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| 1 | Combined cytotoxic action of paclitaxel and ceramide against the human Tu138 head and neck squamous carcinoma cell line显示文摘 | SHASHI MEHTA DILSHAD BLACKINTON IMRAN OMAR | 2000 | Cancer Chemother Pharmacol2000，46，： | 1 |
| 2 | Systematic Review of Perioperative and Quality-of-life Outcomes Following Surgical Management of Localised Renal Cancer显示文摘 | Steven MacLennan Mari Imamura Marie C. Lapitan Muhammad Imran Omar Thomas B.L. Lam Ana M. Hilvano-Cabungcal Pam Royle Fiona Stewart Graeme MacLennan Sara J. MacLennan Philipp Dahm Steven E. Canfield Sam McClinton T.R. Leyshon Griffiths B?rje Ljungberg Jam | 2012 | European Urology2012，，6： | 1 |
| 3 | China's Foreign Direct Investment in Africa :An overview 显示文摘 | Omar Mohamed Ali Shah Muhammad Imran | 2012 | :793-7972012，，： | 1 |
| 4 | Weapons Detection for Security and Video Surveillance Using CNN and YOLO-V5s显示文摘In recent years,the number of Gun-related incidents has crossed over 250,000 per year and over 85%of the existing 1 billion firearms are in civilian hands,manual monitoring has not proven effective in detecting firearms.which is why an automated weapon detection system is needed.Various automated convolutional neural networks(CNN)weapon detection systems have been proposed in the past to generate good results.However,These techniques have high computation overhead and are slow to provide real-time detection which is essential for the weapon detection system.These models have a high rate of false negatives because they often fail to detect the guns due to the low quality and visibility issues of surveillance videos.This research work aims to minimize the rate of false negatives and false positives in weapon detection while keeping the speed of detection as a key parameter.The proposed framework is based on You Only Look Once(YOLO)and Area of Interest(AOI).Initially,themodels take pre-processed frames where the background is removed by the use of the Gaussian blur algorithm.The proposed architecture will be assessed through various performance parameters such as False Negative,False Positive,precision,recall rate,and F1 score.The results of this research work make it clear that due to YOLO-v5s high recall rate and speed of detection are achieved.Speed reached 0.010 s per frame compared to the 0.17 s of the Faster R-CNN.It is promising to be used in the field of security and weapon detection. | Abdul Hanan Ashraf Muhammad Imran Abdulrahman M.Qahtani Abdulmajeed Alsufyani Omar Almutiry Awais Mahmood Muhammad Attique Mohamed Habib | 2022 | Computers, Materials & Continua2022，，2： | 1 |
| 5 | Systematic Review of Oncological Outcomes Following Surgical Management of Localised Renal Cancer显示文摘 | Steven MacLennan Mari Imamura Marie C. Lapitan Muhammad Imran Omar Thomas B.L. Lam Ana M. Hilvano-Cabungcal Pam Royle Fiona Stewart Graeme MacLennan Sara J. MacLennan Steven E. Canfield Sam McClinton T.R. Leyshon Griffiths B?rje Ljungberg James N’Dow | 2012 | European Urology2012，，5： | 1 |
| 6 | Combined cytotoxic action of paclitaxel and ceramide against the human Tu138 head and neck squamous carcinoma cell line显示文摘 | Shashi Mehta Dilshad Blackinton Imran Omar Nicola Kouttab Dorkina Myrick Shashi Mehta Dorkina Myrick Jim Klostergaard Harold Wanebo | 2000 | Cancer Chemotherapy and Pharmacology2000，，2： | 1 |
| 7 | Visibility Enhancement of Scene Images Degraded by Foggy Weather Condition: An Application to Video Surveillance显示文摘:In recent years,video surveillance application played a significant role in our daily lives.Images taken during foggy and haze weather conditions for video surveillance application lose their authenticity and hence reduces the visibility.The reason behind visibility enhancement of foggy and haze images is to help numerous computer and machine vision applications such as satellite imagery,object detection,target killing,and surveillance.To remove fog and enhance visibility,a number of visibility enhancement algorithms and methods have been proposed in the past.However,these techniques suffer from several limitations that place strong obstacles to the real world outdoor computer vision applications.The existing techniques do not perform well when images contain heavy fog,large white region and strong atmospheric light.This research work proposed a new framework to defog and dehaze the image in order to enhance the visibility of foggy and haze images.The proposed framework is based on a Conditional generative adversarial network(CGAN)with two networks;generator and discriminator,each having distinct properties.The generator network generates fog-free images from foggy images and discriminator network distinguishes between the restored image and the original fog-free image.Experiments are conducted on FRIDA dataset and haze images.To assess the performance of the proposed method on fog dataset,we use PSNR and SSIM,and for Haze dataset use e,r−,andσas performance metrics.Experimental results shows that the proposed method achieved higher values of PSNR and SSIM which is 18.23,0.823 and lower values produced by the compared method which are 13.94,0.791 and so on.Experimental results demonstrated that the proposed framework Has removed fog and enhanced the visibility of foggy and hazy images. | Ghulfam Zahra Muhammad Imran Abdulrahman M.Qahtani Abdulmajeed Alsufyani Omar Almutiry Awais Mahmood Fayez Eid Alazemi | 2021 | Computers, Materials & Continua2021，，9： | 0 |
| 8 | Improving Prediction of Chronic Kidney Disease Using KNN Imputed SMOTE Features and TrioNet Model显示文摘Chronic kidney disease(CKD)is a major health concern today,requiring early and accurate diagnosis.Machine learning has emerged as a powerful tool for disease detection,and medical professionals are increasingly using ML classifier algorithms to identify CKD early.This study explores the application of advanced machine learning techniques on a CKD dataset obtained from the University of California,UC Irvine Machine Learning repository.The research introduces TrioNet,an ensemble model combining extreme gradient boosting,random forest,and extra tree classifier,which excels in providing highly accurate predictions for CKD.Furthermore,K nearest neighbor(KNN)imputer is utilized to deal withmissing values while synthetic minority oversampling(SMOTE)is used for class-imbalance problems.To ascertain the efficacy of the proposed model,a comprehensive comparative analysis is conducted with various machine learning models.The proposed TrioNet using KNN imputer and SMOTE outperformed other models with 98.97%accuracy for detectingCKD.This in-depth analysis demonstrates the model’s capabilities and underscores its potential as a valuable tool in the diagnosis of CKD. | Nazik Alturki Abdulaziz Altamimi Muhammad Umer Oumaima Saidani Amal Alshardan Shtwai Alsubai Marwan Omar Imran Ashraf | 2024 | Computer Modeling in Engineering & Sciences2024，139，6： | 0 |
| 9 | Application of ferrous sulfate alleviates negative impact of cadmium in rice(Oryza sativa L.)显示文摘Soil contamination with toxic heavy metals[such as cadmium(Cd)]is becoming a serious global problem due to rapid development of social economy.Iron(Fe),being an important element,has been found effective in enhancing plant tolerance against biotic and abiotic stresses.The present study investigated the extent to which different levels of Ferrous sulphate(FeSO_(4))modulated the Cd tolerance of rice(Oryza sativa L.),when maintained in artificially Cd spiked regimes.A pot experiment was conducted under controlled conditions for 146 days,by using natural soil,mixed with different levels of CdCl_(2)[0(no Cd),0.5 and 1 mg/kg]together with the exogenous application of FeSO_(4) at[0(no Fe),1.5 and 3 mg/kg]levels to monitor different growth,gaseous exchange characteristics,oxidative stress,antioxidative responses,minerals accumulation,organic acid exudation patterns of O.sativa.Our results depicted that addition of Cd to the soil significantly(P<0.05)decreased plant growth and biomass,gaseous exchange parameters,mineral uptake by the plants,sugars(soluble,reducing,and non-reducing sugar)and altered the ultrastructure of chloroplasts,plastoglobuli,mitochondria,and many other cellular organelles in Cd-stressed O.sativa compared to those plants which were grown without the addition of Cd in the soil.However,Cd toxicity boosted the production of reactive oxygen species(ROS)by increasing the contents of malondialdehyde(MDA),which is the indication of oxidative stress in O.sativa and was also manifested by hydrogen peroxide(H_(2)O_(2))contents and electrolyte leakage to the membrane bounded organelles.Although,activities of various antioxidative enzymes like superoxidase dismutase(SOD),peroxidase(POD),catalase(CAT)and ascorbate peroxidase(APX)and non-enzymatic antioxidants like phenolics,flavonoid,ascorbic acid,anthocyanin and proline contents increased up to a Cd level of 0.5 mg/kg in the soil but were significantly diminished at the highest Cd level of 1 mg/kg in the soil compared to those plants which were grown without the addition of Cd in the soil.The negative impacts of Cd injury were reduced by the application of FeSO_(4) which increased plant growth and biomass,improved photosynthetic apparatus,antioxidant enzymes,minerals uptake together with diminished exudation of organic acids as well as oxidative stress indicators in roots and shoots of O.sativa by decreasing Cd retention in different plant parts.These results shed light on the effectiveness of FeSO_(4) in improving the growth and upregulation of antioxidant enzyme activities of O.sativa in response to Cd stress.However,further studies at field levels are required to explore the mechanisms of FeSO_(4)-mediated reduction of the toxicity of not only Cd,but possibly also other heavy metals in plants. | JAVARIA AFZAL XIUKANG WANG MUHAMMAD HAMZAH SALEEM XUECHENG SUN SHAHID HUSSAIN IMRAN KHAN MUHAMMAD SHOAIB RANA SHAKEEL AHMED SAMRAH AFZAL AWAN SAJID FIAZ OMAR AZIZ KASHIF ALI KUBAR SHAFAQAT ALI CHENGXIAO HU | 2021 | BIOCELL2021，45，6： | 0 |
| 10 | ExpressionHash: Securing Telecare Medical Information Systems Using BioHashing显示文摘The COVID-19 outbreak and its medical distancing phenomenon have effectively turned the global healthcare challenge into an opportunity for Telecare Medical Information Systems.Such systems employ the latest mobile and digital technologies and provide several advantages like minimal physical contact between patient and healthcare provider,easy mobility,easy access,consistent patient engagement,and cost-effectiveness.Any leakage or unauthorized access to users’medical data can have serious consequences for any medical information system.The majority of such systems thus rely on biometrics for authenticated access but biometric systems are also prone to a variety of attacks like spoong,replay,Masquerade,and stealing of stored templates.In this article,we propose a new cancelable biometric approach which has tentatively been named as“Expression Hash”for Telecare Medical Information Systems.The idea is to hash the expression templates with a set of pseudo-random keys which would provide a unique code(expression hash).This code can then be serving as a template for verication.Different expressions would result in different sets of expression hash codes,which could be used in different applications and for different roles of each individual.The templates are stored on the server-side and the processing is also performed on the server-side.The proposed technique is a multi-factor authentication system and provides advantages like enhanced privacy and security without the need for multiple biometric devices.In the case of compromise,the existing code can be revoked and can be directly replaced by a new set of expression hash code.The well-known JAFFE(The Japanese Female Facial Expression)dataset has been for empirical testing and the results advocate for the efcacy of the proposed approach. | Ayesha Riaz Naveed Riaz Awais Mahmood Sajid Ali Khan Imran Mahmood Omar Almutiry Habib Dhahri | 2021 | Computers, Materials & Continua2021，，6： | 0 |
| 11 | An Improved Dictionary Cracking Scheme Based on Multiple GPUs for Wi-Fi Network显示文摘The Internet has penetrated all aspects of human society and has promoted social progress.Cyber-crimes in many forms are commonplace and are dangerous to society and national security.Cybersecurity has become a major concern for citizens and governments.The Internet functions and software applications play a vital role in cybersecurity research and practice.Most of the cyber-attacks are based on exploits in system or application software.It is of utmost urgency to investigate software security problems.The demand for Wi-Fi applications is proliferating but the security problem is growing,requiring an optimal solution from researchers.To overcome the shortcomings of the wired equivalent privacy(WEP)algorithm,the existing literature proposed security schemes forWi-Fi protected access(WPA)/WPA2.However,in practical applications,the WPA/WPA2 scheme still has some weaknesses that attackers exploit.To destroy a WPA/WPA2 security,it is necessary to get a PSK pre-shared key in pre-shared key mode,or an MSK master session key in the authentication mode.Brute-force cracking attacks can get a phase-shift keying(PSK)or a minimum shift keying(MSK).In real-world applications,many wireless local area networks(LANs)use the pre-shared key mode.Therefore,brute-force cracking of WPA/WPA2-PSK is important in that context.This article proposes a new mechanism to crack theWi-Fi password using a graphical processing unit(GPU)and enhances the efficiency through parallel computing of multiple GPU chips.Experimental results show that the proposed algorithm is effective and provides a procedure to enhance the security of Wi-Fi networks. | Majdi K.Qabalin Zaid A.Arida Omar A.Saraereh Falin Wu Imran Khan Peerapong Uthansakul Moath Alsafasfeh | 2021 | Computers, Materials & Continua2021，，3： | 0 |
| 12 | MEC-IoT-Healthcare: Analysis and Prospects显示文摘Physical sensors,intelligent sensors,and output recommenda-tions are all examples of smart health technology that can be used to monitor patients’health and change their behavior.Smart health is an Internet-of-Things(IoT)-aware network and sensing infrastructure that provides real-time,intelligent,and ubiquitous healthcare services.Because of the rapid development of cloud computing,as well as related technologies such as fog computing,smart health research is progressively moving in the right direction.Cloud,fog computing,IoT sensors,blockchain,privacy and security,and other related technologies have been the focus of smart health research in recent years.At the moment,the focus in cloud and smart health research is on how to use the cloud to solve the problem of enormous health data and enhance service performance,including cloud storage,retrieval,and calculation of health big data.This article reviews state-of-the-art edge computing methods that has shifted to the collection,transmission,and calculation of health data,which includes various sensors and wearable devices used to collect health data,various wireless sensor technologies,and how to process health data and improve edge performance,among other things.Finally,the typical smart health application cases,blockchain’s application in smart health,and related privacy and security issues were reviewed,as well as future difficulties and potential for smart health services.The comparative analysis provides a reference for the the mobile edge computing in healthcare systems. | Hongyuan Wang Mohammed Dauwed Imran Khan Nor Samsiah Sani Hasmila Amirah Omar Hirofumi Amano Samih M.Mostafa | 2023 | Computers, Materials & Continua2023，，6： | 0 |
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