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| 1 | Surfactant-decorated graphite nanoplatelets(GNPs) reinforced aluminum nanocomposites: sintering effects on hardness and wear显示文摘The exceptional properties of graphene make it ideal as a reinforcement to enhance the properties of aluminum matrices and this critically depends on uniform dispersion. In this study, the dispersion issue was addressed by sonication and non-covalent surface functionalization of graphite nanoplatelets(GNPs) using two types of surfactant: anionic(sodium dodecyl benzene sulfate(SDBS)) and non-ionic polymeric(ethyl cellulose(EC)). After colloidal mixing with Al powder, consolidation was performed at two sintering temperatures(550 and 620°C). The structure, density, mechanical and wear properties of the nanocomposite samples were investigated and compared with a pure Al and a pure GNPs/Al nanocomposite sample. Noticeably, EC-based 0.5 wt% GNPs/Al samples showed the highest increment of 31% increase in hardness with reduced wear rate of 98.25% at 620°C, while a 22% increase in hardness with reduced wear rate of 96.98% at 550°C was observed, as compared to pure Al. Microstructural analysis and the overall results validate the use of EC-based GNPs/Al nanocomposites as they performed better than pure Al and pure GNPs/Al nanocomposite at both sintering temperatures. | Zeeshan Baig Othman Mamat Mazli Mustapha Asad Mumtaz Sadaqat Ali Mansoor Sarfraz | 2018 | International Journal of Minerals,Metallurgy and Materials2018，25，6： | 3 |
| 2 | Estimation of genetic diversity among sunflower genotypes through random amplified polymorphic DNA analysis显示文摘 | Iqbal MA Sadaqat HA Khan IA | 2008 | Genet Mol Res2008，7，4： | 1 |
| 3 | Estimation of genetic diversity among sunflower genotypes through random amplified polymorphic DNA analysis显示文摘 | Iqbal MA Sadaqat HA Khan IA | 2008 | Genet Mol Res2008，7，4： | 1 |
| 4 | Hippocampal neurodegeneration in experimental autoimmune encephalomyelitis (EAE): potential role of inflammation activated myeloperoxidase显示文摘 | Mir Sajad Jamil Zargan Raman Chawla Sadiq Umar Mir Sadaqat Haider A. Khan | 2009 | Molecular and Cellular Biochemistry (-)2009，，1： | 1 |
| 5 | Multi-Scale Attention-Based Deep Neural Network for Brain Disease Diagnosis显示文摘Whole brain functional connectivity(FC)patterns obtained from resting-state functional magnetic resonance imaging(rs-fMRI)have been widely used in the diagnosis of brain disorders such as autism spectrum disorder(ASD).Recently,an increasing number of studies have focused on employing deep learning techniques to analyze FC patterns for brain disease classification.However,the high dimensionality of the FC features and the interpretation of deep learning results are issues that need to be addressed in the FC-based brain disease classification.In this paper,we proposed a multi-scale attention-based deep neural network(MSA-DNN)model to classify FC patterns for the ASD diagnosis.The model was implemented by adding a flexible multi-scale attention(MSA)module to the auto-encoder based backbone DNN,which can extract multi-scale features of the FC patterns and change the level of attention for different FCs by continuous learning.Our model will reinforce the weights of important FC features while suppress the unimportant FCs to ensure the sparsity of the model weights and enhance the model interpretability.We performed systematic experiments on the large multi-sites ASD dataset with both ten-fold and leaveone-site-out cross-validations.Results showed that our model outperformed classical methods in brain disease classification and revealed robust intersite prediction performance.We also localized important FC features and brain regions associated with ASD classification.Overall,our study further promotes the biomarker detection and computer-aided classification for ASD diagnosis,and the proposed MSA module is flexible and easy to implement in other classification networks. | Yin Liang Gaoxu Xu Sadaqat ur Rehman | 2022 | Computers, Materials & Continua2022，，9： | 1 |
| 6 | Medicinal plants of family Cucurbitaceae (Part-2)显示文摘 | Sadaqat 1995 | 1995 | Hamd Med1995，34，： | 1 |
| 7 | Identity-Based Edge Computing Anonymous Authentication Protocol显示文摘With the development of sensor technology and wireless communication technology,edge computing has a wider range of applications.The privacy protection of edge computing is of great significance.In the edge computing system,in order to ensure the credibility of the source of terminal data,mobile edge computing(MEC)needs to verify the signature of the terminal node on the data.During the signature process,the computing power of edge devices such as wireless terminals can easily become the bottleneck of system performance.Therefore,it is very necessary to improve efficiency through computational offloading.Therefore,this paper proposes an identitybased edge computing anonymous authentication protocol.The protocol realizes mutual authentication and obtains a shared key by encrypting the mutual information.The encryption algorithm is implemented through a thresholded identity-based proxy ring signature.When a large number of terminals offload computing,MEC can set the priority of offloading tasks according to the user’s identity and permissions,thereby improving offloading efficiency.Security analysis shows that the scheme can guarantee the anonymity and unforgeability of signatures.The probability of a malicious node forging a signature is equivalent to cracking the discrete logarithm puzzle.According to the efficiency analysis,in the case of MEC offloading,the computational complexity is significantly reduced,the computing power of edge devices is liberated,and the signature efficiency is improved. | Naixin Kang Zhenhu Ning Shiqiang Zhang Sadaqat ur Rehman Waqas | 2023 | Computers, Materials & Continua2023，，2： | 0 |
| 8 | Use of Scrapped Rubber Tires for Sustainable Construction of Manhole Covers显示文摘Scrapped tires from vehicles are produced in large quantities. Despite numerous existing uses of scrapped tires, alarge quantity ends up at the landfill sites, which contributes to environmental degradation. The development ofmore applications of scrapped tire usage can reduce the disposal of tires at landfill sites. This research proposes anovel use of scrapped tires by using the strips taken from scrapped tires in replacement of steel bars as reinforcement. Manhole covers were produced using scrapped tires by completely replacing the steel with scrapped tires.Four different samples of manhole covers were prepared and tested. The highest bearing capacity of 25.5 kN wasrecorded with a sample of 100 mm thickness made with cementitious composite, which is 2.25 times higher thanthe bearing capacity of a conventional reinforced-concrete manhole cover. The use of manhole covers made withscrapped tires can effectively address the theft issue of manhole covers. The lifecycle cost analysis shows that themanhole cover made with scrapped tires is 3.4 times more cost-effective in comparison with the conventionalmanhole cover. This research shows a new avenue of the potential use of scrapped tires as reinforcement in structures, which can improve sustainable construction practices. | Sadaqat Ullah Khan Afzal Ahmed Sajjad Ali Ayesha Ayub Ahmed Shuja Muhammad Ahsan Shahid | 2021 | Journal of Renewable Materials2021，9，5： | 0 |
| 9 | Authentication of Vehicles and Road Side Units in Intelligent Transportation System显示文摘Security threats to smart and autonomous vehicles cause potential consequences such as traffic accidents,economically damaging traffic jams,hijacking,motivating to wrong routes,and financial losses for businesses and governments.Smart and autonomous vehicles are connected wirelessly,which are more attracted for attackers due to the open nature of wireless communication.One of the problems is the rogue attack,in which the attacker pretends to be a legitimate user or access point by utilizing fake identity.To figure out the problem of a rogue attack,we propose a reinforcement learning algorithm to identify rogue nodes by exploiting the channel state information of the communication link.We consider the communication link between vehicle-to-vehicle,and vehicle-to-infrastructure.We evaluate the performance of our proposed technique by measuring the rogue attack probability,false alarm rate(FAR),mis-detection rate(MDR),and utility function of a receiver based on the test threshold values of reinforcement learning algorithm.The results show that the FAR and MDR are decreased significantly by selecting an appropriate threshold value in order to improve the receiver’s utility. | Muhammad Waqas Shanshan Tu Sadaqat Ur Rehman Zahid Halim Sajid Anwar Ghulam Abbas Ziaul Haq Abbas Obaid Ur Rehman | 2020 | Computers, Materials & Continua2020，，7： | 0 |
| 10 | Emotion Recognition from Occluded Facial Images Using Deep Ensemble Model显示文摘Facial expression recognition has been a hot topic for decades,but high intraclass variation makes it challenging.To overcome intraclass variation for visual recognition,we introduce a novel fusion methodology,in which the proposed model first extract features followed by feature fusion.Specifically,RestNet-50,VGG-19,and Inception-V3 is used to ensure feature learning followed by feature fusion.Finally,the three feature extraction models are utilized using Ensemble Learning techniques for final expression classification.The representation learnt by the proposed methodology is robust to occlusions and pose variations and offers promising accuracy.To evaluate the efficiency of the proposed model,we use two wild benchmark datasets Real-world Affective Faces Database(RAF-DB)and AffectNet for facial expression recognition.The proposed model classifies the emotions into seven different categories namely:happiness,anger,fear,disgust,sadness,surprise,and neutral.Furthermore,the performance of the proposed model is also compared with other algorithms focusing on the analysis of computational cost,convergence and accuracy based on a standard problem specific to classification applications. | Zia Ullah Muhammad Ismail Mohmand Sadaqat ur Rehman Muhammad Zubair Maha Driss Wadii Boulila Rayan Sheikh Ibrahim Alwawi | 2022 | Computers, Materials & Continua2022，，12： | 0 |
| 11 | Power Allocation Strategy for Secret Key Generation Method in Wireless Communications显示文摘Secret key generation(SKG)is an emerging technology to secure wireless communication from attackers.Therefore,the SKG at the physical layer is an alternate solution over traditional cryptographic methods due to wireless channels’uncertainty.However,the physical layer secret key generation(PHY-SKG)depends on two fundamental parameters,i.e.,coherence time and power allocation.The coherence time for PHY-SKG is not applicable to secure wireless channels.This is because coherence time is for a certain period of time.Thus,legitimate users generate the secret keys(SKs)with a shorter key length in size.Hence,an attacker can quickly get information about the SKs.Consequently,the attacker can easily get valuable information from authentic users.Therefore,we considered the scheme of power allocation to enhance the secret key generation rate(SKGR)between legitimate users.Hence,we propose an alternative method,i.e.,a power allocation,to improve the SKGR.Our results show 72%higher SKGR in bits/sec by increasing power transmission.In addition,the power transmission is based on two important parameters,i.e.,epsilon and power loss factor,as given in power transmission equations.We found out that a higher value of epsilon impacts power transmission and subsequently impacts the SKGR.The SKGR is approximately 40.7%greater at 250 from 50 mW at epsilon=1.The value of SKGR is reduced to 18.5%at 250 mW when epsilonis 0.5.Furthermore,the transmission power is also measured against the different power loss factor values,i.e.,3.5,3,and 2.5,respectively,at epsilon=0.5.Hence,it is concluded that the value of epsilon and power loss factor impacts power transmission and,consequently,impacts the SKGR. | Bin Zhang Muhammad Waqas Shanshan Tu Syed Mudassir Hussain Sadaqat Ur Rehman | 2021 | Computers, Materials & Continua2021，，8： | 0 |
| 12 | An Efficient Impersonation Attack Detection Method in Fog Computing显示文摘Fog computing paradigm extends computing,communication,storage,and network resources to the network’s edge.As the fog layer is located between cloud and end-users,it can provide more convenience and timely services to end-users.However,in fog computing(FC),attackers can behave as real fog nodes or end-users to provide malicious services in the network.The attacker acts as an impersonator to impersonate other legitimate users.Therefore,in this work,we present a detection technique to secure the FC environment.First,we model a physical layer key generation based on wireless channel characteristics.To generate the secret keys between the legitimate users and avoid impersonators,we then consider a Double Sarsa technique to identify the impersonators at the receiver end.We compare our proposed Double Sarsa technique with the other two methods to validate our work,i.e.,Sarsa and Q-learning.The simulation results demonstrate that the method based on Double Sarsa outperforms Sarsa and Q-learning approaches in terms of false alarm rate(FAR),miss detection rate(MDR),and average error rate(AER). | Jialin Wan Muhammad Waqas Shanshan Tu Syed Mudassir Hussain Ahsan Shah Sadaqat Ur Rehman Muhammad Hanif | 2021 | Computers, Materials & Continua2021，，7： | 0 |
| 13 | Enhanced Nature Inspired-Support Vector Machine for Glaucoma Detection显示文摘Glaucoma is a progressive eye disease that can lead to blindness if left untreated.Early detection is crucial to prevent vision loss,but current manual scanning methods are expensive,time-consuming,and require specialized expertise.This study presents a novel approach to Glaucoma detection using the Enhanced Grey Wolf Optimized Support Vector Machine(EGWO-SVM)method.The proposed method involves preprocessing steps such as removing image noise using the adaptive median filter(AMF)and feature extraction using the previously processed speeded-up robust feature(SURF),histogram of oriented gradients(HOG),and Global features.The enhanced Grey Wolf Optimization(GWO)technique is then employed with SVM for classification.To evaluate the proposed method,we used the online retinal images for glaucoma analysis(ORIGA)database,and it achieved high accuracy,sensitivity,and specificity rates of 94%,92%,and 92%,respectively.The results demonstrate that the proposed method outperforms other current algorithms in detecting the presence or absence of Glaucoma.This study provides a novel and effective approach to Glaucoma detection that can potentially improve the detection process and outcomes. | Jahanzaib Latif Shanshan Tu Chuangbai Xiao Anas Bilal Sadaqat Ur Rehman Zohaib Ahmad | 2023 | Computers, Materials & Continua2023，，7： | 0 |
| 14 | A Cross-Domain Trust Model of Smart City IoT Based on Self-Certification显示文摘Smart city refers to the information system with Intemet of things and cloud computing as the core tec hnology and government management and industrial development as the core content,forming a large scale,heterogeneous and dynamic distributed Internet of things environment between different Internet of things.There is a wide demand for cooperation between equipment and management institutions in the smart city.Therefore,it is necessary to establish a trust mechanism to promote cooperation,and based on this,prevent data disorder caused by the interaction between honest terminals and malicious temminals.However,most of the existing research on trust mechanism is divorced from the Internet of things environment,and does not consider the characteristics of limited computing and storage capacity and large differences of Internet of hings devices,resuling in the fact that the research on abstract trust trust mechanism cannot be directly applied to the Internet of things;On the other hand,various threats to the Internet of things caused by security vulnerabilities such as collision attacks are not considered.Aiming at the security problems of cross domain trusted authentication of Intelligent City Internet of things terminals,a cross domain trust model(CDTM)based on self-authentication is proposed.Unlike most trust models,this model uses self-certified trust.The cross-domain process of internet of things(IoT)terminal can quickly establish a trust relationship with the current domain by providing its trust certificate stored in the previous domain interaction.At the same time,in order to alleviate the collision attack and improve the accuracy of trust evaluation,the overall trust value is calculated by comprehensively considering the quantity weight,time attenuation weight and similarity weight.Finally,the simulation results show that CDTM has good anti collusion attack ability.The success rate of malicious interaction will not increase significantly.Compared with other models,the resource consumption of our proposed model is significantly reduced. | Yao Wang Yubo Wang Zhenhu Ning Sadaqat ur Rehman Muhammad Waqas | 2023 | Intelligent Automation & Soft Computing2023，，4： | 0 |
| 15 | Application of acidic protease in the pickling to simplify the pelt bating process显示文摘Traditionally,universally used pelt bating technologies rely on the application of trypsin,neutral and alkaline microbial proteases but suffer from complicated operation,limited bating efficiency and unsatisfac-tory leather performance.Therefore,devising a new pelt bating approach to achieve high bating efficiency and excellent leather performance has always been wished for by the leather industry.To pursue this goal,years of persistent research work enabled us to develop a novel approach for pelt bating by means of acidic proteases in pickling process.Initially,basic enzymatic characteristics and bating effectiveness of several typical acidic pro-teases in pelt pickling medium were investigated;then,the bating effectiveness through the quantitative charac-terization of protease activity of the optimal acidic protease was compared with that of the conventional bating enzyme.The results indicated that all of the selected acidic proteases had good salt-tolerance and exhibited optimum activity at pH 3.0–4.0.The novel pickling-bating method based on microbial origin acidic protease L80A led to an outstanding performance on pelt bating at the dosage of 150 U/mL of collagenolytic activity.The bating effectiveness of acidic protease L80A was comparable to and even better than that of trypsin BEM due to its mod-erate proteolytic ability.Moreover,the deep and even penetration of acidic protease in the pelt permitted it to produce soft,organoleptically stable and overall better quality crust leather than that of the conventional trypsin bating method.Additionally,pelt bating was performed along with the pickling process without extra inactiva-tion and washing operation,making the bating operation more efficient,economical,and environment friendly.Results had made us to conclude that this cutting-edge acidic proteases based pickling-bating method could be the first step/way forward to replace the decades-old traditional pelt bating technology. | Xu Zhang Mengchu Gao Sadaqat Ali Chattha Yiwen Zhu Biyu Peng Yongbin Ye | 2021 | Journal of Leather Science and Engineering2021，3，1： | 0 |
| 16 | QoS-Aware Cloud Service Optimization Algorithm in Cloud Manufacturing Environment显示文摘In a cloud manufacturing environment with abundant functionally equivalent cloud services,users naturally desire the highest-quality service(s).Thus,a comprehensive measurement of quality of service(QoS)is needed.Opti-mizing the plethora of cloud services has thus become a top priority.Cloud ser-vice optimization is negatively affected by untrusted QoS data,which are inevitably provided by some users.To resolve these problems,this paper proposes a QoS-aware cloud service optimization model and establishes QoS-information awareness and quantification mechanisms.Untrusted data are assessed by an information correction method.The weights discovered by the variable precision Rough Set,which mined the evaluation indicators from historical data,providing a comprehensive performance ranking of service quality.The manufacturing cloud service optimization algorithm thus provides a quantitative reference for service selection.In experimental simulations,this method recommended the optimal services that met users’needs,and effectively reduced the impact of dis-honest users on the selection results. | Wenlong Ma Youhong Xu Jianwei Zheng Sadaqat ur Rehman | 2023 | Intelligent Automation & Soft Computing2023，37，8： | 0 |
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