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| 1 | 基于膨胀实验数据获取角膜屈光手术后力学参数的方法初探显示文摘目的:基于离体膨胀实验获得的角膜顶点与压力数据,探索利用有限元方法获得屈光手术后角膜力学参数的方法。方法:取实验兔4只,左眼为手术眼,右眼为对照眼。行标准的LASIK术实验兔2只,仅制瓣未对角膜基质层消融的实验兔2只,分别于术后不同时间点实施离体角膜膨胀实验。在离体膨胀实验中,利用位移传感器、压力传感器和显微镜分别获得角膜顶点位移、角膜内压力及角膜正侧面轮廓图像。根据获得的角膜轮廓图像构建角膜几何模型,用二阶Ogden模型描述角膜的本构关系,通过有限元方法模拟膨胀实验,将计算结果与膨胀实验数据比对确定角膜的力学参数,分析屈光手术后饲养一定时间时角膜的力学特性。结果:角膜膨胀实验获得的角膜顶点位移与压力呈非线性关系。在相同压力下,术后饲养一定时间后的兔眼角膜顶点位移量比对照眼小。二阶Ogden模型可以较好地描述屈光手术后角膜的力学特性。屈光手术后角膜弹性模量较对照眼大。结论:基于整体膨胀实验数据,利用有限元方法模拟角膜膨胀实验反推屈光手术后角膜力学参数的方法是可行的。 | 张迪 Muhammad A.Khan 秦晓 张海霞 李林 林丁 刘志成 | 2018 | 中国医学物理学杂志2018，35，4： | 1 |
| 2 | Spatial relation between microbleeds and amyloid deposits in amyloid angiopathy显示文摘 | Gregory A.Dierksen Maureen E.Skehan Muhammad A.Khan JedJeng R.N. KaveerNandigam John A.Becker AshokKumar Krista L.Neal Rebecca A.Betensky Matthew P.Frosch JonathanRosand Keith A.Johnson AnandViswanathan David H.Salat Steven M.Greenberg | 2010 | Ann Neurol2010，，4： | 1 |
| 3 | Convolutional Neural Network Based Intelligent Handwritten Document Recognition显示文摘This paper presents a handwritten document recognition system based on the convolutional neural network technique.In today’s world,handwritten document recognition is rapidly attaining the attention of researchers due to its promising behavior as assisting technology for visually impaired users.This technology is also helpful for the automatic data entry system.In the proposed systemprepared a dataset of English language handwritten character images.The proposed system has been trained for the large set of sample data and tested on the sample images of user-defined handwritten documents.In this research,multiple experiments get very worthy recognition results.The proposed systemwill first performimage pre-processing stages to prepare data for training using a convolutional neural network.After this processing,the input document is segmented using line,word and character segmentation.The proposed system get the accuracy during the character segmentation up to 86%.Then these segmented characters are sent to a convolutional neural network for their recognition.The recognition and segmentation technique proposed in this paper is providing the most acceptable accurate results on a given dataset.The proposed work approaches to the accuracy of the result during convolutional neural network training up to 93%,and for validation that accuracy slightly decreases with 90.42%. | Sagheer Abbas Yousef Alhwaiti Areej Fatima Muhammad A.Khan Muhammad Adnan Khan Taher M.Ghazal Asma Kanwal Munir Ahmad Nouh Sabri Elmitwally | 2022 | Computers, Materials & Continua2022，，3： | 1 |
| 4 | Personality Detection Using Context Based Emotions in Cognitive Agents显示文摘Detection of personality using emotions is a research domain in artificial intelligence.At present,some agents can keep the human’s profile for interaction and adapts themselves according to their preferences.However,the effective method for interaction is to detect the person’s personality by understanding the emotions and context of the subject.The idea behind adding personality in cognitive agents begins an attempt to maximize adaptability on the basis of behavior.In our daily life,humans socially interact with each other by analyzing the emotions and context of interaction from audio or visual input.This paper presents a conceptual personality model in cognitive agents that can determine personality and behavior based on some text input,using the context subjectivity of the given data and emotions obtained from a particular situation/context.The proposed work consists of Jumbo Chatbot,which can chat with humans.In this social interaction,the chatbot predicts human personality by understanding the emotions and context of interactive humans.Currently,the Jumbo chatbot is using the BFI technique to interact with a human.The accuracy of proposed work varies and improve through getting more experiences of interaction. | Nouh Sabri Elmitwally Asma Kanwal Sagheer Abbas Muhammad A.Khan Muhammad Adnan Khan Munir Ahmad Saad Alanazi | 2022 | Computers, Materials & Continua2022，，3： | 0 |
| 5 | A Highly Secured Image Encryption Scheme using Quantum Walk and Chaos显示文摘The use of multimedia data sharing has drastically increased in the past few decades due to the revolutionary improvements in communication technologies such as the 4th generation(4G)and 5th generation(5G)etc.Researchers have proposed many image encryption algorithms based on the classical random walk and chaos theory for sharing an image in a secure way.Instead of the classical random walk,this paper proposes the quantum walk to achieve high image security.Classical random walk exhibits randomness due to the stochastic transitions between states,on the other hand,the quantum walk is more random and achieve randomness due to the superposition,and the interference of the wave functions.The proposed image encryption scheme is evaluated using extensive security metrics such as correlation coefficient,entropy,histogram,time complexity,number of pixels change rate and unified average intensity etc.All experimental results validate the proposed scheme,and it is concluded that the proposed scheme is highly secured,lightweight and computationally efficient.In the proposed scheme,the values of the correlation coefficient,entropy,mean square error(MSE),number of pixels change rate(NPCR),unified average change intensity(UACI)and contrast are 0.0069,7.9970,40.39,99.60%,33.47 and 10.4542 respectively. | Muhammad Islam Kamran Muazzam A.Khan Suliman A.Alsuhibany Yazeed Yasin Ghadi Arshad Jameel Arif Jawad Ahmad | 2022 | Computers, Materials & Continua2022，，10： | 0 |
| 6 | Classification of Diabetic Macular Edema and Its Stages Using Color Fundus Image显示文摘Diabetic macular edema(DME)is a retinal thickening involving the center of the macula.It is one of the serious eye diseases which affects the central vision and can lead to partial or even complete visual loss.The only cure is timely diagnosis,prevention,and treatment of the disease.This paper presents an automated system for the diagnosis and classification of DME using color fundus image.In the proposed technique,first the optic disc is removed by applying some preprocessing steps.The preprocessed image is then passed through a classifier for segmentation of the image to detect exudates.The classifier uses dynamic thresholding technique by using some input parameters of the image.The stage classification is done on the basis of an early treatment diabetic retinopathy study(ETDRS)given criteria to assess the severity of disease.The proposed technique gives a sensitivity,specificity,and accuracy of 98.27%,96.58%,and 96.54%,respectively on publically available database. | Muhammad Zubair Shoab A.Khan Ubaid Ullah Yasin | 2014 | Journal of Electronic Science and Technology2014，12，2： | 0 |
| 7 | CNTFET Based Grounded Active Inductor for Broadband Applications显示文摘A new carbon nanotube field effect transistor(CNTFET)based grounded active inductor(GAI)circuit is presented in this work.The suggested GAI offers a tunable inductance with a very wide inductive bandwidth,high quality factor(QF)and low power dissipation.The tunability of the realized circuit is achieved through CNTFET based varactor.The proposed topology shows inductive behavior in the frequency range of 0.1–101 GHz and achieves to a maximum QF of 9125.The GAI operates at 0.7 V with 0.337 mW of power consumption.To demonstrate the performance of GAI,a broadband low noise amplifier(LNA)circuit is designed by utilizing the GAI based input matching-network.The realized LNA provides high frequency bandwidth(17.5–57 GHz),low noise figure(<3 dB)and occupies less space due to absence of any spiral inductor.Moreover,it exhibits a flat forward gain of 15.9 than±0.9 dB,a reverse isolation less than−63 dB and input return loss less−10 dB over the entire frequency bandwidth.The proposed CNTFET based GAI and LNA circuits are designed and verified by using HSPICE simulations with Stanford CNTFET model at 16 nm technology node. | Muhammad I.Masud Nasir Shaikh-Husin Iqbal A.Khan Abu K.Bin A’Ain | 2022 | Computers, Materials & Continua2022，，10： | 0 |
| 8 | CNTFET Based Fully Differential First Order All Pass Filter显示文摘A novel,carbon nanotubefield effect transistor(CNTFET)based fully differentialfirst order all passfilter(FDFAPF)circuit configuration is presented.The FDFAPF uses CNTFET based negative transconductors(NTs)and positive transconductors(PTs)in its realization.The proposed circuit topology employs two PTs,two NTs,two resistors and one capacitor.All the passive components of the realized topology are grounded.Active only fully differentialfirst order all passfilter(AO-FDFAPF)topology is also derived from the proposed FDFAPF.The electronic tunability of the AO-FDFAPF is obtained by controlling the employed CNTFET based varactor.A tunabilty of pole frequency in the range of 10.5 to 26 GHz is obtained.Both the circuits are potential candidates for high frequency fully differential analog signal processing applications.As compared to prior state-of-the-art works,both the realized topologies have achieved highest pole frequency and lowest power dissipation.Moreover,they utilize compact circuit structures and suitable for low voltage applications.Moreover,both topologies work equally well in the deep submicron.The proposedfilters are analyzed and verified through HPSPICE simulations by utilizing Stanford CNTFET model at 16 nm technology node.It is observed that the proposed circuit simulation outcomes verify the theory. | Muhammad I.Masud Iqbal A.Khan | 2023 | Computer Systems Science & Engineering2023，44，3： | 0 |
| 9 | Intelligent Energy Consumption For Smart Homes Using Fused Machine-Learning Technique显示文摘Energy is essential to practically all exercises and is imperative for the development of personal satisfaction.So,valuable energy has been in great demand for many years,especially for using smart homes and structures,as individuals quickly improve their way of life depending on current innovations.However,there is a shortage of energy,as the energy required is higher than that produced.Many new plans are being designed to meet the consumer’s energy requirements.In many regions,energy utilization in the housing area is 30%–40%.The growth of smart homes has raised the requirement for intelligence in applications such as asset management,energy-efficient automation,security,and healthcare monitoring to learn about residents’actions and forecast their future demands.To overcome the challenges of energy consumption optimization,in this study,we apply an energy management technique.Data fusion has recently attracted much energy efficiency in buildings,where numerous types of information are processed.The proposed research developed a data fusion model to predict energy consumption for accuracy and miss rate.The results of the proposed approach are compared with those of the previously published techniques and found that the prediction accuracy of the proposed method is 92%,which is higher than the previously published approaches. | Hanadi AlZaabi Khaled Shaalan Taher M.Ghazal Muhammad A.Khan Sagheer Abbas Beenu Mago Mohsen A.A.Tomh Munir Ahmad | 2023 | Computers, Materials & Continua2023，，1： | 0 |
| 10 | A Systematic Literature Review of Machine Learning and Deep Learning Approaches for Spectral Image Classification in Agricultural Applications Using Aerial Photography显示文摘Recently,there has been a notable surge of interest in scientific research regarding spectral images.The potential of these images to revolutionize the digital photography industry,like aerial photography through Unmanned Aerial Vehicles(UAVs),has captured considerable attention.One encouraging aspect is their combination with machine learning and deep learning algorithms,which have demonstrated remarkable outcomes in image classification.As a result of this powerful amalgamation,the adoption of spectral images has experienced exponential growth across various domains,with agriculture being one of the prominent beneficiaries.This paper presents an extensive survey encompassing multispectral and hyperspectral images,focusing on their applications for classification challenges in diverse agricultural areas,including plants,grains,fruits,and vegetables.By meticulously examining primary studies,we delve into the specific agricultural domains where multispectral and hyperspectral images have found practical use.Additionally,our attention is directed towards utilizing machine learning techniques for effectively classifying hyperspectral images within the agricultural context.The findings of our investigation reveal that deep learning and support vector machines have emerged as widely employed methods for hyperspectral image classification in agriculture.Nevertheless,we also shed light on the various issues and limitations of working with spectral images.This comprehensive analysis aims to provide valuable insights into the current state of spectral imaging in agriculture and its potential for future advancements. | Usman Khan Muhammad Khalid Khan Muhammad Ayub Latif Muhammad Naveed Muhammad Mansoor Alam Salman A.Khan Mazliham Mohd Su’ud | 2024 | Computers, Materials & Continua2024，78，3： | 0 |
| 11 | Experimental investigation of evaporative cooling systems for agricultural storage and livestock air-conditioning in Pakistan显示文摘Evaporative cooling(EC)is an ancient technique that is usually suitable for hot and dry climatic conditions due to the potential of water vapor evaporation.In this study,three kinds of evaporative cooling systems such as direct EC(DEC),indirect EC(IEC),and Maisotsenko cycle EC(MEC)were locally developed at lab-scale.The performance of the systems was evaluated and compared for agricultural storage and livestock air-conditioning application in Pakistan.The experiments were performed for climatic conditions of Multan city(Pakistan)and the data were collected for hourly and daily basis.According to the results,it was observed that the DEC system has the ability to reduce the temperature of ambient air to an average of 8.5℃.Whilst IEC and MEC systems were able to drop the temperature of ambient air to an average of 6.8℃and 8.9℃,respectively.As per the results,the DEC system remained behind to provide desired conditions for livestock and agricultural product storage applications due to excessive humidity.On the other hand,the IEC and MEC systems can achieve the desired conditions for livestock application,but could not provide feasible conditions for various fruits and vegetable storage.The study concludes that hybrid EC systems can be developed to provide desired conditions for a wide range of applications under varying climatic conditions. | Hafiz M.U.Raza Muhammad Sultan Majid Bahrami Alamgir A.Khan | 2021 | Building Simulation2021，14，3： | 0 |
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