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Cognitive Skill Enhancement System Using Neuro-Feedback for ADHD Patients

Computers, Materials & Continua 2021年第8期68卷 2363-2376页

作者： muhammad usman Ghani Khan Zubaira Naz Javeria Khan Tanzila Saba Ibrahim Abunadi Amjad Rehman usman Tariq Al-khawarizmi Institute of Computer Science University of Engineering and TechnologyLahore54890Pakistan Department of Computer Science University of Engineering and TechnologyLahore54890Pakistan Artificial Intelligence and Data Analytics Lab CCIS Prince Sultan UniversityRiyadhSaudi Arabia College of Computer Engineering and Science Prince Sattam bin Abdulaziz UniversityAlkharjSaudi Arabia

The National Health Interview Survey(NHIS)shows that there are 13.2%of children at the age of 11 to 17 who are suffering from Attention Deficit Hyperactivity Disorder(ADHD),*** treatment methods for ADHD are either psycho-stimulant medications or cognitive *** traditional methods,namely therapy,need a large number of visits to hospitals and include *** could be used for the effective treatment of *** could be a helpful tool in improving children and ADHD patients’cognitive skills by using Brain–Computer Interfaces(BCI).BCI enables the user to interact with the computer through brain activity using Electroencephalography(EEG),which can be used to control different computer applications by processing acquired brain *** paper proposes a system based on neurofeedback that can improve cognitive skills such as attention level,mediation level,and spatial *** proposed system consists of a puzzle game where its complexity increases with each *** signals were acquired using the Neurosky headset;then sent the signals to the designed gaming *** neurofeedback system was tested on 10 different subjects,and their performance was calculated using different evaluation *** results show that this game improves player overall performance from 74%to 98%by playing each game level.

关键词： Neurogaming brain-computer interface attention deficit hyperactivity disorder electroencephalography spatial memory cognitive skills attention level

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Energy Harvesting in Multi-Relay Based Wireless Networks

Energy Harvesting in Multi-Relay Based Wireless Networks

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作者： muhammad usman 上海交通大学

学位级别：硕士

Energy harvesting or energy scavenging is the process to generate electrical energy from environmental energy sources. There exists a variety of energy sources such as solar energy, wind energy and thermal energy. Energy harvesting（EH） based relay networks has gained substantial attention of researchers both from academia and industry because of its potential to overcome the problems of path-loss, fading, coverage and capacity by adopting spatial multiplexing and diversity gain to improve the quality and performance of wireless networks. By joining the EH with relaying provides the solutions of all problems described above. EH provides ultimate solution to counter greenhouse impact and help to reduce the emission of CO2 which has become a critical problem. EH improves the life time of battery dependent networks where replacement or recharging of battery is crucial such as sensor implanted in human body, sensor in buildings and in nuclear radiation monitoring *** harvesting utilizes the ambient radio frequency signals from the environment to transfer data. Simultaneous wireless information and power transfer（SWIPT） is a key technology that has distinguished characteristic and provide solution for energy efficiency,better spectrum utilization and extension to coverage of more area in wireless networks. It has become one of the fastest growing research direction in the communication industry. In order to satisfy the exponential growth of demand, wireless service providers are striving to improve the communication systems so that higher data rate wireless transmission can be supported. Relay based wireless network has ability to extend the coverage range with reduced infrastructure and deployment *** dissertation deals with SWIPT and multi-relay selection（MRS）. The analysis of the considered system is based on information theoretical performance limits, energy efficiency and achievable rates. In this thesis, we developed SWIPT with amplify-and-forward（

关键词：能量收获 Multi-Relay 无线网络中继选择算法

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Research on the Method of Judging Litchi Maturity and Size Based on Image Deep Learning

Research on the Method of Judging Litchi Maturity and Size B...

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作者： usman muhammad 华南理工大学

学位级别：硕士

Object detection is the documentation of an object in the image laterally with its localization and *** has inclusive range applications and critical component for visionbased software *** fruit picking is a challenging problem in robotics with wide application field.A requirement for realization of a robotic fruit picker is its ability to detect fruits in tree *** expert system,which would be able to compete with human perception,must be skillful of recognizing fruits among leaves and branches under uncontrolled conditions,where fruits are occluded and *** the other hand,the localization accuracy can easily be affected by unstructured growing environments with variable illumination conditions and unpredictable growing shapes of weight-bearing stems carrying litchi *** picking points plays a vital role in robotic litchi harvesting in *** Fruit is detected in images using a state-of-the-art,Faster R-CNN *** adopt this model,through finetuning,for the task of litchi fruit based *** main objective of current research is to design an efficient and accurate Faster-RCNN based detection of litchi *** test results show the proposed algorithm has achieved higher detection accuracy and lower processing time than the traditional *** work demonstrated that we introduce a new,high-quality dataset of images containing litchi *** work presents a new multi-sensor framework to identify resourcefully,track,localize,and map every piece of fruit in a commercial Litchi *** performances of the several investigated techniques were assessed based on accuracy and *** proposed faster R-CNN method proves to be efficient and also produce highly accurate and consistent results.

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12-Tungstophosphoric acid niched in Zr-based metal-organic framework:a stable and efficient catalyst for Friedel-Crafts acylation

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Science China Chemistry 2018年第4期61卷 402-411页

作者： Latif Ullah Guoying Zhao Zichen Xu Hongyan He muhammad usman Suojiang Zhang Beijing Key Laboratory of Ionic Liquids Clean Process Key Laboratory of Green Process EngineeringState Key Laboratory of Multiphase Complex SystemsInstitute of Process EngineeringChinese Academy of SciencesBeijing 100190China University of Chinese Academy of Sciences Beijing 100049China Center of Excellence in Nanotechnology King Fahd University of Petroleum and MineralsDhahran 3126Saudi Arabia

Heteropoly acids(HPA) are well known for their versatile solid acid catalysis in diverse chemical reactions, however they suffer from low surface area(<10 m^2/g) and leaching into the reactions media, which reduce their prospects as industrial ***, a novel hybrid material HPW@Zr-BTC,composed of 12-tungstophoric acid(HPW) and Zr^(Ⅳ)-benzene tri-carboxylate(Zr-BTC) metal-organic framework(MOF), was prepared via one-pot solvothermal method. Excellent HPW loading up to 32.3 wt% was achieved, and HPW@Zr-BTC composite proved to be highly stable, besides the crystalline morphology of Zr-BTC was intact. The catalytic activity of the hybrid composite was explored via Friedel-Crafts acylation of anisole with benzoyl *** 28.2 wt% HPW@Zr-BTC showed excellent catalytic performance, with 99.4% anisole conversion and 97.6% yield(pmethoxybenzophenone) under solvent free conditions. Excellent retention of catalytic activity was achieved after at least five consecutive runs due to non-observable HPW leaching. The promising activity and stability of the catalyst forecasted its potential industrial applications.

关键词： dodeca-tungstophosphoric acid Zr-BTC metal-organic frameworks one-pot solvothermal synthesis heterogeneouscatalysis anisole acylation high temperature XRD

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Influences of Marangoni convection and variable magnetic field on hybrid nanofluid thin-film flow past a stretching surface

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Chinese Physics B 2022年第6期31卷 494-501页

作者： Noor Wali Khan Arshad Khan muhammad usman Taza Gul Abir Mouldi Ameni Brahmia Department of Mathematics City University of Science and ITPeshawar 25000Pakistan College of Aeronautical Engineering National University of Sciences and Technology(NUST)Sector H-12Islamabad 44000Pakistan Higher Education Archives and Libraries Department KP Govt.Superior Science CollegePeshawarPakistan Department of Industrial Engineering College of EngineeringKing Khalid UniversityAbha 61421KSA Chemistry Department College of ScienceKing Khalid UniversityAbha 61413Saudi Arabia

Investigations on thin-film flow play a vital role in the field of optoelectronics and magnetic *** films are reasonably hard and thermally stable but quite *** thermal stability of a thin film can be further improved by incorporating the effects of *** the current work,a stretchable surface is considered upon which hybrid nanofluid thin-film flow is taken into *** idea of augmenting heat transmission by making use of a hybrid nanofluid is a focus of the current *** flow is affected by variations in the viscous forces,along with viscous dissipation effects and Marangoni convection.A time-constrained magnetic field is applied in the normal direction to the flow *** equations governing the flow system are shifted to a non-dimensional form by applying similarity *** homotopy analysis method is employed to find the solution to the resultant *** is noticed in this study that the flow characteristics decline with augmentation of magnetic,viscosity and unsteadiness parameters while they increase with enhanced values of thin-film *** characteristics are supported by increasing values of the Eckert number and the unsteadiness parameter and opposed by the viscosity parameter and Prandtl *** numerical impact of different emerging parameters upon skin friction and the Nusselt number is calculated in tabular form.A comparison of current work with established results is carried out,with good agreement.

关键词： thin-film flow hybrid nanofluid viscous dissipation stretching surface homotopy analysis method

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Inception-CNN for Improvement of P300 Detection in Brain-Computer Interface

Inception-CNN for Improvement of P300 Detection in Brain-Com...

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作者： usman muhammad 华南理工大学

学位级别：硕士

P300 detection is a difficult task in the P300 speller-based brain-computer interface（BCI）system due to its low signal-to-noise ratio（SNR）.Previously Convolutional Neural Networks（CNN）have shown prominent results for P300 detection as compared to various machine learning ***,current CNN architectures limit P300 detection accuracy because these models usually only extract single-scale *** Inception module has been proposed by Google Net to improve the classification ability of CNN using a multi-kernel convolutional *** to enhance the P300 detection accuracy,the proposed model in this paper employed an inception module to traditional CNN architecture,which increases the width of a *** proposed P300 detection model can extract multi-scale features using filters of different sizes to efficiently improve the P300 detection ***,the proposed model effectively learns discriminative spatial and temporal features of *** proposed P300 detection model was evaluated on dataset II of the third BCI *** experimental results show the effectiveness of the proposed *** importantly,the character spelling accuracy over early epochs is greatly improved as compared to existing CNN architectures.

关键词：脑-计算机接口卷积神经网络 P300检测

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Exploration of uniform heat flux on the flow and heat transportation of ferrofluids along a smooth plate： Comparative investigation

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International Journal of Biomathematics 2018年第4期11卷 57-75页

作者： muhammad usman muhammad Hamid Syed Tauseef Mohyud Din Asif Waheed Wei Wang School of Mathematical Sciences Peking University Beijing 100871 P. R. China Department of Mathematics Faculty of Sciences HITEC University Taxila Cantt Pakistan Department of Mathematics COMSATS Institute of Information Technology Attock Pakistan

The paper is devoted to a new extension in Gegenbauer wavelet method （GWM） to investigate the transfer of heat and MHD boundary-layer flow of ferrofluids beside a flat plate with velocity slip. A homogenous model study is conducted in which we assumed the heat transfer and forced convective flow of ferrofluids along a flat plate with a uniform wall heat flux. In the direction of transverse to plate, a magnetic field is imposed. Three various magnetic nanoparticle types including Mn-ZnFe204, CoFe204, Fe3O4 are incorporated inside the base fluid. Two types of base fluids （water and kerosene） with bad thermal conductivity as compared to nanoparticles of solid magnetic have been assumed. The mathematical model is tackled via modified Gegenbauer wavelet method （MGWM）. A simulation is accomplished for individual ferrofluid mixture by assuming the prevailing impacts of uniform and slip heat fluxes. The variation of heat transfers and skin friction were also observed at the surface of the plate and we analyzed the better heat transfer for every mixture. Kerosene-based magnetite （Fe304） delivers the better rate of heat transfer at wall due to its association with the kerosene-based Mn-Zn and cobalt ferrites. The slip velocity and magnetic field effects on the temperature, dimensionless velocity, rate of heat transfer and skin friction are examined for various magnetic nanoparticles inside the kerosene oil and water. We observed that the primary influence of magnetic field reduces the dimensionless surface temperature and accelerates the dimensionless velocity as compared to the hydrodynamic case, thus enhancing the rate of heat transfer and skin friction ferrofluids. Moreover, a detailed evaluation of outcomes obtained by MGWM, already published work and numerical RK-4 were found to be in excellent agreement. The error and convergence analysis are presented. Comparison of results,graphical plots, error and convergence analysis reveal the appropriateness of proposed method. T

关键词： Gegenbauer polynomials collocation method ferrofluids heat flux numericalsolution.

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A Hybrid Duo-Deep Learning and Best Features Based Framework for Action Recognition

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Computers, Materials & Continua 2022年第11期73卷 2555-2576页

作者： muhammad Naeem Akbar Farhan Riaz Ahmed Bilal Awan muhammad Attique Khan usman Tariq Saad Rehman National University of Sciences and Technology(NUST) Islamabad46000Pakistan Department of Computer Science HITEC UniversityTaxilaPakistan College of Computer Engineering and Science Prince Sattam Bin Abdulaziz UniversityAl-Kharaj 11942Saudi Arabia

Human Action Recognition(HAR)is a current research topic in the field of computer vision that is based on an important application known as video *** in computer vision have introduced various intelligent methods based on deep learning and machine learning,but they still face many challenges such as similarity in various actions and redundant *** proposed a framework for accurate human action recognition(HAR)based on deep learning and an improved features optimization algorithm in this *** deep learning feature extraction to feature classification,the proposed framework includes several critical *** training fine-tuned deep learning models–MobileNet-V2 and Darknet53–the original video frames are *** feature extraction,pre-trained deep models are used,which are fused using the canonical correlation *** that,an improved particle swarm optimization(IPSO)-based algorithm is used to select the best *** that,the selected features were used to classify actions using various *** experimental process was performed on six publicly available datasets such as KTH,UT-Interaction,UCF Sports,Hollywood,IXMAS,and UCF YouTube,which attained an accuracy of 98.3%,98.9%,99.8%,99.6%,98.6%,and 100%,*** comparison with existing techniques,it is observed that the proposed framework achieved improved accuracy.

关键词： Action recognition deep learning features fusion features selection recognition

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The outbreak of dengue during the COVID-19 pandemic in Pakistan:The emergence of overlapping crises

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Asian Pacific Journal of Tropical Medicine 2022年第2期15卷 53-55页

作者： muhammad Suleman Rana muhammad usman muhammad Masroor Alam Aamer Ikram muhammad Salman Rani Faryal Massab Umair National Institute of Health IslamabadPakistan Department of Microbiology Quaid-I-Azam University Islamabad Pakistan

COVID-19 pandemic has become a serious public health crisis for developed and developing countries around the *** of February 17,2022,over 420 million cases including 5.8 million deaths have been reported across the globe[1].The first case of COVID-19 in Pakistan was detected on February 26,2020;since then,the toll of confirmed COVID-19 cases reached 1491423 including 29877 deaths as of February 17,2022[1].

关键词： cases Pakistan COV

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Fake News Classification: Past, Current, and Future

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Computers, Materials & Continua 2023年第11期77卷 2225-2249页

作者： muhammad usman Ghani Khan Abid Mehmood Mourad Elhadef Shehzad Ashraf Chaudhry Department of Computer Science University of Engineering and TechnologyLahore54890Pakistan Department of Computer Science&Information Technology Abu Dhabi UniversityAbu Dhabi59911United Arab Emirates Department of Software Engineering Faculty of Engineering and ArchitectureNisantasi UniversityIstanbulTurkey

The proliferation of deluding data such as fake news and phony audits on news web journals,online publications,and internet business apps has been aided by the availability of the web,cell phones,and social *** can quickly fabricate comments and news on social *** most difficult challenge is determining which news is real or ***,tracking down programmed techniques to recognize fake news online is *** an emphasis on false news,this study presents the evolution of artificial intelligence techniques for detecting spurious social media *** study shows past,current,and possible methods that can be used in the future for fake news *** different publicly available datasets containing political news are utilized for performing *** supervised learning algorithms are used,and their results show that conventional Machine Learning(ML)algorithms that were used in the past perform better on shorter text *** contrast,the currently used Recurrent Neural Network(RNN)and transformer-based algorithms perform better on longer ***,a brief comparison of all these techniques is provided,and it concluded that transformers have the potential to revolutionize Natural Language Processing(NLP)methods in the near future.

关键词： Supervised learning algorithms fake news classification online disinformation transformers recurrent neural network(RNN)disinformation transformers recurrent neural network(RNN)

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