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| 1 | 一个多功能机器人仿真软件V-REP显示文摘随着机器人技术的快速发展和机器人系统的多样化,机器人的仿真变得越来越复杂。介绍了一个多功能的、可扩展的通用机器人仿真软件V-REP。首先描述V-REP的整体框架,介绍软件中的实体和计算模块;其次介绍V-REP中仿真的控制方法;最后通过V-REP与MATLAB使用多种关节控制方法实现HOAP3机器人的仿真。 | 许浩燕 ABBA Gabriel 满庆丰 夏继强 | 2018 | 机械工程与自动化2018，0，2： | 7 |
| 2 | Drag reduction via turbulent boundary layer flow control显示文摘Turbulent boundary layer control(TBLC) for skin-friction drag reduction is a relatively new technology made possible through the advances in computational-simulation capabilities,which have improved the understanding of the flow structures of turbulence.Advances in micro-electronic technology have enabled the fabrication of active device systems able to manipulating these structures.The combination of simulation,understanding and micro-actuation technologies offers new opportunities to significantly decrease drag,and by doing so,to increase fuel efficiency of future aircraft.The literature review that follows shows that the application of active control turbulent skin-friction drag reduction is considered of prime importance by industry,even though it is still at a low technology readiness level(TRL).This review presents the state of the art of different technologies oriented to the active and passive control for turbulent skin-friction drag reduction and contributes to the improvement of these technologies. | ABBAS Adel BUGEDA Gabriel FERRER Esteban FU Song PERIAUX Jacques PONS-PRATS Jordi VALERO Eusebio ZHENG Yao | 2017 | Science China(Technological Sciences)2017，60，9： | 4 |
| 3 | Modeling and Robust control of winding systems for elasticwebs显示文摘 | Hakan Koc Dominique Knittel Michd de Mathelin Gabriel Abba | 2002 | IEEE Transactions on Control Systems Technology2002，2，10： | 1 |
| 4 | 微铣刀刀刃轨迹预测模型及影响因素分析显示文摘微铣削是一种柔性很强的微加工方法,可对多种材料进行微器件的加工.但由于微铣刀具有独特的几何特征,微铣削时的刀刃轨迹与传统意义上的铣削刀刃轨迹有明显区别.针对2刃微铣刀,开发了一个考虑刀具回转误差和转子振动效应的刀刃轨迹预测模型,并分析了其对加工过程的影响.同时提出了一种基于刀柄测量结果,计算刀尖回转误差和刀具装夹不平衡量的方法.将这两个结果输入刀刃轨迹模型后,可以准确地预测刀尖中心和两个刀刃的轨迹,并以此来计算即时切屑厚度、切削力、铣槽宽度(加工误差)和表面质量.实验结果很好地验证了模型的预测.分析结果表明,在微铣削过程中,单刃切削经常发生;刀刃角和进给角这两个模型参数对加工误差和刀具磨损非常重要,刀刃角的最优值为±90°,进给角可根据加工要求进行选择. | 王晋生 巩亚东 GABRIEL Abba 史家顺 蔡光起 | 2009 | 纳米技术与精密工程2009，7，5： | 1 |
| 5 | Asymptotically Stable Walking for Biped Robots: Analysis via Systems with Impulse Effects 显示文摘 | J W Grizzle Gabriel Abba Franck Plestan | 2001 | IEEE T-AC (S0018-9286)2001，46，1： | 1 |
| 6 | Hydrologic and economic evaluation of water - saving options in irrigation systems 显示文摘 | S Khan A Abbas HF Gabriel | 2007 | Irrigation and Drainage2007，57，1： | 1 |
| 7 | Asymptotically stable walking for biped robots: analysis via systems with impulse effects 显示文摘 | Jessy W Grizzle Gabriel Abba Franek Plestan | 2001 | IEEE Transactions on Automatic Control (S0018-9286)2001，46，1： | 1 |
| 8 | Asymptotically Stable Walking for Biped Robots: Analysis via Systems with Impulse Effects 显示文摘 | Grizzle J W Gabriel Abba Franck Plestan | 2001 | IEEE Transactions on Automatic Control (S0018-9286)2001，46，1： | 1 |
| 9 | Hydrologic and economic evaluation of water-saving options in irrigation systems显示文摘 | Khan S Abbas A Gabriel H F | 2008 | Irrigation and Drainage2008，57，1： | 1 |
| 10 | An Efficient Stacked Ensemble Model for Heart Disease Detection and Classification显示文摘Cardiac disease is a chronic condition that impairs the heart’s functionality.It includes conditions such as coronary artery disease,heart failure,arrhythmias,and valvular heart disease.These conditions can lead to serious complications and even be life-threatening if not detected and managed in time.Researchers have utilized Machine Learning(ML)and Deep Learning(DL)to identify heart abnormalities swiftly and consistently.Various approaches have been applied to predict and treat heart disease utilizing ML and DL.This paper proposes a Machine and Deep Learning-based Stacked Model(MDLSM)to predict heart disease accurately.ML approaches such as eXtreme Gradient Boosting(XGB),Random Forest(RF),Naive Bayes(NB),Decision Tree(DT),and KNearest Neighbor(KNN),along with two DL models:Deep Neural Network(DNN)and Fine Tuned Deep Neural Network(FT-DNN)are used to detect heart disease.These models rely on electronic medical data that increases the likelihood of correctly identifying and diagnosing heart disease.Well-known evaluation measures(i.e.,accuracy,precision,recall,F1-score,confusion matrix,and area under the Receiver Operating Characteristic(ROC)curve)are employed to check the efficacy of the proposed approach.Results reveal that the MDLSM achieves 94.14%prediction accuracy,which is 8.30%better than the results from the baseline experiments recommending our proposed approach for identifying and diagnosing heart disease. | Sidra Abbas Gabriel Avelino Sampedro Shtwai Alsubai Ahmad Almadhor Tai-hoon Kim | 2023 | Computers, Materials & Continua2023，77，10： | 0 |
| 11 | 多晶材料的微铣削建模与实验研究显示文摘对微铣削多晶材料的加工机理进行了详细分析,建立了相应的加工过程模型.重点考虑了最小切屑厚度和材料金相组织的作用,并对微铣削力和加工表面生成的影响因素进行了细致分析.分析发现多晶材料不同的晶粒特性会导致生成表面产生波动,并致使切削力产生附加振动.最小切屑厚度将决定刀具对晶粒是否进行材料去除,并使切削过程产生高频波动.大量的实验研究表明,模型准确地预测了微铣削现象,对优化加工参数、提高生产效率和加工质量提供了理论基础. | 王晋生 史家顺 巩亚东 ABBA Gabriel | 2008 | 东北大学学报(自然科学版)2008，29，10： | 0 |
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