper also introduces a new similarity measure also defined in the context of a semiotic-based approach. The first originality of this measure, called SEMIOSEM, is to consider the three semiotic dimensions of the conceptualization underlying an ontology. Thus, SEMIOSEM aims at aggregating and improving existing extensional-based and intentional-based measures. The second originality of this measure is to be context-sensitive, and in particular user-sensitive. This makes SEMIOSEM more flexible, more robust and more close to the end-user’s judgment than the other similarity measures which are usually only based on one aspect of a conceptualization and never take the end-user’s perceptions and purposes into account.

异构并行计算下高维混合型数据聚类算法研究

高维数据维度增加,数据空间的体积呈指数增长,容易陷入“维数灾难”,导致聚类算法执行效率低,为此,提出异构并行计算下高维混合型数据聚类算法。构建高维混合型数据相异度矩阵,提取高维混合型数据的统计序列特征值,利用时间窗口进行特征优化。采用K⁃Prototypes聚类算法提取高维混合型数据的统计序列特征,评估数据与类中心的相异性,计算数据与类中心的欧氏距离,实现高维混合型数据聚类。采用异构并行计算技术进行高维混合型数据K⁃Prototypes聚类的并行化处理,合理分配CPU与GPU工作,达到CPU与GPU的工作负载平衡,提高K⁃Prototypes的聚类效率。实验结果表明,此算法对于高维混合型数据的聚类效果好、运行时间短、性能稳定。

An Integrated Control Framework for Torque Vectoring and Active Suspension System

Four-wheel independently driven electric vehicles(FWID-EV)endow a flexible and scalable control framework to improve vehicle performance.This paper integrates the torque vectoring and active suspension system(ASS)to enhance the vehicle’s longitudinal and vertical motion control performance.While the nonlinear characteristic of the tire model leads to a relatively heavier computational burden.To facilitate the controller design and ease the load,a half-vehicle dynamics system is built and simplified to the linear-time-varying(LTV)model.Then a model predictive controller is developed by formulating the objective function by comprehensively considering the safety,energy-saving and comfort requirements.The in-wheel motor efficiency and the power loss of tire slip are treated as optimization indices in this work to reduce energy consumption.Finally,the effectiveness of the proposed controller is verified through the rapid-control-prototype(RCP)test.The results demonstrate the enhancement of the energy-saving as well as comfort on the basis of vehicle stability.

Theoretical and experimental investigations on an X-shaped vibration isolator with active controlled variable stiffness

A novel X-shaped variable stiffness vibration isolator(X-VSVI)is proposed.The Runge-Kutta method,harmonic balance method,and wavelet transform spectra are introduced to evaluate the performance of the X-VSVI under various excitations.The layer number,the installation angle of the X-shaped structure,the stiffness,and the active control parameters are systematically analyzed.In addition,a prototype of the X-VSVI is manufactured,and vibration tests are carried out.The results show that the proposed X-VSVI has a superior adaptability to that of a traditional X-shaped mechanism,and shows excellent vibration isolation performance in response to different amplitudes and forms of excitations.Moreover,the vibration isolation efficiency of the device can be improved by appropriate adjustment of parameters.

Model-free Speed Control of Single-phase Flux Switching Motor with an Asymmetrical Rotor

This paper proposes and implements a model-free open-loop iterative learning control(ILC)strategy to realize the speed control of the single-phase flux switching motor(FSM)with an asymmetrical rotor.Base on the proposed winding control method,the asymmetrical rotor enables the motor to generate continuous positive torque for positive rotation,and relatively small resistance torque for negative rotation.An initial iteration coefficient and variable iteration coefficient optimized scheme was proposed based on the characteristics of the hardware circuit,thereby forming the model-free strategy.A series of prototype experiments was carried out.Experimental results verify the effectiveness and practicability of the proposed ILC strategy.

Winding Function Model-based Performance Evaluation of a PM Transverse Flux Generator for Applications in Direct-drive Systems

The magnetic flux in a permanent magnet transverse flux generator(PMTFG) is three-dimensional(3D), therefore, its efficacy is evaluated using 3D magnetic field analysis. Although the 3D finite-element method(FEM) is highly accurate and reliable for machine simulation, it requires a long computation time, which is crucial when it is to be used in an iterative optimization process. Therefore, an alternative to 3DFEM is required as a rapid and accurate analytical technique. This paper presents an analytical model for PMTFG analysis using winding function method. To obtain the air gap MMF distribution, the excitation magneto-motive force(MMF) and the turn function are determined based on certain assumptions. The magnetizing inductance, flux density, and back-electro-magnetomotive force of the winding are then determined. To assess the accuracy of the proposed method, the analytically calculated parameters of the generator are compared to those obtained by a 3D-FEM. The presented method requires significantly shorter computation time than the 3D-FEM with comparable accuracy.

Few-shot image recognition based on multi-scale features prototypical network

In order to improve the models capability in expressing features during few-shot learning,a multi-scale features prototypical network(MS-PN)algorithm is proposed.The metric learning algo-rithm is employed to extract image features and project them into a feature space,thus evaluating the similarity between samples based on their relative distances within the metric space.To sufficiently extract feature information from limited sample data and mitigate the impact of constrained data vol-ume,a multi-scale feature extraction network is presented to capture data features at various scales during the process of image feature extraction.Additionally,the position of the prototype is fine-tuned by assigning weights to data points to mitigate the influence of outliers on the experiment.The loss function integrates contrastive loss and label-smoothing to bring similar data points closer and separate dissimilar data points within the metric space.Experimental evaluations are conducted on small-sample datasets mini-ImageNet and CUB200-2011.The method in this paper can achieve higher classification accuracy.Specifically,in the 5-way 1-shot experiment,classification accuracy reaches 50.13%and 66.79%respectively on these two datasets.Moreover,in the 5-way 5-shot ex-periment,accuracy of 66.79%and 85.91%are observed,respectively.

Unknown DDoS Attack Detection with Fuzzy C-Means Clustering and Spatial Location Constraint Prototype Loss

Since its inception,the Internet has been rapidly evolving.With the advancement of science and technology and the explosive growth of the population,the demand for the Internet has been on the rise.Many applications in education,healthcare,entertainment,science,and more are being increasingly deployed based on the internet.Concurrently,malicious threats on the internet are on the rise as well.Distributed Denial of Service(DDoS)attacks are among the most common and dangerous threats on the internet today.The scale and complexity of DDoS attacks are constantly growing.Intrusion Detection Systems(IDS)have been deployed and have demonstrated their effectiveness in defense against those threats.In addition,the research of Machine Learning(ML)and Deep Learning(DL)in IDS has gained effective results and significant attention.However,one of the challenges when applying ML and DL techniques in intrusion detection is the identification of unknown attacks.These attacks,which are not encountered during the system’s training,can lead to misclassification with significant errors.In this research,we focused on addressing the issue of Unknown Attack Detection,combining two methods:Spatial Location Constraint Prototype Loss(SLCPL)and Fuzzy C-Means(FCM).With the proposed method,we achieved promising results compared to traditional methods.The proposed method demonstrates a very high accuracy of up to 99.8%with a low false positive rate for known attacks on the Intrusion Detection Evaluation Dataset(CICIDS2017)dataset.Particularly,the accuracy is also very high,reaching 99.7%,and the precision goes up to 99.9%for unknown DDoS attacks on the DDoS Evaluation Dataset(CICDDoS2019)dataset.The success of the proposed method is due to the combination of SLCPL,an advanced Open-Set Recognition(OSR)technique,and FCM,a traditional yet highly applicable clustering technique.This has yielded a novel method in the field of unknown attack detection.This further expands the trend of applying DL and ML techniques in the development of intrusion detection systems and cybersecurity.Finally,implementing the proposed method in real-world systems can enhance the security capabilities against increasingly complex threats on computer networks.

The Advertisement Translation Based on the Prototype Theory

Based on the Prototype Theory,the prototypical feature of advertisement is found to be the combination of three language functions:the informative function,the expressive function,and the vocative function.The advertisement translation means the adjustment of the informative function and the expressive function according to the differences between languages or cultures in order to maximize the vocative function.The faithful translation is the closest to the prototype of the source text but not necessarily the best translation.

Rapid Prototype Development Approach for Genetic Programming

Genetic Programming (GP) is an important approach to deal with complex problem analysis and modeling, and has been applied in a wide range of areas. The development of GP involves various aspects, including design of genetic operators, evolutionary controls and implementations of heuristic strategy, evaluations and other mechanisms. When designing genetic operators, it is necessary to consider the possible limitations of encoding methods of individuals. And when selecting evolutionary control strategies, it is also necessary to balance search efficiency and diversity based on representation characteristics as well as the problem itself. More importantly, all of these matters, among others, have to be implemented through tedious coding work. Therefore, GP development is both complex and time-consuming. To overcome some of these difficulties that hinder the enhancement of GP development efficiency, we explore the feasibility of mutual assistance among GP variants, and then propose a rapid GP prototyping development method based on πGrammatical Evolution (πGE). It is demonstrated through regression analysis experiments that not only is this method beneficial for the GP developers to get rid of some tedious implementations, but also enables them to concentrate on the essence of the referred problem, such as individual representation, decoding means and evaluation. Additionally, it provides new insights into the roles of individual delineations in phenotypes and semantic research of individuals.

The Role and Place of Artificial Neural Network Architectures Structural Redundancy in the Input Data Prototypes and Generalization Development

Neural Networks (NN) are the functional unit of Deep Learning and are known to mimic the behavior of the human brain to solve complex data-driven problems. Whenever we train our own neural networks, we need to take care of something called the generalization of the neural network. The performance of Artificial Neural Networks (ANN) mostly depends upon its generalization capability. In this paper, we propose an innovative approach to enhance the generalization capability of artificial neural networks (ANN) using structural redundancy. A novel perspective on handling input data prototypes and their impact on the development of generalization, which could improve to ANN architectures accuracy and reliability is described.

混合属性数据聚类初始点选择的改进

k-prototypes和模糊k-prototypes是处理数值属性和分类属性混合数据主要的聚类算法。但这两种聚类算法不足之处是对初值有明显的依赖。对初值选取方法进行了分析和研究,提出一种新的改进方法,可在一定程度上减少随机性。实际数据集仿真结果表明改进算法有更高的稳定性和较强的伸缩性。

Efficient channelized technology based on filter banks

With the appearance of novel radar signal with low intercept probability, the bandwidth of radar receiver is wider and wider. Wideband digital receiver becomes a research hotspot in the field of communication, radar and electronic reconnaissance, etc. As one of wideband digital receiver systems, digital channelized receiver has become a research emphasis due to the characteristics of full probability receiving and processing multiple signals. Digital channelized technology and signal sampling theory are deeply studied and an efficient channelized model is derived based on filter banks. The correctness of the model is verified by computer simulation The model has less computation compared with the traditional model, which is suitable for engineering application

隔膜泵动力端虚拟样机的计算机仿真研究与验证（英文）

采用Pro/e软件进行隔膜泵动力端-曲柄滑块机构的三维建模,利用机械系统动力学仿真软件ADAMS构建虚拟样机,通过样机仿真确定隔膜泵曲柄滑块机构的运动学和动力学参数,为隔膜泵动力端的设计打下基础。

PARAMETERIZED-PROTOTYPE-BASED DYNAMIC OPTIMIZATION DESIGN FOR CAM PROFILE

Aiming at the problems in current cam profile optimization processes, such as simple dynamics models, limited geometric accuracy and low design automatization level, a new dynamic optimization mode is put forward. Based on the parameterization modeling technique of MSC. ADAMS platform, the different steps in current mode are reorganized, thus obtaining an upgraded mode called the ＂parameterized-prototype-based cam profile dynamic optimization mode＂. A parameterized prototype（PP） of valve mechanism is constructed in the course of dynamic optimization for cam profiles. Practically, by utilizing PP and considering the flexibility of the parts in valve mechanism, geometric accuracy and design automatization are improved.

Experimental Investigation on Basic Prototype of Solid Propellant Impulsive Microthrusters

A new type of impulsive microthruster and its measurement system were designed for the aim of testing the performance of a basic prototype of solid propellant impulsive microthruster. Two sets of tests were conducted. The tests show that the ignitor and the main charge of the microthruster match well, the dynamic and static capability of the test and measurement meets the test requirement and the result is creditable. The measured technical characteristics of the microthruster are that the ignition delay time is shorter than 0 3?ms, the total impulse is over 3?N·s, the operational time is shorter than 16?ms and the mass ratio of the thruster is 0 216.

信息安全评估日志数据的一种混合聚类算法

首先引入能够处理混合型数据的K-prototypes聚类算法,在此基础上构造了一种基于粒子群优化算法和K-prototypes方法的混合聚类算法.利用粒子群优化算法良好的全局搜索能力,克服K-prototypes容易陷入局部最优值的不足.实验结果表明,该算法能够避免陷入局部最优值,具有较好的全局收敛性,并且提高了聚类的正确率和算法的稳定性.

基于Ajax on Rails的WebGIS应用

运用目前两种炙手可热的Web开发技术:AJAX和Ruby on Rails为WebGIS提供一个新的解决方案,AJAX技术作为一种新兴的网络技术比传统页面刷新模式具有更好的性能和友好的用户体验,不过在建立大量的Javascript的代码基础上的,本文通过对AJAX on Rails原理进行分析,运用Ruby on Rails的动态性和敏捷性使AJAX模式带来的程序量大、首页加载时间长的缺陷得到改善,进一步提高程序性能。在实现环节上,在该平台上结合使用Google Maps API,以GXmlHttp在Rails上实现了AJAX的WebGIS关键应用。

基于Rifidi平台下的一种RFID端到端解决方案

RFID是一项无线电频率识别技术,使软件系统可以自动的探测和识别在现实中的物体。由于这种能力,RFID受到很多公司的热捧;可惜的是涉及到RFID一个新的业务的发展的投资方案,需要在时间、硬件和基础设施方面的重大投资。相反,Rifidi是一个工具,能够迅速和切实地进行RFID情景模拟,以探讨其发展的可能性在进行投资之前。而Prototyper是一款基于RifidiEmulator的仿真软件,仿真阅读器可以被创建并被放置在一个代表工厂和仓库的蓝图上,而且各种被创建的标签可以随意的拖动,远离或接近热点。这将会使你更容易地测试工作流程和业务逻辑,而不需要昂贵的硬件设置。任何问题都可以在这款软件上发现,并得以纠正。

北京奥运会徽“中国印”的认知解读

以"中国印,舞动的北京"作为主题的北京奥运会徽蕴含着浓重的中国韵味。它将中国特色、北京特点和奥林匹克运动元素巧妙地结合起来。文章试用认知语言学中的五个基本理论:原型(prototype)、图形-背景(figure-ground)、隐喻(metaphor)、象似性(iconicity)、语域(domain),对"中国印"进行全新视角分析,希望能够达到两个目的:一是帮助学生理解并熟悉掌握这些抽象的认知语言学概念;另一方面又可以加深读者对"中国印"蕴含的丰富含义的正确认知与理解。