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Weber Law Based Approach for Multi-Class Image Forgery Detection

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Computers, Materials & Continua 2024年第1期78卷 145-166页

作者： Arslan Akram javed Rashid Arfan Jaffar Fahima Hajjej Waseem Iqbal Nadeem Sarwar Department of Computer Science Superior UniversityLahore54000Pakistan Information Technology Services University of OkaraOkara56300Pakistan Departmet of Computer Science MLC LabOkara56300Pakistan Department of CS&SE International Islamic UniversityIslamabad44000Pakistan Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Software Engineering Superior UniversityLahore54000Pakistan Department of Computer Science Bahria UniversityLahore CampusLahore54600Pakistan

Today’s forensic science introduces a new research area for digital image analysis formultimedia ***,Image authentication issues have been raised due to the wide use of image manipulation software to obtain an illegitimate benefit or createmisleading publicity by using tempered *** forgery detectionmethods can classify only one of the most widely used Copy-Move and splicing ***,an image can contain one or more types of *** study has proposed a hybridmethod for classifying Copy-Move and splicing images using texture information of images in the spatial ***,images are divided into equal blocks to get scale-invariant *** law has been used for getting texture features,and finally,XGBOOST is used to classify both Copy-Move and splicing *** proposed method classified three types of forgeries,i.e.,splicing,Copy-Move,and ***(CASIA 2.0,MICCF200)and RCMFD datasets are used for training and *** average,the proposed method achieved 97.3% accuracy on benchmarked datasets and 98.3% on RCMFD datasets by applying 10-fold cross-validation,which is far better than existing methods.

关键词： Copy-Move and splicing non-overlapping block division texture features weber law spatial domain xgboost

Enhanced Steganalysis for Color Images Using Curvelet Features and Support Vector Machine

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Computers, Materials & Continua 2024年第1期78卷 1311-1328页

作者： Arslan Akram Imran Khan javed Rashid Mubbashar Saddique Muhammad Idrees yazeed yasin Ghadi Abdulmohsen Algarni Faculty of Computer Science and Information Technology Department of Computer ScienceSuperior UniversityLahore54000Pakistan Machine Learning Code(MLC)Lab Meharban HouseHouse Number 209Zafar ColonyOkara56300Pakistan Information Technology Services University of OkaraOkara56310Pakistan Department of Computer Science&Engineering University of Engineering&Technology LahoreNarowal CampusNarowal51601Pakistan Department of Computer Science and Software Engineering Al Ain UniversityAl Ain11671Abu Dhabi Department of Computer Science King Khalid UniversityAbha61421Saudi Arabia

Algorithms for steganography are methods of hiding data transfers in media *** machine learning architectures have been presented recently to improve stego image identification performance by using spatial information,and these methods have made it feasible to handle a wide range of problems associated with image *** with little information or low payload are used by information embedding methods,but the goal of all contemporary research is to employ high-payload images for *** address the need for both low-and high-payload images,this work provides a machine-learning approach to steganography image classification that uses Curvelet transformation to efficiently extract characteristics from both type of *** Vector Machine(SVM),a commonplace classification technique,has been employed to determine whether the image is a stego or *** Wavelet Obtained Weights(WOW),Spatial Universal Wavelet Relative Distortion(S-UNIWARD),Highly Undetectable Steganography(HUGO),and Minimizing the Power of Optimal Detector(MiPOD)steganography techniques are used in a variety of experimental scenarios to evaluate the performance of the *** WOW at several payloads,the proposed approach proves its classification accuracy of 98.60%.It exhibits its superiority over SOTA methods.

关键词： Curvelets fast fourier transformation support vector machine high pass filters steganography

Application of Synthetic Iron Oxyhydroxide with Influencing Factors for Removal of As(Ⅴ) and As(Ⅲ) from Groundwater

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Journal of Earth Science 2024年第3期35卷 998-1009页

作者： Shakeel Ahmed Talpur Muhammad yousuf Jat Baloch Chunli Su javed Iqbal Aziz Ahmed Hafeez Ahmed Talpur School of Environmental Studies China University of GeosciencesWuhan 430078China DiSPUTer Department of PsychologicalHealth and Territory SciencesUniversity“G.d′Annunzio”Chieti-Pescara66100 ChietiItaly College of New Energy and Environment Jilin UniversityChangchun 130021China School of Plant Environment and Soil SciencesLouisiana State University Agricultural CentreBaton Rouge LA 70803USA Department od Engineering and Geology University“G.d′Annunzio”Chieti-Pescara66100 ChietiItaly

Synthesized iron oxyhydroxide was applied for the adsorptive removal of As(V)and As(III)from the aquas ***,this investigation highlighted the synergistic effect of calcium carbonate in conjunction with iron oxyhydroxide,resulting in enhanced removal *** experiment was conducted under various conditions:concentration,dosage,pH,agitation,and *** characterizations such as Brunauer Emmett Teller,X-ray diffraction,scanning electron microscopy,and Fourier transform infrared spectroscopy were implied to understand adsorption *** Langmuir model revealed optimal concentrations for As(V)=500μg/L at pH-5 and As(III)=200μg/L at pH-7,resulting in 95%and 93%adsorption efficiencies,*** adsorption capacities“qm”were found to be 1266.943μg/g for As(V)and 1080.241μg/g for As(III).Freundlich model demonstrated favorable adsorption by indicating“n>1”such as As(V)=2.542 and As(III)=2.707;similarly,the speciation factor“RLy presented a pseudo-second-order model as best fitted,indicating throughout chemisorption processes for removing As(V)and As(III).Furthermore,incorporating calcium carbonate presented a significant leap in the removal efficiency,indicating As(V)from 95%to 98%and As(III)from 93%to 96%,*** findings offer profound motivation for developing effective and sustainable solutions to tackle arsenic contamination,underscoring the exceptional promise of iron oxyhydroxide in conjunction with calcium carbonate to achieve maximum removal efficiency.

关键词： adsorption arsenic As(V) As(III) iron oxyhydroxide isotherms kinetics groundwater.

MAX-DOAS and in-situ measurements of aerosols and trace gases over Dongying,China:Insight into ozone formation sensitivity based on secondary HCHO

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Journal of Environmental Sciences 2024年第1期135卷 656-668页

作者： Xiaojun Zheng Zeeshan javed Cheng Liu Aimon Tanvir Osama Sandhu Haoran Liu Xiangguang Ji Chengzhi Xing Hua Lin Daolin Du Institute of Environment and Ecology School of the Environment and Safety EngineeringJiangsu UniversityZhenjiang 212013China Department of Precision Machinery and Precision Instrumentation University of Science and Technology of ChinaHefei 230026China Key Laboratory of Environmental Optics&Technology Anhui Institute of Optics and Fine MechanicsHefei Institutes of Physical ScienceChinese Academy of SciencesHefei 230031China Center for Excellence in Regional Atmospheric Environment Institute of Urban EnvironmentChinese Academy of SciencesXiamen 361021China Key Laboratory of Precision Scientific Instrumentation of Anhui Higher Education Institutes University of Science and Technology of ChinaHefei 230026China Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention(LAP3) Department of Environmental Science and EngineeringFudan UniversityShanghai 200433China National Agromet Center Pakistan Meteorological DepartmentIslamabad 44000Pakistan Institute of Physical Science and Information Technology Anhui UniversityHefei 230601China Information Materials and Intelligent Sensing Laboratory of Anhui Province Anhui UniversityHefei 230601China School of Environmental Science and Optoelectronic Technology University of Science and Technology of ChinaHefei 230026China

This study presents a comprehensive overview of the atmospheric pollutants including Sulfur dioxide(SO_(2)),Nitrogen dioxide(NO_(2)),Formaldehyde(HCHO),Particulate Matter PM;PM_(10):diameter≤10μm,and PM_(2.5):diameter≤2.5μm,and Ozone(O_(3)),over Dongying(Shandong Province)from March-April 2018 and September-October 2019 by employing ground-based Multiple Axis Differential Optical Absorption Spectroscopy(MAX-DOAS)observations along with the in-situ measurements attained by the national air quality monitoring *** concentrations of SO_(2)and NO_(2)were under the acceptable level,while both PM_(2.5),and PM_(10)were higher than the safe levels as prescribed by national and international air quality *** results depict that 21%of the total observation days were found to be complex polluted days(PM_(2.5)>35μg/m^(3) and O_(3)>160μg/m^(3)).The secondary HCHO was used for accurate analysis of O_(3)sensitivity.A difference of 11.40%and 10%during March-April 2018 and September-October 2019 respectively in O_(3)sensitivity was found between HCHO_(total)/NO_(2)and HCHO_(sec)/NO_(2).The results indicate that primary HCHO have significant contribution in HCHO.O_(3)formation predominantly remained to be in VOC-limited and transitional regime during March-April 2018 and September-October 2019 in *** results imply that concurrent control of both NO_(x) and VOCs would benefit in ozone ***,the criteria pollutants(PM,SO_(2),and NO_(2))depicted strong correlations with each other except for O_(3)for which weak correlation coefficient was obtained with all the *** study will prove to be baseline for designing of air pollution control strategies.

关键词： MAX-DOAS Trace gases Ozone sensitivity Secondary HCHO Complex Pollution

CapsNet-FR: Capsule Networks for Improved Recognition of Facial Features

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Computers, Materials & Continua 2024年第5期79卷 2169-2186页

作者： Mahmood Ul Haq Muhammad Athar javed Sethi Najib Ben Aoun Ala Saleh Alluhaidan Sadique Ahmad Zahid farid Department of Computer System Engineering University of Engineering&TechnologyPeshawar25000Pakistan College of Computer Science and Information Technology Al-Baha UniversityAlaqiq65779-7738Saudi Arabia REGIM-Lab:Research Groups in Intelligent Machines National School of Engineers of Sfax(ENIS)University of SfaxSfax3038Tunisia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh84428Saudi Arabia EIAS:Data Science and Blockchain Laboratory College of Computer and Information SciencesPrince Sultan UniversityRiyadh11586Saudi Arabia Department of Computer Sciences Bahria University Karachi CampusKarachi541004Pakistan Department of Electrical Engineering Abasyn UniversityPeshawar25000Pakistan

Face recognition (FR) technology has numerous applications in artificial intelligence including biometrics, security,authentication, law enforcement, and surveillance. Deep learning (DL) models, notably convolutional neuralnetworks (CNNs), have shown promising results in the field of FR. However CNNs are easily fooled since theydo not encode position and orientation correlations between features. Hinton et al. envisioned Capsule Networksas a more robust design capable of retaining pose information and spatial correlations to recognize objects morelike the brain does. Lower-level capsules hold 8-dimensional vectors of attributes like position, hue, texture, andso on, which are routed to higher-level capsules via a new routing by agreement algorithm. This provides capsulenetworks with viewpoint invariance, which has previously evaded CNNs. This research presents a FR model basedon capsule networks that was tested using the LFW dataset, COMSATS face dataset, and own acquired photos usingcameras measuring 128 × 128 pixels, 40 × 40 pixels, and 30 × 30 pixels. The trained model outperforms state-ofthe-art algorithms, achieving 95.82% test accuracy and performing well on unseen faces that have been blurred orrotated. Additionally, the suggested model outperformed the recently released approaches on the COMSATS facedataset, achieving a high accuracy of 92.47%. Based on the results of this research as well as previous results, capsulenetworks perform better than deeper CNNs on unobserved altered data because of their special equivarianceproperties.

关键词： CapsNet face recognition artificial intelligence

Variable range hopping transport and dielectric relaxation mechanism in GdCrO_(3) rare-earth orthochromite perovskite

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Journal of Rare Earths 2024年第7期42卷 1304-1316,I0004页

作者： Muhammad javed Ayaz Arif Khan Jamal Kazmi Naeem Akbar Said Nasir Khisro Amanullah Dar Aleem Dad Khan Tareen Mohd Ambri Mohamed Department of Physics The University of Azad Jammu and KashmirMuzaffarabad13100Pakistan Department of Physics University of Kotli Azad Jammu and KashmirKotli11100Pakistan Institute of Microengineering and Nanoelectronics Universiti Kebangsaan Malaysia43600BangiSelangorMalaysia Department of Mathematics University of Kotli Azad Jammu and KashmirKotli11100Pakistan

The polycrystalline GdCrO_(3)(GCO)perovskite orthochromite was synthesized by the sol-gel auto-combustion *** Rietveld refined X-ray diffraction(XRD)profile of GCO confirms that the orthorhombic phase crystallizes in perovskite crystal structure with space group *** transmission electron microscopy and selected area electron diffraction divulge the polycrystalline nature of the perovskite *** field emission scanning electron microscopy(FESEM)images reveal the microstructural polyhedral growth of grains separated by sharp grain *** chemical states of the ions present in the compound were investigated by X-ray photoelectron spectroscopy(XPS)studies,and the electrical pathways were *** impedance studies were carried out in the experimental frequency and temperature ranges of 40 Hz-4 MHz and 178-408 K,*** equivalent circuit model(RGQG)(RGBQGB)resolves the impedance response into two contributions originating from the intra-grain and inter-granular micro-constituents of the *** electrical conduction mechanism is based on the Mott variable range hopping *** complex electric modulus studies demonstrate the short-and long-range mobility of the charge carriers and rule out the presence of electrode effects on the dielectric relaxation mechanism of the *** decreasing pattern of dielectric permittivity with frequency is explained by the Maxwell-Wagner type of *** frequency dependence of the loss factor exhibits the presence of thermally activated relaxation time distribution in the material.

关键词： Auto-combustion Perovskite Electro-ceramic Dielectric Electrical transport Impedance

Identification of Software Bugs by Analyzing Natural Language-Based Requirements Using Optimized Deep Learning Features

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Computers, Materials & Continua 2024年第3期78卷 4379-4397页

作者： Qazi Mazhar ul Haq Fahim Arif Khursheed Aurangzeb Noor ul Ain javed Ali Khan Saddaf Rubab Muhammad Shahid Anwar Department of Computer Science and Engineering and International Bachelor’s Program in Informatics Yuan Ze UniversityZhongliTaoyuan320315Taiwan Department of Computer Science National University of PakistanRawalpindiPunjab46000Pakistan Department of Computer Software Engineering MCSNational University of Sciences and TechnologyIslamabad44000Pakistan Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Saudi Arabia Department of Computer Science School of PhysicsEngineering and Computer ScienceUniversity of HertfordshireHatfieldAL109ABUK Department of Computer Engineering College of Computing and InformaticsUniversity of SharjahSharjah27272United Arab Emirates Department of AI and Software Gachon UniversitySeongnam-SI13120South Korea

Software project outcomes heavily depend on natural language requirements,often causing diverse interpretations and issues like ambiguities and incomplete or faulty *** are exploring machine learning to predict software bugs,but a more precise and general approach is *** bug prediction is crucial for software evolution and user training,prompting an investigation into deep and ensemble learning ***,these studies are not generalized and efficient when extended to other ***,this paper proposed a hybrid approach combining multiple techniques to explore their effectiveness on bug identification *** methods involved feature selection,which is used to reduce the dimensionality and redundancy of features and select only the relevant ones;transfer learning is used to train and test the model on different datasets to analyze how much of the learning is passed to other datasets,and ensemble method is utilized to explore the increase in performance upon combining multiple classifiers in a *** National Aeronautics and Space Administration(NASA)and four Promise datasets are used in the study,showing an increase in the model’s performance by providing better Area Under the Receiver Operating Characteristic Curve(AUC-ROC)values when different classifiers were *** reveals that using an amalgam of techniques such as those used in this study,feature selection,transfer learning,and ensemble methods prove helpful in optimizing the software bug prediction models and providing high-performing,useful end mode.

关键词： Natural language processing software bug prediction transfer learning ensemble learning feature selection

Modelling of debris-flow susceptibility and propagation: a case study from Northwest Himalaya

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Journal of Mountain Science 2024年第1期21卷 200-217页

作者： Hamza DAUD javed Iqbal TANOLI Sardar Muhammad ASIF Muhammad QASIM Muhammad ALI Junaid KHAN Zahid Imran BHATTI Ishtiaq Ahmad Khan JADOON Badong National Observation and Research Station of Geohazards China University of GeosciencesWuhan 430074China Department of Earth Sciences COMSATS University IslamabadAbbottabad Campus 22010Pakistan Department of Earth Sciences Sultan Qaboos UniversityAl-KhoudMascat 123Oman Faculty of Engineering China University of Geosciences(Wuhan)Wuhan 430074China Department of Earth Sciences Abbottabad University of Science and TechnologyHavelian 22500Pakistan

The geological and geographical position of the Northwest Himalayas makes it a vulnerable area for mass movements particularly landslides and debris flows. Mass movements have had a substantial impact on the study area which is extending along Karakorum Highway(KKH) from Besham to Chilas. Intense seismicity, deep gorges, steep terrain and extreme climatic events trigger multiple mountain hazards along the KKH, among which debris flow is recognized as the most destructive geohazard. This study aims to prepare a field-based debris flow inventory map at a regional scale along a 200 km stretch from Besham to Chilas. A total of 117 debris flows were identified in the field, and subsequently, a point-based debris-flow inventory and catchment delineation were performed through Arc GIS analysis. Regional scale debris flow susceptibility and propagation maps were prepared using Weighted Overlay Method(WOM) and Flow-R technique sequentially. Predisposing factors include slope, slope aspect, elevation, Topographic Roughness Index(TRI), Topographic Wetness Index(TWI), stream buffer, distance to faults, lithology rainfall, curvature, and collapsed material layer. The dataset was randomly divided into training data(75%) and validation data(25%). Results were validated through the Receiver Operator Characteristics(ROC) curve. Results show that Area Under the Curve(AUC) using WOM model is 79.2%. Flow-R propagation of debris flow shows that the 13.15%, 22.94%, and 63.91% areas are very high, high, and low susceptible to debris flow respectively. The propagation predicated by Flow-R validates the naturally occurring debris flow propagation as observed in the field surveys. The output of this research will provide valuable input to the decision makers for the site selection, designing of the prevention system, and for the protection of current infrastructure.

关键词： North Pakistan Debris flow Flow-R Propagation Susceptibility mapping Debris-flow inventory Weighted Overlay Method

Three-Dimensional Sound Source Location Algorithm for Subsea Leakage Using Hydrophone

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China Ocean Engineering 2024年第2期38卷 326-337页

作者： LI Hao-jie CAI Bao-ping yUAN Xiao-bing KONG Xiang-di LIU yong-hong javed Akbar KHAN CHU Zheng-de yANG Chao TANG An-bang College of Mechanical and Electronic Engineering China University of PetroleumQingdao 266580China Shenzhen Urban Public Safety Technology Institute Shenzhen 518000China Institute of Hydrocarbon Recovery Universiti Teknologi PETRONASBandar Seri IskandarPerak Darul Ridzuan 32610Malaysia

Leakages from subsea oil and gas equipment cause substantial economic losses and damage to marine ecosystem,so it is essential to locate the source of the ***,due to the complexity and variability of the marine environment,the signals collected by hydrophone contain a variety of noises,which makes it challenging to extract useful signals for *** solve this problem,a hydrophone denoising algorithm is proposed based on variational modal decomposition(VMD)with grey wolf ***,the average envelope entropy is used as the fitness function of the grey wolf optimizer to find the optimal solution for the parameters K andα.Afterward,the VMD algorithm decomposes the original signal parameters to obtain the intrinsic mode functions(IMFs).Subsequently,the number of interrelationships between each IMF and the original signal was calculated,the threshold value was set,and the noise signal was removed to calculate the time difference using the valid signal obtained by ***,the arrival time difference is used to locate the origin of the *** localization accuracy of the method in finding leaks is investigated experimentally by constructing a simulated leak test rig,and the effectiveness and feasibility of the method are verified.

关键词： grey wolf optimizer variational modal decomposition mean envelope entropy correlation coefficient time difference of arrival