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Physical information-enhanced graph neural network for predicting phase separation

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Chinese Physics B 2024年第7期33卷 278-283页

作者：张亚强王煦文王雅楠郑文 Institute of Public-Safety and Big data College of Computer Science and Technology(College of Data Science)Taiyuan University of TechnologyJinzhong 030600China Shanxi Engineering Research centre for Intelligent data Assisted Treatment Changzhi Medical CollegeChangzhi 046000China Innovation Academy for Microsatellites of Chinese Academy of Sciences Shanghai 200050China

Although phase separation is a ubiquitous phenomenon, the interactions between multiple components make it difficult to accurately model and predict. In recent years, machine learning has been widely used in physics simulations. Here,we present a physical information-enhanced graph neural network(PIENet) to simulate and predict the evolution of phase separation. The accuracy of our model in predicting particle positions is improved by 40.3% and 51.77% compared with CNN and SVM respectively. Moreover, we design an order parameter based on local density to measure the evolution of phase separation and analyze the systematic changes with different repulsion coefficients and different Schmidt *** results demonstrate that our model can achieve long-term accurate predictions of order parameters without requiring complex handcrafted features. These results prove that graph neural networks can become new tools and methods for predicting the structure and properties of complex physical systems.

关键词： graph neural network phase separation machine learning dissipative particle dynamics

Robust zero-watermarking algorithm based on discrete wavelet transform and daisy descriptors for encrypted medical image

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CAAI Transactions on Intelligence Technology 2024年第1期9卷 40-53页

作者： Yiyi Yuan Jingbing Li Jing Liu Uzair Aslam Bhatti Zilong Liu Yen-wei Chen School of information and Communication Engineering Hainan UniversityHaikouChina Research Center for Healthcare data Science Zhejiang LabHangzhouChina Graduate School of information Science and Engineering Ritsumeikan University ShigaJapan

In the intricate network environment,the secure transmission of medical images faces challenges such as information leakage and malicious tampering,significantly impacting the accuracy of disease diagnoses by medical *** address this problem,the authors propose a robust feature watermarking algorithm for encrypted medical images based on multi-stage discrete wavelet transform(DWT),Daisy descriptor,and discrete cosine transform(DCT).The algorithm initially encrypts the original medical image through DWT-DCT and Logistic ***,a 3-stage DWT transformation is applied to the encrypted medical image,with the centre point of the LL3 sub-band within its low-frequency component serving as the sampling *** Daisy descriptor matrix for this point is then ***,a DCT transformation is performed on the Daisy descriptor matrix,and the low-frequency portion is processed using the perceptual hashing algorithm to generate a 32-bit binary feature vector for the medical *** scheme utilises cryptographic knowledge and zero-watermarking technique to embed watermarks without modifying medical images and can extract the watermark from test images without the original image,which meets the basic re-quirements of medical image *** embedding and extraction of water-marks are accomplished in a mere 0.160 and 0.411s,respectively,with minimal computational *** results demonstrate the robustness of the algorithm against both conventional attacks and geometric attacks,with a notable performance in resisting rotation attacks.

关键词： daisy descriptor DCT DWT encryption domain medical image zero-watermarking

Characterizing structure of cross-disciplinary impact of global disciplines:A perspective of the Hierarchy of Science

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Journal of data and information Science 2024年第1期9卷 53-81页

作者： Ruolan Liu Jin Mao Gang Li Yujie Cao Center for Studies of information Resources Wuhan UniversityWuhan 430072China School of information management Wuhan UniversityWuhan 430072China School of information management Central China Normal University 430072WuhanChina

Purpose:Interdisciplinary fields have become the driving force of modern science and a significant source of scientific ***,there is still a paucity of analysis about the essential characteristics of disciplines’cross-disciplinary ***/methodology/approach:In this study,we define cross-disciplinary impact on one discipline as its impact to other disciplines,and refer to a three-dimensional framework of variety-balance-disparity to characterize the structure of cross-disciplinary *** variety of cross-disciplinary impact of the discipline was defined as the proportion of the high cross-disciplinary impact publications,and the balance and disparity of cross-disciplinary impact were measured as *** demonstrate the cross-disciplinary impact of the disciplines in science,we chose Microsoft Academic Graph(MAG)as the data source,and investigated the relationship between disciplines’cross-disciplinary impact and their positions in the Hierarchy of Science(HOS).Findings:Analytical results show that there is a significant correlation between the ranking of cross-disciplinary impact and the HOS structure,and that the discipline exerts a greater cross-disciplinary impact on its neighboring *** bibliometric features that measure the hardness of a discipline,including the number of references,the number of cited disciplines,the citation distribution,and the Price index have a significant positive effect on the variety of cross-disciplinary *** number of references,the number of cited disciplines,and the citation distribution have significant positive and negative effects on balance and disparity,*** is concluded that the less hard the discipline,the greater the cross-disciplinary impact,the higher balance and the lower disparity of cross-disciplinary *** limitations:In the empirical analysis of HOS,we only included five broad *** study also has some biases caused by the data source and a

关键词： Interdisciplinary research cross-disciplinary Scientific impact Soft science Hard science Citation

A comparative study on characteristics of retracted publications across different open access levels

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Journal of data and information Science 2024年第2期9卷 22-40页

作者： Er-Te Zheng Hui-Zhen Fu Department of information Resources management School of Public AffairsZhejiang UniversityHangzhou 310058China School of information Resource management Renmin University of ChinaBeijing 100872China

Purpose:Recently,global science has shown an increasing open trend,however,the characteristics of research integrity of open access(OA)publications have rarely been *** aim of this study is to compare the characteristics of retracted articles across different OA levels and discover whether OA level influences the characteristics of retracted ***/methodology/approach:The research conducted an analysis of 6,005 retracted publications between 2001 and 2020 from the Web of Science and Retraction Watch *** publications were categorized based on their OA levels,including Gold OA,Green OA,and *** study explored retraction rates,time lags and reasons within these ***:The findings of this research revealed distinct patterns in retraction rates among different OA *** with Gold OA demonstrated the highest retraction rate,followed by Green OA and non-OA.A comparison of retraction reasons between Gold OA and non-OA categories indicated similar proportions,while Green OA exhibited a higher proportion due to falsification and manipulation issues,along with a lower occurrence of plagiarism and authorship *** retraction time lag was shortest for Gold OA,followed by non-OA,and longest for Green *** prolonged retraction time for Green OA could be attributed to an atypical distribution of retraction reasons.A comparative study on characteristics of retracted publications across different open access levels Research limitations:There is no exploration of a wider range of OA levels,such as Hybrid OA and Bronze *** implications:The outcomes of this study suggest the need for increased attention to research integrity within the OA *** occurrences offalsification,manipulation,and ethical concerns within Green OA publications warrant attention from the scientific ***/value:This study contributes to the understanding of research integrity in the realm of OA publications,she

关键词： Open access Retracted publications Reasons for retraction Retraction time lag Bibliometrics

A new evolutional model for institutional field knowledge flow network

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Journal of data and information Science 2024年第1期9卷 101-123页

作者： Jinzhong Guo Kai Wang Xueqin Liao Xiaoling Liu School of information management Xinjiang University of Finance and EconomicsUrumqiChina

Purpose:This paper aims to address the limitations in existing research on the evolution of knowledge flow networks by proposing a meso-level institutional field knowledge flow network evolution model(IKM).The purpose is to simulate the construction process of a knowledge flow network using knowledge organizations as units and to investigate its effectiveness in replicating institutional field knowledge flow ***/Methodology/Approach:The IKM model enhances the preferential attachment and growth observed in scale-free BA networks,while incorporating three adjustment parameters to simulate the selection of connection targets and the types of nodes involved in the network evolution process Using the PageRank algorithm to calculate the significance of nodes within the knowledge flow *** compare its performance,the BA and DMS models are also employed for simulating the *** coefficient analysis is conducted on the simulated networks generated by the IKM,BA and DMS models,as well as on the actual ***:The research findings demonstrate that the IKM model outperforms the BA and DMS models in replicating the institutional field knowledge flow *** provides comprehensive insights into the evolution mechanism of knowledge flow networks in the scientific research *** model also exhibits potential applicability to other knowledge networks that involve knowledge organizations as node *** Limitations:This study has some ***,it primarily focuses on the evolution of knowledge flow networks within the field of physics,neglecting other ***,the analysis is based on a specific set of data,which may limit the generalizability of the *** research could address these limitations by exploring knowledge flow networks in diverse fields and utilizing broader *** Implications:The proposed IKM model offers practical implications for the construction and analysis of knowledge

关键词： Knowledge flow networks Evolutionary mechanism BA model Knowledge units

data-Driven Earthquake Multi-impact Modeling: A Comparison of Models

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International Journal of Disaster Risk Science 2024年第3期15卷 421-433页

作者： Hamish Patten Max Anderson Loake David Steinsaltz information management International Federation of Red Cross and Red Crescent Societies (IFRC) Department of Statistics University of Oxford

In this study, a broad range of supervised machine learning and parametric statistical, geospatial, and non-geospatial models were applied to model both aggregated observed impact estimate data and satellite image-derived geolocated building damage data for earthquakes, via regression-and classification-based models, respectively. For the aggregated observational data, models were ranked via predictive performance of mortality, population displacement, building damage, and building destruction for 375 observations across 161 earthquakes in 61 countries. For the satellite image-derived data, models were ranked via classification performance(damaged/unaff ected) of 369,813 geolocated buildings for 26 earthquakes in 15 countries. Grouped k-fold, 3-repeat cross validation was used to ensure out-of-sample predictive performance. Feature importance of several variables used as proxies for vulnerability to disasters indicates covariate utility. The 2023 Türkiye–Syria earthquake event was used to explore model limitations for extreme events. However, applying the AdaBoost model on the 27,032 held-out buildings of the 2023 Türkiye–Syria earthquake event, predictions had an AUC of 0.93. Therefore, without any geospatial, building-specific, or direct satellite image information, this model accurately classified building damage,with significantly improved performance over satellite image trained models found in the literature.

关键词： Disaster risk modeling Earthquake impact models Machine learning Disaster statistics Satellite image-derived building damage

Recent Developments in Authentication Schemes Used in Machine-Type Communication Devices in Machine-to-Machine Communication: Issues and Challenges

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Computers, Materials & Continua 2024年第4期79卷 93-115页

作者： Shafi Ullah Sibghat Ullah Bazai Mohammad Imran Qazi Mudassar Ilyas Abid Mehmood Muhammad Asim Saleem Muhmmad Aasim Rafique Arsalan Haider Ilyas Khan Sajid Iqbal Yonis Gulzar Kauser Hameed Department of Computer Engineering Balochistan University of Information TechnologyEngineering and Management SciencesQuetta87300Pakistan Department of information Technology Balochistan University of Information TechnologyEngineeringand Management SciencesQuetta87300Pakistan Department of information Systems College of Computer Sciences and Information TechnologyKing Faisal UniversityHofuf in Al-Ahsa31982Saudi Arabia Department of management information Systems College of Business AdministrationKing Faisal UniversityHofuf in Al-Ahsa31982Saudi Arabia Department of Software Engineering College of ComputingRiphah International UniversityFaisalabad44000Pakistan Department of Electrical Engineering Balochistan University of information Technology Engineeringand Management SciencesQuetta87300Pakistan Department of Mathematics College of Science Al-ZulfiMajmaah UniversityAl-Majmaah11952Saudi Arabia

Machine-to-machine (M2M) communication plays a fundamental role in autonomous IoT (Internet of Things)-based infrastructure, a vital part of the fourth industrial revolution. Machine-type communication devices(MTCDs) regularly share extensive data without human intervention while making all types of decisions. Thesedecisions may involve controlling sensitive ventilation systems maintaining uniform temperature, live heartbeatmonitoring, and several different alert systems. Many of these devices simultaneously share data to form anautomated system. The data shared between machine-type communication devices (MTCDs) is prone to risk dueto limited computational power, internal memory, and energy capacity. Therefore, securing the data and devicesbecomes challenging due to factors such as dynamic operational environments, remoteness, harsh conditions,and areas where human physical access is difficult. One of the crucial parts of securing MTCDs and data isauthentication, where each devicemust be verified before data transmission. SeveralM2Mauthentication schemeshave been proposed in the literature, however, the literature lacks a comprehensive overview of current M2Mauthentication techniques and the challenges associated with them. To utilize a suitable authentication schemefor specific scenarios, it is important to understand the challenges associated with it. Therefore, this article fillsthis gap by reviewing the state-of-the-art research on authentication schemes in MTCDs specifically concerningapplication categories, security provisions, and performance efficiency.

关键词： Authentication cyber security internet of things machine-type communication devices machine-to-machine communication

Research on Credit Regulation Mechanism of E-commerce Platform Based on Evolutionary Game Theory

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Journal of Systems Science and Systems Engineering 2024年第3期33卷 330-359页

作者： Zeguo Qiu Yuchen Yin Yao Yuan Yunhao Chen School of Computer and information Engineering Harbin University of CommerceHarbin150028China School of management Harbin University of CommerceHarbin150028China

In the growing e-commerce industry,the problem of malicious business operations has become increasingly prominent,exposing many problems such as weak supervision of e-commerce platforms and no way for consumers to *** order to solve the problems of counterfeit and shoddy products on e-commerce platforms and promote the sustainable development of the e-commerce industry in China,this paper constructs a three-party evolutionary game model of e-commerce platforms,merchants,and consumers,investigates the influence of each influencing factor on each party’s strategy choice,and provides targeted suggestions to e-commerce platforms based on relevant ***,the impact of several important parameters on the equilibrium solution is discussed through sensitivity *** results show that:1)the smaller the cost difference between active and negative regulation,the more the e-commerce platform tends to active regulation strategy,but increasing fines for dishonest merchants and consumer complaints have little impact on the e-commerce platform;2)increasing consumer compensation,creating an honest business environment,and reducing the cost of honest business all help companies tend to operate in good faith;3)the only factor that affects the tendency of consumer complaint strategies is the cost of *** loss suffered by silence and the compensation given to consumers have little effect on consumers’tendency to complain *** results can provide theoretical guidance for participants to make useful strategic decisions in the e-commerce market.

关键词： Evolutionary game e-commerce data simulation

Novel Rifle Number Recognition Based on Improved YOLO in Military Environment

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Computers, Materials & Continua 2024年第1期78卷 249-263页

作者： Hyun Kwon Sanghyun Lee Department of Artificial Intelligence and data Science Korea Military AcademySeoulKorea Graduate School of information Security Korea Advanced Institute of Science and TechnologyDaejeonKorea

Deep neural networks perform well in image recognition,object recognition,pattern analysis,and speech *** military applications,deep neural networks can detect equipment and recognize *** military equipment,it is necessary to detect and recognize rifle management,which is an important piece of equipment,using deep neural *** have been no previous studies on the detection of real rifle numbers using real rifle image *** this study,we propose a method for detecting and recognizing rifle numbers when rifle image data are *** proposed method was designed to improve the recognition rate of a specific dataset using data fusion and transfer *** the proposed method,real rifle images and existing digit images are fusedas trainingdata,andthe final layer is transferredto theYolov5 *** detectionand recognition performance of rifle numbers was improved and analyzed using rifle image and numerical *** used actual rifle image data(K-2 rifle)and numeric image datasets,as an experimental *** was used as the machine learning *** results show that the proposed method maintains 84.42% accuracy,73.54% precision,81.81% recall,and 77.46% F1-score in detecting and recognizing rifle *** proposed method is effective in detecting rifle numbers.

关键词： Machine learning deep neural network rifle number recognition detection