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Unsupervised Color Segmentation with Reconstructed Spatial Weighted Gaussian Mixture Model and Random Color Histogram

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Computers, Materials & Continua 2024年第3期78卷 3323-3348页

作者： Umer Sadiq khan Zhen Liu Fang Xu Muhib Ullah khan Lerui Chen Touseef Ahmed khan Muhammad Kashif Khattak Yuquan Zhang School of Computer and Information Science Hubei Engineering UniversityXiaogan432000China Institute for AI Industrial Technology Research Hubei Engineering UniversityXiaogan432000China Key Lab of Mountain Hazards and Surface Processes Institute of Mountain Hazards and EnvironmentChinese Academy of SciencesChengdu610041China University of Chinese Academy of Sciences Beijing100049China College of Aviation Zhongyuan University of TechnologyZhengzhou451191China Research Center of Digital Mountain and Remote Sensing Application Institute of Mountain Hazards and EnvironmentChinese Academy of SciencesChengdu610041China School of Computer Science University of PoonchAzad Jammu Kashmir12350Pakistan School of Computer Science and Information Engineering Hubei UniversityWuhan430062China

Image classification and unsupervised image segmentation can be achieved using the Gaussian mixture *** the Gaussian mixture model enhances the flexibility of image segmentation,it does not reflect spatial information and is sensitive to the segmentation *** this study,we first present an efficient algorithm that incorporates spatial information into the Gaussian mixture model(GMM)without parameter *** proposed model highlights the residual region with considerable information and constructs color ***,we incorporate the content-based color saliency as spatial information in the Gaussian mixture *** segmentation is performed by clustering each pixel into an appropriate component according to the expectation maximization and maximum ***,the random color histogram assigns a unique color to each cluster and creates an attractive color by default for segmentation.A random color histogram serves as an effective tool for data visualization and is instrumental in the creation of generative art,facilitating both analytical and aesthetic *** experiments,we have used the Berkeley segmentation dataset BSDS-500 and Microsoft Research in Cambridge *** the study,the proposed model showcases notable advancements in unsupervised image segmentation,with probabilistic rand index(PRI)values reaching 0.80,BDE scores as low as 12.25 and 12.02,compactness variations at 0.59 and 0.7,and variation of information(VI)reduced to 2.0 and 1.49 for the BSDS-500 and MSRC datasets,respectively,outperforming current leading-edge methods and yielding more precise segmentations.

关键词： Unsupervised segmentation color saliency spatial weighted GMM random color histogram

A Systematic Literature Review of Machine Learning and Deep Learning Approaches for Spectral Image Classification in Agricultural Applications Using Aerial Photography

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Computers, Materials & Continua 2024年第3期78卷 2967-3000页

作者： Usman khan Muhammad Khalid khan Muhammad Ayub Latif Muhammad Naveed Muhammad Mansoor Alam Salman A.khan Mazliham Mohd Su’ud College of Computing and Information Sciences Karachi Institute of Economics and TechnologyKarachi75190Pakistan Faculty of Computing and Informatics(FCI) Multimedia UniversityCyberjaya63100Malaysia Faculty of Computing Riphah International UniversityIslamabad46000Pakistan Faculty of Engineering and Information Technology School of Computer ScienceUniversity of Technology SydneySydneyAustralia

Recently,there has been a notable surge of interest in scientific research regarding spectral *** potential of these images to revolutionize the digital photography industry,like aerial photography through Unmanned Aerial Vehicles(UAVs),has captured considerable *** encouraging aspect is their combination with machine learning and deep learning algorithms,which have demonstrated remarkable outcomes in image *** a result of this powerful amalgamation,the adoption of spectral images has experienced exponential growth across various domains,with agriculture being one of the prominent *** paper presents an extensive survey encompassing multispectral and hyperspectral images,focusing on their applications for classification challenges in diverse agricultural areas,including plants,grains,fruits,and *** meticulously examining primary studies,we delve into the specific agricultural domains where multispectral and hyperspectral images have found practical ***,our attention is directed towards utilizing machine learning techniques for effectively classifying hyperspectral images within the agricultural *** findings of our investigation reveal that deep learning and support vector machines have emerged as widely employed methods for hyperspectral image classification in ***,we also shed light on the various issues and limitations of working with spectral *** comprehensive analysis aims to provide valuable insights into the current state of spectral imaging in agriculture and its potential for future advancements.

关键词： Machine learning deep learning unmanned aerial vehicles multi-spectral images image recognition object detection hyperspectral images aerial photography

Depositional and Bio-Sequence Stratigraphic Framework of Late Cretaceous Kawagarh Formation,Kala-Chitta Range,Pakistan:Equivalent of Gurpi Formation(Iran)

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Journal of Earth Science 2024年第2期35卷 332-348页

作者： Muhammad Awais Bilal Wadood Muhammad Ishaq Muhammad Bilal Zeeshan Zafar Nasar khan Aminullah khan Department of Geology University of SwabiAnbar-SwabiKhyber PakhtunkhwaSwabi23561Pakistan Department of Earth Environmental and Resources SciencesUniversity of Naples FedericoⅡNaples80126Italy State Key Laboratory of Continental Dynamics Department of GeologyNorthwest UniversityXi’an710069China National Centre of Excellence in Geology University of PeshawarPeshawarKhyber Pakhtunkhwa25130Pakistan Department of Geological Engineering School of Earth Sciences and EngineeringXi’an Shiyou UniversityXi’an610500China Department of Petroleum Geology and Engineering School of Earth ResourcesChina University of GeosciencesWuhan430074China Department of Geology University of MalakandDir Lower18800ChakdaraPakistan Department of Earth and Environmental Sciences KU LeuvenLeuven3001Belgium

The present study is focused on evaluation of deep marine pelagic sediments of Late Cretaceous Kawagarh Formation of Kala-Chitta Range in the context of microfacies analysis,paleoenvironmental interpretation,planktonic foraminiferal biostratigraphy,sequence stratigraphy and diversification of species.A total of thirty three rock samples were collected from the measured *** microfacies are interpreted,namely planktonic foraminifera wackestone,planktonic foraminifera mudstone and sandy mudstone indicating low energy depositional environment i.e.,outer *** biostratigraphic studies show plentiful planktonic foraminifera species of Globotruncana,Heterohelix and ***,no association of benthic or siliceous organisms was *** the basis of available species assemblage,a single local planktonic foraminifera biozone i.e.,Globotruncana-Heterohelix-Globotruncanita Assemblage Biozone is *** biozone information is combined with published literature and Lower Santonian to Middle Maastrichtian age has been assigned to the Kawagarh *** trend of species occurrences evinces that species number decreases over time with pulsated rise in the Kawagarh *** Kawagarh Formation carbonates show an overall Transgressive Systems Tract(TST).The Kawagarh Formation of Pakistan evinces analogous characteristics to that of the Late Cretaceous Gurpi Formation of Iran based on the geologic age,outcrop lithology,microfacies,planktonic foraminiferal assemblages,depositional setting and sequence stratigraphy.

关键词： depositional fabric biostratigraphy sequence stratigraphy Late Cretaceous Kawagarh Formation Pakistan Gurpi Formation Iran

A Hybrid and Lightweight Device-to-Server Authentication Technique for the Internet of Things

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Computers, Materials & Continua 2024年第3期78卷 3805-3823页

作者： Shaha Al-Otaibi Rahim khan Hashim Ali Aftab Ahmed khan Amir Saeed Jehad Ali Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science Abdul Wali Khan University MardanMardan23200Pakistan Department of Computer Science and IT UET PeshawarJalozai Campus PeshawarPeshawar24240Pakistan Department of AI Convergence Network Ajou UniversitySuwon16499South Korea

The Internet of Things(IoT)is a smart networking infrastructure of physical devices,i.e.,things,that are embedded with sensors,actuators,software,and other technologies,to connect and share data with the respective server *** IoTs are cornerstones in different application domains,the device’s authenticity,i.e.,of server(s)and ordinary devices,is the most crucial issue and must be resolved on a priority ***,various field-proven methodologies were presented to streamline the verification process of the communicating devices;however,location-aware authentication has not been reported as per our knowledge,which is a crucial metric,especially in scenarios where devices are *** paper presents a lightweight and location-aware device-to-server authentication technique where the device’s membership with the nearest server is subjected to its location information along with other ***,Media Access Control(MAC)address and Advance Encryption Scheme(AES)along with a secret shared key,i.e.,λ_(i) of 128 bits,have been utilized by Trusted Authority(TA)to generate MaskIDs,which are used instead of the original ID,for every device,i.e.,server and member,and are shared in the offline ***,TA shares a list of authentic devices,i.e.,server S_(j) and members C_(i),with every device in the IoT for the onward verification process,which is required to be executed before the initialization of the actual communication ***,every device should be located such that it lies within the coverage area of a server,and this location information is used in the authentication process.A thorough analytical analysis was carried out to check the susceptibility of the proposed and existing authentication approaches against well-known intruder attacks,i.e.,man-in-the-middle,masquerading,device,and server impersonations,etc.,especially in the IoT ***,proposed authentication and existing state-of-the-art approaches have been s

关键词： Internet of things authenticity security location communication

The role of green industrial transformation in mitigating carbon emissions:Exploring the channels of technological innovation and environmental regulation

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Energy and Built Environment 2024年第3期5卷 464-479页

作者： Saima Mehmood Khalid Zaman Shiraz khan Zohaib Ali Haroon ur Rashid khan Department of Economics The University of HaripurHaripurKhyber Pakhtunkhwa 22620Pakistan Department of Management Sciences The University of HaripurHaripurKhyber Pakhtunkhwa 22620Pakistan Department of Energy and Process Engineering(EPT) Norwegian University of Science and TechnologyHøgskoleringen 1Trondheim 7034Norway Faculty of Business The University of Wollongong in DubaiDubai 20183United Arab Emirates

The industrial sector is vital to economic progress,yet industrial pollution poses environmental and economic *** purpose of the study was to investigate the influence of green industrial transformation in re-ducing Pakistan’s carbon intensity between 1975 and *** emissions are considered an endogenous construct,while foreign direct investment(FDI)inflows,technological innovation,green industrial transforma-tion,environmental legislation,and research and development(R&D)investment are possible *** association between variables is assessed using the robust least-squares *** industrial transforma-tion is connected with lower carbon emissions,yet technical innovation,R&D investment,and inbound FDI raise a country’s carbon *** findings support the pollution haven hypothesis in a *** causality esti-mates indicate that inward FDI contributes to environmental regulations;green industrial transformation directly relates to inbound FDI and R&D expenditures;and technological innovations correspond to inbound FDI,R&D ex-penditures,industrial ecofriendly progression,and environmental *** to the impulse response function,environmental policies are anticipated to have a differential effect on carbon emissions in 2023,2024,2028-2030,while they are likely to decrease in the years 2025-2027 and 2031 ***,inward FDI and technology advancements would almost certainly result in a rise in carbon emissions over *** industrial transitions are projected to result in a ten-year reduction in carbon *** variance decomposi-tion analysis indicates that eco-friendly industrial adaptations would likely have the largest variance error shock on carbon emissions(11.747%),followed by inbound FDI,technological advancements,and regulatory changes,with R&D spending having a minimal impact over ***’s economy should foster a green industrial revolution to avoid pollution and increase environm

关键词： Carbon intensity Industrial green transformation Environmental regulations Technological innovations Robust least squares regression

Magnesium-reinforced Electrospun Synthetic-polymer Nanofibers Designed for Promoting Tissue Growth

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Journal of Bionic Engineering 2024年第3期21卷 1412-1426页

作者： Muheeb Rafiq Anjum Hamid Rather Rumysa Saleem khan Taha Umair Wani Haseeb A.khan Abdullah S.Alhomida Faheem A.Sheikh Nanostructured and Biomimetic Lab Department of NanotechnologyUniversity of Kashmir HazratbalSrinagarJammu and Kashmir190006India Non-Clinical Evaluation Center Biomedical Research InstituteJeonbuk National University HospitalJeonjuJeollabuk-do54907South Korea College of Pharmacy and Research Institute of Pharmaceutical Sciences Gyeongsang National UniversityJinju52828South Korea Research Chair for Biomedical Applications of Nanomaterials Department of BiochemistryCollege of ScienceKing Saud UniversityRiyadh11451Saudi Arabia

The creation of 3D nanofibers offering desirable functions for bone regeneration is developed due to the latest improvisations to the electrospinning *** polymers are among the best choices for medical usage due to their lower costs,high tensile properties,and ease of spinnability compared to natural *** this communication,we report a series of interventions to polymers modified with Mg-based fillers for ideal tissue engineering *** literature survey indicated that these filler materials(e.g.,nano-sized particles)enhanced biocompatibility,antibacterial activity,tensile strength,and anti-corrosive *** review discusses electrospinning parameters,properties,and applications of the poly(ε-caprolactone),poly(lactic acid),poly(3-hydroxybutyric acid-co-3-hydroxy valeric acid),polyurethane,and poly(vinyl pyrrolidone)nanofibers when modified with Mg-based *** report encourages researchers to use synthetic polymers with Mg as fillers and validate them for tissue engineering applications.

关键词： Bone regeneration Magnesium Nanofibers Tissue engineering

AMachine Learning Approach to User Profiling for Data Annotation of Online Behavior

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Computers, Materials & Continua 2024年第2期78卷 2419-2440页

作者： Moona Kanwal Najeed Akhan Aftab A.khan Computer Science and Information Technology Department NED University of Engineering and TechnologyKarachiPakistan Computer Engineering Department Sir Syed University of Engineering and TechnologyKarachiPakistan College of Education Health and Human ServicesLongwood UniversityFarmvilleVAUSA

The user’s intent to seek online information has been an active area of research in user *** profiling considers user characteristics,behaviors,activities,and preferences to sketch user intentions,interests,and *** user characteristics can help capture implicit and explicit preferences and intentions for effective user-centric and customized content *** user’s complete online experience in seeking information is a blend of activities such as searching,verifying,and sharing it on social ***,a combination of multiple behaviors in profiling users has yet to be *** research takes a novel approach and explores user intent types based on multidimensional online behavior in information *** research explores information search,verification,and dissemination behavior and identifies diverse types of users based on their online engagement using machine *** research proposes a generic user profile template that explains the user characteristics based on the internet experience and uses it as ground truth for data *** feedback is based on online behavior and practices collected by using a survey *** participants include both males and females from different occupation sectors and different *** data collected is subject to feature engineering,and the significant features are presented to unsupervised machine learning methods to identify user intent classes or profiles and their *** techniques are evaluated,and the K-Mean clustering method successfully generates five user groups observing different user characteristics with an average silhouette of 0.36 and a distortion score of *** average is computed to identify user intent type *** user intent classes are then further generalized to create a user intent template with an Inter-Rater Reliability of 75%.This research successfully extracts different user types based on th

关键词： User intent cluster user profile online search information sharing user behavior search reasons

Developing Lexicons for Enhanced Sentiment Analysis in Software Engineering:An Innovative Multilingual Approach for Social Media Reviews

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Computers, Materials & Continua 2024年第5期79卷 2771-2793页

作者： Zohaib Ahmad khan Yuanqing Xia Ahmed khan Muhammad Sadiq Mahmood Alam Fuad AAwwad Emad A.A.Ismail School of Automation Beijing Institute of TechnologyBeijing100081China Department of Computer Science and Technology University of Science and Technology BannuKPKBannu28100Pakistan School of Computer Science and Engineering Central South UniversityChangsha410083China Department of Quantitative Analysis College of Business AdministrationKing Saud UniversityP.O.Box 71115Riyadh11587Saudi Arabia

Sentiment analysis is becoming increasingly important in today’s digital age, with social media being a significantsource of user-generated content. The development of sentiment lexicons that can support languages other thanEnglish is a challenging task, especially for analyzing sentiment analysis in social media reviews. Most existingsentiment analysis systems focus on English, leaving a significant research gap in other languages due to limitedresources and tools. This research aims to address this gap by building a sentiment lexicon for local languages,which is then used with a machine learning algorithm for efficient sentiment analysis. In the first step, a lexiconis developed that includes five languages: Urdu, Roman Urdu, Pashto, Roman Pashto, and English. The sentimentscores from SentiWordNet are associated with each word in the lexicon to produce an effective sentiment score. Inthe second step, a naive Bayesian algorithm is applied to the developed lexicon for efficient sentiment analysis ofRoman Pashto. Both the sentiment lexicon and sentiment analysis steps were evaluated using information retrievalmetrics, with an accuracy score of 0.89 for the sentiment lexicon and 0.83 for the sentiment analysis. The resultsshowcase the potential for improving software engineering tasks related to user feedback analysis and productdevelopment.

关键词： Emotional assessment regional dialects SentiWordNet naive bayesian technique lexicons software engineering user feedback

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基于频繁模式树和预设权限权重的角色挖掘

基于频繁模式树和预设权限权重的角色挖掘

作者：马全（maqbool khan）华中科技大学

学位级别：硕士

定义一个完整、正确有效的角色集合和相关权限的过程称为角色工程。角色工程有两种方法，自下而上和自上而下。自上而下的方法主要是业务驱动的，根据给定工作职能的责任定义角色。自下而上的方法是使用数据挖掘技术根据已有访问权限抽... 详细信息

定义一个完整、正确有效的角色集合和相关权限的过程称为角色工程。角色工程有两种方法，自下而上和自上而下。自上而下的方法主要是业务驱动的，根据给定工作职能的责任定义角色。自下而上的方法是使用数据挖掘技术根据已有访问权限抽象出角色。这种自下而上的方法被称为是角色挖掘。之前的研究方法大多是基于Apriori数据挖掘技术，并将所有权限同等对待。这些工作都没有包括预设权重分配以及基于频繁模式树（FP-tree）的频繁模式增长（FP-增长）数据挖掘技术。现有研究是致力于使用角色挖掘技术来帮助安全专家及管理员来实施有效的基于角色的访问控制（RBAC）。现在已经设计出不同的角色挖掘算法，大多数都是基于先验的方式（Apriori方法）。研究使用著名的基于FP-tree的频繁模式增长数据挖掘技术，这种技术比角色挖掘中使用的其他算法更为高效。基于先验的角色挖掘（Apriori）算法效率较低，因为它使用生成和测试的方法，即首先产生频繁的候选项目集，然后测试它们是否是频繁的，而基于FP-tree的角色挖掘的方法在空间和时间上都更高效，因为它可以不产生候选项目集而发现频繁项目。根据组织需要，使用该方法给予权限预先分配的权重。权重根据相关组织安全模型架构来确定。不同的组织有不同的安全级别，并根据自己的需要对权限进行分级。我们提出的方法在基于FP-Tree和FP-growth角色挖掘技术的角色挖掘算法中引入预设的权重。研究提出了一种新的方法来计算权限集合的权重、加权支持度和加权可信度，这在角色挖掘领域是一个重要增强。实验结果表明，研究提出的引入预设权重的基于FP-树的角色挖掘算法，在速度和效率方面均显示出了优越性。

关键词：角色工程加权角色挖掘频繁模式树频繁模式增长