The fast convergence without initial value dependence is the key to solving large angle relative orientation.Therefore,a hybrid conjugate gradient algorithm is proposed in this paper.The concrete process is:①stochast...The fast convergence without initial value dependence is the key to solving large angle relative orientation.Therefore,a hybrid conjugate gradient algorithm is proposed in this paper.The concrete process is:①stochastic hill climbing(SHC)algorithm is used to make a random disturbance to the given initial value of the relative orientation element,and the new value to guarantee the optimization direction is generated.②In local optimization,a super-linear convergent conjugate gradient method is used to replace the steepest descent method in relative orientation to improve its convergence rate.③The global convergence condition is that the calculation error is less than the prescribed limit error.The comparison experiment shows that the method proposed in this paper is independent of the initial value,and has higher accuracy and fewer iterations.展开更多
Quantum coherence plays a central role in Grover’s search algorithm.We study the Tsallis relative a entropy of coherence dynamics of the evolved state in Grover’s search algorithm.We prove that the Tsallis relative ...Quantum coherence plays a central role in Grover’s search algorithm.We study the Tsallis relative a entropy of coherence dynamics of the evolved state in Grover’s search algorithm.We prove that the Tsallis relative a entropy of coherence decreases with the increase of the success probability,and derive the complementarity relations between the coherence and the success probability.We show that the operator coherence of the first H■relies on the size of the database N,the success probability and the target states.Moreover,we illustrate the relationships between coherence and entanglement of the superposition state of targets,as well as the production and deletion of coherence in Grover iterations.展开更多
A weighted algorithm for watermarking relational databases for copyright protection is presented. The possibility of watermarking an attribute is assigned according to its weight decided by the owner of the database. ...A weighted algorithm for watermarking relational databases for copyright protection is presented. The possibility of watermarking an attribute is assigned according to its weight decided by the owner of the database. A one-way hash function and a secret key known only to the owner of the data are used to select tuples and bits to mark. By assigning high weight to significant attributes, the scheme ensures that important attributes take more chance to be marked than less important ones. Experimental results show that the proposed scheme is robust against various forms of attacks, and has perfect immunity to subset attack.展开更多
AIM： To figure out the contributed factors of the hospitalization expenses of senile cataract patients（HECP） and build up an area-specified senile cataract diagnosis related group（DRG） of Shanghai thereby formula...AIM： To figure out the contributed factors of the hospitalization expenses of senile cataract patients（HECP） and build up an area-specified senile cataract diagnosis related group（DRG） of Shanghai thereby formulating the reference range of HECP and providing scientific basis for the fair use and supervision of the health care insurance fund.METHODS： The data was collected from the first page of the medical records of 22 097 hospitalized patients from tertiary hospitals in Shanghai from 2010 to 2012 whose major diagnosis were senile cataract. Firstly, we analyzed the influence factors of HECP using univariate and multivariate analysis. DRG grouping was conducted according to the exhaustive Chi-squared automatic interaction detector（E-CHAID） model, using HECP as target variable. Finally we evaluated the grouping results using non-parametric test such as Kruskal-Wallis H test, RIV, CV, etc.RESULTS： The 6 DRGs were established as well as criterion of HECP, using age, sex, type of surgery and whether complications/comorbidities occurred as the key variables of classification node of senile cataract cases.CONCLUSION： The grouping of senile cataract cases based on E-CHAID algorithm is reasonable. And the criterion of HECP based on DRG can provide a feasible way of management in the fair use and supervision of medical insurance fund.展开更多
This paper studies the correlation between Traditional Chinese Medicine(TCM)Constitution discrimination and physical examination index based on BPNN algorithm.253cases of routine urine test were used to build a linkag...This paper studies the correlation between Traditional Chinese Medicine(TCM)Constitution discrimination and physical examination index based on BPNN algorithm.253cases of routine urine test were used to build a linkage model between TCM Constitution and physical indicators via BPNN algorithm.According to the test,the correct rate of learning and test group are60%and40%,respectively.A strong correlation was found between TCM Constitution and physical examination indexes.By applying cutting-edge knowledge and technologies,the development and modernization process of TCM can be greatly promoted.展开更多
In this paper, a novel empirical equation is proposed to calculate the relative permeability of low permeability reservoir. An improved item is introduced on the basis of Rose empirical formula and Al-Fattah empirical...In this paper, a novel empirical equation is proposed to calculate the relative permeability of low permeability reservoir. An improved item is introduced on the basis of Rose empirical formula and Al-Fattah empirical formula, with one simple model to describe oil/water relative permeability. The position displacement idea of bare bones particle swarm optimization is applied to change the mutation operator to improve the RNA genetic algorithm. The parameters of the new empirical equation are optimized with the hybrid RNA genetic algorithm(HRGA) based on the experimental data. The data is obtained from a typical low permeability reservoir well 54 core 27-1 in Gu Dong by unsteady method. We carry out matlab programming simulation with HRGA. The comparison and error analysis show that the empirical equation proposed is more accurate than the Rose empirical formula and the exponential model. The generalization of the empirical equation is also verified.展开更多
As the current calculation methods for wellbore separation factor have some deficiencies, we propose and analyze a new calculation approach for wellbore separation factor based on the relative position of adjacent wel...As the current calculation methods for wellbore separation factor have some deficiencies, we propose and analyze a new calculation approach for wellbore separation factor based on the relative position of adjacent wellbores, named as relative position method for short. Based on the trajectory error ellipsoid model of single wellbore, the error ellipsoids model of adjacent wellbore was derived considering the correlation of trajectory errors between adjacent wells. Furthermore, the calculation formula of the separation factor based on relative position of adjacent wellbore was derived and solved with the conjugate gradient algorithm. Case study shows that the new approach is more precise and higher in applicability than the ellipsoid scaling method and the minimum distance method, it can evaluate the state of well collision more reasonably. By doing batch calculation with the new method and following the criterion of well collision avoidance, the permissible ranges of key parameters in the well design can be worked out quickly. This method has good application in the design of cluster wells and directional wells.展开更多
In recent years, there is a wide interest in Sarkovskii's theorem ami the related study. According to Sarkovskii's theoren if the continuous self-mapf of the closed interval has a 3-pcriodic orbit, then fmust ...In recent years, there is a wide interest in Sarkovskii's theorem ami the related study. According to Sarkovskii's theoren if the continuous self-mapf of the closed interval has a 3-pcriodic orbit, then fmust has an n-pcriodic orbit for any positive integer n. But f can not has all n-periodic orbits for some n.For example, letEvidently, f has only one kind of 3-periodic orbit in the two kinds of 3-periodic orbits. This explains that it isn't far enough to uncover the relation between periodic orbits by information which Sarkovskii's theorem has offered. In this paper, we raise the concept of type of periodic orbits, and give a feasible algorithm which decides the relation of implication between two periodic orbits.展开更多
In the era of exponential growth of digital information,recommender algorithms are vital for helping users navigate vast data to find relevant items.Traditional approaches such as collaborative filtering and contentba...In the era of exponential growth of digital information,recommender algorithms are vital for helping users navigate vast data to find relevant items.Traditional approaches such as collaborative filtering and contentbasedmethods have limitations in capturing complex,multi-faceted relationships in large-scale,sparse datasets.Recent advances in Graph Neural Networks(GNNs)have significantly improved recommendation performance by modeling high-order connection patterns within user-item interaction networks.However,existing GNN-based models like LightGCN and NGCF focus primarily on single-type interactions and often overlook diverse semantic relationships,leading to reduced recommendation diversity and limited generalization.To address these challenges,this paper proposes a dual multi-relational graph neural network recommendation algorithm based on relational interactions.Our approach constructs two complementary graph structures:a User-Item Interaction Graph(UIIG),which explicitly models direct user behaviors such as clicks and purchases,and a Relational Association Graph(RAG),which uncovers latent associations based on user similarities and item attributes.The proposed Dual Multi-relational Graph Neural Network(DMGNN)features two parallel branches that perform multi-layer graph convolutional operations,followed by an adaptive fusion mechanism to effectively integrate information from both graphs.This design enhances the model’s capacity to capture diverse relationship types and complex relational patterns.Extensive experiments conducted on benchmark datasets—including MovieLens-1M,Amazon-Electronics,and Yelp—demonstrate thatDMGNN outperforms state-of-the-art baselines,achieving improvements of up to 12.3%in Precision,9.7%in Recall,and 11.5%in F1 score.Moreover,DMGNN significantly boosts recommendation diversity by 15.2%,balancing accuracy with exploration.These results highlight the effectiveness of leveraging hierarchical multi-relational information,offering a promising solution to the challenges of data sparsity and relation heterogeneity in recommendation systems.Our work advances the theoretical understanding of multi-relational graph modeling and presents practical insights for developing more personalized,diverse,and robust recommender systems.展开更多
This study introduces a novel approach to addressing the challenges of high-dimensional variables and strong nonlinearity in reservoir production and layer configuration optimization.For the first time,relational mach...This study introduces a novel approach to addressing the challenges of high-dimensional variables and strong nonlinearity in reservoir production and layer configuration optimization.For the first time,relational machine learning models are applied in reservoir development optimization.Traditional regression-based models often struggle in complex scenarios,but the proposed relational and regression-based composite differential evolution(RRCODE)method combines a Gaussian naive Bayes relational model with a radial basis function network regression model.This integration effectively captures complex relationships in the optimization process,improving both accuracy and convergence speed.Experimental tests on a multi-layer multi-channel reservoir model,the Egg reservoir model,and a real-field reservoir model(the S reservoir)demonstrate that RRCODE significantly reduces water injection and production volumes while increasing economic returns and cumulative oil recovery.Moreover,the surrogate models employed in RRCODE exhibit lightweight characteristics with low computational overhead.These results highlight RRCODE's superior performance in the integrated optimization of reservoir production and layer configurations,offering more efficient and economically viable solutions for oilfield development.展开更多
Purpose–The deformation of the roadbed is easily influenced by the external environment to improve the accuracy of high-speed railway subgrade settlement prediction.Design/methodology/approach–A high-speed railway s...Purpose–The deformation of the roadbed is easily influenced by the external environment to improve the accuracy of high-speed railway subgrade settlement prediction.Design/methodology/approach–A high-speed railway subgrade settlement interval prediction method using the secretary bird optimization(SBOA)algorithm to optimize the BP neural network under the premise of gray relational analysis is proposed.Findings–Using the SBOA algorithm to optimize the BP neural network,the optimal weights and thresholds are obtained,and the best parameter prediction model is combined.The data were collected from the sensors deployed through the subgrade settlement monitoring system,and the gray relational analysis is used to verify that all four influencing factors had a great correlation to the subgrade settlement,and the collected data are verified using the model.Originality/value–The experimental results show that the SBOA-BP model has higher prediction accuracy than the BP model,and the SBOA-BP model has a wider range of prediction intervals for a given confidence level,which can provide higher guiding value for practical engineering applications.展开更多
The traditional algorithms for formation flying satellites treat the satellite position and attitude sepa- rately. A novel algorithm combining satellite attitude with position is proposed. The principal satellite traj...The traditional algorithms for formation flying satellites treat the satellite position and attitude sepa- rately. A novel algorithm combining satellite attitude with position is proposed. The principal satellite trajectory is obtained by dual quaternion interpolation, then the relative position and attitude of the deputy satellite are ob- tained by dual quaternion modeling on the principal satellite. Through above process, relative position and atti- tude are unified. Compared with the orbital parameter and the quaternion methods, the simulation result proves that the algorithm can unify position and attitude, and satisfy the precision requirement of formation flying satel- lites.展开更多
Based on the job demands-resources(JD-R)model,this study aims to investigate how algorithmic behavioral constraint and algorithmic tracking evaluation affect gig workers’turnover intention by increasing relative depr...Based on the job demands-resources(JD-R)model,this study aims to investigate how algorithmic behavioral constraint and algorithmic tracking evaluation affect gig workers’turnover intention by increasing relative deprivation and the extent to which this mediating role is moderated by algorithmic standardized guidance.Data from 242 gig workers were collected in two rounds and used to test the hypotheses.The results reveal that algorithmic behavioral constraints and algorithmic tracking evaluation are positively related to turnover intention,while algorithmic standardized guidance is negatively related to turnover intention.Moreover,algorithmic behavioral constraint and algorithmic tracking evaluation are positively related to turnover intention through relative deprivation,with algorithmic standardized guidance weakening this effect.展开更多
As the information technology rapidly develops,many network applications appear and their communication protocols are unknown.Although many protocol keyword recognition based protocol reverse engineering methods have ...As the information technology rapidly develops,many network applications appear and their communication protocols are unknown.Although many protocol keyword recognition based protocol reverse engineering methods have been proposed,most of the keyword recognition algorithms are time consuming.This paper firstly uses the traffic clustering method F-DBSCAN to cluster the unknown protocol traffic.Then an improved CFSM(Closed Frequent Sequence Mining)algorithm is used to mine closed frequent sequences from the messages and identify protocol keywords.Finally,CFGM(Closed Frequent Group Mining)algorithm is proposed to explore the parallel,sequential and hierarchical relations between the protocol keywords and obtain accurate protocol message formats.Experimental results show that the proposed protocol formats extraction method is better than Apriori algorithm and Sequence alignment algorithm in terms of time complexity and it can achieve high keyword recognition accuracy.Additionally,based on the relations between the keywords,the method can obtain accurate protocol formats.Compared with the protocol formats obtained from the existing methods,our protocol format can better grasp the overall structure of target protocols and the results perform better in the application of protocol reverse engineering such as fuzzing test.展开更多
基金National Natural Science Foundation of China(Nos.4156108241161061)。
文摘The fast convergence without initial value dependence is the key to solving large angle relative orientation.Therefore,a hybrid conjugate gradient algorithm is proposed in this paper.The concrete process is:①stochastic hill climbing(SHC)algorithm is used to make a random disturbance to the given initial value of the relative orientation element,and the new value to guarantee the optimization direction is generated.②In local optimization,a super-linear convergent conjugate gradient method is used to replace the steepest descent method in relative orientation to improve its convergence rate.③The global convergence condition is that the calculation error is less than the prescribed limit error.The comparison experiment shows that the method proposed in this paper is independent of the initial value,and has higher accuracy and fewer iterations.
基金supported by the National Natural Science Foundation of China(Grant Nos.12161056,12075159,12171044)Beijing Natural Science Foundation(Grant No.Z190005)the Academician Innovation Platform of Hainan Province。
文摘Quantum coherence plays a central role in Grover’s search algorithm.We study the Tsallis relative a entropy of coherence dynamics of the evolved state in Grover’s search algorithm.We prove that the Tsallis relative a entropy of coherence decreases with the increase of the success probability,and derive the complementarity relations between the coherence and the success probability.We show that the operator coherence of the first H■relies on the size of the database N,the success probability and the target states.Moreover,we illustrate the relationships between coherence and entanglement of the superposition state of targets,as well as the production and deletion of coherence in Grover iterations.
基金Supported by the Aeronautics Science Foundation of China (02F52033), the High-Technology Research Project of Jiangsu Province (BG2004005) and Youth Research Foundation of Qufu Normal Univer-sity(XJ02057)
文摘A weighted algorithm for watermarking relational databases for copyright protection is presented. The possibility of watermarking an attribute is assigned according to its weight decided by the owner of the database. A one-way hash function and a secret key known only to the owner of the data are used to select tuples and bits to mark. By assigning high weight to significant attributes, the scheme ensures that important attributes take more chance to be marked than less important ones. Experimental results show that the proposed scheme is robust against various forms of attacks, and has perfect immunity to subset attack.
基金Supported by the Key Research and Development Program of Hunan Province(No.2017SK2011)
文摘AIM： To figure out the contributed factors of the hospitalization expenses of senile cataract patients（HECP） and build up an area-specified senile cataract diagnosis related group（DRG） of Shanghai thereby formulating the reference range of HECP and providing scientific basis for the fair use and supervision of the health care insurance fund.METHODS： The data was collected from the first page of the medical records of 22 097 hospitalized patients from tertiary hospitals in Shanghai from 2010 to 2012 whose major diagnosis were senile cataract. Firstly, we analyzed the influence factors of HECP using univariate and multivariate analysis. DRG grouping was conducted according to the exhaustive Chi-squared automatic interaction detector（E-CHAID） model, using HECP as target variable. Finally we evaluated the grouping results using non-parametric test such as Kruskal-Wallis H test, RIV, CV, etc.RESULTS： The 6 DRGs were established as well as criterion of HECP, using age, sex, type of surgery and whether complications/comorbidities occurred as the key variables of classification node of senile cataract cases.CONCLUSION： The grouping of senile cataract cases based on E-CHAID algorithm is reasonable. And the criterion of HECP based on DRG can provide a feasible way of management in the fair use and supervision of medical insurance fund.
基金funding support from the Young Talents for research on Traditional Chinese Medicine Science and Technology in Sichuan (No.2016Q065)
文摘This paper studies the correlation between Traditional Chinese Medicine(TCM)Constitution discrimination and physical examination index based on BPNN algorithm.253cases of routine urine test were used to build a linkage model between TCM Constitution and physical indicators via BPNN algorithm.According to the test,the correct rate of learning and test group are60%and40%,respectively.A strong correlation was found between TCM Constitution and physical examination indexes.By applying cutting-edge knowledge and technologies,the development and modernization process of TCM can be greatly promoted.
基金Supported by the National Natural Science Foundation of China(60974039)the Natural Science Foundation of Shandong Province(ZR2011FM002)
文摘In this paper, a novel empirical equation is proposed to calculate the relative permeability of low permeability reservoir. An improved item is introduced on the basis of Rose empirical formula and Al-Fattah empirical formula, with one simple model to describe oil/water relative permeability. The position displacement idea of bare bones particle swarm optimization is applied to change the mutation operator to improve the RNA genetic algorithm. The parameters of the new empirical equation are optimized with the hybrid RNA genetic algorithm(HRGA) based on the experimental data. The data is obtained from a typical low permeability reservoir well 54 core 27-1 in Gu Dong by unsteady method. We carry out matlab programming simulation with HRGA. The comparison and error analysis show that the empirical equation proposed is more accurate than the Rose empirical formula and the exponential model. The generalization of the empirical equation is also verified.
基金Supported by the Major Program of the Strategic Pilot Science and Technology Foundation of Chinese Academy of Sciences(XDA14020500)the CNPC Science and Technology Major Project(2019A-3912,2018E-2107).
文摘As the current calculation methods for wellbore separation factor have some deficiencies, we propose and analyze a new calculation approach for wellbore separation factor based on the relative position of adjacent wellbores, named as relative position method for short. Based on the trajectory error ellipsoid model of single wellbore, the error ellipsoids model of adjacent wellbore was derived considering the correlation of trajectory errors between adjacent wells. Furthermore, the calculation formula of the separation factor based on relative position of adjacent wellbore was derived and solved with the conjugate gradient algorithm. Case study shows that the new approach is more precise and higher in applicability than the ellipsoid scaling method and the minimum distance method, it can evaluate the state of well collision more reasonably. By doing batch calculation with the new method and following the criterion of well collision avoidance, the permissible ranges of key parameters in the well design can be worked out quickly. This method has good application in the design of cluster wells and directional wells.
基金Projects Supported by the National Natural Science Foundation of China
文摘In recent years, there is a wide interest in Sarkovskii's theorem ami the related study. According to Sarkovskii's theoren if the continuous self-mapf of the closed interval has a 3-pcriodic orbit, then fmust has an n-pcriodic orbit for any positive integer n. But f can not has all n-periodic orbits for some n.For example, letEvidently, f has only one kind of 3-periodic orbit in the two kinds of 3-periodic orbits. This explains that it isn't far enough to uncover the relation between periodic orbits by information which Sarkovskii's theorem has offered. In this paper, we raise the concept of type of periodic orbits, and give a feasible algorithm which decides the relation of implication between two periodic orbits.
文摘In the era of exponential growth of digital information,recommender algorithms are vital for helping users navigate vast data to find relevant items.Traditional approaches such as collaborative filtering and contentbasedmethods have limitations in capturing complex,multi-faceted relationships in large-scale,sparse datasets.Recent advances in Graph Neural Networks(GNNs)have significantly improved recommendation performance by modeling high-order connection patterns within user-item interaction networks.However,existing GNN-based models like LightGCN and NGCF focus primarily on single-type interactions and often overlook diverse semantic relationships,leading to reduced recommendation diversity and limited generalization.To address these challenges,this paper proposes a dual multi-relational graph neural network recommendation algorithm based on relational interactions.Our approach constructs two complementary graph structures:a User-Item Interaction Graph(UIIG),which explicitly models direct user behaviors such as clicks and purchases,and a Relational Association Graph(RAG),which uncovers latent associations based on user similarities and item attributes.The proposed Dual Multi-relational Graph Neural Network(DMGNN)features two parallel branches that perform multi-layer graph convolutional operations,followed by an adaptive fusion mechanism to effectively integrate information from both graphs.This design enhances the model’s capacity to capture diverse relationship types and complex relational patterns.Extensive experiments conducted on benchmark datasets—including MovieLens-1M,Amazon-Electronics,and Yelp—demonstrate thatDMGNN outperforms state-of-the-art baselines,achieving improvements of up to 12.3%in Precision,9.7%in Recall,and 11.5%in F1 score.Moreover,DMGNN significantly boosts recommendation diversity by 15.2%,balancing accuracy with exploration.These results highlight the effectiveness of leveraging hierarchical multi-relational information,offering a promising solution to the challenges of data sparsity and relation heterogeneity in recommendation systems.Our work advances the theoretical understanding of multi-relational graph modeling and presents practical insights for developing more personalized,diverse,and robust recommender systems.
基金supported by the National Natural Science Foundation of China under Grant 52325402,52274057,and 52074340the National Key R&D Program of China under Grant 2023YFB4104200+2 种基金the Major Scientific and Technological Projects of CNOOC under Grant CCL2022RCPS0397RSN111 Project under Grant B08028China Scholarship Council under Grant 202306450108.
文摘This study introduces a novel approach to addressing the challenges of high-dimensional variables and strong nonlinearity in reservoir production and layer configuration optimization.For the first time,relational machine learning models are applied in reservoir development optimization.Traditional regression-based models often struggle in complex scenarios,but the proposed relational and regression-based composite differential evolution(RRCODE)method combines a Gaussian naive Bayes relational model with a radial basis function network regression model.This integration effectively captures complex relationships in the optimization process,improving both accuracy and convergence speed.Experimental tests on a multi-layer multi-channel reservoir model,the Egg reservoir model,and a real-field reservoir model(the S reservoir)demonstrate that RRCODE significantly reduces water injection and production volumes while increasing economic returns and cumulative oil recovery.Moreover,the surrogate models employed in RRCODE exhibit lightweight characteristics with low computational overhead.These results highlight RRCODE's superior performance in the integrated optimization of reservoir production and layer configurations,offering more efficient and economically viable solutions for oilfield development.
文摘Purpose–The deformation of the roadbed is easily influenced by the external environment to improve the accuracy of high-speed railway subgrade settlement prediction.Design/methodology/approach–A high-speed railway subgrade settlement interval prediction method using the secretary bird optimization(SBOA)algorithm to optimize the BP neural network under the premise of gray relational analysis is proposed.Findings–Using the SBOA algorithm to optimize the BP neural network,the optimal weights and thresholds are obtained,and the best parameter prediction model is combined.The data were collected from the sensors deployed through the subgrade settlement monitoring system,and the gray relational analysis is used to verify that all four influencing factors had a great correlation to the subgrade settlement,and the collected data are verified using the model.Originality/value–The experimental results show that the SBOA-BP model has higher prediction accuracy than the BP model,and the SBOA-BP model has a wider range of prediction intervals for a given confidence level,which can provide higher guiding value for practical engineering applications.
基金Supported by the National Natural Science Foundation of China(60974107)the Research Foundation of Nanjing University of Aeronautics and Astronautics(2010219)~~
文摘The traditional algorithms for formation flying satellites treat the satellite position and attitude sepa- rately. A novel algorithm combining satellite attitude with position is proposed. The principal satellite trajectory is obtained by dual quaternion interpolation, then the relative position and attitude of the deputy satellite are ob- tained by dual quaternion modeling on the principal satellite. Through above process, relative position and atti- tude are unified. Compared with the orbital parameter and the quaternion methods, the simulation result proves that the algorithm can unify position and attitude, and satisfy the precision requirement of formation flying satel- lites.
基金supported by the National Natural Science Foundation of China(#71832003,#72272054)Humanities and Social Science Foundation project of Ministry of Education(#22YJA630049)+1 种基金Hunan Provincial Natural Science Foundation Project(#2022JJ30208)Key Project of Changsha Natural Science Foundation(#kq2202302).
文摘Based on the job demands-resources(JD-R)model,this study aims to investigate how algorithmic behavioral constraint and algorithmic tracking evaluation affect gig workers’turnover intention by increasing relative deprivation and the extent to which this mediating role is moderated by algorithmic standardized guidance.Data from 242 gig workers were collected in two rounds and used to test the hypotheses.The results reveal that algorithmic behavioral constraints and algorithmic tracking evaluation are positively related to turnover intention,while algorithmic standardized guidance is negatively related to turnover intention.Moreover,algorithmic behavioral constraint and algorithmic tracking evaluation are positively related to turnover intention through relative deprivation,with algorithmic standardized guidance weakening this effect.
基金supported by the National Key R&D Subsidized Project with 2017YFB0802900.
文摘As the information technology rapidly develops,many network applications appear and their communication protocols are unknown.Although many protocol keyword recognition based protocol reverse engineering methods have been proposed,most of the keyword recognition algorithms are time consuming.This paper firstly uses the traffic clustering method F-DBSCAN to cluster the unknown protocol traffic.Then an improved CFSM(Closed Frequent Sequence Mining)algorithm is used to mine closed frequent sequences from the messages and identify protocol keywords.Finally,CFGM(Closed Frequent Group Mining)algorithm is proposed to explore the parallel,sequential and hierarchical relations between the protocol keywords and obtain accurate protocol message formats.Experimental results show that the proposed protocol formats extraction method is better than Apriori algorithm and Sequence alignment algorithm in terms of time complexity and it can achieve high keyword recognition accuracy.Additionally,based on the relations between the keywords,the method can obtain accurate protocol formats.Compared with the protocol formats obtained from the existing methods,our protocol format can better grasp the overall structure of target protocols and the results perform better in the application of protocol reverse engineering such as fuzzing test.
