To estimate the fuel consumption of a civil aircraft,we propose to use the receiver operating characteristic(ROC)curve to optimize a support vector machine(SVM)model.The new method and procedure has been developed to ...To estimate the fuel consumption of a civil aircraft,we propose to use the receiver operating characteristic(ROC)curve to optimize a support vector machine(SVM)model.The new method and procedure has been developed to build,train,validate,and apply an SVM model.A conceptual support vector network is proposed to model fuel consumption,and the flight data collected from routes are used as the inputs to train an SVM model.During the training phase,an ROC curve is defined to evaluate the performance of the model.To validate the applicability of the trained model,a case study is developed to compare the data from an aircraft performance manual and from the implemented simulation model.The investigated aircraft in the case study is a Boeing 737-800 powered by CFM-56 engines.The comparison has shown that the trained SVM model from the proposed procedure is capable of representing a complex fuel consumption function accurately for all phases during the flight.The proposed methodology is generic,and can be extended to reliably model the fuel consumption of other types of aircraft,such as piston engine aircraft or turboprop engine aircraft.展开更多
Several mathematical models have been proposed to describe the dynamics of irradiated cancer cells and to evaluate the tumour control probability (TCP). In this article, we propose a TCP model-based statistical test f...Several mathematical models have been proposed to describe the dynamics of irradiated cancer cells and to evaluate the tumour control probability (TCP). In this article, we propose a TCP model-based statistical test for predicting the outcome of a radiation treatment. We determine the foresight capability of prostate tumour erradication (cure) from Monte Carlo simulations of the Dawson-Hillen TCP model. We construct the receiver operating characteristic (ROC) curves of the test from the probability distributions of the fraction of remaining tumour cells for simulated experiments that evolve either to cure or non-cure. Simulations show that a similar procedure may be applicable to clinical data. Results suggest that the evaluation of tumour sizes after the treatment has started may be used for short-term prognosis.展开更多
To improve the ability of detecting underwater targets under strong wideband interference environment,an efficient method of line spectrum extraction is proposed,which fully utilizes the feature of the target spectrum...To improve the ability of detecting underwater targets under strong wideband interference environment,an efficient method of line spectrum extraction is proposed,which fully utilizes the feature of the target spectrum that the high intense and stable line spectrum is superimposed on the wide continuous spectrum.This method modifies the traditional beam forming algorithm by calculating and fusing the beam forming results at multi-frequency band and multi-azimuth interval,showing an excellent way to extract the line spectrum when the interference and the target are not in the same azimuth interval simultaneously.Statistical efficiency of the estimated azimuth variance and corresponding power of the line spectrum band depends on the line spectra ratio(LSR)of the line spectrum.The change laws of the output signal to noise ratio(SNR)with the LSR,the input SNR,the integration time and the filtering bandwidth of different algorithms bring the selection principle of the critical LSR.As the basis,the detection gain of wideband energy integration and the narrowband line spectrum algorithm are theoretically analyzed.The simulation detection gain demonstrates a good match with the theoretical model.The application conditions of all methods are verified by the receiver operating characteristic(ROC)curve and experimental data from Qiandao Lake.In fact,combining the two methods for target detection reduces the missed detection rate.The proposed post-processing method in2-dimension with the Kalman filter in the time dimension and the background equalization algorithm in the azimuth dimension makes use of the strong correlation between adjacent frames,could further remove background fluctuation and improve the display effect.展开更多
Coronavirus 2019(COVID-19)is the current global buzzword,putting the world at risk.The pandemic’s exponential expansion of infected COVID-19 patients has challenged the medical field’s resources,which are already fe...Coronavirus 2019(COVID-19)is the current global buzzword,putting the world at risk.The pandemic’s exponential expansion of infected COVID-19 patients has challenged the medical field’s resources,which are already few.Even established nations would not be in a perfect position to manage this epidemic correctly,leaving emerging countries and countries that have not yet begun to grow to address the problem.These problems can be solved by using machine learning models in a realistic way,such as by using computer-aided images during medical examinations.These models help predict the effects of the disease outbreak and help detect the effects in the coming days.In this paper,Multi-Features Decease Analysis(MFDA)is used with different ensemble classifiers to diagnose the disease’s impact with the help of Computed Tomography(CT)scan images.There are various features associated with chest CT images,which help know the possibility of an individual being affected and how COVID-19 will affect the persons suffering from pneumonia.The current study attempts to increase the precision of the diagnosis model by evaluating various feature sets and choosing the best combination for better results.The model’s performance is assessed using Receiver Operating Characteristic(ROC)curve,the Root Mean Square Error(RMSE),and the Confusion Matrix.It is observed from the resultant outcome that the performance of the proposed model has exhibited better efficient.展开更多
Flash floods are one of the most dangerous natural disasters,especially in hilly terrain,causing loss of life,property,and infrastructures and sudden disruption of traffic.These types of floods are mostly associated w...Flash floods are one of the most dangerous natural disasters,especially in hilly terrain,causing loss of life,property,and infrastructures and sudden disruption of traffic.These types of floods are mostly associated with landslides and erosion of roads within a short time.Most of Vietnamis hilly and mountainous;thus,the problem due to flash flood is severe and requires systematic studies to correctly identify flood susceptible areas for proper landuse planning and traffic management.In this study,three Machine Learning(ML)methods namely Deep Learning Neural Network(DL),Correlation-based FeatureWeighted Naive Bayes(CFWNB),and Adaboost(AB-CFWNB)were used for the development of flash flood susceptibility maps for hilly road section(115 km length)of National Highway(NH)-6 inHoa Binh province,Vietnam.In the proposedmodels,88 past flash flood events were used together with 14 flash floods affecting topographical and geo-environmental factors.The performance of themodels was evaluated using standard statisticalmeasures including Receiver Operating Characteristic(ROC)Curve,Area Under Curve(AUC)and Root Mean Square Error(RMSE).The results revealed that all the models performed well(AUC>0.80)in predicting flash flood susceptibility zones,but the performance of the DL model is the best(AUC:0.972,RMSE:0.352).Therefore,the DL model can be applied to develop an accurate flash flood susceptibility map of hilly terrain which can be used for proper planning and designing of the highways and other infrastructure facilities besides landuse management of the area.展开更多
Objective:To test the diagnostic performance of percent free prostate-specific antigen(%fPSA)in predicting any prostate cancer(PCa)and high-grade prostate cancer(HGPCa)in a retrospective multi-center biopsy cohort wit...Objective:To test the diagnostic performance of percent free prostate-specific antigen(%fPSA)in predicting any prostate cancer(PCa)and high-grade prostate cancer(HGPCa)in a retrospective multi-center biopsy cohort with a PSA level of 4.0e10.0 ng/mL in China.Methods:Consecutive patients with a PSA of 4.0-10.0 ng/mL who underwent transrectal ultrasound-guided biopsy were enrolled at 16 Chinese medical centers from January 1st,2010 to December 31st,2013.Total and free serum PSA determinations were performed using three types of electro-chemiluminescence immunoassays recalibrated to the World Health Organization(WHO)standard.The diagnostic accuracy of PSA,%fPSA,and %fPSA in combination with PSA(%fPSA t PSA)was determined using the area under the receiver operating characteristic(ROC)curve(AUC).Results:A total of 2310 consecutive men with PSA levels between 4.0 and 10.0 ng/mL were included,and the detection rate of PCa was 25.1%.The AUC of%fPSA and %fPSA t PSA in predicting any PCa was superior to PSA alone in men aged≥60 years(0.623 vs.0.534,p<0.0001)but not in men aged 40e59 years(0.517 vs.0.518,p=0.939).Similar result was yield in predicting HGPCa.Conclusion:In a clinical setting of Chinese men with 4.0e10.0 ng/mL PSA undergoing initial prostate biopsy,adding %fPSA to PSA can moderately improve the diagnostic accuracy for any PCa and HGPCa compared with PSA alone in patients≥60 but not in patients aged 40-59 years.展开更多
The construction of a pest detection algorithm is an important step to couple"ground-space"characteristics,which is also the basis for rapid and accurate monitoring and detection of pest damage.In four exper...The construction of a pest detection algorithm is an important step to couple"ground-space"characteristics,which is also the basis for rapid and accurate monitoring and detection of pest damage.In four experimental areas in Sanming City,Jiangle County,Sha County and Yanping District in Fujian Province,sample data on pest damage in 182 sets of Dendrolimus punctatus were collected.The data were randomly divided into a training set and testing set,and five duplicate tests and one eliminating-indicator test were done.Based on the characterization analysis of the host for D.punctatus damage,seven characteristic indicators of ground and remote sensing including leaf area index,standard error of leaf area index(SEL)of pine forest,normalized difference vegetation index(NDVI),wetness from tasseled cap transformation(WET),green band(B2),red band(B3),near-infrared band(B4)of remote sensing image are obtained to construct BP neural networks and random forest models of pest levels.The detection results of these two algorithms were comprehensively compared from the aspects of detection precision,kappa coefficient,receiver operating characteristic curve,and a paired t test.The results showed that the seven indicators all were responsive to pest damage,and NDVI was relatively weak;the average pest damage detection precision of six tests by BP neural networks was 77.29%,the kappa coefficient was 0.6869 and after the RF algorithm,the respective values were 79.30%and 0.7151,showing that the latter is more optimized,but there was no significant difference(p>0.05);the detection precision,kappa coefficient and AUC of the RF algorithm was higher than the BP neural networks for three pest levels(no damage,moderate damage and severe damage).The detection precision and AUC of BP neural networks were a little higher for mild damage,but the difference was not significant(p>0.05)except for the kappa coefficient for the no damage level(p<0.05).An"over-fitting"phenomenon tends to occur in BP neural networks,while RF method is more robust,providing a detection effect that is better than the BP neural networks.Thus,the application of the random forest algorithm for pest damage and multilevel dispersed variables is thus feasible and suggests that attention to the proportionality of sample data from various categories is needed when collecting data.展开更多
BACKGROUND:In the management of critically ill patients,the assessment of volume responsiveness and the decision to administer a fluid bolus constitute a common dilemma for physicians.Static indices of cardiac preload...BACKGROUND:In the management of critically ill patients,the assessment of volume responsiveness and the decision to administer a fluid bolus constitute a common dilemma for physicians.Static indices of cardiac preload are poor predictors of volume responsiveness.Passive leg raising(PLR) mimics an endogenous volume expansion(VE) that can be used to predict fluid responsiveness.This study was to assess the changes in stroke volume index(SVI) induced by PLR as an indicator of fluid responsiveness in mechanically ventilated patients with severe sepsis.METHODS:This was a prospective study.Thirty-two mechanically ventilated patients with severe sepsis were admitted for VE in ICU of the First Affiliated Hospital,Zhejiang University School of Medicine and Ningbo Medical Treatment Center Lihuili Hospital from May 2010 to December 2011.Patients with non-sinus rhythm or arrhythmia,parturients,and amputation of the lower limbs were excluded.Measurements of SVI were obtained in a semi-recumbent position(baseline) and during PLR by the technique of pulse indicator continuous cardiac output(PiCCO) system prior to VE.Measurements were repeated after VE(500 mL 6%hydroxyethyl starch infusion within 30 minutes)to classify patients as either volume responders or non-responders based on their changes in stroke volume index(ASVI) over 15%.Heart rate(HR),systolic artery blood pressure(ABPs),diastolic artery blood pressure(ABPd),mean arterial blood pressure(ABPm),mean central venous pressure(CVPm)and cardiac index(CI) were compared between the two groups.The changes of ABPs,ABPm,CVPm,and SVI after PLR and VE were compared with the indices at the baseline.The ROC curve was drawn to evaluate the value of ASVI and the change of CVPm(ACVPm) in predicting volume responsiveness.SPSS 17.0 software was used for statistical analysis.RESULTS:Among the 32 patients,22 were responders and 10 were non-responders.After PLR among the responders,some hemodynamic variables(including ABPs,ABPd,ABPm and CVPm)were significantly elevated(101.2±17.6 vs.118.6±23.7,P=0.03;52.8±10.7 vs.64.8±10.7,P=0.006;68.3+11.7 vs.81.9±14.4,P=0.008;6.8±3.2 vs.11.9±4.0,P=0.001).After PLR,the area under curve(AUC) and the ROC curve of △SV1 and ACVPm for predicting the responsiveness after VE were0.882±0.061(95%CI 0.759-1.000) and 0.805±0.079(95%CI 0.650-0.959) when the cut-off levels of ASVI and ACVPm were 8.8%and 12.7%,the sensitivities were 72.7%and 72.7%,and the specificities were 80%and 80%.CONCLUSION:Changes in ASVI and ACVPm induced by PLR are accurate indices for predicting fluid responsiveness in mechanically ventilated patients with severe sepsis.展开更多
BACKGROUND Smear cytology(SC)using endoscopic ultrasound-guided fine needle aspiration(EUS-FNA)is the established and traditional choice for diagnosing pancreatic lesions.Liquid-based cytology(LBC)is a novel alternati...BACKGROUND Smear cytology(SC)using endoscopic ultrasound-guided fine needle aspiration(EUS-FNA)is the established and traditional choice for diagnosing pancreatic lesions.Liquid-based cytology(LBC)is a novel alternative cytological method,however,the comparative diagnostic efficacy of LBC remains inconclusive.AIM To examine the diagnostic efficacy of LBC and SC for pancreatic specimens obtained through EUS-FNA via a systematic review and meta-analysis.METHODS A systematic literature search was performed using PubMed,EMBASE,the Cochrane Library,and Web of Science.The numbers of true positives,false positives,true negatives,and false negatives for each cytological test(LBC and CS)were extracted from the included studies.The pooled sensitivity and specificity and the area under the summary receiver operating characteristic curve(AUC)were calculated,and the AUC was compared by Tukey's multiple comparisons test.The quality of the included studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies II tool.RESULTS A total of 1656 patients in eight studies were included.The pooled sensitivity and specificity and the AUC for LBC were 0.76(95%CI:0.72-0.79),1.00(95%CI:0.98-1.00),and 0.9174,respectively,for diagnosing pancreatic lesions.The pooled estimates for SC were as follows:Sensitivity,0.68(95%CI:0.64-0.71);specificity,0.99(95%CI:0.96-100.00);and AUC,0.9714.Similarly,the corresponding values for LBC combined with SC were 0.87(95%CI:0.84-0.90),0.99(95%CI:0.96-1.00),and 0.9894.Tukey’s multiple comparisons test was used to compare the sensitivities and AUCs of the three diagnostic methods;statistically significant differences were found between the three methods,and LBC combined with SC was superior to both LBC(P<0.05)and SC(P<0.05).The pooled sensitivity and AUC did not change significantly in the sensitivity analysis.CONCLUSION LBC may be sensitive than SC in the cytological diagnosis of pancreatic lesions,however,the superior diagnostic performance of their combination emphasizes their integrated usage in the clinical evaluation of pancreatic lesions.展开更多
Objective:To explore the diagnostic value of abnormal prothrombinⅡ(PIVKA-Ⅱ)and alpha-fetoprotein(AFP)in primary hepatocellular carcinoma(HCC).Methods:From 20180.01 to 2020.01,there were 158 patients with primary liv...Objective:To explore the diagnostic value of abnormal prothrombinⅡ(PIVKA-Ⅱ)and alpha-fetoprotein(AFP)in primary hepatocellular carcinoma(HCC).Methods:From 20180.01 to 2020.01,there were 158 patients with primary liver cancer caused by chronic hepatitis B(male 116,women 42)and 62 patients with chronic hepatitis B(male 34,female 28).The levels of serum PIVKA-Ⅱand AFP were measured,and the results were statistically analyzed.Results:The value of PIVKA-Ⅱin liver cancer group was distinctly higher than that in chronic viral hepatitis B group,the difference is statistically significant(P<0.05).So does the value of AFP.Draw the subject working characteristic curve(ROC curve),the area under the curve of AFP and PIVKA-Ⅱis 0.799 and 0.836,and that of the combination of AFP and PIVKA-Ⅱis 0.854,the sensitivity is 57.6%,68.4%,72.2%,respectively,the specificity is93.5%,98.4%,96.8%,respectively.After operation or interventional therapy,the value of PIVKA-Ⅱin liver cancer group was clearly lower than that before treatment,and the difference was statistically significant.Conclusion:In the diagnostic value of primary liver cancer,PIVKA-Ⅱcombined with AFP is higher than PIVKA-Ⅱ,while AFP has the lowest benefit.We also find that PIVKA-Ⅱhas higher disease monitoring value than AFP.展开更多
Objective: To compare the feasibility and applicability of predicting the prognosis of patients using the Early Warning Score(MEWS) system and the Acute Physiology and Chronic Health Evaluation(APACHE Ⅱ) system in th...Objective: To compare the feasibility and applicability of predicting the prognosis of patients using the Early Warning Score(MEWS) system and the Acute Physiology and Chronic Health Evaluation(APACHE Ⅱ) system in the Emergency Department.Methods: Using a prospective study method, the APACHE Ⅱ and MEWS data for 640 patients hospitalized in the Emergency Internal Medicine Department were collected. The prognoses, two scores to predict the corresponding prediction index of sensitivity, specificity and positive predictive value for the prognosis,the negative predictive value and the ROC curve for predicting the prognosis were analyzed for all patients.Results: In the prediction of the risk of mortality, the MEWS system had a high resolution. The MEWS area under the ROC curve was 0.93. The area under the ROC curve for the APACHE score was 0.79, and the difference was statistically significant(Z =4.348, P < 0.01).Conclusions: Both the MEWS and APACHE Ⅱ systems can be used to determine the severity of emergency patients and have a certain predictive value for the patient's mortality risk. However, the MEWS system is simple and quick to operate, making it a useful supplement for APACHE Ⅱ score.展开更多
<b><span style="font-family:Verdana;">Objective</span></b><b><span style="font-family:Verdana;">:</span></b><b><span style="font-family...<b><span style="font-family:Verdana;">Objective</span></b><b><span style="font-family:Verdana;">:</span></b><b><span style="font-family:""> </span></b><span style="font-family:""><span style="font-family:Verdana;">To compare the distribution of “mean corpuscular hemoglobin”-MCV, “mean corpuscular volume”-MCH, “hemoglobin”-HGB, “hemoglobin A”-HbA and “hemoglobin A2”-HbA2 in </span><i><span style="font-family:Verdana;">α</span></i><span style="font-family:Verdana;"> and </span><i><span style="font-family:Verdana;">β</span></i><span style="font-family:Verdana;"> thalassemia hematology screening between Li and Han nationality, and analyze the best diagnostic cut-off value. </span><b><span style="font-family:Verdana;">Methods</span></b></span><b><span style="font-family:Verdana;">:</span></b><b><span style="font-family:""> </span></b><span style="font-family:""><span style="font-family:Verdana;">Select 7816 middle school students from Li nationality area as the research object, collect peripheral blood for blood cell analysis, hemoglobin electrophoresis and thalassaemia gene detection, and compare the difference in hematological parameters of common thalassemia genotype between Li and Han nationalities. Taking the genetic test results as the gold standard, construct the receiver operator characteristic curve (ROC curve) of relevant hematology parameters, calculate the Youden index and take its maximum diagnostic cut-off point as the best critical value.</span><b><span style="font-family:Verdana;"> Results</span></b></span><b><span style="font-family:Verdana;">:</span></b><b><span style="font-family:""> </span></b><span style="font-family:""><span style="font-family:Verdana;">Comparison of hematological parameters of common thalassemia genotypes showed that the average value of MCH and MCV of -</span><i><span style="font-family:Verdana;">α</span></i><span style="font-family:Verdana;">3.7/-</span><i><span style="font-family:Verdana;">α</span></i><span style="font-family:Verdana;">4.2 type in Li nationality was lower than that of Han nationality, and the average value of HbA2 of CD41-42/</span><i><span style="font-family:Verdana;">β</span></i><span style="font-family:Verdana;">N type was higher than that of Han nationality, there was no significant difference among other genotypes. ROC curve analysis shows that the MCH, MCV, and HGB values </span></span><span style="font-family:Verdana;">have p</span><span style="font-family:""><span style="font-family:Verdana;">oor diagnostic efficiency for thalassaemia, HbA has a slightly better diagnostic efficiency for </span><i><span style="font-family:Verdana;">α</span></i><span style="font-family:Verdana;"> thalassaemia, and the optimal cut-off values </span></span><span style="font-family:Verdana;">of HbA for Li and Han </span><span style="font-family:""><span style="font-family:Verdana;">nationalities are 96.95% and 97.75%, respectively;HbA2 has better screening efficiency for </span><i><span style="font-family:Verdana;">β</span></i><span style="font-family:Verdana;">-thalassemia, and the optimal cut-off values of HbA2 for Li and Han nationalities are 4.20% and 3.45% respectively. </span><b><span style="font-family:Verdana;">Conclusion</span></b></span><b><span style="font-family:Verdana;">:</span></b><span style="font-family:Verdana;"> In the prevention and control screening of thalassaemia in the Li and Han nationalities, hemoglobin electrophoresis technology has a better diagnostic efficiency.展开更多
This work diagnosed the precipitation extremes over the Brazilian Northeast (NEB) based on logistic regression for obtaining associations between precipitation extremes and the meteorological variables by Odd Ratio (O...This work diagnosed the precipitation extremes over the Brazilian Northeast (NEB) based on logistic regression for obtaining associations between precipitation extremes and the meteorological variables by Odd Ratio (OR). Data of ten meteorological variables to the NEB (North (NNEB), East (ENEB), South (SNEB) and Semiarid (SANEB)) were used daily. The OR results evidenced that the outgoing longwave radiation was the key variable on the precipitation extremes detection in three sub-regions: ENEB with 2.91 times (95% confidence interval (CI): 2.11, 4.02), NNEB with 3.63 times (95% CI: 1.93, 6.83), and SANEB with 5.40 times (95% CI: 3.04, 9.61);while on SNEB, it was relative humidity with 3.88 times (95% CI: 2.89, 5.20) more chance to favor the precipitation extremes. The maximum temperature, zonal wind component, evaporation, specific humidity and RH also had influence on these extremes. Goodness-of-fit and ROC analysis demonstrated that all models had a good fit and good predictive capability.展开更多
To evaluate the applicability of the M-score model in the Chinese capital market,this research observed 190 financial fraud samples punished by the China Securities Regulatory Commission(CSRC)in the years from 2014 to...To evaluate the applicability of the M-score model in the Chinese capital market,this research observed 190 financial fraud samples punished by the China Securities Regulatory Commission(CSRC)in the years from 2014 to 2018.The test results indicate that two types of errors are high,which means that the applicability of the M-score is unacceptable.Therefore,in this paper,a 9-index model is constructed by Wald's backward stepwise regression method,and the optimal threshold is set by the Beneish expected cost method(ECM).The accuracy of the modified M-score is significantly improved,especially the Type I error rate of is reduced from 70.37%to 19.75%.The receiver operating characteristic(ROC)curve test also proves the superior identification effect of the modified M-score applied in the Chinese market.Finally,variables such as current ratio,fixed asset index,and equity concentration in the modified model could represent the fraud characteristics of Chinese listed companies.展开更多
Understanding the drivers of biological invasions in landscapes is a major goal in invasion ecology.The control of biological invasions has increasingly become critical in the past few decades because invasive species...Understanding the drivers of biological invasions in landscapes is a major goal in invasion ecology.The control of biological invasions has increasingly become critical in the past few decades because invasive species are thought to be a major threat to endemism.In this study,by examining the key variables that influence Acacia mearnsii,we sought to understand its potential invasion in eastern Zimbabwe.We used the maximum entropy(MaxEnt)method against a set of environmental variables to predict the potential invasion front of A.mearnsii.Our study showed that the predictor variables,i.e.,aspect,elevation,distance from streams,soil type and distance from the nearest A.mearnsii plantation adequately explained(training AUC=0.96 and test AUC=0.93)variability in the spatial distribution of invading A.mearnsii.The front of invasion by A.mearnsii seemed also to occur next to existing A.mearnsii plantations.Results from our study could be useful in identifying priority areas that could be targeted for controlling the spread of A.mearnsii in Zimbabwe and other areas under threat from A.mearnsii invasion.We recommend that the plantation owners pay for the control of A.mearnsii invasion about their plantations.展开更多
Achieving higher true positive rate when decreasing false positive rate is always a great challenge to the imbalance learning community.This work combines penalized empirical likelihood method,lower bound algorithm an...Achieving higher true positive rate when decreasing false positive rate is always a great challenge to the imbalance learning community.This work combines penalized empirical likelihood method,lower bound algorithm and Nyströmmethod and applies these techniques along with kernel method to density ratio model.The resulting classifier,density ratio classifier(DRC),is a combination of kernelization,regularization,efficient implementation and threshold moving,all of which are critical to enable DRC to be an effective and powerful method for solving difficult imbalance problems.Compared with other methods,DRC is competitive in that it is widely applicable and it is simple and easy to use without additional imbalance handling skills.In addition,the convergence rate of the estimate of log density ratio is discussed as well.And the results of numerical analysis also show that DRC outperforms other methods in AUC and G-mean score.展开更多
Power systems transport an increasing amount of electricity,and in the future,involve more distributed renewables and dynamic interactions of the equipment.The system response to disturbances must be secure and predic...Power systems transport an increasing amount of electricity,and in the future,involve more distributed renewables and dynamic interactions of the equipment.The system response to disturbances must be secure and predictable to avoid power blackouts.The system response can be simulated in the time domain.However,this dynamic security assessment(DSA)is not computationally tractable in real-time.Particularly promising is to train decision trees(DTs)from machine learning as interpretable classifiers to predict whether the systemwide responses to disturbances are secure.In most research,selecting the best DT model focuses on predictive accuracy.However,it is insufficient to focus solely on predictive accuracy.Missed alarms and false alarms have drastically different costs,and as security assessment is a critical task,interpretability is crucial for operators.In this work,the multiple objectives of interpretability,varying costs,and accuracies are considered for DT model selection.We propose a rigorous workflow to select the best classifier.In addition,we present two graphical approaches for visual inspection to illustrate the selection sensitivity to probability and impacts of disturbances.We propose cost curves to inspect selection combining all three objectives for the first time.Case studies on the IEEE 68 bus system and the French system show that the proposed approach allows for better DT-selections,with an 80%increase in interpretability,5%reduction in expected operating cost,while making almost zero accuracy compromises.The proposed approach scales well with larger systems and can be used for models beyond DTs.Hence,this work provides insights into criteria for model selection in a promising application for methods from artificial intelligence(AI).展开更多
The aim is to explore the predictive value of salivary bacteria for the presence of esophageal squamous cell carcinoma (ESCC). Saliva samples were obtained from 178 patients with ESCC and 101 healthy controls, and all...The aim is to explore the predictive value of salivary bacteria for the presence of esophageal squamous cell carcinoma (ESCC). Saliva samples were obtained from 178 patients with ESCC and 101 healthy controls, and allocated to screening and verification cohorts, respectively. In the screening phase, after saliva DNA was extracted, 16S rRNA V4 regions of salivary bacteria were amplified by polymerase chain reaction (PCR) with high-throughput sequencing. Highly expressed target bacteria were screened by Operational Taxonomic Units clustering, species annotation and microbial diversity assessment. In the verification phase, the expression levels of target bacteria identified in the screening phase were verified by absolute quantitative PCR (Q-PCR). Receiver operating characteristic (ROC) curves were plotted to investigate the predictive value of target salivary bacteria. LEfSe analysis revealed higher proportions of Fusobacterium, Streptococcus and Porphyromonas, and Q-PCR assay showed significantly higher numbers of Streptococcus salivarius, Fusobacterium nucleatum and Porphyromonas gingivalis in patients with ESCC, when compared with healthy controls (all P < 0.05). The areas under the ROC curves for Streptococcus salivarius, Fusobacterium nucleatum, Porphyromonas gingivalis and the combination of the three bacteria for predicting patients with ESCC were 69%, 56.5%, 61.8% and 76.4%, respectively. The sensitivities corresponding to cutoff value were 69.3%, 22.7%, 35.2% and 86.4%, respectively, and the matched specificity were 78.4%, 96.1%, 90.2% and 58.8%, respectively. These highly expressed Streptococcus salivarius, Fusobacterium nucleatum and Porphyromonas gingivalis in the saliva, alone or in combination, indicate their predictive value for ESCC.展开更多
基金This paper was supported by the National Natural Science Foundation of China(NSFC)[61179066].
文摘To estimate the fuel consumption of a civil aircraft,we propose to use the receiver operating characteristic(ROC)curve to optimize a support vector machine(SVM)model.The new method and procedure has been developed to build,train,validate,and apply an SVM model.A conceptual support vector network is proposed to model fuel consumption,and the flight data collected from routes are used as the inputs to train an SVM model.During the training phase,an ROC curve is defined to evaluate the performance of the model.To validate the applicability of the trained model,a case study is developed to compare the data from an aircraft performance manual and from the implemented simulation model.The investigated aircraft in the case study is a Boeing 737-800 powered by CFM-56 engines.The comparison has shown that the trained SVM model from the proposed procedure is capable of representing a complex fuel consumption function accurately for all phases during the flight.The proposed methodology is generic,and can be extended to reliably model the fuel consumption of other types of aircraft,such as piston engine aircraft or turboprop engine aircraft.
基金the Brazilian agency CNPq for financial support.
文摘Several mathematical models have been proposed to describe the dynamics of irradiated cancer cells and to evaluate the tumour control probability (TCP). In this article, we propose a TCP model-based statistical test for predicting the outcome of a radiation treatment. We determine the foresight capability of prostate tumour erradication (cure) from Monte Carlo simulations of the Dawson-Hillen TCP model. We construct the receiver operating characteristic (ROC) curves of the test from the probability distributions of the fraction of remaining tumour cells for simulated experiments that evolve either to cure or non-cure. Simulations show that a similar procedure may be applicable to clinical data. Results suggest that the evaluation of tumour sizes after the treatment has started may be used for short-term prognosis.
基金supported by the National Natural Science Foundation of China(51875535)the Natural Science Foundation for Young Scientists of Shanxi Province(201701D221017,201901D211242)。
文摘To improve the ability of detecting underwater targets under strong wideband interference environment,an efficient method of line spectrum extraction is proposed,which fully utilizes the feature of the target spectrum that the high intense and stable line spectrum is superimposed on the wide continuous spectrum.This method modifies the traditional beam forming algorithm by calculating and fusing the beam forming results at multi-frequency band and multi-azimuth interval,showing an excellent way to extract the line spectrum when the interference and the target are not in the same azimuth interval simultaneously.Statistical efficiency of the estimated azimuth variance and corresponding power of the line spectrum band depends on the line spectra ratio(LSR)of the line spectrum.The change laws of the output signal to noise ratio(SNR)with the LSR,the input SNR,the integration time and the filtering bandwidth of different algorithms bring the selection principle of the critical LSR.As the basis,the detection gain of wideband energy integration and the narrowband line spectrum algorithm are theoretically analyzed.The simulation detection gain demonstrates a good match with the theoretical model.The application conditions of all methods are verified by the receiver operating characteristic(ROC)curve and experimental data from Qiandao Lake.In fact,combining the two methods for target detection reduces the missed detection rate.The proposed post-processing method in2-dimension with the Kalman filter in the time dimension and the background equalization algorithm in the azimuth dimension makes use of the strong correlation between adjacent frames,could further remove background fluctuation and improve the display effect.
基金This work was supported by the Deanship of Scientific Research,Vice Presidency for Graduate Studies and Scientific Research,King Faisal University,Saudi Arabia(Project no.GRANT 324).
文摘Coronavirus 2019(COVID-19)is the current global buzzword,putting the world at risk.The pandemic’s exponential expansion of infected COVID-19 patients has challenged the medical field’s resources,which are already few.Even established nations would not be in a perfect position to manage this epidemic correctly,leaving emerging countries and countries that have not yet begun to grow to address the problem.These problems can be solved by using machine learning models in a realistic way,such as by using computer-aided images during medical examinations.These models help predict the effects of the disease outbreak and help detect the effects in the coming days.In this paper,Multi-Features Decease Analysis(MFDA)is used with different ensemble classifiers to diagnose the disease’s impact with the help of Computed Tomography(CT)scan images.There are various features associated with chest CT images,which help know the possibility of an individual being affected and how COVID-19 will affect the persons suffering from pneumonia.The current study attempts to increase the precision of the diagnosis model by evaluating various feature sets and choosing the best combination for better results.The model’s performance is assessed using Receiver Operating Characteristic(ROC)curve,the Root Mean Square Error(RMSE),and the Confusion Matrix.It is observed from the resultant outcome that the performance of the proposed model has exhibited better efficient.
基金funded by Vietnam National Foundation for Science and Technology Development (NAFOSTED)under Grant No.105.08-2019.03.
文摘Flash floods are one of the most dangerous natural disasters,especially in hilly terrain,causing loss of life,property,and infrastructures and sudden disruption of traffic.These types of floods are mostly associated with landslides and erosion of roads within a short time.Most of Vietnamis hilly and mountainous;thus,the problem due to flash flood is severe and requires systematic studies to correctly identify flood susceptible areas for proper landuse planning and traffic management.In this study,three Machine Learning(ML)methods namely Deep Learning Neural Network(DL),Correlation-based FeatureWeighted Naive Bayes(CFWNB),and Adaboost(AB-CFWNB)were used for the development of flash flood susceptibility maps for hilly road section(115 km length)of National Highway(NH)-6 inHoa Binh province,Vietnam.In the proposedmodels,88 past flash flood events were used together with 14 flash floods affecting topographical and geo-environmental factors.The performance of themodels was evaluated using standard statisticalmeasures including Receiver Operating Characteristic(ROC)Curve,Area Under Curve(AUC)and Root Mean Square Error(RMSE).The results revealed that all the models performed well(AUC>0.80)in predicting flash flood susceptibility zones,but the performance of the DL model is the best(AUC:0.972,RMSE:0.352).Therefore,the DL model can be applied to develop an accurate flash flood susceptibility map of hilly terrain which can be used for proper planning and designing of the highways and other infrastructure facilities besides landuse management of the area.
文摘Objective:To test the diagnostic performance of percent free prostate-specific antigen(%fPSA)in predicting any prostate cancer(PCa)and high-grade prostate cancer(HGPCa)in a retrospective multi-center biopsy cohort with a PSA level of 4.0e10.0 ng/mL in China.Methods:Consecutive patients with a PSA of 4.0-10.0 ng/mL who underwent transrectal ultrasound-guided biopsy were enrolled at 16 Chinese medical centers from January 1st,2010 to December 31st,2013.Total and free serum PSA determinations were performed using three types of electro-chemiluminescence immunoassays recalibrated to the World Health Organization(WHO)standard.The diagnostic accuracy of PSA,%fPSA,and %fPSA in combination with PSA(%fPSA t PSA)was determined using the area under the receiver operating characteristic(ROC)curve(AUC).Results:A total of 2310 consecutive men with PSA levels between 4.0 and 10.0 ng/mL were included,and the detection rate of PCa was 25.1%.The AUC of%fPSA and %fPSA t PSA in predicting any PCa was superior to PSA alone in men aged≥60 years(0.623 vs.0.534,p<0.0001)but not in men aged 40e59 years(0.517 vs.0.518,p=0.939).Similar result was yield in predicting HGPCa.Conclusion:In a clinical setting of Chinese men with 4.0e10.0 ng/mL PSA undergoing initial prostate biopsy,adding %fPSA to PSA can moderately improve the diagnostic accuracy for any PCa and HGPCa compared with PSA alone in patients≥60 but not in patients aged 40-59 years.
基金supported by the National Natural Science Foundation of China(Grant Nos.41501361,41401385,30871965)the China Postdoctoral Science Foundation(No.2018M630728)+2 种基金the Open Fund of Fujian Provincial Key Laboratory of Resources and Environment Monitoring&Sustainable Management and Utilization(No.ZD1403)the Open Fund of Fujian Mine Ecological Restoration Engineering Technology Research Center(No.KS2018005)the Scientific Research Foundation of Fuzhou University(No.XRC1345)
文摘The construction of a pest detection algorithm is an important step to couple"ground-space"characteristics,which is also the basis for rapid and accurate monitoring and detection of pest damage.In four experimental areas in Sanming City,Jiangle County,Sha County and Yanping District in Fujian Province,sample data on pest damage in 182 sets of Dendrolimus punctatus were collected.The data were randomly divided into a training set and testing set,and five duplicate tests and one eliminating-indicator test were done.Based on the characterization analysis of the host for D.punctatus damage,seven characteristic indicators of ground and remote sensing including leaf area index,standard error of leaf area index(SEL)of pine forest,normalized difference vegetation index(NDVI),wetness from tasseled cap transformation(WET),green band(B2),red band(B3),near-infrared band(B4)of remote sensing image are obtained to construct BP neural networks and random forest models of pest levels.The detection results of these two algorithms were comprehensively compared from the aspects of detection precision,kappa coefficient,receiver operating characteristic curve,and a paired t test.The results showed that the seven indicators all were responsive to pest damage,and NDVI was relatively weak;the average pest damage detection precision of six tests by BP neural networks was 77.29%,the kappa coefficient was 0.6869 and after the RF algorithm,the respective values were 79.30%and 0.7151,showing that the latter is more optimized,but there was no significant difference(p>0.05);the detection precision,kappa coefficient and AUC of the RF algorithm was higher than the BP neural networks for three pest levels(no damage,moderate damage and severe damage).The detection precision and AUC of BP neural networks were a little higher for mild damage,but the difference was not significant(p>0.05)except for the kappa coefficient for the no damage level(p<0.05).An"over-fitting"phenomenon tends to occur in BP neural networks,while RF method is more robust,providing a detection effect that is better than the BP neural networks.Thus,the application of the random forest algorithm for pest damage and multilevel dispersed variables is thus feasible and suggests that attention to the proportionality of sample data from various categories is needed when collecting data.
文摘BACKGROUND:In the management of critically ill patients,the assessment of volume responsiveness and the decision to administer a fluid bolus constitute a common dilemma for physicians.Static indices of cardiac preload are poor predictors of volume responsiveness.Passive leg raising(PLR) mimics an endogenous volume expansion(VE) that can be used to predict fluid responsiveness.This study was to assess the changes in stroke volume index(SVI) induced by PLR as an indicator of fluid responsiveness in mechanically ventilated patients with severe sepsis.METHODS:This was a prospective study.Thirty-two mechanically ventilated patients with severe sepsis were admitted for VE in ICU of the First Affiliated Hospital,Zhejiang University School of Medicine and Ningbo Medical Treatment Center Lihuili Hospital from May 2010 to December 2011.Patients with non-sinus rhythm or arrhythmia,parturients,and amputation of the lower limbs were excluded.Measurements of SVI were obtained in a semi-recumbent position(baseline) and during PLR by the technique of pulse indicator continuous cardiac output(PiCCO) system prior to VE.Measurements were repeated after VE(500 mL 6%hydroxyethyl starch infusion within 30 minutes)to classify patients as either volume responders or non-responders based on their changes in stroke volume index(ASVI) over 15%.Heart rate(HR),systolic artery blood pressure(ABPs),diastolic artery blood pressure(ABPd),mean arterial blood pressure(ABPm),mean central venous pressure(CVPm)and cardiac index(CI) were compared between the two groups.The changes of ABPs,ABPm,CVPm,and SVI after PLR and VE were compared with the indices at the baseline.The ROC curve was drawn to evaluate the value of ASVI and the change of CVPm(ACVPm) in predicting volume responsiveness.SPSS 17.0 software was used for statistical analysis.RESULTS:Among the 32 patients,22 were responders and 10 were non-responders.After PLR among the responders,some hemodynamic variables(including ABPs,ABPd,ABPm and CVPm)were significantly elevated(101.2±17.6 vs.118.6±23.7,P=0.03;52.8±10.7 vs.64.8±10.7,P=0.006;68.3+11.7 vs.81.9±14.4,P=0.008;6.8±3.2 vs.11.9±4.0,P=0.001).After PLR,the area under curve(AUC) and the ROC curve of △SV1 and ACVPm for predicting the responsiveness after VE were0.882±0.061(95%CI 0.759-1.000) and 0.805±0.079(95%CI 0.650-0.959) when the cut-off levels of ASVI and ACVPm were 8.8%and 12.7%,the sensitivities were 72.7%and 72.7%,and the specificities were 80%and 80%.CONCLUSION:Changes in ASVI and ACVPm induced by PLR are accurate indices for predicting fluid responsiveness in mechanically ventilated patients with severe sepsis.
基金the Natural Science Foundation of Zhejiang Province,No.LQ20H160061Medical Health Science and Technology Project of Zhejiang Provincial Health Commission,No.2018255969.
文摘BACKGROUND Smear cytology(SC)using endoscopic ultrasound-guided fine needle aspiration(EUS-FNA)is the established and traditional choice for diagnosing pancreatic lesions.Liquid-based cytology(LBC)is a novel alternative cytological method,however,the comparative diagnostic efficacy of LBC remains inconclusive.AIM To examine the diagnostic efficacy of LBC and SC for pancreatic specimens obtained through EUS-FNA via a systematic review and meta-analysis.METHODS A systematic literature search was performed using PubMed,EMBASE,the Cochrane Library,and Web of Science.The numbers of true positives,false positives,true negatives,and false negatives for each cytological test(LBC and CS)were extracted from the included studies.The pooled sensitivity and specificity and the area under the summary receiver operating characteristic curve(AUC)were calculated,and the AUC was compared by Tukey's multiple comparisons test.The quality of the included studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies II tool.RESULTS A total of 1656 patients in eight studies were included.The pooled sensitivity and specificity and the AUC for LBC were 0.76(95%CI:0.72-0.79),1.00(95%CI:0.98-1.00),and 0.9174,respectively,for diagnosing pancreatic lesions.The pooled estimates for SC were as follows:Sensitivity,0.68(95%CI:0.64-0.71);specificity,0.99(95%CI:0.96-100.00);and AUC,0.9714.Similarly,the corresponding values for LBC combined with SC were 0.87(95%CI:0.84-0.90),0.99(95%CI:0.96-1.00),and 0.9894.Tukey’s multiple comparisons test was used to compare the sensitivities and AUCs of the three diagnostic methods;statistically significant differences were found between the three methods,and LBC combined with SC was superior to both LBC(P<0.05)and SC(P<0.05).The pooled sensitivity and AUC did not change significantly in the sensitivity analysis.CONCLUSION LBC may be sensitive than SC in the cytological diagnosis of pancreatic lesions,however,the superior diagnostic performance of their combination emphasizes their integrated usage in the clinical evaluation of pancreatic lesions.
基金Zhejiang Medical and Health Science and Technology Plan Project(2019KY663)Wenzhou Science and Technology Plan Project of Zhejiang Province(Y20180182)Science and Technology Plan Project of Ruian City,Zhejiang Province(Y2014017)。
文摘Objective:To explore the diagnostic value of abnormal prothrombinⅡ(PIVKA-Ⅱ)and alpha-fetoprotein(AFP)in primary hepatocellular carcinoma(HCC).Methods:From 20180.01 to 2020.01,there were 158 patients with primary liver cancer caused by chronic hepatitis B(male 116,women 42)and 62 patients with chronic hepatitis B(male 34,female 28).The levels of serum PIVKA-Ⅱand AFP were measured,and the results were statistically analyzed.Results:The value of PIVKA-Ⅱin liver cancer group was distinctly higher than that in chronic viral hepatitis B group,the difference is statistically significant(P<0.05).So does the value of AFP.Draw the subject working characteristic curve(ROC curve),the area under the curve of AFP and PIVKA-Ⅱis 0.799 and 0.836,and that of the combination of AFP and PIVKA-Ⅱis 0.854,the sensitivity is 57.6%,68.4%,72.2%,respectively,the specificity is93.5%,98.4%,96.8%,respectively.After operation or interventional therapy,the value of PIVKA-Ⅱin liver cancer group was clearly lower than that before treatment,and the difference was statistically significant.Conclusion:In the diagnostic value of primary liver cancer,PIVKA-Ⅱcombined with AFP is higher than PIVKA-Ⅱ,while AFP has the lowest benefit.We also find that PIVKA-Ⅱhas higher disease monitoring value than AFP.
基金supported by Pudong New Area Health System leadership program(No.PWRd2016-11)National Natural Science Foundation of China(No.81360231)
文摘Objective: To compare the feasibility and applicability of predicting the prognosis of patients using the Early Warning Score(MEWS) system and the Acute Physiology and Chronic Health Evaluation(APACHE Ⅱ) system in the Emergency Department.Methods: Using a prospective study method, the APACHE Ⅱ and MEWS data for 640 patients hospitalized in the Emergency Internal Medicine Department were collected. The prognoses, two scores to predict the corresponding prediction index of sensitivity, specificity and positive predictive value for the prognosis,the negative predictive value and the ROC curve for predicting the prognosis were analyzed for all patients.Results: In the prediction of the risk of mortality, the MEWS system had a high resolution. The MEWS area under the ROC curve was 0.93. The area under the ROC curve for the APACHE score was 0.79, and the difference was statistically significant(Z =4.348, P < 0.01).Conclusions: Both the MEWS and APACHE Ⅱ systems can be used to determine the severity of emergency patients and have a certain predictive value for the patient's mortality risk. However, the MEWS system is simple and quick to operate, making it a useful supplement for APACHE Ⅱ score.
文摘<b><span style="font-family:Verdana;">Objective</span></b><b><span style="font-family:Verdana;">:</span></b><b><span style="font-family:""> </span></b><span style="font-family:""><span style="font-family:Verdana;">To compare the distribution of “mean corpuscular hemoglobin”-MCV, “mean corpuscular volume”-MCH, “hemoglobin”-HGB, “hemoglobin A”-HbA and “hemoglobin A2”-HbA2 in </span><i><span style="font-family:Verdana;">α</span></i><span style="font-family:Verdana;"> and </span><i><span style="font-family:Verdana;">β</span></i><span style="font-family:Verdana;"> thalassemia hematology screening between Li and Han nationality, and analyze the best diagnostic cut-off value. </span><b><span style="font-family:Verdana;">Methods</span></b></span><b><span style="font-family:Verdana;">:</span></b><b><span style="font-family:""> </span></b><span style="font-family:""><span style="font-family:Verdana;">Select 7816 middle school students from Li nationality area as the research object, collect peripheral blood for blood cell analysis, hemoglobin electrophoresis and thalassaemia gene detection, and compare the difference in hematological parameters of common thalassemia genotype between Li and Han nationalities. Taking the genetic test results as the gold standard, construct the receiver operator characteristic curve (ROC curve) of relevant hematology parameters, calculate the Youden index and take its maximum diagnostic cut-off point as the best critical value.</span><b><span style="font-family:Verdana;"> Results</span></b></span><b><span style="font-family:Verdana;">:</span></b><b><span style="font-family:""> </span></b><span style="font-family:""><span style="font-family:Verdana;">Comparison of hematological parameters of common thalassemia genotypes showed that the average value of MCH and MCV of -</span><i><span style="font-family:Verdana;">α</span></i><span style="font-family:Verdana;">3.7/-</span><i><span style="font-family:Verdana;">α</span></i><span style="font-family:Verdana;">4.2 type in Li nationality was lower than that of Han nationality, and the average value of HbA2 of CD41-42/</span><i><span style="font-family:Verdana;">β</span></i><span style="font-family:Verdana;">N type was higher than that of Han nationality, there was no significant difference among other genotypes. ROC curve analysis shows that the MCH, MCV, and HGB values </span></span><span style="font-family:Verdana;">have p</span><span style="font-family:""><span style="font-family:Verdana;">oor diagnostic efficiency for thalassaemia, HbA has a slightly better diagnostic efficiency for </span><i><span style="font-family:Verdana;">α</span></i><span style="font-family:Verdana;"> thalassaemia, and the optimal cut-off values </span></span><span style="font-family:Verdana;">of HbA for Li and Han </span><span style="font-family:""><span style="font-family:Verdana;">nationalities are 96.95% and 97.75%, respectively;HbA2 has better screening efficiency for </span><i><span style="font-family:Verdana;">β</span></i><span style="font-family:Verdana;">-thalassemia, and the optimal cut-off values of HbA2 for Li and Han nationalities are 4.20% and 3.45% respectively. </span><b><span style="font-family:Verdana;">Conclusion</span></b></span><b><span style="font-family:Verdana;">:</span></b><span style="font-family:Verdana;"> In the prevention and control screening of thalassaemia in the Li and Han nationalities, hemoglobin electrophoresis technology has a better diagnostic efficiency.
基金CAPES for doctoral financial supportGeorge Pedra and Naurinete Barreto by several contributions for this article.P.S.Lucio is sponsored by a PQ2 grant(Proc.302493/2007-7)from CNPq(Brazil).
文摘This work diagnosed the precipitation extremes over the Brazilian Northeast (NEB) based on logistic regression for obtaining associations between precipitation extremes and the meteorological variables by Odd Ratio (OR). Data of ten meteorological variables to the NEB (North (NNEB), East (ENEB), South (SNEB) and Semiarid (SANEB)) were used daily. The OR results evidenced that the outgoing longwave radiation was the key variable on the precipitation extremes detection in three sub-regions: ENEB with 2.91 times (95% confidence interval (CI): 2.11, 4.02), NNEB with 3.63 times (95% CI: 1.93, 6.83), and SANEB with 5.40 times (95% CI: 3.04, 9.61);while on SNEB, it was relative humidity with 3.88 times (95% CI: 2.89, 5.20) more chance to favor the precipitation extremes. The maximum temperature, zonal wind component, evaporation, specific humidity and RH also had influence on these extremes. Goodness-of-fit and ROC analysis demonstrated that all models had a good fit and good predictive capability.
文摘To evaluate the applicability of the M-score model in the Chinese capital market,this research observed 190 financial fraud samples punished by the China Securities Regulatory Commission(CSRC)in the years from 2014 to 2018.The test results indicate that two types of errors are high,which means that the applicability of the M-score is unacceptable.Therefore,in this paper,a 9-index model is constructed by Wald's backward stepwise regression method,and the optimal threshold is set by the Beneish expected cost method(ECM).The accuracy of the modified M-score is significantly improved,especially the Type I error rate of is reduced from 70.37%to 19.75%.The receiver operating characteristic(ROC)curve test also proves the superior identification effect of the modified M-score applied in the Chinese market.Finally,variables such as current ratio,fixed asset index,and equity concentration in the modified model could represent the fraud characteristics of Chinese listed companies.
文摘Understanding the drivers of biological invasions in landscapes is a major goal in invasion ecology.The control of biological invasions has increasingly become critical in the past few decades because invasive species are thought to be a major threat to endemism.In this study,by examining the key variables that influence Acacia mearnsii,we sought to understand its potential invasion in eastern Zimbabwe.We used the maximum entropy(MaxEnt)method against a set of environmental variables to predict the potential invasion front of A.mearnsii.Our study showed that the predictor variables,i.e.,aspect,elevation,distance from streams,soil type and distance from the nearest A.mearnsii plantation adequately explained(training AUC=0.96 and test AUC=0.93)variability in the spatial distribution of invading A.mearnsii.The front of invasion by A.mearnsii seemed also to occur next to existing A.mearnsii plantations.Results from our study could be useful in identifying priority areas that could be targeted for controlling the spread of A.mearnsii in Zimbabwe and other areas under threat from A.mearnsii invasion.We recommend that the plantation owners pay for the control of A.mearnsii invasion about their plantations.
基金supported by National Natural Science Foundation of China(Grant No.71873128).
文摘Achieving higher true positive rate when decreasing false positive rate is always a great challenge to the imbalance learning community.This work combines penalized empirical likelihood method,lower bound algorithm and Nyströmmethod and applies these techniques along with kernel method to density ratio model.The resulting classifier,density ratio classifier(DRC),is a combination of kernelization,regularization,efficient implementation and threshold moving,all of which are critical to enable DRC to be an effective and powerful method for solving difficult imbalance problems.Compared with other methods,DRC is competitive in that it is widely applicable and it is simple and easy to use without additional imbalance handling skills.In addition,the convergence rate of the estimate of log density ratio is discussed as well.And the results of numerical analysis also show that DRC outperforms other methods in AUC and G-mean score.
基金The authors were supported by a scholarship funded by the Nige-rian National Petroleum Corporation,NNPC,the TU Delft AI Labs Programme,NL,and the research project IDLES,UK(EP/R045518/1).
文摘Power systems transport an increasing amount of electricity,and in the future,involve more distributed renewables and dynamic interactions of the equipment.The system response to disturbances must be secure and predictable to avoid power blackouts.The system response can be simulated in the time domain.However,this dynamic security assessment(DSA)is not computationally tractable in real-time.Particularly promising is to train decision trees(DTs)from machine learning as interpretable classifiers to predict whether the systemwide responses to disturbances are secure.In most research,selecting the best DT model focuses on predictive accuracy.However,it is insufficient to focus solely on predictive accuracy.Missed alarms and false alarms have drastically different costs,and as security assessment is a critical task,interpretability is crucial for operators.In this work,the multiple objectives of interpretability,varying costs,and accuracies are considered for DT model selection.We propose a rigorous workflow to select the best classifier.In addition,we present two graphical approaches for visual inspection to illustrate the selection sensitivity to probability and impacts of disturbances.We propose cost curves to inspect selection combining all three objectives for the first time.Case studies on the IEEE 68 bus system and the French system show that the proposed approach allows for better DT-selections,with an 80%increase in interpretability,5%reduction in expected operating cost,while making almost zero accuracy compromises.The proposed approach scales well with larger systems and can be used for models beyond DTs.Hence,this work provides insights into criteria for model selection in a promising application for methods from artificial intelligence(AI).
基金This study was supported by the Scientific Research Project of Guangzhou, Guangdong Province, China (No. 20184010458).
文摘The aim is to explore the predictive value of salivary bacteria for the presence of esophageal squamous cell carcinoma (ESCC). Saliva samples were obtained from 178 patients with ESCC and 101 healthy controls, and allocated to screening and verification cohorts, respectively. In the screening phase, after saliva DNA was extracted, 16S rRNA V4 regions of salivary bacteria were amplified by polymerase chain reaction (PCR) with high-throughput sequencing. Highly expressed target bacteria were screened by Operational Taxonomic Units clustering, species annotation and microbial diversity assessment. In the verification phase, the expression levels of target bacteria identified in the screening phase were verified by absolute quantitative PCR (Q-PCR). Receiver operating characteristic (ROC) curves were plotted to investigate the predictive value of target salivary bacteria. LEfSe analysis revealed higher proportions of Fusobacterium, Streptococcus and Porphyromonas, and Q-PCR assay showed significantly higher numbers of Streptococcus salivarius, Fusobacterium nucleatum and Porphyromonas gingivalis in patients with ESCC, when compared with healthy controls (all P < 0.05). The areas under the ROC curves for Streptococcus salivarius, Fusobacterium nucleatum, Porphyromonas gingivalis and the combination of the three bacteria for predicting patients with ESCC were 69%, 56.5%, 61.8% and 76.4%, respectively. The sensitivities corresponding to cutoff value were 69.3%, 22.7%, 35.2% and 86.4%, respectively, and the matched specificity were 78.4%, 96.1%, 90.2% and 58.8%, respectively. These highly expressed Streptococcus salivarius, Fusobacterium nucleatum and Porphyromonas gingivalis in the saliva, alone or in combination, indicate their predictive value for ESCC.
