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| 1 | Structural, morphological, Raman, optical, magnetic, and antibacterial characteristics of CeO2 nanostructures显示文摘In this study, CeO_2 nanostructures were synthesized by a soft chemical method. A hydrothermal treatment was observed to lead to an interesting morphological transformation of the nanoparticles into homogeneous microspheres composed of nanosheets with an average thickness of 40 nm. Structural analysis revealed the formation of a single-phase cubic fluorite structure of CeO_2 for both samples. A Raman spectroscopic study confirmed the XRD results and furthermore indicated the presence of a large number of oxygen vacancies in the nanosheets. These oxygen vacancies led to room-temperature ferromagnetism(RTFM) of the CeO_2 nanosheets with enhanced magnetic characteristics. Amazingly, the nanosheets exhibited substantially greater antibacterial activity than the nanoparticles. This greater antibacterial activity was attributed to greater exposure of high-surface-energy polar surfaces and to the presence of oxygen vacancies. | Fazal Abbas Javed Iqbal Tariq Jan Noor Badshah Qaisar Mansoor Muhammad Ismail | 2016 | International Journal of Minerals,Metallurgy and Materials2016，23，1： | 6 |
| 2 | Strengths,weaknesses,opportunities,and threats(SWOT)analysis of supercapacitors:A review显示文摘The development of clean and sustainable energy sources has received widespread interest in the past few decades due to the rolling energy demands while extenuating the rising tiers of greenhouse gases and environmental pollution.Due to their intermittent nature,these green and sustainable sources require appropriate energy storage systems.Amongst different energy storage technologies,electrochemical energy storage devices,particularly supercapacitors(SCs),have fascinated global attention for their utilization in electric vehicles,power supports,portable electronics,and many others application requiring electric energy devices for their operation.Thus,the growth of SCs in the commercial market has squeezed requirements,and further developments are obligatory for their effective industrialization.In the meantime,SCs also face technical complications and contests for their introduction in industrial settings because of their low energy density and high Levelized cost.The present study combines core strengths,weaknesses,opportunities,and threats(SWOT)analysis of SCs with new perspectives and recent ideas.The challenges and the future progressive prospects of SCs are also presented in detail.This review will afford consistent direction and new superhighways for the further development of SCs as standalone and complementary energy storage systems. | Pragati A.Shinde Qaisar Abbas Nilesh R.Chodankar Katsuhiko Ariga Mohammad Ali Abdelkareem Abdul Ghani Olabi | 2023 | Journal of Energy Chemistry2023，，4： | 2 |
| 3 | Per- ceived investment in employee development and turnover intention:A social exchange perspective显示文摘 | Omer Farooq Malik Qaisar Abbas Talat Mahmood Kiyani Khalil-Ur-Rehman Malik Aamer Waheed | 1904 | African Journal of Business Management1904，5，5： | 1 |
| 4 | The relevance of pecking order hypothesis for the financing of computer software and biotechnology small firms: some UK evidence显示文摘 | Farid Ullah Qaisar Abbas Saeed Akbar | 2010 | International Entrepreneurship and Management Journal2010，，3： | 1 |
| 5 | A Flexible Boundary Procedure for Hyperbolic Problems: Multiple Penalty Terms Applied in a Domain显示文摘A new weak boundary procedure for hyperbolic problems is presented.We consider high order finite difference operators of summation-by-parts form with weak boundary conditions and generalize that technique.The new boundary procedure is applied near boundaries in an extended domain where data is known.We show how to raise the order of accuracy of the scheme,how to modify the spectrum of the resulting operator and how to construct non-reflecting properties at the boundaries.The new boundary procedure is cheap,easy to implement and suitable for all numerical methods,not only finite difference methods,that employ weak boundary conditions.Numerical results that corroborate the analysis are presented. | Jan Nordstrom Qaisar Abbas Brittany A.Erickson Hannes Frenander | 2014 | Communications in Computational Physics2014，16，7： | 0 |
| 6 | A Semantic Adversarial Network for Detection and Classification of Myopic Maculopathy显示文摘The diagnosis of eye disease through deep learning (DL) technologyis the latest trend in the field of artificial intelligence (AI). Especially indiagnosing pathologic myopia (PM) lesions, the implementation of DL is adifficult task because of the classification complexity and definition system ofPM. However, it is possible to design an AI-based technique that can identifyPM automatically and help doctors make relevant decisions. To achieve thisobjective, it is important to have adequate resources such as a high-qualityPM image dataset and an expert team. The primary aim of this research isto design and train the DLs to automatically identify and classify PM intodifferent classes. In this article, we have developed a new class of DL models(SAN-FSL) for the segmentation and detection of PM through semanticadversarial networks (SAN) and few-short learning (FSL) methods, respectively.Compared to DL methods, the conventional segmentation methodsuse supervised learning models, so they (a) require a lot of data for trainingand (b) fixed weights are used after the completion of the training process.To solve such problems, the FSL technique was employed for model trainingwith few samples. The ability of FSL learning in UNet architectures is beingexplored, and to fine-tune the weights, a few new samples are being providedto the UNet. The outcomes show improvement in the detection area andclassification of PM stages. Betterment in the result is observed by sensitivity(SE) of 95%, specificity (SP) of 96%, and area under the receiver operatingcurve (AUC) of 98%, and the higher F1-score is achieved using 10-fold crossvalidation.Furthermore, the obtained results confirmed the superiority of theSAN-FSL method. | Qaisar Abbas Abdul Rauf Baig Ayyaz Hussain | 2023 | Computers, Materials & Continua2023，，4： | 0 |
| 7 | Hypo-Driver: A Multiview Driver Fatigue and Distraction Level Detection System显示文摘Traffic accidents are caused by driver fatigue or distraction in many cases.To prevent accidents,several low-cost hypovigilance(hypo-V)systems were developed in the past based on a multimodal-hybrid(physiological and behavioral)feature set.Similarly in this paper,real-time driver inattention and fatigue(Hypo-Driver)detection system is proposed through multi-view cameras and biosignal sensors to extract hybrid features.The considered features are derived from non-intrusive sensors that are related to the changes in driving behavior and visual facial expressions.To get enhanced visual facial features in uncontrolled environment,three cameras are deployed on multiview points(0◦,45◦,and 90◦)of the drivers.To develop a Hypo-Driver system,the physiological signals(electroencephalography(EEG),electrocardiography(ECG),electro-myography(sEMG),and electrooculography(EOG))and behavioral information(PERCLOS70-80-90%,mouth aspect ratio(MAR),eye aspect ratio(EAR),blinking frequency(BF),head-titled ratio(HT-R))are collected and pre-processed,then followed by feature selection and fusion techniques.The driver behaviors are classified into five stages such as normal,fatigue,visual inattention,cognitive inattention,and drowsy.This improved hypo-Driver system utilized trained behavioral features by a convolutional neural network(CNNs),recurrent neural network and long short-term memory(RNN-LSTM)model is used to extract physiological features.After fusion of these features,the Hypo-Driver system is classified hypo-V into five stages based on trained layers and dropout-layer in the deep-residual neural network(DRNN)model.To test the performance of a hypo-Driver system,data from 20 drivers are acquired.The results of Hypo-Driver compared to state-of-theart methods are presented.Compared to the state-of-the-art Hypo-V system,on average,the Hypo-Driver system achieved a detection accuracy(AC)of 96.5%.The obtained results indicate that the Hypo-Driver system based on multimodal and multiview features outperforms other state-of-the-art driver Hypo-V systems by handling many anomalies. | Qaisar Abbas Mostafa EAIbrahim Shakir Khan Abdul Rauf Baig | 2022 | Computers, Materials & Continua2022，，4： | 0 |
| 8 | Transfer Learning-based Computer-aided Diagnosis System for Predicting Grades of Diabetic Retinopathy显示文摘Diabetic retinopathy(DR)diagnosis through digital fundus images requires clinical experts to recognize the presence and importance of many intricate features.This task is very difficult for ophthalmologists and timeconsuming.Therefore,many computer-aided diagnosis(CAD)systems were developed to automate this screening process ofDR.In this paper,aCAD-DR system is proposed based on preprocessing and a pre-train transfer learningbased convolutional neural network(PCNN)to recognize the five stages of DR through retinal fundus images.To develop this CAD-DR system,a preprocessing step is performed in a perceptual-oriented color space to enhance the DR-related lesions and then a standard pre-train PCNN model is improved to get high classification results.The architecture of the PCNN model is based on three main phases.Firstly,the training process of the proposed PCNN is accomplished by using the expected gradient length(EGL)to decrease the image labeling efforts during the training of the CNN model.Secondly,themost informative patches and images were automatically selected using a few pieces of training labeled samples.Thirdly,the PCNN method generated useful masks for prognostication and identified regions of interest.Fourthly,the DR-related lesions involved in the classification task such as micro-aneurysms,hemorrhages,and exudates were detected and then used for recognition of DR.The PCNN model is pre-trained using a high-end graphical processor unit(GPU)on the publicly available Kaggle benchmark.The obtained results demonstrate that the CAD-DR system outperforms compared to other state-of-the-art in terms of sensitivity(SE),specificity(SP),and accuracy(ACC).On the test set of 30,000 images,the CAD-DR system achieved an average SE of 93.20%,SP of 96.10%,and ACC of 98%.This result indicates that the proposed CAD-DR system is appropriate for the screening of the severity-level of DR. | Qaisar Abbas Mostafa E.A.Ibrahim Abdul Rauf Baig | 2022 | Computers, Materials & Continua2022，，6： | 0 |
| 9 | An optical-sensing modality that exploits Dyakonov–Tamm waves显示文摘Surface-wave-based optical sensing of an analyte in a fluid relies on the sensitivity of the surface wave to the electromagnetic properties of the analyte-containing fluid in the vicinity of the guiding interface. Surfaceplasmon-polariton(SPP) waves are most commonly used for optical sensing because of the ease of the excitation of an SPP wave when the fluid is partnered with a metal. If the fluid is replaced by a porous, anisotropic, and periodically nonhomogeneous solid filled with the fluid, while the metal is replaced by an isotropic homogeneous dielectric material, the surface wave is called a Dyakonov–Tamm(DT) wave. We have theoretically determined that the incorporation of the DT-waveguiding interface in a prism-coupled configuration provides an alternative to the analogous SPP wave-based sensor, with comparable dynamic sensitivity. | Farhat Abbas Akhlesh Lakhtakia Qaisar ANaqvi Muhammad Faryad | 2015 | Photonics Research2015，3，1： | 0 |
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