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Recognizing Breast Cancer Using Edge-Weighted Texture Features of Histopathology Images

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Computers, Materials & Continua 2023年第10期77卷 1081-1101页

作者： Arslan Akram Javed Rashid Fahima Hajjej Sobia yaqoob Muhammad Hamid Asma Arshad Nadeem Sarwar Department of Computer Science and Information Technology Superior UniversityLahore54000Pakistan MLC Lab Maharban HouseHouse#209Zafar ColonyOkara56300Pakistan Information Technology Services University of OkaraOkara56300Pakistan Department of CS&SE International Islamic UniversityIslamabad44000Pakistan Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Computer Science University of OkaraOkara56300Pakistan Department of Statistics and Computer Science University of Veterinary and Animal SciencesLahorePunjab54000Pakistan School of Biochemistry and Biotechnology University of the PunjabLahore54000Pakistan Department of Computer Science Bahria UniversityLahore CampusLahore54600Pakistan

Around one in eight women will be diagnosed with breast cancer at some *** patient outcomes necessitate both early detection and an accurate *** images are routinely utilized in the process of diagnosing breast *** proposed in recent research only focus on classifying breast cancer on specific magnification *** study has focused on using a combined dataset with multiple magnification levels to classify breast cancer.A strategy for detecting breast cancer is provided in the context of this *** image texture data is used with the wavelet transform in this *** proposed method comprises converting histopathological images from Red Green Blue(RGB)to Chrominance of Blue and Chrominance of Red(YCBCR),utilizing a wavelet transform to extract texture information,and classifying the images with Extreme Gradient Boosting(XGBOOST).Furthermore,SMOTE has been used for resampling as the dataset has imbalanced *** suggested method is evaluated using 10-fold cross-validation and achieves an accuracy of 99.27%on the BreakHis 1.040X dataset,98.95%on the BreakHis 1.0100X dataset,98.92%on the BreakHis 1.0200X dataset,98.78%on the BreakHis 1.0400X dataset,and 98.80%on the combined *** findings of this study imply that improved breast cancer detection rates and patient outcomes can be achieved by combining wavelet transformation with textural signals to detect breast cancer in histopathology images.

关键词： Benign and malignant color conversion wavelet domain texture features xgboost

Scalability of biomass-derived graphene derivative materials as viable anode electrode for a commercialized microbial fuel cell: A systematic review

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Chinese Journal of Chemical Engineering 2023年第3期55卷 277-292页

作者： Mustapha Omenesa Idris Claudia Guerrero-Barajas Hyun-Chul Kim Asim Ali yaqoob Mohamad Nasir Mohamad Ibrahim School of Chemical Sciences Universiti Sains Malaysia11800 PenangMalaysia Department of Pure and Industrial Chemistry Kogi State UniversityP.M.B 1008 AnyigbaKogi StateNigeria Laboratorio de Biotecnologia Ambiental Departamento de BioprocesosUnidad Profesional Interdisciplinaria de BiotecnologiaInstituto Politecnico NacionalAv.Acueducto s/nCol.Barrio La Laguna Ticoman07340 Mexico CityMexico Research Institute for Advanced Industrial Technology College of Science and TechnologyKorea UniversitySejong 30019Republic of Korea

Microbial fuel cell(MFC) is an advanced bioelectrochemical technique that can utilize biomass materials in the process of simultaneously generating electricity and biodegrading or bio transforming toxic pollutants from wastewater. The overall performance of the system is largely dependent on the efficiency of the anode electrode to enhance electron transportation. Furthermore, the anode electrode has a significant impact on the overall cost of MFC setup. Hence, the need to explore research focused towards developing cost-effective material as anode in MFC. This material must also have favourable properties for electron transportation. Graphene oxide(GO) derivatives and its modification with nanomaterials have been identified as a viable anode material. Herein, we discussed an economically effective strategy for the synthesis of graphene derivatives from waste biomass materials and its subsequent fabrication into anode electrode for MFC applications. This review article offers a promising approach towards replacing commercial graphene materials with biomass-derived graphene derivatives in a view to achieve a sustainable and commercialized MFC.

关键词： Microbial fuel cell Biomass Anode fabrication Catalyst Design Cost-effective performance

Optimizing Traffic Signals in Smart Cities Based on Genetic Algorithm

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Computer Systems Science & Engineering 2022年第1期40卷 65-74页

作者： Nagham A.Al-Madi adnan A.Hnaif Al-Zaytoonah University of Jordan Faculty of Science and Information TechnologyAmman11733Jordan

Current traffic signals in Jordan suffer from severe congestion due to many factors,such as the considerable increase in the number of vehicles and the use of fixed timers,which still control existing traffic *** condition affects travel demand on the streets of *** study aims to improve an intelligent road traffic management system(IRTMS)derived from the human community-based genetic algorithm(HCBGA)to mitigate traffic signal congestion in Amman,Jordan’s capital *** parameters considered for IRTMS are total time and waiting time,and fixed timers are still used for *** contrast,the enhanced system,called enhanced-IRTMS(E-IRTMS),considers additional important parameters,namely,the speed performance index(SPI),speed reduction index(SRI),road congestion index(R i),and congestion period,to enhance IRTMS decision.A significant reduction in congestion period was measured using E-IRTMS,improving by 13% compared with that measured using ***,the IRTMS result surpasses that of the current traffic signal system by approximately 83%.This finding demonstrates that the E-IRTMS based on HCBGA and with unfixed timers achieves shorter congestion period in terms of SPI,SRI,and R_(i) compared with IRTMS.

关键词： Genetic algorithm traffic signal congestion smart cities

Data-driven Approach for State Prediction and Detection of False Data Injection Attacks in Smart Grid

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Journal of Modern Power Systems and Clean Energy 2023年第2期11卷 455-467页

作者： Haftu Tasew Reda adnan Anwar Abdun Mahmood Naveen Chilamkurti Department of Computer Science and IT La Trobe UniversityBundooraVIC 3086Australia School of IT Deakin UniversityWaurn PondsVIC 3216Australia

In a smart grid,state estimation(SE)is a very important component of energy management *** main functions include system SE and detection of cyber ***,it has been shown that conventional SE techniques are vulnerable to false data injection(FDI)attack,which is a sophisticated new class of attacks on data integrity in smart *** main contribution of this paper is to propose a new FDI attack detection technique using a new data-driven SE model,which is different from the traditional weighted least square based SE *** SE model has a number of unique advantages compared with traditional SE ***,the prediction technique can better maintain the inherent temporal correlations among consecutive measurement ***,the proposed SE model can learn the actual power system ***,this paper shows that this SE model can be effectively used to detect FDI attacks that otherwise remain stealthy to traditional SE-based bad data *** proposed FDI attack detection technique is evaluated on a number of standard bus *** performance of state prediction and the accuracy of FDI attack detection are benchmarked against the state-ofthe-art *** results show that the proposed FDI attack detection technique has a higher detection rate compared with the existing techniques while reducing the false alarms significantly.

关键词： Data-driven false data injection machine learning power system security state estimation smart grid

Detection of Lung Nodules on X-ray Using Transfer Learning and Manual Features

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Computers, Materials & Continua 2022年第7期72卷 1445-1463页

作者： Imran Arshad Choudhry adnan N.Qureshi Faculty of Information Technology University of Central PunjabLahorePakistan

The well-established mortality rates due to lung cancers,scarcity of radiology experts and inter-observer variability underpin the dire need for robust and accurate computer aided diagnostics to provide a second *** this end,we propose a feature grafting approach to classify lung cancer images from publicly available National Institute of Health(NIH)chest X-Ray dataset comprised of 30,805 unique *** performance of transfer learning with pre-trained VGG and Inception models is evaluated in comparison against manually extracted radiomics features added to convolutional neural network using custom *** classification with both approaches,Support VectorsMachines(SVM)are *** results from the 5-fold cross validation report Area Under Curve(AUC)of 0.92 and accuracy of 96.87%in detecting lung nodules with the proposed *** is a plausible improvement against the observed accuracy of transfer learning using Inception(79.87%).The specificity of allmethods is>99%,however,the sensitivity of the proposed method(97.24%)surpasses that of transfer learning approaches(<67%).Furthermore,it is observed that the true positive rate with SVM is highest at the same false-positive rate in experiments amongst Random Forests,Decision Trees,and K-Nearest Neighbor ***,the proposed approach can be used in clinical and research environments to provide second opinions very close to the experts’intuition.

关键词： Lungs cancer convolutional neural network hand-crafted feature extraction deep learning classification

Automatic Unusual Activities Recognition Using Deep Learning in Academia

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Computers, Materials & Continua 2022年第1期70卷 1829-1844页

作者： Muhammad Ramzan adnan Abid Shahid Mahmood Awan School of Systems and Technology University of Management and TechnologyLahore54782Pakistan Department of Computer Science and Information Technology University of SargodhaSargodha40100Pakistan School of Electronics Computing and MathematicsUniversity of DerbyDerbyUnited Kingdom

In the current era,automatic surveillance has become an active research problem due to its vast real-world applications,particularly for maintaining law and order.A continuous manual monitoring of human activities is a tedious *** use of cameras and automatic detection of unusual surveillance activity has been growing exponentially over the last few *** computer vision techniques have been applied for observation and surveillance of real-world *** research study focuses on detecting and recognizing unusual activities in an academic situation such as examinationhalls,which may help the invigilators observe and restrict the students from cheating or using *** the best of our knowledge,this is the first research work in this area that develops a dataset for unusual activities in the examination and proposes a deep learning model to detect those unusual *** proposed model has been named Automatic Unusual Activity Recognition(AUAR),which employsmotion-based frame extraction approaches to extract key-frames and then applies advanced deep learning Convolutional Neural Network algorithm with diverse *** evaluation using standard performancemeasures confirmthat theAUARmodel outperforms the already proposed approaches for unusual activity *** from evaluating the proposed model on the examination dataset,we also apply AUAR on Violent and Movies datasets,widely used in the relevant literature to detect suspicious *** results reveal that AUAR performs well on various data sets compared to existing state-of-the-art models.

关键词： Deep learning unusual activities examination CNN surveillance human activity recognition

Traversable wormhole solutions in the f(R)theories of gravity under the Karmarkar condition

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Chinese Physics C 2022年第9期46卷 276-286页

作者： adnan Malik Fatemah Mofarreh Aqsa Zia Akram Ali Department of Mathematics University of Management and TechnologySialkot CampusPakistan Mathematical Science Department Faculty of Science Princess Nourah bint Abdulrahman University.Riyadh 11546 Saudi Arabia Department of Mathematics College of ScienceKing Khalid University9004 AbhaSaudi Arabia

This paper examines traversable wormhole models in the f(R) theories of gravity by applying the Karmarkar condition. For this purpose, we consider spherically symmetric space-time to examine the structure of wormholes. First, we investigate wormholes and their geometry using the redshift function under various conditions. Subsequently, we discuss the embedding diagram of the upper and lower universe using radial coordinates in two and three-dimensional Euclidean affine space. Three exclusive models are considered for the f(R) theories of gravity,and the radial and tangential pressures are observed. Furthermore, by taking a definite shape function, we observe the behavior of energy conditions. We determine that energy conditions are violated, and their violation is generic and represents the presence of exotic matter. According to Einstein’s field theory, the existence of wormholes is predicated on the occurrence of rare material. Hence, we conclude that our study is more realistic and stable.

关键词： wormhole geometry Karmarkar condition red shift function energy conditions

Advanced tools and methods for single-cell surgery

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Microsystems & Nanoengineering 2022年第2期8卷 1-21页

作者： adnan Shakoor Wendi Gao Libo Zhao Zhuangde Jiang Dong Sun Department of Biomedical Engineering City University of Hong KongHong KongChina State Key Laboratory for Manufacturing Systems Engineering International Joint Laboratory for Micro/Nano Manufacturing and Measurement TechnologiesThe School of Mechanical EngineeringXi'an Jiaotong UniversityXi'anChina

Highly precise micromanipulation tools that can manipulate and interrogate cell organelles and components must be developed to support the rapid development of new cell-based medical therapies,thereby facilitating in-depth understanding of cell dynamics,cell component functions,and disease *** paper presents a literature review on micro/nanomanipulation tools and their control methods for single-cell *** methods specifically based on laser,microneedle,and untethered micro/nanotools are presented in *** limitations of these techniques are also *** biological significance and clinical applications of single-cell surgery are also addressed in this paper.

关键词： manipulation surgery needle

Locating the Source Regions of the Single and Double-Frequency Microseisms to Investigate the Source Effects on HVSR in Site Effect Analysis

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Journal of Earth Science 2022年第5期33卷 1219-1232页

作者： Zhen Guo Mei Xue adnan Aydin Yu Huang State Key Laboratory of Marine Geology Tongji UniversityShanghai200092China College of Civil Engineering Tongji UniversityShanghai200092China Key Laboratory of Geotechnical and Underground Engineering of the Ministry of Education Tongji UniversityShanghai200092China Shanghai Sheshan National Geophysical Observatory Shanghai201602China Department of Geology and Geological Engineering University of MississippiOxfordMS38677USA

Evaluating the seismic site effect by the ambient noise based horizontal-to-vertical spectral ratio(HVSR)method is strongly affected by the spatial and temporal variations of the ambient noise ***,it is necessary to locate the source regions of ambient noise and investigate the relationships between the source energy and HVSR values at the predominant frequency(HVSRf_(0))of the *** generation mechanisms of the single-and double-frequency microseisms(SFMs,0.05-0.085 Hz and DFMs,0.1-0.5 Hz)in ambient noise are better understood than the noise in other frequency bands and they are dominantly composed of fundamental Rayleigh(Rg)*** this advantage,the recordings of SFMs and DFMs at 30 stations in the east coast region of the United States are used to demonstrate a study on locating their source regions with reasonable certainty and constructing the functional relationship between the HVSRf_(0) and the source energy of SFMs and *** recordings are processed in four sub-frequency bands(Fs)of SF and DF bands and a polarization analysis is carried out to select the ellipsoids approximating the particle motions of Rg *** the probability density functions of the back azimuths of the ellipsoids’semi-major axes are computed for each F and station,and are projected on the ocean to determine their possible source *** regions are further constrained by(1)the correlation coefficients between the SFMs and the WAVEWATCHⅢ(WWⅢ)hindcasts of ocean wave spectra in the SF band,or between the DFMs and the modeled DF energy on ocean surface in the selected time windows in the DF band,(2)the energy contribution defined by(i)the average WWⅢocean wave energy and the ocean bottom topographical gradient in the SF band,or(ii)the average modeled DF energy on ocean surface and a frequency and water depth dependent coefficient measuring the conversion efficiency of DF energy from water to solid earth in the DF band,and(3)the percentile retained energy of

关键词： seismic site effect HVSR single-frequency microseisms double-frequency microseisms polarization analysis geophysics