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.

Rapid assembling organ prototypes with controllable cell-laden multi-scale sheets

A native organ has heterogeneous structures, sirength, and cell components. It is a big challenge to fabricate organ prototypes with controllable shapes, strength, and cells. Herein, a hybrid method is developed to fabricate organ prototypes with controlled cell deposition by integrating extrusion-based 3D printing, electrospinning, and 3D bioprinting. Multi-scale sheets were first fabricated by 3D printing and electrospinning;then, all the sheets were assembled into organ prototypes by sol-gel react io n duri ng bioprinting. With this method, macroscale structures fabricated by 3D printing ensure the customized structures and provide mechanical support, nanoscale structures fabricated by electrospinning offer a favorable environment for cell growth, and different types of cells with controllable densities are deposited in accurate locations by bioprinting. The results show that L929 mouse fibroblasts encapsulated in the structures exhibited over 90% survival within 10 days and maintai ned a high proliferation rate. Furthermore, the cells grew in spherical shapes first and then migrated to the nano scale fibers showing stretched morphology. Additionally, a branched vascular structure was successfully fabricated using the presented method. Compared with other methods, this strategy offers an easy way to simultancously realize the shape control, nanolibrous structures, and cell accurate deposition, which will have potemidi applications in tissue cngineering.

EFFECT OF TIME AND ENVIRONMENT ON THE DIMENSION PRECISION AND MASS OF LOM PROTOTYPES

The effect of time and environment on the dimension precision and mass of LOM prototypes was experimentally investigated.It is to identify the stability of the dimension of LOM prototypes after forming.The results show that the dimension and the mass tendency to grow,which is mainly caused by elastic recovery and moisture absorption and is characterized principally by the growth of Z dimension.Self restraint can be a significant factor to influence Z growth of LOM prototypes.

Prototypes and Vocabulary Teaching

The prototype theory suggests that many metal concepts we have are really prototypes.It claims that children first learn words that are "basic" because they reflect aspects of the world,prototypes, which stand out automatically from the rest of what they see.Basic level words should be taught first.

Improvement of the Fit of Bra Prototypes Developed Based on the Existing Bodice Blocks for Adult Women

An in-depth study of bra pattern designs based on the existing bodice blocks was conducted to improve bra fit.The two popular bra prototypes,D's and Y's prototypes developed based on the existing bodice blocks for adult women,were first analyzed to understand their structural differences.Four bra samples were created and modified with respect to the standard shape and size of 75 B female mannequin breasts to compare the fit of the two bra prototypes.The fitness of these four bra samples was then tested on the mannequin and also on a real model of the same size.The examples demonstrated in the paper illustrate the principles and procedures for designing good-fit bras,and the bodice blocks using to develop bra prototypes in this study can also be replaced and widespread applied in other kind of bodice blocks in the future.

Three-Dimensional Prototypes and Evaluation of Their Structure and Form

In order to reveal the appearance of the clothing prototype on the human body,the characteristics of the human body’s structure above the waist section were studied.Based on the experimental data of the fit prototype,three-dimensional prototypes features were comparatively analyzed.And then objectively evaluating the relationship was conducted between the planar structure lines of different prototypes and the human body.The results showed that the prototypes analyzed basically conformed to the size of the human body.However,when they were worn on the human body,there were problems in the structure and forming.The main reason was that the side seam was skewed to different degrees.The results of this study provide reference for many practitioners to choose prototypes.

On Prototypes from the Perspective of Semantics and Categorization

Cognitive linguistics is a new approach to language study, which can offer better explanation for language phenomena, and provide more theoretical instructions for English learning. In recent years, the prototype theory, as the cornerstone of cognitive linguistics, has been employed in different research fields, such as phonology, syntax, semantics, English teaching, etc..This thesis attempts to review and discuss the researches done so far on semantics and categorization based on a cognitive theory -- the prototype theory.

Safety Assessment of Ionic Liquid-Based Lithium-Ion Battery Prototypes

In this paper we report the results of combined cycle- and life-aging and abuse tests carried out under severe conditions on Li4Ti5O12/LiFePO4 lithium-ion stacked prototypes using a PYR14 FSI-LiTFSI ionic liquid electrolyte. No relevant degradation phenomena took place within ionic liquid electrolyte during prolonged inactivity period or overcharging. No fire/explosion or venting event as well as no gas development occurred during abuse tests, which led only to modest raise in temperature. Therefore, electrodes based on Li4Ti5O12 and LiFePO4 active materials can be favorably combined with non-volatile and non-flammable pyrrolidinium FSI ionic liquid electrolytes to realize highly safe lithium-ion battery systems.

Prototypes,modifications,and hydrocarbon enrichment variations in basins influenced by Tethyan evolution:A comparative analysis of the Persian Gulf Basin and the Sichuan Basin

The hydrocarbon accumulation modes and differences in the Tethyan realm serve as a hot research topic in the petroleum geology community at home and abroad.Both the Persian Gulf Basin in the Middle East and the Sichuan Basin in China,situated on the southern and northern sides of the Tethyan realm,respectively,record the whole geological process of the opening and closure of the Prototethys,the Paleotethys,and the Neotethys sequentially,exhibiting anomalous hydrocarbon enrichment.Based on the analysis of the plate tectonic evolution in the Tethyan realm,this study dissects the structures and hydrocarbon accumulation conditions of both basins.Followed by a systematic comparative analysis of the factors controlling hydrocarbon enrichment in the process of plate breakup and convergence in the Tethyan realm,this study proposes petroleum exploration targets in the realm.The results are as follows:(1)Since the Meso-Neoproterozoic,the Persian Gulf Basin and the Sichuan Basin have undergone similar tectonic evolution in the early stage but different in the late stage.Under the influence of the formation and evolution of the Prototethys,Paleotethys,and Neotethys oceans,both basins experienced multi-stage development and modification,forming two major extension-convergence cycles.Consequently,both basins are characterized by the vertical orderly superimposition of various basin prototypes in the order of rift-intracratonic basin(passive continental margin)-foreland.(2)The fact that the Tethyan realm was long located at medium-low latitudes and the local anoxic environment formed in the process of plate breakup and convergence played a vital role in the formation of extensive source rocks.The source rocks are predominantly distributed in underfilled rifts and deep depressions that were connected to the ocean in the unidirectional continental breakup process;basin-slopes and intra-shelf basins on passive continental margins;basinal lows within intracratonic basins,and underfilled foredeeps in foreland basins.The favorable areas for the formation of carbonate reservoirs include platform margins,submarine highs and paleo-uplifts within platforms,and fault zones.The evaporite cap rocks,intimately associated with the basin evolutionary stages and global dry-hot events,are critical for large-scale hydrocarbon preservation.(3)Under the influence of Tethyan evolution,the Persian Gulf Basin and the Sichuan Basin share similar primary factors controlling hydrocarbon enrichment.The moderate tectono-sedimentary differentiation and structural modification in the process of prototype basin superimposition,as well as the spatio-temporal matching of elements critical for hydrocarbon accumulation,are beneficial for the development of large oil and gas fields.The macroscopic hydrocarbon distribution is dictated by source rock-cap rock assemblages,while the local hydrocarbon distribution is governed by trap-reservoir assemblages.The critical factors determining the differential hydrocarbon enrichment in the Persian Gulf Basin and the Sichuan Basin include plate size and position,basement stability,eustatic movement,paleoclimate,and tectonic transformation.Besides,different tectonic modification intensities are closely related to the type,enrichment degree,and distribution of hydrocarbon reservoirs.

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。

CSNS Magnet System and Prototypes Fabrication

The 1.6GeV synchrotron of China Spallation Neutron Source(CSNS)project is a Rapid Cycling Synchrotron (RCS),which accelerates a high-intensity proton beam from 80MeV to 1.6GeV at a repetition rate of 25Hz.The RCS magnet system consists of 24 dipole magnets(main dipoles),48 quadrupole magnets(main quadrupoles),16 sextupole magnets,some tune shift quadrupoles and corrector magnets.All the magnets are of large aperture for a high beam power of 0.1MW,one design issue is the fringe field at pole end.And the main dipoles and main quadrupoles work at 25Hz repetition rate,the eddy current is an additional issue.In this paper the magnet design of the two kinds of main magnets will be described.

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.

Uncomfortable prototypes： Rethinking socio-cultural factors for the design of public housing in Billiri, north east Nigeria

Public housing delivery in developing countries often involves the provision of government- funded housing units. Over time, occupants transform such units to suit their changing needs or to increase and improve housing stock-a practice that has been the focus of several documented studies intended to inform policy makers about changing housing trends. Abandoned units have, however, received comparatively less attention. The present paper reports findings from the documentation and analyses of abandoned and modified prototype units in Billiri, the main town occupied by the Tangale community in north east Nigeria. The methodology involves space syntax methods, as well as the analyses of space use patterns in 45 randomly selected compounds built by the community and in two sets of prototype housing units in the study area. Results suggest that socio-cultural factors related to kinship, security, and basic needs, which form part of the community heritage, are inadequately reflected in the location and design of the units, accounting for their abandonment and modification. These findings have implications for future housing policies in the area.