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Design of Intelligent Alzheimer Disease Diagnosis Model on CIoT Environment

Computers, Materials & Continua 2022年第6期71卷 5979-5994页

作者： Anwer Mustafa Hilal Fahd NAl-Wesabi mohamed Tahar ben Othman Khaled Mohamad Almustafa Nadhem Nemri Mesfer Al Duhayyim Manar Ahmed Hamza Abu Sarwar Zamani Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia Department of Computer Science King King Khalid UniversityMuhayel Aseer62529Saudi Arabia Faculty of Computer and IT Sana’a UniversitySana’a61101Yemen Department of Computer Science College of ComputerQassim UniversityAl-Bukairiyah52571Saudi Arabia Department of Information Systems College of Computer and Information SystemsPrince Sultan UniversitySaudi Arabia Department of Information Systems King King Khalid UniversityMuhayel Aseer62529Saudi Arabia Department of Natural and Applied Sciences College of Community-AflajPrince Sattam bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia

Presently,cognitive Internet of Things(CIoT)with cloud computing(CC)enabled intelligent healthcare models are developed,which enables communication with intelligent devices,sensor modules,and other stakeholders in the healthcare sector to avail effective decision *** the other hand,Alzheimer disease(AD)is an advanced and degenerative illness which injures the brain cells,and its earlier detection is necessary for suitable interference by healthcare *** this aspect,this paper presents a new Oriented Features from Accelerated Segment Test(FAST)with Rotated Binary Robust Independent Elementary Features(BRIEF)Detector(ORB)with optimal artificial neural network(ORB-OANN)model for AD diagnosis and classification on the CIoT based smart healthcare *** initial pre-processing,bilateral filtering(BLF)based noise removal and region of interest(RoI)detection processes are carried *** addition,the ORBOANN model includes ORB based feature extractor and principal component analysis(PCA)based feature ***,artificial neural network(ANN)model is utilized as a classifier and the parameters of the ANN are optimally chosen by the use of salp swarm algorithm(SSA).A comprehensive experimental analysis of the ORB-OANN model is carried out on the benchmark database and the obtained results pointed out the promising outcome of the ORB-OANN technique in terms of different measures.

关键词： Cognitive internet of things machine learning parameter tuning alzheimer’s disease healthcare decision making

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Intelligent Intrusion Detection System for the Internet of Medical Things Based on Data-Driven Techniques

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Computer Systems Science & Engineering 2023年第11期47卷 1593-1609页

作者： Okba Taouali Sawcen Bacha Khaoula ben Abdellafou Ahamed Aljuhani Kamel Zidi Rehab Alanazi mohamed Faouzi Harkat Faculty of Computers and Information Technology University of TabukTabuk71491Saudi Arabia National Engineering School of Monastir University of MonastirMonastir5000Tunisia Applied College University of TabukTabuk71491Saudi Arabia Department of Electronics Faculty of Engineering AnnabaAnnaba23000Algeria

Introducing IoT devices to healthcare fields has made it possible to remotely monitor patients’information and provide a proper diagnosis as needed,resulting in the Internet of Medical Things(IoMT).However,obtaining good security features that ensure the integrity and confidentiality of patient’s information is a significant ***,due to the computational resources being limited,an edge device may struggle to handle heavy detection tasks such as complex machine learning ***,designing and developing a lightweight detection mechanism is *** address the aforementioned challenges,a new lightweight IDS approach is developed to effectively combat a diverse range of cyberattacks in IoMT *** proposed anomaly-based IDS is divided into three steps:pre-processing,feature selection,and *** the pre-processing phase,data cleaning and normalization are *** the feature selection step,the proposed approach uses two data-driven kernel techniques:kernel principal component analysis and kernel partial least square techniques to reduce the dimension of extracted features and to ameliorate the detection ***,in decision step,in order to classify whether the traffic flow is normal or malicious the kernel extreme learning machine is *** check the efficiency of the developed detection scheme,a modern IoMT dataset named WUSTL-EHMS-2020 is considered to evaluate and discuss the achieved *** proposed method achieved 99.9%accuracy,99.8%specificity,100%Sensitivity,99.9 F-score.

关键词： Machine learning data-driven technique KPCA KPLS intrusion detection IoT Internet of Medical Things(IoMT)

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FMS-Workflow Modeling Based on P-Timed Stochastic Petri Net

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Journal of Software Engineering and Applications 2023年第9期16卷 443-482页

作者： Walid ben Mesmia Kamel Barkaoui mohamed Escheikh Sys’Com-ENIT Tunisia ENIT Le Belvédère Tunis Tunisia CEDRIC-CNAM Paris France

In this paper, we propose astochastic Petri net model P-timed Workflow (WPTSPN) to specify, verify, and analyze a business process (BP) of a Flexible Manufacturing System (FMS). After formalizing the semantics of our model, we illustrate how to verifysome of its properties (reachability, safety, boundedness, liveness, correctness, alive tokens, and security) in the P-Timed context. Next, we validate the relevance of the proposed model with MATLAB simulation through a specific FMS case study. Finally, we use a generalized truncated density function to predict the duration of a token’s sojourn (residence) in a timed place with respect to the sequence states of the global FMS workflow.

关键词： WPTSPN SPN Workflow FMS P-Timed Specification Verification Prediction

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Harmonic Distortion Rate Analysis of H-Bridges Multilevel Inverter

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材料科学与工程（中英文B版） 2011年第3期1卷 308-315页

作者： mohamed Nejib ben Nasr Khammassi Anis Kebir Faouzi ben Ammar Unite de recherche SICISI ESSTT 5av. Taha Hussein BP 56 Bab Mnara-1008 Universite de Tunis Tunisia Unite de recherche. LSE INSAT Centre Urbain Nord BP 676 1080 Tunisia

This paper represents comparative study on two control techniques applied to H-bridges multilevel inverter. The considered techniques are standard PWM and harmonic elimination control. Their performances are compared in terms of THD and commutation’s losses so that the choice of power switches is optimized. Simulation results indicated that the harmonic elimination technique exhibits better results than the standard PWM technique, which is sustained by the reduce of the commutation losses, and a power rise for the switches ensuring the use of GTOs, IGCTs.

关键词：多电平逆变器 H桥失真率 PWM技术谐波技术标准电源开关控制技术

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Study of Cd2+, Al3+, and SO42−Ions Influence on Struvite Precipitation from Synthetic Water by Dissolved CO2Degasification Technique

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Open Journal of Inorganic Chemistry 2015年第3期5卷 41-51页

作者： Hassidou Saidou Atef Korchef Sami ben Moussa mohamed ben Amor Departement of Chemistry Faculty of Sciences and Techniques Dan Dicko Dan Koulodo University of Maradi Maradi Niger Laboratory of Traitment of Natural Water Center of Research and Technology of Water Technopark of Borj Cedria Tunisia Laboratory of Valorization of Useful Materials National Center of Research in Material Sciences Technopark of Borj Cedria Tunisia

The effect of cadmium, aluminum, and sulphate ions on struvite precipitation kinetics and morphology of solids obtained was investigated in this study. Thus, these ions were introduced as additives in solution where struvite precipitation was achieved. The main results obtained showed that the Cd2+ ions cause the probable co-formation, with struvite, of an amorphous phase observed from Cd2+ concentration of 10 mg/L;the addition of aluminum ions in the solution does not affect the nature of the crystalline phase, identified as struvite. However, these ions cause the formation of agglomerates of larger and larger as the concentration rises. Moreover, their increasing improved significantly the yield of phosphates removal;although the sulfate ions have no effect on the nature of the precipitated phase identified as struvite, independently of molar ratio studied, they affect the thermal decomposition of struvite. This latter is done in a single step by increasing the concentration of these ions for the SO42−/PO43−molar ratio of 8.

关键词： CO2 Degasification Technique Struvite Precipitation Cd2+ Al3+ SO42-

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Malware Detection Using Decision Tree Based SVM Classifier for IoT

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Computers, Materials & Continua 2022年第7期72卷 713-726页

作者： Anwer Mustafa Hilal Siwar ben Haj Hassine Souad Larabi-Marie-Sainte Nadhem Nemri mohamed K.Nour Abdelwahed Motwakel Abu Sarwar Zamani Mesfer Al Duhayyim Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Department of Computer Science College of Science and ArtsKing Khalid UniversityMahayil AsirSaudi Arabia Department of Computer Science College of Computer and Information SciencesPrince Sultan UniversitySaudi Arabia Department of Computer Science College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Natural and Applied Sciences College of Community-AflajPrince Sattam bin Abdulaziz UniversitySaudi Arabia

The development in Information and Communication Technology has led to the evolution of new computing and communication *** revolution with Internet of Things(IoTs)has developed various applications in almost all domains from health care,education to entertainment with sensors and smart *** of the subsets of IoT is Internet of Medical things(IoMT)which connects medical devices,hardware and software applications through *** enables secure wireless communication over the Internet to allow efficient analysis of medical *** these smart advancements and exploitation of smart IoT devices in health care technology there increases threat and malware attacks during transmission of highly confidential medical *** work proposes a scheme by integrating machine learning approach and block chain technology to detect malware during data transmission in *** proposed Machine Learning based Block Chain Technology malware detection scheme(MLBCT-Mdetect)is implemented in three steps namely:feature extraction,Classification and *** extraction is performed by calculating the weight of each feature and reduces the features with less *** Vector Machine classifier is employed in the second step to classify the malware and benign ***,third step uses blockchain to store details of the selected features which eventually improves the detection of malware with significant improvement in speed and ***-BCT-Mdetect achieves higher accuracy with low false positive rate and higher True positive rate.

关键词： Blockchain malware detection classification feature selection internet of medical things

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Effect of Blending Ratio of Fibers on the Properties of Nonwoven Fabrics Based of Alfa Fibers

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Advances in Materials Physics and Chemistry 2014年第6期4卷 116-125页

作者： Lassaad Ghali mohamed Taher Halimi mohamed ben Hassen Faouzi Sakli Textile Engineering Laboratory Monastir University Monastir Tunisia

Natural fibers are nowadays increasingly employed for making nonwoven, replacing the synthetic materials due to economic and environmental considerations. In this setting, we examine the use of Alfa fibers in nonwoven. Extracted Alfa fibers present satisfying mechanical properties that allow them to be used to produce nonwoven textiles materials. Therefore, Alfa fibers are, mainly, blended with cotton, polyester, Tencel and wool. Webs are prepared using cotton or wool cards in regular width. The nonwoven consolidation is made by needle-punching method. The weight, thickness, air permeability, adiathermic capacity and tensile properties are investigated. The results exhibit that the air permeability increases with the increase of Alfa fibers ratio for the nonwoven Alfa blended with short fibers. It decreases in case of Alfa/Wool blend. We can conclude also that the nonwoven Alfa blended with wool fibers have the highest properties values for all the Alfa fibers blends. Data also revealed that the tensile properties are reduced with the increment of Alfa fibers ratio.

关键词： Alfa Fibers Nonwoven Air Permeability Specific Strength

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Cascaded H-Bridges Asymmetrical 11-Levels Optimization

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材料科学与工程（中英文B版） 2011年第4期1卷 496-503页

作者： mohamed Nejib ben Nasr Khammassi Anis Kebir Faouzi ben Ammar Unite de Recherche SICISI ESSTT 5av. Taha Hussein BP 56 Bab Mnara-lO08 Universite de Tunis Tunisia Unitd de Recherche.＂ LSE INSA T Centre Urbain Nord BP 676 1080 Tunis

The following dissertation aims at investigating the multilevel topology basis through the analyses of the harmonic elimination control modeling methodology of the asymmetrical inverter. Thus the contribution of this paper can be summarized mainly by the fact that the pre-calculated PWM control used to control the symmetrical structure, as applied to the asymmetrical structure with a reduced number of cells, provides the same performance level resolution and signal strength to the load terminals, which guarantees a constant voltage frequency report. This observation is similar for the three cells, which allows the use of different drivers such as MOSFET, IGBT and GTO. These results have a good performance from the intrinsic proprieties of each semiconductor for each cell.

关键词：水平分辨率不对称非对称结构优化 H桥级联 MOSFET 消谐控制

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Adaptive Internal Model Control of a DC Motor Drive System Using Dynamic Neural Network

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Journal of Software Engineering and Applications 2012年第3期5卷 168-189页

作者： Farouk Zouari Kamel ben Saad mohamed benrejeb Unité de Recherche LARA Automatique Ecole Nationale d'Ingénieurs de Tunis (ENIT) Tunis Tunisia.

This work concerns the study of problems relating to the adaptive internal model control of DC motor in both cases conventional and neural. The most important aspects of design building blocks of adaptive internal model control are the choice of architectures, learning algorithms, and examples of learning. The choice of parametric adaptation algorithm for updating elements of the conventional adaptive internal model control shows limitations. To overcome these limitations, we chose the architectures of neural networks deduced from the conventional models and the Levenberg-marquardt during the adjustment of system parameters of the adaptive neural internal model control. The results of this latest control showed compensation for disturbance, good trajectory tracking performance and system stability.

关键词： Adaptive Internal Model Control Recurrent Neural Network DC Motor Parametric Adaptation Algorithm Levenberg-Marquardt

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Episodic Sedimentation of Heavy Metals and Iron in Bizerte Lagoon, Northern Tunisia

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International Journal of Geosciences 2013年第1期4卷 24-35页

作者： Amor ben Garali mohamed Ouakad Moncef Gueddari Faculté des Sciences de Bizerte Laboratoire de Sédimentologie et Géochimie Marine Bizerte Tunisie Faculté des Sciences de Tunis Université El Manar Tunis Tunisie

The correlations between various sedimentological and geochemical parameters permit to identify the main sedimenta tion phases of pollution carriers, especially those related to the sediment cores lithology in Bizerte Lagoon. A close re lationship exists between the TOC distribution and the fine fraction (r = 0.70;threshold 5%). This is to identify the for mation of organic minerals aggregates. Significant correlations between specific organic matter and heavy metals have been identified. Indeed, the calculated correlation coefficient varies between 0.4 for Zn and 0.85 for Mn. The enrich ment of the intermediate horizons in heavy metals result in specific sedimentations episodes of the prodeltaic zones. Under these conditions, the surface sediments profit from a “salting-out” phenomenon, which explains the excess of lead observed on the surface. The enriched zones in manganese and zinc correspond to the strongest contents of kaolin ite and in smectite, thus, there would be an association with the finest phyllosilicates and/or the colloidal oxyhydroxy des. This is primarily due to the formation of an organic minerals complex via the trapping phenomenon of the argilla ceous particles (smectite) and the organic matter of anthropogenic origin. It is to be specified that the presence of metal elements of natural origin (Mn) or anthropogenic origin (Fe, Zn, Pb and Ni) which induce the consolidation of these organic minerals complexes.

关键词： Core Clay Minerals Organic Matters Heavy Metals Bizerte Lagoon Tunisia

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