期刊文献+
共找到56篇文章
< 1 2 3 >
每页显示 20 50 100
A Model Transformation Approach for Detecting Distancing Violations in Weighted Graphs
1
作者 Ahmad F.Subahi 《Computer Systems Science & Engineering》 SCIE EI 2021年第1期13-39,共27页
This work presents the design of an Internet of Things(IoT)edge-based system based on model transformation and complete weighted graph to detect violations of social distancing measures in indoor public places.Awirele... This work presents the design of an Internet of Things(IoT)edge-based system based on model transformation and complete weighted graph to detect violations of social distancing measures in indoor public places.Awireless sensor network based on Bluetooth Low Energy is introduced as the infrastructure of the proposed design.A hybrid model transformation strategy for generating a graph database to represent groups of people is presented as a core middleware layer of the detecting system’s proposed architectural design.A Neo4j graph database is used as a target implementation generated from the proposed transformational system to store all captured real-time IoT data about the distances between individuals in an indoor area and answer user predefined queries,expressed using Neo4j Cypher,to provide insights from the stored data for decision support.As proof of concept,a discrete-time simulation model was adopted for the design of a COVID-19 physical distancing measures case study to evaluate the introduced system architecture.Twenty-one weighted graphs were generated randomly and the degrees of violation of distancing measures were inspected.The experimental results demonstrate the capability of the proposed system design to detect violations of COVID-19 physical distancing measures within an enclosed area. 展开更多
关键词 model-driven engineering(MDE) Internet-of-Things(IoTs) model transformation edge computing system design Neo4j graph databases
下载PDF
Classification of Conversational Sentences Using an Ensemble Pre-Trained Language Model with the Fine-Tuned Parameter
2
作者 R.Sujatha K.Nimala 《Computers, Materials & Continua》 SCIE EI 2024年第2期1669-1686,共18页
Sentence classification is the process of categorizing a sentence based on the context of the sentence.Sentence categorization requires more semantic highlights than other tasks,such as dependence parsing,which requir... Sentence classification is the process of categorizing a sentence based on the context of the sentence.Sentence categorization requires more semantic highlights than other tasks,such as dependence parsing,which requires more syntactic elements.Most existing strategies focus on the general semantics of a conversation without involving the context of the sentence,recognizing the progress and comparing impacts.An ensemble pre-trained language model was taken up here to classify the conversation sentences from the conversation corpus.The conversational sentences are classified into four categories:information,question,directive,and commission.These classification label sequences are for analyzing the conversation progress and predicting the pecking order of the conversation.Ensemble of Bidirectional Encoder for Representation of Transformer(BERT),Robustly Optimized BERT pretraining Approach(RoBERTa),Generative Pre-Trained Transformer(GPT),DistilBERT and Generalized Autoregressive Pretraining for Language Understanding(XLNet)models are trained on conversation corpus with hyperparameters.Hyperparameter tuning approach is carried out for better performance on sentence classification.This Ensemble of Pre-trained Language Models with a Hyperparameter Tuning(EPLM-HT)system is trained on an annotated conversation dataset.The proposed approach outperformed compared to the base BERT,GPT,DistilBERT and XLNet transformer models.The proposed ensemble model with the fine-tuned parameters achieved an F1_score of 0.88. 展开更多
关键词 Bidirectional encoder for representation of transformer conversation ensemble model fine-tuning generalized autoregressive pretraining for language understanding generative pre-trained transformer hyperparameter tuning natural language processing robustly optimized BERT pretraining approach sentence classification transformer models
下载PDF
Test-driven verification/validation of model transformations
3
作者 Lfiszlo LENGYEL Hassan CHARAF 《Frontiers of Information Technology & Electronic Engineering》 SCIE EI CSCD 2015年第2期85-97,共13页
Why is it important to verify/validate model transformations? The motivation is to improve the quality of the trans- formations, and therefore the quality of the generated software artifacts. Verified/validated model... Why is it important to verify/validate model transformations? The motivation is to improve the quality of the trans- formations, and therefore the quality of the generated software artifacts. Verified/validated model transformations make it possible to ensure certain properties of the generated software artifacts. In this way, verification/validation methods can guarantee different requirements stated by the actual domain against the generated/modified/optimized software products. For example, a verified/ validated model transformation can ensure the preservation of certain properties during the model-to-model transformation. This paper emphasizes the necessity of methods that make model transformation verified/validated, discusses the different scenarios of model transformation verification and validation, and introduces the principles of a novel test-driven method for verifying/ validating model transformations. We provide a solution that makes it possible to automatically generate test input models for model transformations. Furthermore, we collect and discuss the actual open issues in the field of verification/validation of model transformations. 展开更多
关键词 Graph rewriting based model transformations Verification/validation Test-driven verification
原文传递
Pragmatic model transformations for refactoring in Scilab/Xcos
4
作者 Umut Durak 《International Journal of Modeling, Simulation, and Scientific Computing》 EI 2016年第1期39-61,共23页
Model-Based Development has become an industry wide standard paradigm.As an open source alternative,Scilab/Xcos is being widely employed as a hybrid dynamic systems modeling tool.With the increasing efficiency in impl... Model-Based Development has become an industry wide standard paradigm.As an open source alternative,Scilab/Xcos is being widely employed as a hybrid dynamic systems modeling tool.With the increasing efficiency in implementation using graphical model development and code generation,the modeling and simulation community is struggling with assuring quality as well as maintainability and extendibility.Refactoring is defined as an evolutionary modernization activity where,most of the time,the structure of the artifact is changed to alter its quality characteristics,while keeping its behavior unchanged.It has been widely established as a technique for textual programming languages to improve the code structure and quality.While refactoring is also regarded as one of the key practices of model engineering,the methodologies and approaches for model refactoring are still under development.Architecture-Driven Modernization(ADM)has been introduced by the software engineering community as a model-based approach to software modernization,in which the implicit information that lies in software artifacts is extracted to models and model transformations are applied for modernization tasks.Regarding refactoring as a low level modernization task,the practices from ADM are adaptable.Accordingly,this paper proposes a model-based approach for model refactoring in order to come up with more efficient and effective model refactoring methodology that is accessible and extendable by modelers.Like other graphical modeling tools,Scilab/Xcos also possesses a formalized model specification conforming to its implicit metamodel.Rather than proposing another metamodel for knowledge extraction,this pragmatic approach proposes to conduct in place model-to-model transformations for refactoring employing the Scilab/Xcos model specification.To construct a structured model-based approach,the implicit Scilab/Xcos metamodel is explicitly presented utilizing ECORE as a meta-metamodel.Then a practical model transformation approach is established based on Scilab scripting.A Scilab toolset is provided to the modeler for in-place model-to-model transformations.Using a sample case study,it is demonstrated that proposed model transformation functions in Scilab provide a valuable refactoring tool. 展开更多
关键词 model refactoring Scilab/Xcos model engineering model transformations
原文传递
NC Machining of Spiral Bevel Gear and Hypoid Gear Based on Unity Transformation Model
5
作者 王太勇 邢元 +1 位作者 赵林 李清 《Transactions of Tianjin University》 EI CAS 2011年第4期264-269,共6页
A unity transformation model (UTM) was presented for flexible NC machining of spiral bevel gears and hypoid gears. The model can support various machining methods for Gleason spiral bevel gears and hypoid gears, inclu... A unity transformation model (UTM) was presented for flexible NC machining of spiral bevel gears and hypoid gears. The model can support various machining methods for Gleason spiral bevel gears and hypoid gears, including generation machining and formation machining for wheel or pinion on a universal five-axis machining center, and then directly produce NC codes for the selected machining method. Wheel machining and pinion machining under UTM were simulated in Vericut 6.0 and tested on a five-axis machining center TDNC-W2000 with NC unit TDNC-H8. The results from simulation and real-cut verify the feasibility of gear machining under UTM as well as the correctness of NC codes. 展开更多
关键词 spiral bevel gear NC machining unity transformation model
下载PDF
Micro-expression recognition algorithm based on graph convolutional network and Transformer model 被引量:1
6
作者 吴进 PANG Wenting +1 位作者 WANG Lei ZHAO Bo 《High Technology Letters》 EI CAS 2023年第2期213-222,共10页
Micro-expressions are spontaneous, unconscious movements that reveal true emotions.Accurate facial movement information and network training learning methods are crucial for micro-expression recognition.However, most ... Micro-expressions are spontaneous, unconscious movements that reveal true emotions.Accurate facial movement information and network training learning methods are crucial for micro-expression recognition.However, most existing micro-expression recognition technologies so far focus on modeling the single category of micro-expression images and neural network structure.Aiming at the problems of low recognition rate and weak model generalization ability in micro-expression recognition, a micro-expression recognition algorithm is proposed based on graph convolution network(GCN) and Transformer model.Firstly, action unit(AU) feature detection is extracted and facial muscle nodes in the neighborhood are divided into three subsets for recognition.Then, graph convolution layer is used to find the layout of dependencies between AU nodes of micro-expression classification.Finally, multiple attentional features of each facial action are enriched with Transformer model to include more sequence information before calculating the overall correlation of each region.The proposed method is validated in CASME II and CAS(ME)^2 datasets, and the recognition rate reached 69.85%. 展开更多
关键词 micro-expression recognition graph convolutional network(GCN) action unit(AU)detection Transformer model
下载PDF
Asymptotic Efficiency of the Maximum Likelihood Estimator for the Box-Cox Transformation Model with Heteroscedastic Disturbances
7
作者 Kazumitsu Nawata 《Open Journal of Statistics》 2016年第5期835-841,共8页
This paper considers the asymptotic efficiency of the maximum likelihood estimator (MLE) for the Box-Cox transformation model with heteroscedastic disturbances. The MLE under the normality assumption (BC MLE) is a con... This paper considers the asymptotic efficiency of the maximum likelihood estimator (MLE) for the Box-Cox transformation model with heteroscedastic disturbances. The MLE under the normality assumption (BC MLE) is a consistent and asymptotically efficient estimator if the “small ” condition is satisfied and the number of parameters is finite. However, the BC MLE cannot be asymptotically efficient and its rate of convergence is slower than ordinal order when the number of parameters goes to infinity. Anew consistent estimator of order is proposed. One important implication of this study is that estimation methods should be carefully chosen when the model contains many parameters in actual empirical studies. 展开更多
关键词 Maximum Likelihood Estimator (MLE) Asymptotic Efficiency Box-Cox transformation model HETEROSCEDASTICITY
下载PDF
Implementation of Rapid Code Transformation Process Using Deep Learning Approaches
8
作者 Bao Rong Chang Hsiu-Fen Tsai Han-Lin Chou 《Computer Modeling in Engineering & Sciences》 SCIE EI 2023年第7期107-134,共28页
Our previous work has introduced the newly generated program using the code transformation model GPT-2,verifying the generated programming codes through simhash(SH)and longest common subsequence(LCS)algo-rithms.Howeve... Our previous work has introduced the newly generated program using the code transformation model GPT-2,verifying the generated programming codes through simhash(SH)and longest common subsequence(LCS)algo-rithms.However,the entire code transformation process has encountered a time-consuming problem.Therefore,the objective of this study is to speed up the code transformation process signi􀀀cantly.This paper has proposed deep learning approaches for modifying SH using a variational simhash(VSH)algorithm and replacing LCS with a piecewise longest common subsequence(PLCS)algorithm to faster the veri􀀀cation process in the test phase.Besides the code transformation model GPT-2,this study has also introduced MicrosoMASS and Facebook BART for a comparative analysis of their performance.Meanwhile,the explainable AI technique using local interpretable model-agnostic explanations(LIME)can also interpret the decision-making ofAImodels.The experimental results show that VSH can reduce the number of quali􀀀ed programs by 22.11%,and PLCS can reduce the execution time of selected pocket programs by 32.39%.As a result,the proposed approaches can signi􀀀cantly speed up the entire code transformation process by 1.38 times on average compared with our previous work. 展开更多
关键词 Code transformation model variational simhash piecewise longest common subsequence explainable AI LIME
下载PDF
A Deep Learning Ensemble Method for Forecasting Daily Crude Oil Price Based on Snapshot Ensemble of Transformer Model
9
作者 Ahmed Fathalla Zakaria Alameer +1 位作者 Mohamed Abbas Ahmed Ali 《Computer Systems Science & Engineering》 SCIE EI 2023年第7期929-950,共22页
The oil industries are an important part of a country’s economy.The crude oil’s price is influenced by a wide range of variables.Therefore,how accurately can countries predict its behavior and what predictors to emp... The oil industries are an important part of a country’s economy.The crude oil’s price is influenced by a wide range of variables.Therefore,how accurately can countries predict its behavior and what predictors to employ are two main questions.In this view,we propose utilizing deep learning and ensemble learning techniques to boost crude oil’s price forecasting performance.The suggested method is based on a deep learning snapshot ensemble method of the Transformer model.To examine the superiority of the proposed model,this paper compares the proposed deep learning ensemble model against different machine learning and statistical models for daily Organization of the Petroleum Exporting Countries(OPEC)oil price forecasting.Experimental results demonstrated the outperformance of the proposed method over statistical and machine learning methods.More precisely,the proposed snapshot ensemble of Transformer method achieved relative improvement in the forecasting performance compared to autoregressive integrated moving average ARIMA(1,1,1),ARIMA(0,1,1),autoregressive moving average(ARMA)(0,1),vector autoregression(VAR),random walk(RW),support vector machine(SVM),and random forests(RF)models by 99.94%,99.62%,99.87%,99.65%,7.55%,98.38%,and 99.35%,respectively,according to mean square error metric. 展开更多
关键词 Deep learning ensemble learning transformer model crude oil price
下载PDF
Vehicle Density Prediction in Low Quality Videos with Transformer Timeseries Prediction Model(TTPM)
10
作者 D.Suvitha M.Vijayalakshmi 《Computer Systems Science & Engineering》 SCIE EI 2023年第1期873-894,共22页
Recent advancement in low-cost cameras has facilitated surveillance in various developing towns in India.The video obtained from such surveillance are of low quality.Still counting vehicles from such videos are necess... Recent advancement in low-cost cameras has facilitated surveillance in various developing towns in India.The video obtained from such surveillance are of low quality.Still counting vehicles from such videos are necessity to avoid traf-fic congestion and allows drivers to plan their routes more precisely.On the other hand,detecting vehicles from such low quality videos are highly challenging with vision based methodologies.In this research a meticulous attempt is made to access low-quality videos to describe traffic in Salem town in India,which is mostly an un-attempted entity by most available sources.In this work profound Detection Transformer(DETR)model is used for object(vehicle)detection.Here vehicles are anticipated in a rush-hour traffic video using a set of loss functions that carry out bipartite coordinating among estimated and information acquired on real attributes.Every frame in the traffic footage has its date and time which is detected and retrieved using Tesseract Optical Character Recognition.The date and time extricated and perceived from the input image are incorporated with the length of the recognized objects acquired from the DETR model.This furnishes the vehicles report with timestamp.Transformer Timeseries Prediction Model(TTPM)is proposed to predict the density of the vehicle for future prediction,here the regular NLP layers have been removed and the encoding temporal layer has been modified.The proposed TTPM error rate outperforms the existing models with RMSE of 4.313 and MAE of 3.812. 展开更多
关键词 Detection transformer self-attention tesseract optical character recognition transformer timeseries prediction model time encoding vector
下载PDF
HOSVD-based LPV modeling and mixed robust H_2/H_∞ control design for air-breathing hypersonic vehicle 被引量:5
11
作者 Wei Jiang Hongli Wang +1 位作者 Jinghui Lu Zheng Xie 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2016年第1期183-191,共9页
This paper focuses on synthesizing a mixed robust H_2/H_∞ linear parameter varying(LPV) controller for the longitudinal motion of an air-breathing hypersonic vehicle via a high order singular value decomposition(H... This paper focuses on synthesizing a mixed robust H_2/H_∞ linear parameter varying(LPV) controller for the longitudinal motion of an air-breathing hypersonic vehicle via a high order singular value decomposition(HOSVD) approach.The design of hypersonic flight control systems is highly challenging due to the enormous complexity of the vehicle dynamics and the presence of significant uncertainties.Motivated by recent results on both LPV control and tensor-product(TP) model transformation approach,the velocity and altitude tracking control problems for the air-breathing hypersonic vehicle is reduced to that of a state feedback stabilizing controller design for a polytopic LPV system with guaranteed performances.The controller implementation is converted into a convex optimization problem with parameterdependent linear matrix inequalities(LMIs) constraints,which is intuitively tractable using LMI control toolbox.Finally,numerical simulation results demonstrate the effectiveness of the proposed approach. 展开更多
关键词 high order singular value decomposition(HOSVD) linear parameter varying(LPV) tensor product model transformation linear matrix inequality(LMI) air-breathing hypersonic vehicle
下载PDF
Formal Verification of TASM Models by Translating into UPPAAL 被引量:1
12
作者 胡凯 张腾 +3 位作者 杨志斌 顾斌 蒋树 姜泮昌 《Journal of Donghua University(English Edition)》 EI CAS 2012年第1期51-54,共4页
Timed abstract state machine(TASM) is a formal specification language used to specify and simulate the behavior of real-time systems. Formal verification of TASM model can be fulfilled through model checking activitie... Timed abstract state machine(TASM) is a formal specification language used to specify and simulate the behavior of real-time systems. Formal verification of TASM model can be fulfilled through model checking activities by translating into UPPAAL. Firstly, the translational semantics from TASM to UPPAAL is presented through atlas transformation language(ATL). Secondly, the implementation of the proposed model transformation tool TASM2UPPAAL is provided. Finally, a case study is given to illustrate the automatic transformation from TASM model to UPPAAL model. 展开更多
关键词 timed abstract state machine(TASM) formal verification model transformation atlas transformation language(ATL) UPPAAL
下载PDF
Research on transformation from UML statechart to interface automata 被引量:1
13
作者 李良明 Wang Zhijian Tang Longye 《High Technology Letters》 EI CAS 2010年第2期152-156,共5页
This paper studies the problem of deriving an interface automata model from UML statechart, in which, interface automata is a formaliged model for describing component behavior in an open system, but there is no unive... This paper studies the problem of deriving an interface automata model from UML statechart, in which, interface automata is a formaliged model for describing component behavior in an open system, but there is no universal criterion for deriving behavior from component to construct the model. UML is a widely used modeling standard, yet it is very difficult to apply it to system verification and testing directly for its imprecise semantics. After analyzing the expression ability of the two models, several transforma- tion rules are defined and each step of transformation is described in detail, after that, the approach is illustrated with an example. The paper provides a method for acquiring interface automata and lays the foundation for related research. 展开更多
关键词 model transformation interface automata (IA) UML stateehart
下载PDF
MoTransFrame:Model Transfer Framework for CNNs on Low-Resource Edge Computing Node
14
作者 Panyu Liu Huilin Ren +4 位作者 Xiaojun Shi Yangyang Li Zhiping Cai Fang Liu Huacheng Zeng 《Computers, Materials & Continua》 SCIE EI 2020年第12期2321-2334,共14页
Deep learning technology has been widely used in computer vision,speech recognition,natural language processing,and other related fields.The deep learning algorithm has high precision and high reliability.However,the ... Deep learning technology has been widely used in computer vision,speech recognition,natural language processing,and other related fields.The deep learning algorithm has high precision and high reliability.However,the lack of resources in the edge terminal equipment makes it difficult to run deep learning algorithms that require more memory and computing power.In this paper,we propose MoTransFrame,a general model processing framework for deep learning models.Instead of designing a model compression algorithm with a high compression ratio,MoTransFrame can transplant popular convolutional neural networks models to resources-starved edge devices promptly and accurately.By the integration method,Deep learning models can be converted into portable projects for Arduino,a typical edge device with limited resources.Our experiments show that MoTransFrame has good adaptability in edge devices with limited memories.It is more flexible than other model transplantation methods.It can keep a small loss of model accuracy when the number of parameters is compressed by tens of times.At the same time,the computational resources needed in the reasoning process are less than what the edge node could handle. 展开更多
关键词 Edge computing convolutional neural network model transformation model compression
下载PDF
AADL2TASM: a Verification and Analysis Tool for AADL Models
15
作者 蒋树 胡凯 +3 位作者 杨志斌 顾斌 张腾 姜泮昌 《Journal of Donghua University(English Edition)》 EI CAS 2012年第1期94-98,共5页
Architecture analysis and design language (AADL) is an architecture description language standard for embedded real-time systems and it is widely used in safety-critical applications. For facilitating verifcafion an... Architecture analysis and design language (AADL) is an architecture description language standard for embedded real-time systems and it is widely used in safety-critical applications. For facilitating verifcafion and analysis, model transformation is one of the methods. A synchronous subset of AADL and a general methodology for translating the AADL subset into timed abstract state machine (TASM) were studied. Based on the arias transformation language ( ATL ) framework, the associated translating tool AADL2TASM was implemented by defining the meta-model of both AADL and TASM, and the ATL transformation rules. A case study with property verification of the AADL model was also presented for validating the tool. 展开更多
关键词 architecture analysis and design language AADL timed abstract state machine TASM model transformation atlas transformation languaee( ATL
下载PDF
A Study on the Impact of Voice-to-Text Technology on Academic Achievement of the Hearing-Impaired
16
作者 Zhe Wang 《Journal of Contemporary Educational Research》 2024年第8期276-282,共7页
Hearing loss is a significant barrier to academic achievement,with hearing-impaired(HI)individuals often facing challenges in speech recognition,language development,and social interactions.Lip-reading,a crucial skill... Hearing loss is a significant barrier to academic achievement,with hearing-impaired(HI)individuals often facing challenges in speech recognition,language development,and social interactions.Lip-reading,a crucial skill for HI individuals,is essential for effective communication and learning.However,the COVID-19 pandemic has exacerbated the challenges faced by HI individuals,with the face masks hindering lip-reading.This literature review explores the relationship between hearing loss and academic achievement,highlighting the importance of lip-reading and the potential of artificial intelligence(AI)techniques in mitigating these challenges.The introduction of Voice-to-Text(VtT)technology,which provides real-time text captions,can significantly improve speech recognition and academic performance for HI students.AI models,such as Hidden Markov models and Transformer models,can enhance the accuracy and robustness of VtT technology in diverse educational settings.Furthermore,VtT technology can facilitate better teacher-student interactions,provide transcripts of lectures and classroom discussions,and bridge the gap in standardized testing performance between HI and hearing students.While challenges and limitations exist,the successful implementation of VtT technology can promote inclusive education and enhance academic achievement.Future research directions include popularizing VtT technology,addressing technological barriers,and customizing VtT systems to cater to individual needs. 展开更多
关键词 LIP-READING HEARING-IMPAIRED Voice-to-text Academic achievement Hidden Markov models Transformer models Inclusive education
下载PDF
Integrated Modelling of Microstructure Evolution and Mechanical Properties Prediction for Q&P Hot Stamping Process of Ultra‑High Strength Steel 被引量:3
17
作者 Yang Chen Huizhen Zhang +2 位作者 Johnston Jackie Tang Xianhong Han Zhenshan Cui 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2020年第3期160-173,共14页
High strength steel products with good ductility can be produced via Q&P hot stamping process,while the phase transformation of the process is more complicated than common hot stamping since two-step quenching and... High strength steel products with good ductility can be produced via Q&P hot stamping process,while the phase transformation of the process is more complicated than common hot stamping since two-step quenching and one-step carbon partitioning processes are involved.In this study,an integrated model of microstructure evolution relating to Q&P hot stamping was presented with a persuasively predicted results of mechanical properties.The transformation of diffusional phase and non-diffusional phase,including original austenite grain size individually,were considered,as well as the carbon partitioning process which affects the secondary martensite transformation temperature and the subsequent phase transformations.Afterwards,the mechanical properties including hardness,strength,and elongation were calculated through a series of theoretical and empirical models in accordance with phase contents.Especially,a modified elongation prediction model was generated ultimately with higher accuracy than the existed Mileiko’s model.In the end,the unified model was applied to simulate the Q&P hot stamping process of a U-cup part based on the finite element software LS-DYNA,where the calculated outputs were coincident with the measured consequences. 展开更多
关键词 Q&P hot stamping Phase transformation model Microstructure evolution Product properties prediction
下载PDF
Correlation of coordinate transformation parameters 被引量:1
18
作者 Du Lan Zhang Hanwei +1 位作者 Zhou Qingyong Wang Ruopu 《Geodesy and Geodynamics》 2012年第1期34-38,共5页
Coordinate transformation parameters between two spatial Cartesian coordinate systems can be solved from the positions of non-colinear corresponding points. Based on the characteristics of translation, rotation and zo... Coordinate transformation parameters between two spatial Cartesian coordinate systems can be solved from the positions of non-colinear corresponding points. Based on the characteristics of translation, rotation and zoom components of the transformation, the complete solution is divided into three steps. Firstly, positional vectors are regulated with respect to the centroid of sets of points in order to separate the translation compo- nents. Secondly, the scale coefficient and rotation matrix are derived from the regulated positions independent- ly and correlations among transformation model parameters are analyzed. It is indicated that this method is applicable to other sets of non-position data to separate the respective attributions for transformation parameters. 展开更多
关键词 coordinate transformation model Bursa model orthnormal matrix singular value decomposition (SVD) CORRELATION
下载PDF
Model Transformer Evaluation of High-Permeability Grain-Oriented Electrical Steels 被引量:1
19
作者 Masayoshi Ishida, Seiji Okabe, Takeshi Imamura and Michiro Komatsubara (Kawasaki Steel Corporation, Kurashiki 712-8511, Japan) 《Journal of Materials Science & Technology》 SCIE EI CAS CSCD 2000年第2期223-227,共5页
The dependence of transformer performance on the material properties was investigated using two laboratory-processed 0.23 mm thick grain-oriented electrical steels domain-refined with elec-trolytically etched grooves ... The dependence of transformer performance on the material properties was investigated using two laboratory-processed 0.23 mm thick grain-oriented electrical steels domain-refined with elec-trolytically etched grooves having different magnetic properties. The iron loss at 1.7 T, 50 Hz and the flux density at 800 A/m of material A were 0.73 W/kg and 1.89 T, respectively; and those of material B, 0.83 W/kg and 1.88 T. Model stacked and wound transformer core experiments using the tested materials exhibited performance well reflecting the material characteristics. In a three-phase stacked core with step-lap joints excited to 1.7 T, 50 Hz, the core loss, the exciting current and the noise level were 0.86 W/kg, 0.74 A and 52 dB, respectively, with material A; and 0.97 W/kg, 1.0 A and 54 dB with material B. The building factors for the core losses of the two materials were almost the same in both core configurations. The effect of higher harmonics on transformer performance was also investigated. 展开更多
关键词 model Transformer Evaluation of High-Permeability Grain-Oriented Electrical Steels
下载PDF
Bionic Attitude Transformation Combined with Closed Motion for a Free Floating Space Robot 被引量:1
20
作者 Zhanpeng Sun Yongjin Lu +1 位作者 Lixian Xu Liang Wang 《Journal of Beijing Institute of Technology》 EI CAS 2018年第1期118-126,共9页
In order to realize the small error attitude transformation of a free floating space robot,a new method of three degrees of freedom( DOF) attitude transformation was proposed for the space robot using a bionic joint... In order to realize the small error attitude transformation of a free floating space robot,a new method of three degrees of freedom( DOF) attitude transformation was proposed for the space robot using a bionic joint. A general kinematic model of the space robot was established based on the law of linear and angular momentum conservation. A combinational joint model was established combined with bionic joint and closed motion. The attitude transformation of planar,two DOF and three DOF is analyzed and simulated by the model,and it is verified that the feasibility of attitude transformation in three DOF space. Finally,the specific scheme of disturbance elimination in attitude transformation is presented and simulation results are obtained.Therefore,the range of application field of the bionic joint model has been expanded. 展开更多
关键词 double rigid bodies model bionic mechanism closed motion attitude transformation eliminating disturbance
下载PDF
上一页 1 2 3 下一页 到第
使用帮助 返回顶部