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Amine Zemri,Mohammed Sid Ahmed Houari,Abdelmoumen Anis Bousahla,Abdelouahed Tounsi 국제구조공학회 2015 Structural Engineering and Mechanics, An Int'l Jou Vol.54 No.4
This paper presents a nonlocal shear deformation beam theory for bending, buckling, and vibration of functionally graded (FG) nanobeams using the nonlocal differential constitutive relations of Eringen. The developed theory account for higher-order variation of transverse shear strain through the depth of the nanobeam, and satisfy the stress-free boundary conditions on the top and bottom surfaces of the nanobeam. A shear correction factor, therefore, is not required. In addition, this nonlocal nanobeam model incorporates the length scale parameter which can capture the small scale effect and it has strong similarities with Euler–Bernoulli beam model in some aspects such as equations of motion, boundary conditions, and stress resultant expressions. The material properties of the FG nanobeam are assumed to vary in the thickness direction. The equations of motion are derived from Hamilton’s principle. Analytical solutions are presented for a simply supported FG nanobeam, and the obtained results compare well with those predicted by the nonlocal Timoshenko beam theory.
A Reconfigurable Multilayer Substrate Antenna for Aerospace Applications
amine, Ksiksi Mohamed,azizi, Mohamed karim,Gharsallah, Ali International Journal of Computer ScienceNetwork S 2021 International journal of computer science and netw Vol.21 No.9
In this paper, we have simulated a rectangular microstrip patch antenna for aerospace applications based on graphen as a conductor and a multilayer substrate .as a result of the use of the graphen patch we obtained a reconfigurable antenna on the frequency range (0.6-0.7 terahertz) with a gain up to 12 db. The simulation of this antenna has been performed by using CST Microwave Studio, which is a commercially available finite integral based electromagnetic simulator.
An Experimental Investigation of the Impact of Mobile IPv6 Handover on Transport Protocols
Amine Dhraief,Abdelfettah Belghith 한국산학기술학회 2012 SmartCR Vol.2 No.1
Mobile IPv6 is the current IETF standard for end host mobility management in the Internet. In order to provide a transparent location management, Mobile IPv6 operates in two different modes. In the first mode, mobile node incoming packets are tunneled to the node current location via the home network. In the second mode, traffic is exchanged directly between the mobile node and its communicating peers. In this paper, we evaluate the performance of these two modes on a real test bed. We first analytically model the Mobile IPv6 handover. Afterwards, we empirically assess its impact on transport protocols in general and more specifically on TCP CUBIC, the default TCP implementation in the current Linux kernel since version 2.6.19. We demonstrate that this TCP implementation induces high handover latency as it was not designed to be deployed in a dynamic environment.
Multiple Instance Mamdani Fuzzy Inference
Amine B. Khalifa,Hichem Frigui 한국지능시스템학회 2015 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGE Vol.15 No.4
A novel fuzzy learning framework that employs fuzzy inference to solve the problem of Multiple Instance Learning (MIL) is presented. The framework introduces a new class of fuzzy inference systems called Multiple Instance Mamdani Fuzzy Inference Systems (MIMamdani). In multiple instance problems, the training data is ambiguously labeled. Instances are grouped into bags, labels of bags are known but not those of individual instances. MIL deals with learning a classifier at the bag level. Over the years, many solutions to this problem have been proposed. However, no MIL formulation employing fuzzy inference exists in the literature. Fuzzy logic is powerful at modeling knowledge uncertainty and measurements imprecision. It is one of the best frameworks to model vagueness. However, in addition to uncertainty and imprecision, there is a third vagueness concept that fuzzy logic does not address quiet well, yet. This vagueness concept is due to the ambiguity that arises when the data have multiple forms of expression, this is the case for multiple instance problems. In this paper, we introduce multiple instance fuzzy logic that enables fuzzy reasoning with bags of instances. Accordingly, a MI-Mamdani that extends the standard Mamdani inference system to compute with multiple instances is introduced. The proposed framework is tested and validated using a synthetic dataset suitable for MIL problems. Additionally, we apply the proposed multiple instance inference to fuse the output of multiple discrimination algorithms for the purpose of landmine detection using Ground Penetrating Radar.
( Amine Dahane ),( Nasr Eddine Berrached ),( Abdelhamid Loukil ) 한국정보처리학회 2015 Journal of information processing systems Vol.11 No.2
In this paper, we present a virtual laboratory platform (VLP) baptized Mercury allowing students to make practical work (PW) on different aspects of mobile wireless sensor networks (WSNs). Our choice of WSNs is motivated mainly by the use of real experiments needed in most courses about WSNs. These experiments require an expensive investment and a lot of nodes in the classroom. To illustrate our study, we propose a course related to energy efficient and safe weighted clustering algorithm. This algorithm which is coupled with suitable routing protocols, aims to maintain stable clustering structure, to prevent most routing attacks on sensor networks, to guaranty energy saving in order to extend the lifespan of the network. It also offers a better performance in terms of the number of re-affiliations. The platform presented here aims at showing the feasibility, the flexibility and the reduced cost of such a realization. We demonstrate the performance of the proposed algorithms that contribute to the familiarization of the learners in the field of WSNs.
막증발 공정 모델링과 유기오염물질에 의한 막오염 효과 분석
( Amine Charfi ),( Fida Tibi ),김정환 ( Jeonghwan Kim ),조진우 ( Jin-woo Cho ) 한국폐기물자원순환학회(구 한국폐기물학회) 2021 한국폐기물자원순환학회 춘계학술발표논문집 Vol.2021 No.-
Nowadays the membrane distillation (MD) technology for wastewater treatment has been regarded with growing interest. The MD is able to separate non-volatile contaminants to obtain highly purified water. Operated at low pressure, the MD system showed less fouling risk than pressure-driven separation technologies. Nevertheless, the fouling phenomenon is still an issue which hinders the MD performance by decreasing its productivity as well as its separation effectiveness. This study aims at better understanding the organic fouling mechanisms and their effect on permeate flux decline in a direct contact membrane distillation treating synthetic wastewater. A mathematical model was developed to simulate the permeate flux variation with time. The model simulates the deposit mass of the cake layer as the difference between the matter dragged by convective forces to the membrane surface and the mass detached by the turbulence effect. The permeate flux is expressed by a resistance in series model as the ratio of the vapor pressure difference and the sum of the initial membrane resistance and the cake layer resistance. The cake layer resistance is proportional to the deposit mass and the specific cake resistance expressed by kozeny-Carman relation as proportional to the cake porosity. The model was validated using experimental flux data obtained using a synthetic solutions of sodium alginate and bovine serum albumin to simulate polysaccharides and proteins, respectively, considered as the main organic foulants, at different temperatures and pHs. The model showed a satisfactory fitting result with a coefficient of determination R2 ≥ 90%.
Amine, Khalil,Chen, Zonghai,Zhang, Z.,Liu, Jun,Lu, Wenquan,Qin, Yan,Lu, Jun,Curtis, Larry,Sun, Yang-Kook Royal Society of Chemistry 2011 Journal of materials chemistry Vol.21 No.44
<P>The performance degradation of graphite/Li<SUB>1.1</SUB>[Ni<SUB>1/3</SUB>Mn<SUB>1/3</SUB>Co<SUB>1/3</SUB>]<SUB>0.9</SUB>O<SUB>2</SUB> lithium-ion cells at elevated temperature was investigated. The electrochemical data suggest that the migration of dissolved transition metals from the cathode to the anode is the key contributor to the performance degradation. With the help of density function theory calculations, lithium difluoro[oxalato] borate was tested to be an effective electrolyte additive to mitigate the performance degradation of lithium-ion cells. The application of this novel electrolyte additive was found to significantly improve both the life and safety characteristics of graphite/Li<SUB>1.1</SUB>[Ni<SUB>1/3</SUB>Mn<SUB>1/3</SUB>Co<SUB>1/3</SUB>]<SUB>0.9</SUB>O<SUB>2</SUB> lithium-ion cells.</P> <P>Graphic Abstract</P><P>The performance degradation of graphite/Li<SUB>1.1</SUB>[Ni<SUB>1/3</SUB>Mn<SUB>1/3</SUB>Co<SUB>1/3</SUB>]<SUB>0.9</SUB>O<SUB>2</SUB> lithium-ion cells at elevated temperature was investigated. <IMG SRC='http://pubs.rsc.org/services/images/RSCpubs.ePlatform.Service.FreeContent.ImageService.svc/ImageService/image/GA?id=c1jm11584g'> </P>
Amine Charfi,Muhammad Aslam,Geoffroy Lesage,Marc Heran,김정환 한국공업화학회 2017 Journal of Industrial and Engineering Chemistry Vol.49 No.-
A mathematical model was presented to understand membrane fouling in anaerobicfluidized bedmembrane bioreactor (AFMBR). Assuming three fouling mechanisms, the cake formation, progressiveporosity reduction and the pore blocking, the model describes the effect of granular activated carbon(GAC) on fouling resistance and mechanisms. The model shows satisfactory description of transmem-brane pressure with R299%. Using GAC particles (2–3 mm) allows a better fouling mitigation byremoving cake deposit while long term fouling is due to pore blocking. Thefluidized small GAC particles(0.18–0.5 mm) foster the cake formation by their deposit on membrane surface.
Automated recognition of white blood cells using deep learning
Amin Khouani,Mostafa El Habib Daho,Sidi Ahmed Mahmoudi,Mohammed Amine Chikh,Brahim Benzineb 대한의용생체공학회 2020 Biomedical Engineering Letters (BMEL) Vol.10 No.3
The detection, counting, and precise segmentation of white blood cells in cytological images are vital steps in the eff ectivediagnosis of several cancers. This paper introduces an effi cient method for automatic recognition of white blood cells inperipheral blood and bone marrow images based on deep learning to alleviate tedious tasks for hematologists in clinicalpractice. First, input image pre-processing was proposed before applying a deep neural network model adapted to cellslocalization and segmentation. Then, model outputs were improved by using combined predictions and corrections. Finally,a new algorithm that uses the cooperation between model results and spatial information was implemented to improve thesegmentation quality. To implement our model, python language, Tensorfl ow, and Keras libraries were used. The calculationswere executed using NVIDIA GPU 1080, while the datasets used in our experiments came from patients in the Hemobiologyservice of Tlemcen Hospital (Algeria). The results were promising and showed the effi ciency, power, and speed of theproposed method compared to the state-of-the-art methods. In addition to its accuracy of 95.73%, the proposed approachprovided fast predictions (less than 1 s).