Effectiveness of inhibitors in increasing chloride threshold value for steel corrosion

This investigation was aimed at evaluating the effectiveness of corrosion inhibitors in increasing the chloride threshold value for steel corrosion. Three types of corrosion inhibitors, calcium nitrite （Ca（NO2）2）, zinc oxide （ZnO）, and N,N＇-dimethylaminoethanol （DMEA）, which respectively represented the anodic inhibitor, cathodic inhibitor, and mixed inhibitor, were chosen. The experiment was carried out in a saturated calcium hydroxide （Ca（OH）2） solution to simulate the electrolytic environment of concrete. The inhibitors were initially mixed at different levels, and then chloride ions were gradually added into the solution in several steps. The open-circuit potential （Ecorr） and corrosion current density （lcorr） determined by electrochemical impedance spectra （EIS） were used to identify the initiation of active corrosion, thereby determining the chloride threshold value. It was found that although all the inhibitors were effective in decreasing the corrosion rate of steel reinforcement, they had a marginal effect on increasing the chloride threshold value.

Predicting the Threshold Values based on Diffusion Model of Nitrite Ions in Reinforced Concrete

The prediction model for inhibition effect of reinforced concrete was presented based on the Magge＇s model when the concrete surface was brushed with nitrite solution. The influence of the amount of nitrite solution on inhibiting duration was also discussed through a simulation analysis when the amount of solution were 250 g/m^2, 500 g/m^2, 1000 g/m^2 and 1500 g/m^2, respectively. The experimental results confirm that nitrite ion can diffuse well in concrete to reach an effective mol ratio from the surface of the concrete to the surface of the reinforcement, and has an effective protection for the bars against corrosion. The higher the amount of solution, the better it will accelerate getting the threshold value of mol ratio on the surface of rebar, and retarding the time for loosing the effective threshold value of mol ratio. It helps to increase the tendency of inhibiting duration and prolong the life of reinforced concrete. The nitrite solution amount is used to predict the corrosion inhibiting duration of concrete that contains chloride salt.

On Accelerated Singular Value Thresholding Algorithm for Matrix Completion

An accelerated singular value thresholding (SVT) algorithm was introduced for matrix completion in a recent paper [1], which applies an adaptive line search scheme and improves the convergence rate from O(1/N) for SVT to O(1/N2), where N is the number of iterations. In this paper, we show that it is the same as the Nemirovski’s approach, and then modify it to obtain an accelerate Nemirovski’s technique and prove the convergence. Our preliminary computational results are very favorable.

THRESHOLD VALUE FOR DIAGNOSIS OF CHAOTIC NATURE OF THE DATA OBTAINED IN NONLINEAR DYNAMIC ANALYSIS

In this paper surrogate data method of phase-randomized is proposed to identify the random or chaotic nature of the data obtained in dynamic analysis: The calculating results validate the phase-randomized method to be useful as it can increase the extent of accuracy of the results. And the calculating results show that threshold values of the random timeseries and nonlinear chaotic timeseries have marked difference.

The Effect of a High-Frequency-Hearing-Threshold Weighted Value on the Diagnosis of Occupational-Noise-Induced Deafness

Objective: In order to provide a theoretical basis for the revision of the current diagnostic criteria for occupational noise-induced deafness (ONID), we evaluated the degree of ONID by analyzing different high-frequency-hearing- threshold-weighted values (HFTWVs). Methods: A retrospective study was conducted to evaluate the diagnosis of patients with ONID from January 2016 to January 2017 in Guangdong province, China. Based on 3 hearing tests (each interval between the tests was greater than 3 days), the minimum threshold value of each frequency was obtained using the 2007 edition’s diagnostic criteria for ONID. The speech frequency and the HFTWVs were analyzed based on age, noise exposure, and diagnostic classi-fication using SPSS21.0. Results: 168 patients in total were involved in this study, 154 males and 14 females, and the average age was 41.18 ± 6.07. The diagnosis rate was increased by the weighted value of the high frequencies and was more than the mean value of the pure speech frequency (MVPSF). The diagnosis rate for the weighted 4 kHz frequency level increased by 13.69% (χ2 = 9.880, P = 0.002), the weighted 6 kHz level increased by 15.47% (χ2 = 9.985, P = 0.002), and the weighted 4 kHz + 6 kHz level increased by 15.47% (χ2 = 9.985, P = 0.002). The differences were all statistically significant. The diagnostic rate of the different thresholds showed no obvious difference between the genders. The age groups were divided into less than or equal to 40 years old (group A) and 40 - 50 years old (group B). There were several groups with a high frequency: high frequency weighted 4 kHz ( group A χ2 = 3.380, P = 0.050;group B χ2 = 4.054, P = 0.032), high frequency weighted 6 kHz (group A χ2 = 6.362, P = 0.012;group B χ2 = 4.054, P = 0.032), weighted 4 kHz + 6 kHz (group A χ2 = 6.362 P = 0.012;B χ2 = 4.054, P = 0.032) than those of MVPSF in the same group on ONID diagnosis rate. The differences between the groups were statistically significant. There was no significant difference between the age groups (χ2 = 2.265, P = 0.944). The better ear’s (the smaller hearing threshold weighted value) MVPSF and the weighted values for the different high frequencies were examined in light of the number of working years;the group that was exposed to noise for more than 10 years had significantly higher values than those of the average thresholds of each frequency band in the groups with 3 - 5 years of exposure (F = 2.271, P = 0.001) and 6 - 10 years of exposure (F = 1.563, P = 0.046). The differences were statistically significant. The different HFTWVs were higher than those of the MVPSF values, and the high frequency weighted 4 kHz + 6 kHz level showed the greatest difference, with an average increase of 2.83 dB. The diagnostic rate that included the weighted high frequency values was higher for the mild, moderate, and severe cases than those patients who were only screened with the pure frequency tests. The results of the comparisons of the diagnosis rates for mild ONID were as follows: the weighted 3 kHz high frequency level (χ2 = 3.117, P = 0.077) had no significant difference, but the weighted 4 kHz level (χ2 = 10.835, P = 0.001), 6 kHz level (χ2 = 9.985, P = 0.002), 3 kHz + 4 kHz level (χ2 = 6.315, P = 0.012), 3 kHz + 6 kHz level (χ2 = 6.315, P = 0.012), 4 kHz + 6 kHz level (χ2 = 9.985, P = 0.002), and 3 kHz + 4 kHz + 6 kHz level (χ2 = 7.667, P = 0.002) were significantly higher than the diagnosis rate of the mean value of the PSF. There was no significant difference between the 2 groups for the moderate and severe grades (P > 0.05). Conclusion: Different HFTWVs increase the diagnostic rate of ONID. The weighted 4 kHz, 6 kHz, and 4 kHz + 6 kHz high frequency values greatly affected the diagnostic results, and the weighted 4 kHz + 6 kHz high frequency hearing threshold value has the maximum the effect on the ONID diagnosis results.

Application of S-transform threshold filtering in Anhui experiment airgun sounding data de-noising

As a relatively new method of processing non-stationary signal with high time-frequency resolution, S transform can be used to analyze the time-frequency characteristics of seismic signals. It has the following characteristics: its time-frequency resolution corresponding to the signal frequency, reversible inverse transform, basic wavelet that does not have to meet the permit conditions. We combined the threshold method, proposed the S-transform threshold filtering on the basis of S transform timefrequency filtering, and processed airgun seismic records from temporary stations in "Yangtze Program"(the Anhui experiment). Compared with the results of the bandpass filtering, the S transform threshold filtering can improve the signal to noise ratio(SNR) of seismic waves and provide effective help for first arrival pickup and accurate travel time. The first arrival wave seismic phase can be traced farther continuously, and the Pm seismic phase in the subsequent zone is also highlighted.

Super-resolution reconstruction of synthetic-aperture radar image using adaptive-threshold singular value decomposition technique

A super-resolution reconstruction approach of radar image using an adaptive-threshold singular value decomposition (SVD) technique was presented,and its performance was analyzed,compared and assessed detailedly.First,radar imaging model and super-resolution reconstruction mechanism were outlined.Then,the adaptive-threshold SVD super-resolution algorithm,and its two key aspects,namely the determination method of point spread function (PSF) matrix T and the selection scheme of singular value threshold,were presented.Finally,the super-resolution algorithm was demonstrated successfully using the measured synthetic-aperture radar (SAR) images,and a Monte Carlo assessment was carried out to evaluate the performance of the algorithm by using the input/output signal-to-noise ratio (SNR).Five versions of SVD algorithms,namely 1) using all singular values,2) using the top 80% singular values,3) using the top 50% singular values,4) using the top 20% singular values and 5) using singular values s such that s2≥max(s2)/rinSNR were tested.The experimental results indicate that when the singular value threshold is set as smax/(rinSNR)1/2,the super-resolution algorithm provides a good compromise between too much noise and too much bias and has good reconstruction results.

Reduction of ultrasonic echo noise based on improved wavelet threshold de-noising algorithm for friction welding

In the ultrasonic detection of defects in friction welded joints, it is difficult to exactly detect some weak bonding defects because of the noise pollution. This paper proposed an improved threshold function based on the multi-resolution analysis wavelet threshold de-noising method which was put forward by Donoho and Johnstone, and applied this method in the de-noising of the defective signals. This threshold function overcomes the discontinuous shortcoming of the hard-threshold function and the disadvantage of soft threshold function which causes an invariable deviation between the estimated wavelet coeffwients and the decomposed wavelet coefficients. The improved threshold function is of simple expression and convenient for calculation. The actual test results of defect noise signal show that this improved method can get less mean square error （ MSE ） and higher signal-to-noise ratio of reconstructed signals than those calculated from hard threshold and soft threshold methods. The improved threshold function has excellent de-noising effect.

DWT-SVD Based Image Steganography Using Threshold Value Encryption Method

Digital image steganography technique based on hiding the secret data behind of cover image in such a way that it is not detected by the human visual system.This paper presents an image scrambling method that is very useful for grayscale secret images.In this method,the secret image decomposes in three parts based on the pixel’s threshold value.The division of the color image into three parts is very easy based on the color channel but in the grayscale image,it is difficult to implement.The proposed image scrambling method is implemented in image steganography using discrete wavelet transform(DWT),singular value decomposition(SVD),and sorting function.There is no visual difference between the stego image and the cover image.The extracted secret image is also similar to the original secret image.The proposed algorithm outcome is compared with the existed image steganography techniques.The comparative results show the strength of the proposed technique.

Optimized quantum singular value thresholding algorithm based on a hybrid quantum computer

Quantum singular value thresholding(QSVT) algorithm,as a core module of many mathematical models,seeks the singular values of a sparse and low rank matrix exceeding a threshold and their associated singular vectors.The existing all-qubit QSVT algorithm demands lots of ancillary qubits,remaining a huge challenge for realization on nearterm intermediate-scale quantum computers.In this paper,we propose a hybrid QSVT(HQSVT) algorithm utilizing both discrete variables(DVs) and continuous variables(CVs).In our algorithm,raw data vectors are encoded into a qubit system and the following data processing is fulfilled by hybrid quantum operations.Our algorithm requires O [log(MN)] qubits with0(1) qumodes and totally performs 0(1) operations,which significantly reduces the space and runtime consumption.

Efficient Global Threshold Vector Outlyingness Ratio Filter for the Removal of Random Valued Impulse Noise

This research paper proposes a filter to remove Random Valued Impulse Noise (RVIN) based on Global Threshold Vector Outlyingness Ratio (GTVOR) that is applicable for real time image processing. This filter works with the algorithm that breaks the images into various decomposition levels using Discrete Wavelet Transform (DWT) and searches for the noisy pixels using the outlyingness of the pixel. This algorithm has the capability of differentiating high frequency pixels and the “noisy pixel” using the threshold as well as window adjustments. The damage and the loss of information are prevented by means of interior mining. This global threshold based algorithm uses different thresholds for different quadrants of DWT and thus helps in recovery of noisy image even if it is 90% affected. Experimental results exhibit that this method outperforms other existing methods for accurate noise detection and removal, at the same time chain of connectivity is not lost.

A More Effective Method of Extracting the Characteristic Value of Pulse Wave Signal Based on Wavelet Transform

Pulse wave contains human physiological and pathological information. Different people will exhibit different characteristics, and hence determining the characteristic points of the pulse wave of human physiological health makes sense. It is common that we extract the characteristic value of pulse wave signal with the method based on wavelet transform on a small scale, and then determine the locations of the characteristic points by modulus maxima and modulus minima. Before determining characteristic value by detecting modulus maxima and modulus minima, we need to determine every period of the pulse wave. This paper presents a new kind of adaptive threshold determination method which is more effective. It can accurately determine every period of the pulse wave, and then extract characteristic values by modulus maxima and modulus minima in every period of the pulse wave. The method presented in this paper promotes the research utilizing pulse wave on health life.

Implementation of GPR Signals De-Noising Based on DSP

An important issue of ground-penetrating radar （GPR） signals analysis is de-noising thai is the guarantee of acquiring good detecting effect. The paper illustrates a successful application of digital single processor （DSP） based on wavelet shrinkage algorithm. In order to realize real-time GPP, signals analysis, some key issues are discussed such as the realization of fast wavelet transformation, the selection of CPU chip and the optimization of data movement. Experimenial results show that the DSP based application not only basically meets the real-time requirement of GPP, signals analysis, but also assures the quality of the GPR signals analysis.

Alarm Correlation Rules Generation Algorithm Based on Confidence Covered Value

In communication alarm correlation analysis,traditional association rules generation(ARG) algorithm usually has low efficiency and high error rate.This paper proposes an alarm correlation rules generation algorithm based on the confidence covered value.Confidence covered value method can judge whether a rule is redundant or not scientific After the rules that based on weighted frequent patterns(WFPs) generated,the association rules were deleted by the confidence covered value,in order to delete the redundant rules and keep the rules with more information.Experiments show that the alarm correlation rules generation algorithm based on the confidence covered value has higher efficiency than the traditional method,and can effectively remove redundant rules.Thus it is very suitable for telecommunication alarm association rules processing.

Analysis of Network Traffic with Extreme Value Theory

It is very im portant to analyze network traffic in the network control and management. In thi s paper, extreme value theory is first introduced and a model with threshold met hods is proposed to analyze the characteristics of network traffic. In this mode l, only some traffic data that is greater than threshold value is considered. Th en the proposed model with the trace is simulated by using S Plus software. The modeling results show the network traffic model constructed from the extreme va lue theory fits well with that of empirical distribution. Finally, the extreme v alue model with the FARIMA(p,d,q) modeling is compared. The anal ytical results illustrate that extreme value theory has a good application foreg round in the statistic analysis of network traffic. In addition, since only some traffic data which is greater than the threshold is processed, the computation overhead is reduced greatly.

高桩码头结构安全监测预警模型及工程应用

高桩码头结构在服役期内会出现不同程度的损伤,导致码头结构安全性降低。为保证码头长期安全运行,可通过实时监测确定码头运行状态并及时预警。提出一种高桩码头结构安全监测预警模型,采用不同结构状态的设计控制值作为不同级别的预警阈值,每级预警阈值对应不同的风险程度,针对不同级别的预警提出相应处置措施。将该预警模型应用于南京港某高桩码头的安全监测,对可变荷载作用下码头结构位移和桩基应变进行实时监测,并计算设置码头结构位移和桩基应变三级安全预警阈值。结果表明,码头安全预警阈值的设置及安全告警的应对措施科学有效,实现了码头结构全工况整体技术状态评估和安全预警。

纺织企业国际化程度、研发投入与企业价值——基于门槛回归的经验证据

本研究以2018—2022年纺织类上市企业的面板数据为基础,采用非线性视角与资源有限性理论,运用门槛模型探讨了在不同国际化程度下,研发投入与企业价值之间的关系。研究结果显示:(1)当国际化程度作为门槛变量时,研发投入与企业价值之间呈现出倒U型关系,存在两个门槛值,最优区间为DI≤0.389;(2)研发投入滞后一期和滞后二期与企业价值的关系同样呈现倒U型,最优区间为DI≤0.383;(3)在135个样本企业中,有29.63%的企业国际化程度高于第一门槛值0.389,但未处于最优区间;(4)企业成长性和人力投入回报率与企业价值呈显著正相关,资产负债率与企业价值呈显著负相关。研究结果表明,我国纺织类企业的研发投入整体偏低,引导纺织企业加大研发投入仍是提升企业价值的重要路径。本文对我国纺织企业有效参与国际市场竞争、实现可持续发展具有重要的参考意义。

国内贸易网络与企业全球价值链地位——基于市场可达性的中介效应

现代经济生产与分工日渐网络化,促使国内贸易网络对企业全球价值链地位攀升的重要作用逐步凸显。文章基于2012—2022年我国上市公司和中国海关匹配数据,考察国内贸易网络对企业全球价值链地位的影响和作用机制。研究结果表明:国内贸易网络对企业全球价值链地位具有显著促进作用;中介机制检验结果显示,市场可达性在国内贸易网络影响企业全球价值链地位过程中发挥中介作用;门槛效应检验发现,在市场可达性较高地区,国内贸易网络对企业全球价值链地位的促进作用更强;异质性检验表明,国内贸易网络对企业全球价值链地位的正向影响在高生产率企业和中低质量产品企业中更显著。据此,文章提出跨区域拓展与延伸国内贸易网络、制定差异化扶持策略、借助于现有交通网络深化市场可达性等对策建议,以期更好助力企业实现全球价值链地位攀升。