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Robust Adaptive Multi-Switching Synchronization of Multiple Different Orders Unknown Chaotic Systems

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Journal of Systems Science & Complexity 2020年第5期33卷 1330-1359页

作者： MUHAMMAD Shafiq israr ahmad AMBUSAIDI Mohammed BASHIR Naderi Department of Electrical Engineering Sultan Qaboos UniversityOman Department of General Requirements College of Appled Sciences NizwaOman Department of Mathematics Payame Noor University

Multi-switching synchronizatio of multiple different orders unknown chaotisystems confines hacking in the digital transmission ***,the suppression of undesirable chattering increases synchronization *** paper proposes a new robust synchronization contro technique and discusses the MSS of multiple different orders UC *** controller accomplishe quick convergence reduces the transient oscillations,an the rate of convergence decreases in the vicinity of the origin that causes the suppression of *** based on the Lyapunov direct method assures this convergence behavior with any positive values of the feedback *** work also provides parameters updated law that estimates the true values of unknown *** examples of five UC systems different orders are *** computer based graphical results validate the efficiency and performance of the proposed RASC technique and the synchronization strategy when compare to peer *** the simulation,the proposed synchronization strategy successfully recovers an encrypted received image on a communication *** article suggests some future research problems to extend the use of the proposed work.

关键词： Chaos synchronization Lyapunov stability theory robust adaptive controller unknown chaotic systems

Detection of parathion methyl using a surface plasmon resonance sensor combined with molecularly imprinted films

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Chinese Chemical Letters 2015年第6期26卷 797-800页

作者： Yuan Tan israr ahmad Tian-Xin Wei Key Laboratory of Cluster Science of Ministry of Education Beijing Institute of Technology

An ultra-sensitive and highly selective parathion methyl （PM） detection method by surface plasmon resonance （SPR） combined with molecularly imprinted films （MIF） was developed. The PM-imprinted film was prepared by thermo initiated polymerization on the bare Au surface of an SPR sensor chip, Template PM molecules were quickly removed by an organic solution of acetonitrilelacetic acid （9：1, v/v）, causing a shift of 0.5° in SPR angle. In the concentrations range of 10^-13-10^-10 mol/L, the refractive index showed a gradual increase with higher concentrations of template PM and the changes of SPR angles were linear with the negative logarithm of PM concentrations. In the experiment, the minimum detectable concentration was 10^-13 mol/L. The selectivity of the thin PM-imprinted film against diuron, tetrachlorvinphose and fenitrothion was examined, but no observable binding was detected. The results in the experiment suggested that the MIF had the advantages of high sensitivity and selectivity.

关键词： PM detection Surface plasmon resonance Molecularly imprinted films

Classification of Benign and Malignant Thyroid Nodules in Ultrasound Images

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Classification of Benign and Malignant Thyroid Nodules in Ul...

作者： ahmad israr 华南理工大学

学位级别：硕士

随着计算机视觉技术的进步,医学图像处理已被广泛用于医疗诊断。近年来,为了提高癌症早期检测准确率并改善治疗的效果,特别是在脑癌、肺癌、乳腺癌等肿瘤结节的诊断。超声图像的分辨率较低,并且图像中显示肿瘤的区域通常是模糊的,如边... 详细信息

随着计算机视觉技术的进步,医学图像处理已被广泛用于医疗诊断。近年来,为了提高癌症早期检测准确率并改善治疗的效果,特别是在脑癌、肺癌、乳腺癌等肿瘤结节的诊断。超声图像的分辨率较低,并且图像中显示肿瘤的区域通常是模糊的,如边缘模糊,形状不规则。甲状腺结节是人体内分泌系统常最见的疾病,自动实现结节的良恶性分类可以辅助医生进行相关疾病的诊断。本质上,大多数甲状腺结节是良性的,只有不到5%是恶性的。大多数现有技术都有一些局限性,因为这些技术是在有限的数据集下进行检查和评估并且没有实现自动分类。因此,为了更加准确的实现甲状腺结节良恶性自动分类,我们将卷积神经网络应用于甲状腺结节超声图像的分类。为了提高检测的准确性,我们使用了深度卷积神经网络VGG-16提取结节区域的特征用于分类。在本研究中,VGG-16被用于甲状腺结节的分类。我们在公共数据集和本地数据集上训练和测试了模型。该模型可以较为快速、可靠地对甲状腺癌结节的良恶性进行分类,在医学领域具有一定的应用价值。

关键词：甲状腺结节超声图像卷积神经网络 VGG-16

On the monetary measures of global liquidity

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Financial Innovation 2019年第1期5卷 295-317页

作者： israr ahmad Shah Hashmi Arshad Ali Bhatti School of Economics IIIEInternational Islamic UniversityIslamabadPakistan

This study constructs and examines the dynamics of theoretical and atheoretical measures of global liquidity,using monthly data on the components of broad money over the period 2001 M12-2017 M12 for 39 high income *** group the countries into five regional blocks as categorized by the World Bank:East Asia and the Pacific,Europe and Central Asia,Latin America and the Caribbean,Middle East and North Africa,and North *** atheoretical measures exploited by this study comprise of the simple-sum,GDP-weighted growth rates and PCA based aggregation methods;whereas theoretical measures include the currency equivalent and Divisia index techniques of monetary *** employ a graphical approach to investigate the trends and dynamics of the aggregates overtime,and a cross-correlation between cyclical components of global real economic activity and the lag of cyclical components of the measures of global liquidity to gauge the strength of their *** findings of this study reveal that theoretical measures outperform atheoretical ones in effective delineation of financial and liquidity conditions,and policy *** cyclical components are also strongly associated with those of global real business *** currency equivalent measure,besides being a leading indicator of the shift in policy stance,has a sturdy association with global real business ***,the theoretical measures,as noted by some empirical studies,contain some information content that the atheoretical lack.

关键词： Monetary aggregates Divisia index Currency equivalent Simple-sum GDP-weighted growth rates PCA

Deep Learning Method to Detect the Road Cracks and Potholes for Smart Cities

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Computers, Materials & Continua 2023年第4期75卷 1863-1881页

作者： Hong-Hu Chu Muhammad Rizwan Saeed Javed Rashid Muhammad Tahir Mehmood israr ahmad Rao Sohail Iqbal Ghulam Ali College of Civil Engineering Hunan UniversityChangsha410082China Department of CS University of OkaraOkara56310Pakistan Department of CS&SE Islamic International UniversityIslamabad44000Pakistan Department of IT Services University of OkaraOkara56310Pakistan Department of CS Government College UniversityFaisalabad38000Pakistan Department of Automation Science Beihang UniversityBeijing100191China

The increasing global population at a rapid pace makes road trafficdense;managing such massive traffic is challenging. In developing countrieslike Pakistan, road traffic accidents (RTA) have the highest mortality percentageamong other Asian countries. The main reasons for RTAs are roadcracks and potholes. Understanding the need for an automated system forthe detection of cracks and potholes, this study proposes a decision supportsystem (DSS) for an autonomous road information system for smart citydevelopment with the use of deep learning. The proposed DSS works in layerswhere initially the image of roads is captured and coordinates attached to theimage with the help of global positioning system (GPS), communicated tothe decision layer to find about the cracks and potholes in the roads, andeventually, that information is passed to the road management informationsystem, which gives information to drivers and the maintenance *** the decision layer, we projected a CNN-based model for pothole crackdetection (PCD). Aimed at training, a K-fold cross-validation strategy wasused where the value of K was set to 10. The training of PCD was completedwith a self-collected dataset consisting of 6000 images from Pakistani *** proposed PCD achieved 98% of precision, 97% recall, and accuracy whiletesting on unseen images. The results produced by our model are higher thanthe existing model in terms of performance and computational cost, whichproves its significance.

关键词： Road cracks and potholes CNN smart cities pothole crack detection decision support system

Morphogenetic Study of Pepino and Other Members of Solanaceae Family

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American Journal of Plant Sciences 2014年第26期5卷 3761-3768页

作者： Habib ahmad Ayaz Khan Khushi Muhammad Muhammad Shahid Nadeem Waqar ahmad Sajjad Iqbal Aniqa Nosheen Nazia Akbar israr ahmad Youxiong Que Department of Genetics Hazara University Manshera Pakistan Institute of Chemical and Biological Sciences Department of Botany University of the Gujrat Gujrat Pakistan Key Lab of Sugarcane Biology and Genetic Breeding Ministry of Agriculture Fujian Agriculture and Forestry University Fuzhou China

This paper reports the findings regarding morphology, DNA markers and fruit quality of Solanum muricatum L., a newly introduced fruit in Hazara University, Pakistan, and other locally grown members of the Solanaceae family. In this study, RAPD (Random Amplified Polymorphic NA) based PCR report on phylogenetic affinities of pepino with brinjal, chilies, potato and tomato was also included. Total genomic DNA was isolated and 120 arbitrary decamers were applied to the genomic DNA of all these species. Only five out of the 120 decamers produced 27 polymorphic loci with the range of 400 - 1400 bp. We observed the specificity of markers, and primer B-08 amplified 700 bp locus linked to Solanum muricatum L., (Pepino), which could be used to identify this particular species of this family. Cluster analysis was also performed using the DNAMAN software (version 5.***.2.0) against the bivariate data collected from the products of several decamers. The UPGMA (Unweighted pair Group Method with Arithmetic Mean) analyses depicted three distinct groups, i.e. group I sorted out brinjal-tomato, group II sorted out chili-potato and pepino sorted out into its independent group III. Though on the basis of morphological traits pepino clustered with tomato, its DNA analyses proved it as a distinct species, far more related to the tomato. Moreover a total six parameters in biochemical analysis were studied, which revealed that pepino is a juicy fruit with maximum 93.25% moisture. This study could be helpful to maximize the new crop pepino in Pakistan.

关键词： Phylogeny Genetic Identity PCR Pepino RAPD

Emerging insights into the function of very long chain fatty acids at cerebellar synapses

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Neural Regeneration Research 2025年第6期20卷 1709-1710页

作者： Martin-Paul Agbaga Mohiuddin ahmad Department of Cell Biology and Ophthalmology University of Oklahoma Health Sciences Centerand Dean McGee Eye InstituteOklahoma CityOKUSA

Very long chain-saturated and-polyunsaturated fatty acids(VLC-SFA and VLC-PUFA, respectively) are a functionally important class of fatty acids containing 28 carbons or more in their acyl chain. They are synthesized by the elongation of very long fatty acids-4(ELOVL4) enzyme, expressed mainly in the brain, retina, skin, testes, and meibomian gland, where these fatty acids are found(Agbaga et al., 2008). Further, these organs exhibit tissuespecific VLC-PUFA and VLC-SFA biosynthesis and incorporation into complex lipids for specific functions. In the brain, skin, and Meibomian glands, the ELOVL4 mainly makes VLC-SFA, which are incorporated into complex sphingolipids. In the retina, the ELOVL4 makes VLC-PUFA that are incorporated into phosphatidylcholine, that are critical for visual function, while in testes and sperm, the VLC-PUFA are incorporated into sphingolipids that are critical for fertility(Yeboah et al., 2021).

关键词： functions function insight

Towards a Dynamic Virtual IoT Network Based on User Requirements

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Computers, Materials & Continua 2021年第11期69卷 2231-2244页

作者： Faisal Mehmood Shabir ahmad israr Ullah Faisal Jamil DoHyeun Kim Department of Computer Engineering Jeju National UniversityJeju63243Korea Department of I.T.Convergence Engineering Gachon UniversitySeongnam-Si461-701Korea Department of Software Engineering University of Engineering&Technology MardanMardan23200Pakistan

The data being generated by the Internet of Things needs to be stored,monitored,and analyzed for maximum IoT resource *** Defined Networking has been extensively utilized to address issues such as heterogeneity and ***,for small-scale IoT application,sometimes it is considered an inefficient *** paper proposes an alternate lightweight mechanism to the design and implementation of a dynamic virtual network based on user *** key idea is to provide users a virtual interface that enables them to reconfigure the communication flow between the sensors and actuators at *** throughput of the communication flow depends on the data traffic load and optimal *** can reconfigure the communication flow,and virtual agents find the optimal route to handle the traffic *** virtual network provides a user-friendly interface to allow physical devices to be mapped with the corresponding virtual *** proposed network is applicable for all systems that lie in the Internet of Things *** conclude that the proposed network is efficient,reliable,and responsive to network reconfiguration at runtime.

关键词： Internet of things software-defined networks virtual network inter-process communication cloud of things

Pedestrian Physical Education Training Over Visualization Tool

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Computers, Materials & Continua 2022年第11期73卷 2389-2405页

作者： Tamara al Shloul israr Akhter Suliman A.Alsuhibany Yazeed Yasin Ghadi ahmad Jalal Jeongmin Park Department of Humanities and Social Science Al Ain UniversityAl Ain15551UAE Department of Computer Science Air UniversityIslamabad44000Pakistan Department of Computer Science College of ComputerQassim UniversityBuraydah51452Saudi Arabia Department of Computer Science and Software Engineering Al Ain UniversityAl Ain15551UAE Department of Computer Engineering Korea Polytechnic UniversitySiheung-siGyeonggi-do237Korea

E-learning approaches are one of the most important learning platforms for the learner through electronic *** study techniques are useful for other groups of learners such as the crowd,pedestrian,sports,transports,communication,emergency services,management systems and education sectors.E-learning is still a challenging domain for researchers and developers to find new trends and advanced tools and *** of them are currently working on this domain to fulfill the requirements of industry and the *** this paper,we proposed a method for pedestrian behavior mining of aerial data,using deep flow feature,graph mining technique,and convocational neural *** input data,the state-of-the-art crowd activity University of Minnesota(UMN)dataset is adopted,which contains the aerial indoor and outdoor view of the pedestrian,for simplification of extra information and computational cost reduction the pre-processing is *** flow features are extracted to find more accurate ***,to deal with repetition in features data and features mining the graph mining algorithm is applied,while Convolution Neural Network(CNN)is applied for pedestrian behavior *** proposed method shows 84.50%of mean accuracy and a 15.50%of error ***,the achieved results show more accuracy as compared to state-ofthe-art classification algorithms such as decision tree,artificial neural network(ANN).

关键词： Artificial intelligence behavior mining convolution neural network(CNN) deep flow e-learning environment