Information on Land Use and Land Cover Map(LULCM)is essential for environment and socioeconomic applications.Such maps are generally derived from Multispectral Remote Sensing Images(MRSI)via classification.The classif...Information on Land Use and Land Cover Map(LULCM)is essential for environment and socioeconomic applications.Such maps are generally derived from Multispectral Remote Sensing Images(MRSI)via classification.The classification process can be described as information flow from images to maps through a trained classifier.Characterizing the information flow is essential for understanding the classification mechanism,providing solutions that address such theoretical issues as“what is the maximum number of classes that can be classified from a given MRSI?”and“how much information gain can be obtained?”Consequently,two interesting questions naturally arise,i.e.(i)How can we characterize the information flow?and(ii)What is the mathematical form of the information flow?To answer these two questions,this study first hypothesizes that thermodynamic entropy is the appropriate measure of information for both MRSI and LULCM.This hypothesis is then supported by kinetic-theory-based experiments.Thereafter,upon such an entropy,a generalized Jarzynski equation is formulated to mathematically model the information flow,which contains such parameters as thermodynamic entropy of MRSI,thermodynamic entropy of LULCM,weighted F1-score(classification accuracy),and total number of classes.This generalized Jarzynski equation has been successfully validated by hypothesis-driven experiments where 694 Sentinel-2 images are classified into 10 classes by four classical classifiers.This study provides a way for linking thermodynamic laws and concepts to the characterization and understanding of information flow in land cover classification,opening a new door for constructing domain knowledge.展开更多
The management of information flow for production improvement has always been a target in the research. In this paper, the focus is on the analysis model of the characteristics of information flow in shop floor operat...The management of information flow for production improvement has always been a target in the research. In this paper, the focus is on the analysis model of the characteristics of information flow in shop floor operations based on the influence that dimension (support or medium), direction and the quality information flow have on the value of information flow using machine learning classification algorithms. The obtained results of classification algorithms used to analyze the value of information flow are Decision Trees (DT) and Random Forest (RF) with a score of 0.99% and the mean absolute error of 0.005. The results also show that the management of information flow using DT or RF shows that, the dimension of information such as digital information has the greatest value of information flow in shop floor operations when the shop floor is totally digitalized. Direction of information flow does not have any great influence on shop floor operations processes when the operations processes are digitalized or done by operators as machines.展开更多
Accelerate processor, efficient software and pervasive connections provide sensor nodes with more powerful computation and storage ability, which can offer various services to user. Based on these atomic services, dif...Accelerate processor, efficient software and pervasive connections provide sensor nodes with more powerful computation and storage ability, which can offer various services to user. Based on these atomic services, different sensor nodes can cooperate and compose with each other to complete more complicated tasks for user. However, because of the regional characteristic of sensor nodes, merging data with different sensitivities become a primary requirement to the composite services, and information flow security should be intensively considered during service composition. In order to mitigate the great cost caused by the complexity of modeling and the heavy load of single-node verification to the energy-limited sensor node, in this paper, we propose a new distributed verification framework to enforce information flow security on composite services of smart sensor network. We analyze the information flows in composite services and specify security constraints for each service participant. Then we propose an algorithm over the distributed verification framework involving each sensor node to participate in the composite service verification based on the security constraints. The experimental results indicate that our approach can reduce the cost of verification and provide a better load balance.展开更多
Cloud computing provides services to users through Internet.This open mode not only facilitates the access by users,but also brings potential security risks.In cloud computing,the risk of data leakage exists between u...Cloud computing provides services to users through Internet.This open mode not only facilitates the access by users,but also brings potential security risks.In cloud computing,the risk of data leakage exists between users and virtual machines.Whether direct or indirect data leakage,it can be regarded as illegal information flow.Methods,such as access control models can control the information flow,but not the covert information flow.Therefore,it needs to use the noninterference models to detect the existence of illegal information flow in cloud computing architecture.Typical noninterference models are not suitable to certificate information flow in cloud computing architecture.In this paper,we propose several information flow models for cloud architecture.One model is for transitive cloud computing architecture.The others are for intransitive cloud computing architecture.When concurrent access actions execute in the cloud architecture,we want that security domain and security domain do not affect each other,that there is no information flow between security domains.But in fact,there will be more or less indirect information flow between security domains.Our models are concerned with how much information is allowed to flow.For example,in the CIP model,the other domain can learn the sequence of actions.But in the CTA model,the other domain can’t learn the information.Which security model will be used in an architecture depends on the security requirements for that architecture.展开更多
Based on Bayesian network (BN) and information flow (IF),a new machine learning-based model named IFBN is put forward to interpolate missing time series of multiple ocean variables. An improved BN structural learning ...Based on Bayesian network (BN) and information flow (IF),a new machine learning-based model named IFBN is put forward to interpolate missing time series of multiple ocean variables. An improved BN structural learning algorithm with IF is designed to mine causal relationships among ocean variables to build network structure. Nondirectional inference mechanism of BN is applied to achieve the synchronous interpolation of multiple missing time series. With the IFBN,all ocean variables are placed in a causal network visually,making full use of information about related variables to fill missing data. More importantly,the synchronous interpolation of multiple variables can avoid model retraining when interpolative objects change. Interpolation experiments show that IFBN has even better interpolation accuracy,effectiveness and stability than existing methods.展开更多
Multi-product collaborative development is adopted widely in manufacturing enterprise, while the present multi-project planning models don＇t take techni- cal/data interactions of multiple products into account. To de...Multi-product collaborative development is adopted widely in manufacturing enterprise, while the present multi-project planning models don＇t take techni- cal/data interactions of multiple products into account. To decrease the influence of technical/data interactions on project progresses, the information flow scheduling models based on the extended DSM is presented. Firstly, infor- mation dependencies are divided into four types： series, parallel, coupling and similar. Secondly, different types of dependencies are expressed as DSM units, and the exten- ded DSM model is brought forward, described as a block matrix. Furthermore, the information flow scheduling methods is proposed, which involves four types of opera- tions, where partitioning and clustering algorithm are modified from DSM for ensuring progress of high-priority project, merging and converting is the specific computation of the extended DSM. Finally, the information flow scheduling of two machine tools development is analyzed with example, and different project priorities correspond to different task sequences and total coordination cost. The proposed methodology provides a detailed instruction for information flow scheduling in multi-product development, with specially concerning technical/data interactions.展开更多
The information flow chart within product life cycle is given out based on collaborative production commerce （CPC） thoughts. In this chart, the separated information systems are integrated by means of enterprise kno...The information flow chart within product life cycle is given out based on collaborative production commerce （CPC） thoughts. In this chart, the separated information systems are integrated by means of enterprise knowledge assets that are promoted by CPC from production knowledge. The information flow in R＆D process is analyzed in the environment of virtual R＆D group and distributed PDM. In addition, the information flow throughout the manufacturing and marketing process is analyzed in CPC environment.展开更多
BACKGROUND：Neuro-rehabilitative training has been shown to promote motor function recovery in stroke patients,although the underlying mechanisms have not been fully clarified.OBJECTIVE：To investigate the effects of ...BACKGROUND：Neuro-rehabilitative training has been shown to promote motor function recovery in stroke patients,although the underlying mechanisms have not been fully clarified.OBJECTIVE：To investigate the effects of finger movement training on functional connectivity and information flow direction in cerebral motor areas of healthy people using electroencephalogram （EEG）.DESIGN,TIME AND SETTING：A self-controlled,observational study was performed at the College of Life Science and Bioengineering,Beijing University of Technology between December 2008 and April 2009.PARTICIPANTS：Nineteen healthy adults,who seldom played musical instruments or keyboards,were included in the present study.METHODS：Specific finger movement training was performed,and all subjects were asked to separately press keys with their left or right hand fingers,according to instructions.The task comprised five sessions of test train test train-test.Thirty-six channel EEG signals were recorded in different test sessions prior to and after training.Data were statistically analyzed using one-way analysis of variance.MAIN OUTCOME MEASURES：The number of effective performances,correct ratio,average response time,average movement time,correlation coefficient between pairs of EEG channels,and information flow direction in motor regions were analyzed and compared between different training sessions.RESULTS：Motor function of all subjects was significantly improved in the third test comparedwith the first test （P〈 0.01）.More than 80% of connections were strengthened in the motor-related areas following two training sessions,in particular the primary motor regions under the C4 electrode.Compared to the first test,a greater amount of information flowed from the Cz and Fcz electrodes （corresponding to supplementary motor area） to the C4 electrode in the third test.CONCLUSION：Finger task training increased motor ability in subjects by strengthening connections and changing information flow in the motor areas.These results provided a greater understanding of the mechanisms involved in motor rehabilitation.展开更多
With the spread use of the computers, a new crime space and method are presented for criminals. Thus computer evidence plays a key part in criminal cases. Traditional computer evidence searches require that the comput...With the spread use of the computers, a new crime space and method are presented for criminals. Thus computer evidence plays a key part in criminal cases. Traditional computer evidence searches require that the computer specialists know what is stored in the given computer. Binary-based information flow tracking which concerns the changes of control flow is an effective way to analyze the behavior of a program. The existing systems ignore the modifications of the data flow, which may be also a malicious behavior. Thus the function recognition is introduced to improve the information flow tracking. Function recognition is a helpful technique recognizing the function body from the software binary to analyze the binary code. And that no false positive and no false negative in our experiments strongly proves that our approach is effective.展开更多
Flume, which implements decentralized information flow control （DIFC）, allows a high security level process to ＂pre-create＂ secret files in a low security level directory. However, the pre-create mechanism makes s...Flume, which implements decentralized information flow control （DIFC）, allows a high security level process to ＂pre-create＂ secret files in a low security level directory. However, the pre-create mechanism makes some normal system calls unavailable, and moreover, it needs priori knowledge to create a large quantity of objects, which is difficult to estimate in practical operating systems. In this paper, we present an extended Flume file access control mechanism, named Effect, to substitute the mechanism of pre-create, which permits write operations （create, delete, and rename a file） on directories and creates a file access virtual layer that allocates operational views for each process with noninterference properties. In the end, we further present an analysis on the security of Effect. Our work makes it easier for multi-user to share confidential information in decentralized information flow control systems.展开更多
The characteristics of highway transport and the application of information technology in highway transport service are combined; the information flows＇ promotion and substitution on highway transport are analyzed; a...The characteristics of highway transport and the application of information technology in highway transport service are combined; the information flows＇ promotion and substitution on highway transport are analyzed; and the highway transport development strategy based on information flow impact is proposed.展开更多
Microblog is a new Internet featured product, which has seen a rapid development in recent years. Researchers from different countries are making various technical analyses on microblogging applications. In this study...Microblog is a new Internet featured product, which has seen a rapid development in recent years. Researchers from different countries are making various technical analyses on microblogging applications. In this study, through using the natural language processing(NLP) and data mining, we analyzed the information content transmitted via a microblog, users' social networks and their interactions, and carried out an empirical analysis on the dissemination process of one particular piece of information via Sina Weibo.Based on the result of these analyses, we attempt to develop a better understanding about the rule and mechanism of the informal information flow in microblogging.展开更多
Startups form an information network that reflects their growth trajectories through information flow channels established by shared investors.However,traditional static network metrics overlook temporal dynamics and ...Startups form an information network that reflects their growth trajectories through information flow channels established by shared investors.However,traditional static network metrics overlook temporal dynamics and rely on single indicators to assess startups’roles in predicting future success,failing to comprehensively capture topological variations and structural diversity.To address these limitations,we construct a temporal information network using 14547 investment records from 1013 global blockchain startups between 2004 and 2020,sourced from Crunchbase.We propose two dynamic methods to characterize the information flow:temporal random walk(sTRW)for modeling information flow trajectories and temporal betweenness centrality(tTBET)for identifying key information hubs.These methods enhance walk coverage while ensuring random stability,allowing for more effective identification of influential startups.By integrating sTRW and tTBET,we develop a comprehensive metric to evaluate a startup’s influence within the network.In experiments assessing startups’potential for future success—where successful startups are defined as those that have undergone M&A or IPO—incorporating this metric improves accuracy,recall,and F1 score by 0.035,0.035,and 0.042,respectively.Our findings indicate that information flow from key startups to others diminishes as the network distance increases.Additionally,successful startups generally exhibit higher information inflows than outflows,suggesting that actively seeking investment-related information contributes to startup growth.Our research provides valuable insights for formulating startup development strategies and offers practical guidance for market regulators.展开更多
In view of the imperfect supply chain management of prefabricated building,inadequate information interaction among the participating subjects,and untimely information updates,the integration and development of BIM te...In view of the imperfect supply chain management of prefabricated building,inadequate information interaction among the participating subjects,and untimely information updates,the integration and development of BIM technology plus the supply chain of prefabricated building is analyzed,and the problems existing in the current supply chain and the application of BIM technology at various stages are elaborated.By analyzing the structural composition of the prefabricated building supply chain,an information sharing platform framework for prefabricated building supply chain based on BIM was established,which serves as a valuable reference for managing prefabricated building supply chains.BIM technology aligns well with assembly construction,laying a solid foundation for their synergistic development and offering novel research avenues for the prefabricated building supply chain.展开更多
The Indonesian Throughflow(ITF)plays important roles in global ocean circulation and climate systems.Previous studies suggested the ITF interannual variability is driven by both the El Niño-Southern Oscillation(E...The Indonesian Throughflow(ITF)plays important roles in global ocean circulation and climate systems.Previous studies suggested the ITF interannual variability is driven by both the El Niño-Southern Oscillation(ENSO)and the Indian Ocean Dipole(IOD)events.The detailed processes of ENSO and/or IOD induced anomalies impacting on the ITF,however,are still not clear.In this study,this issue is investigated through causal relation,statistical,and dynamical analyses based on satellite observation.The results show that the driven mechanisms of ENSO on the ITF include two aspects.Firstly,the ENSO related wind field anomalies driven anomalous cyclonic ocean circulation in the western Pacific,and off equatorial upwelling Rossby waves propagating westward to arrive at the western boundary of the Pacific,both tend to induce negative sea surface height anomalies(SSHA)in the western Pacific,favoring ITF reduction since the develop of the El Niño through the following year.Secondly,the ENSO events modulate equatorial Indian Ocean zonal winds through Walker Circulation,which in turn trigger eastward propagating upwelling Kelvin waves and westward propagating downwelling Rossby waves.The Rossby waves are reflected into downwelling Kelvin waves,which then propagate eastward along the equator and the Sumatra-Java coast in the Indian Ocean.As a result,the wave dynamics tend to generate negative(positive)SSHA in the eastern Indian Ocean,and thus enhance(reduce)the ITF transport with time lag of 0-6 months(9-12 months),respectively.Under the IOD condition,the wave dynamics also tend to enhance the ITF in the positive IOD year,and reduce the ITF in the following year.展开更多
Information leak,which can undermine the compliance of web-service-composition business processes for some policies,is one of the major concerns in web service composition.We present an automated and effective approac...Information leak,which can undermine the compliance of web-service-composition business processes for some policies,is one of the major concerns in web service composition.We present an automated and effective approach for the detection of implicit information leaks in business process execution language(BPEL)based on information flow analysis.We introduce an adequate meta-model for BPEL representation based on a Petri net for transformation and analysis.Building on the concept of Petri net place-based noninterference,the core contribution of this paper is the application of a Petri net reachability graph to estimate Petri net interference and thereby to detect implicit information leaks in web service composition.In addition,a case study illustrates the application of the approach on a concrete workflow in BPEL notation.展开更多
Information Flow Tracking(IFT)is an established formal method for proving security properties related to confidentiality,integrity,and isolation.It has seen promise in identifying security vulnerabilities resulting fr...Information Flow Tracking(IFT)is an established formal method for proving security properties related to confidentiality,integrity,and isolation.It has seen promise in identifying security vulnerabilities resulting from design flaws,timing channels,and hardware Trojans for secure hardware design.However,existing IFT methods tend to take a qualitative approach and only enforce binary security properties,requiring strict non-interference for the properties to hold while real systems usually allow a small amount of information flows to enable desirable interactions.Consequently,existing methods are inadequate for reasoning about quantitative security properties or measuring the security of a design in order to assess the severity of a security vulnerability.In this work,we propose two multi-flow solutions—multiple verifications for replicating existing IFT model and multi-flow IFT method.The proposed multi-flow IFT method provides more insight into simultaneous information flow behaviors and allows for proof of quantitative information flow security properties,such as diffusion,randomization,and boundaries on the amount of simultaneous information flows.Experimental results show that our method can be used to prove a new type of information flow security property with verification performance benefits.展开更多
This study examines whether the number of forward patent citations(along with alternative patent data)dwhen used as a proxy for the mixing variabledcould infer the aggregate amount of economic-innovation information a...This study examines whether the number of forward patent citations(along with alternative patent data)dwhen used as a proxy for the mixing variabledcould infer the aggregate amount of economic-innovation information arriving at the New York Stock Exchange(NYSE)in the United States.The results show that the number of forward patent citations,when used as a mixing variable,fails to eliminate total volatility persistence in the conditional variance equation of the exponential generalized autoregressive conditional heteroscedastic(EGARCH)model.However,the trading volume successfully eliminates total volatility persistence,thus confirming the validity of the framework used.When the volatility is modeled with an expectation of mean return,the persistence of conditional variance is deterministically increased,and the sum of the volatility coefficients exceeds unity.The inclusion of trading volume with a time trend in the variance equation rectifies the deterministic increase in the conditional volatility.These findings suggest that the form of heteroscedasticity(i.e.,as per the autoregressive conditional heteroscedastic model,ARCH model)in NYSE portfolio returns is based on the type of shocks to volatility(e.g.,deterministic vs.stochastic),which manifests as news arrivals(i.e.,new information arrivals proxied by trading volume)at the stock market.The volume therefore reflects the time dependence in the innovations to the ARCH error generation process.The response of volatility to volume persists over time when the volatility estimates are derived from the EGARCH model with an expectation for the mean of return.Backward patent citations,patent applications,and patents issued have been found to interact somewhat with trading volume,suggesting that each of these variables could play the role of an absorptive capacity variable as the new information flow associated with economic innovation(i.e.,flow of firms’stock of new knowledge)could be picked up by the trading volume.展开更多
How can we approach the truth in a society？ It may depend on various factors. In this paper, using a well-established truth seeking model, the authors show that the persistent free information flow will bring us to t...How can we approach the truth in a society？ It may depend on various factors. In this paper, using a well-established truth seeking model, the authors show that the persistent free information flow will bring us to the truth. Here the free information flow is modeled as the environmental random noise that could alter one＇s cognition. Without the random noise, the model predicts that the truth can only be captured by the truth seekers who own actively perceptive ability of the truth and their believers, while the other individuals may stick to falsehood. But under the influence of the random noise, the authors strictly prove that even there is only one truth seeker in the group, all individuals will finally approach the truth.展开更多
After a composite service is deployed, user privacy requirements and trust levels of component services are subject to variation. When the changes occur, it is critical to preserve privacy information flow security. W...After a composite service is deployed, user privacy requirements and trust levels of component services are subject to variation. When the changes occur, it is critical to preserve privacy information flow security. We propose an approach to preserve privacy information flow security in composite service evolution. First, a privacy data item dependency analysis method based on a Petri net model is presented. Then the set of privacy data items collected by each component service is derived through a privacy data item dependency graph, and the security scope of each component service is calculated. Finally, the evolution operations that preserve privacy information flow security are defined. By applying these evolution operations, the re-verification process is avoided and the evolution efficiency is improved. To illustrate the effectiveness of our approach, a case study is presented. The experimental results indicate that our approach has high evolution efficiency and can greatly reduce the cost of evolution compared with re-verifying the entire composite service.展开更多
基金supported by the National Natural Science Foundation of China[grant number 41930104]by the Research Grants Council of Hong Kong[grant number PolyU 152219/18E].
文摘Information on Land Use and Land Cover Map(LULCM)is essential for environment and socioeconomic applications.Such maps are generally derived from Multispectral Remote Sensing Images(MRSI)via classification.The classification process can be described as information flow from images to maps through a trained classifier.Characterizing the information flow is essential for understanding the classification mechanism,providing solutions that address such theoretical issues as“what is the maximum number of classes that can be classified from a given MRSI?”and“how much information gain can be obtained?”Consequently,two interesting questions naturally arise,i.e.(i)How can we characterize the information flow?and(ii)What is the mathematical form of the information flow?To answer these two questions,this study first hypothesizes that thermodynamic entropy is the appropriate measure of information for both MRSI and LULCM.This hypothesis is then supported by kinetic-theory-based experiments.Thereafter,upon such an entropy,a generalized Jarzynski equation is formulated to mathematically model the information flow,which contains such parameters as thermodynamic entropy of MRSI,thermodynamic entropy of LULCM,weighted F1-score(classification accuracy),and total number of classes.This generalized Jarzynski equation has been successfully validated by hypothesis-driven experiments where 694 Sentinel-2 images are classified into 10 classes by four classical classifiers.This study provides a way for linking thermodynamic laws and concepts to the characterization and understanding of information flow in land cover classification,opening a new door for constructing domain knowledge.
文摘The management of information flow for production improvement has always been a target in the research. In this paper, the focus is on the analysis model of the characteristics of information flow in shop floor operations based on the influence that dimension (support or medium), direction and the quality information flow have on the value of information flow using machine learning classification algorithms. The obtained results of classification algorithms used to analyze the value of information flow are Decision Trees (DT) and Random Forest (RF) with a score of 0.99% and the mean absolute error of 0.005. The results also show that the management of information flow using DT or RF shows that, the dimension of information such as digital information has the greatest value of information flow in shop floor operations when the shop floor is totally digitalized. Direction of information flow does not have any great influence on shop floor operations processes when the operations processes are digitalized or done by operators as machines.
基金supported in part by National Natural Science Foundation of China(61502368,61303033,U1135002 and U1405255)the National High Technology Research and Development Program(863 Program)of China(No.2015AA017203)+1 种基金the Fundamental Research Funds for the Central Universities(XJS14072,JB150308)the Aviation Science Foundation of China(No.2013ZC31003,20141931001)
文摘Accelerate processor, efficient software and pervasive connections provide sensor nodes with more powerful computation and storage ability, which can offer various services to user. Based on these atomic services, different sensor nodes can cooperate and compose with each other to complete more complicated tasks for user. However, because of the regional characteristic of sensor nodes, merging data with different sensitivities become a primary requirement to the composite services, and information flow security should be intensively considered during service composition. In order to mitigate the great cost caused by the complexity of modeling and the heavy load of single-node verification to the energy-limited sensor node, in this paper, we propose a new distributed verification framework to enforce information flow security on composite services of smart sensor network. We analyze the information flows in composite services and specify security constraints for each service participant. Then we propose an algorithm over the distributed verification framework involving each sensor node to participate in the composite service verification based on the security constraints. The experimental results indicate that our approach can reduce the cost of verification and provide a better load balance.
基金Natural Science Research Project of Jiangsu Province Universities and Colleges(No.17KJD520005,Congdong Lv).
文摘Cloud computing provides services to users through Internet.This open mode not only facilitates the access by users,but also brings potential security risks.In cloud computing,the risk of data leakage exists between users and virtual machines.Whether direct or indirect data leakage,it can be regarded as illegal information flow.Methods,such as access control models can control the information flow,but not the covert information flow.Therefore,it needs to use the noninterference models to detect the existence of illegal information flow in cloud computing architecture.Typical noninterference models are not suitable to certificate information flow in cloud computing architecture.In this paper,we propose several information flow models for cloud architecture.One model is for transitive cloud computing architecture.The others are for intransitive cloud computing architecture.When concurrent access actions execute in the cloud architecture,we want that security domain and security domain do not affect each other,that there is no information flow between security domains.But in fact,there will be more or less indirect information flow between security domains.Our models are concerned with how much information is allowed to flow.For example,in the CIP model,the other domain can learn the sequence of actions.But in the CTA model,the other domain can’t learn the information.Which security model will be used in an architecture depends on the security requirements for that architecture.
基金The National Natural Science Foundation of China under contract Nos 41875061 and 41976188the“Double First-Class”Research Program of National University of Defense Technology under contract No.xslw05.
文摘Based on Bayesian network (BN) and information flow (IF),a new machine learning-based model named IFBN is put forward to interpolate missing time series of multiple ocean variables. An improved BN structural learning algorithm with IF is designed to mine causal relationships among ocean variables to build network structure. Nondirectional inference mechanism of BN is applied to achieve the synchronous interpolation of multiple missing time series. With the IFBN,all ocean variables are placed in a causal network visually,making full use of information about related variables to fill missing data. More importantly,the synchronous interpolation of multiple variables can avoid model retraining when interpolative objects change. Interpolation experiments show that IFBN has even better interpolation accuracy,effectiveness and stability than existing methods.
基金Supported by National Natural Science Foundation of China(Grant Nos.51475077,51005038)Science and Technology Foundation of Liaoning China(Grant Nos.201301002,2014028012)
文摘Multi-product collaborative development is adopted widely in manufacturing enterprise, while the present multi-project planning models don＇t take techni- cal/data interactions of multiple products into account. To decrease the influence of technical/data interactions on project progresses, the information flow scheduling models based on the extended DSM is presented. Firstly, infor- mation dependencies are divided into four types： series, parallel, coupling and similar. Secondly, different types of dependencies are expressed as DSM units, and the exten- ded DSM model is brought forward, described as a block matrix. Furthermore, the information flow scheduling methods is proposed, which involves four types of opera- tions, where partitioning and clustering algorithm are modified from DSM for ensuring progress of high-priority project, merging and converting is the specific computation of the extended DSM. Finally, the information flow scheduling of two machine tools development is analyzed with example, and different project priorities correspond to different task sequences and total coordination cost. The proposed methodology provides a detailed instruction for information flow scheduling in multi-product development, with specially concerning technical/data interactions.
文摘The information flow chart within product life cycle is given out based on collaborative production commerce （CPC） thoughts. In this chart, the separated information systems are integrated by means of enterprise knowledge assets that are promoted by CPC from production knowledge. The information flow in R＆D process is analyzed in the environment of virtual R＆D group and distributed PDM. In addition, the information flow throughout the manufacturing and marketing process is analyzed in CPC environment.
基金the National Natural Science Foundation of China,No. 30670543
文摘BACKGROUND：Neuro-rehabilitative training has been shown to promote motor function recovery in stroke patients,although the underlying mechanisms have not been fully clarified.OBJECTIVE：To investigate the effects of finger movement training on functional connectivity and information flow direction in cerebral motor areas of healthy people using electroencephalogram （EEG）.DESIGN,TIME AND SETTING：A self-controlled,observational study was performed at the College of Life Science and Bioengineering,Beijing University of Technology between December 2008 and April 2009.PARTICIPANTS：Nineteen healthy adults,who seldom played musical instruments or keyboards,were included in the present study.METHODS：Specific finger movement training was performed,and all subjects were asked to separately press keys with their left or right hand fingers,according to instructions.The task comprised five sessions of test train test train-test.Thirty-six channel EEG signals were recorded in different test sessions prior to and after training.Data were statistically analyzed using one-way analysis of variance.MAIN OUTCOME MEASURES：The number of effective performances,correct ratio,average response time,average movement time,correlation coefficient between pairs of EEG channels,and information flow direction in motor regions were analyzed and compared between different training sessions.RESULTS：Motor function of all subjects was significantly improved in the third test comparedwith the first test （P〈 0.01）.More than 80% of connections were strengthened in the motor-related areas following two training sessions,in particular the primary motor regions under the C4 electrode.Compared to the first test,a greater amount of information flowed from the Cz and Fcz electrodes （corresponding to supplementary motor area） to the C4 electrode in the third test.CONCLUSION：Finger task training increased motor ability in subjects by strengthening connections and changing information flow in the motor areas.These results provided a greater understanding of the mechanisms involved in motor rehabilitation.
基金This work is supported by National Natural Science Foundation of China （Grant No.60773093, 60873209, and 60970107）, the Key Program for Basic Research of Shanghai （Grant No. 09JC1407900, 09510701600, 10511500100）, IBM SUR Funding and IBM Research-China JP Funding, and Key Lab of Information Network Security, Ministry of Public Security.
文摘With the spread use of the computers, a new crime space and method are presented for criminals. Thus computer evidence plays a key part in criminal cases. Traditional computer evidence searches require that the computer specialists know what is stored in the given computer. Binary-based information flow tracking which concerns the changes of control flow is an effective way to analyze the behavior of a program. The existing systems ignore the modifications of the data flow, which may be also a malicious behavior. Thus the function recognition is introduced to improve the information flow tracking. Function recognition is a helpful technique recognizing the function body from the software binary to analyze the binary code. And that no false positive and no false negative in our experiments strongly proves that our approach is effective.
基金Supported by the National Natural Science Foundation of China(61003268,61103220,91118003,61173138,61170022)Hubei Provincial Natural Science Foundation(2010CDB08601)The Fundamental ResearchFunds for the Central Universities (3101038,274629)
文摘Flume, which implements decentralized information flow control （DIFC）, allows a high security level process to ＂pre-create＂ secret files in a low security level directory. However, the pre-create mechanism makes some normal system calls unavailable, and moreover, it needs priori knowledge to create a large quantity of objects, which is difficult to estimate in practical operating systems. In this paper, we present an extended Flume file access control mechanism, named Effect, to substitute the mechanism of pre-create, which permits write operations （create, delete, and rename a file） on directories and creates a file access virtual layer that allocates operational views for each process with noninterference properties. In the end, we further present an analysis on the security of Effect. Our work makes it easier for multi-user to share confidential information in decentralized information flow control systems.
文摘The characteristics of highway transport and the application of information technology in highway transport service are combined; the information flows＇ promotion and substitution on highway transport are analyzed; and the highway transport development strategy based on information flow impact is proposed.
文摘Microblog is a new Internet featured product, which has seen a rapid development in recent years. Researchers from different countries are making various technical analyses on microblogging applications. In this study, through using the natural language processing(NLP) and data mining, we analyzed the information content transmitted via a microblog, users' social networks and their interactions, and carried out an empirical analysis on the dissemination process of one particular piece of information via Sina Weibo.Based on the result of these analyses, we attempt to develop a better understanding about the rule and mechanism of the informal information flow in microblogging.
基金the funding from the National Natural Science Foundation of China(Grant Nos.42001236,71991481,and 71991480)Young Elite Scientist Sponsor-ship Program by Bast(Grant No.BYESS2023413)。
文摘Startups form an information network that reflects their growth trajectories through information flow channels established by shared investors.However,traditional static network metrics overlook temporal dynamics and rely on single indicators to assess startups’roles in predicting future success,failing to comprehensively capture topological variations and structural diversity.To address these limitations,we construct a temporal information network using 14547 investment records from 1013 global blockchain startups between 2004 and 2020,sourced from Crunchbase.We propose two dynamic methods to characterize the information flow:temporal random walk(sTRW)for modeling information flow trajectories and temporal betweenness centrality(tTBET)for identifying key information hubs.These methods enhance walk coverage while ensuring random stability,allowing for more effective identification of influential startups.By integrating sTRW and tTBET,we develop a comprehensive metric to evaluate a startup’s influence within the network.In experiments assessing startups’potential for future success—where successful startups are defined as those that have undergone M&A or IPO—incorporating this metric improves accuracy,recall,and F1 score by 0.035,0.035,and 0.042,respectively.Our findings indicate that information flow from key startups to others diminishes as the network distance increases.Additionally,successful startups generally exhibit higher information inflows than outflows,suggesting that actively seeking investment-related information contributes to startup growth.Our research provides valuable insights for formulating startup development strategies and offers practical guidance for market regulators.
基金“Education Department of Hebei Funding Project for Cultivating the Innovative Capabilities of Graduate Students”(Project No.:XJCX202510)。
文摘In view of the imperfect supply chain management of prefabricated building,inadequate information interaction among the participating subjects,and untimely information updates,the integration and development of BIM technology plus the supply chain of prefabricated building is analyzed,and the problems existing in the current supply chain and the application of BIM technology at various stages are elaborated.By analyzing the structural composition of the prefabricated building supply chain,an information sharing platform framework for prefabricated building supply chain based on BIM was established,which serves as a valuable reference for managing prefabricated building supply chains.BIM technology aligns well with assembly construction,laying a solid foundation for their synergistic development and offering novel research avenues for the prefabricated building supply chain.
基金The Fund of Laoshan Laboratory under contract No.LSKJ202202700the Basic Scientific Fund for National Public Research Institutes of China under contract No.2024Q02+1 种基金the National Natural Science Foundation of China under contract Nos 42076023 and 42430402the Global Change and Air-Sea InteractionⅡProject under contract No.GASI-01-ATP-STwin.
文摘The Indonesian Throughflow(ITF)plays important roles in global ocean circulation and climate systems.Previous studies suggested the ITF interannual variability is driven by both the El Niño-Southern Oscillation(ENSO)and the Indian Ocean Dipole(IOD)events.The detailed processes of ENSO and/or IOD induced anomalies impacting on the ITF,however,are still not clear.In this study,this issue is investigated through causal relation,statistical,and dynamical analyses based on satellite observation.The results show that the driven mechanisms of ENSO on the ITF include two aspects.Firstly,the ENSO related wind field anomalies driven anomalous cyclonic ocean circulation in the western Pacific,and off equatorial upwelling Rossby waves propagating westward to arrive at the western boundary of the Pacific,both tend to induce negative sea surface height anomalies(SSHA)in the western Pacific,favoring ITF reduction since the develop of the El Niño through the following year.Secondly,the ENSO events modulate equatorial Indian Ocean zonal winds through Walker Circulation,which in turn trigger eastward propagating upwelling Kelvin waves and westward propagating downwelling Rossby waves.The Rossby waves are reflected into downwelling Kelvin waves,which then propagate eastward along the equator and the Sumatra-Java coast in the Indian Ocean.As a result,the wave dynamics tend to generate negative(positive)SSHA in the eastern Indian Ocean,and thus enhance(reduce)the ITF transport with time lag of 0-6 months(9-12 months),respectively.Under the IOD condition,the wave dynamics also tend to enhance the ITF in the positive IOD year,and reduce the ITF in the following year.
基金Project supported by the National High-Tech R&D Program(863)of China(No.2015AA015303)the National Natural Science Foundation of China(No.61272083)
文摘Information leak,which can undermine the compliance of web-service-composition business processes for some policies,is one of the major concerns in web service composition.We present an automated and effective approach for the detection of implicit information leaks in business process execution language(BPEL)based on information flow analysis.We introduce an adequate meta-model for BPEL representation based on a Petri net for transformation and analysis.Building on the concept of Petri net place-based noninterference,the core contribution of this paper is the application of a Petri net reachability graph to estimate Petri net interference and thereby to detect implicit information leaks in web service composition.In addition,a case study illustrates the application of the approach on a concrete workflow in BPEL notation.
基金supported in part by the National Natural Science Foundation of China(No.61672433)the Natural Science Foundation of Shaanxi Province(No.2019JM-244)。
文摘Information Flow Tracking(IFT)is an established formal method for proving security properties related to confidentiality,integrity,and isolation.It has seen promise in identifying security vulnerabilities resulting from design flaws,timing channels,and hardware Trojans for secure hardware design.However,existing IFT methods tend to take a qualitative approach and only enforce binary security properties,requiring strict non-interference for the properties to hold while real systems usually allow a small amount of information flows to enable desirable interactions.Consequently,existing methods are inadequate for reasoning about quantitative security properties or measuring the security of a design in order to assess the severity of a security vulnerability.In this work,we propose two multi-flow solutions—multiple verifications for replicating existing IFT model and multi-flow IFT method.The proposed multi-flow IFT method provides more insight into simultaneous information flow behaviors and allows for proof of quantitative information flow security properties,such as diffusion,randomization,and boundaries on the amount of simultaneous information flows.Experimental results show that our method can be used to prove a new type of information flow security property with verification performance benefits.
文摘This study examines whether the number of forward patent citations(along with alternative patent data)dwhen used as a proxy for the mixing variabledcould infer the aggregate amount of economic-innovation information arriving at the New York Stock Exchange(NYSE)in the United States.The results show that the number of forward patent citations,when used as a mixing variable,fails to eliminate total volatility persistence in the conditional variance equation of the exponential generalized autoregressive conditional heteroscedastic(EGARCH)model.However,the trading volume successfully eliminates total volatility persistence,thus confirming the validity of the framework used.When the volatility is modeled with an expectation of mean return,the persistence of conditional variance is deterministically increased,and the sum of the volatility coefficients exceeds unity.The inclusion of trading volume with a time trend in the variance equation rectifies the deterministic increase in the conditional volatility.These findings suggest that the form of heteroscedasticity(i.e.,as per the autoregressive conditional heteroscedastic model,ARCH model)in NYSE portfolio returns is based on the type of shocks to volatility(e.g.,deterministic vs.stochastic),which manifests as news arrivals(i.e.,new information arrivals proxied by trading volume)at the stock market.The volume therefore reflects the time dependence in the innovations to the ARCH error generation process.The response of volatility to volume persists over time when the volatility estimates are derived from the EGARCH model with an expectation for the mean of return.Backward patent citations,patent applications,and patents issued have been found to interact somewhat with trading volume,suggesting that each of these variables could play the role of an absorptive capacity variable as the new information flow associated with economic innovation(i.e.,flow of firms’stock of new knowledge)could be picked up by the trading volume.
基金supported by the National Natural Science Foundation of China under Grant No.11371049the Fundamental Research Funds for the Central Universities under Grant No.2016JBM070
文摘How can we approach the truth in a society？ It may depend on various factors. In this paper, using a well-established truth seeking model, the authors show that the persistent free information flow will bring us to the truth. Here the free information flow is modeled as the environmental random noise that could alter one＇s cognition. Without the random noise, the model predicts that the truth can only be captured by the truth seekers who own actively perceptive ability of the truth and their believers, while the other individuals may stick to falsehood. But under the influence of the random noise, the authors strictly prove that even there is only one truth seeker in the group, all individuals will finally approach the truth.
基金Project supported by the National Natural Science Foundation of China(Nos.61562087 and 61772270)the National High-Tech R&D Program(863)of China(No.2015AA015303)+2 种基金the Natural Science Foundation of Jiangsu Province,China(No.BK20130735)the Universities Natural Science Foundation of Jiangsu Province,China(No.13KJB520011)the Science Foundation of Nanjing Institute of Technology,China(No.YKJ201420)
文摘After a composite service is deployed, user privacy requirements and trust levels of component services are subject to variation. When the changes occur, it is critical to preserve privacy information flow security. We propose an approach to preserve privacy information flow security in composite service evolution. First, a privacy data item dependency analysis method based on a Petri net model is presented. Then the set of privacy data items collected by each component service is derived through a privacy data item dependency graph, and the security scope of each component service is calculated. Finally, the evolution operations that preserve privacy information flow security are defined. By applying these evolution operations, the re-verification process is avoided and the evolution efficiency is improved. To illustrate the effectiveness of our approach, a case study is presented. The experimental results indicate that our approach has high evolution efficiency and can greatly reduce the cost of evolution compared with re-verifying the entire composite service.
