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Multi-hazard susceptibility mapping based on Convolutional Neural Networks

Geoscience Frontiers 2022年第5期13卷 59-74页

作者： kashif ullah Yi Wang Zhice Fang Lizhe Wang Mahfuzur Rahman Institute of Geophysics and Geomatics China University of GeosciencesWuhan 430074China State Key Laboratory of Biogeology and Environmental Geology China University of GeosciencesWuhan 430074China School of Computer Science China University of GeosciencesWuhan 430074China Hubei Key Laboratory of Intelligent Geo-Information Processing China University of GeosciencesWuhan 430074China Department of Civil Engineering International University of Business Agriculture and Technology(IUBAT)Dhaka 1230Bangladesh

Multi-hazard susceptibility prediction is an important component of disasters risk management *** effective multi-hazard risk mitigation strategy includes assessing individual hazards as well as their ***,with the rapid development of artificial intelligence technology,multi-hazard susceptibility prediction techniques based on machine learning has encountered a huge *** order to effectively solve this problem,this study proposes a multi-hazard susceptibility mapping framework using the classical deep learning algorithm of Convolutional Neural Networks(CNN).First,we use historical flash flood,debris flow and landslide locations based on Google Earth images,extensive field surveys,topography,hydrology,and environmental data sets to train and validate the proposed CNN ***,the proposed CNN method is assessed in comparison to conventional logistic regression and k-nearest neighbor methods using several objective criteria,i.e.,coefficient of determination,overall accuracy,mean absolute error and the root mean square *** results show that the CNN method outperforms the conventional machine learning algorithms in predicting probability of flash floods,debris flows and ***,the susceptibility maps of the three hazards based on CNN are combined to create a multi-hazard susceptibility *** can be observed from the map that 62.43%of the study area are prone to hazards,while 37.57%of the study area are *** hazard-prone areas,16.14%,4.94%and 30.66%of the study area are susceptible to flash floods,debris flows and landslides,*** terms of concurrent hazards,0.28%,7.11%and 3.13%of the study area are susceptible to the joint occurrence of flash floods and debris flow,debris flow and landslides,and flash floods and landslides,respectively,whereas,0.18%of the study area is subject to all the three *** results of this study can benefit engineers,disaster managers and local government offici

关键词： Multi-hazard Convolutional Neural Network Machine learning Eastern Hindukush Pakistan

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DSFA: cross-scene domain style and feature adaptation for landslide detection from high spatial resolution images

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International Journal of Digital Earth 2023年第1期16卷 2426-2447页

作者： Penglei Li Yi Wang Tongzhen Si kashif ullah Wei Han Lizhe Wang School of Geophysics and Geomatics China University of GeosciencesWuhanPeople’s Republic of China School of Computer Science Wuhan UniversityWuhanPeople’s Republic of China School of Computer Science China University of GeosciencesWuhanPeople’s Republic of China

Rapid and accurate landslide inventory mapping is significant for emergency rescue and post-disaster ***,deep learning methods exhibit excellent performance in supervised landslide ***,due to differences between cross-scene images,the performance of existing methods is significantly degraded when directly applied to another scene,which limits the application of rapid landslide inventory *** this study,we propose a novel Domain Style and Feature Adaptation(DSFA)method for cross-scene landslide detection from high spatial resolution images,which can leverage labeled source domain images and unlabeled target domain images to mine robust landslide representations for different ***,we mitigate the large discrepancy between domains at the dataset level and feature *** the dataset level,we introduce a domain style adaptation strategy to shift landslide styles,which not only bridges the domain gap,but also increases the diversity of landslide *** the feature level,adversarial learning and domain distance minimization are integrated to narrow large feature distribution discrepancies for learning domain-invariant *** addition,to avoid information omission,we improve the U-Net3+*** experimental results demonstrate that DSFA has superior detection capability and outperforms other methods,showing its great application potential in unsupervised landslide domain detection.

关键词： Landslide detection deep learning remote sensing domain adaptation high spatial resolution

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Enhancing Solar Photovoltaic Efficiency:A Computational Fluid Dynamics Analysis

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Energy Engineering 2025年第1期122卷 153-166页

作者： Rahool Rai Fareed HussainMangi kashif Ahmed Sudhakar Kumaramsay Faculty of Mechanical and Automotive Engineering Universiti Malaysia Pahang Al-Sultan AbdullahPekan26600PahangMalaysia Faculty of Engineering Science&Technology Hamdard UniversityKarachi74600Pakistan Electrical Engineering Department SUKKUR IBA UniversitySukkur65200Pakistan Berlin School of Business and Innovation BSBI Faculty of Computer Science and InformaticsBerlin12043Germany Automotive Engineering Centre University Malaysia Pahang Al Sultan AbdullahPekan26600PahangMalaysia Centre for Research in Advanced Fluid&Processes(Fluid Centre) Universiti Malaysia Pahang Al-Sultan Abdullah(UMPSA)Paya BesarKuantan26300PahangMalaysia

The growing need for sustainable energy solutions,driven by rising energy shortages,environmental concerns,and the depletion of conventional energy sources,has led to a significant focus on renewable *** energy,among the various renewable sources,is particularly appealing due to its abundant ***,the efficiency of commercial solar photovoltaic(PV)modules is hindered by several factors,notably their conversion efficiency,which averages around 19%.This efficiency can further decline to 10%–16%due to temperature increases during peak sunlight *** study investigates the cooling of PV modules by applying water to their front surface through Computational fluid dynamics(CFD).The study aimed to determine the optimal conditions for cooling the PV module by analyzing the interplay between water film thickness,Reynolds number,and their effects on temperature reduction and heat *** CFD analysis revealed that the most effective cooling condition occurred with a 5 mm thick water film and a Reynolds number of *** specific parameters were found to maximize the heat transfer and temperature reduction *** finding is crucial for the development of practical and efficient cooling systems for PV modules,potentially leading to improved performance and longevity of solar *** cooling fluids or advanced cooling techniques that might offer even better efficiency or practical benefits.

关键词： PV module efficiency water film thickness reynolds number CFD analysis PV/T renewable energy

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Reservoir characteristics of Datta Formation (Early Jurassic), Marwat-Khisor Ranges, sub-Himalayas, Pakistan

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Petroleum Science 2023年第4期20卷 2026-2044页

作者： Muhammad Tariq Muhammad kashif Noor Ahmed Zaheen ullah Jose Nicanor Mendez Muhammad Armaghan Faisal Miraj Department of Earth Sciences University of SargodhaSargodha40100Pakistan Department of Geosciences University of BaltistanSkarduPakistan School of Geosciences China University of PetroleumQingdao266580China Institute of Geology University of the PunjabLahorePakistan

The present work has been accomplished to carry out a detailed study of the characteristics of the Early Jurassic Datta Formation of Trans-Indus Ranges, Pakistan. The discovery of Saib well-1 (Gas and condensate discovery from Jurassic limestone) in the study basin takes an active interest in carrying out extensive exploration activities in the same basin. Jurassic rocks especially Datta Sandstone and Samana Suk Limestone are acting as good reservoirs. The study unit consists of variegated sandstone interbedded with siltstone, carbonaceous clay, and shale and coal stringer. For the current work, two stratigraphic sections (Pezu and Abbo Wanda) have been measured. To examine its sedimentology, depositional environment, diagenetic settings, and reservoir characteristics, a detailed study was conducted and various laboratory techniques have been utilized. About 95 rock samples from the bottom to the top of both sections were collected, and 50 rock samples have been selected for thin section analysis and were examined under a polarizing microscope to show their mineralogical composition, diagenesis, and their reservoir characteristics. XRD (X-ray diffraction), Cathodoluminescence (CL), SEM (Scanning electron microscope) with EDS (Energy-dispersive spectroscope), and Core plug porosity and permeability analysis have been used to interpret its chemical and mineralogical composition and its reservoir characteristics, respectively. Based on field observations and thin section analysis, four depositional facies and six lithofacies have been established. The sedimentary structures, depositional facies, and lithofacies indicate that Datta Formation was deposited in a deltaic environment. Compactions, cementation, fracturing and dissolution can greatly affect the quality of reservoir rock. Based on thin section and SEM analysis, large numbers of primary pores, fracture and secondary pores were observed and connectivity between the pores is good, and at some places, these pores

关键词： Reservoir characteristics Jurassic Datta Formation Porosity.permeability Sandstone

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Difficulty-aware prior-guided hierarchical network for adaptive segmentation of breast tumors

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Science China(Information Sciences) 2023年第2期66卷 127-141页

作者： Sumaira HUSSAIN Xiaoming XI Inam ullah Syeda Wajiha NAIM kashif SHAHEED Cuihuan TIAN Yilong YIN School of Software Engineering Shandong University Department of Computer Science Sindh Madressatul Islam University School of Computer Science and Technology Shandong Jianzhu University School of Computer Science and Engineering South China University of Technology School of Medicine Shandong University Health Management Center Qilu Hospital of Shandong University

Breast tumor segmentation is vital to tumor detection at the early stages. Deep learning methods are typically used in automatic tumor segmentation tasks. However, in existing methods, the difference between pixels is disregarded, and the union network architecture is used to segment all pixels; these methods involve a tradeoff between accuracy and efficiency. A novel, difficulty-aware, prior-guided hierarchical network for the adaptive segmentation of breast tumors is presented herein. A difficulty prior learning module is proposed to learn the pixel’s difficulty prior to guild adaptive segmentation in the proposed network. To achieve a more accurate segmentation of hard pixels, a hard pixel processing unit is presented to learn more discriminative features for hard pixels. Experiments are conducted based on three datasets. The experimental results show that the proposed methods outperform traditional deep learning methods and achieve a balance between accuracy and efficiency.

关键词： breast tumor ultrasound image segmentation deep neural network difficulty-awareness

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Deep Learning and Machine Learning-Based Model for Conversational Sentiment Classification

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Computers, Materials & Continua 2022年第8期72卷 2323-2339页

作者： Sami ullah Muhammad Ramzan Talib Toqir A.Rana Muhammad kashif Hanif Muhammad Awais Department of Computer Science Government College University Faisalabad38000Pakistan Department of Computer Science and IT The University of Lahore54590Pakistan School of Computer Sciences Universiti Sains Malaysia(USM)11800PenangMalaysia Department of Software Engineering Government College University Faisalabad38000Pakistan

In the current era of the internet,people use online media for conversation,discussion,chatting,and other similar *** of such material where more than one person is involved has a spate challenge as compared to other text analysis *** are several approaches to identify users’emotions fromthe conversational text for the English language,however regional or low resource languages have been *** Urdu language is one of them and despite being used by millions of users across the globe,with the best of our knowledge there exists no work on dialogue analysis in the Urdu ***,in this paper,we have proposed a model which utilizes deep learning and machine learning approaches for the classification of users’emotions from the *** accomplish this task,we have first created a dataset for the Urdu language with the help of existing English language datasets for dialogue *** that,we have preprocessed the data and selected dialogues with common *** the dataset is prepared,we have used different deep learning and machine learning techniques for the classification of *** have tuned the algorithms according to the Urdu language *** experimental evaluation has shown encouraging results with 67%accuracy for the Urdu dialogue datasets,more than 10,000 dialogues are classified into five emotions i.e.,joy,fear,anger,sadness,and *** believe that this is the first effort for emotion detection from the conversational text in the Urdu language domain.

关键词： Dialogue analysis conversational opinion mining sentiment analysis sentiment analysis in Urdu language deep learning machine learning

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Graphene photodetectors integrated with silicon and perovskite quantum dots

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Microsystems & Nanoengineering 2024年第3期10卷 21-33页

作者： kashif Abbas Peirui Ji Naveed ullah Shareen Shafique Ze Zhang Muhammad Faizan Ameer Shenghan Qin Shuming Yang State Key Laboratory for Manufacturing Systems Engineering Xi’an Jiaotong UniversityXi’an 710049China Department of Microelectronic Science and Engineering Laboratory of Clean Energy Storage and ConversionSchool of Physical Science and TechnologyNingbo Collaborative Innovation Center of Nonlinear Calamity System of Ocean and AtmosphereNingbo UniversityNingbo 315211China

Photodetectors(PDs)play a crucial role in imaging,sensing,communication systems,***(Gr),a leading two-dimensional material,has demonstrated significant potential for photodetection in recent ***,its relatively weak interaction with light poses challenges for practical *** integration of silicon(Si)and perovskite quantum dots(PQDs)has opened new avenues for Gr in the realm of next-generation *** review provides a comprehensive investigation of Gr/Si Schottky junction PDs and Gr/PQD hybrid PDs as well as their *** operating principles,design,fabrication,optimization strategies,and typical applications of these devices are studied and *** these discussions,we aim to illuminate the current challenges and offer insights into future directions in this rapidly evolving field.

关键词： quantum discussions summarized

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Sustainable food industrial waste management through single cell protein production and characterization of protein enriched bread

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Food Bioscience 2022年第2期46卷 639-646页

作者： Muhammad kashif Iqbal Khan Muhammad Asif Zafar ullah Razzaq Akmal Nazir Abid Aslam Maan Department of Food Engineering University of AgricultureFaisalabadPakistan National Institute of Food Science and Technology University of AgricultureFaisalabadPakistan Department of Food Science College of Agriculture and Veterinary MedicineUnited Arab Emirates UniversityAl AinUnited Arab Emirates

Production of single cell protein(SCP)from food waste is one of the promising approaches for excellent waste *** the present study,SCP was produced through submerged fermentation using selected food wastes(banana peel,citrus peel,carrot pomace and potato peel).During process optimization,combinations of various temperature and nitrogen sources were studied for optimum SCP yield(g/100g).The results indicated that maximum SCP yield was obtained at 30℃ for 7 days on potato peels,whereas citrus and banana peels exhibited the lowest SCP yield at the same process *** SCP compositional analysis indicated that the amount of non-essential amino acids was significantly higher than wheat ***,SCP enriched bread was prepared by adding SCP at different concentrations(0,4,8,and 12%).The organoleptic properties indicated that SCP addition up to 4%was acceptable to prepare protein enriched ***,SCP may be effectively used for food waste management and food security.

关键词： Fruit waste Food security Single cell protein Bread Protein deficiency Malnourishment

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Evolutionary Safe Padé Approximation Scheme for Dynamical Study of Nonlinear Cervical Human Papilloma Virus Infection Model

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Computer Modeling in Engineering & Sciences 2024年第9期140卷 2275-2296页

作者： Javaid Ali Armando Ciancio kashif Ali Khan Nauman Raza Haci Mehmet Baskonus Muhammad Luqman Zafar-ullah Khan Department of Mathematics Govt.Graduate College TownshipLahore54770Pakistan Universitàdegli Studi di Messina Dipartimento di Scienze BiomedicheOdontoiatriche e delle Immagini Morfologiche e FunzionaliMessina98122Italy Department of Mathematics University of Engineering and TechnologyLahore54890Pakistan Department of Mathematics University of the PunjabLahore54590Pakistan Mathematics Research Center Near East University TRNCMersin 10Nicosia99138Turkey Department of Mathematics and Science Education Faculty of EducationHarran UniversitySanliurfa63190Turkey Department of Dermatology Rashid Latif Medical CollegeLahore54600Pakistan

This study proposes a structure-preserving evolutionary framework to find a semi-analytical approximate solution for a nonlinear cervical cancer epidemic(CCE)*** underlying CCE model lacks a closed-form exact *** solutions obtained through traditional finite difference schemes do not ensure the preservation of the model’s necessary properties,such as positivity,boundedness,and ***,the development of structure-preserving semi-analytical approaches is always *** research introduces an intelligently supervised computational paradigm to solve the underlying CCE model’s physical properties by formulating an equivalent unconstrained optimization ***-free safe Padérational functions approximate the mathematical shape of state variables,while the model’s physical requirements are treated as problem *** primary model of the governing differential equations is imposed to minimize the error between approximate *** evolutionary algorithm,the Genetic Algorithm with Multi-Parent Crossover(GA-MPC),executes the optimization *** resulting method is the Evolutionary Safe PadéApproximation(ESPA)*** proof of unconditional convergence of the ESPA scheme on the CCE model is supported by numerical *** performance of the ESPA scheme on the CCE model is thoroughly investigated by considering various orders of non-singular Padéapproximants.

关键词： Nonlinear cervical cancer epidemic non-singular Padéapproximants approximate solutions computational biology

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Parameters effect on heterogeneous photocatalysed degradation of phenolin aqueous dispersion of TiO_2

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Journal of Environmental Sciences 2009年第4期21卷 527-533页

作者： kashif Naeem Department of Urban and Civil Engineering Harbin Institute of Technology Shenzhen Graduate School

Photocatalytic degradation of phenol selected as model compound of organic pollutant had been investigated in aqueous titanium dioxide （TiO2） dispersion under UV irradiation. The effects of various parameters such as pH, catalyst concentration, phenol concentration, anions, metal ions, electron acceptors, and surfactants on the photocatalytic degradation of phenol were investigated. The degradation kinetics was determined by the change in phenol concentration employing UV-Vis spectrometry as a function of irradiation time. The degradation kinetics of phenol follows pseudo first-order kinetics. The results showed a significant dependence of the photocatalytic degradation of phenol on the functional parameters. The probable promising roles of the additives on the degradation process were discussed.

关键词： irradiation phenol photocatalytic degradation titanium dioxide UV light

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