When multiple LCC-HVDC transmission lines are densely fed into a receiving AC system,voltage dips can easily propagate in the power system,resulting in multiple LCC commutation failures simultaneously.The VSC-HVDC can...When multiple LCC-HVDC transmission lines are densely fed into a receiving AC system,voltage dips can easily propagate in the power system,resulting in multiple LCC commutation failures simultaneously.The VSC-HVDC can be used to divide the receiving sys-tem into several interconnected sub-partitions and improve the voltage support capability of the receiving system.Compared with asyn-chronous interconnection,which completely separates the receiving systems with VSC-HVDC,incomplete segmentation with an AC connection is a more pertinent segmenting method for multilayer complex regional power grids.To analyze the voltage support capability of the VSC in incomplete segmentation,a micro-incremental model of the VSC was established,the operating impedance of the VSC was calculated,and the voltage support function of the VSC was quantified.The effect of the fault on the system short-circuit capacity was analyzed,and a calculation method for the multi-infeed short-circuit ratio in an incompletely segmented scenario was obtained.A VSC-segmented model of a two-infeed DC system was built on the EMTDC/PSCAD simulation platform,and the validity of the micro-increment model and accuracy of the proposed conclusions were verified.展开更多
At present,the operation and maintenance of photovoltaic power generation systems mainly comprise regular maintenance,breakdown maintenance,and condition-based maintenance,which is very likely to lead to over-or under...At present,the operation and maintenance of photovoltaic power generation systems mainly comprise regular maintenance,breakdown maintenance,and condition-based maintenance,which is very likely to lead to over-or under-repair of equipment.Therefore,a preventive maintenance and replacement strategy for PV power generation systems based on reliability as a constraint is proposed.First,a hybrid failure function with a decreasing service age factor and an increasing failure rate factor is introduced to describe the deterioration of PV power generation equipment,and the equipment is replaced when its reliability drops to the replacement threshold in the last cycle.Then,based on the reliability as a constraint,the average maintenance cost and availability of the equipment are considered,and the non-periodic incomplete maintenance model of the PV power generation system is established to obtain the optimal number of repairs,each maintenance cycle and the replacement cycle of the PV power generation system components.Next,the inverter of a PV power plant is used as a research object.The model in this paper is compared and analyzed with the equal cycle maintenance model without considering reliability and the maintenance model without considering the equipment replacement threshold,Through model comparison,when the optimal maintenance strategy is(0.80,4),the average maintenance cost of this paper’s model are decreased by 20.3%and 5.54%and the availability is increased by 0.2395% and 0.0337%,respectively,compared with the equal-cycle maintenance model without considering the reliability constraint and the maintenance model without considering the equipment replacement threshold.Therefore,this maintenance model can ensure the high reliability of PV plant operation while increasing the equipment availability to improve the system economy.展开更多
Objective:To compare the clinical efficacy of mifepristone-misoprostol medical management versus surgical curettage for first-trimester missed miscarriage,and to establish evidence-based sonographic cutoff values pred...Objective:To compare the clinical efficacy of mifepristone-misoprostol medical management versus surgical curettage for first-trimester missed miscarriage,and to establish evidence-based sonographic cutoff values predictive of incomplete abortion requiring surgical intervention.Methods:We retrospectively analyzed a cohort of 702 women diagnosed with first-trimester missed miscarriage between January 2020 and May 2023.Demographic characteristics and ultrasound parameters were systematically recorded.Receiver operating characteristic(ROC)curve analysis was performed to establish optimal sonographic cutoff values for predicting incomplete abortion requiring surgical intervention.Results:146 patients received medical treatment(mifepristone and misoprostol)and 556 underwent surgical curettage.At the 1-month follow-up,the medical group showed significantly greater endometrial thickness and longer postoperative bleeding duration than the surgical group(P<0.05).The menstrual volume reduction rate(23.56%)was significantly lower in the medical group than in the surgical group.The incomplete abortion rate was higher in the medical group(17.12%,25/146)than in the surgical group(2.88%,16/556).Among the medical group,14 patients(9.59%)required curettage due to incomplete abortion,while 11 cases resolved spontaneously after prolonged medication.ROC curve analysis identified two cut-off values indicating the need for surgical intervention:endometrial thickness>1.21 cm at 24 h post-medical abortion,and residual mass diameter>0.95 cm at 7 days post-medical abortion.Conclusions:Medical management of first-trimester missed miscarriage using mifepristone-misoprostol demonstrates comparable efficacy to surgical curettage.An endometrial thickness>1.21 cm at 24 h or residual tissue diameter>0.95 cm at 7 days post-medical abortion should prompt consideration of incomplete abortion.展开更多
High complexity and uncertainty of air combat pose significant challenges to target intention prediction.Current interpolation methods for data pre-processing and wrangling have limitations in capturing interrelations...High complexity and uncertainty of air combat pose significant challenges to target intention prediction.Current interpolation methods for data pre-processing and wrangling have limitations in capturing interrelationships among intricate variable patterns.Accordingly,this study proposes a Mogrifier gate recurrent unit-D(Mog-GRU-D)model to address the com-bat target intention prediction issue under the incomplete infor-mation condition.The proposed model directly processes miss-ing data while reducing the independence between inputs and output states.A total of 1200 samples from twelve continuous moments are captured through the combat simulation system,each of which consists of seven dimensional features.To bench-mark the experiment,a missing valued dataset has been gener-ated by randomly removing 20%of the original data.Extensive experiments demonstrate that the proposed model obtains the state-of-the-art performance with an accuracy of 73.25%when dealing with incomplete information.This study provides possi-ble interpretations for the principle of target interactive mecha-nism,highlighting the model’s effectiveness in potential air war-fare implementation.展开更多
The widespread usage of rechargeable batteries in portable devices,electric vehicles,and energy storage systems has underscored the importance for accurately predicting their lifetimes.However,data scarcity often limi...The widespread usage of rechargeable batteries in portable devices,electric vehicles,and energy storage systems has underscored the importance for accurately predicting their lifetimes.However,data scarcity often limits the accuracy of prediction models,which is escalated by the incompletion of data induced by the issues such as sensor failures.To address these challenges,we propose a novel approach to accommodate data insufficiency through achieving external information from incomplete data samples,which are usually discarded in existing studies.In order to fully unleash the prediction power of incomplete data,we have investigated the Multiple Imputation by Chained Equations(MICE)method that diversifies the training data through exploring the potential data patterns.The experimental results demonstrate that the proposed method significantly outperforms the baselines in the most considered scenarios while reducing the prediction root mean square error(RMSE)by up to 18.9%.Furthermore,we have also observed that the penetration of incomplete data benefits the explainability of the prediction model through facilitating the feature selection.展开更多
In this paper,a distributed adaptive dynamic programming(ADP)framework based on value iteration is proposed for multi-player differential games.In the game setting,players have no access to the information of others&#...In this paper,a distributed adaptive dynamic programming(ADP)framework based on value iteration is proposed for multi-player differential games.In the game setting,players have no access to the information of others'system parameters or control laws.Each player adopts an on-policy value iteration algorithm as the basic learning framework.To deal with the incomplete information structure,players collect a period of system trajectory data to compensate for the lack of information.The policy updating step is implemented by a nonlinear optimization problem aiming to search for the proximal admissible policy.Theoretical analysis shows that by adopting proximal policy searching rules,the approximated policies can converge to a neighborhood of equilibrium policies.The efficacy of our method is illustrated by three examples,which also demonstrate that the proposed method can accelerate the learning process compared with the centralized learning framework.展开更多
For the fault detection and diagnosis problem in largescale industrial systems, there are two important issues： the missing data samples and the non-Gaussian property of the data. However, most of the existing data-d...For the fault detection and diagnosis problem in largescale industrial systems, there are two important issues： the missing data samples and the non-Gaussian property of the data. However, most of the existing data-driven methods cannot be able to handle both of them. Thus, a new Bayesian network classifier based fault detection and diagnosis method is proposed. At first, a non-imputation method is presented to handle the data incomplete samples, with the property of the proposed Bayesian network classifier, and the missing values can be marginalized in an elegant manner. Furthermore, the Gaussian mixture model is used to approximate the non-Gaussian data with a linear combination of finite Gaussian mixtures, so that the Bayesian network can process the non-Gaussian data in an effective way. Therefore, the entire fault detection and diagnosis method can deal with the high-dimensional incomplete process samples in an efficient and robust way. The diagnosis results are expressed in the manner of probability with the reliability scores. The proposed approach is evaluated with a benchmark problem called the Tennessee Eastman process. The simulation results show the effectiveness and robustness of the proposed method in fault detection and diagnosis for large-scale systems with missing measurements.展开更多
A new and intelligent design method for PID controller with incomplete derivation is proposed based on the ant system algorithm ( ASA) . For a given control system with this kind of PID controller, a group of optimal ...A new and intelligent design method for PID controller with incomplete derivation is proposed based on the ant system algorithm ( ASA) . For a given control system with this kind of PID controller, a group of optimal PID controller parameters K p * , T i * , and T d * can be obtained by taking the overshoot, settling time, and steady-state error of the system's unit step response as the performance indexes and by use of our improved ant system algorithm. K p * , T i * , and T d * can be used in real-time control. This kind of controller is called the ASA-PID controller with incomplete derivation. To verify the performance of the ASA-PID controller, three different typical transfer functions were tested, and three existing typical tuning methods of PID controller parameters, including the Ziegler-Nichols method (ZN),the genetic algorithm (GA),and the simulated annealing (SA), were adopted for comparison. The simulation results showed that the ASA-PID controller can be used to control different objects and has better performance compared with the ZN-PID and GA-PID controllers, and comparable performance compared with the SA-PID controller.展开更多
Presently, the notion of multigranulation has been brought to our attention. In this paper, the multigranulation technique is introduced into incomplete information systems. Both tolerance relations and maximal consis...Presently, the notion of multigranulation has been brought to our attention. In this paper, the multigranulation technique is introduced into incomplete information systems. Both tolerance relations and maximal consistent blocks are used to construct multigranulation rough sets. Not only are the basic properties about these models studied, but also the relationships between different multigranulation rough sets are explored. It is shown that by using maximal consistent blocks, the greater lower approximation and the same upper approximation as from tolerance relations can be obtained. Such a result is consistent with that of a single-granulation framework.展开更多
This paper focuses on fast algorithm for computing the assignment reduct in inconsistent incomplete decision systems. It is quite inconvenient to judge the assignment reduct directly ac-cording to its definition. We p...This paper focuses on fast algorithm for computing the assignment reduct in inconsistent incomplete decision systems. It is quite inconvenient to judge the assignment reduct directly ac-cording to its definition. We propose the judgment theorem for the assignment reduct in the inconsistent incomplete decision system, which greatly simplifies judging this type reduct. On such basis, we derive a novel attribute significance measure and construct the fast assignment reduction algorithm （F-ARA）, intended for com-puting the assignment reduct in inconsistent incomplete decision systems. Final y, we make a comparison between F-ARA and the discernibility matrix-based method by experiments on 13 Univer-sity of California at Irvine （UCI） datasets, and the experimental results prove that F-ARA is efficient and feasible.展开更多
Based on the rough set theory which is a powerful tool in dealing with vagueness and uncertainty, an algorithm to mine association rules in incomplete information systems was presented and the support and confidence w...Based on the rough set theory which is a powerful tool in dealing with vagueness and uncertainty, an algorithm to mine association rules in incomplete information systems was presented and the support and confidence were redefined. The algorithm can mine the association rules with decision attributes directly without processing missing values. Using the incomplete dataset Mushroom from UCI machine learning repository, the new algorithm was compared with the classical association rules mining algorithm based on Apriori from the number of rules extracted, testing accuracy and execution time. The experiment results show that the new algorithm has advantages of short execution time and high accuracy.展开更多
Objective:To evaluate the effectiveness and safety of Chinese herbal medicines(CHMs)for incomplete immune reconstruction in patients with HIV/AIDS.Methods:Eight electronic databases were searched for randomized contro...Objective:To evaluate the effectiveness and safety of Chinese herbal medicines(CHMs)for incomplete immune reconstruction in patients with HIV/AIDS.Methods:Eight electronic databases were searched for randomized controlled trials(RCTs)on the use of CHM for patients with HIV/AIDS with incomplete immune reconstruction.Outcomes included CD4þcell count,quality of life,and adverse events/effects.The Cochrane Risk of Bias was employed to evaluate the methodological quality of the included RCTs.Results:We identified 13 eligible RCTs,with an overall high risk of bias,on 10 different CHMs.There was a significant increase in CD4þcell count after the use of Jianpi Yiqi medicinal paste for 3 months;tripterygium glycosides tablets(TGTs)for 3 months(mean difference[MD]52.63 cells/mL,95%confidence interval[CI,46.98,58.28]),6,9,and 12 months;Wenshen Jianpi granules for 6 months;Shenling Fuzheng capsules for 6 months(MD 49.53 cells/mL,95%CI[8.45,90.61])and 12 months;Aikeqing granules for 9 months(MD 61.51 cells/mL,95%CI[16.25,106.77])and 12 months;Guipi decoction for 12 months;Mianyi No.2 granules(JT)for 12 and 18 months;and Chinese medicine granules for 18 months.The increase in the mean difference of CD4þcell count from 6 to 18 months was larger in Chinese medicine granules and Mianyi No.2 granules(JT).Guipi decoction and Jianpi Qushi decoction improved the Karnofsky score.Four RCTs reported the outcome of adverse events/effects,while four cases of minor adverse effects were reported in the TGTs group.Conclusion:Jianpi Yiqi medicinal paste,Wenshen Jianpi granules,Shenling Fuzheng capsules,Aikeqing granules,Guipi decoction,and TGTs may be effective in increasing CD4þwithin 12 months,and Mianyi No.2 granules(JT)and Chinese medicine granules may show long-term effects.High-quality large RCTs on the effectiveness and safety of CHMs are still warranted.展开更多
The tolerance rough set is developed as one of the outstanding extensions of the Pawlak's rough set model under incomplete information,and the limited tolerance relation is developed to overcome the problem that o...The tolerance rough set is developed as one of the outstanding extensions of the Pawlak's rough set model under incomplete information,and the limited tolerance relation is developed to overcome the problem that objects leniently satisfy the tolerance relation.However,the classification based on the limited tolerance relationship cannot reflect the matching degree of uncertain information of objects.In this article,we explore the influence of null values in an incomplete system,and propose the constrained tolerance relation based on the matching degree of uncertain information of objects.The proposed rough set based on the constrained tolerance relation can provide a more detailed structure of an object class through threshold.Proofs and example analyses further show the rationality and superiority of the proposed model.展开更多
In order to understand the security conditions of the incomplete interval-valued information system （IllS） and acquire the corresponding solution of security problems, this paper proposes a multi-attribute group dec...In order to understand the security conditions of the incomplete interval-valued information system （IllS） and acquire the corresponding solution of security problems, this paper proposes a multi-attribute group decision- making （MAGDM） security assessment method based on the technique for order performance by similarity to ideal solution （TOPSIS）. For IllS with preference information, combining with dominance-based rough set approach （DRSA）, the effect of incomplete interval-valued information on decision results is discussed. For the imprecise judgment matrices, the security attribute weight can be obtained using Gibbs sampling. A numerical example shows that the proposed method can acquire some valuable knowledge hidden in the incomplete interval-valued information. The effectiveness of the proposed method in the synthetic security assessment for IIIS is verified.展开更多
Rock mass quality serves as a vital index for predicting the stability and safety status of rock tunnel faces.In tunneling practice,the rock mass quality is often assessed via a combination of qualitative and quantita...Rock mass quality serves as a vital index for predicting the stability and safety status of rock tunnel faces.In tunneling practice,the rock mass quality is often assessed via a combination of qualitative and quantitative parameters.However,due to the harsh on-site construction conditions,it is rather difficult to obtain some of the evaluation parameters which are essential for the rock mass quality prediction.In this study,a novel improved Swin Transformer is proposed to detect,segment,and quantify rock mass characteristic parameters such as water leakage,fractures,weak interlayers.The site experiment results demonstrate that the improved Swin Transformer achieves optimal segmentation results and achieving accuracies of 92%,81%,and 86%for water leakage,fractures,and weak interlayers,respectively.A multisource rock tunnel face characteristic(RTFC)dataset includes 11 parameters for predicting rock mass quality is established.Considering the limitations in predictive performance of incomplete evaluation parameters exist in this dataset,a novel tree-augmented naive Bayesian network(BN)is proposed to address the challenge of the incomplete dataset and achieved a prediction accuracy of 88%.In comparison with other commonly used Machine Learning models the proposed BN-based approach proved an improved performance on predicting the rock mass quality with the incomplete dataset.By utilizing the established BN,a further sensitivity analysis is conducted to quantitatively evaluate the importance of the various parameters,results indicate that the rock strength and fractures parameter exert the most significant influence on rock mass quality.展开更多
This paper presents a novel cooperative value iteration(VI)-based adaptive dynamic programming method for multi-player differential game models with a convergence proof.The players are divided into two groups in the l...This paper presents a novel cooperative value iteration(VI)-based adaptive dynamic programming method for multi-player differential game models with a convergence proof.The players are divided into two groups in the learning process and adapt their policies sequentially.Our method removes the dependence of admissible initial policies,which is one of the main drawbacks of the PI-based frameworks.Furthermore,this algorithm enables the players to adapt their control policies without full knowledge of others’ system parameters or control laws.The efficacy of our method is illustrated by three examples.展开更多
Incompleteness of information about objects may be the greatest obstruct to performing induction learning from examples. In this paper, the concept of limited-non-symmetric similarity relation is used to formulate a n...Incompleteness of information about objects may be the greatest obstruct to performing induction learning from examples. In this paper, the concept of limited-non-symmetric similarity relation is used to formulate a new definition of approximation to an incomplete information system. With the new definition of approximation to an object set and the concept of attribute value pair, rough-setsbased methodology for certain rule acquisition in an incomplete information system is developed. The algorithm can deal with incomplete data directly and does not require changing the size of the original incomplete system. Experiments show that the algorithm provides precise and simple certain decision rules and is not affected by the missing values.展开更多
It is helpful for people to understand the essence of rough set theory to study the concepts and operations of rough set theory from its information view. In this paper we address knowledge expression and knowledge re...It is helpful for people to understand the essence of rough set theory to study the concepts and operations of rough set theory from its information view. In this paper we address knowledge expression and knowledge reduction in incomplete infolvnation systems from the information view of rough set theory. First, by extending information entropy-based measures in complete information systems, two new measures of incomplete entropy and incomplete conditional entropy are presented for incomplete information systems. And then, based on these measures the problem of knowledge reduction in incomplete information systems is analyzed and the reduct definitions in incomplete information system and incomplete decision table are proposed respectively. Finally, the reduct definitions based on incomplete entropy and the reduct definitions based on similarity relation are compared. Two equivalent relationships between them are proved by theorems and an in equivalent relationship between them is illustrated by an example. The work of this paper extends the research of rough set theory from information view to incomplete information systems and establishes the theoretical basis for seeking efficient algorithm of knowledge acquisition in incomplete information systems.展开更多
This paper studies the nonsystematic Low-Density Parity-Check(LDPC)codes based onSymmetric Balanced Incomplete Block Design(SBIBD).First,it is concluded that the performancedegradation of nonsystematic linear block co...This paper studies the nonsystematic Low-Density Parity-Check(LDPC)codes based onSymmetric Balanced Incomplete Block Design(SBIBD).First,it is concluded that the performancedegradation of nonsystematic linear block codes is bounded by the average row weight of generalizedinverses of their generator matrices and code rate.Then a class of nonsystematic LDPC codes con-structed based on SBIBD is presented.Their characteristics include:both generator matrices andparity-check matrices are sparse and cyclic,which are simple to encode and decode;and almost arbi-trary rate codes can be easily constructed,so they are rate-compatible codes.Because there aresparse generalized inverses of generator matrices,the performance of the proposed codes is only0.15dB away from that of the traditional systematic LDPC codes.展开更多
Introduction: The United States government supported Ugandan government by introducing the District Health Information Software 2 (DHIS2) in 2012 to improve HIV/AIDS surveillance. Districts have yet to fully adopt thi...Introduction: The United States government supported Ugandan government by introducing the District Health Information Software 2 (DHIS2) in 2012 to improve HIV/AIDS surveillance. Districts have yet to fully adopt this relatively new system given a 70.2% reporting completeness achieved nationally between April-June 2013. Methods: The study examined one dependent variable of districts’ reporting completeness against four independent variables: 1) Number of client visits;2) Number of district health units;3) Number of NGOs delivering HIV/AIDS services;and 4) Regional location. The study employed cross-sectional study design which allowed researchers to compare many different variables at the same time. HIV/AIDS program data that were reported by districts into DHIS2 during the period of April to June 2013 were used to assess for reporting completeness. Findings: Districts with the lowest number of client visits (under 2500) achieved the highest mean reporting completeness (81.6%), whereas a range of 2501 - 5000, or over 5001client visits recorded 72.4% and 51.7% respectively. The higher the number of client visits is, the lower the reporting completeness is (p < 0.05). Those districts that were receiving support from only one and two NGO recorded 56.7% and 67.2% respectively. Districts supported by over three NGOs had the highest (80.6%) mean reporting completeness. NGOs-district support was statistically associated with reporting completeness (p < 0.05). The number of health units operated by a district was also significantly associated with reporting completeness (p < 0.05). The regional location of a district was not associated with reporting completeness (p = 0.674). Conclusion: The study results led us to recommend targeted future NGO support to districts with higher patient volume for HIV/AIDS services. Particularly, newly funded NGOs are to be established in districts operating over 40 health units. Incomplete reporting undermines identification of HIV-affected individuals and limits the ability to make evidence-based decisions regarding HIV/AIDS program planning and service delivery.展开更多
基金supported by the State Grid Science and Technology Project 5108-202218280A-2-87-XG.
文摘When multiple LCC-HVDC transmission lines are densely fed into a receiving AC system,voltage dips can easily propagate in the power system,resulting in multiple LCC commutation failures simultaneously.The VSC-HVDC can be used to divide the receiving sys-tem into several interconnected sub-partitions and improve the voltage support capability of the receiving system.Compared with asyn-chronous interconnection,which completely separates the receiving systems with VSC-HVDC,incomplete segmentation with an AC connection is a more pertinent segmenting method for multilayer complex regional power grids.To analyze the voltage support capability of the VSC in incomplete segmentation,a micro-incremental model of the VSC was established,the operating impedance of the VSC was calculated,and the voltage support function of the VSC was quantified.The effect of the fault on the system short-circuit capacity was analyzed,and a calculation method for the multi-infeed short-circuit ratio in an incompletely segmented scenario was obtained.A VSC-segmented model of a two-infeed DC system was built on the EMTDC/PSCAD simulation platform,and the validity of the micro-increment model and accuracy of the proposed conclusions were verified.
基金This researchwas supported by the National Natural Science Foundation of China(Nos.51767017 and 51867015)the Basic Research and Innovation Group Project of Gansu(No.18JR3RA133)the Natural Science Foundation of Gansu(No.21JR7RA258).
文摘At present,the operation and maintenance of photovoltaic power generation systems mainly comprise regular maintenance,breakdown maintenance,and condition-based maintenance,which is very likely to lead to over-or under-repair of equipment.Therefore,a preventive maintenance and replacement strategy for PV power generation systems based on reliability as a constraint is proposed.First,a hybrid failure function with a decreasing service age factor and an increasing failure rate factor is introduced to describe the deterioration of PV power generation equipment,and the equipment is replaced when its reliability drops to the replacement threshold in the last cycle.Then,based on the reliability as a constraint,the average maintenance cost and availability of the equipment are considered,and the non-periodic incomplete maintenance model of the PV power generation system is established to obtain the optimal number of repairs,each maintenance cycle and the replacement cycle of the PV power generation system components.Next,the inverter of a PV power plant is used as a research object.The model in this paper is compared and analyzed with the equal cycle maintenance model without considering reliability and the maintenance model without considering the equipment replacement threshold,Through model comparison,when the optimal maintenance strategy is(0.80,4),the average maintenance cost of this paper’s model are decreased by 20.3%and 5.54%and the availability is increased by 0.2395% and 0.0337%,respectively,compared with the equal-cycle maintenance model without considering the reliability constraint and the maintenance model without considering the equipment replacement threshold.Therefore,this maintenance model can ensure the high reliability of PV plant operation while increasing the equipment availability to improve the system economy.
基金supported by National Natural Science Foundation of China(Project approval number 82201825).
文摘Objective:To compare the clinical efficacy of mifepristone-misoprostol medical management versus surgical curettage for first-trimester missed miscarriage,and to establish evidence-based sonographic cutoff values predictive of incomplete abortion requiring surgical intervention.Methods:We retrospectively analyzed a cohort of 702 women diagnosed with first-trimester missed miscarriage between January 2020 and May 2023.Demographic characteristics and ultrasound parameters were systematically recorded.Receiver operating characteristic(ROC)curve analysis was performed to establish optimal sonographic cutoff values for predicting incomplete abortion requiring surgical intervention.Results:146 patients received medical treatment(mifepristone and misoprostol)and 556 underwent surgical curettage.At the 1-month follow-up,the medical group showed significantly greater endometrial thickness and longer postoperative bleeding duration than the surgical group(P<0.05).The menstrual volume reduction rate(23.56%)was significantly lower in the medical group than in the surgical group.The incomplete abortion rate was higher in the medical group(17.12%,25/146)than in the surgical group(2.88%,16/556).Among the medical group,14 patients(9.59%)required curettage due to incomplete abortion,while 11 cases resolved spontaneously after prolonged medication.ROC curve analysis identified two cut-off values indicating the need for surgical intervention:endometrial thickness>1.21 cm at 24 h post-medical abortion,and residual mass diameter>0.95 cm at 7 days post-medical abortion.Conclusions:Medical management of first-trimester missed miscarriage using mifepristone-misoprostol demonstrates comparable efficacy to surgical curettage.An endometrial thickness>1.21 cm at 24 h or residual tissue diameter>0.95 cm at 7 days post-medical abortion should prompt consideration of incomplete abortion.
基金supported by the Aeronautical Science Foundation of China(2020Z023053002).
文摘High complexity and uncertainty of air combat pose significant challenges to target intention prediction.Current interpolation methods for data pre-processing and wrangling have limitations in capturing interrelationships among intricate variable patterns.Accordingly,this study proposes a Mogrifier gate recurrent unit-D(Mog-GRU-D)model to address the com-bat target intention prediction issue under the incomplete infor-mation condition.The proposed model directly processes miss-ing data while reducing the independence between inputs and output states.A total of 1200 samples from twelve continuous moments are captured through the combat simulation system,each of which consists of seven dimensional features.To bench-mark the experiment,a missing valued dataset has been gener-ated by randomly removing 20%of the original data.Extensive experiments demonstrate that the proposed model obtains the state-of-the-art performance with an accuracy of 73.25%when dealing with incomplete information.This study provides possi-ble interpretations for the principle of target interactive mecha-nism,highlighting the model’s effectiveness in potential air war-fare implementation.
文摘The widespread usage of rechargeable batteries in portable devices,electric vehicles,and energy storage systems has underscored the importance for accurately predicting their lifetimes.However,data scarcity often limits the accuracy of prediction models,which is escalated by the incompletion of data induced by the issues such as sensor failures.To address these challenges,we propose a novel approach to accommodate data insufficiency through achieving external information from incomplete data samples,which are usually discarded in existing studies.In order to fully unleash the prediction power of incomplete data,we have investigated the Multiple Imputation by Chained Equations(MICE)method that diversifies the training data through exploring the potential data patterns.The experimental results demonstrate that the proposed method significantly outperforms the baselines in the most considered scenarios while reducing the prediction root mean square error(RMSE)by up to 18.9%.Furthermore,we have also observed that the penetration of incomplete data benefits the explainability of the prediction model through facilitating the feature selection.
基金supported by the Aeronautical Science Foundation of China(20220001057001)an Open Project of the National Key Laboratory of Air-based Information Perception and Fusion(202437)
文摘In this paper,a distributed adaptive dynamic programming(ADP)framework based on value iteration is proposed for multi-player differential games.In the game setting,players have no access to the information of others'system parameters or control laws.Each player adopts an on-policy value iteration algorithm as the basic learning framework.To deal with the incomplete information structure,players collect a period of system trajectory data to compensate for the lack of information.The policy updating step is implemented by a nonlinear optimization problem aiming to search for the proximal admissible policy.Theoretical analysis shows that by adopting proximal policy searching rules,the approximated policies can converge to a neighborhood of equilibrium policies.The efficacy of our method is illustrated by three examples,which also demonstrate that the proposed method can accelerate the learning process compared with the centralized learning framework.
基金supported by the National Natural Science Foundation of China(61202473)the Fundamental Research Funds for Central Universities(JUSRP111A49)+1 种基金"111 Project"(B12018)the Priority Academic Program Development of Jiangsu Higher Education Institutions
文摘For the fault detection and diagnosis problem in largescale industrial systems, there are two important issues： the missing data samples and the non-Gaussian property of the data. However, most of the existing data-driven methods cannot be able to handle both of them. Thus, a new Bayesian network classifier based fault detection and diagnosis method is proposed. At first, a non-imputation method is presented to handle the data incomplete samples, with the property of the proposed Bayesian network classifier, and the missing values can be marginalized in an elegant manner. Furthermore, the Gaussian mixture model is used to approximate the non-Gaussian data with a linear combination of finite Gaussian mixtures, so that the Bayesian network can process the non-Gaussian data in an effective way. Therefore, the entire fault detection and diagnosis method can deal with the high-dimensional incomplete process samples in an efficient and robust way. The diagnosis results are expressed in the manner of probability with the reliability scores. The proposed approach is evaluated with a benchmark problem called the Tennessee Eastman process. The simulation results show the effectiveness and robustness of the proposed method in fault detection and diagnosis for large-scale systems with missing measurements.
基金This work was supported by the National Natural Science Foundation of China (No. 50275150)the Foundation of Robotics Laboratory, Chinese Academy of Sciences( No. RL200002).
文摘A new and intelligent design method for PID controller with incomplete derivation is proposed based on the ant system algorithm ( ASA) . For a given control system with this kind of PID controller, a group of optimal PID controller parameters K p * , T i * , and T d * can be obtained by taking the overshoot, settling time, and steady-state error of the system's unit step response as the performance indexes and by use of our improved ant system algorithm. K p * , T i * , and T d * can be used in real-time control. This kind of controller is called the ASA-PID controller with incomplete derivation. To verify the performance of the ASA-PID controller, three different typical transfer functions were tested, and three existing typical tuning methods of PID controller parameters, including the Ziegler-Nichols method (ZN),the genetic algorithm (GA),and the simulated annealing (SA), were adopted for comparison. The simulation results showed that the ASA-PID controller can be used to control different objects and has better performance compared with the ZN-PID and GA-PID controllers, and comparable performance compared with the SA-PID controller.
基金This work was supported by the National Natural Science Foundation of China （Grant Nos. 61170165, 61100116, 61272419, 61373062）, Natural Science Foundation of Jiangsu Province of China （BK2011492, BK2012700, BK20130471）, Qing Lan Project of JiangsuProvince of China, Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information （Nanjing University of Science and Tech- nology）, Ministry of Education （30920130122005）, Key Laboratory of Arti- ficial Intelligence of Sichuan Province （2013RYJ03）, Natural Science Foun- dation of Jiangsu Higher Education Institutions of China （13KJB520003, 13KJD520008）.
文摘Presently, the notion of multigranulation has been brought to our attention. In this paper, the multigranulation technique is introduced into incomplete information systems. Both tolerance relations and maximal consistent blocks are used to construct multigranulation rough sets. Not only are the basic properties about these models studied, but also the relationships between different multigranulation rough sets are explored. It is shown that by using maximal consistent blocks, the greater lower approximation and the same upper approximation as from tolerance relations can be obtained. Such a result is consistent with that of a single-granulation framework.
基金supported by the National Natural Science Foundation of China(61363047)the Jiangxi Education Department(GJJ13760)the Science and Technology Support Foundation of Jiangxi Province(20111BBE50008)
文摘This paper focuses on fast algorithm for computing the assignment reduct in inconsistent incomplete decision systems. It is quite inconvenient to judge the assignment reduct directly ac-cording to its definition. We propose the judgment theorem for the assignment reduct in the inconsistent incomplete decision system, which greatly simplifies judging this type reduct. On such basis, we derive a novel attribute significance measure and construct the fast assignment reduction algorithm （F-ARA）, intended for com-puting the assignment reduct in inconsistent incomplete decision systems. Final y, we make a comparison between F-ARA and the discernibility matrix-based method by experiments on 13 Univer-sity of California at Irvine （UCI） datasets, and the experimental results prove that F-ARA is efficient and feasible.
基金Projects(10871031, 60474070) supported by the National Natural Science Foundation of ChinaProject(07A001) supported by the Scientific Research Fund of Hunan Provincial Education Department, China
文摘Based on the rough set theory which is a powerful tool in dealing with vagueness and uncertainty, an algorithm to mine association rules in incomplete information systems was presented and the support and confidence were redefined. The algorithm can mine the association rules with decision attributes directly without processing missing values. Using the incomplete dataset Mushroom from UCI machine learning repository, the new algorithm was compared with the classical association rules mining algorithm based on Apriori from the number of rules extracted, testing accuracy and execution time. The experiment results show that the new algorithm has advantages of short execution time and high accuracy.
基金supported by the National Natural Science Foundation of China(81673828).
文摘Objective:To evaluate the effectiveness and safety of Chinese herbal medicines(CHMs)for incomplete immune reconstruction in patients with HIV/AIDS.Methods:Eight electronic databases were searched for randomized controlled trials(RCTs)on the use of CHM for patients with HIV/AIDS with incomplete immune reconstruction.Outcomes included CD4þcell count,quality of life,and adverse events/effects.The Cochrane Risk of Bias was employed to evaluate the methodological quality of the included RCTs.Results:We identified 13 eligible RCTs,with an overall high risk of bias,on 10 different CHMs.There was a significant increase in CD4þcell count after the use of Jianpi Yiqi medicinal paste for 3 months;tripterygium glycosides tablets(TGTs)for 3 months(mean difference[MD]52.63 cells/mL,95%confidence interval[CI,46.98,58.28]),6,9,and 12 months;Wenshen Jianpi granules for 6 months;Shenling Fuzheng capsules for 6 months(MD 49.53 cells/mL,95%CI[8.45,90.61])and 12 months;Aikeqing granules for 9 months(MD 61.51 cells/mL,95%CI[16.25,106.77])and 12 months;Guipi decoction for 12 months;Mianyi No.2 granules(JT)for 12 and 18 months;and Chinese medicine granules for 18 months.The increase in the mean difference of CD4þcell count from 6 to 18 months was larger in Chinese medicine granules and Mianyi No.2 granules(JT).Guipi decoction and Jianpi Qushi decoction improved the Karnofsky score.Four RCTs reported the outcome of adverse events/effects,while four cases of minor adverse effects were reported in the TGTs group.Conclusion:Jianpi Yiqi medicinal paste,Wenshen Jianpi granules,Shenling Fuzheng capsules,Aikeqing granules,Guipi decoction,and TGTs may be effective in increasing CD4þwithin 12 months,and Mianyi No.2 granules(JT)and Chinese medicine granules may show long-term effects.High-quality large RCTs on the effectiveness and safety of CHMs are still warranted.
基金National Natural Science Foundation of China,Grant/Award Numbers:61,662,001,61,762,002Young and Middle-aged Talents Training Program of National Ethnic Affair Commission,Grant/AwardNurnber:2016GQR06Ningxia First-class Construction Discipline Program,Grant/AwardNumber:NXYLXK2017B09,Open Foundation ofNingxia Kcy Laboratory of Intelligcnt Informationand Big Data Processing,Grant/Award Number:2019KLBD006。
文摘The tolerance rough set is developed as one of the outstanding extensions of the Pawlak's rough set model under incomplete information,and the limited tolerance relation is developed to overcome the problem that objects leniently satisfy the tolerance relation.However,the classification based on the limited tolerance relationship cannot reflect the matching degree of uncertain information of objects.In this article,we explore the influence of null values in an incomplete system,and propose the constrained tolerance relation based on the matching degree of uncertain information of objects.The proposed rough set based on the constrained tolerance relation can provide a more detailed structure of an object class through threshold.Proofs and example analyses further show the rationality and superiority of the proposed model.
基金Supported by the National Natural Science Foundation of China（No.60605019）
文摘In order to understand the security conditions of the incomplete interval-valued information system （IllS） and acquire the corresponding solution of security problems, this paper proposes a multi-attribute group decision- making （MAGDM） security assessment method based on the technique for order performance by similarity to ideal solution （TOPSIS）. For IllS with preference information, combining with dominance-based rough set approach （DRSA）, the effect of incomplete interval-valued information on decision results is discussed. For the imprecise judgment matrices, the security attribute weight can be obtained using Gibbs sampling. A numerical example shows that the proposed method can acquire some valuable knowledge hidden in the incomplete interval-valued information. The effectiveness of the proposed method in the synthetic security assessment for IIIS is verified.
基金supported by the National Natural Science Foundation of China(Nos.52279107 and 52379106)the Qingdao Guoxin Jiaozhou Bay Second Submarine Tunnel Co.,Ltd.,the Academician and Expert Workstation of Yunnan Province(No.202205AF150015)the Science and Technology Innovation Project of YCIC Group Co.,Ltd.(No.YCIC-YF-2022-15)。
文摘Rock mass quality serves as a vital index for predicting the stability and safety status of rock tunnel faces.In tunneling practice,the rock mass quality is often assessed via a combination of qualitative and quantitative parameters.However,due to the harsh on-site construction conditions,it is rather difficult to obtain some of the evaluation parameters which are essential for the rock mass quality prediction.In this study,a novel improved Swin Transformer is proposed to detect,segment,and quantify rock mass characteristic parameters such as water leakage,fractures,weak interlayers.The site experiment results demonstrate that the improved Swin Transformer achieves optimal segmentation results and achieving accuracies of 92%,81%,and 86%for water leakage,fractures,and weak interlayers,respectively.A multisource rock tunnel face characteristic(RTFC)dataset includes 11 parameters for predicting rock mass quality is established.Considering the limitations in predictive performance of incomplete evaluation parameters exist in this dataset,a novel tree-augmented naive Bayesian network(BN)is proposed to address the challenge of the incomplete dataset and achieved a prediction accuracy of 88%.In comparison with other commonly used Machine Learning models the proposed BN-based approach proved an improved performance on predicting the rock mass quality with the incomplete dataset.By utilizing the established BN,a further sensitivity analysis is conducted to quantitatively evaluate the importance of the various parameters,results indicate that the rock strength and fractures parameter exert the most significant influence on rock mass quality.
基金supported by the Industry-University-Research Cooperation Fund Project of the Eighth Research Institute of China Aerospace Science and Technology Corporation (USCAST2022-11)Aeronautical Science Foundation of China (20220001057001)。
文摘This paper presents a novel cooperative value iteration(VI)-based adaptive dynamic programming method for multi-player differential game models with a convergence proof.The players are divided into two groups in the learning process and adapt their policies sequentially.Our method removes the dependence of admissible initial policies,which is one of the main drawbacks of the PI-based frameworks.Furthermore,this algorithm enables the players to adapt their control policies without full knowledge of others’ system parameters or control laws.The efficacy of our method is illustrated by three examples.
文摘Incompleteness of information about objects may be the greatest obstruct to performing induction learning from examples. In this paper, the concept of limited-non-symmetric similarity relation is used to formulate a new definition of approximation to an incomplete information system. With the new definition of approximation to an object set and the concept of attribute value pair, rough-setsbased methodology for certain rule acquisition in an incomplete information system is developed. The algorithm can deal with incomplete data directly and does not require changing the size of the original incomplete system. Experiments show that the algorithm provides precise and simple certain decision rules and is not affected by the missing values.
基金Sponsored by the Youth Natural Science Foundation of Yantai Normal University.
文摘It is helpful for people to understand the essence of rough set theory to study the concepts and operations of rough set theory from its information view. In this paper we address knowledge expression and knowledge reduction in incomplete infolvnation systems from the information view of rough set theory. First, by extending information entropy-based measures in complete information systems, two new measures of incomplete entropy and incomplete conditional entropy are presented for incomplete information systems. And then, based on these measures the problem of knowledge reduction in incomplete information systems is analyzed and the reduct definitions in incomplete information system and incomplete decision table are proposed respectively. Finally, the reduct definitions based on incomplete entropy and the reduct definitions based on similarity relation are compared. Two equivalent relationships between them are proved by theorems and an in equivalent relationship between them is illustrated by an example. The work of this paper extends the research of rough set theory from information view to incomplete information systems and establishes the theoretical basis for seeking efficient algorithm of knowledge acquisition in incomplete information systems.
基金the National Natural Science Foundation of China(No.60272009,No.60472045,and No.60496313).
文摘This paper studies the nonsystematic Low-Density Parity-Check(LDPC)codes based onSymmetric Balanced Incomplete Block Design(SBIBD).First,it is concluded that the performancedegradation of nonsystematic linear block codes is bounded by the average row weight of generalizedinverses of their generator matrices and code rate.Then a class of nonsystematic LDPC codes con-structed based on SBIBD is presented.Their characteristics include:both generator matrices andparity-check matrices are sparse and cyclic,which are simple to encode and decode;and almost arbi-trary rate codes can be easily constructed,so they are rate-compatible codes.Because there aresparse generalized inverses of generator matrices,the performance of the proposed codes is only0.15dB away from that of the traditional systematic LDPC codes.
文摘Introduction: The United States government supported Ugandan government by introducing the District Health Information Software 2 (DHIS2) in 2012 to improve HIV/AIDS surveillance. Districts have yet to fully adopt this relatively new system given a 70.2% reporting completeness achieved nationally between April-June 2013. Methods: The study examined one dependent variable of districts’ reporting completeness against four independent variables: 1) Number of client visits;2) Number of district health units;3) Number of NGOs delivering HIV/AIDS services;and 4) Regional location. The study employed cross-sectional study design which allowed researchers to compare many different variables at the same time. HIV/AIDS program data that were reported by districts into DHIS2 during the period of April to June 2013 were used to assess for reporting completeness. Findings: Districts with the lowest number of client visits (under 2500) achieved the highest mean reporting completeness (81.6%), whereas a range of 2501 - 5000, or over 5001client visits recorded 72.4% and 51.7% respectively. The higher the number of client visits is, the lower the reporting completeness is (p < 0.05). Those districts that were receiving support from only one and two NGO recorded 56.7% and 67.2% respectively. Districts supported by over three NGOs had the highest (80.6%) mean reporting completeness. NGOs-district support was statistically associated with reporting completeness (p < 0.05). The number of health units operated by a district was also significantly associated with reporting completeness (p < 0.05). The regional location of a district was not associated with reporting completeness (p = 0.674). Conclusion: The study results led us to recommend targeted future NGO support to districts with higher patient volume for HIV/AIDS services. Particularly, newly funded NGOs are to be established in districts operating over 40 health units. Incomplete reporting undermines identification of HIV-affected individuals and limits the ability to make evidence-based decisions regarding HIV/AIDS program planning and service delivery.
