Data-driven methods for predicting the representative temperature of bridge cable based on limited measured data

Cable-stayed bridges have been widely used in high-speed railway infrastructure.The accurate determination of cable’s representative temperatures is vital during the intricate processes of design,construction,and maintenance of cable-stayed bridges.However,the representative temperatures of stayed cables are not specified in the existing design codes.To address this issue,this study investigates the distribution of the cable temperature and determinates its representative temperature.First,an experimental investigation,spanning over a period of one year,was carried out near the bridge site to obtain the temperature data.According to the statistical analysis of the measured data,it reveals that the temperature distribution is generally uniform along the cable cross-section without significant temperature gradient.Then,based on the limited data,the Monte Carlo,the gradient boosted regression trees(GBRT),and univariate linear regression(ULR)methods are employed to predict the cable’s representative temperature throughout the service life.These methods effectively overcome the limitations of insufficient monitoring data and accurately predict the representative temperature of the cables.However,each method has its own advantages and limitations in terms of applicability and accuracy.A comprehensive evaluation of the performance of these methods is conducted,and practical recommendations are provided for their application.The proposed methods and representative temperatures provide a good basis for the operation and maintenance of in-service long-span cable-stayed bridges.

易流态化货物安全装运研究

文章结合理论研究和生产实际，介绍易流态化货物含水量、流动水分点和适运水分限的测定原则，提出了易流态化货物适运性判定方法，总结了此类货物装运及管理的注意事项，供广大海员在生产中参考应用。

Integrated assessment of sea water quality based on BP artificial neural network

In order to carry out an integrated assessment of sea water quality objectively, this paper based on the concept and principle of artificial neural network, generated appropriate training samples for BP artificial neural network model through the method of producing samples to the concentration of various pollution index of sea water quality from the viewpoint of threshold, established the BP artificial neural network model of sea water quality assessment using multi-layer neural network with error back-propagation algorithm. This model was used to assess water environment and obtain sea water quality categories of offshore area in Bohai Bay through calculating. The calculations shown that pollution index in river＇s wet season was higher than that in dry season from 2004 to 2007, and the pollution was particularly serious in 2005 and 2006, but a little better in 2007. The assessed results of cases shown that the model was reasonable in design and higher in generalization, meanwhile, it was common, objective and practical to sea water quality assessment.

Cascaded projection of Gaussian mixture model for emotion recognition in speech and ECG signals

A cascaded projection of the Gaussian mixture model algorithm is proposed.First,the marginal distribution of the Gaussian mixture model is computed for different feature dimensions, and a number of sub-classifiers are generated using the marginal distribution model.Each sub-classifier is based on different feature sets.The cascaded structure is adopted to fuse the sub-classifiers dynamically to achieve sample adaptation ability.Secondly,the effectiveness of the proposed algorithm is verified on electrocardiogram emotional signal and speech emotional signal.Emotional data including fidgetiness,happiness and sadness is collected by induction experiments.Finally,the emotion feature extraction method is discussed,including heart rate variability, the chaotic electrocardiogram feature and utterance level static feature.The emotional feature reduction methods are studied, including principle component analysis,sequential forward selection, the Fisher discriminant ratio and maximal information coefficient.The experimental results show that the proposed classification algorithm can effectively improve recognition accuracy in two different scenarios.

Rapid vision-based system for secondary copper content estimation

A vision-based color analysis system was developed for rapid estimation of copper content in the secondary copper smelting process. Firstly, cross section images of secondary copper samples were captured by the designed vision system. After the preprocessing and segmenting procedures, the images were selected according to their grayscale standard deviations of pixels and percentages of edge pixels in the luminance component. The selected images were then used to extract the information of the improved color vector angles, from which the copper content estimation model was developed based on the least squares support vector regression (LSSVR) method. For comparison, three additional LSSVR models, namely, only with sample selection, only with improved color vector angle, without sample selection or improved color vector angle, were developed. In addition, two exponential models, namely, with sample selection, without sample selection, were developed. Experimental results indicate that the proposed method is more effective for improving the copper content estimation accuracy, particularly when the sample size is small.

LOCAL BAGGING AND ITS APPLICATIONON FACE RECOGNITION

Bagging is not quite suitable for stable classifiers such as nearest neighbor classifiers due to the lack of diversity and it is difficult to be directly applied to face recognition as well due to the small sample size （SSS） property of face recognition. To solve the two problems,local Bagging （L-Bagging） is proposed to simultaneously make Bagging apply to both nearest neighbor classifiers and face recognition. The major difference between L-Bagging and Bagging is that L-Bagging performs the bootstrap sampling on each local region partitioned from the original face image rather than the whole face image. Since the dimensionality of local region is usually far less than the number of samples and the component classifiers are constructed just in different local regions,L-Bagging deals with SSS problem and generates more diverse component classifiers. Experimental results on four standard face image databases （AR,Yale,ORL and Yale B） indicate that the proposed L-Bagging method is effective and robust to illumination,occlusion and slight pose variation.

NEW HYBRID AI-SVM ALGORITHM: COMBINATION OF SUPPORT VECTOR MACHINES AND ARTIFICIAL IMMUNE NETWORKS

Support vector machines （SVMs） are combined with the artificial immune network （aiNet）, thus forming a new hybrid ai-SVM algorithm. The algorithm is used to reduce the number of samples and the training time of SVM on large datasets, aiNet is an artificial immune system （AIS） inspired method to perform the automatic data compression, extract the relevant information and retain the topology of the original sample distribution. The output of aiNet is a set of antibodies for representing the input dataset in a simplified way. Then the SVM model is built in the compressed antibody network instead of the original input data. Experimental results show that the ai-SVM algorithm is effective to reduce the computing time and simplify the SVM model, and the accuracy is not decreased.

Application of Artificial Neural Network to Battlefield Target Classification

To study the capacity of artificial neural network (ANN) applying to battlefield target classification and result of classification, according to the characteristics of battlefield target acoustic and seismic signals, an on the spot experiment was carried out to derive acoustic and seismic signals of a tank and jeep by special experiment system. Experiment data processed by fast Fourier transform(FFT) were used to train the ANN to distinguish the two battlefield targets. The ANN classifier was performed by the special program based on the modified back propagation (BP) algorithm. The ANN classifier has high correct identification rates for acoustic and seismic signals of battlefield targets, and is suitable for the classification of battlefield targets. The modified BP algorithm eliminates oscillations and local minimum of the standard BP algorithm, and enhances the convergence rate of the ANN.

基于TensorFlow的CNN自由手写数字识别研究

CNN卷积神经网络是图像识别和分类等领域的前沿研究方法。由于CNN模型训练效果与实际测试之间存在较大的差距,为提高自由手写数字的识别率,尝试使用TensorFlow搭构CNN网络模型,在完成MNIST数据集训练的基础上实现对自由手写数字的识别,并根据两种样本状态的差别和识别结果提出效果分析及改进方法,实验证明该改进方法获得明显效果。

On the Confidence Limits of Bernoulli Parameter in Any Sequential Case

Let x 1,x 2,… be independent identically distributed (i.i.d.) random variables, in which x n=0 or 1 and the probability of ｛x n=1｝ is p. Here p is unknown. Let τ be any finite stopping time for (x n,n1). For any sequential sample (x 1,x 2,…,x τ ) and γ∈(0,1), we have given an optimal confidence limit of p with confidence level γ . Some related problems are also discussed.

Novel technique for cost reduction in mutation testing

Aimed at the problem of expensive costs in mutation testing which has hampered its wide use,a technique of introducing a test case selection into the process of mutation testing is proposed.For each mutant,a fixed number of test cases are selected to constrain the maximum allowable executions so as to reduce useless work.Test case selection largely depends on the degree of mutation.The mutation distance is an index describing the semantic difference between the original program and the mutated program.It represents the percentage of effective test cases in a test set,so it can be used to guide the selection of test cases.The bigger the mutation distance is,the easier it is that the mutant will be killed,so the corresponding number of effective test cases for this mutant is greater.Experimental results suggest that the technique can remarkably reduce execution costs without a significant loss of test effectiveness.

Research on Stoichiometry of Early-spring Herbs Functional Group in the Subtropical Artificial Wetland

[Objective]The aim was to carry out stoichiometry on the early-spring herbs functional group in subtropical artificial wetland.[Method]UV-Vis spectrophotometer was used for the determination of nitrate-nitrogen,ammonium nitrogen and phosphorus concentrations.Potassium persulfate absorptiometry was used for the measurement of total N content,while the flame photometer was used to detect the potassium and sodium concentration in plants.All the nutrient determination of plant samples were repeated for four times.[Result]The four nutrient concentrations in almost all samples were in the normal range of natural plant nutrition concentrations;in early-spring herbs functional groups,different species showed diversity on the nutrient concentrations;plant height had no significant effect on the nutrient concentrations in plants;the nutrient concentrations of non-grass group plants were higher than that of grass group plants;the nutrient concentrations of the annual herb were higher than that of perennial herbs.[Conclusion]The study had provided basis for the understanding of the effects of changes in nutritional conditions on species diversity,community structure and succession of the system.

Endoscopic ultrasonography-guided fine needle aspiration:Relatively low sensitivity in the endosonographer population

AIM： To assess the characteristics and quality of endoscopic ultrasonography-guided fine needle aspiration （EUS-FNA） in a large panel of endosonographers.METHODS： A survey was conducted during the 13th annual live course of endoscopic ultrasonography （EUS） held in Amsterdam, Netherlands. A 2-page question- naire was developed for the study. Content validity of the questionnaire was determined based on input by experts in the field and a review of the relevant literature. It contained 30 questions that pertained to demographics and the current practice for EUS-FNA of responders, including sampling technique, sample processing, cytopathological diagnosis and sensitivity of EUS-FNA for the diagnosis of solid mass lesions. One hundred and sixty-one endosonographers whoattended the course were asked to answer the survey. This allowed assessing the current practice of EUS-FNA as well as the self-reported sensitivity of EUS-FNA for the diagnosis of solid mass lesions. We also examined which factors were associated with a self-reported sensitivity of EUS-FNA for the diagnosis of solid mass lesions 〉 80%.RESULTS： Completed surveys were collected from 92 （57.1%） of 161 endosonographers who attended the conference. The endosonographers had been practio ing endoscopy and EUS for 22.5 4. 7.8 years and 4.8 4- 4.1 years, respectively; one third of them worked in a hospital with an annual caseload 〉 100 EUS-FNA. Endoscopy practices were located in 29 countries, in- cluding 13 countries in Western Europe that totaled 75.3% of the responses. Only one third of endosonog raphers reported a sensitivity for the diagnosis of solid mass lesions 〉 80% （interquartile range of sensitivities, 25.0%-75.0%）. Factors independently associated with a sensitivity 〉 80% were （1） 〉 7 needle passes for pancreatic lesions or rapid on-site cytopathological evaluation （ROSE） （P 〈 0.0001）, （2） a high annual hospital caseload （P = 0.024） and （3） routine isolation of microcores from EUS-FNA samples （P = 0.042）. ROSE was routinely available to 27.9% of respondents. For lymph nodes and pancreatic masses, a maximum of three needle passes was performed by approximately two thirds of those who did not have ROSE. Microcores were routinely harvested from EUS-FNA samples by approximately one third （37.2%） of survey respondents.CONCLUSION： EUS-FNA sensitivity was considerably lower than reported in the literature. Low EUS-FNA sensitivity was associated with unavailability of ROSE, few needle passes, absence of microcore isolation and low hospital caseload.

Effects of Acute Normovolemic Hemodilution on Perioperative Coagulation and Fibrinolysis in Elderly Patients Undergoing Hepatic Carcinectomy

Objective To observe the effects of acute normovolemic hemodilution （ANH） on coagulation function and fibrinolysis in elderly patients undergoing hepatic carcinectomy. Methods Thirty elderly patients （aged 60-70 years） with liver cancer （American Society of Anesthesiologists physical status I-II） scheduled for hepatic carcinectomy from February 2007 to February 2008 were randomly divided into ANH group （n= 15） and control group （n= 15）. After tracheal intubation, patients in ANH group and control group were infused with 6% hydroxyethyl starch （HES） （130/0.4）, and basic liquid containing 6% HES and routine Ringer＇s solution, respectively. In all the studied patients, blood samples were drawn at five different time points： before anesthesia induction （T1）, 30 minutes after ANH （T2）, 1 hour after start of operation （T3）, immediately after operation （T4）, and 24 hours after operation （Ts）. Then co- agulation function, soluble fibrin monomer complex （SFMC）, prothrombin fragment （F1＋2）, and platelet membrane glycoprotein （activated GPIIb/GPIIIa and P-selectin） were measured. Results The perioperative blood loss was not significantly different between the two groups （P〉 0.05）. The volume of allogeneic blood transfusion in ANH group was significantly smaller than that in control group （350.5±70.7 mL vs. 457.8±181.3 mL, P〈0.01）. Compared with the data ofT1, prothrombin time （PT） and activated partial thromboplastin time in both groups prolonged significantly after T3 （P〈0.05）, but still within normal range. There were no significant changes in thrombin time and D-dimer between the two groups and between different time points in each group （all P〉0.05）. SFMC and F1 ＋2 increased in both groups, but without statistical significance. P-selectin expression on the platelet surface of ANH group was significantly lowered atT2 andT3 compared with the level atT1 （P〈 0.05）. Compared with control group, P-selectin was sig-nificantly lower in ANH group atT2-T3 （all P〈0.05）. Conclusions In elderly patients undergoing resection of liver cancer, ANH may not hamper fibri- nolvsis and coagulation function. It coukt therefore be safe to largely reduce allogeneic blood transfusion.

Improved pedestrian detection with peer AdaBoost cascade

Focusing on data imbalance and intraclass variation,an improved pedestrian detection with a cascade of complex peer AdaBoost classifiers is proposed.The series of the AdaBoost classifiers are learned greedily,along with negative example mining.The complexity of classifiers in the cascade is not limited,so more negative examples are used for training.Furthermore,the cascade becomes an ensemble of strong peer classifiers,which treats intraclass variation.To locally train the AdaBoost classifiers with a high detection rate,a refining strategy is used to discard the hardest negative training examples rather than decreasing their thresholds.Using the aggregate channel feature(ACF),the method achieves miss rates of 35%and 14%on the Caltech pedestrian benchmark and Inria pedestrian dataset,respectively,which are lower than that of increasingly complex AdaBoost classifiers,i.e.,44%and 17%,respectively.Using deep features extracted by the region proposal network(RPN),the method achieves a miss rate of 10.06%on the Caltech pedestrian benchmark,which is also lower than 10.53%from the increasingly complex cascade.This study shows that the proposed method can use more negative examples to train the pedestrian detector.It outperforms the existing cascade of increasingly complex classifiers.

Prospective controlled study on the effects of polyethylene glycol in capsule endoscopy

AIM:To prospectively confirm whether a small amount of polyethylene glycol(PEG)ingested after swallowing endoscopy capsule improves image quality and completion rate.METHODS:Forty-four consecutive patients referred to us for capsule endoscopy(CE)were randomized to two groups.All patients were restricted to clear fluids for 12 h before the examination.Patients in group A(22 cases)received no additional preparation,while those in group B(20 cases)ingested 500 mL of PEG within a 2 h period starting 30 min after swallowing the capsule.Clear fluids and meals were allowed 2 h and 4 h after capsule ingestion,respectively.Image quality was assessed as the percentage of visualized bowel surface area as follows:1:<25%;2:25%-49%;3:50%-74%;4:75%-89%;5:>90%.The small bowel record was divided into five segments by time,and the score for each segment was evaluated.All CE examinations were performed with the Pillcam SB capsule endoscopy sys-tem(Given Imaging Co.Ltd.,Yoqnem).RESULTS:This study ended in December 2009,because sample size was considered large enough.A total of 44 patients were enrolled.Two patients in group B were excluded from the analysis because small bowel images could not be obtained from these patients;one had a full stomach,while the other presented with a massive gastric bleed.Thus,22 patients from group A and 20 patients from group B completed the study.There was no significant difference in age(P=0.22),sex(P=0.31),and indication for CE.No significant adverse events occurred in any of the study patients.In group A,image quality deteriorated as the capsule progressed distally.However,in group B,image quality was maintained to the distal small bowel.In each of the five segments,the visibility score was significantly higher in group B than in group A(segment 1:4.3± 0.7vs 4.7±0.5,P=0.03;segment 2:4.2±0.9vs 4.8 ±0.4,P=0.01;segment 3:4.0±1.0 vs 4.6±0.7,P =0.04;segment 4:3.6±1.1 vs 4.5±0.6,P=0.003;segment 5:2.7±1.0vs 4.4±0.8,P=0.00004).Thus,the use of PEG during CE examination significantly improved image quality in all time segments,and this effect was more pronounced in the distal ileum.The completion rate to the cecum was not significantly different between groups A and B(81.8%vs 85.0%,P =0.89).There was no difference in the gastric transit time between groups(36.2±35.0 min vs 54.0±56.6 min,P=0.23),but the small bowel transit time was significantly longer in group A than in group B(246.0± 107.0 minvs 171.0±104.0 min,P=0.04).CONCLUSION:The ingestion of a small amount of PEG after the swallowing of an endoscopy capsule significantly improved CE image quality,but did not enhance the completion rate to the cecum.

Lower Bifidobacteria counts in both duodenal mucosa-associated and fecal microbiota in irritable bowel syndrome patients

AIM: To determine the composition of both fecal and duodenal mucosa-associated microbiota in irritable bowel syndrome (IBS) patients and healthy subjects using molecular-based techniques. METHODS: Fecal and duodenal mucosa brush samples were obtained from 41 IBS patients and 26 healthy subjects. Fecal samples were analyzed for the composition of the total microbiota using fluorescent in situ hybridization (FISH) and both fecal and duodenal brush samples were analyzed for the composition of bif idobacteria using real-time polymerase chain reaction. RESULTS: The FISH analysis of fecal samples revealed a 2-fold decrease in the level of bifidobacteria (4.2 ± 1.3 vs 8.3 ± 1.9, P < 0.01) in IBS patients compared to healthy subjects, whereas no major differences in other bacterial groups were observed. At the species level, Bifidobacterium catenulatum levels were significantly lower (6 ± 0.6 vs 19 ± 2.5, P < 0.001) in the IBS patients in both fecal and duodenal brush samples than in healthy subjects.CONCLUSION: Decreased bifidobacteria levels in both fecal and duodenal brush samples of IBS patients compared to healthy subjects indicate a role for microbiotic composition in IBS pathophysiology.

Advances in circulating microRNAs as diagnostic and prognostic markers for ovarian cancer

Ovarian cancer is one of the most lethal malignant gynecological tumors. More than 70% of patients with ovarian cancer are diagnosed at advanced stage. The 5-year survival in patients with advanced ovarian cancer is less than 30% because of the lack of effective biomarkers for diagnosis, prognosis, and personalized treatment. MicroRNA （miR） is a class of small noncoding RNAs that negatively regulate gene expression primarily through post-transcriptional repression. Many studies on tissue miR in ovarian cancer have been carried out and show great potential in clinical practice. However, tissue samples are not easily available because sampling causes injur）n Researchers have started to focus on plasma/serum miR, assuming that blood samples may replace tissue samples in miR research in the future. Plasma/serum miR research is still in its early stages. Studies on its function in the early diagnosis of ovarian cancer have achieved some progress, but plasma/serum miR profiling for prognosis and personalized treatment of ovarian cancer remains unknown. A thorough understanding of the function of plasma/serum miR in ovarian cancer will facilitate early diagnosis and improve treatment for ovarian cancer.

Comparison of three PCR methods for detection of Helicobacter pylori DNA and detection of cagA gene in gastric biopsy specimens

AIM:To comparatively evaluate PCR and other diagnostic methods (the rapid urease test and/or culture) in order to determine which of the three PCR methods (ureA,glmM and 26-kDa,SSA gene) was most appropriate in the diagnosis of Helicobacterpylori(Hpylori) infection and also to evaluate the detection of a putative virulence marker of H pylori,the cage,gene,by PCR in biopsy specimens. METHODS:One hundred and eighty-nine biopsy specimens were collected from 63 patients (three biopsies each) undergoing upper gastroduodenal endoscopy for various dyspeptic symptoms.The PCR methods used to detect H pylori DNA directly from biopsies were the glmM,26-kDa, ureA and then cagA was used to compare the culture technique and CLO for urease with the culture technique being used as the gold standard. RESULTS:Thirty-five percent of the biopsies were positive for H pylori DNA using the 3 PCR methods,while 68% of these were positive for the cagA gene.Twenty-four percent of the biopsies were negative for H pylori DNA in all PCR methods screened.The remaining 41% were either positive for ureA gene only,glmM only,26-kDa only,or ureA+glmM, ureA+26-kDa,glmM+26-kDa.Out of the 35% positive biopsies,41% and 82% were positive by culture and CLO respectively,while all negative biopsies were also negative by culture and cagA.Cag A+ infection was also predominantly found in H pylori DNA of the biopsies irrespective of the clinical diagnosis. CONCLUSION:This method is useful for correctly identifying infections caused by H pylori and can be easily applied in our laboratory for diagnostic purposes.