The probability hypothesis density (PHD) propagates the posterior intensity in place of the poste- rior probability density of the multi-target state. The cardinalized PHD (CPHD) recursion is a generalization of P...The probability hypothesis density (PHD) propagates the posterior intensity in place of the poste- rior probability density of the multi-target state. The cardinalized PHD (CPHD) recursion is a generalization of PHD recursion, which jointly propagates the posterior intensity function and posterior cardinality distribution. A number of sequential Monte Carlo (SMC) implementations of PHD and CPHD filters (also known as SMC- PHD and SMC-CPHD filters, respectively) for general non-linear non-Gaussian models have been proposed. However, these approaches encounter the limitations when the observation variable is analytically unknown or the observation noise is null or too small. In this paper, we propose a convolution kernel approach in the SMC-CPHD filter. The simuIation results show the performance of the proposed filter on several simulated case studies when compared to the SMC-CPHD filter.展开更多
In the traditional radar unmanned aerial vehicle(UAV)detection process,coherent integration and micro-Doppler(m-D)parameter estimation are carried out separately.The target discrimination process needs to obtain the p...In the traditional radar unmanned aerial vehicle(UAV)detection process,coherent integration and micro-Doppler(m-D)parameter estimation are carried out separately.The target discrimination process needs to obtain the position information of the target,which will lose energy.In this paper,a long time integration method of radar signal based on rotating target radon Fourier transform(RTRFT)is proposed.This method modifies the distance and frequency terms in the traditional generalized radon Fourier transform(GRFT),and adds the frequency sinusoidal modulation term.Then,based on the cardinality balanced multi-target multi-Bernoulli(CBMeMBer)filter,the position of the target is detected in the high-dimensional space obtained by RTRFT.This method can combine coherent integration and micro-motion parameter estimation.Simulation experiments show that the proposed method can estimate the main translational parameters and rotational micro-motion parameters of the target while detecting the target,and the target detection performance is improved.展开更多
Cardinality estimation is crucial for query optimization,but traditional methods struggle with complex queries.We propose LW-CQ,a lightweight machine learning-based algorithm that improves cardinality estimation for c...Cardinality estimation is crucial for query optimization,but traditional methods struggle with complex queries.We propose LW-CQ,a lightweight machine learning-based algorithm that improves cardinality estimation for complex queries by enhancing the LW-XGB method.LW-CQ introduces four feature-level improvements and extends support for disjunctive queries and LIKE predicates.Experimental results show that LW-CQ achieves competitive accuracy while significantly reducing training and inference time,making it a promising solution for real-world database applications.展开更多
In multiple extended targets tracking, replacing traditional multiple measurements with a rectangular region of the nonzero volume in the state space inspired by the box-particle idea is exactly suitable to deal with ...In multiple extended targets tracking, replacing traditional multiple measurements with a rectangular region of the nonzero volume in the state space inspired by the box-particle idea is exactly suitable to deal with extended targets, without distinguishing the measurements originating from the true targets or clutter.Based on our recent work on extended box-particle probability hypothesis density(ET-BP-PHD) filter, we propose the extended labeled box-particle cardinalized probability hypothesis density(ET-LBP-CPHD) filter, which relaxes the Poisson assumptions of the extended target probability hypothesis density(PHD) filter in target numbers, and propagates not only the intensity function but also cardinality distribution. Moreover, it provides the identity of individual target by adding labels to box-particles. The proposed filter can improve the precision of estimating target number meanwhile achieve targets' tracks. The effectiveness and reliability of the proposed algorithm are verified by the simulation results.展开更多
In this paper, a cardinality compensation method based on Information-weighted Consensus Filter(ICF) using data clustering is proposed in order to accurately estimate the cardinality of the Cardinalized Probability Hy...In this paper, a cardinality compensation method based on Information-weighted Consensus Filter(ICF) using data clustering is proposed in order to accurately estimate the cardinality of the Cardinalized Probability Hypothesis Density(CPHD) filter. Although the joint propagation of the intensity and the cardinality distribution in the CPHD filter process allows for more reliable estimation of the cardinality(target number) than the PHD filter, tracking loss may occur when noise and clutter are high in the measurements in a practical situation. For that reason, the cardinality compensation process is included in the CPHD filter, which is based on information fusion step using estimated cardinality obtained from the CPHD filter and measured cardinality obtained through data clustering. Here, the ICF is used for information fusion. To verify the performance of the proposed method, simulations were carried out and it was confirmed that the tracking performance of the multi-target was improved because the cardinality was estimated more accurately as compared to the existing techniques.展开更多
BACKGROUND The procedure for lateral lymph node(LLN)dissection(LLND)is complicated and can result in complications.We developed a technique for laparoscopic LLND based on two fascial spaces to simplify the procedure.A...BACKGROUND The procedure for lateral lymph node(LLN)dissection(LLND)is complicated and can result in complications.We developed a technique for laparoscopic LLND based on two fascial spaces to simplify the procedure.AIM To clarify the anatomical basis of laparoscopic LLND in two fascial spaces and to evaluate its efficacy and safety in treating locally advanced low rectal cancer(LALRC).METHODS Cadaveric dissection was performed on 24 pelvises,and the fascial composition related to LLND was observed and described.Three dimensional-laparoscopic total mesorectal excision with LLND was performed in 20 patients with LALRC,and their clinical data were analyzed.RESULTS The cadaver study showed that the fascia propria of the rectum,urogenital fascia,vesicohypogastric fascia and parietal fascia lie side by side in a medial-lateral direction constituting the dissection plane for curative rectal cancer surgery,and the last three fasciae formed two spaces(Latzko's pararectal space and paravesical space)which were the surgical area for LLND.Laparoscopic LLND in two fascial spaces was performed successfully in all 20 patients.The median operating time,blood loss and postoperative hospitalization were 178(152-243)min,55(25-150)mL and 10(7-20)d,respectively.The median number of harvested LLNs was 8.6(6-12),and pathologically positive LLN metastasis was confirmed in 7(35.0%)cases.Postoperative complications included lower limb pain in 1 case and lymph leakage in 1 case.CONCLUSION Our preliminary surgical experience suggests that laparoscopic LLND based on fascial spaces is a feasible,effective and safe procedure for treating LALRC.展开更多
An excellent cardinality estimation can make the query optimiser produce a good execution plan.Although there are some studies on cardinality estimation,the prediction results of existing cardinality estimators are in...An excellent cardinality estimation can make the query optimiser produce a good execution plan.Although there are some studies on cardinality estimation,the prediction results of existing cardinality estimators are inaccurate and the query efficiency cannot be guaranteed as well.In particular,they are difficult to accurately obtain the complex relationships between multiple tables in complex database systems.When dealing with complex queries,the existing cardinality estimators cannot achieve good results.In this study,a novel cardinality estimator is proposed.It uses the core techniques with the BiLSTM network structure and adds the attention mechanism.First,the columns involved in the query statements in the training set are sampled and compressed into bitmaps.Then,the Word2vec model is used to embed the word vectors about the query statements.Finally,the BiLSTM network and attention mechanism are employed to deal with word vectors.The proposed model takes into consideration not only the correlation between tables but also the processing of complex predicates.Extensive experiments and the evaluation of BiLSTM-Attention Cardinality Estimator(BACE)on the IMDB datasets are conducted.The results show that the deep learning model can significantly improve the quality of cardinality estimation,which is a vital role in query optimisation for complex databases.展开更多
The purpose of this study is to reduce the uncertainty in the calculation process on hesitant fuzzy sets(HFSs).The innovation of this study is to unify the cardinal numbers of hesitant fuzzy elements(HFEs)in a special...The purpose of this study is to reduce the uncertainty in the calculation process on hesitant fuzzy sets(HFSs).The innovation of this study is to unify the cardinal numbers of hesitant fuzzy elements(HFEs)in a special way.Firstly,a probability density function is assigned for any given HFE.Thereafter,equal-probability transformation is introduced to transform HFEs with different cardinal numbers on the condition into the same probability density function.The characteristic of this transformation is that the higher the consistency of the membership degrees in HFEs,the higher the credibility of the mentioned membership degrees is,then,the bigger the probability density values for them are.According to this transformation technique,a set of novel distance measures on HFSs is provided.Finally,an illustrative example of intersection traffic control is introduced to show the usefulness of the given distance measures.The example also shows that this study is a good complement to operation theories on HFSs.展开更多
A new lane-level road modeling method based on cardinal spline is proposed for the special intersections which are covered by vegetation or artificial landscape in their central regions.First,cardinal spline curves ar...A new lane-level road modeling method based on cardinal spline is proposed for the special intersections which are covered by vegetation or artificial landscape in their central regions.First,cardinal spline curves are used to fit the virtual lanes inside special intersections,and an initial road model is established using a series of control points and tension parameters.Then,the progressive optimization algorithm is proposed to determine the final road model based on the initial model.The algorithm determines reasonable control points and optimal tension parameters according to the degree of road curvature changes,so as to achieve a balance between the efficiency and reliability of the road model.Finally,the proposed intersection model is verified and evaluated through experiments.The results show that this method can effectively describe the lane-level topological relationship and geometric details of this kind of special intersection where the central area is covered by vegetation or artificial landscape,and can achieve a good balance between the efficiency and reliability of the road model.展开更多
基金Supported in Part by the Foundation of the Excellent State Key Laboratory under Grant 40523005,and the Ministry of Education of China
摘要The probability hypothesis density (PHD) propagates the posterior intensity in place of the poste- rior probability density of the multi-target state. The cardinalized PHD (CPHD) recursion is a generalization of PHD recursion, which jointly propagates the posterior intensity function and posterior cardinality distribution. A number of sequential Monte Carlo (SMC) implementations of PHD and CPHD filters (also known as SMC- PHD and SMC-CPHD filters, respectively) for general non-linear non-Gaussian models have been proposed. However, these approaches encounter the limitations when the observation variable is analytically unknown or the observation noise is null or too small. In this paper, we propose a convolution kernel approach in the SMC-CPHD filter. The simuIation results show the performance of the proposed filter on several simulated case studies when compared to the SMC-CPHD filter.
摘要In the traditional radar unmanned aerial vehicle(UAV)detection process,coherent integration and micro-Doppler(m-D)parameter estimation are carried out separately.The target discrimination process needs to obtain the position information of the target,which will lose energy.In this paper,a long time integration method of radar signal based on rotating target radon Fourier transform(RTRFT)is proposed.This method modifies the distance and frequency terms in the traditional generalized radon Fourier transform(GRFT),and adds the frequency sinusoidal modulation term.Then,based on the cardinality balanced multi-target multi-Bernoulli(CBMeMBer)filter,the position of the target is detected in the high-dimensional space obtained by RTRFT.This method can combine coherent integration and micro-motion parameter estimation.Simulation experiments show that the proposed method can estimate the main translational parameters and rotational micro-motion parameters of the target while detecting the target,and the target detection performance is improved.
基金supported by Sichuan Science and Technology Program(2024YFHZ0161).
摘要Cardinality estimation is crucial for query optimization,but traditional methods struggle with complex queries.We propose LW-CQ,a lightweight machine learning-based algorithm that improves cardinality estimation for complex queries by enhancing the LW-XGB method.LW-CQ introduces four feature-level improvements and extends support for disjunctive queries and LIKE predicates.Experimental results show that LW-CQ achieves competitive accuracy while significantly reducing training and inference time,making it a promising solution for real-world database applications.
摘要In multiple extended targets tracking, replacing traditional multiple measurements with a rectangular region of the nonzero volume in the state space inspired by the box-particle idea is exactly suitable to deal with extended targets, without distinguishing the measurements originating from the true targets or clutter.Based on our recent work on extended box-particle probability hypothesis density(ET-BP-PHD) filter, we propose the extended labeled box-particle cardinalized probability hypothesis density(ET-LBP-CPHD) filter, which relaxes the Poisson assumptions of the extended target probability hypothesis density(PHD) filter in target numbers, and propagates not only the intensity function but also cardinality distribution. Moreover, it provides the identity of individual target by adding labels to box-particles. The proposed filter can improve the precision of estimating target number meanwhile achieve targets' tracks. The effectiveness and reliability of the proposed algorithm are verified by the simulation results.
基金supported by the National GNSS Research Center Program of the Defense Acquisition Program Administration and Agency for Defense Developmentthe Ministry of Science and ICT of the Republic of Korea through the Space Core Technology Development Program (No. NRF2018M1A3A3A02065722)
摘要In this paper, a cardinality compensation method based on Information-weighted Consensus Filter(ICF) using data clustering is proposed in order to accurately estimate the cardinality of the Cardinalized Probability Hypothesis Density(CPHD) filter. Although the joint propagation of the intensity and the cardinality distribution in the CPHD filter process allows for more reliable estimation of the cardinality(target number) than the PHD filter, tracking loss may occur when noise and clutter are high in the measurements in a practical situation. For that reason, the cardinality compensation process is included in the CPHD filter, which is based on information fusion step using estimated cardinality obtained from the CPHD filter and measured cardinality obtained through data clustering. Here, the ICF is used for information fusion. To verify the performance of the proposed method, simulations were carried out and it was confirmed that the tracking performance of the multi-target was improved because the cardinality was estimated more accurately as compared to the existing techniques.
基金Supported by The National Natural Science Foundation of China,No.81874201.
摘要BACKGROUND The procedure for lateral lymph node(LLN)dissection(LLND)is complicated and can result in complications.We developed a technique for laparoscopic LLND based on two fascial spaces to simplify the procedure.AIM To clarify the anatomical basis of laparoscopic LLND in two fascial spaces and to evaluate its efficacy and safety in treating locally advanced low rectal cancer(LALRC).METHODS Cadaveric dissection was performed on 24 pelvises,and the fascial composition related to LLND was observed and described.Three dimensional-laparoscopic total mesorectal excision with LLND was performed in 20 patients with LALRC,and their clinical data were analyzed.RESULTS The cadaver study showed that the fascia propria of the rectum,urogenital fascia,vesicohypogastric fascia and parietal fascia lie side by side in a medial-lateral direction constituting the dissection plane for curative rectal cancer surgery,and the last three fasciae formed two spaces(Latzko's pararectal space and paravesical space)which were the surgical area for LLND.Laparoscopic LLND in two fascial spaces was performed successfully in all 20 patients.The median operating time,blood loss and postoperative hospitalization were 178(152-243)min,55(25-150)mL and 10(7-20)d,respectively.The median number of harvested LLNs was 8.6(6-12),and pathologically positive LLN metastasis was confirmed in 7(35.0%)cases.Postoperative complications included lower limb pain in 1 case and lymph leakage in 1 case.CONCLUSION Our preliminary surgical experience suggests that laparoscopic LLND based on fascial spaces is a feasible,effective and safe procedure for treating LALRC.
基金supported by the National Natural Science Foundation of China under grant nos.61772091,61802035,61962006,61962038,U1802271,U2001212,and 62072311the Sichuan Science and Technology Program under grant nos.2021JDJQ0021 and 22ZDYF2680+7 种基金the CCF‐Huawei Database System Innovation Research Plan under grant no.CCF‐HuaweiDBIR2020004ADigital Media Art,Key Laboratory of Sichuan Province,Sichuan Conservatory of Music,Chengdu,China under grant no.21DMAKL02the Chengdu Major Science and Technology Innovation Project under grant no.2021‐YF08‐00156‐GXthe Chengdu Technology Innovation and Research and Development Project under grant no.2021‐YF05‐00491‐SNthe Natural Science Foundation of Guangxi under grant no.2018GXNSFDA138005the Guangdong Basic and Applied Basic Research Foundation under grant no.2020B1515120028the Science and Technology Innovation Seedling Project of Sichuan Province under grant no 2021006the College Student Innovation and Entrepreneurship Training Program of Chengdu University of Information Technology under grant nos.202110621179 and 202110621186.
摘要An excellent cardinality estimation can make the query optimiser produce a good execution plan.Although there are some studies on cardinality estimation,the prediction results of existing cardinality estimators are inaccurate and the query efficiency cannot be guaranteed as well.In particular,they are difficult to accurately obtain the complex relationships between multiple tables in complex database systems.When dealing with complex queries,the existing cardinality estimators cannot achieve good results.In this study,a novel cardinality estimator is proposed.It uses the core techniques with the BiLSTM network structure and adds the attention mechanism.First,the columns involved in the query statements in the training set are sampled and compressed into bitmaps.Then,the Word2vec model is used to embed the word vectors about the query statements.Finally,the BiLSTM network and attention mechanism are employed to deal with word vectors.The proposed model takes into consideration not only the correlation between tables but also the processing of complex predicates.Extensive experiments and the evaluation of BiLSTM-Attention Cardinality Estimator(BACE)on the IMDB datasets are conducted.The results show that the deep learning model can significantly improve the quality of cardinality estimation,which is a vital role in query optimisation for complex databases.
基金supported by Shanghai Pujiang Program (No.2019PJC062)the Natural Science Foundation of Shandong Province (No.ZR2021MG003)the Research Project on Undergraduate Teaching Reform of Higher Education in Shandong Province (No.Z2021046).
摘要The purpose of this study is to reduce the uncertainty in the calculation process on hesitant fuzzy sets(HFSs).The innovation of this study is to unify the cardinal numbers of hesitant fuzzy elements(HFEs)in a special way.Firstly,a probability density function is assigned for any given HFE.Thereafter,equal-probability transformation is introduced to transform HFEs with different cardinal numbers on the condition into the same probability density function.The characteristic of this transformation is that the higher the consistency of the membership degrees in HFEs,the higher the credibility of the mentioned membership degrees is,then,the bigger the probability density values for them are.According to this transformation technique,a set of novel distance measures on HFSs is provided.Finally,an illustrative example of intersection traffic control is introduced to show the usefulness of the given distance measures.The example also shows that this study is a good complement to operation theories on HFSs.
基金The National Natural Science Foundation of China(No.61973079,61273236)the Program for Special Talents in Six Major Fields of Jiangsu Province(No.2017JXQC-003)。
摘要A new lane-level road modeling method based on cardinal spline is proposed for the special intersections which are covered by vegetation or artificial landscape in their central regions.First,cardinal spline curves are used to fit the virtual lanes inside special intersections,and an initial road model is established using a series of control points and tension parameters.Then,the progressive optimization algorithm is proposed to determine the final road model based on the initial model.The algorithm determines reasonable control points and optimal tension parameters according to the degree of road curvature changes,so as to achieve a balance between the efficiency and reliability of the road model.Finally,the proposed intersection model is verified and evaluated through experiments.The results show that this method can effectively describe the lane-level topological relationship and geometric details of this kind of special intersection where the central area is covered by vegetation or artificial landscape,and can achieve a good balance between the efficiency and reliability of the road model.