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Cognitive Skill Enhancement System Using Neuro-Feedback for ADHD Patients

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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

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)

Vision based intelligent traffic light management system using Faster R‐CNN

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CAAI Transactions on Intelligence Technology 2024年第4期9卷 932-947页

作者： Syed Konain Abbas muhammad usman ghani khan Jia Zhu Raheem Sarwar Naif R.Aljohani Ibrahim A.Hameed muhammad Umair Hassan Department of Computer Science and Engineering University of Engineering and TechnologyLahorePakistan Zhejiang Key Laboratory of Intelligent Education Technology and Application Zhejiang Normal UniversityJinhuaChina OTHEM Manchester Metropolitan UniversityManchesterUK Faculty of Computing and Information Technology King Abdulaziz UniversityJeddahSaudi Arabia Department of ICT and Natural Sciences Norwegian University of Science and Technology(NTNU)ÅlesundNorway

Transportation systems primarily depend on vehicular flow on roads. Developed coun-tries have shifted towards automated signal control, which manages and updates signal synchronisation automatically. In contrast, traffic in underdeveloped countries is mainly governed by manual traffic light systems. These existing manual systems lead to numerous issues, wasting substantial resources such as time, energy, and fuel, as they cannot make real‐time decisions. In this work, we propose an algorithm to determine traffic signal durations based on real‐time vehicle density, obtained from live closed circuit television camera feeds adjacent to traffic signals. The algorithm automates the traffic light system, making decisions based on vehicle density and employing Faster R‐CNN for vehicle detection. Additionally, we have created a local dataset from live streams of Punjab Safe City cameras in collaboration with the local police authority. The proposed algorithm achieves a class accuracy of 96.6% and a vehicle detection accuracy of 95.7%. Across both day and night modes, our proposed method maintains an average precision, recall, F1 score, and vehicle detection accuracy of 0.94, 0.98, 0.96 and 0.95, respectively. Our proposed work surpasses all evaluation metrics compared to state‐of‐the‐art methodologies.

关键词： access control artificial intelligence computer vision intelligent control

First Principles Calculations for Corrosion in Mg-Li-Al Alloys with Focus on Corrosion Resistance: A Comprehensive Review

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Computers, Materials & Continua 2024年第11期81卷 1905-1952页

作者： muhammad Abdullah khan muhammad usman Yuhong Zhao School of Materials Science and Engineering Collaborative Innovation Center of Ministry of Education and Shanxi Province for High-Performance Al/Mg Alloy MaterialsNorth University of ChinaTaiyuan030051China Electronics Department North University of ChinaTaiyuan030000China Beijing Advanced Innovation Center for Materials Genome Engineering University of Science and Technology BeijingBeijing100083China Institute of Materials Intelligent Technology Liaoning Academy of MaterialsShenyang110004China

This comprehensive review examines the structural,mechanical,electronic,and thermodynamic properties of Mg-Li-Al alloys,focusing on their corrosion resistance and mechanical performance *** first-principles calculations based on Density Functional Theory(DFT)and the quasi-harmonic approximation(QHA),the combined properties of the Mg-Li-Al phase are explored,revealing superior incompressibility,shear resistance,and stiffness compared to individual *** review highlights the brittleness of the alloy,supported by B/G ratios,Cauchy pressures,and Poisson’s *** structure analysis shows metallic behavior with varied covalent bonding characteristics,while Mulliken population analysis emphasizes significant electron transfer within the *** paper also studied thermodynamic properties,including Debye temperature,heat capacity,enthalpy,free energy,and entropy,which are precisely examined,highlighting the Mg-Li-Al phase sensitive to thermal conductivity and thermal performance *** density of states(PHDOS)confirms dynamic stability,while anisotropic sound velocities reveal elastic *** comprehensive review not only consolidates the current understanding of the Mg-Li-Al alloy’s properties but also proposes innovative strategies for enhancing corrosion *** these strategies is the introduction of a corrosion barrier akin to the Mg-Li-Al network,which holds promise for advancing both the applications and performance of these *** review serves as a crucial foundation for future research aimed at optimizing alloy design and processing methods.

关键词： First-principles calculations Mg-Li-Al alloys corrosion resistance thermodynamic properties mechanical properties

Acral melanoma detection using dermoscopic images and convolutional neural networks

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Visual Computing for Industry,Biomedicine,and Art 2021年第1期4卷 246-257页

作者： Qaiser Abbas Farheen Ramzan muhammad usman ghani Department of Computer Science University of Engineering and Technology54890 LahorePakistan

Acral melanoma(AM)is a rare and lethal type of skin *** can be diagnosed by expert dermatologists,using dermoscopic *** is challenging for dermatologists to diagnose melanoma because of the very minor differences between melanoma and non-melanoma *** of the research on skin cancer diagnosis is related to the binary classification of lesions into melanoma and ***,to date,limited research has been conducted on the classification of melanoma *** current study investigated the effectiveness of dermoscopy and deep learning in classifying melanoma subtypes,such as,*** this study,we present a novel deep learning model,developed to classify skin *** utilized a dermoscopic image dataset from the Yonsei University Health System South Korea for the classification of skin *** image processing and data augmentation techniques have been applied to develop a robust automated system for AM *** custombuilt model is a seven-layered deep convolutional network that was trained from ***,transfer learning was utilized to compare the performance of our model,where AlexNet and ResNet-18 were modified,fine-tuned,and trained on the same *** achieved improved results from our proposed model with an accuracy of more than 90%for AM and benign nevus,***,using the transfer learning approach,we achieved an average accuracy of nearly 97%,which is comparable to that of state-of-the-art *** our analysis and results,we found that our model performed well and was able to effectively classify skin *** results show that the proposed system can be used by dermatologists in the clinical decision-making process for the early diagnosis of AM.

关键词： Deep learning Acral melanoma Skin cancer detection Convolutional networks Dermoscopic images Medical image analysis Computer based diagnosis

Joint Non-Orthogonal Multiple Access (NOMA) & Walsh-Hadamard Transform: Enhancing the Receiver Performance

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China Communications 2018年第9期15卷 160-177页

作者： muhammad Rehan usman Arsla khan muhammad Arslan usman Soo young Shin Department of Electrical Engineering The Superior College (University Campus) Department of IT Convergence Engineering Kumoh National Institute of Technology (KIT) Department of Electrical Engineering COMSATS University Islamabad Lahore Campus

Non-orthogonal multiple access(NOMA) is a new access method to achieve high performance gains in terms of capacity and throughput, so it is currently under consideration as one of the candidates for fifth generation(5 G) technologies. NOMA utilizes power domain in order to superimpose signals of multiple users in a single transmitted signal. This creates a lot of interference at the receive side. Although the use of successive interference cancellation(SIC) technique reduces the interference, but to further improve the receiver performance, in this paper, we have proposed a joint Walsh-Hadamard transform(WHT) and NOMA approach for achieving better performance gains than the conventional NOMA. WHT is a well-known code used in communication systems and is used as an orthogonal variable spreading factor(OVSF) in communication systems. Application of WHT to NOMA results in low bit error rate(BER) and high throughput performance for both low and high channel gain users. Further, it also reduces peak to average power ratio(PAPR) of the user signal. The results are discussed in terms of comparison between the conventionalNOMA and the proposed technique, which shows that it offers high performance gains in terms of low BER at different SNR levels, reduced PAPR, high user throughput performance and better spectral efficiency.

关键词： Bit error rate (BER) non-orthogonal multiple access (NOMA) orthogonal frequency division multiplexing (OFDM) peak to average power ratio (PAPR) successive interference cancellation (SIC) throughput and Walsh-Hadamard transform (WHT).

HybridHR-Net:Action Recognition in Video Sequences Using Optimal Deep Learning Fusion Assisted Framework

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Computers, Materials & Continua 2023年第9期76卷 3275-3295页

作者： muhammad Naeem Akbar Seemab khan muhammad Umar Farooq Majed Alhaisoni usman Tariq muhammad usman Akram Department of Computer Engineering National University of Sciences and Technology(NUST)Islamabad46000Pakistan Department of Robotics SMME NUSTIslamabad45600Pakistan Computer Sciences Department College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia Management Information System Department College of Business AdministrationPrince Sattam bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia

The combination of spatiotemporal videos and essential features can improve the performance of human action recognition(HAR);however,the individual type of features usually degrades the performance due to similar actions and complex *** deep convolutional neural network has improved performance in recent years for several computer vision applications due to its spatial *** article proposes a new framework called for video surveillance human action recognition dubbed *** a few selected datasets,deep transfer learning is used to pre-trained the EfficientNet-b0 deep learning *** optimization is employed for the tuning of hyperparameters of the fine-tuned deep *** of fully connected layer features,we considered the average pooling layer features and performed two feature selection techniques-an improved artificial bee colony and an entropy-based *** a serial nature technique,the features that were selected are combined into a single vector,and then the results are categorized by machine learning *** publically accessible datasets have been utilized for the experimental approach and obtained notable accuracy of 97%,98.7%,100%,99.7%,and 96.8%,***,a comparison of the proposed framework with contemporarymethods is done to demonstrate the increase in accuracy.

关键词： Action recognition entropy deep learning transfer learning artificial bee colony feature fusion

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

Empirical Analysis of Software Success Rate Forecasting During Requirement Engineering Processes

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Computers, Materials & Continua 2023年第1期74卷 783-799页

作者： muhammad Hasnain Imran ghani Seung Ryul Jeong muhammad Fermi Pasha Sardar usman Anjum Abbas Lahore Leads University Lahore42000Pakistan Computer and Information Sciences Virginia Military InstituteLexingtonVA24450USA Graduate School of Business IT Kookmin UniversitySeoul136Korea School of Information Technology Monash UniversityBandar Sunway47500Malaysia Department of Computer Science and Software Engineering Grand Asian University Sialkot51040Pakistan Government Sarwar Shaheed Associate College Gujjar KhanRawalpindi46000Pakistan

Forecasting on success or failure of software has become an interesting and,in fact,an essential task in the software development *** order to explore the latest data on successes and failures,this research focused on certain questions such as is early phase of the software development life cycle better than later phases in predicting software success and avoiding high rework?What human factors contribute to success or failure of a software?What software practices are used by the industry practitioners to achieve high quality of software in their day-to-day work?In order to conduct this empirical analysis a total of 104 practitioners were recruited to determine how human factors,misinterpretation,and miscommunication of requirements and decision-making processes play their roles in software success *** discussed a potential relationship between forecasting of software success or failure and the development *** noticed that experienced participants had more confidence in their practices and responded to the questionnaire in this empirical study,and they were more likely to rate software success forecasting linking to the development *** analysis also shows that cognitive bias is the central human factor that negatively affects forecasting of software success *** results of this empirical study also validated that requirements’misinterpretation and miscommunication were themain causes behind software systems’*** has been seen that reliable,relevant,and trustworthy sources of information help in decision-making to predict software systems’success in the software *** empirical study highlights a need for other software practitioners to avoid such bias while working on software *** investigation can be performed to identify the other human factors that may impact software systems’success.

关键词： Cognitive bias misinterpretation of requirements miscommunication software success and failure prediction decision making