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18篇 您的检索式:作者名="Chabani"
    题名 作者 年代 出处 被引量
1Activation and hydrogen absorption in thermally prepared RuO2 and IrO2 显示文摘Chabanier C Guay D 2004Journal of Electroanalytical Chemistry2004,570,1:1
2Kinetics of nitrates adsorption on Amberlite IRA 400 resin 显示文摘Chabani M Amrane A Bensmaili A 2007Desalination2007,206,13:1
3Tin dioxide opals and inverted opals:near-ideal microstructures for gas sensors显示文摘Scott R W J Yang S M Chabanis G 2001Adv Mater2001,13,:1
4Kinetic modelling of the adsorption of nitrates by ion exchange resin显示文摘CHABANI M AMRANE A BENSMAILI A 2006Chemical Engineering Journal2006,125,2:1
5Tin Dioxide Opals and Inverted Opals: Near-Ideal Microstructures for Gas Sensors 显示文摘Scott R W J Yang S M Chabanis G 2001Adv Mater2001,13,:1
6Tin dioxide opals and inverted opals:near-ideal microstructures for gas sensors显示文摘SCOTT W J YANG S M CHABANIS G 2001Adv Mater2001,13,19:1
7Kinetic modelling of the adsorption of nitrates by ion exchange resin显示文摘CHABANI M AMRANE A BENSMAILI A 2006Chemical Eng J2006,125,2:1
8Kinetic modelling of the adsorption of nitrates by ion exchange resin显示文摘M. Chabani A. Amrane A. Bensmaili 2006Chemical Engineering Journal2006,,2:1
9Tin dioxide opals and inverted opals: Near-ideal microstructures for gas sensors 显示文摘Scott W J Yang S M Chabanis G 2001Adv Mater2001,,13:1
10Kinetics of nitrates adsorption on Amberlite IRA 400 resin 显示文摘Chabani M Amrane A Bensmaili A 2007Desalination2007,206,13:1
11Kinetics of nitrates adsorption on Amberlite IRA 400 resin 显示文摘CHABANI M AMRANE A BENSMAILI A 2007Desalination2007,206,13:1
12Kinetics of nitrates adsorption on Amberlite IRA 400 resin 显示文摘CHABANI M AMRANE A BENSMAILI A 2007Desalination2007,206,13:1
13Coupling Adsorption with Photocatalysis Process for the Cr(Ⅵ) Removal显示文摘Kebir G Chabani M Nasrallah N 0,,1:1
14Kinetics of nitrates adsorption on Amberlite IRA 400 resin显示文摘Chabani M Amrane A Bensmaili A 2007Desalination2007,206,123:1
15Tin dioxide opalsand inverted opals:Near-ideal microstructures for gas sensors显示文摘SCOTT R W J YANG S M CHABANIS G 2001AdvMater2001,13,14:1
16Synaptopodin deficient mice lack a spine apparatus and show deficits in synaptic plasticity(Article)显示文摘Deller T Korte M Chabanis S 2003Proc Natl Acad Sci USA2003,100,10:1
17Modeling and Verification of Aircraft Takeoff Through Novel Quantum Nets显示文摘The formal modeling and verification of aircraft takeoff is a challenge because it is a complex safety-critical operation.The task of aircraft takeoff is distributed amongst various computer-based controllers,however,with the growing malicious threats a secure communication between aircraft and controllers becomes highly important.This research serves as a starting point for integration of BB84 quantum protocol with petri nets for secure modeling and verification of takeoff procedure.The integrated model combines the BB84 quantum cryptographic protocol with powerful verification tool support offered by petri nets.To model certain important properties of BB84,a new variant of petri nets coined as Quantum Nets are proposed by defining their mathematical foundations and overall system dynamics,furthermore,some important system properties are also abstractly defined.The proposed QuantumNets are then applied for modeling of aircraft takeoff process by defining three quantum nets:namely aircraft,runway controller and gate controller.For authentication between quantum nets,the use of external places and transitions is demonstrated to describe the encryptiondecryption process of qubits stream.Finally,the developed takeoff quantum network is verified through simulation offered by colored petri-net(CPN)Tools.Moreover,reachability tree(RT)analysis is also performed to have greater confidence in feasibility and correctness of the proposed aircraft takeoff model through the Quantum Nets.Maryam Jamal Nazir Ahmad Zafar Atta-ur-Rahman Dhiaa Musleh Mohammed A.Gollapalli Sghaier Chabani 2022Computers, Materials & Continua2022,,8:0
18Supervised Machine Learning-Based Prediction of COVID-19显示文摘COVID-19 turned out to be an infectious and life-threatening viral disease,and its swift and overwhelming spread has become one of the greatest challenges for the world.As yet,no satisfactory vaccine or medication has been developed that could guarantee its mitigation,though several efforts and trials are underway.Countries around the globe are striving to overcome the COVID-19 spread and while they are finding out ways for early detection and timely treatment.In this regard,healthcare experts,researchers and scientists have delved into the investigation of existing as well as new technologies.The situation demands development of a clinical decision support system to equip the medical staff ways to timely detect this disease.The state-of-the-art research in Artificial intelligence(AI),Machine learning(ML)and cloud computing have encouraged healthcare experts to find effective detection schemes.This study aims to provide a comprehensive review of the role of AI&ML in investigating prediction techniques for the COVID-19.A mathematical model has been formulated to analyze and detect its potential threat.The proposed model is a cloud-based smart detection algorithm using support vector machine(CSDC-SVM)with cross-fold validation testing.The experimental results have achieved an accuracy of 98.4%with 15-fold cross-validation strategy.The comparison with similar state-of-the-art methods reveals that the proposed CSDC-SVM model possesses better accuracy and efficiency.Atta-ur-Rahman Kiran Sultan Iftikhar Naseer Rizwan Majeed Dhiaa Musleh Mohammed Abdul Salam Gollapalli Sghaier Chabani Nehad Ibrahim Shahan Yamin Siddiqui Muhammad Adnan Khan 2021Computers, Materials & Continua2021,,10:0
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