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Predictive factors and model validation of post-colon polyp surgery Helicobacter pylori infection 被引量:1
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作者 Zheng-Sen Zhang 《World Journal of Gastrointestinal Surgery》 SCIE 2024年第1期173-185,共13页
BACKGROUND Recently,research has linked Helicobacter pylori(H.pylori)stomach infection to colonic inflammation,mediated by toxin production,potentially impacting colorectal cancer occurrence.AIM To investigate the ris... BACKGROUND Recently,research has linked Helicobacter pylori(H.pylori)stomach infection to colonic inflammation,mediated by toxin production,potentially impacting colorectal cancer occurrence.AIM To investigate the risk factors for post-colon polyp surgery,H.pylori infection,and its correlation with pathologic type.METHODS Eighty patients who underwent colon polypectomy in our hospital between January 2019 and January 2023 were retrospectively chosen.They were then randomly split into modeling(n=56)and model validation(n=24)sets using R.The modeling cohort was divided into an H.pylori-infected group(n=37)and an H.pylori-uninfected group(n=19).Binary logistic regression analysis was used to analyze the factors influencing the occurrence of H.pylori infection after colon polyp surgery.A roadmap prediction model was established and validated.Finally,the correlation between the different pathological types of colon polyps and the occurrence of H.pylori infection was analyzed after colon polyp surgery.RESULTS Univariate results showed that age,body mass index(BMI),literacy,alcohol consumption,polyp pathology type,high-risk adenomas,and heavy diet were all influential factors in the development of H.pylori infection after intestinal polypectomy.Binary multifactorial logistic regression analysis showed that age,BMI,and type of polyp pathology were independent predictors of the occurrence of H.pylori infection after intestinal polypectomy.The area under the receiver operating characteristic curve was 0.969[95%confidence interval(95%CI):0.928–1.000]and 0.898(95%CI:0.773–1.000)in the modeling and validation sets,respectively.The slope of the calibration curve of the graph was close to 1,and the goodness-of-fit test was P>0.05 in the two sets.The decision analysis curve showed a high rate of return in both sets.The results of the correlation analysis between different pathological types and the occurrence of H.pylori infection after colon polyp surgery showed that hyperplastic polyps,inflammatory polyps,and the occurrence of H.pylori infection were not significantly correlated.In contrast,adenomatous polyps showed a significant positive correlation with the occurrence of H.pylori infection.CONCLUSION Age,BMI,and polyps of the adenomatous type were independent predictors of H.pylori infection after intestinal polypectomy.Moreover,the further constructed column-line graph prediction model of H.pylori infection after intestinal polypectomy showed good predictive ability. 展开更多
关键词 Colon polyps Helicobacter pylori Risk factors Pathologic type Columnar graphic modeling
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Development of a building information model-guided post-earthquake building inspection framework using 3D synthetic environments 被引量:1
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作者 Nathaniel M.Levine Yasutaka Narazaki Billie F.Spencer 《Earthquake Engineering and Engineering Vibration》 SCIE EI CSCD 2023年第2期279-307,共29页
Computer vision-based inspection methods show promise for automating post-earthquake building inspections.These methods survey a building with unmanned aerial vehicles and automatically detect damage in the collected ... Computer vision-based inspection methods show promise for automating post-earthquake building inspections.These methods survey a building with unmanned aerial vehicles and automatically detect damage in the collected images.Nevertheless,assessing the damage′s impact on structural safety requires localizing damage to specific building components with known design and function.This paper proposes a BIM-based automated inspection framework to provide context for visual surveys.A deep learning-based semantic segmentation algorithm is trained to automatically identify damage in images.The BIM automatically associates any identified damage with specific building components.Then,components are classified into damage states consistent with component fragility models for integration with a structural analysis.To demonstrate the framework,methods are developed to photorealistically simulate severe structural damage in a synthetic computer graphics environment.A graphics model of a real building in Urbana,Illinois,is generated to test the framework;the model is integrated with a structural analysis to apply earthquake damage in a physically realistic manner.A simulated UAV survey is flown of the graphics model and the framework is applied.The method achieves high accuracy in assigning damage states to visible structural components.This assignment enables integration with a performance-based earthquake assessment to classify building safety. 展开更多
关键词 computer vision earthquake engineering building information model physics-based graphics model synthetic environment
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A framework for computer vision-based health monitoring of a truss structure subjected to unknown excitations
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作者 Mariusz Ostrowski Bartlomiej Blachowski +3 位作者 Bartosz Wójcik Mateusz Żarski Piotr Tauzowski Łukasz Jankowski 《Earthquake Engineering and Engineering Vibration》 SCIE EI CSCD 2023年第1期1-17,共17页
Computer vision(CV)methods for measurement of structural vibration are less expensive,and their application is more straightforward than methods based on sensors that measure physical quantities at particular points o... Computer vision(CV)methods for measurement of structural vibration are less expensive,and their application is more straightforward than methods based on sensors that measure physical quantities at particular points of a structure.However,CV methods produce significantly more measurement errors.Thus,computer vision-based structural health monitoring(CVSHM)requires appropriate methods of damage assessment that are robust with respect to highly contaminated measurement data.In this paper a complete CVSHM framework is proposed,and three damage assessment methods are tested.The first is the augmented inverse estimate(AIE),proposed by Peng et al.in 2021.This method is designed to work with highly contaminated measurement data,but it fails with a large noise provided by CV measurement.The second method,as proposed in this paper,is based on the AIE,but it introduces a weighting matrix that enhances the conditioning of the problem.The third method,also proposed in this paper,introduces additional constraints in the optimization process;these constraints ensure that the stiffness of structural elements can only decrease.Both proposed methods perform better than the original AIE.The latter of the two proposed methods gives the best results,and it is robust with respect to the selected coefficients,as required by the algorithm. 展开更多
关键词 computer vision structural health monitoring physics-based graphical models augmented inverse estimate model updating non-negative least square method
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Enhancing Feature Discretization in Alarm and Fire Detection Systems Using Probabilistic Inference Models
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作者 Joe Essien 《Journal of Computer and Communications》 2023年第7期140-155,共16页
Sensors for fire alarms require a high level of predictive variables to ensure accurate detection, injury prevention, and loss prevention. Bayesian networks can aid in enhancing early fire detection capabilities and r... Sensors for fire alarms require a high level of predictive variables to ensure accurate detection, injury prevention, and loss prevention. Bayesian networks can aid in enhancing early fire detection capabilities and reducing the frequency of erroneous fire alerts, thereby enhancing the effectiveness of numerous safety monitoring systems. This research explores the development of optimized probabilistic graphic models for the discretization thresholds of alarm system predictor variables. The study presents a statistical model framework that increases the efficacy of fire detection by predicting the discretization thresholds of alarm system predictor variable fluctuations used to detect the onset of fire. The work applies the Bayesian networks and probabilistic visual models to reveal the specific characteristics required to cope with fire detection strategies and patterns. The adopted methodology utilizes a combination of prior knowledge and statistical data to draw conclusions from observations. Utilizing domain knowledge to compute conditional dependencies between network variables enabled predictions to be made through the application of specialized analytical and simulation techniques. 展开更多
关键词 Neural Network DISCRETIZATION Alarm Systems Graphical Models Machine Learning
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Toward the Next Generation of Retinal Neuroprosthesis: Visual Computation with Spikes 被引量:3
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作者 Zhaofei Yu Jian K.Liu +4 位作者 Shanshan Jia Yichen Zhang Yajing Zheng Yonghong Tian Tiejun Huang 《Engineering》 SCIE EI 2020年第4期449-461,共13页
A neuroprosthesis is a type of precision medical device that is intended to manipulate the neuronal signals of the brain in a closed-loop fashion,while simultaneously receiving stimuli from the environment and control... A neuroprosthesis is a type of precision medical device that is intended to manipulate the neuronal signals of the brain in a closed-loop fashion,while simultaneously receiving stimuli from the environment and controlling some part of a human brain or body.Incoming visual information can be processed by the brain in millisecond intervals.The retina computes visual scenes and sends its output to the cortex in the form of neuronal spikes for further computation.Thus,the neuronal signal of interest for a retinal neuroprosthesis is the neuronal spike.Closed-loop computation in a neuroprosthesis includes two stages:encoding a stimulus as a neuronal signal,and decoding it back into a stimulus.In this paper,we review some of the recent progress that has been achieved in visual computation models that use spikes to analyze natural scenes that include static images and dynamic videos.We hypothesize that in order to obtain a better understanding of the computational principles in the retina,a hypercircuit view of the retina is necessary,in which the different functional network motifs that have been revealed in the cortex neuronal network are taken into consideration when interacting with the retina.The different building blocks of the retina,which include a diversity of cell types and synaptic connections-both chemical synapses and electrical synapses(gap junctions)-make the retina an ideal neuronal network for adapting the computational techniques that have been developed in artificial intelligence to model the encoding and decoding of visual scenes.An overall systems approach to visual computation with neuronal spikes is necessary in order to advance the next generation of retinal neuroprosthesis as an artificial visual system. 展开更多
关键词 Visual coding RETINA NEUROPROSTHESIS Brain-machine interface Artificial intelligence Deep learning Spiking neural network Probabilistic graphical model
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BURST-LDA: A NEW TOPIC MODEL FOR DETECTING BURSTY TOPICS FROM STREAM TEXT 被引量:3
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作者 Qi Xiang Huang Yu +4 位作者 Chen Ziyan Liu Xiaoyan Tian Jing Huang Tinglei Wang Hongqi 《Journal of Electronics(China)》 2014年第6期565-575,共11页
Topic models such as Latent Dirichlet Allocation(LDA) have been successfully applied to many text mining tasks for extracting topics embedded in corpora. However, existing topic models generally cannot discover bursty... Topic models such as Latent Dirichlet Allocation(LDA) have been successfully applied to many text mining tasks for extracting topics embedded in corpora. However, existing topic models generally cannot discover bursty topics that experience a sudden increase during a period of time. In this paper, we propose a new topic model named Burst-LDA, which simultaneously discovers topics and reveals their burstiness through explicitly modeling each topic's burst states with a first order Markov chain and using the chain to generate the topic proportion of documents in a Logistic Normal fashion. A Gibbs sampling algorithm is developed for the posterior inference of the proposed model. Experimental results on a news data set show our model can efficiently discover bursty topics, outperforming the state-of-the-art method. 展开更多
关键词 Text mining Burst detection Topic model Graphical model Bayesian inference
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Seed Selection for Data Offloading Based on Social and Interest Graphs 被引量:1
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作者 Ying Li Jianbo Li +2 位作者 Jianwei Chen Minchao Lu Caoyuan Li 《Computers, Materials & Continua》 SCIE EI 2018年第12期571-587,共17页
The explosive growth of mobile data demand is becoming an increasing burden on current cellular network.To address this issue,we propose a solution of opportunistic data offloading for alleviating overloaded cellular ... The explosive growth of mobile data demand is becoming an increasing burden on current cellular network.To address this issue,we propose a solution of opportunistic data offloading for alleviating overloaded cellular traffic.The principle behind it is to select a few important users as seeds for data sharing.The three critical steps are detailed as follows.We first explore individual interests of users by the construction of user profiles,on which an interest graph is built by Gaussian graphical modeling.We then apply the extreme value theory to threshold the encounter duration of user pairs.So,a contact graph is generated to indicate the social relationships of users.Moreover,a contact-interest graph is developed on the basis of the social ties and individual interests of users.Corresponding on different graphs,three strategies are finally proposed for seed selection in an aim to maximize overloaded cellular data.We evaluate the performance of our algorithms by the trace data of real-word mobility.It demonstrates the effectiveness of the strategy of taking social relationships and individual interests into account. 展开更多
关键词 Mobile social network social data offloading extreme value model Gaussian graphical model
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An integrative multivariate approach for predicting functional recovery using magnetic resonance imaging parameters in a translational pig ischemic stroke model
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作者 Erin E.Kaiser J.C.Poythress +6 位作者 Kelly M.Scheulin Brian J.Jurgielewicz Nicole A.Lazar Cheolwoo Park Steven L.Stice Jeongyoun Ahn Franklin D.West 《Neural Regeneration Research》 SCIE CAS CSCD 2021年第5期842-850,共9页
Magnetic resonance imaging(MRI)is a clinically relevant,real-time imaging modality that is frequently utilized to assess stroke type and severity.However,specific MRI biomarkers that can be used to predict long-term f... Magnetic resonance imaging(MRI)is a clinically relevant,real-time imaging modality that is frequently utilized to assess stroke type and severity.However,specific MRI biomarkers that can be used to predict long-term functional recovery are still a critical need.Consequently,the present study sought to examine the prognostic value of commonly utilized MRI parameters to predict functional outcomes in a porcine model of ischemic stroke.Stroke was induced via permanent middle cerebral artery occlusion.At 24 hours post-stroke,MRI analysis revealed focal ischemic lesions,decreased diffusivity,hemispheric swelling,and white matter degradation.Functional deficits including behavioral abnormalities in open field and novel object exploration as well as spatiotemporal gait impairments were observed at 4 weeks post-stroke.Gaussian graphical models identified specific MRI outputs and functional recovery variables,including white matter integrity and gait performance,that exhibited strong conditional dependencies.Canonical correlation analysis revealed a prognostic relationship between lesion volume and white matter integrity and novel object exploration and gait performance.Consequently,these analyses may also have the potential of predicting patient recovery at chronic time points as pigs and humans share many anatomical similarities(e.g.,white matter composition)that have proven to be critical in ischemic stroke pathophysiology.The study was approved by the University of Georgia(UGA)Institutional Animal Care and Use Committee(IACUC;Protocol Number:A2014-07-021-Y3-A11 and 2018-01-029-Y1-A5)on November 22,2017. 展开更多
关键词 behavior testing canonical correlation analysis gait analysis Gaussian graphical models ischemic stroke magnetic resonance imaging pig model principal component analysis
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Analysis of Eigenvalues for Molecular Structures
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作者 Muhammad Haroon Aftab Kamel Jebreen +1 位作者 Mohammad Issa Sowaity Muhammad Hussain 《Computers, Materials & Continua》 SCIE EI 2022年第10期1225-1236,共12页
In this article,we study different molecular structures such as Polythiophene network,PLY(n)for n=1,2,and 3,Orthosilicate(Nesosilicate)SiO4,Pyrosilicates(Sorosilicates)Si2O7,Chain silicates(Pyroxenes)(SiO3)n,and Cycli... In this article,we study different molecular structures such as Polythiophene network,PLY(n)for n=1,2,and 3,Orthosilicate(Nesosilicate)SiO4,Pyrosilicates(Sorosilicates)Si2O7,Chain silicates(Pyroxenes)(SiO3)n,and Cyclic silicates(Ring Silicates)Si3O9 for their cardinalities,chromatic numbers,graph variations,eigenvalues obtained from the adjacency matrices which are square matrices in order and their corresponding characteristics polynomials.We convert the general structures of these chemical networks in to mathematical graphical structures.We transform the molecular structures of these chemical networks which are mentioned above,into a simple and undirected planar graph and sketch them with various techniques of mathematics.The matrices obtained from these simple undirected graphs are symmetric.We also label the molecular structures by assigning different colors.Their graphs have also been studied for analysis.For a connected graph,the eigenvalue that shows its peak point(largest value)obtained from the adjacency matrix has multiplicity 1.Therefore,the gap between the largest and its smallest eigenvalues is interlinked with some form of“connectivity measurement of the structural graph”.We also note that the chemical structures,Orthosilicate(Nesosilicate)SiO4,Pyrosilicates(Sorosilicates)Si2O7,Chain silicates(Pyroxenes)(SiO3)n,and Cyclic silicates(Ring Silicates)Si3O9 generally have two same eigenvalues.Adjacency matrices have great importance in the field of computer science. 展开更多
关键词 Vertex degree EDGES EIGENVALUES characteristics polynomials adjacency matrices graphical model GENETICS POLYTHIOPHENE SILICATES
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An Approximation for the Entropy Measuring in the General Structure of SGSP_(3)
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作者 Zeeshan Saleem Muftiand Muhammad Hussain Kamel Jebreen +3 位作者 Muhammad Haroon Aftab Mohammad Issa Sowaity Zeeshan Saleem Mufti Muhammad Hussain 《Computers, Materials & Continua》 SCIE EI 2022年第12期4455-4463,共9页
In this article,we calculate various topological invariants such as symmetric division degree index,redefined Zagreb index,VL index,first and second exponential Zagreb index,first and second multiplicative exponential... In this article,we calculate various topological invariants such as symmetric division degree index,redefined Zagreb index,VL index,first and second exponential Zagreb index,first and second multiplicative exponential Zagreb indices,symmetric division degree entropy,redefined Zagreb entropy,VL entropy,first and second exponential Zagreb entropies,multiplicative exponential Zagreb entropy.We take the chemical compound named Proanthocyanidins,which is a very useful polyphenol in human’s diet.They are very beneficial for one’s health.These chemical compounds are extracted from grape seeds.They are tremendously anti-inflammatory.A subdivision formof this compound is presented in this article.The compound named subdivided grape seed Proanthocyanidins is abbreviated as SGSP_(3).This network SGSP_(3),is converted and modeled into its mathematical graphical formation with the support of the latest mathematical tools.We have also developed many closed formulas for the measurement of entropy for the general chemical structure of the subdivided grape seed Proanthocyanidins network.The achieved outcomes can be correlated with the chemical version of SGSP_(3) to get a better understanding of its biological as well as physical features. 展开更多
关键词 Symmetric division degree redefined Zagreb VL index EXPONENTIAL multiplicative Zagreb subdivided grape seed Proanthocyanidins graphical model GENETICS ENTROPY
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Graphical model construction based on evolutionary algorithms
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作者 Youlong YANG Yan WU Sanyang LIU 《控制理论与应用(英文版)》 EI 2006年第4期349-354,共6页
Using Bayesian networks to model promising solutions from the current population of the evolutionary algorithms can ensure efficiency and intelligence search for the optimum. However, to construct a Bayesian network t... Using Bayesian networks to model promising solutions from the current population of the evolutionary algorithms can ensure efficiency and intelligence search for the optimum. However, to construct a Bayesian network that fits a given dataset is a NP-hard problem, and it also needs consuming mass computational resources. This paper develops a methodology for constructing a graphical model based on Bayesian Dirichlet metric. Our approach is derived from a set of propositions and theorems by researching the local metric relationship of networks matching dataset. This paper presents the algorithm to construct a tree model from a set of potential solutions using above approach. This method is important not only for evolutionary algorithms based on graphical models, but also for machine learning and data mining. The experimental results show that the exact theoretical results and the approximations match very well. 展开更多
关键词 Graphical model Evolutionary algorithms Bayesian network Tree models Bayesian Dirichlet metric
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Unsupervised Graph-Based Tibetan Multi-Document Summarization
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作者 Xiaodong Yan Yiqin Wang +3 位作者 Wei Song Xiaobing Zhao A.Run Yang Yanxing 《Computers, Materials & Continua》 SCIE EI 2022年第10期1769-1781,共13页
Text summarization creates subset that represents the most important or relevant information in the original content,which effectively reduce information redundancy.Recently neural network method has achieved good res... Text summarization creates subset that represents the most important or relevant information in the original content,which effectively reduce information redundancy.Recently neural network method has achieved good results in the task of text summarization both in Chinese and English,but the research of text summarization in low-resource languages is still in the exploratory stage,especially in Tibetan.What’s more,there is no large-scale annotated corpus for text summarization.The lack of dataset severely limits the development of low-resource text summarization.In this case,unsupervised learning approaches are more appealing in low-resource languages as they do not require labeled data.In this paper,we propose an unsupervised graph-based Tibetan multi-document summarization method,which divides a large number of Tibetan news documents into topics and extracts the summarization of each topic.Summarization obtained by using traditional graph-based methods have high redundancy and the division of documents topics are not detailed enough.In terms of topic division,we adopt two level clustering methods converting original document into document-level and sentence-level graph,next we take both linguistic and deep representation into account and integrate external corpus into graph to obtain the sentence semantic clustering.Improve the shortcomings of the traditional K-Means clustering method and perform more detailed clustering of documents.Then model sentence clusters into graphs,finally remeasure sentence nodes based on the topic semantic information and the impact of topic features on sentences,higher topic relevance summary is extracted.In order to promote the development of Tibetan text summarization,and to meet the needs of relevant researchers for high-quality Tibetan text summarization datasets,this paper manually constructs a Tibetan summarization dataset and carries out relevant experiments.The experiment results show that our method can effectively improve the quality of summarization and our method is competitive to previous unsupervised methods. 展开更多
关键词 Multi-document summarization text clustering topic feature fusion graphic model
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VIDEO MULTI-TARGET TRACKING BASED ON PROBABILISTIC GRAPHICAL MODEL
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作者 Xu Feng Huang Chenrong +1 位作者 Wu Zhengjun Xu Lizhong 《Journal of Electronics(China)》 2011年第4期548-557,共10页
In the technique of video multi-target tracking,the common particle filter can not deal well with uncertain relations among multiple targets.To solve this problem,many researchers use data association method to reduce... In the technique of video multi-target tracking,the common particle filter can not deal well with uncertain relations among multiple targets.To solve this problem,many researchers use data association method to reduce the multi-target uncertainty.However,the traditional data association method is difficult to track accurately when the target is occluded.To remove the occlusion in the video,combined with the theory of data association,this paper adopts the probabilistic graphical model for multi-target modeling and analysis of the targets relationship in the particle filter framework.Ex-perimental results show that the proposed algorithm can solve the occlusion problem better compared with the traditional algorithm. 展开更多
关键词 Video tracking Multi-target tracking Data association Probabilistic graphical model Particle filter
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Systemic Risk of Conventional and Islamic Banks: Comparison with Graphical Network Models
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作者 Shatha Qamhieh Hashem Paolo Giudici 《Applied Mathematics》 2016年第17期2079-2096,共19页
The main aim of this paper is to compare the stability, in terms of systemic risk, of conventional and Islamic banking systems. To this aim, we propose correlation network models for stock market returns based on grap... The main aim of this paper is to compare the stability, in terms of systemic risk, of conventional and Islamic banking systems. To this aim, we propose correlation network models for stock market returns based on graphical Gaussian distributions, which allows us to capture the contagion effects that move along countries. We also consider Bayesian graphical models, to account for model uncertainty in the measurement of financial systems interconnectedness. Our proposed model is applied to the Middle East and North Africa (MENA) region banking sector, characterized by the presence of both conventional and Islamic banks, for the period from 2007 to the beginning of 2014. Our empirical findings show that there are differences in the systemic risk and stability of the two banking systems during crisis times. In addition, the differences are subject to country specific effects that are amplified during crisis period. 展开更多
关键词 Financial Stability Centrality Measures Graphical Gaussian Models Islamic Banks Conventional Banks Systemic Risk
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A Modeling and Probabilistic Reasoning Method of Dynamic Uncertain Causality Graph for Industrial Fault Diagnosis 被引量:1
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作者 Chun-Ling Dong Qin Zhang Shi-Chao Geng 《International Journal of Automation and computing》 EI CSCD 2014年第3期288-298,共11页
Online automatic fault diagnosis in industrial systems is essential for guaranteeing safe, reliable and efficient operations.However, difficulties associated with computational overload, ubiquitous uncertainties and i... Online automatic fault diagnosis in industrial systems is essential for guaranteeing safe, reliable and efficient operations.However, difficulties associated with computational overload, ubiquitous uncertainties and insufficient fault samples hamper the engineering application of intelligent fault diagnosis technology. Geared towards the settlement of these problems, this paper introduces the method of dynamic uncertain causality graph, which is a new attempt to model complex behaviors of real-world systems under uncertainties. The visual representation to causality pathways and self-relied "chaining" inference mechanisms are analyzed. In particular, some solutions are investigated for the diagnostic reasoning algorithm to aim at reducing its computational complexity and improving the robustness to potential losses and imprecisions in observations. To evaluate the effectiveness and performance of this method, experiments are conducted using both synthetic calculation cases and generator faults of a nuclear power plant. The results manifest the high diagnostic accuracy and efficiency, suggesting its practical significance in large-scale industrial applications. 展开更多
关键词 Fault diagnosis causality model probabilistic graphical model uncertain knowledge representation weighted logic inference.
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Hand Interface in Traditional Modeling and Animation Tasks
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作者 孙汉秋 《Journal of Computer Science & Technology》 SCIE EI CSCD 1996年第3期286-295,共10页
3-D task space in modeling and animation is usually reduced to the separate control dimensions supported by conventional interactive devices. This limitation maps only patial view of the problem to the device space at... 3-D task space in modeling and animation is usually reduced to the separate control dimensions supported by conventional interactive devices. This limitation maps only patial view of the problem to the device space at a time, and results in tedious and un natural interface of control. This paper uses the DataGlove interface for modeling and animating scene behaviors. The modeling interface selects, scales, rotates, translates,copies and deletes the instances of the prindtives. These basic modeling processes are directly performed in the task spacet using hand shapes and motions. Hand shapes are recoginzed as discrete states that trigger the commands, and hand motion are mapped to the movement of a selected instance. The interactions through hand interface place the user as a participant in the process of behavior simulation. Both event triggering and role switching of hand are experimented in simulation. The event mode of hand triggers control signals or commands through a menu interface. The object mode of hand simulates itself as an object whose appearance or motion inlluences the motions of other objects in scene. The involvement of hand creates a diversity of dyndric situations for testing variable scene behaviors. Our experiments have shown the potential use of this interface directly in the 3-D modeling and animation task space. 展开更多
关键词 Interactive graphics scene modeling behavior simulation DataGlove virtual reality
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Support Recovery of Gaussian Graphical Model with False Discovery Rate Control
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作者 ZHANG Yuhao LIU Yanhong WANG Zhaojun 《Journal of Systems Science & Complexity》 SCIE EI CSCD 2023年第6期2605-2623,共19页
This paper focuses on the support recovery of the Gaussian graphical model(GGM)with false discovery rate(FDR)control.The graceful symmetrized data aggregation(SDA)technique which involves sample splitting,data screeni... This paper focuses on the support recovery of the Gaussian graphical model(GGM)with false discovery rate(FDR)control.The graceful symmetrized data aggregation(SDA)technique which involves sample splitting,data screening and information pooling is exploited via a node-based way.A matrix of test statistics with symmetry property is constructed and a data-driven threshold is chosen to control the FDR for the support recovery of GGM.The proposed method is shown to control the FDR asymptotically under some mild conditions.Extensive simulation studies and a real-data example demonstrate that it yields a better FDR control while offering reasonable power in most cases. 展开更多
关键词 False discovery rate Gaussian graphical model support recovery symmetrized data aggregation
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A Probabilistic Framework for Temporal Cognitive Diagnosis in Online Learning Systems
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作者 刘嘉聿 汪飞 +4 位作者 马海平 黄振亚 刘淇 陈恩红 苏喻 《Journal of Computer Science & Technology》 SCIE EI CSCD 2023年第6期1203-1222,共20页
Cognitive diagnosis is an important issue of intelligent education systems,which aims to estimate students'proficiency on specific knowledge concepts.Most existing studies rely on the assumption of static student ... Cognitive diagnosis is an important issue of intelligent education systems,which aims to estimate students'proficiency on specific knowledge concepts.Most existing studies rely on the assumption of static student states and ig-nore the dynamics of proficiency in the learning process,which makes them unsuitable for online learning scenarios.In this paper,we propose a unified temporal item response theory(UTIRT)framework,incorporating temporality and random-ness of proficiency evolving to get both accurate and interpretable diagnosis results.Specifically,we hypothesize that stu-dents'proficiency varies as a Wiener process and describe a probabilistic graphical model in UTIRT to consider temporali-ty and randomness factors.Furthermore,based on the relationship between student states and exercising answers,we hy-pothesize that the answering result at time k contributes most to inferring a student's proficiency at time k,which also re-flects the temporality aspect and enables us to get analytical maximization(M-step)in the expectation maximization(EM)algorithm when estimating model parameters.Our UTIRT is a framework containing unified training and inferenc-ing methods,and is general to cover several typical traditional models such as Item Response Theory(IRT),multidimen-sional IRT(MIRT),and temporal IRT(TIRT).Extensive experimental results on real-world datasets show the effective-ness of UTIRT and prove its superiority in leveraging temporality theoretically and practically over TIRT. 展开更多
关键词 cognitive diagnosis probabilistic graphical model item response theory(IRT) stochastic process expectation maximization(EM)algorithm
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Decoding transcriptional regulation via a human gene expression predictor
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作者 Yuzhou Wang Yu Zhang +5 位作者 Ning Yu Bingyan Li Jiazhen Gong Yide Mei Jianqiang Bao Shisong Ma 《Journal of Genetics and Genomics》 SCIE CAS CSCD 2023年第5期305-317,共13页
Transcription factors(TFs)regulate cellular activities by controlling gene expression,but a predictive model describing how TFs quantitatively modulate human transcriptomes is lacking.We construct a universal human ge... Transcription factors(TFs)regulate cellular activities by controlling gene expression,but a predictive model describing how TFs quantitatively modulate human transcriptomes is lacking.We construct a universal human gene expression predictor named EXPLICIT-Human and utilize it to decode transcriptional regulation.Using the expression of 1613 TFs,the predictor reconstitutes highly accurate transcriptomes for samples derived from a wide range of tissues and conditions.The broad applicability of the predictor indicates that it recapitulates the quantitative relationships between TFs and target genes ubiquitous across tissues.Significant interacting TF-target gene pairs are extracted from the predictor and enable downstream inference of TF regulators for diverse pathways involved in development,immunity,metabolism,and stress response.A detailed analysis of the hematopoiesis process reveals an atlas of key TFs regulating the development of different hematopoietic cell lineages,and a portion of these TFs are conserved between humans and mice.The results demonstrate that our method is capable of delineating the TFs responsible for fate determination.Compared to other existing tools,EXPLICIT-Human shows a better performance in recovering the correct TF regulators. 展开更多
关键词 Gene expression predictor Gene regulatory network Graphical Gaussian model Gene module Human MOUSE
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Compression schemes for concept classes induced by three types of discrete undirected graphical models
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作者 Tingting Luo Benchong Li 《Statistical Theory and Related Fields》 CSCD 2023年第4期287-295,共9页
Sample compression schemes were first proposed by Littlestone and Warmuth in 1986.Undi-rected graphical model is a powerful tool for classification in statistical learning.In this paper,we consider labelled compressio... Sample compression schemes were first proposed by Littlestone and Warmuth in 1986.Undi-rected graphical model is a powerful tool for classification in statistical learning.In this paper,we consider labelled compression schemes for concept classes induced by discrete undirected graphical models.For the undirected graph of two vertices with no edge,where one vertex takes two values and the other vertex can take any finite number of values,we propose an algorithm to establish a labelled compression scheme of size VC dimension of associated concept class.Further,we extend the result to other two types of undirected graphical models and show the existence of labelled compression schemes of size VC dimension for induced concept classes.The work of this paper makes a step forward in solving sample compression problem for concept class induced by a general discrete undirected graphical model. 展开更多
关键词 Discrete undirected graphical models concept classes VC dimension sample compression schemes
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