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| 1 | Specific Capacitance and Cyclic Stability of Graphene Based Metal/Metal Oxide Nanocomposites:A Review显示文摘Graphene has become a worldwide admired material among researchers and scientists equally due to its unique richness in mechanical strength,electrical conductivity,optical and thermal properties.Researchers have explored that the composite materials based on graphene and metal/metal oxide nanostructures possess excellent potential for energy storage technologies.In particular,supercapacitors based on such composite materials have engrossed the extreme interest of researchers for its rapid charging/discharging time,safe operation and longer cyclic constancy.Till now,several fabrication techniques for composite materials and their energy storage applications have been explored.Here,specially,we have concentrated on the hottest research progress for the fabrication of graphene oxide and metal/metal oxide nanocomposites.We also emphasized on the characteristics and properties of supercapacitors fabricated using these composite materials.Moreover,our study is focused on the specific capacitance and cyclic stability of various composites to haul out the most efficient material for supercapacitor applications. | Abdul Waheed Anwar Abdul Majeed Nadeem Iqbal Wasi Ullah Ahmad Shuaib Usman Ilyas Fozia Bibi Hafiz Muhammad Rafique | 2015 | Journal of Materials Science & Technology2015，31，7： | 1 |
| 2 | MWCNTs/SWCNTs Nanofluid Thin Film Flow over a Nonlinear Extending Disc: OHAM Solution显示文摘The aim of this research is the improvement towards the consumption of energy in the field of engineering and industry. The efforts have been paid to the enhancement of heat transmission and cooling process through a nanofluid coating of a nonlinear stretching disc. The combination of Water(H2 O) and multiple walled carbon nanotubes(MWCNT)/single walled carbon nanotubes(SWCNT) have been used as a nanofluid. The spreading of a thin nano-layer with variable thickness over a nonlinear and radially stretching surface has been considered. The estimated results of the problem have been accomplished using the Optimal Homotopy Analysis Method(OHAM). The residual errors of the OHAM method have been shown physically and numerically. The important physical parameters of skin friction and Nusselt number have been calculated and discussed. The other embedding parameters like generalized magnetic parameter, Prantl number, nanofluid volume fraction and Eckert number have been intended and discussed. The obtained results have been compared with the Numerical(ND-Solve) method for both sorts of CNTs. The closed agreement of both methods has been achieved. | GOHAR TAZA Gul WARIS Khan MUHAMMAD Shuaib MUHAMMAD Altaf Khan EBENEZER Bonyah | 2019 | Journal of Thermal Science2019，28，1： | 1 |
| 3 | Automated Controller Placement for Software-Defined Networks to Resist DDoS Attacks显示文摘In software-defined networks(SDNs),controller placement is a critical factor in the design and planning for the future Internet of Things(IoT),telecommunication,and satellite communication systems.Existing research has concentrated largely on factors such as reliability,latency,controller capacity,propagation delay,and energy consumption.However,SDNs are vulnerable to distributed denial of service(DDoS)attacks that interfere with legitimate use of the network.The ever-increasing frequency of DDoS attacks has made it necessary to consider them in network design,especially in critical applications such as military,health care,and financial services networks requiring high availability.We propose a mathematical model for planning the deployment of SDN smart backup controllers(SBCs)to preserve service in the presence of DDoS attacks.Given a number of input parameters,our model has two distinct capabilities.First,it determines the optimal number of primary controllers to place at specific locations or nodes under normal operating conditions.Second,it recommends an optimal number of smart backup controllers for use with different levels of DDoS attacks.The goal of the model is to improve resistance to DDoS attacks while optimizing the overall cost based on the parameters.Our simulated results demonstrate that the model is useful in planning for SDN reliability in the presence of DDoS attacks while managing the overall cost. | Muhammad Reazul Haque Saw Chin Tan Zulfadzli Yusoff Kashif Nisar Lee Ching Kwang Rizaludin Kaspin Bhawani Shankar Chowdhry Rajkumar Buyya Satya Prasad Majumder Manoj Gupta Shuaib Memon | 2021 | Computers, Materials & Continua2021，，9： | 0 |
| 4 | Fuzzy-Based Automatic Epileptic Seizure Detection Framework显示文摘Detection of epileptic seizures on the basis of Electroencephalogram(EEG)recordings is a challenging task due to the complex,non-stationary and non-linear nature of these biomedical signals.In the existing literature,a number of automatic epileptic seizure detection methods have been proposed that extract useful features from EEG segments and classify them using machine learning algorithms.Some characterizing features of epileptic and non-epileptic EEG signals overlap;therefore,it requires that analysis of signals must be performed from diverse perspectives.Few studies analyzed these signals in diverse domains to identify distinguishing characteristics of epileptic EEG signals.To pose the challenge mentioned above,in this paper,a fuzzy-based epileptic seizure detection model is proposed that incorporates a novel feature extraction and selection method along with fuzzy classifiers.The proposed work extracts pattern features along with time-domain,frequencydomain,and non-linear analysis of signals.It applies a feature selection strategy on extracted features to get more discriminating features that build fuzzy machine learning classifiers for the detection of epileptic seizures.The empirical evaluation of the proposed model was conducted on the benchmark Bonn EEG dataset.It shows significant accuracy of 98%to 100%for normal vs.ictal classification cases while for three class classification of normal vs.inter-ictal vs.ictal accuracy reaches to above 97.5%.The obtained results for ten classification cases(including normal,seizure or ictal,and seizure-free or inter-ictal classes)prove the superior performance of proposed work as compared to other state-of-the-art counterparts. | Aayesha Muhammad Bilal Qureshi Muhammad Afzaal Muhammad Shuaib Qureshi Jeonghwan Gwak | 2022 | Computers, Materials & Continua2022，，3： | 0 |
| 5 | 甘氨酸钠水溶液在298.15K到343.15K温度下非沉淀方法中的理化性质(英文)显示文摘The physicochemical properties,including the density,viscosity,and refractive index of aqueous solutions of sodium glycinate as a solvent for CO_2 absorption in the non-precipitation regime were measured under the wide temperature range of 298.15 to 343.15 K.The concentration of the sodium glycinate in an aqueous form in the non-precipitation regime was identified up to 2.0 mol ? L^(-1).The coefficients of thermal expansion values were estimated from measured density data.It was found that,the densities,viscosities and refractive indices of the aqueous sodium glycinate decrease with an increase in temperature,whereas with increasing sodium glycinate concentration in the solution,all three properties increase.Thermal expansion coefficients slightly increase with rising temperature and concentration.The measured values of density,viscosity and refractive index were correlated as a function of temperature by using the least squares method.The predicted data obtained from correlation equations for all measured properties were in fairly good agreement with the experimental data. | Muhammad Shuaib Shaikh Azmi Mohd Shariff Mohd Azmi Bustam Ghulam Murshid | 2015 | Chinese Journal of Chemical Engineering2015，23，3： | 0 |
| 6 | Experimental studies and artificial neural network modeling of surface tension of aqueous sodium L-prolinate solutions and piperazine blends显示文摘The surface tension study is very crucial for the design of CO2 gas absorption contacting equipment. The significance of the surface tension has been increasing due to its consideration in various technological fields. This property influences the mass transfer and hydrodynamics of gas absorption systems, mainly multiphase systems, in which the interface between gas and liquid exists. Therefore, in this study, surface tension of aqueous solutions of sodium L-prolinate(SP) and piperazine(PZ) blends were measured at ten different temperatures from(298.15 to 343.15) K. The SP mass fractions were 0.10, 0.20, and 0.30;while the mass fractions of PZ were 0.02 and 0.05. The experimental results showed that the surface tension increase with increasing the mass fractions of SP and PZ in aqueous blends, and decrease linearly with rising temperature. The experimental data of surface tension were correlated by two empirical correlations as a function of temperature and mass fractions for estimating the predicted data using the optimized correlation coefficients. Moreover, the modeling of surface tension data was carried out using Artificial Neural Network(ANN) approach. The results obtianed from ANN modeling were compared with applied empirical correlation. It was found that the ANN approach outperformed the empirical correlation used in this study. Besides, a quantitative analysis of variation(ANOVA) was performed in order to determine the significance of data. The surface tension of aqueous SP and SP + PZ was also compared with various conventional solvents. | Muhammad Shuaib Shaikh A.M.Shariff M.A.Bustam Sahil Garg Khadija Qureshi Pervez Hameed Shaikh Inamullah Bhatti | 2019 | Chinese Journal of Chemical Engineering2019，27，8： | 0 |
| 7 | A Survey on the Role of Complex Networks in IoT and Brain Communication显示文摘Complex networks on the Internet of Things(IoT)and brain communication are the main focus of this paper.The benefits of complex networks may be applicable in the future research directions of 6G,photonic,IoT,brain,etc.,communication technologies.Heavy data traffic,huge capacity,minimal level of dynamic latency,etc.are some of the future requirements in 5G+and 6G communication systems.In emerging communication,technologies such as 5G+/6G-based photonic sensor communication and complex networks play an important role in improving future requirements of IoT and brain communication.In this paper,the state of the complex system considered as a complex network(the connection between the brain cells,neurons,etc.)needs measurement for analyzing the functions of the neurons during brain communication.Here,we measure the state of the complex system through observability.Using 5G+/6G-based photonic sensor nodes,finding observability influenced by the concept of contraction provides the stability of neurons.When IoT or any sensors fail to measure the state of the connectivity in the 5G+or 6G communication due to external noise and attacks,some information about the sensor nodes during the communication will be lost.Similarly,neurons considered sing the complex networks concept neuron sensors in the brain lose communication and connections.Therefore,affected sensor nodes in a contraction are equivalent to compensate for maintaining stability conditions.In this compensation,loss of observability depends on the contraction size which is a key factor for employing a complex network.To analyze the observability recovery,we can use a contraction detection algorithm with complex network properties.Our survey paper shows that contraction size will allow us to improve the performance of brain communication,stability of neurons,etc.,through the clustering coefficient considered in the contraction detection algorithm.In addition,we discuss the scalability of IoT communication using 5G+/6G-based photonic technology. | Vijey Thayananthan Aiiad Albeshri Hassan A.Alamri Muhammad Bilal Qureshi Muhammad Shuaib Qureshi | 2023 | Computers, Materials & Continua2023，76，9： | 0 |
| 8 | Fractional Analysis of Viscous Fluid Flow with Heat and Mass Transfer Over a Flexible Rotating Disk显示文摘An unsteady viscous fluid flow with Dufour and Soret effect,which results in heat and mass transfer due to upward and downward motion of flexible rotating disk,has been studied.The upward or downward motion of non rotating disk results in two dimensional flow,while the vertical action and rotation of the disk results in three dimensional flow.By using an appropriate transformation the governing equations are transformed into the system of ordinary differential equations.The system of ordinary differential equations is further converted into first order differential equation by selecting suitable variables.Then,we generalize the model by using the Caputo derivative.The numerical result for the fractional model is presented and validated with Runge Kutta order 4 method for classical case.The compared results are presented in Table and Figures.It is concluded that the fractional model is more realistic than that of classical one,because it simulates the fluid behavior at each fractional value rather than the integral values. | Muhammad Shuaib Muhammad Bilal Muhammad Altaf Khan Sharaf J.Malebary | 2020 | Computer Modeling in Engineering & Sciences2020，，4： | 0 |
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