http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
Mohamed Brayek,Zied Driss,Mohamed Ali Jemni,Ali Damak,Mohamed Salah Abid 대한기계학회 2023 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.37 No.1
Combustion characteristics and emission in spark-ignition engines could be enhanced using hydrogen as supplementary fuel. However, its production, storage, and introduction in the combustion chamber face several challenges. To overcome the necessity of a storage device, a conventional electrolyser was used to produce a hydrogen-oxygen mixture (hydroxygen). The produced hydroxygen bubbles are characterized by their macro and nanometric size. In the present work, gasoline was on top of the water in the electrolyser. Therefore, hydroxygen nanobubbles are diffused in both water and gasoline. Combustion analysis was carried out for different engine speeds. An improvement in brake torque and a reduction in fuel consumption, HC, CO, and CO 2 emissions have been witnessed in the engine during test performance. However, the emission analysis shows a slight increase in NO x emission. Finally, this disadvantage could be neglected compared to the improvements that come with the use of hydroxygen nanobubble gasoline blends.
Nature of Complex Network of Dengue Epidemic as a Scale-Free Network
Hafiz Abid Mahmood Malik,Faiza Abid,Nadeem Mahmood,Mohamed Ridza Wahiddin,Asif Malik 대한의료정보학회 2019 Healthcare Informatics Research Vol.25 No.3
Objectives: Dengue epidemic is a dynamic and complex phenomenon that has gained considerable attention due to its injurious effects. The focus of this study is to statically analyze the nature of the dengue epidemic network in terms of whether it follows the features of a scale-free network or a random network. Methods: A multifarious network of Aedes aegypti is addressed keeping the viewpoint of a complex system and modelled as a network. The dengue network has been transformed into a one-mode network from a two-mode network by utilizing projection methods. Furthermore, three network features have been analyzed, the power-law, clustering coefficient, and network visualization. In addition, five methods have been applied to calculate the global clustering coefficient. Results: It has been observed that dengue epidemic follows a powerlaw, with the value of its exponent γ = –2.1. The value of the clustering coefficient is high for dengue cases, as weight of links. The minimum method showed the highest value among the methods used to calculate the coefficient. Network visualization showed the main areas. Moreover, the dengue situation did not remain the same throughout the observed period. Conclusions: The results showed that the network topology exhibits the features of a scale-free network instead of a random network. Focal hubs are highlighted and the critical period is found. Outcomes are important for the researchers, health officials, and policy makers who deal with arbovirus epidemic diseases. Zika virus and Chikungunya virus can also be modelled and analyzed in this manner.
Abdelmonaam Abid,Moncef Hammadi,Maher Barkallah,Jean-Yves Choley,Jamel Louati,Alain Rivière,Mohamed Haddar 한국정밀공학회 2018 International Journal of Precision Engineering and Vol.19 No.12
Globalization and mass customization are demanding a higher level of productivity. The relevance of modelling approaches to the study and design of reconfigurable manufacturing system (RMS) is widely claimed to achieve the highest productivity. Principally, reconfigurability in manufacturing systems should support the changeability with precisely the production capacity and functionality needed and exactly when needed. Simulation of such reconfigurable systems has become more and more difficult with the increasing complexity of system requirements. In spite of the promising methodology for designing RMS, an effective framework that bridges the gap between conceptual modelling level process and simulation level process is still a major challenge for Scientist. For this reason, we propose in this paper a generic framework especially designed for building and running executable agent-based models of RMS. This framework relies on SysML (Systems Modelling Language) models specifications, the holonic system techniques and multi-agent system in order to generate executable models of RMS. The considered case study for this paper is based on a steel converter process. Results showed an increase in the productivity rate after simulating the reconfigurability test cases through the developed agent-based models.
An Indirect Model Reference Robust Fuzzy Adaptive Control for a Class of SISO Nonlinear Systems
Hafedh Abid,Mohamed Chtourou,Ahmed Toumi 제어·로봇·시스템학회 2009 International Journal of Control, Automation, and Vol.7 No.6
In this paper we are interested in robust adaptive fuzzy control of nonlinear SISO systems in the presence of parametric uncertainties. The plant model structure is represented by the Takagi-Sugeno (T-S) type fuzzy system. An indirect adaptive fuzzy controller based on model reference control scheme is proposed to provide asymptotic tracking of reference signal. The controller parameters are computed at each time. The plant state tracks asymptotically the state of the reference model for any bounded reference input signal. Inverted pendulum and mass spring damper are used to check the performance of the proposed controller.
High-performance computing for SARS-CoV-2 RNAs clustering: a data science-based genomics approach
Oujja, Anas,Abid, Mohamed Riduan,Boumhidi, Jaouad,Bourhnane, Safae,Mourhir, Asmaa,Merchant, Fatima,Benhaddou, Driss Korea Genome Organization 2021 Genomics & informatics Vol.19 No.4
Nowadays, Genomic data constitutes one of the fastest growing datasets in the world. As of 2025, it is supposed to become the fourth largest source of Big Data, and thus mandating adequate high-performance computing (HPC) platform for processing. With the latest unprecedented and unpredictable mutations in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the research community is in crucial need for ICT tools to process SARS-CoV-2 RNA data, e.g., by classifying it (i.e., clustering) and thus assisting in tracking virus mutations and predict future ones. In this paper, we are presenting an HPC-based SARS-CoV-2 RNAs clustering tool. We are adopting a data science approach, from data collection, through analysis, to visualization. In the analysis step, we present how our clustering approach leverages on HPC and the longest common subsequence (LCS) algorithm. The approach uses the Hadoop MapReduce programming paradigm and adapts the LCS algorithm in order to efficiently compute the length of the LCS for each pair of SARS-CoV-2 RNA sequences. The latter are extracted from the U.S. National Center for Biotechnology Information (NCBI) Virus repository. The computed LCS lengths are used to measure the dissimilarities between RNA sequences in order to work out existing clusters. In addition to that, we present a comparative study of the LCS algorithm performance based on variable workloads and different numbers of Hadoop worker nodes.
Mohammad Fadhil Abid,Mohammed Ebrahim,Orroba Nafi,Luma Hussain,Neran Maneual,Abeer Sameer 한국화학공학회 2014 Korean Journal of Chemical Engineering Vol.31 No.7
The aim of the present project was to design and operate a solar reactor system and to analyze its performancefor the removal of different types of toxic organic pollutants (e.g., synthetic methyl violet dye and phenol) fromwater with titanium dioxide as the photocatalyst. Various operating parameters were studied to investigate the behaviorof the designed reactor like initial substrate concentration, loading of catalyst, pH of solution, and H2O2 concentration. The operating parameters were optimized to give higher efficiency to the reactor performance. Results showedthat a photocatalysis system, operating at optimum conditions, offered within one hour of operation degradation upto 95.27% for synthetic dye, while a conversion of 99.95% was obtained in three hours. With phenol, degradation wasup to 80.0% and 98.0%, respectively. The removal of TOC for the two toxic materials was also at high levels. Thisconfirmed the feasibility of the designed solar system. The kinetics of dye degradation was first order with respect todye concentration and could be well described by Langmuir-Hinshelwood model. A preliminary design of a solar photocatalysissystem as an alternative treatment method for wastewater effluents from an Iraqi textile mill was introduced.
( Abderrahmen Guermazi ),( Abdelfettah Belghith ),( Mohamed Abid ),( Sofien Gannouni ) 한국인터넷정보학회 2017 KSII Transactions on Internet and Information Syst Vol.11 No.2
Efficient key distribution and management mechanisms as well as lightweight ciphers are the main pillar for establishing secure wireless sensor networks (WSN). Several symmetric based key distribution protocols are already proposed, but most of them are not scalable, yet vulnerable to a small number of compromised nodes. In this paper, we propose an efficient and scalable key management and distribution framework, named KMMR, for large scale WSNs. The KMMR contributions are three fold. First, it performs lightweight local processes orchestrated into upward and downward tiers. Second, it limits the impact of compromised nodes to only local links. Third, KMMR performs efficient secure node addition and revocation. The security analysis shows that KMMR withstands several known attacks. We implemented KMMR using the NesC language and experimented on Telosb motes. Performance evaluation using the TOSSIM simulator shows that KMMR is scalable, provides an excellent key connectivity and allows a good resilience, yet it ensures both forward and backward secrecy. For a WSN comprising 961 sensor nodes monitoring a 60 hectares agriculture field, KMMR requires around 2.5 seconds to distribute all necessary keys, and attains a key connectivity above 96% and a resilience approaching 100%. Quantitative comparisons to earlier work show that KMMR is more efficient in terms of computational complexity, required storage space and communication overhead.