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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

Optimization of gob ventilation boreholes design in longwall mining

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International Journal of Mining Science and Technology 2020年第6期30卷 811-817页

作者： Saqib Ahmad Saki Jürgen F.Brune Muhammad usman khan University of Engineering and Technology Lahore Lahore 54890Pakistan Colorado School of Mines GoldenCO 80401USA

Gob ventilation boreholes(GVBs)are widely used for degasification in *** coal *** on geological conditions,30–50%of methane can be recovered from longwall gob using GVBs.A NIOSH funded research at the Colorado School of Mines confirmed that GVBs can efficiently reduce methane at the ***,GVBs can also draw some fresh air from the face and create explosive gas zones(EGZs).Explosive gas mixtures may be formed in gob areas due to the increased ingress of oxygen from *** is critical to identify the locations for GVBs for maximizing extraction of methane and minimizing hazards of *** study analyzes the effect of operating parameters and design of GVB on methane extraction,EGZs formation,and face and tailgate methane *** extraction,formation of EGZs,and concentration of methane in working areas are significantly impacted by various *** factors include the distance of work face and tailgate from GVBs,diameter of GVBs,vacuum pressure of wellhead,GVB distance from the roof of the coal seam,and number of operating GVBs in a *** fluid dynamics(CFD)evaluations suggest optimal design and operating parameters of GVBs that can contribute to maximum benefits with minimum risks.

关键词： Longwall mining Explosive gas zones Computational fluid dynamics Gob ventilation boreholes

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)

A Robust MPPT Control Based on Double Ended Forward Converter Architecture

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Computers, Materials & Continua 2022年第1期70卷 135-150页

作者： M.usman khan K.M.Hasan A.Faisal Murtaza H.M.usman Hadeed A.Sher University of Engineering&Technology Lahore54000Pakistan University of Central Punjab Lahore54000Pakistan Ghulam Ishaq khan Institute of Engineering Sciences and Technology Swabi23430Pakistan

In this paper,a stand-alone photovoltaic(PV)system based on a Double Ended Forward Converter(DEFC)is *** proposed converter is specified for 48 V,100Wapplications as most of the equipment used in telecommunication and aircraft fall in this *** literature has limited potential application of DEFCin PV *** research work deals with an in-depth study of DEFCand proposes an improvedDEFCfor PV applications with battery ***,a bi-directional dc-dc converter for the battery is integrated to track theMaximumPower Point(MPP)of the PV *** converter is examined under variable irradiance and load conditions,and the analytical analysis of boundary conditions are *** converter’s architecture also ensures built-in I-V curve tracing for the identification of MPP of PV *** offers low voltage stresses across switches and avoids sinking power supply and core resetting *** topology’s behavior is analyzed based onMPP achievement and maintaining output under different conditions of battery backup availability,environmental,and load *** PV system architecture is designed and analyzed theoretically and verified with simulations on the PSIM software.

关键词： Photovoltaic power converter forward converter double ended forward converter bi-directional dc-dc converter MPP I-V curve tracing

A Systematic Literature Review of Machine Learning and Deep Learning Approaches for Spectral Image Classification in Agricultural Applications Using Aerial Photography

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Computers, Materials & Continua 2024年第3期78卷 2967-3000页

作者： usman khan Muhammad Khalid khan Muhammad Ayub Latif Muhammad Naveed Muhammad Mansoor Alam Salman A.khan Mazliham Mohd Su’ud College of Computing and Information Sciences Karachi Institute of Economics and TechnologyKarachi75190Pakistan Faculty of Computing and Informatics(FCI) Multimedia UniversityCyberjaya63100Malaysia Faculty of Computing Riphah International UniversityIslamabad46000Pakistan Faculty of Engineering and Information Technology School of Computer ScienceUniversity of Technology SydneySydneyAustralia

Recently,there has been a notable surge of interest in scientific research regarding spectral *** potential of these images to revolutionize the digital photography industry,like aerial photography through Unmanned Aerial Vehicles(UAVs),has captured considerable *** encouraging aspect is their combination with machine learning and deep learning algorithms,which have demonstrated remarkable outcomes in image *** 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 *** 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 *** meticulously examining primary studies,we delve into the specific agricultural domains where multispectral and hyperspectral images have found practical ***,our attention is directed towards utilizing machine learning techniques for effectively classifying hyperspectral images within the agricultural *** findings of our investigation reveal that deep learning and support vector machines have emerged as widely employed methods for hyperspectral image classification in ***,we also shed light on the various issues and limitations of working with spectral *** comprehensive analysis aims to provide valuable insights into the current state of spectral imaging in agriculture and its potential for future advancements.

关键词： Machine learning deep learning unmanned aerial vehicles multi-spectral images image recognition object detection hyperspectral images aerial photography

Recent advances in 2D organic−inorganic heterostructures for electronics and optoelectronics

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SmartMat 2023年第2期4卷 37-68页

作者： Jahangir khan Rana Tariq Mehmood Ahmad Junyang Tan Rongjie Zhang usman khan Bilu Liu Shenzhen Geim Graphene Center Tsinghua‐Berkeley Shenzhen Institute&Institute of Materials ResearchTsinghua Shenzhen International Graduate SchoolTsinghua UniversityShenzhenChina Department of Electrical Engineering Narowal CampusUniversity of Engineering and TechnologyLahorePakistan Institute of Functional Porous Materials School of Materials Science and EngineeringZhejiang Sci‐Tech UniversityHangzhouChina

Two‐dimensional(2D)materials show outstanding properties such as dangling bond‐free surfaces,strong in‐plane while weak out‐of‐plane bonding,layer‐dependent electronic structures,and tunable electronic and optoelectronic properties,making them promising for numerous *** 2D inorganics with organic materials to make van der Waals heterostructures at the 2D thickness limit has created new platforms for fabricating on‐demand multifunctional *** further broaden the limited choices of 2D inorganic‐based heterostructures,a wide range of available 2D organic materials with tunable properties have opened new opportunities for designing large numbers of heterostructures with 2D inorganic *** review aims to attract the attention of researchers toward this emerging 2D organic−inorganic *** first highlight recent progress in organic−inorganic heterostructures and their synthesis and then discuss their potential applications,such as field‐effect transistors,photodetectors,solar cells,and neuromorphic computing *** the end,we present a summary of challenges and opportunities in this field.

关键词： 2D materials 2D organic−inorganic heterostructures electronics inorganic materials optoelectronics organic materials synthesis

Efficient Facial Recognition Authentication Using Edge and Density Variant Sketch Generator

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Computers, Materials & Continua 2022年第1期70卷 505-521页

作者： Summra Saleem M.usman Ghani khan Tanzila Saba Ibrahim Abunadi Amjad Rehman Saeed Ali Bahaj Department of Computer Science UETLahorePakistan Al-Khwarizmi Institute of Computer Science UETLahorePakistan Artificial Intelligence&Data Analytics Lab CCIS Prince Sultan University Riyadh11586Saudi Arabia MIS Department College of Business Administration Prince Sattam Bin Abdulaziz UniversityAlkharjSaudi Arabia

Image translation plays a significant role in realistic image synthesis,entertainment tasks such as editing and colorization,and security including personal *** Edge GAN,the major contribution is attribute guided vector that enables high visual quality content *** research study proposes automatic face image realism from freehand sketches based on Edge *** propose a density variant image synthesis model,allowing the input sketch to encompass face features with minute *** density level is projected into non-latent space,having a linear controlled function *** assists the user to appropriately devise the variant densities of facial sketches and image *** data set of Large Scale CelebFaces Attributes(ClebA),Labelled Faces in theWild(LFWH),Chinese University of Hong Kong(CHUK),and self-generated Asian images are used to evaluate the proposed *** solution is validated to have the capability for generating realistic face images through quantitative and qualitative results and human evaluation.

关键词： Edge generator density variant sketch generator face translation recognition residual block

Confined van der Waals Epitaxial Growth of Two-Dimensional Large Single-Crystal In_(2)Se_(3) for Flexible Broadband Photodetectors

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Research 2019年第1期2019卷 1096-1105页

作者： Lei Tang Changjiu Teng Yuting Luo usman khan Haiyang Pan Zhengyang Cai Yue Zhao Bilu Liu Hui-Ming Cheng Shenzhen Geim Graphene Center Tsinghua-Berkeley Shenzhen InstituteTsinghua UniversityShenzhen 518055China Shenzhen Institute for Quantum Science and Engineering and Department of Physics Southern University of Science and TechnologyShenzhen 518055China Shenzhen Key Laboratory of Quantum Science and Engineering Shenzhen 518055China Shenyang National Laboratory for Materials Sciences Institute of Metal ResearchChinese Academy of SciencesShenyang 110016China

The controllable growth of two-dimensional(2D)semiconductors with large domain sizes and high quality is much needed in order to reduce the detrimental efect of grain boundaries on device performance but has proven to be ***,we analyze the precursor concentration on the substrate surface which signifcantly infuences nucleation density in a vapor deposition growth process and design a confned micro-reactor to grow 2D In_(2)Se_(3) with large domain sizes and high *** uniqueness of this confned micro-reactor is that its size is∼102-103 times smaller than that of a conventional *** a remarkably small reactor causes a very low precursor concentration on the substrate surface,which reduces nucleation density and leads to the growth of 2D In_(2)Se_(3) grains with sizes larger than 200�*** experimental results show large domain sizes of the 2D In_(2)Se_(3) with high *** fexible broadband photodetectors based on the as-grown In_(2)Se_(3) show rise and decay times of 140 ms and 25 ms,efcient response(5.6 A/W),excellent detectivity(7×10^(10) Jones),high external quantum efciency(251%),good fexibility,and high *** study,in principle,provides an efective strategy for the controllable growth of high quality 2D materials with few grain boundaries.

关键词： stability grain sizes

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