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Analysis of 3D localization in underwater optical wireless networks with uncertain anchor positions

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Science China(Information Sciences) 2020年第10期63卷 174-181页

作者： nasir saeed Abdulkadir CELIK Mohamed-Slim ALOUINI Tareq Y.AL-NAFFOURI Computer ElectricalMathematical Sciences & Engineering (CEMSE) DivisionKing Abdullah University of Science and Technology (KAUST)

Localization accuracy is of paramount importance for the proper operation of underwater optical wireless sensor networks(UOWSNs). However, underwater localization is prone to hostile environmental impediments such as drifts owing to the surface and deep currents. These cause uncertainty in the deployed anchor node positions and pose daunting challenges to achieve accurate location estimations. Therefore, this paper analyzes the performance of three-dimensional(3D) localization for UOWSNs and derives a closedform expression for the Cramer Rao lower bound(CRLB) by using time of arrival(ToA) and angle of arrival(AoA) measurements under the presence of uncertainty in anchor node positions. Numerical results validate the analytical findings by comparing the localization accuracy in scenarios with and without anchor nodes position uncertainty. Results are also compared with the linear least square(LLS) method and weighted LLS(WLLS) method.

关键词： underwater optical wireless sensor networks localization three-dimensional uncertainty

Robust graph‐based localization for industrial Internet of things in the presence of flipping ambiguities

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CAAI Transactions on Intelligence Technology 2023年第4期8卷 1140-1149页

作者： Mian Imtiaz ul Haq Ruhul Amin Khalil Muhannad Almutiry Ahmad Sawalmeh Tanveer Ahmad nasir saeed Faculty of Electrical Engineering Swedish College of Engineering and TechnologyWah CanttPakistan Department of Electrical Engineering Faculty of Electrical and Computer EngineeringUniversity of Engineering and TechnologyPeshawarPakistan Department of Electrical Engineering Remote Sensing UnitNorthern Border UniversityArarSaudi Arabia Data Science and Artificial Intelligence Department‐College of Science and Information Technology Irbid National UniversityIrbadJordan Innovation Education and Research Center for On‐Device AI Software(Bk21) Department of Computer Science and EngineeringChungnam National UniversityDaejeonRepublic of Korea Department of Electrical and Communication Engineering United Arab Emirates University(UAEU)Al AinUnited Arab Emirates

Localisation of machines in harsh Industrial Internet of Things(IIoT)environment is necessary for various ***,a novel localisation algorithm is proposed for noisy range measurements in IIoT *** position of an unknown machine device in the network is estimated using the relative distances between blind machines(BMs)and anchor machines(AMs).Moreover,a more practical and challenging scenario with the erroneous position of AM is considered,which brings additional uncertainty to the final position ***,the AMs selection algorithm for the localisation of BMs in the IIoT network is *** those AMs will participate in the localisation process,which increases the accuracy of the final location ***,the closed‐form expression of the proposed greedy successive anchorization process is derived,which prevents possible local convergence,reduces computation,and achieves Cramér‐Rao lower bound accuracy for white Gaussian measurement *** results are compared with the state‐of‐the‐art and verified through numerous simulations.

关键词： Cramér‐Rao lower bound greedy successive anchorization industrial internet of things localization

Augmenting IoT Intrusion Detection System Performance Using Deep Neural Network

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Computers, Materials & Continua 2023年第1期74卷 1351-1374页

作者： nasir Sayed Muhammad Shoaib Waqas Ahmed Sultan Noman Qasem Abdullah M.Albarrak Faisal saeed Department of Computer Science Islamia College PeshawarPeshawar25120Pakistan Department of Computer Science CECOS University of IT and Emerging SciencesPeshawar25000Pakistan Department of Electrical Engineering HITEC University TaxilaTaxila47080Pakistan Computer Science Department College of Computer and Information SciencesImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11432Saudi Arabia DAAI Research Group Department of Computing and Data ScienceSchool of Computing and Digital TechnologyBirmingham City UniversityBirminghamB47XGUK

Due to their low power consumption and limited computing power,Internet of Things(IoT)devices are difficult to ***,the rapid growth of IoT devices in homes increases the risk of *** detection systems(IDS)are commonly employed to prevent *** systems detect incoming attacks and instantly notify users to allow for the implementation of appropriate *** have been made in the past to detect new attacks using machine learning and deep learning techniques,however,these efforts have been *** this paper,we propose two deep learning models to automatically detect various types of intrusion attacks in IoT ***,we experimentally evaluate the use of two Convolutional Neural Networks(CNN)to detect nine distinct types of attacks listed in the NF-UNSW-NB15-v2 *** accomplish this goal,the network stream data were initially converted to twodimensional images,which were then used to train the neural network *** also propose two baseline models to demonstrate the performance of the proposed ***,both models achieve high accuracy in detecting the majority of these nine attacks.

关键词： Internet of things intrusion detection system deep learning convolutional neural network supervised learning

Antimicrobial activities of methanolic extract of Carissa opaca roots and its fractions and compounds isolated from the most active ethyl acetate fraction

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Asian Pacific Journal of Tropical Biomedicine 2015年第7期5卷 533-537页

作者： Dildar Ahmed Ramsha saeed nasir Shakeel Khaizran Fatima Aneela Arshad Department of Chemistry Forman Christian College (A Chartered University) Microbiology Lab Pharmagen Lahore Pakistan

Objective: To study the antibacterial and antifungal activities of methanolic extract of roots of Carissa opaca and its fractions in hexane, chloroform, ethyl acetate, n-butanol and water, and the isolated ***: The zones of inhibition of the samples against test microorganisms were determined by agar well diffusion method. Minimum inhibitory concentrations of the samples were determined by agar well dilution method. Test microorganisms included four standard bacteria [Bacillus subtilis ATCC 6633(B. subtilis), Escherichia coli ATCC 8739(E. coli), Pseudomonas aeruginosa ATCC 9027(P. aeruginosa), and Staphylococcus aureus ATCC 6538], two standard fungi [Candida albicans ATCC 10231(C. albicans)] and Aspergillus niger, and six clinical isolates(B. subtilis, E. coli, P. aeruginosa, Staphylococcus aureus, Salmonella typhi and Enterobacter cloacae). The most active fraction was investigated to isolate compounds. The chemical compounds isolated from the ethyl acetate fraction were identified by gas chromatography-mass spectrometer, high performance liquid chromatography and liquid chromatography-mass ***: E. coli, P. aeruginosa, and C. albicans were the most susceptible. Less polar fractions exhibited stronger efficacy than polar ones, and ethyl acetate fraction proved to be the most potent. Zones of inhibition of hexane, chloroform and ethyl acetate fractions, and amoxil against C. albicans were 19.96, 22.01, 23.10 and 19.20 mm, respectively. Ethyl acetate faction was the most toxic to all the test microorganisms, with minimum inhibitory concentrations of 8.0, 7.8 and 7.78 μg/m L against P. aeruginosa, C. albicans and B. subtilis, respectively. Isolated compounds, limonene, 2'-hydroxyacetophenone, vanillin, naphthalenone, 2,3,3-trimethyl-2-(3-methylbuta-1,3-dienyl)-6-methylenecyclohexanone, 2-benzenedicarboxylic acid, mono(2-ethylhexyl) ester, β-sitosterol, vitamin E, rutin, quercetin, lupeol, epigallocatechin, showed considerable antimicrobia

关键词： Carissa opaca Antibacterial Antifungal Bioactive compounds

Root-Of-Trust for Continuous Integration and Continuous Deployment Pipeline in Cloud Computing

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Computers, Materials & Continua 2022年第11期73卷 2223-2239页

作者： Abdul Saboor Mohd Fadzil Hassan Rehan Akbar Erwin Susanto Syed nasir Mehmood Shah Muhammad Aadil Siddiqui saeed Ahmed Magsi High-Performance Cloud Computing Centre(HPC3) Department of Computer&Information SciencesUniversiti Teknologi PETRONASSeri IskandarPerakMalaysia Centre for Research in Data Science(CeRDaS) Department of Computer&Information SciencesUniversiti Teknologi PETRONASSeri IskandarPerakMalaysia School of Electrical Engineering Telkom UniversityBandungIndonesia KICSIT Institute of Space Technology(IST)IslamabadPakistan Department of Electrical and Electronics Engineering Universiti Teknologi PETRONASSeri IskandarPerakMalaysia

Cloud computing has gained significant use over the last decade due to its several benefits,including cost savings associated with setup,deployments,delivery,physical resource sharing across virtual machines,and availability of on-demand cloud ***,in addition to usual threats in almost every computing environment,cloud computing has also introduced a set of new threats as consumers share physical resources due to the physical co-location ***,since there are a growing number of attacks directed at cloud environments(including dictionary attacks,replay code attacks,denial of service attacks,rootkit attacks,code injection attacks,etc.),customers require additional assurances before adopting cloud ***,the continuous integration and continuous deployment of the code fragments have made cloud services more prone to security *** this study,the model based on the root of trust for continuous integration and continuous deployment is proposed,instead of only relying on a single signon authentication method that typically uses only id and *** underlying study opted hardware security module by utilizing the Trusted Platform Module(TPM),which is commonly available as a cryptoprocessor on the motherboards of the personal computers and data center *** preliminary proof of concept demonstrated that the TPM features can be utilized through RESTful services to establish the root of trust for continuous integration and continuous deployment pipeline and can additionally be integrated as a secure microservice feature in the cloud computing environment.

关键词： Root of Trust(RoT) Trusted Platform Module(TPM) cryptoprocessor microservices Hardware Security Modules(HSM) DevOps

Energy Theft Identification Using Adaboost Ensembler in the Smart Grids

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Computers, Materials & Continua 2022年第7期72卷 2141-2158页

作者： Muhammad Irfan nasir Ayub Faisal Althobiani Zain Ali Muhammad Idrees saeed Ullah Saifur Rahman Abdullah saeed Alwadie Saleh Mohammed Ghonaim Hesham Abdushkour Fahad Salem Alkahtani Samar Alqhtani Piotr Gas Electrical Engineering Department College of EngineeringNajran University Saudi ArabiaNajran61441Saudi Arabia Department of Computer Science Federal Urdu University of Science and TechnologyIslamabad44000Pakistan Faculty of Maritime Studies King Abdulaziz UniversityJeddah21589Saudi Arabia Department of Electrical Engineering HITEC UniversityTaxila47080Pakistan Department of Computer Science and Engineering University of Engineering and TechnologyNarowal CampusLahore54000Pakistan College of Computer Science and Information Systems Najran UniversityNajran61441Saudi Arabia Department of Electrical and Power Engineering AGH University of Science and Technology Mickiewicza 30 AvenueKrakow30-059Poland

One of the major concerns for the utilities in the Smart Grid(SG)is electricity *** the implementation of smart meters,the frequency of energy usage and data collection from smart homes has increased,which makes it possible for advanced data analysis that was not previously *** this purpose,we have taken historical data of energy thieves and normal *** avoid imbalance observation,biased estimates,we applied the interpolation ***,the data unbalancing issue is resolved in this paper by Nearmiss undersampling technique and makes the data suitable for further *** proposing an improved version of Zeiler and Fergus Net(ZFNet)as a feature extraction approach,we had able to reduce the model’s time *** minimize the overfitting issues,increase the training accuracy and reduce the training loss,we have proposed an enhanced method by merging Adaptive Boosting(AdaBoost)classifier with Coronavirus Herd Immunity Optimizer(CHIO)and Forensic based Investigation Optimizer(FBIO).In terms of low computational complexity,minimized over-fitting problems on a large quantity of data,reduced training time and training loss and increased training accuracy,our model outperforms the benchmark *** proposed algorithms Ada-CHIO andAda-FBIO,have the low MeanAverage Percentage Error(MAPE)value of error,i.e.,6.8%and 9.5%,***,due to the stability of our model our proposed algorithms Ada-CHIO and Ada-FBIO have achieved the accuracy of 93%and 90%.Statistical analysis shows that the hypothesis we proved using statistics is authentic for the proposed technique against benchmark algorithms,which also depicts the superiority of our proposed techniques.

关键词： Smart grids and meters electricity theft detection machine learning AdaBoost optimization techniques

Federated Learning Security and Privacy-Preserving Algorithm and Experiments Research Under Internet of Things Critical Infrastructure

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Tsinghua Science and Technology 2024年第2期29卷 400-414页

作者： nasir Ahmad Jalali Hongsong Chen Department of Computer Science University of Science and Technology Beijing(USTB)Beijing 100083China

The widespread use of the Internet of Things(IoTs)and the rapid development of artificial intelligence technologies have enabled applications to cross commercial and industrial band *** such systems,all participants related to commercial and industrial systems must communicate and generate ***,due to the small storage capacities of IoT devices,they are required to store and transfer the generated data to third-party entity called“cloud”,which creates one single point to store their ***,as the number of participants increases,the size of generated data also ***,such a centralized mechanism for data collection and exchange between participants is likely to face numerous challenges in terms of security,privacy,and *** address these challenges,Federated Learning(FL)has been proposed as a reasonable decentralizing approach,in which clients no longer need to transfer and store real data in the central ***,they only share updated training models that are trained over their private *** the same time,FL enables clients in distributed systems to share their machine learning models collaboratively without their training data,thus reducing data privacy and security ***,slow model training and the execution of additional unnecessary communication rounds may hinder FL applications from operating properly in a distributed ***,these unnecessary communication rounds make the system vulnerable to security and privacy issues,because irrelevant model updates are sent between clients and ***,in this work,we propose an algorithm for fully homomorphic encryption called Cheon-Kim-Kim-Song(CKKS)to encrypt model parameters for their local information privacy-preserving *** proposed solution uses the impetus term to speed up model convergence during the model training ***,it establishes a secure communication channel between IoT devices and the *** a

关键词： Federated Learning(FL) Internet of Things(IoTs) lightweight Transport Layer Security(iTLS) Cheon-Kim-Kim-Song(CKKS)

A Deep Learning Approach for Crowd Counting in Highly Congested Scene

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Computers, Materials & Continua 2022年第12期73卷 5825-5844页

作者： Akbar Khan Kushsairy Abdul Kadir Jawad Ali Shah Waleed Albattah Muhammad saeed Haidawati nasir Megat Norulazmi Megat Mohamed Noor Muhammad Haris Kaka Khel Electrical Section Universiti Kuala Lumpur British Malaysian InstituteSelangor53100Malaysia Department of Electrical Engineering International Islamic UniversityIslamabad44000Pakistan Department of Information Technology College of ComputerQassim UniversityBuraydah51452Saudi Arabia Department of Electrical Engineering National University of Computer and Emerging SciencesIslamabad44000Pakistan Computer Engineering Technology Section Universiti Kuala Lumpur Malaysian Institute of Information TechnologyKuala Lumpur50250Malaysia

With the rapid progress of deep convolutional neural networks,several applications of crowd counting have been proposed and explored in the *** congested scene monitoring,a variety of crowd density estimating approaches has been *** understanding of highly congested scenes for crowd counting during Muslim gatherings of Hajj and Umrah is a challenging task,as a large number of individuals stand nearby and,it is hard for detection techniques to recognize them,as the crowd can vary from low density to high *** deal with such highly congested scenes,we have proposed the Congested Scene Crowd Counting Network(CSCC-Net)using VGG-16 as a core network with its first ten layers due to its strong and robust transfer learning rate.A hole dilated convolutional neural network is used at the back end to widen the relevant field to extract a large range of information from the image without losing its original *** dilated convolution neural network is mainly chosen to expand the kernel size without changing other ***,several loss functions have been applied to strengthen the evaluation accuracy of the ***,the entire experiments have been evaluated using prominent data sets namely,ShanghaiTech parts A,B,UCF_CC_50,and UCF_*** model has achieved remarkable results i.e.,68.0 and 9.0 MAE on ShanghaiTech parts A,B,199.1 MAE on UCF_CC_50,and 99.8 on UCF_QNRF data sets respectively.

关键词： Deep learning congested scene crowd counting fully convolutional neural network dilated convolution

In vitro Selection for Fusarium Wilt Resistance in Gladiolus

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Journal of Integrative Plant Biology 2008年第5期50卷 601-612页

作者： Idrees Ahmad nasir Sheikh Riazuddin National Centre of Excellence in Molecular Biology University of the PunjabCanal BankThokar Niaz Baig Lahore 53700Pakistan

Cormels pieces of four Fusarium susceptible Gladiolus cultivars （Friendship, Peter Pears, Victor Borge and Novalux） formed friable calli when cultured in vitro on Murashige and Skoog basal medium containing various concentrations of auxin and cytokinin. The friable calli established cell suspensions. Plantlet regeneration was obtained from the control callus, control cell suspension derived callus and in vitro selected Fusarium oxysporum Schlecht. resistant cell-lines of Friendship. The in vitro cormlets showed 85-95% germination after breaking dormancy of 8 weeks at 4℃. Cell suspensions of all four Gladiolus cultivars were found to be highly sensitive to fusaric acid. Gradual increase in fusaric acid concentrations to the cell-suspension cultures decreased cell growth considerably. One albino plant was found from the second generation of the in vitro selected cell line of Friendship. The albino plant was found to be highly susceptible to F. oxysporum. The cormlets of all in vitro selected cell lines of Friendship were inoculated with a conidial suspension of the F. oxysporum before planting and were also sprayed with the same spore suspension for further characterization when the height of plants was about 6cm. The four selected cell lines showed the same response whether or not they were inoculated with conidia of the F. oxysporum. Plantlets of all of the selected cell lines exhibited significant growth as compared with the control after application of conidia of the F. oxysporum.

关键词： cell suspension fusaric acid fusadum Gladiolus in vitro selection regeneration.