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A Comprehensive Systematic Review: Advancements in Skin Cancer Classification and Segmentation Using the ISIC Dataset

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Computer Modeling in Engineering & Sciences 2024年第9期140卷 2131-2164页

作者： Madiha Hameed Aneela Zameer muhammad asif zahoor.raja Department of Computer Sciences Pakistan Institute of Engineering and Applied SciencesNilore50700Islamabad Future Technology Research Center National Yunlin University of Science and TechnologyDouliou64002TaiwanChina Directorate of IT Services University of GujratGujrat50700Pakistan

The International Skin Imaging Collaboration(ISIC)datasets are pivotal resources for researchers in machine learning for medical image analysis,especially in skin cancer *** datasets contain tens of thousands of dermoscopic photographs,each accompanied by gold-standard lesion diagnosis *** challenges associated with ISIC datasets have spurred significant advancements,with research papers reporting metrics surpassing those of human *** cancers are categorized into melanoma and non-melanoma types,with melanoma posing a greater threat due to its rapid potential for metastasis if left *** paper aims to address challenges in skin cancer detection via visual inspection and manual examination of skin lesion images,processes historically known for their *** notable advancements in machine learning and deep learning models,persistent challenges remain,largely due to the intricate nature of skin lesion *** review research on convolutional neural networks(CNNs)in skin cancer classification and segmentation,identifying issues like data duplication and augmentation *** explore the efficacy of Vision Transformers(ViTs)in overcoming these challenges within ISIC dataset *** leverage their capabilities to capture both global and local relationships within images,reducing data duplication and enhancing model ***,ViTs alleviate augmentation issues by effectively leveraging original *** a thorough examination of ViT-based methodologies,we illustrate their pivotal role in enhancing ISIC image classification and *** study offers valuable insights for researchers and practitioners looking to utilize ViTs for improved analysis of dermatological ***,this paper emphasizes the crucial role of mathematical and computational modeling processes in advancing skin cancer detection methodologies,highlighting their significance in improving algorithmic

关键词： Medical image skin cancer classification skin cancer segmentation international skin imaging collaboration convolutional neural network deep learning

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Phonon Thermal Transport at Interfaces of a Graphene/Vertically Aligned Carbon Nanotubes/Hexagonal Boron Nitride Sandwiched Heterostructure

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Chinese Physics Letters 2024年第1期41卷 57-62页

作者：李檬璘 muhammad asif Shakoori 王瑞鹏李海鹏 School of Materials Science and Physics China University of Mining and TechnologyXuzhou 221116China

Molecular dynamics simulation is used to calculate the interfacial thermal resistance of a graphene/carbon nanotubes/hexagonal boron nitride(Gr/CNTs/hBN)sandwiched heterostructure,in which vertically aligned carbon nanotube(VACNT)arrays are covalently bonded to graphene and hexagonal boron nitride *** find that the interfacial thermal resistance(ITR)of the Gr/VACNT/hBN sandwiched heterostructure is one to two orders of magnitude smaller than the ITR of a Gr/hBN van der Waals heterostructure with the same plane *** is observed that covalent bonding effectively enhances the phonon coupling between Gr and hBN layers,resulting in an increase in the overlap factor of phonon density of states between Gr and hBN,thus reducing the ITR of Gr and *** addition,the chirality,size(diameter and length),and packing density of sandwich-layer VACNTs have an important influence on the ITR of the *** the same CNT diameter and length,the ITR of the sandwiched heterostructure with armchair-shaped VACNTs is higher than that of the sandwiched heterostructure with zigzag-shaped VACNTs due to the different chemical bonding of chiral CNTs with Gr and *** the armchair-shaped CNT diameter increases or the length decreases,the ITR of the sandwiched heterostructure tends to ***,the increase in the VACNT packing density also leads to a continuous decrease in the ITR of the sandwiched heterostructure,attributed to the extremely high intrinsic thermal conductivity of CNTs and the increase of out-of-plane heat transfer *** work may be helpful for understanding the mechanism for ITR in multilayer vertical heterostructures,and provides theoretical guidance for a new strategy to regulate the interlayer thermal resistance of heterostructures by optimizing the design of sandwich layer thermal interface materials.

关键词： sandwich shaped packing

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Progress in electrocatalytic nitrate reduction for green energy:Catalyst engineering,mechanisms,and techno-economic feasibility

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Journal of Energy Chemistry 2024年第8期95卷 380-406,I0009页

作者： Hafiz muhammad Adeel Sharif Hafiz muhammad Farooq Khan Sadeeq Ullah Yuwei Wang muhammad Ahmad Bo Yang Changping Li muhammad Bilal asif Research Center for Eco-Environmental Engineering Dongguan University of TechnologyDongguan 523808GuangdongChina College of Chemistry and Engineering Shenzhen UniversityShenzhen 518060GuangdongChina FMH College of Medicine and Dentistry LahorePakistan School of Environment and Civil Engineering Research Center for Eco-Environment EngineeringDongguan University of TechnologyDongguan 523106GuangdongChina Advanced Membranes and Porous Materials Center(AMPMC) Physical Sciences and Engineering(PSE)King Abdullah University of Science and Technology(KAUST)Thuwal 23955Saudi Arabia

Ammonia(NH_(3))is an irreplaceable chemical that has been widely demanded to keep the sustainable development of modern ***,its industrial production consumes a huge amount of energy and releases extraordinary greenhouse gases(GHGs),leading to various environmental *** the green production of ammonia is a great challenge,which has been extensively pursued in the last *** this review,the most promising strategy,electrochemical nitrate reduction reaction(e-NO_(3)RR),is comprehensively investigated to give a complete understanding of its development and mechanism and provide guidance for future ***,owing to the complex reactions and limited selectivity,a comprehensive understanding of the mechanisms is crucial to further development and ***,NO_(3)^(-)RR is a promising strategy for simultaneous water treatment and NH_(3)production.A detailed overview of the recent progress in NO_(3)^(-)RR for NH_(3)production with nontransition and transition metal based electrocatalysts is *** addition,critical advanced techniques,future challenges,and prospects are discussed to guide future research on transition metal-based catalysts for commercial NH_(3)synthesis by NO_(3)^(-)reduction.

关键词： Nitrate reduction Electrolysis Pollution to solution Transition metal catalysts Ammonia synthesis Green energy

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Smart prediction of liquefaction-induced lateral spreading

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Journal of Rock Mechanics and Geotechnical Engineering 2024年第6期16卷 2310-2325页

作者： muhammad Nouman Amjad raja Tarek Abdoun Waleed El-Sekelly New York University(NYU)Abu Dhabi Abu Dhabi129188United Arab Emirates University of Management and Technology Lahore54372Pakistan Department of Civil and Environmental Eng. Rensselaer Polytechnic Institute(RPI)1108th StreetJEC 4049TroyNY12180USA Department of Structural Engineering Mansoura UniversityMansoura35516Egypt

The prediction of liquefaction-induced lateral spreading/displacement(Dh)is a challenging task for civil/geotechnical *** this study,a new approach is proposed to predict Dh using gene expression programming(GEP).Based on statistical reasoning,individual models were developed for two topographies:free-face and gently sloping *** with a comparison with conventional approaches for predicting the Dh,four additional regression-based soft computing models,*** process regression(GPR),relevance vector machine(RVM),sequential minimal optimization regression(SMOR),and M5-tree,were developed and compared with the GEP *** results indicate that the GEP models predict Dh with less bias,as evidenced by the root mean square error(RMSE)and mean absolute error(MAE)for training(i.e.1.092 and 0.815;and 0.643 and 0.526)and for testing(i.e.0.89 and 0.705;and 0.773 and 0.573)in free-face and gently sloping ground topographies,*** overall performance for the free-face topology was ranked as follows:GEP>RVM>M5-tree>GPR>SMOR,with a total score of 40,32,24,15,and 10,*** the gently sloping condition,the performance was ranked as follows:GEP>RVM>GPR>M5-tree>SMOR with a total score of 40,32,21,19,and 8,***,the results of the sensitivity analysis showed that for both free-face and gently sloping ground,the liquefiable layer thickness(T_(15))was the major parameter with percentage deterioration(%D)value of 99.15 and 90.72,respectively.

关键词： Lateral spreading Intelligent modeling Gene expression programming(GEP) Closed-form solution Feature importance

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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

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Design of an Efficient and Provable Secure Key Exchange Protocol for HTTP Cookies

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Computers, Materials & Continua 2024年第7期80卷 263-280页

作者： Waseem Akram Khalid Mahmood Hafiz Burhan ul Haq muhammad asif Shehzad Ashraf Chaudhry Taeshik Shon Graduate School of Engineering Science and Technology National Yunlin University of Science and TechnologyYunlin64002TaiwanChina Future Technology Research Center National Yunlin University of Science and TechnologyYunlin64002TaiwanChina Department of Computer Science Lahore Garrison UniversityLahore54920Pakistan Department of Computer Science and Information Technology College of EngineeringAbu Dhabi UniversityAbu Dhabi69911United Arab Emirates Department of Software Engineering Faculty of Engineering and ArchitectureNisantasi UniversityIstanbul34398Turkey Department of Cybersecurity Ajou UniversitySuwon16499Republic of Korea

Cookies are considered a fundamental means of web application services for authenticating various Hypertext Transfer Protocol(HTTP)requests andmaintains the states of clients’information over the *** cookies are exploited to carry client patterns observed by a *** client patterns facilitate the particular client’s future visit to the corresponding ***,security and privacy are the primary concerns owing to the value of information over public channels and the storage of client information on the *** protocols have been introduced that maintain HTTP cookies,but many of those fail to achieve the required security,or require a lot of resource *** this article,we have introduced a lightweight Elliptic Curve Cryptographic(ECC)based protocol for authenticating client and server transactions to maintain the privacy and security of HTTP *** proposed protocol uses a secret key embedded within a *** proposed protocol ismore efficient and lightweight than related protocols because of its reduced computation,storage,and communication ***,the analysis presented in this paper confirms that proposed protocol resists various known attacks.

关键词： Cookies authentication protocol impersonation attack ECC

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Unsupervised neural networks for solving Troesch＇s problem

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Chinese Physics B 2014年第1期23卷 546-556页

作者： muhammad asif zahoor.raja Department of Electrical Engineering COMSATS Institute of Information Technology Attock Campus Attock Pakistan

In this study, stochastic computational intelligence techniques are presented for the solution of Troesch's boundary value problem. The proposed stochastic solvers use the competency of a feed-forward artificial neural network for mathematical modeling of the problem in an unsupervised manner, whereas the learning of unknown parameters is made with local and global optimization methods as well as their combinations. Genetic algorithm (GA) and pattern search (PS) techniques are used as the global search methods and the interior point method (IPM) is used for an efficient local search. The combination of techniques like GA hybridized with IPM (GA-IPM) and PS hybridized with IPM (PS-IPM) are also applied to solve different forms of the equation. A comparison of the proposed results obtained from GA, PS, IPM, PS-IPM and GA-IPM has been made with the standard solutions including well known analytic techniques of the Adomian decomposition method, the variational iterational method and the homotopy perturbation method. The reliability and effectiveness of the proposed schemes, in term of accuracy and convergence, are evaluated from the results of statistical analysis based on sufficiently large independent runs.

关键词： Troesch’s problem artificial neural network genetic algorithm hybrid methods

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Magnetic properties of gadolinium and/or dysprosium substituted Sm-Co nanocomposite ribbons

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Journal of Rare Earths 2024年第6期42卷 1093-1100,I0004页

作者： Akila raja Shampa Aich Department of Metallurgical A Materials EngineeringIndian Institute of Technology(IIT) Kharagpur721302India

The present study reported the influence of heavy rare-earth elements(Gd and/or Dy)on Sm-Co-based melt-spun *** and magnetic properties of Sm-Co-based(Sm_(1-x)RE_(x)Co_(5))ternary and quaternary systems were *** X-ray diffraction,Auger spectroscopy,scanning electron microscopy(SEM)and transmission electron microscopy(TEM)analyses reveal the presence of the 1:5H and 2:17R phases in the as-spun ribbons.A high-temperature magnetic measurement reports a Curie temperature(Tc)at~825 and~869 K in Sm0.6Gd0.4Co5(ribbon A)and Sm_(0.6)Gd_(0.3)Dy_(0.1)Co_(5)(ribbon B),respectively.A low-temperature magnetic measurement on Sm0.6Gd0.3Dy0.1Co5 ribbons exhibits a type-2 SR(spin reorientation)behaviour at~72 K,which arises due to the presence of the DyCo5 *** temperature magnetic measurements reveal that overall magnetic measurement(OMP)is about 24 and 29.9 for ribbons A and B,***,the comparative investigations profess that ribbon B shows better magnetic performance due to Dy addition with reduced grain *** observation indicates that the Gd and Dy substituted Sm-Co magnet can be a potential magnet for high-temperature applications.

关键词： Permanent magnets Melt-spinning Heavy rare-earth Curie temperature Rare earths

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Quintessence anisotropic stellar models in quadratic and Born-Infeld modified teleparallel Rastall gravity

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Chinese Physics B 2024年第3期33卷 179-189页

作者： Allah Ditta 夏铁成 Irfan Mahmood asif Mahmood Department of Mathematics Shanghai University and Newtouch Center for Mathematics of Shanghai UniversityShanghai 200444China Centre for High Energy Physics University of the PunjabLahorePakistan College of Engineering Chemical Engineering DepartmentKing Saud University RiyadhSaudi Arabia

This study aims to discuss anisotropic solutions that are spherically symmetric in the quintessence field,which describe compact stellar objects in the modified Rastall teleparallel theory of *** achieve this goal,the Krori and Barua arrangement for spherically symmetric components of the line element is *** explore the field equations by selecting appropriate off-diagonal tetrad ***-Infeld function of torsion f(T)=β√λT+1-1 and power law form h(T)=δTn are *** Born-Infeld gravity was the first modified teleparallel gravity to discuss *** use the linear equation of state pr=ξρto separate the quintessence *** obtaining the field equations,we investigate different physical parameters that demonstrate the stability and physical acceptability of the stellar *** use observational data,such as the mass and radius of the compact star candidates PSRJ 1416-2230,Cen X-3,&4U 1820-30,to ensure the physical plausibility of our findings.

关键词： anisotropic spheres quintessence field modified Rastall teleparallel gravity equation of state(EoS) f(T)gravity

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Heart-Net: AMulti-Modal Deep Learning Approach for Diagnosing Cardiovascular Diseases

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Computers, Materials & Continua 2024年第9期80卷 3967-3990页

作者： DeemaMohammed Alsekait Ahmed Younes Shdefat AymanNabil asif Nawaz muhammad Rizwan Rashid Rana Zohair Ahmed Hanaa Fathi Diaa Salama Abd Elminaam Department of Computer Science and Information Technology Applied CollegePrincess Nourah bint Abdulrahman UniversityRiyadh84428Saudi Arabia College of Engineering and Technology American University of the Middle EastEgaila15453Kuwait Faculty of Computers Science Misr International UniversityCairo11800Egypt University Institute of Information Technology—PMAS Arid Agriculture University Rawalpjndi46000Pakistan Department of Computer Science International Islamic UniversityIslamabad04436Pakistan Jadara Research Center Jadara UniversityIrbid21110Jordan Information System Department Faculty of Computers and Artificial IntelligenceBenha UniversityBanha13511Egypt MEU Research Unit Middle East UniversityAmman11831Jordan

Heart disease remains a leading cause of morbidity and mortality worldwide,highlighting the need for improved diagnostic *** diagnostics face limitations such as reliance on single-modality data and vulnerability to apparatus faults,which can reduce accuracy,especially with poor-quality ***,these methods often require significant time and expertise,making them less accessible in resource-limited *** technologies like artificial intelligence and machine learning offer promising solutions by integrating multi-modality data and enhancing diagnostic precision,ultimately improving patient outcomes and reducing healthcare *** study introduces Heart-Net,a multi-modal deep learning framework designed to enhance heart disease diagnosis by integrating data from Cardiac Magnetic Resonance Imaging(MRI)and Electrocardiogram(ECG).Heart-Net uses a 3D U-Net for MRI analysis and a Temporal Convolutional Graph Neural Network(TCGN)for ECG feature extraction,combining these through an attention mechanism to emphasize relevant *** is performed using Optimized *** approach improves early detection,reduces diagnostic errors,and supports personalized risk assessments and continuous health *** proposed approach results show that Heart-Net significantly outperforms traditional single-modality models,achieving accuracies of 92.56%forHeartnetDataset Ⅰ(HNET-DSⅠ),93.45%forHeartnetDataset Ⅱ(HNET-DSⅡ),and 91.89%for Heartnet Dataset Ⅲ(HNET-DSⅢ),mitigating the impact of apparatus faults and image quality *** findings underscore the potential of Heart-Net to revolutionize heart disease diagnostics and improve clinical outcomes.

关键词： Heart diseases magnetic resonance imaging electrocardiogram deep learning classification

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