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Improvement in Sensing Accuracy of an OFDM-Based W-Band System

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Journal of Communications and Information Networks 2022年第1期7卷 37-47页

作者： nazar muhammad Idrees Zijie Lu Mu hammad Saqlain Hongqi Zhang Shiwei Wang Lu Zhang Xianbin Yu College of Information Science and Electronic Engineering Zhejiang UniversityHangzhou 310027China Zhejiang Laboratory Hangzhou 31121China

Orthogonal frequency division multiplexing (OFDM) waveform is promising to converge communications and sensing functionalities for future wireless applications. This paper presents a novel method to improve the OFDM-based sensing accuracy by estimating the delay/Doppler leakages in the channel matrix, which is constructed by the received and the transmitted OFDM symbols. Both simulation and proof-of-concept experiment validate the proposed method for sensing *** experiment uses a heterodyne W-band system at 97 GHz to transmit and receive an OFDM waveform of bandwidth 3.9 *** achieve an improvement in sensing accuracy by an order of magnitude which is significant for OFDM-based converged systems.

关键词： communications and sensing delay/Doppler leakage orthogonal frequency division multiplexing sensing accuracy

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太赫兹感知通信一体化波形设计与信号处理

通信学报 2022年第2期43卷 76-88页

作者：余显斌吕治东李涟漪 nazar muhammad Idrees 张鹿浙江大学信息与电子工程学院浙江杭州310027 之江实验室浙江杭州311121

太赫兹波段感知通信一体化技术能够在提高数据传输速率和感知分辨率的同时,有效降低硬件资源和频谱资源的消耗。首先,简要介绍了感知通信一体化及太赫兹通信、感知的现状。然后,分别从感知和通信的角度讨论了一体化波形设计及优化策略,... 详细信息

太赫兹波段感知通信一体化技术能够在提高数据传输速率和感知分辨率的同时,有效降低硬件资源和频谱资源的消耗。首先,简要介绍了感知通信一体化及太赫兹通信、感知的现状。然后,分别从感知和通信的角度讨论了一体化波形设计及优化策略,同时分析了两类信号接收机的信号处理算法,并实验展示了一种97GHz基于OFDM信号的一体化系统,对系统的距离、速度和通信等性能进行了测试。最后,总结和展望了太赫兹感知通信一体化的技术难题和未来研究方向。

关键词：太赫兹感知通信一体化波形设计信号处理算法

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脱氮硫杆菌的筛选及其对锶离子的矿化作用

核化学与放射化学 2017年第2期39卷 187-192页

作者：邬琴琴代群威韩林宝王岩党政赵玉连 nazar muhammad 西南科技大学环境与资源学院四川绵阳621000

放射性污染日益严重,其中锶污染作为土壤典型污染之一成为研究热点。土壤中存在着一些矿化菌,能够对锶离子进行矿化固定。本实验对从土壤中分离的3株脱氮硫杆菌的特性及其对Sr^(2+)的矿化行为进行了研究,发现该菌对1.0g/L模拟Sr^(2+)污... 详细信息

放射性污染日益严重,其中锶污染作为土壤典型污染之一成为研究热点。土壤中存在着一些矿化菌,能够对锶离子进行矿化固定。本实验对从土壤中分离的3株脱氮硫杆菌的特性及其对Sr^(2+)的矿化行为进行了研究,发现该菌对1.0g/L模拟Sr^(2+)污染的去除率可达80%。扫描电子显微镜(SEM)、能谱分析(EDS)、X射线衍射(XRD)、傅里叶变换红外光谱(FTIR)等结果显示,矿化产物为硫酸锶。可见,利用脱氮硫杆菌治理土壤中Sr^(2+)污染具有可行性,该方法将会有一定应用前景。

关键词：脱氮硫杆菌筛选锶矿化

Enhanced urease inhibition activity of Ag nanomaterials capped with N-substituted methyl 5-acetamido-β-resorcylate

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Progress in Natural Science:Materials International 2019年第2期29卷 129-137页

作者： Syeda Sohaila Naz muhammad Raza Shah nazar Ul Islam Syed Sartaj Alam Nanosciences and Technology Department National Centre for Physics Quaid-i-Azam University Campus ICCBS H.E.J.Research Institute of Chemistry University of Karachi Institute of Chemical Sciences University of Peshawar Sarhad University of Science and Information Technology Department of Plant Pathology The University of AgriculturePeshawar Pakistan

Medically, bacterial ureases are important virulent factors and are used for treatment of peptic ulcers and urinary tones. Reported urease inhibitors are associated with various side effects including antibiotic resistance as a major one. Still there is an urgent need to synthesize new urease inhibitors. In this context we have synthesized new urease inhibitor i.e. AgL that is composed of Ag nanomaterials capped with N-substituted methyl 5-acetamido-β-resorcylate(L). The conjugation of L to silver was confirmed through FTIR, UV–vis and TEM *** silver nanomaterials(Ag) were also prepared. The stability of AgL nanostructures was determined against various parameters(temperature, high salt concentration, pH) and found to be stable. The in vitro antimicrobial(antibacterial, antifungal), enzyme inhibition(xanthine oxidase, urease, carbonic anhydrase, α-chymotrypsin,cholinesterase) and antioxidant activities of AgL were investigated and compared with Ag, L and standard *** comparison to other bioactivities, AgL shows statistically enhanced selective enzyme inhibition activity against urease enzyme. Urease inhibition activity of AgL was significantly greater than standard drug(thiourea),L and Ag. On a per weight basis, AgL required about 11–18 times less amount of L for inhibition of urease enzyme.

关键词： β-Resorcylic acid N-Substituted methyl 5-acetamido-β-resorcylate Silver nanomaterials Enhanced urease inhibition activity

Properties of Certain Subclasses of Analytic Functions Involving q-Poisson Distribution

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Computer Modeling in Engineering & Sciences 2022年第6期131卷 1465-1477页

作者： Bilal Khan Zhi-Guo Liu nazar Khan Aftab Hussain Nasir Khan muhammad Tahir School of Mathematical Sciences and Shanghai Key Laboratory of PMMP East China Normal UniversityShanghai200241China Department of Mathematics Abbottabad University of Science and TechnologyAbbottabad22010Pakistan Department of Mathematics King Abdulaziz UniversityJeddah21589Saudi Arabia Department of Mathematics FATA UniversityAkhorwal(Darra Adam Khel)FR Kohat26000Pakistan

By using the basic(or q)-Calculus many subclasses of analytic and univalent functions have been generalized and studied from different viewpoints and *** this paper,we aim to define certain new subclasses of an analytic *** then give necessary and sufficient conditions for each of the defined function *** also study necessary and sufficient conditions for a function whose coefficients are probabilities of q-Poisson *** validate our results,some known consequences are also given in the form of Remarks and Corollaries.

关键词： Analytic function q-difference operator sufficient condition q-Poisson distribution

An Integrated Deep Learning Framework for Fruits Diseases Classification

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Computers, Materials & Continua 2022年第4期71卷 1387-1402页

作者： Abdul Majid muhammad Attique Khan Majed Alhaisoni muhammad Asfand Eyar Usman Tariq nazar Hussain Yunyoung Nam Seifedine Kadry Department of Computer Science HITEC University TaxilaTaxilaPakistan College of Computer Science and Engineering University of Ha’ilHa’ilSaudi Arabia Department of Computer Science Bahria UniversityIslamabad College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz UniversityAl-KhrajSaudi Arabia Department of Computer Science and Engineering Soonchunhyang UniversityAsanKorea Faculty of Applied Computing and Technology Noroff University CollegeKristiansandNorway

:Agriculture has been an important research area in the field of image processing for the last five *** affect the quality and quantity of fruits,thereby disrupting the economy of a *** computerized techniques have been introduced for detecting and recognizing fruit ***,some issues remain to be addressed,such as irrelevant features and the dimensionality of feature vectors,which increase the computational time of the ***,we propose an integrated deep learning framework for classifying fruit *** consider seven types of fruits,i.e.,apple,cherry,blueberry,grapes,peach,citrus,and *** proposed method comprises several important ***,data increase is applied,and then two different types of features are *** the first feature type,texture and color features,i.e.,classical features,are *** the second type,deep learning characteristics are extracted using a pretrained *** pretrained model is reused through transfer ***,both types of features are merged using the maximum mean value of the serial ***,the resulting fused vector is optimized using a harmonic threshold-based genetic ***,the selected features are classified using multiple *** evaluation is performed on the PlantVillage dataset,and an accuracy of 99%is achieved.A comparison with recent techniques indicate the superiority of the proposed method.

关键词： Fruit diseases data augmentation deep learning classical features features fusion features selection

Performance Analysis of Magnetic Nanoparticles during Targeted Drug Delivery:Application of OHAM

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Computer Modeling in Engineering & Sciences 2022年第2期130卷 723-749页

作者： muhammad Zafar muhammad Saif Ullah Tareq Manzoor Muddassir Ali Kashif nazar Shaukat Iqbal HabibUllah Manzoor Rizwan Haider Woo Young Kim Institute of Energy and Environmental Engineering University of the PunjabQuaid-e-Azam CampusLahore54590Pakistan Energy Research Centre COMSATS University IslamabadLahore54000Pakistan Department of Energy Engineering Faculty of Mechanical and Aeronautical EngineeringUniversity of Engineering and TechnologyTaxila47080Pakistan Department of Mathematics COMSATS University IslamabadLahore54000Pakistan School of Systems and Technology University of Management Sciences and TechnologyLahore54770Pakistan Department of Electrical Electronics and TelecommunicationEngineeringUniversity of Engineering and TechnologyLahore(FSD Campus)Faisalabad38000Pakistan Department of Electronic Engineering Faculty of Applied Energy SystemJeju National UniversityJeju Special Self-Governing ProvinceJeju-si63243Korea

In recent years,the emergence of nanotechnology experienced incredible development in the field of medical *** the past decade,investigating the characteristics of nanoparticles during fluid flow has been one of the intriguing *** distribution and uniformity have emerged as substantial criteria in both medical and engineering *** effects of chemotherapy on healthy tissues are known to be a significant concern during cancer therapy.A novel treatment method of magnetic drug targeting(MDT)has emerged as a promising topical cancer treatment along with some attractive advantages of improving efficacy,fewer side effects,and reduce drug *** magnetic drug targeting,the appropriate movement of nanoparticles(magnetic)as carriers is essential for the therapeutic process in the blood clot removal,infection treatment,and tumor cell *** this study,we have numerically investigated the behavior of an unsteady blood flowinfused with magnetic nanoparticles during MDT under the influence of a uniform external magnetic field in a *** optimal homotopy asymptotic method(OHAM)is employed to compute the governing equation for unsteady electromagnetohydrodynamics *** influence of Hartmann number(Ha),particle mass parameter(G),particle concentration parameter(R),and electro-osmotic parameter(k)is investigated on the velocity of magnetic nanoparticles and blood *** obtained show that the electro-osmotic parameter,along with Hartmann’s number,dramatically affects the velocity of magnetic nanoparticles,blood flow velocity,and flow ***,results also reveal that at a higher Hartman number,homogeneity in nanoparticles distribution improved *** particle concentration andmass parameters effectively influence the capturing effect on nanoparticles in the blood flow using a micro-tube for magnetic drug ***,investigation also indicates that the OHAM analysis is efficient and quick to h

关键词： Hartmann number magnetic nanoparticles nonlinear analysis targeted drug delivery optimal homotopy asymptotic method(OHAM)

Multiclass Stomach Diseases Classication Using Deep Learning Features Optimization

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Computers, Materials & Continua 2021年第6期67卷 3381-3399页

作者： muhammad Attique Khan Abdul Majid nazar Hussain Majed Alhaisoni Yu-Dong Zhang Seifedine Kadry Yunyoung Nam Department of Computer Science HITEC UniversityTaxila47040Pakistan College of Computer Science and Engineering University of Ha’ilHa’ilSaudi Arabia Department of Informatics University of LeicesterLeicesterUK Department of Mathematics and Computer Science Faculty of ScienceBeirut Arab UniversityLebanon Department of Computer Science and Engineering Soonchunhyang UniversityAsanKorea

In the area of medical image processing,stomach cancer is one of the most important cancers which need to be diagnose at the early *** this paper,an optimized deep learning method is presented for multiple stomach disease *** proposed method work in few important steps—preprocessing using the fusion of ltering images along with Ant Colony Optimization(ACO),deep transfer learning-based features extraction,optimization of deep extracted features using nature-inspired algorithms,and nally fusion of optimal vectors and classication using Multi-Layered Perceptron Neural Network(MLNN).In the feature extraction step,pretrained Inception V3 is utilized and retrained on selected stomach infection classes using the deep transfer learning *** on,the activation function is applied to Global Average Pool(GAP)for feature ***,the extracted features are optimized through two different nature-inspired algorithms—Particle Swarm Optimization(PSO)with dynamic tness function and Crow Search Algorithm(CSA).Hence,both methods’output is fused by a maximal value approach and classied the fused feature vector by *** datasets are used to evaluate the proposed method—CUI WahStomach Diseases and Combined dataset and achieved an average accuracy of 99.5%.The comparison with existing techniques,it is shown that the proposed method shows signicant performance.

关键词： Stomach infections deep features features optimization fusion classication

Multiclass Cucumber Leaf Diseases Recognition Using Best Feature Selection

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Computers, Materials & Continua 2022年第2期70卷 3281-3294页

作者： nazar Hussain muhammad Attique Khan Usman Tariq Seifedine Kadry muhammad Asfand E.Yar Almetwally M.Mostafa Abeer Ali Alnuaim Shafiq Ahmad Department of Computer Science HITEC University TaxilaTaxilaPakistan College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz UniversityAl-KhrajSaudi Arabia Department of Applied Data Science Noroff University CollegeNorway Department of Computer Science Bahria UniversityIslamabadPakistan Department of Information Systems College of Computer and Information SciencesKing Saud UniversityRiyadh11543KSASaudi Arabia Department of natural and engineering sciences College of Applied Studies and Community ServiceKing Saud UniversityRiyadh11421Saudi Arabia Faculty of Engineering Industrial Engineering DepartmentKing Saud UniversityRiyadh11421Saudi Arabia

Agriculture is an important research area in the field of visual recognition by *** diseases affect the quality and yields of ***-stage identification of crop disease decreases financial losses and positively impacts crop *** manual identification of crop diseases,which aremostly visible on leaves,is a very time-consuming and costly *** this work,we propose a new framework for the recognition of cucumber leaf *** proposed framework is based on deep learning and involves the fusion and selection of the best *** the feature extraction phase,VGG(Visual Geometry Group)and Inception V3 deep learning models are considered and *** fine-tuned models are trained using deep transfer *** are extracted in the later step and fused using a parallel maximum fusion *** the later step,best features are selected usingWhale Optimization *** best-selected features are classified using supervised learning algorithms for the final classification *** experimental process was conducted on a privately collected dataset that consists of five types of cucumber disease and achieved accuracy of 96.5%.A comparison with recent techniques shows the significance of the proposed method.

关键词： Cucumber diseases database preparation deep learning parallel fusion features selection