|
|
|
题名
|
作者
|
年代
|
出处
|
被引量
|
| 1 | A Hybrid Deep Learning Architecture for the Classification of Superhero Fashion Products:An Application for Medical-Tech Classification显示文摘Comic character detection is becoming an exciting and growing research area in the domain of machine learning.In this regard,recently,many methods are proposed to provide adequate performance.However,most of these methods utilized the custom datasets,containing a few hundred images and fewer classes,to evaluate the performances of their models without comparing it,with some standard datasets.This article takes advantage of utilizing a standard publicly dataset taken from a competition,and proposes a generic data balancing technique for imbalanced dataset to enhance and enable the in-depth training of the CNN.In addition,to classify the superheroes efficiently,a custom 17-layer deep convolutional neural network is also proposed.The computed results achieved overall classification accuracy of 97.9%which is significantly superior to the accuracy of competition’s winner. | Inzamam Mashood Nasir Muhammad Attique Khan Majed Alhaisoni Tanzila Saba Amjad Rehman Tassawar Iqbal | 2020 | Computer Modeling in Engineering & Sciences2020，，9： | 1 |
| 2 | Abstract 3274 : early symp- tom onset to arterial puncture time in the endovascular management of acute ischemic stroke predicts successful revascularization 显示文摘 | Richard SJ Jitendra S Tanzila S | 2012 | Stroke2012，43，： | 1 |
| 3 | Dual blockade of endothelin action exacerbates up-regulated VEGF angiogenic signaling in the heart of lipopolysaccharide-induced endotoxemic rat model显示文摘 | Masami Oki Subrina Jesmin Md. Majedul Islam Chishimba Nathan Mowa Tanzila Khatun Nobutake Shimojo Hideaki Sakuramoto Junko Kamiyama Satoru Kawano Takashi Miyauchi Taro Mizutani | 2014 | Life Sciences2014，，： | 1 |
| 4 | Implications of E - learning systems and self-efficiency on students outcomes: a model approach 显示文摘 | Tanzila Saba | 2012 | Human - centric Computing and Information Sciences2012，，2： | 1 |
| 5 | Profiling Casualty Severity Levels of Road Accident Using Weighted Majority Voting显示文摘To determine the individual circumstances that account for a road traffic accident,it is crucial to consider the unplanned connections amongst various factors related to a crash that results in high casualty levels.Analysis of the road accident data concentrated mainly on categorizing accidents into different types using individually built classification methods which limit the prediction accuracy and fitness of the model.In this article,we proposed a multi-model hybrid framework of the weighted majority voting(WMV)scheme with parallel structure,which is designed by integrating individually implemented multinomial logistic regression(MLR)and multilayer perceptron(MLP)classifiers using three different accident datasets i.e.,IRTAD,NCDB,and FARS.The proposed WMV hybrid scheme overtook individual classifiers in terms of modern evaluation measures like ROC,RMSE,Kappa rate,classification accuracy,and performs better than state-of-theart approaches for the prediction of casualty severity level.Moreover,the proposed WMV hybrid scheme adds up to accident severity analysis through knowledge representation by revealing the role of different accident-related factors which expand the risk of casualty in a road crash.Critical aspects related to casualty severity recognized by the proposed WMV hybrid approach can surely support the traffic enforcement agencies to develop better road safety plans and ultimately save lives. | Saba Awan Zahid Mehmood Hassan Nazeer Chaudhry Usman Tariq Amjad Rehman Tanzila Saba Muhammad Rashid | 2022 | Computers, Materials & Continua2022，，6： | 1 |
| 6 | Detection of Copy-Move Forgery in Digital Images Using Singular Value Decomposition显示文摘This paper presents an improved approach for detecting copy-move forgery based on singular value decomposition(SVD).It is a block-based method where the image is scanned from left to right and top to down by a sliding window with a determined size.At each step,the SVD is determined.First,the diagonal matrix’s maximum value(norm)is selected(representing the scaling factor for SVD and a fixed value for each set of matrix elements even when rotating thematrix or scaled).Then,the similar norms are grouped,and each leading group is separated into many subgroups(elements of each subgroup are neighbors)according to 8-adjacency(the subgroups for each leading group must be far from others by a specific distance).After that,a weight is assigned for each subgroup to classify the image as forgery or not.Finally,the F1 score of the proposed system is measured,reaching 99.1%.This approach is robust against rotation,scaling,noisy images,and illumination variation.It is compared with other similarmethods and presents very promised results. | Zaid Nidhal Khudhair Farhan Mohamed Amjad Rehman Tanzila Saba Saeed Ali bahaj | 2023 | Computers, Materials & Continua2023，，2： | 1 |
| 7 | Evidence-based review of primary and secondary ischemic stroke prevention in adults: a neurosurgical perspective显示文摘 | Manjila Tony Masri Tanzila Shams | 2011 | Neurosurgical focus2011，30，6： | 1 |
| 8 | Statistical Histogram Decision Based Contrast Categorization of Skin Lesion Datasets Dermoscopic Images显示文摘Most of the melanoma cases of skin cancer are the life-threatening form of cancer.It is prevalent among the Caucasian group of people due to their light skin tone.Melanoma is the second most common cancer that hits the age group of 15–29 years.The high number of cases has increased the importance of automated systems for diagnosing.The diagnosis should be fast and accurate for the early treatment of melanoma.It should remove the need for biopsies and provide stable diagnostic results.Automation requires large quantities of images.Skin lesion datasets contain various kinds of dermoscopic images for the detection of melanoma.Three publicly available benchmark skin lesion datasets,ISIC 2017,ISBI 2016,and PH2,are used for the experiments.Currently,the ISIC archive and PH2 are the most challenging and demanding dermoscopic datasets.These datasets’pre-analysis is necessary to overcome contrast variations,under or over segmented images boundary extraction,and accurate skin lesion classification.In this paper,we proposed the statistical histogram-based method for the pre-categorization of skin lesion datasets.The image histogram properties are utilized to check the image contrast variations and categorized these images into high and low contrast images.The two performance measures,processing time and efficiency,are computed for evaluation of the proposed method.Our results showed that the proposed methodology improves the pre-processing efficiency of 77%of ISIC 2017,67%of ISBI 2016,and 92.5%of PH2 datasets. | Rabia Javed Mohd Shafry Mohd Rahim Tanzila Saba Suliman Mohamed Fati Amjad Rehman Usman Tariq | 2021 | Computers, Materials & Continua2021，，5： | 0 |
| 9 | Target specificity of selective bioactive compounds in blocking α-dystroglycan receptor to suppress Lassa virus infection: an in silico approach显示文摘Lassa hemorrhagic fever,caused by Lassa mammarenavirus(LASV)infection,accumulates up to 5000 deaths every year.Currently,there is no vaccine available to combat this disease.In this study,a library of 200 bioactive compounds was virtually screened to study their drug-likeness with the capacity to block theα-dystroglycan(α-DG)receptor and prevent LASV influx.Following rigorous absorption,distribution,metabolism,and excretion(ADME)and quantitative structure-activity relationship(QSAR)profiling,molecular docking was conducted with the top ligands against theα-DG receptor.The compounds chrysin,reticuline,and 3-caffeoylshikimic acid emerged as the top three ligands in terms of binding affinity.Post-docking analysis revealed that interactions with Arg76,Asn224,Ser259,and Lys302 amino acid residues of the receptor protein were important for the optimum binding affinity of ligands.Molecular dynamics simulation was performed comprehensively to study the stability of the protein-ligand complexes.In-depth assessment of root-mean-square deviation(RMSD),root mean square fluctuation(RMSF),polar surface area(PSA),B-Factor,radius of gyration(Rg),solvent accessible surface area(SASA),and molecular surface area(MolSA)values of the protein-ligand complexes affirmed that the candidates with the best binding affinity formed the most stable protein-ligand complexes.To authenticate the potentialities of the ligands as target-specific drugs,an in vivo study is underway in real time as the continuation of the research. | Adittya Arefin Tanzila Ismail Ema Tamnia Islam MdSaddam Hossen Tariqul Islam Salauddin Al Azad MdNasir Uddin Badal MdAminul Islam Partha Biswas Nafee Ul Alam Enayetul Islam Maliha Anjum Afsana Masud MdShaikh Kamran Ahsab Rahman Parag Kumar Paul | 2021 | The Journal of Biomedical Research2021，35，6： | 0 |
| 10 | ANTIVIRAL EFFECTS OF BACTERIOCIN AGAINST ANIMAL-TO-HUMAN TRANSMITTABLE MUTATED SARS-COV-2:A SYSTEMATIC REVIEW显示文摘The COVID-19 caused by SARS-CoV-2 has resulted in millions of people being infected and thousands of deaths globally since November 2019.To date,no unique therapeutic agent has been developed to slow the progression of this pandemic.Despite possessing antiviral traits the potential of bacteriocins to combat SARS-CoV-2 infection has not been fully investigated.This review summarizes the mechanisms by which bacteriocins can be manipulated and implemented as effective virus entry blockers with infection suppression potential properties to highly transmissible viruses through comprehensive immune modulations that are potentially effective against COVID-19.These antimicrobial peptides have been suggested as effective antiviral therapeutics and therapeutic supplements to prevent rapid virus transmission.This review also provides a new insight into the cellular and molecular alterations which have made SARS-CoV-2 self-modified with diversified infection patterns.In addition,the possible applications of antimicrobial peptides through both natural and induced mechanisms in infection prevention perspectives on changeable virulence cases are comprehensively analyzed.Specific attention is given to the antiviral mechanisms of the molecules along with their integrative use with synthetic biology and nanosensor technology for rapid detection.Novel bacteriocin based therapeutics with cutting-edge technologies might be potential substitutes for existing time-consuming and expensive approaches to fight this newly emerged global threat. | Dipta DEY Tanzila Ismail EMA Partha BISWAS Sharmin AKTAR Shoeba ISLAM Urmi Rahman RINIK Mahmudul FIROZ Shahlaa Zernaz AHMED Salauddin AL AZAD Ahsab RAHMAN Sadia AFRIN Rezwan Ahmed MAHEDI MdNasir Uddin BADAL | 2021 | Frontiers of Agricultural Science and Engineering2021，8，4： | 0 |
| 11 | Efficiency and safety of sofosbuvir in Bangladeshi children with chronic hepatitis C virus显示文摘Background and aims:Currently,treatment with oral direct-acting antivirals is recommended for all hepatitis C virus(HCV)-infected pediatric patients.The aim of this study was to evaluate the efficacy and safety of sofosbuvir and ribavirin combination ther apy for children and adolescents in Bangladesh who are living with chronic HCV in fection.Methods:An experimental study was performed from January 2021 to December 2022.HCV polymerase chain reaction(PCR)-positive thalassemic children,who were 6–18 years of age,were enrolled by consecutive non-probability sampling.Clinical features were recorded,and investigations were performed.All patients were initially treated with sofosbuvir(200 mg for 6-to 11-year-olds and 400 mg for 12-to 18-year-olds)and ribavirin(10–15 mg/kg/day)and were assessed clinically on a four-weekly basis,along with liver-function testing.The total duration of therapy was 24 weeks.HCV PCR was done at the end of treatment and 12 weeks after the completion of treatment to see the sustained virological response.Results:There were 26 cases in total,with a mean age of 9.26?2.82 years;14 were males(53.8%),and 12 females(46.2%).Twenty-five(96.15%)patients achieved a sustained virological response,and the end-of-treatment PCR was negative.One patient(3.85%)was a nonresponder even after 24 weeks of treatment.The medication was well received,with only four patients(15.3%)reporting headaches that were reported untreated.Conclusion:The combination of sofosbuvir and ribavirin is effective in treating chronic HCV infection and is not accompanied by any major negative side effects. | Salahuddin Mahmud Jahida Gulshan MdBelayet Hossain Madhabi Baidya Rafia Rashid Farhana Tasneem Ahmed Rashidul Hasan Tanzila Farhana Mohammed Reaz Mobarak MdJahangir Alam Syed Shafi Ahmed | 2023 | iLIVER2023，2，3： | 0 |
| 12 | A New Hybrid SARFIMA-ANN Model for Tourism Forecasting显示文摘Many countries developed and increased greenery in their country sights to attract international tourists.This planning is now significantly contributing to their economy.The next task is to facilitate the tourists by sufficient arrangements and providing a green and clean environment;it is only possible if an upcoming number of tourists’arrivals are accurately predicted.But accurate prediction is not easy as empirical evidence shows that the tourists’arrival data often contains linear,nonlinear,and seasonal patterns.The traditional model,like the seasonal autoregressive fractional integrated moving average(SARFIMA),handles seasonal trends with seasonality.In contrast,the artificial neural network(ANN)model deals better with nonlinear time series.To get a better forecasting result,this study combines the merits of the SARFIMA and the ANN models and the purpose of the hybrid SARFIMA-ANN model.Then,we have used the proposed model to predict the tourists’arrival inNew Zealand,Australia,and London.Empirical results showed that the proposed hybrid model outperforms in predicting tourists’arrival compared to the traditional SARFIMA and ANN models.Moreover,these results can be generalized to predict tourists’arrival in any country or region with a complicated data pattern. | Tanzila Saba Mirza Naveed Shahzad Sonia Iqbal Amjad Rehman Ibrahim Abunadi | 2022 | Computers, Materials & Continua2022，，6： | 0 |
| 13 | Swarm-LSTM: Condition Monitoring of Gearbox Fault Diagnosis Based on Hybrid LSTM Deep Neural Network Optimized by Swarm Intelligence Algorithms显示文摘Nowadays,renewable energy has been emerging as the major source of energy and is driven by its aggressive expansion and falling costs.Most of the renewable energy sources involve turbines and their operation and maintenance are vital and a difficult task.Condition monitoring and fault diagnosis have seen remarkable and revolutionary up-gradation in approaches,practices and technology during the last decade.Turbines mostly do use a rotating type of machinery and analysis of those signals has been challenging to localize the defect.This paper proposes a new hybrid model wherein multiple swarm intelligence models have been evaluated to optimize the conventional Long Short-Term Memory(LSTM)model in classifying the faults from the vibration signals data acquired from the gearbox.This helps to analyze the performance and behavioral patterns of the system more effectively and efficiently which helps to suggest for replacement of the unit with higher precision.The results have demonstrated that the proposed hybrid modeling approach is effective in classifying the faults of the gearbox from the time series data and achieve higher diagnostic accuracy in comparison to the conventional LSTM methods. | Gopi Krishna Durbhaka Barani Selvaraj Mamta Mittal Tanzila Saba Amjad Rehman Lalit Mohan Goyal | 2021 | Computers, Materials & Continua2021，，2： | 0 |
| 14 | Crowd region detection in outdoor scenes using color spaces显示文摘In the last few decades,crowd detection has gained much interest from the research community to assist a variety of applications in surveillance systems.While human detection in partially crowded scenarios have achieved many reliable works,a highly dense crowdlike situation still is far from being solved.Densely crowded scenes offer patterns that could be used to tackle these challenges.This problem is challenging due to the crowd volume,occlusions,clutter and distortion.Crowd region classification is a precursor to several types of applications.In this paper,we propose a novel approach for crowd region detection in outdoor densely crowded scenarios based on color variation context and RGB channel dissimilarity.Experimental results are presented to demonstrate the effectiveness of the new color-based features for better crowd region detection. | Huma Chaudhry Mohd Shafry Mohd Rahim Tanzila Saba Amjad Rehman | 2018 | International Journal of Modeling, Simulation, and Scientific Computing2018，9，2： | 0 |
| 15 | IoMT Enabled Melanoma Detection Using Improved Region Growing Lesion Boundary Extraction显示文摘The Internet ofMedical Things(IoMT)and cloud-based healthcare applications,services are beneficial for better decision-making in recent years.Melanoma is a deadly cancer with a highermortality rate than other skin cancer types such as basal cell,squamous cell,andMerkel cell.However,detection and treatment at an early stage can result in a higher chance of survival.The classical methods of detection are expensive and labor-intensive.Also,they rely on a trained practitioner’s level,and the availability of the needed equipment is essential for the early detection of Melanoma.The current improvement in computer-aided systems is providing very encouraging results in terms of precision and effectiveness.In this article,we propose an improved region growing technique for efficient extraction of the lesion boundary.This analysis and detection ofMelanoma are helpful for the expert dermatologist.The CNN features are extracted using the pre-trained VGG-19 deep learning model.In the end,the selected features are classified by SVM.The proposed technique is gauged on openly accessible two datasets ISIC 2017 and PH2.For the evaluation of our proposed framework,qualitative and quantitative experiments are performed.The suggested segmentation method has provided encouraging statistical results of Jaccard index 0.94,accuracy 95.7%on ISIC 2017,and Jaccard index 0.91,accuracy 93.3%on the PH2 dataset.These results are notably better than the results of prevalent methods available on the same datasets.The machine learning SVMclassifier executes significantly well on the suggested feature vector,and the comparative analysis is carried out with existing methods in terms of accuracy.The proposed method detects and classifies melanoma far better than other methods.Besides,our framework gained promising results in both segmentation and classification phases. | Tanzila Saba Rabia Javed Mohd Shafry Mohd Rahim Amjad Rehman Saeed Ali Bahaj | 2022 | Computers, Materials & Continua2022，，6： | 0 |
| 16 | Efficient Facial Recognition Authentication Using Edge and Density Variant Sketch Generator显示文摘Image translation plays a significant role in realistic image synthesis,entertainment tasks such as editing and colorization,and security including personal identification.In Edge GAN,the major contribution is attribute guided vector that enables high visual quality content generation.This research study proposes automatic face image realism from freehand sketches based on Edge GAN.We propose a density variant image synthesis model,allowing the input sketch to encompass face features with minute details.The density level is projected into non-latent space,having a linear controlled function parameter.This assists the user to appropriately devise the variant densities of facial sketches and image synthesis.Composite 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 approach.The solution is validated to have the capability for generating realistic face images through quantitative and qualitative results and human evaluation. | Summra Saleem M.Usman Ghani Khan Tanzila Saba Ibrahim Abunadi Amjad Rehman Saeed Ali Bahaj | 2022 | Computers, Materials & Continua2022，，1： | 0 |
| 17 | Induced magnetic field stagnation point flow of nanofluid past convectively heated stretching sheet with Buoyancy effects显示文摘This paper presents the buoyancy effects on the magneto-hydrodynamics stagnation point flow of an incompressible,viscous,and electrically conducting nanofluid over a vertically stretching sheet.The impacts of an induced magnetic field and viscous dissipation are taken into account.Both assisting and opposing flows are considered.The overseeing nonlinear partial differential equations with the associated boundary conditions are reduced to an arrangement of coupled nonlinear ordinary differential equations utilizing similarity transformations and are then illuminated analytically by using the optimal homotopy investigation strategy(OHAM).Graphs are introduced and examined for different parameters of the velocity,temperature,and concentration profile.Additionally,numerical estimations of the skin friction,local Nusselt number,and local Sherwood number are explored using numerical values. | Tanzila Hayat S Nadeem | 2016 | Chinese Physics B2016，25，11： | 0 |
| 18 | Cognitive Skill Enhancement System Using Neuro-Feedback for ADHD Patients显示文摘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),globally.The treatment methods for ADHD are either psycho-stimulant medications or cognitive therapy.These traditional methods,namely therapy,need a large number of visits to hospitals and include medication.Neurogames could be used for the effective treatment of ADHD.It 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 signals.This paper proposes a system based on neurofeedback that can improve cognitive skills such as attention level,mediation level,and spatial memory.The proposed system consists of a puzzle game where its complexity increases with each level.EEG signals were acquired using the Neurosky headset;then sent the signals to the designed gaming environment.This neurofeedback system was tested on 10 different subjects,and their performance was calculated using different evaluation measures.The results show that this game improves player overall performance from 74%to 98%by playing each game level. | Muhammad Usman Ghani Khan Zubaira Naz Javeria Khan Tanzila Saba Ibrahim Abunadi Amjad Rehman Usman Tariq | 2021 | Computers, Materials & Continua2021，，8： | 0 |
| 19 | Dynamic transcriptional programs define distinct mammalian cortical lineages显示文摘The cerebral cortex is composed of billions of neurons and glia that are generated sequentially during corticogenesis.These cells are generated in an organized fashion during development.At early stages of brain development,neural stem cells(NSCs)undergo symmetric divisions to expand their pool. | Tanzila Mukhtar Verdon Taylor | 2024 | Neural Regeneration Research2024，19，2： | 0 |
| 20 | Role of T cells in cancer immunotherapy:Opportunities and challenges显示文摘Immunotherapies boosting the immune system's ability to target cancer cells are promising for the treatment of various tumor types,yet clinical responses differ among patients and cancers.Recently,there has been increasing interest in novel cancer immunotherapy practices aimed at triggering T cell-mediated anti-tumor responses.Antigen-directed cytotoxicity mediated by T lymphocytes has become a central focal point in the battle against cancer utilizing the immune system.The molecular and cellular mechanisms involved in the actions of T lymphocytes have directed new therapeutic approaches in cancer immunotherapy,including checkpoint blockade,adoptive and chimeric antigen receptor(CAR)T cell therapy,and cancer vaccinology.This review addresses all the strategies targeting tumor pathogenesis,including metabolic pathways,to evaluate the clinical significance of current and future immunotherapies for patients with cancer,which are further engaged in T cell activation,differentiation,and response against tumors. | Hossain Ahmed Aar Rafi Mahmud Mohd.Faijanur-Rob-Siddiquee Asif Shahriar Partha Biswas Ebrahim Khalil Shimul Shahlaa Zernaz Ahmed Tanzila Ismail Ema Nova Rahman Arif Khan Furkanur Rahaman Mizan Talha Bin Emran | 2023 | Cancer Pathogenesis and Therapy2023，1，2： | 0 |
您所在的机构暂未开通此部分的功能，请联系管理员