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A model to measure the spread power of rumors

Journal of Ambient Intelligence and Humanized Computing 2023年第10期14卷 13787-13811页

作者： Jahanbakhsh-Nagadeh, Zoleikha Feizi-Derakhshi, Mohammad-Reza Ramezani, Majid Akan, Taymaz Asgari-Chenaghlu, Meysam Nikzad-Khasmakhi, Narjes Feizi-Derakhshi, Ali-Reza Ranjbar-Khadivi, Mehrdad Zafarani-Moattar, Elnaz Balafar, Mohammad-Ali Computerized Intelligence Systems Laboratory Department of Computer Engineering University of Tabriz Tabriz Iran Department of Computer Engineering Naghadeh Branch Islamic Azad University Naghadeh Iran Department of Computer Engineering Science and Research Branch Islamic Azad University Tehran Iran Department of Software Engineering Istanbul Topkapi University Istanbul Turkey Clinical Informatics Louisiana State University Health Sciences Center Shreveport Shreveport United States Department of Computer Engineering Shabestar Branch Islamic Azad University Shabestar Iran Department of Computer Engineering Tabriz Branch Islamic Azad University Tabriz Iran Department of Computer Engineering University of Tabriz Tabriz Iran

With technologies that have democratized the production and reproduction of information, a significant portion of daily interacted posts in social media has been infected by rumors. Despite the extensive research on rumor detection and verification, so far, the problem of calculating the spread power of rumors has not been considered. To address this research gap, the present study seeks a model to calculate the Spread Power of Rumor (SPR) as the function of content-based features in two categories: False Rumor (FR) and True Rumor (TR). For this purpose, the theory of Allport and Postman will be adopted, which it claims that importance and ambiguity are the key variables in rumor-mongering and the power of rumor. Totally 42 content features in two categories "importance" (28 features) and "ambiguity" (14 features) are introduced to compute SPR. The proposed model is evaluated on two datasets, Twitter and Telegram. The results showed that (i) the spread power of False Rumor documents is rarely more than True Rumors. (ii) there is a significant difference between the SPR means of two groups False Rumor and True Rumor. (iii) SPR as a criterion can have a positive impact on distinguishing False Rumors and True Rumors. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Cell proliferation

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Multi-Agent Formation Control under Switching Network and Input Constraints

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IFAC-PapersOnLine 2023年第2期56卷 2620-2625页

作者： Djati Wibowo Djamari Azwirman Gusrialdi Muhamad Rausyan Fikri Yuliana Susilowati Autonomous Systems Laboratory Faculty of Engineering Technology Sampoerna University Indonesia Faculty of Engineering and Natural Sciences Tampere University Finland Climate Change and Sustainable Development Research Center for Climate and Atmosphere The National Research and Innovation Agency Indonesia

This work discusses formation control of heterogeneous Multi-Agent systems (MASs) under discrete time setting where its formation size is scalable by a scaling factor. The case with and without input constraints are discussed. The communication network is assumed to be jointly connected and the leader-follower network is assumed for the unconstrained case. Compared to the previous work on distributed scalable formation control for heterogeneous agents, this work considers input constraints in the formulation. The proposed algorithm is based on the discrete time version of the internal model principle and the constraint is handled by the command governor. Numerical examples are shown to illustrate the proposed method.

关键词： Multi-agent formation Internal Model Principle Input Constraint

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Computer-Vision-Based Non-Contact Paste Concentration Measurement*

Computer-Vision-Based Non-Contact Paste Concentration Measur...

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Automation in Manufacturing, Transportation and Logistics (ICaMaL), International Conference on

作者： Tailin Liang Zhaolin Yuan State Key Laboratory of Software Development Environment School of Computer Science and Engineering Beihang University Beijing China Department of Industrial and Systems Engineering Research Institute of Advanced Manufacturing The Hong Kong Polytechnic University Hong Kong China

ISBN: (数字)9798350378658

ISBN: (纸本)9798350378665

For monitoring the paste concentration, existing techniques, such as ultrasonic concentration meters and neutron meters, suffer from radiation hazards and low precision in high concentrations. This paper proposes a novel non-contact concentration measurement method based on deep learning. With the dataset collected by preparing the paste with different concentrations and taking photographs from the paste surface, a convolutional neural network is trained to extract the features from images and predict the concentration. The experiments indicate that the measurement accuracy is close to 88.79 % for the manual stirring paste dataset and 91.42 % for the automatic stirring paste dataset, which are sufficient in industrial applications. As a substitution of traditional concentration measurement instruments, the proposed vision-based concentration measurement method is non-contact and its accuracy is sufficient in industrial applications.

关键词： Meters Deep learning Accuracy Ultrasonic variables measurement Transportation Manuals Feature extraction Surface texture Convolutional neural networks Surface treatment

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Identification of microRNA and analysis of target genes in Panax ginseng

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Chinese Herbal Medicines 2023年第1期15卷 69-75页

作者： Yingfang Wang Yanlin Chen Mengyuan Peng Chang Yang Zemin Yang Mengjuan Gong Yongqin Yin Yu Zeng Guangdong Provincial Key Laboratory of Advanced Drug Delivery Systems and Guangdong Provincial Engineering Center of Topical Precise Drug Delivery System Center for Drug Research and DevelopmentGuangdong Pharmaceutical UniversityGuangzhou 510006China School of Traditional Chinese Medicine Guangdong Pharmaceutical UniversityGuangzhou 510006China School of Basic Courses Guangdong Pharmaceutical UniversityGuangzhou 510006China

Objective: Ginsenosides, polysaccharides and phenols, the main active ingredients in Panax ginseng, are not different significantly in content between 3 and 5 years old of ginsengs called Yuan ginseng and more than ten years old ones called Shizhu ginseng. The responsible chemical compounds cannot fully explain difference in efficacy between them. According to reports in Lonicerae Japonicae Flos(Jinyinhua in Chinese) and Glycyrrhizae Radix et Rhizoma(Gancao in Chinese), microRNA may play a role in efficacy,so we identified microRNAs in P. ginseng at the different growth years and analyzed their target ***: Using high-throughput sequencing, the RNA-Seq, small RNA-Seq and degradome databases of P. ginseng were constructed. The differentially expressed microRNAs was identified by ***: A total of 63,875 unigenes and 24,154,579 small RNA clean reads were obtained from the roots of P. ginseng. From these small RNAs, 71 miRNA families were identified by bioinformatics target prediction software, including 34 conserved miRNAs, 37 non-conserved miRNA families, as well as 179 target genes of 17 known miRNAs. Through degradome sequencing and computation, we finally verified 13 targets of eight miRNAs involved in transcription, energy metabolism, biological stress and disease resistance, suggesting the significance of miRNAs in the development of P. ginseng. Consistently, major miRNA targets exhibited tissue specificity and complexity in expression ***: Differential expression microRNAs were found in different growth years of ginsengs(Shizhu ginseng and Yuan ginseng), and the regulatory roles and functional annotations of miRNA targets in P. ginseng need further investigation.

关键词： high-throughput sequencing miRNA target genes Panax ginseng C.A.Mey

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software fault localization based on eigenvector centrality in complex network theory

Software fault localization based on eigenvector centrality ...

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IEEE International Conference on software Quality, Reliability and Security Companion (QRS-C)

作者： Wentao Wu Shihai Wang Yuanxun Shao Wandong Xie School of Reliability and Systems Engineering Beihang University Beijing China Science and Technology on Reliability and Environmental Engineering Laboratory China State Key Laboratory of Software Development Environment China Aerospace Science and Engineering Network Information development CO. LTD Beijing China Information Center of China North Industries Group Corporation Beijing China

ISBN: (数字)9798350365658

ISBN: (纸本)9798350365665

software debugging plays a crucial role in fault localization tasks, and spectrum-based fault localization (SBFL) is a hot topic in software automation debugging research. However, existing SBFL technologies are generally limited by tie within ranks, where a large number of elements share the same suspiciousness, which in turn severely limits the performance of SBFL. To this end, we propose an SBFL model based on eigenvector centrality (FLEC). This algorithm first utilizes the statement coverage information in the program spectrum to construct a statement network, and adopts the correlation between statements as edge weights. Then, FLEC takes statement suspiciousness as node weight. On this basis, the algorithm utilizes the eigenvector centrality to calculate the weighted suspiciousness of each statement while considering both node importance and correlation between nodes. Finally, FLEC conducted experimental validation on 3 datasets of Defects4J, and the results showed an average improvement of 10.7% in ACC@N compared to the optimal baseline.

关键词： Location awareness Correlation software algorithms software quality Debugging Complex networks Reliability engineering software reliability Security software debugging

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HealthEdge: A Machine Learning-Based Smart Healthcare Framework for Prediction of Type 2 Diabetes in an Integrated IoT, Edge, and Cloud Computing System 14

HealthEdge: A Machine Learning-Based Smart Healthcare Framew...

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14th International Conference on Ambient systems, Networks and Technologies Networks, ANT 2023 and The 6th International Conference on Emerging Data and Industry 4.0, EDI40 2023

作者： Hennebelle, Alain Materwala, Huned Ismail, Leila Melbourne Australia Research Laboratory Department of Computer Science and Software Engineering College of Information Technology United Arab Emirates University United Arab Emirates National Water and Energy Center United Arab Emirates University United Arab Emirates Lab School of Computing and Information Systems The University of Melbourne Australia

Diabetes Mellitus has no permanent cure to date and is one of the leading causes of death globally. The alarming increase in diabetes calls for the need to take precautionary measures to avoid/predict the occurrence of diabetes. This paper proposes HealthEdge, a machine learning-based smart healthcare framework for type 2 diabetes prediction in an integrated IoT-edge-cloud computing system. Numerical experiments and comparative analysis were carried out between the two most used machine learning algorithms in the literature, Random Forest (RF) and Logistic Regression (LR), using two real-life diabetes datasets. The results show that RF predicts diabetes with 6% more accuracy on average compared to LR. © 2023 Elsevier B.V.. All rights reserved.

关键词： Edge computing

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Grider-Ho: Rapid and Efficient Parallel software for High-Order Curvilinear Mesh Generation

SSRN

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SSRN 2024年

作者： Liu, Xiangyu Wang, He Zhao, Zhong Wang, Huadong Guan, Zhidong Wang, Nianhua School of Aeronautic Science and Engineering Beihang University Beijing100191 China Tianfu Engineering-oriented Numerical Simulation & Software Innovation Center Sichuan University Chengdu610207 China State Key Laboratory of Aerodynamics China Aerodynamics Research and Development Center Mianyang621000 China Computational Aerodynamics Institute China Aerodynamics Research and Development Center Mianyang621000 China

The advancement in high-order computational methods is reshaping the landscape of mesh generation in Computational Fluid Dynamics (CFD), steering the focus towards curvilinear mesh techniques to meet the escalating accuracy demands. Grider-HO, a software designed for generating high-order curvilinear mesh efficiently and rapidly, has been developed. It features a layered architecture and utilizes the concurrent hash table and the Alternating Digital Tree (ADT) data structure, supporting thread-level parallelism to convert the straight-edge mesh into the high-order curvilinear mesh seamlessly. Grider-HO initially inserts high-order nodes to a straight-edge mesh using a concurrent hash table, then projects them onto the geometry model with a parallel thread pool. Finally, it employs a localized RBF method with ADT for volume node interpolation, avoiding mesh entanglement. Validated through CFD simulations using the GPU-accelerated PyFR high-order solver, the practicality of Grider-HO is demonstrated across various Reynolds numbers in typical cases like the sphere, the cylinder, and the SD7003 airfoil cases. These results confirm that the high-order curvilinear mesh generated by Grider-HO can meet the high-order requirements of emerging computational methods. Moreover, Grider-HO exemplifies its effectiveness in generating large-scale, high-order curvilinear meshes for DLR-F6 cases. It elevates a 5 million mesh to P2 in 3min39sec at 68% parallel efficiency on 16 threads, and a 14 million mesh to P3 in 52min39sec at 60% parallel efficiency on 16 threads, which illustrates its efficiency and potential in satisfying the demands of complex geometries in engineering applications. © 2024, The Authors. All rights reserved.

关键词： Computational fluid dynamics

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SnoRNAs: The promising targets for anti-tumor therapy

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Journal of Pharmaceutical Analysis 2024年第11期14卷 1588-1602页

作者： Xiaoyun Hu Wanlin Cui Min Liu Fangxiao Zhang Yingqi Zhao Mingrong Zhang Yuhang Yin Yalun Li Ying Che Xianglong Zhu Yuxuan Fan Xiaolan Deng Minjie Wei Huizhe Wu Department of Pharmacology School of PharmacyChina Medical UniversityShenyang110122China Liaoning Key Laboratory of Molecular Targeted Anti-tumor Drug Development and Evaluation Liaoning Cancer Immune Peptide Drug Engineering Technology Research CenterKey Laboratory of Precision Diagnosis and Treatment of Gastrointestinal TumorsMinistry of EducationChina Medical UniversityShenyang110122China Scientific Experimental Center School of PharmacyChina Medical UniversityShenyang110122China The Second Department of Infectious Diseases The First Affiliated Hospital of China Medical UniversityShenyang110001China Department of Anorectal Surgery The First Affiliated Hospital of China Medical UniversityShenyang110001China Department of Systems Biology Beckman Research Institute of City of HopeMonroviaCA91016USA Shenyang Kangwei Medical Laboratory Analysis Co. Ltd.Shenyang110000China

Recently,small nucleolar RNAs(snoRNAs)have transcended the genomic“noise”to emerge as pivotal molecular markers due to their essential roles in tumor *** evidence indicates a strong association between snoRNAs and critical clinical features such as tumor pathology and drug ***,snoRNA research has concentrated on two classical mechanisms:2'-O-ribose methylation and *** review specifically summarizes the novel regulatory mechanisms and functional patterns of snoRNAs in tumors,encompassing transcriptional,post-transcriptional,and post-translational *** further discuss the synergistic effect between snoRNA host genes(SNHGs)and snoRNAs in tumor *** importantly,snoRNAs extensively contribute to the development of tumor cell resistance as oncogenes or tumor suppressor ***,we provide a comprehensive review of the clinical diagnosis and treatment associated with snoRNAs and explore their significant potential as novel drug targets.

关键词： snoRNA Cancer snoRNA host gene Multidrug resistance Targeted therapy Tumor immune microenvironment

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Hierarchical Rule-Base Reduction Based ANFIS With Online Optimization Through DDPG

TechRxiv

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TechRxiv 2024年

作者： Juston, Marius F.R. Dekhterman, Samuel R. Norris, William R. Nottage, Dustin Soylemezoglu, Ahmet Department of Industrial and Enterprise Systems Engineering University of Illinois Urbana-Champaign IL61801 United States Construction Engineering Research Laboratory U.S. Army Corps of Engineers Engineering Research and Development Center IL61822 United States

This paper presents a comprehensive approach to designing and optimizing a Hierarchical Rule-Base Reduction (HRBR) based Adaptive-Network-Based Fuzzy Inference System (ANFIS) for symmetric linguistic variables. Specifically, the linguistic connected membership functions that underlie the ANFIS are defined, focusing on symmetrical inputs/outputs and jointly optimized trapezoid membership functions to reduce the number of training parameters. Further optimizations for the ANFIS were derived based on design assumptions, including training the membership functions on closed or single-sided domains. The optimal output membership weights based on mean square error optimization were also symbolically obtained. The online training of the ANFIS’s input/output membership functions was performed using the DDPG (Deep Deterministic Policy Gradient) algorithm. A simulated skid-steered vehicle was used to validate the approach and performed waypoint-to-waypoint path following. Experimental results using the Clearpath Jackal demonstrated that the ANFIS model converged quickly, typically within 6 to 10 episodes of training, from an initial MAE and RMSE of 0.88 and 1.02 meters, respectively, to a final MAE and RMSE of 0.087 and 0.10 meters. The results highlight the effectiveness of the ANFIS approach for vehicular robotics applications and suggest promising avenues for future research and development. © 2024, CC BY.

关键词： Fuzzy neural networks

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A CPK-Based Identity Authentication Scheme for IoT

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Computer systems Science & engineering 2022年第3期40卷 1217-1231页

作者： Mingming Zhang Jiaming Mao Yuanyuan Ma Liangjie Xu Chuanjun Wang Ran Zhao Zhihao Li Lu Chen Wenbing Zhao State Grid Jiangsu Electric Power Co. Ltd.Information&Telecommunication BranchNanjing210008China State Grid Key Laboratory of Information&Network Security Institute of Information and CommunicationGlobal Energy Interconnection Research InstituteNanjing210003China Anhui Jiyuan Software Co.Ltd SGITGHefei230088China Engineering Research Center of Post Big Data Technology and Application of Jiangsu Province Research and Development Center of Post Industry Technology of the State Posts Bureau(Internet of Things Technology)Engineering Research Center of Broadband Wireless Communication Technology of the Ministry of EducationNanjing University of Posts and TelecommunicationsNanjing210003China Department of Electrical Engineering and Computer Science Cleveland State UniversityCleveland44115USA

As the power Internet of Things(IoT)enters the security construction stage,the massive use of perception layer devices urgently requires an identity authentication scheme that considers both security and *** existing public key infrastructure(PKI)-based security authentication scheme is currently difficult to apply in many terminals in *** key distribution and management costs are high,which hinders the development of power IoT security *** Public Key(CPK)technology uses a small number of seeds to generate unlimited public *** is very suitable for identity authentication in the power Internet of *** this paper,we propose a novel identity authentication scheme for power *** scheme combines the physical unclonable function(PUF)with improved CPK technology to achieve mutual identity authentication between power IoT terminals and *** proposed scheme does not require third-party authentication and improves the security of identity authentication for power ***,the scheme reduces the resource consumption of power IoT *** improved CPK algorithm solves the key collision problem,and the third party only needs to save the private key and the public key *** results show that the amount of storage resources occupied in our scheme is *** proposed scheme is more suitable for the power IoT.

关键词： Power Internet of Things terminal equipment identity authentication CPK PUF

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