Due to the uneven seabed and heaving of soil during pumping,incomplete soil plugs may occur during the installation of bucket foundations,and the impacts on the bearing capacities of bucket foundations need to be eval...Due to the uneven seabed and heaving of soil during pumping,incomplete soil plugs may occur during the installation of bucket foundations,and the impacts on the bearing capacities of bucket foundations need to be evaluated.In this paper,the contact ratio(the ratio of the top diameter of the soil plug to the diameter of the bucket)and the soil plug ratio(the ratio of the soil heave height to the skirt height)are defined to describe the shape and size of the incomplete soil plug.Then,finite element models are established to investigate the bearing capacities of bucket foundations with incomplete soil plugs and the influences of the contact ratios,and the soil plug ratios on the bearing capacities are analyzed.The results show that the vertical bearing capacity of bucket foundations in homogeneous soil continuously improves with the increase of the contact ratio.However,in normally consolidated soil,the vertical bearing capacity barely changes when the contact ratio is smaller than 0.75,while the bearing capacity suddenly increases when the contact ratio increases to 1 due to the change of failure mode.The contact ratio hardly affects the horizontal bearing capacity of bucket foundations.Moreover,the moment bearing capacity improves with the increase of the contact ratio for small aspect ratios,but hardly varies with increasing contact ratio for aspect ratios larger than 0.5.Consequently,the reduction coefficient method is proposed based on this analysis to calculate the bearing capacities of bucket foundations considering the influence of incomplete soil plugs.The comparison results show that the proposed reduction coefficient method can be used to evaluate the influences of incomplete soil plug on the bearing capacities of bucket foundations.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
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
According to the disease module hypothesis,the cellular components associated with a disease segregate in the same neighborhood of the human interactome,the map of biologically relevant molecular interactions.Yet,give...According to the disease module hypothesis,the cellular components associated with a disease segregate in the same neighborhood of the human interactome,the map of biologically relevant molecular interactions.Yet,given the incompleteness of the interactome and the limited knowledge of disease-associated genes,it is not obvious if the available data have sufficient coverage to map out modules associated with each disease.展开更多
According to the disease module hypothesis,the cellular components associated with a disease segregate in the same neighborhood of the human interactome,the map of biologically relevant molecular interactions.Yet,give...According to the disease module hypothesis,the cellular components associated with a disease segregate in the same neighborhood of the human interactome,the map of biologically relevant molecular interactions.Yet,given the incompleteness of the interactome and the limited knowledge of disease-associated genes,it is not obvious if the available data have sufficient coverage to map out modules associated with each disease.Here we derive mathematical conditions for the identifiability of disease modules and show that the network-based location of each disease module determines its pathobiological relationship to other diseases.For example,diseases with overlapping network modules show significant coexpression patterns,symptom similarity,and comorbidity,whereas diseases residing in separated network neighborhoods are phenotypically distinct.These tools represent an interactome-based platform to predict molecular commonalities between phenotypically related diseases,even if they do not share primary disease genes.展开更多
Due to the high inherent uncertainty of renewable energy,probabilistic day-ahead wind power forecasting is crucial for modeling and controlling the uncertainty of renewable energy smart grids in smart cities.However,t...Due to the high inherent uncertainty of renewable energy,probabilistic day-ahead wind power forecasting is crucial for modeling and controlling the uncertainty of renewable energy smart grids in smart cities.However,the accuracy and reliability of high-resolution day-ahead wind power forecasting are constrained by unreliable local weather prediction and incomplete power generation data.This article proposes a physics-informed artificial intelligence(AI)surrogates method to augment the incomplete dataset and quantify its uncertainty to improve wind power forecasting performance.The incomplete dataset,built with numerical weather prediction data,historical wind power generation,and weather factors data,is augmented based on generative adversarial networks.After augmentation,the enriched data is then fed into a multiple AI surrogates model constructed by two extreme learning machine networks to train the forecasting model for wind power.Therefore,the forecasting models’accuracy and generalization ability are improved by mining the implicit physics information from the incomplete dataset.An incomplete dataset gathered from a wind farm in North China,containing only 15 days of weather and wind power generation data withmissing points caused by occasional shutdowns,is utilized to verify the proposed method’s performance.Compared with other probabilistic forecastingmethods,the proposed method shows better accuracy and probabilistic performance on the same incomplete dataset,which highlights its potential for more flexible and sensitive maintenance of smart grids in smart cities.展开更多
Cooperative autonomous air combat of multiple unmanned aerial vehicles(UAVs)is one of the main combat modes in future air warfare,which becomes even more complicated with highly changeable situation and uncertain info...Cooperative autonomous air combat of multiple unmanned aerial vehicles(UAVs)is one of the main combat modes in future air warfare,which becomes even more complicated with highly changeable situation and uncertain information of the opponents.As such,this paper presents a cooperative decision-making method based on incomplete information dynamic game to generate maneuver strategies for multiple UAVs in air combat.Firstly,a cooperative situation assessment model is presented to measure the overall combat situation.Secondly,an incomplete information dynamic game model is proposed to model the dynamic process of air combat,and a dynamic Bayesian network is designed to infer the tactical intention of the opponent.Then a reinforcement learning framework based on multiagent deep deterministic policy gradient is established to obtain the perfect Bayes-Nash equilibrium solution of the air combat game model.Finally,a series of simulations are conducted to verify the effectiveness of the proposed method,and the simulation results show effective synergies and cooperative tactics.展开更多
With the rapid development of the economy,the scale of the power grid is expanding.The number of power equipment that constitutes the power grid has been very large,which makes the state data of power equipment grow e...With the rapid development of the economy,the scale of the power grid is expanding.The number of power equipment that constitutes the power grid has been very large,which makes the state data of power equipment grow explosively.These multi-source heterogeneous data have data differences,which lead to data variation in the process of transmission and preservation,thus forming the bad information of incomplete data.Therefore,the research on data integrity has become an urgent task.This paper is based on the characteristics of random chance and the Spatio-temporal difference of the system.According to the characteristics and data sources of the massive data generated by power equipment,the fuzzy mining model of power equipment data is established,and the data is divided into numerical and non-numerical data based on numerical data.Take the text data of power equipment defects as the mining material.Then,the Apriori algorithm based on an array is used to mine deeply.The strong association rules in incomplete data of power equipment are obtained and analyzed.From the change trend of NRMSE metrics and classification accuracy,most of the filling methods combined with the two frameworks in this method usually show a relatively stable filling trend,and will not fluctuate greatly with the growth of the missing rate.The experimental results show that the proposed algorithm model can effectively improve the filling effect of the existing filling methods on most data sets,and the filling effect fluctuates greatly with the increase of the missing rate,that is,with the increase of the missing rate,the improvement effect of the model for the existing filling methods is higher than 4.3%.Through the incomplete data clustering technology studied in this paper,a more innovative state assessment of smart grid reliability operation is carried out,which has good research value and reference significance.展开更多
A generalized flexibility–based objective function utilized for structure damage identification is constructed for solving the constrained nonlinear least squares optimized problem. To begin with, the generalized fle...A generalized flexibility–based objective function utilized for structure damage identification is constructed for solving the constrained nonlinear least squares optimized problem. To begin with, the generalized flexibility matrix (GFM) proposed to solve the damage identification problem is recalled and a modal expansion method is introduced. Next, the objective function for iterative optimization process based on the GFM is formulated, and the Trust-Region algorithm is utilized to obtain the solution of the optimization problem for multiple damage cases. And then for computing the objective function gradient, the sensitivity analysis regarding design variables is derived. In addition, due to the spatial incompleteness, the influence of stiffness reduction and incomplete modal measurement data is discussed by means of two numerical examples with several damage cases. Finally, based on the computational results, it is evident that the presented approach provides good validity and reliability for the large and complicated engineering structures.展开更多
Colonoscopic polypectomy is extremely effective in protecting against colorectal cancers,and recognition of adenomas by colonoscopy is of paramount importance in preventing colorectal cancer(CRC)and CRC-associated mor...Colonoscopic polypectomy is extremely effective in protecting against colorectal cancers,and recognition of adenomas by colonoscopy is of paramount importance in preventing colorectal cancer(CRC)and CRC-associated mortality.Incomplete polyp resection(IPR)occurs routinely in medical practice following polypectomy.We conducted a comprehensive literature search to identify studies that reported on the potential risk factors for IPR using MEDLINE,EMBASE,and PubMed.Publication time was limited between January 2004 and July 2021.Our search revealed assessments of the position,morphology,and histologic variation of the polypsdas well as the relevant skills that may interfere with IPR.The included studies showed that colonic polyps with a diameter>20 mm and proximal in location should be dealt with cautiously.For smaller polyps,cold-snare polypectomy appeared to be the most effective method used to accomplish comprehensive polyp removal.In addition,endoscopist experience in narrow-band imaging in polyp detection were also associated with IPR.Therefore,polypectomy should be performed cautiously if the polyp growth is expected to be cancerous and situated in the proximal portion of the colon or rectum,and modalities should be standardized so as to lower the potential risk for IPR.展开更多
AIM:To evaluate significant risk factors for incomplete colonoscopy at a Japanese academic hospital.METHODS:A total of 11812 consecutive Japanese people were identified who underwent a colonoscopy at an academic hospi...AIM:To evaluate significant risk factors for incomplete colonoscopy at a Japanese academic hospital.METHODS:A total of 11812 consecutive Japanese people were identified who underwent a colonoscopy at an academic hospital.A multiple logistic regression model was used to evaluate retrospectively the significant risk factors for incomplete colonoscopy.RESULTS:The cecal intubation rate was 95.0%.By univariate analysis,age,female sex,poor bowel cleansing,and a history of abdominal or pelvic surgery were significant risk factors for incomplete colonoscopy(P<0.001).Moreover,age-and sex-adjusted analysis showed that significant risk factors for incomplete colonoscopy were female sex(OR=1.38,95%CI:1.17-1.64,P=0.0002),age≥60 years old(OR=1.44,95%CI:1.22-1.71,P<0.0001),a history of prior abdominal or pelvic surgery(OR=1.55,95%CI:1.28-1.86,P<0.0001),poor bowel cleansing(OR=4.64,95%CI:3.69-5.84,P<0.0001),and inflammatory bowel disease(IBD)(OR=1.48,95%CI:1.13-1.95,P=0.0048).In Japanese men,by age-adjusted analysis,IBD(OR=1.69,95%CI:1.18-2.43,P=0.005)was an independent risk factor for incomplete colonoscopy.CONCLUSION:Several characteristics in the Japanese population were identified that could predict technical difficulty with colonoscopy.展开更多
AIM:To identify patient risk factors associated with incomplete small bowel capsule endoscopy(CE) studies.METHODS:Data from all CE procedures performed at St.Paul's Hospital in Vancouver,British Columbia,Canada,be...AIM:To identify patient risk factors associated with incomplete small bowel capsule endoscopy(CE) studies.METHODS:Data from all CE procedures performed at St.Paul's Hospital in Vancouver,British Columbia,Canada,between December 2001 and June 2008 were collected and analyzed on a retrospective basis.Data collection for complete and incomplete CE study groups included patient demographics as well as a number of potential risk factors for incomplete CE including indication for the procedure,hospitalization,diabetes mellitus with or without end organ damage,limitations in mobility,renal insufficiency,past history of bowel obstruction,abdominal surgery,abdominal radiation therapy and opiate use.Risk factors were analyzed using a univariable and multivariable logistic regression model.RESULTS:From a total of 535 CE procedures performed,158 were incomplete(29.5%).The univariable analysis showed that CE procedures performed for overt gastrointestinal bleeding(P = 0.002),and for patients with a prior history of abdominal surgery(P = 0.023) or bowel obstruction(P = 0.023) were significantly associated with incomplete CE studies.Patients on opiate medications(P = 0.094) as well as hospitalized patients(P = 0.054) were not statistically significant,but did show a trend towards incomplete CE.The multivariable analysis showed that independent risk factors for an incomplete CE procedure include prior history of bowel obstruction [odds ratios(OR) 2.77,P = 0.02,95% confidence intervals(CI):1.17-6.56] and procedures performed for gastrointestinal bleeding(Occult OR 2.04,P = 0.037,95% CI:1.04-4.02 and Overt OR 2.69,P = 0.002,95% CI:1.44-5.05).Patients with a prior history of abdominal surgery(OR 1.46,P = 0.068,95% CI:0.97-2.19),those taking opiate medications(OR 1.54,P = 0.15,95% CI:0.86-2.76) and hospitalized patients(OR 1.82,P = 0.124,95% CI:0.85-3.93) showed a trend towards statistical significance.CONCLUSION:We have identified a number of risk factors for incomplete CE procedures that can be used to risk-stratify patients and guide interventions to improve completion rates.展开更多
At present, the studies on multi-team antagonistic games(MTAGs) are still in the early stage, because this complicated problem involves not only incompleteness of information and conflict of interests, but also select...At present, the studies on multi-team antagonistic games(MTAGs) are still in the early stage, because this complicated problem involves not only incompleteness of information and conflict of interests, but also selection of antagonistic targets.Therefore, based on the previous researches, a new framework is proposed in this paper, which is dynamic multi-team antagonistic games with incomplete information(DMTAGII) model.For this model, the corresponding concept of perfect Bayesian Nash equilibrium(PBNE) is established and the existence of PBNE is also proved. Besides, an interactive iteration algorithm is introduced according to the idea of the best response for solving the equilibrium. Then, the scenario of multiple unmanned aerial vehicles(UAVs) against multiple military targets is studied to solve the problems of tactical decision making based on the DMTAGII model. In the process of modeling, the specific expressions of strategy, status and payoff functions of the games are considered, and the strategy is coded to match the structure of genetic algorithm so that the PBNE can be solved by combining the genetic algorithm and the interactive iteration algorithm.Finally, through the simulation the feasibility and effectiveness of the DMTAGII model are verified. Meanwhile, the calculated equilibrium strategies are also found to be realistic, which can provide certain references for improving the autonomous ability of UAV systems.展开更多
An optimal PID controller with incomplete derivation is proposed based on fuzzy inference and the geneticalgorithm, which is called the fuzzy-GA PID controller with incomplete derivation. It consists of the off-line p...An optimal PID controller with incomplete derivation is proposed based on fuzzy inference and the geneticalgorithm, which is called the fuzzy-GA PID controller with incomplete derivation. It consists of the off-line part andthe on-line part. In the off-line part, by taking the overshoot, rise time, and settling time of system unit step re-sponse as the performance indexes and by using the genetic algorithm, a group of optimal PID parameters K*p , Ti* ,and Tj are obtained, which are used as the initial values for the on-line tuning of PID parameters. In the on-linepart, based on K; , Ti* , and T*d and according to the current system error e and its time derivative, a dedicatedprogram is written, which is used to optimize and adjust the PID parameters on line through a fuzzy inference mech-anism to ensure that the system response has optimal dynamic and steady-state performance. The controller has beenused to control the D. C. motor of the intelligent bionic artificial leg designed by the authors. The result of computersimulation shows that this kind of optimal PID controller has excellent control performance and robust performance.展开更多
AIM:To evaluate whether the use of real time viewer(RTV)and administration of domperidone to patients with delayed gastric passage of the capsule could reduce the rate of incomplete examinations(IE)and improve the dia...AIM:To evaluate whether the use of real time viewer(RTV)and administration of domperidone to patients with delayed gastric passage of the capsule could reduce the rate of incomplete examinations(IE)and improve the diagnostic yield of small bowel capsule endoscopy(SBCE).METHODS:Prospective single center interventional study,from June 2012 to February 2013.Capsule location was systematically checked one hour after ingestion using RTV.If it remained in the stomach,the patient received 10 mg domperidone per os and the location of the capsule was rechecked after 30 min.If the capsule remained in the stomach a second dose of10 mg of domperidone was administered orally.After another 30 min the position was rechecked and if the capsule remained in the stomach,it was passed into the duodenum by upper gastrointestinal(GI)endoscopy.The rate of IE and diagnostic yield of SBCE were compared with those of examinations performed before the use of RTV or domperidone in our Department(control group,January 2009-May 2012).RESULTS:Both groups were similar regarding age,sex,indication,inpatient status and surgical history.The control group included 307 patients,with 48(15.6%)IE.The RTV group included 82 patients,with3(3.7%)IE,P=0.003.In the control group,average gastric time was significantly longer in patients with IE than in patients with complete examination of the small bowel(77 min vs 26 min,P=0.003).In the RTV group,the capsule remained in the stomach one hour after ingestion in 14/82 patients(17.0%)vs 48/307(15.6%)in the control group,P=0.736.Domperidone did not significantly affect small bowel transit time(260min vs 297 min,P=0.229).The capsule detected positive findings in 39%of patients in the control group and 49%in the RTV group(P=0.081).CONCLUSION:The use of RTV and selective administration of domperidone to patients with delayed gastric passage of the capsule significantly reduces incomplete examinations,with no effect on small bowel transit time or diagnostic yield.展开更多
Energy consumption prediction of a CNC machining process is important for energy efficiency optimization strategies.To improve the generalization abilities,more and more parameters are acquired for energy prediction m...Energy consumption prediction of a CNC machining process is important for energy efficiency optimization strategies.To improve the generalization abilities,more and more parameters are acquired for energy prediction modeling.While the data collected from workshops may be incomplete because of misoperation,unstable network connections,and frequent transfers,etc.This work proposes a framework for energy modeling based on incomplete data to address this issue.First,some necessary preliminary operations are used for incomplete data sets.Then,missing values are estimated to generate a new complete data set based on generative adversarial imputation nets(GAIN).Next,the gene expression programming(GEP)algorithm is utilized to train the energy model based on the generated data sets.Finally,we test the predictive accuracy of the obtained model.Computational experiments are designed to investigate the performance of the proposed framework with different rates of missing data.Experimental results demonstrate that even when the missing data rate increases to 30%,the proposed framework can still make efficient predictions,with the corresponding RMSE and MAE 0.903 k J and 0.739 k J,respectively.展开更多
Nowadays, the network defence policy selection using game model of incomplete information ignores the type of the defender, which quantifies cost simply, resulting in unreasonable defence policies selection. Aiming at...Nowadays, the network defence policy selection using game model of incomplete information ignores the type of the defender, which quantifies cost simply, resulting in unreasonable defence policies selection. Aiming at the problem, we use Bayesian game theory to model the active defence policy selection. We take the types of both the attacker and the defender into consideration. Besides, the traditional quantization method is enhanced. Then, we calculate the equilibrium of static Bayesian game. Based on the analysis of the equilibrium, we select the optimal defence policy through the prediction for attackers' actions. The paper calculates the defence effectiveness of defence policies and provides a defence policies selection algorithm. Ultimately, we present an example to verify the effectiveness of the method and model proposed in the paper.展开更多
The different conditions of use of a component result in a variety of damage levels.Therefore,excluding differences in shape and size,used parts show a high degree of uncertainty regarding failure characteristics,qual...The different conditions of use of a component result in a variety of damage levels.Therefore,excluding differences in shape and size,used parts show a high degree of uncertainty regarding failure characteristics,quality conditions,and remaining life,which seriously affects the efficiency of a remanufacturing scheme design.Aiming to address this problem,a remanufacturing scheme design method based on the reconstruction of incomplete information of used parts is proposed.First,the remaining life of the reconstructed model is predicted by finite element analysis,and the demand for the next life cycle is determined.Second,the scanned 3D damage point cloud data are registered with the original point cloud data using the integral iterative method to construct a missing point cloud model to achieve the restoration of geometric information.Then,according to reverse engineering and laser cladding remanufacturing,the tool remanufacturing process path can be generated by the tool contact point path section line method.Finally,the proposed method is adopted for turbine blades to evaluate the effectiveness and feasibility of the proposed scheme.This study proposes a remanufacturing scheme design method based on the incomplete reconstruction of used part information to solve the uncertain and highly personalized problems in remanufacturing.展开更多
Brain plasticity, including anatomical changes and functional reorganization, is the physiological basis of functional recovery after spinal cord injury(SCI). The correlation between brain anatomical changes and funct...Brain plasticity, including anatomical changes and functional reorganization, is the physiological basis of functional recovery after spinal cord injury(SCI). The correlation between brain anatomical changes and functional reorganization after SCI is unclear. This study aimed to explore whether alterations of cortical structure and network function are concomitant in sensorimotor areas after incomplete SCI. Eighteen patients with incomplete SCI(mean age 40.94 ± 14.10 years old; male:female, 7:11) and 18 healthy subjects(37.33 ± 11.79 years old; male:female, 7:11) were studied by resting state functional magnetic resonance imaging. Gray matter volume(GMV) and functional connectivity were used to evaluate cortical structure and network function, respectively. There was no significant alteration of GMV in sensorimotor areas in patients with incomplete SCI compared with healthy subjects. Intra-hemispheric functional connectivity between left primary somatosensory cortex(BA1) and left primary motor cortex(BA4), and left BA1 and left somatosensory association cortex(BA5) was decreased, as well as inter-hemispheric functional connectivity between left BA1 and right BA4, left BA1 and right BA5, and left BA4 and right BA5 in patients with SCI. Functional connectivity between both BA4 areas was also decreased. The decreased functional connectivity between the left BA1 and the right BA4 positively correlated with American Spinal Injury Association sensory score in SCI patients. The results indicate that alterations of cortical anatomical structure and network functional connectivity in sensorimotor areas were non-concomitant in patients with incomplete SCI, indicating the network functional changes in sensorimotor areas may not be dependent on anatomic structure. The strength of functional connectivity within sensorimotor areas could serve as a potential imaging biomarker for assessment and prediction of sensory function in patients with incomplete SCI. This trial was registered with the Chinese Clinical Trial Registry(registration number: Chi CTR-ROC-17013566).展开更多
Global navigation satellite system could provide accurate positioning results in signal complete condition. However, the performance is severe when signal denied, especially for the single-mode Bei Dou receiver. This ...Global navigation satellite system could provide accurate positioning results in signal complete condition. However, the performance is severe when signal denied, especially for the single-mode Bei Dou receiver. This paper proposes a dual-satellite positioning algorithm to promote the positioning performance in the satellite signal gap. The new algorithm utilizes the previous positioning data stored in complete condition to simplify the positioning equations. As the clock bias persists for a short period, this proposed method could work out accurate positioning results by only two visible satellites, without the need of computing the clock bias. Also, the Kalman filtering algorithm is used to smooth the trajectories, and improve the positioning results. During the incomplete period, only two satellites for 30 seconds and three satellites for 60 seconds, the preliminary experiment result shows that, the presented method could provide almost the same positioning results as in complete condition.展开更多
基金financially supported by the National Science Fund for Distinguished Young Scholars of China(Grant No.51825904)the Research on the Form,Design Method and Weathering Resistance of Key Components of Novel Floating Support Structures for Offshore Photovoltaics(Grant No.2022YFB4200701).
文摘Due to the uneven seabed and heaving of soil during pumping,incomplete soil plugs may occur during the installation of bucket foundations,and the impacts on the bearing capacities of bucket foundations need to be evaluated.In this paper,the contact ratio(the ratio of the top diameter of the soil plug to the diameter of the bucket)and the soil plug ratio(the ratio of the soil heave height to the skirt height)are defined to describe the shape and size of the incomplete soil plug.Then,finite element models are established to investigate the bearing capacities of bucket foundations with incomplete soil plugs and the influences of the contact ratios,and the soil plug ratios on the bearing capacities are analyzed.The results show that the vertical bearing capacity of bucket foundations in homogeneous soil continuously improves with the increase of the contact ratio.However,in normally consolidated soil,the vertical bearing capacity barely changes when the contact ratio is smaller than 0.75,while the bearing capacity suddenly increases when the contact ratio increases to 1 due to the change of failure mode.The contact ratio hardly affects the horizontal bearing capacity of bucket foundations.Moreover,the moment bearing capacity improves with the increase of the contact ratio for small aspect ratios,but hardly varies with increasing contact ratio for aspect ratios larger than 0.5.Consequently,the reduction coefficient method is proposed based on this analysis to calculate the bearing capacities of bucket foundations considering the influence of incomplete soil plugs.The comparison results show that the proposed reduction coefficient method can be used to evaluate the influences of incomplete soil plug on the bearing capacities of bucket foundations.
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.
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.
文摘According to the disease module hypothesis,the cellular components associated with a disease segregate in the same neighborhood of the human interactome,the map of biologically relevant molecular interactions.Yet,given the incompleteness of the interactome and the limited knowledge of disease-associated genes,it is not obvious if the available data have sufficient coverage to map out modules associated with each disease.
文摘According to the disease module hypothesis,the cellular components associated with a disease segregate in the same neighborhood of the human interactome,the map of biologically relevant molecular interactions.Yet,given the incompleteness of the interactome and the limited knowledge of disease-associated genes,it is not obvious if the available data have sufficient coverage to map out modules associated with each disease.Here we derive mathematical conditions for the identifiability of disease modules and show that the network-based location of each disease module determines its pathobiological relationship to other diseases.For example,diseases with overlapping network modules show significant coexpression patterns,symptom similarity,and comorbidity,whereas diseases residing in separated network neighborhoods are phenotypically distinct.These tools represent an interactome-based platform to predict molecular commonalities between phenotypically related diseases,even if they do not share primary disease genes.
基金funded by the National Natural Science Foundation of China under Grant 62273022.
文摘Due to the high inherent uncertainty of renewable energy,probabilistic day-ahead wind power forecasting is crucial for modeling and controlling the uncertainty of renewable energy smart grids in smart cities.However,the accuracy and reliability of high-resolution day-ahead wind power forecasting are constrained by unreliable local weather prediction and incomplete power generation data.This article proposes a physics-informed artificial intelligence(AI)surrogates method to augment the incomplete dataset and quantify its uncertainty to improve wind power forecasting performance.The incomplete dataset,built with numerical weather prediction data,historical wind power generation,and weather factors data,is augmented based on generative adversarial networks.After augmentation,the enriched data is then fed into a multiple AI surrogates model constructed by two extreme learning machine networks to train the forecasting model for wind power.Therefore,the forecasting models’accuracy and generalization ability are improved by mining the implicit physics information from the incomplete dataset.An incomplete dataset gathered from a wind farm in North China,containing only 15 days of weather and wind power generation data withmissing points caused by occasional shutdowns,is utilized to verify the proposed method’s performance.Compared with other probabilistic forecastingmethods,the proposed method shows better accuracy and probabilistic performance on the same incomplete dataset,which highlights its potential for more flexible and sensitive maintenance of smart grids in smart cities.
基金supported by the National Natural Science Foundation of China(Grant No.61933010 and 61903301)Shaanxi Aerospace Flight Vehicle Design Key Laboratory。
文摘Cooperative autonomous air combat of multiple unmanned aerial vehicles(UAVs)is one of the main combat modes in future air warfare,which becomes even more complicated with highly changeable situation and uncertain information of the opponents.As such,this paper presents a cooperative decision-making method based on incomplete information dynamic game to generate maneuver strategies for multiple UAVs in air combat.Firstly,a cooperative situation assessment model is presented to measure the overall combat situation.Secondly,an incomplete information dynamic game model is proposed to model the dynamic process of air combat,and a dynamic Bayesian network is designed to infer the tactical intention of the opponent.Then a reinforcement learning framework based on multiagent deep deterministic policy gradient is established to obtain the perfect Bayes-Nash equilibrium solution of the air combat game model.Finally,a series of simulations are conducted to verify the effectiveness of the proposed method,and the simulation results show effective synergies and cooperative tactics.
文摘With the rapid development of the economy,the scale of the power grid is expanding.The number of power equipment that constitutes the power grid has been very large,which makes the state data of power equipment grow explosively.These multi-source heterogeneous data have data differences,which lead to data variation in the process of transmission and preservation,thus forming the bad information of incomplete data.Therefore,the research on data integrity has become an urgent task.This paper is based on the characteristics of random chance and the Spatio-temporal difference of the system.According to the characteristics and data sources of the massive data generated by power equipment,the fuzzy mining model of power equipment data is established,and the data is divided into numerical and non-numerical data based on numerical data.Take the text data of power equipment defects as the mining material.Then,the Apriori algorithm based on an array is used to mine deeply.The strong association rules in incomplete data of power equipment are obtained and analyzed.From the change trend of NRMSE metrics and classification accuracy,most of the filling methods combined with the two frameworks in this method usually show a relatively stable filling trend,and will not fluctuate greatly with the growth of the missing rate.The experimental results show that the proposed algorithm model can effectively improve the filling effect of the existing filling methods on most data sets,and the filling effect fluctuates greatly with the increase of the missing rate,that is,with the increase of the missing rate,the improvement effect of the model for the existing filling methods is higher than 4.3%.Through the incomplete data clustering technology studied in this paper,a more innovative state assessment of smart grid reliability operation is carried out,which has good research value and reference significance.
文摘A generalized flexibility–based objective function utilized for structure damage identification is constructed for solving the constrained nonlinear least squares optimized problem. To begin with, the generalized flexibility matrix (GFM) proposed to solve the damage identification problem is recalled and a modal expansion method is introduced. Next, the objective function for iterative optimization process based on the GFM is formulated, and the Trust-Region algorithm is utilized to obtain the solution of the optimization problem for multiple damage cases. And then for computing the objective function gradient, the sensitivity analysis regarding design variables is derived. In addition, due to the spatial incompleteness, the influence of stiffness reduction and incomplete modal measurement data is discussed by means of two numerical examples with several damage cases. Finally, based on the computational results, it is evident that the presented approach provides good validity and reliability for the large and complicated engineering structures.
基金supported by the National Natural Science Foundation of China(No.81703076 and No.82072628).
文摘Colonoscopic polypectomy is extremely effective in protecting against colorectal cancers,and recognition of adenomas by colonoscopy is of paramount importance in preventing colorectal cancer(CRC)and CRC-associated mortality.Incomplete polyp resection(IPR)occurs routinely in medical practice following polypectomy.We conducted a comprehensive literature search to identify studies that reported on the potential risk factors for IPR using MEDLINE,EMBASE,and PubMed.Publication time was limited between January 2004 and July 2021.Our search revealed assessments of the position,morphology,and histologic variation of the polypsdas well as the relevant skills that may interfere with IPR.The included studies showed that colonic polyps with a diameter>20 mm and proximal in location should be dealt with cautiously.For smaller polyps,cold-snare polypectomy appeared to be the most effective method used to accomplish comprehensive polyp removal.In addition,endoscopist experience in narrow-band imaging in polyp detection were also associated with IPR.Therefore,polypectomy should be performed cautiously if the polyp growth is expected to be cancerous and situated in the proximal portion of the colon or rectum,and modalities should be standardized so as to lower the potential risk for IPR.
基金Supported by Grants in Aid for Scientific Research(C)from the Japanese Ministry of Education,Culture,Sports,Science,and Technology
文摘AIM:To evaluate significant risk factors for incomplete colonoscopy at a Japanese academic hospital.METHODS:A total of 11812 consecutive Japanese people were identified who underwent a colonoscopy at an academic hospital.A multiple logistic regression model was used to evaluate retrospectively the significant risk factors for incomplete colonoscopy.RESULTS:The cecal intubation rate was 95.0%.By univariate analysis,age,female sex,poor bowel cleansing,and a history of abdominal or pelvic surgery were significant risk factors for incomplete colonoscopy(P<0.001).Moreover,age-and sex-adjusted analysis showed that significant risk factors for incomplete colonoscopy were female sex(OR=1.38,95%CI:1.17-1.64,P=0.0002),age≥60 years old(OR=1.44,95%CI:1.22-1.71,P<0.0001),a history of prior abdominal or pelvic surgery(OR=1.55,95%CI:1.28-1.86,P<0.0001),poor bowel cleansing(OR=4.64,95%CI:3.69-5.84,P<0.0001),and inflammatory bowel disease(IBD)(OR=1.48,95%CI:1.13-1.95,P=0.0048).In Japanese men,by age-adjusted analysis,IBD(OR=1.69,95%CI:1.18-2.43,P=0.005)was an independent risk factor for incomplete colonoscopy.CONCLUSION:Several characteristics in the Japanese population were identified that could predict technical difficulty with colonoscopy.
基金Supported by St.Paul's Hospital Division of Gastroenterology and Pacific Gastroenterology Associates,Vancouver,British Columbia,Canada
文摘AIM:To identify patient risk factors associated with incomplete small bowel capsule endoscopy(CE) studies.METHODS:Data from all CE procedures performed at St.Paul's Hospital in Vancouver,British Columbia,Canada,between December 2001 and June 2008 were collected and analyzed on a retrospective basis.Data collection for complete and incomplete CE study groups included patient demographics as well as a number of potential risk factors for incomplete CE including indication for the procedure,hospitalization,diabetes mellitus with or without end organ damage,limitations in mobility,renal insufficiency,past history of bowel obstruction,abdominal surgery,abdominal radiation therapy and opiate use.Risk factors were analyzed using a univariable and multivariable logistic regression model.RESULTS:From a total of 535 CE procedures performed,158 were incomplete(29.5%).The univariable analysis showed that CE procedures performed for overt gastrointestinal bleeding(P = 0.002),and for patients with a prior history of abdominal surgery(P = 0.023) or bowel obstruction(P = 0.023) were significantly associated with incomplete CE studies.Patients on opiate medications(P = 0.094) as well as hospitalized patients(P = 0.054) were not statistically significant,but did show a trend towards incomplete CE.The multivariable analysis showed that independent risk factors for an incomplete CE procedure include prior history of bowel obstruction [odds ratios(OR) 2.77,P = 0.02,95% confidence intervals(CI):1.17-6.56] and procedures performed for gastrointestinal bleeding(Occult OR 2.04,P = 0.037,95% CI:1.04-4.02 and Overt OR 2.69,P = 0.002,95% CI:1.44-5.05).Patients with a prior history of abdominal surgery(OR 1.46,P = 0.068,95% CI:0.97-2.19),those taking opiate medications(OR 1.54,P = 0.15,95% CI:0.86-2.76) and hospitalized patients(OR 1.82,P = 0.124,95% CI:0.85-3.93) showed a trend towards statistical significance.CONCLUSION:We have identified a number of risk factors for incomplete CE procedures that can be used to risk-stratify patients and guide interventions to improve completion rates.
基金supported by Foundation for Innovative Research Groups of National Natural Science Foundation of China(NSFC)(61321002)National Science Fund for Distinguished Young Scholars(60925011)+2 种基金Projects of Major International(Regional)Joint Research Program NSFC(61120106010)Beijing Education Committee Cooperation Building Foundation Project,Program for Changjiang Scholars and Innovative Research Team in University(IRT1208)Chang Jiang Scholars Program and National Natural Science Foundation of China(61203078)
文摘At present, the studies on multi-team antagonistic games(MTAGs) are still in the early stage, because this complicated problem involves not only incompleteness of information and conflict of interests, but also selection of antagonistic targets.Therefore, based on the previous researches, a new framework is proposed in this paper, which is dynamic multi-team antagonistic games with incomplete information(DMTAGII) model.For this model, the corresponding concept of perfect Bayesian Nash equilibrium(PBNE) is established and the existence of PBNE is also proved. Besides, an interactive iteration algorithm is introduced according to the idea of the best response for solving the equilibrium. Then, the scenario of multiple unmanned aerial vehicles(UAVs) against multiple military targets is studied to solve the problems of tactical decision making based on the DMTAGII model. In the process of modeling, the specific expressions of strategy, status and payoff functions of the games are considered, and the strategy is coded to match the structure of genetic algorithm so that the PBNE can be solved by combining the genetic algorithm and the interactive iteration algorithm.Finally, through the simulation the feasibility and effectiveness of the DMTAGII model are verified. Meanwhile, the calculated equilibrium strategies are also found to be realistic, which can provide certain references for improving the autonomous ability of UAV systems.
基金Project (50275150) supported by the National Natural Science Foundation of ChinaProject (RL200002) supported by the Foundation of the Robotics Laboratory, Chinese Academy of Sciences
文摘An optimal PID controller with incomplete derivation is proposed based on fuzzy inference and the geneticalgorithm, which is called the fuzzy-GA PID controller with incomplete derivation. It consists of the off-line part andthe on-line part. In the off-line part, by taking the overshoot, rise time, and settling time of system unit step re-sponse as the performance indexes and by using the genetic algorithm, a group of optimal PID parameters K*p , Ti* ,and Tj are obtained, which are used as the initial values for the on-line tuning of PID parameters. In the on-linepart, based on K; , Ti* , and T*d and according to the current system error e and its time derivative, a dedicatedprogram is written, which is used to optimize and adjust the PID parameters on line through a fuzzy inference mech-anism to ensure that the system response has optimal dynamic and steady-state performance. The controller has beenused to control the D. C. motor of the intelligent bionic artificial leg designed by the authors. The result of computersimulation shows that this kind of optimal PID controller has excellent control performance and robust performance.
文摘AIM:To evaluate whether the use of real time viewer(RTV)and administration of domperidone to patients with delayed gastric passage of the capsule could reduce the rate of incomplete examinations(IE)and improve the diagnostic yield of small bowel capsule endoscopy(SBCE).METHODS:Prospective single center interventional study,from June 2012 to February 2013.Capsule location was systematically checked one hour after ingestion using RTV.If it remained in the stomach,the patient received 10 mg domperidone per os and the location of the capsule was rechecked after 30 min.If the capsule remained in the stomach a second dose of10 mg of domperidone was administered orally.After another 30 min the position was rechecked and if the capsule remained in the stomach,it was passed into the duodenum by upper gastrointestinal(GI)endoscopy.The rate of IE and diagnostic yield of SBCE were compared with those of examinations performed before the use of RTV or domperidone in our Department(control group,January 2009-May 2012).RESULTS:Both groups were similar regarding age,sex,indication,inpatient status and surgical history.The control group included 307 patients,with 48(15.6%)IE.The RTV group included 82 patients,with3(3.7%)IE,P=0.003.In the control group,average gastric time was significantly longer in patients with IE than in patients with complete examination of the small bowel(77 min vs 26 min,P=0.003).In the RTV group,the capsule remained in the stomach one hour after ingestion in 14/82 patients(17.0%)vs 48/307(15.6%)in the control group,P=0.736.Domperidone did not significantly affect small bowel transit time(260min vs 297 min,P=0.229).The capsule detected positive findings in 39%of patients in the control group and 49%in the RTV group(P=0.081).CONCLUSION:The use of RTV and selective administration of domperidone to patients with delayed gastric passage of the capsule significantly reduces incomplete examinations,with no effect on small bowel transit time or diagnostic yield.
基金supported in part by the National Natural Science Foundation of China(51975075)Chongqing Technology Innovation and Application Program(cstc2018jszx-cyzd X0183)。
文摘Energy consumption prediction of a CNC machining process is important for energy efficiency optimization strategies.To improve the generalization abilities,more and more parameters are acquired for energy prediction modeling.While the data collected from workshops may be incomplete because of misoperation,unstable network connections,and frequent transfers,etc.This work proposes a framework for energy modeling based on incomplete data to address this issue.First,some necessary preliminary operations are used for incomplete data sets.Then,missing values are estimated to generate a new complete data set based on generative adversarial imputation nets(GAIN).Next,the gene expression programming(GEP)algorithm is utilized to train the energy model based on the generated data sets.Finally,we test the predictive accuracy of the obtained model.Computational experiments are designed to investigate the performance of the proposed framework with different rates of missing data.Experimental results demonstrate that even when the missing data rate increases to 30%,the proposed framework can still make efficient predictions,with the corresponding RMSE and MAE 0.903 k J and 0.739 k J,respectively.
基金supported by the National Natural Science Foundation of China under Grant No. 61303074 and No. 61309013the Henan Province Science and Technology Project Funds under Grant No. 12210231002
文摘Nowadays, the network defence policy selection using game model of incomplete information ignores the type of the defender, which quantifies cost simply, resulting in unreasonable defence policies selection. Aiming at the problem, we use Bayesian game theory to model the active defence policy selection. We take the types of both the attacker and the defender into consideration. Besides, the traditional quantization method is enhanced. Then, we calculate the equilibrium of static Bayesian game. Based on the analysis of the equilibrium, we select the optimal defence policy through the prediction for attackers' actions. The paper calculates the defence effectiveness of defence policies and provides a defence policies selection algorithm. Ultimately, we present an example to verify the effectiveness of the method and model proposed in the paper.
基金Supported by Plateau Disciplines in ShanghaiNational Natural Science Foundation of China (Grant No. 51675388)Hubei Provincial Department of Education of China (Grant No. D20181102)
文摘The different conditions of use of a component result in a variety of damage levels.Therefore,excluding differences in shape and size,used parts show a high degree of uncertainty regarding failure characteristics,quality conditions,and remaining life,which seriously affects the efficiency of a remanufacturing scheme design.Aiming to address this problem,a remanufacturing scheme design method based on the reconstruction of incomplete information of used parts is proposed.First,the remaining life of the reconstructed model is predicted by finite element analysis,and the demand for the next life cycle is determined.Second,the scanned 3D damage point cloud data are registered with the original point cloud data using the integral iterative method to construct a missing point cloud model to achieve the restoration of geometric information.Then,according to reverse engineering and laser cladding remanufacturing,the tool remanufacturing process path can be generated by the tool contact point path section line method.Finally,the proposed method is adopted for turbine blades to evaluate the effectiveness and feasibility of the proposed scheme.This study proposes a remanufacturing scheme design method based on the incomplete reconstruction of used part information to solve the uncertain and highly personalized problems in remanufacturing.
基金supported by a grant from Tsinghua University Initiative Scientific Research Program,No.2014081266,20131089382the National Natural Science Foundation of China,No.61171002,60372023
文摘Brain plasticity, including anatomical changes and functional reorganization, is the physiological basis of functional recovery after spinal cord injury(SCI). The correlation between brain anatomical changes and functional reorganization after SCI is unclear. This study aimed to explore whether alterations of cortical structure and network function are concomitant in sensorimotor areas after incomplete SCI. Eighteen patients with incomplete SCI(mean age 40.94 ± 14.10 years old; male:female, 7:11) and 18 healthy subjects(37.33 ± 11.79 years old; male:female, 7:11) were studied by resting state functional magnetic resonance imaging. Gray matter volume(GMV) and functional connectivity were used to evaluate cortical structure and network function, respectively. There was no significant alteration of GMV in sensorimotor areas in patients with incomplete SCI compared with healthy subjects. Intra-hemispheric functional connectivity between left primary somatosensory cortex(BA1) and left primary motor cortex(BA4), and left BA1 and left somatosensory association cortex(BA5) was decreased, as well as inter-hemispheric functional connectivity between left BA1 and right BA4, left BA1 and right BA5, and left BA4 and right BA5 in patients with SCI. Functional connectivity between both BA4 areas was also decreased. The decreased functional connectivity between the left BA1 and the right BA4 positively correlated with American Spinal Injury Association sensory score in SCI patients. The results indicate that alterations of cortical anatomical structure and network functional connectivity in sensorimotor areas were non-concomitant in patients with incomplete SCI, indicating the network functional changes in sensorimotor areas may not be dependent on anatomic structure. The strength of functional connectivity within sensorimotor areas could serve as a potential imaging biomarker for assessment and prediction of sensory function in patients with incomplete SCI. This trial was registered with the Chinese Clinical Trial Registry(registration number: Chi CTR-ROC-17013566).
基金partially supported by the National Natural Science Foundation of China under Grant No.61601296, 61601295, and 61671304
文摘Global navigation satellite system could provide accurate positioning results in signal complete condition. However, the performance is severe when signal denied, especially for the single-mode Bei Dou receiver. This paper proposes a dual-satellite positioning algorithm to promote the positioning performance in the satellite signal gap. The new algorithm utilizes the previous positioning data stored in complete condition to simplify the positioning equations. As the clock bias persists for a short period, this proposed method could work out accurate positioning results by only two visible satellites, without the need of computing the clock bias. Also, the Kalman filtering algorithm is used to smooth the trajectories, and improve the positioning results. During the incomplete period, only two satellites for 30 seconds and three satellites for 60 seconds, the preliminary experiment result shows that, the presented method could provide almost the same positioning results as in complete condition.
