Accuracy improvement of quantitative analysis of calorific value of coal by combining support vector machine and partial least square methods in laser-induced breakdown spectroscopy

Laser-induced breakdown spectroscopy(LIBS) is a potential technology for online coal property analysis,but successful quantitative measurement of calorific value using LIBS suffers from relatively low accuracy caused by the matrix effect.To solve this problem,the support vector machine(SVM) and the partial least square(PLS) were combined to increase the measurement accuracy of calorific value in this study.The combination model utilized SVM to classify coal samples into two groups according to their volatile matter contents to reduce the matrix effect,and then applied PLS to establish calibration models for each sample group respectively.The proposed model was applied to the measurement of calorific values of 53 coal samples,showing that the proposed model could greatly increase accuracy of the measurement of calorific values.Compared with the traditional PLS method,the coefficient of determination(R2) was improved from 0.93 to 0.97,the root-mean-square error of prediction was reduced from 1.68 MJ kg-1 to1.08 MJ kg-1,and the average relative error was decreased from 6.7% to 3.93%,showing an overall improvement.

Improving Accuracy of Estimating Two-Qubit States with Hedged Maximum Likelihood

As a widely used reconstruction algorithm in quantum state tomography, maximum likelihood estimation tends to assign a rank-deficient matrix, which decreases estimation accuracy for certain quantum states. Fortunately, hedged maximum likelihood estimation （HMLE） [Phys. Rev. Lett. 105 （2010）200504] was proposed to avoid this problem. Here we study more details about this proposal in the two-qubit case and further improve its performance. We ameliorate the HMLE method by updating the hedging function based on the purity of the estimated state. Both performances of HMLE and ameliorated HMLE are demonstrated by numerical simulation and experimental implementation on the Werner states of polarization-entangled photons.

Distance-Coefficient-Based Imaging Accuracy Improving Method Based on the Lamb Wave

An imaging accuracy improving method is established, within which a distance coefficient including location information between sparse array configuration and the location of defect is proposed to select higher signal- to-noise ratio data from all experimental data and then to use these selected data for elliptical imaging. Tile relationships among imaging accuracy, distance coefficient and residual direct wave are investigated, and then the residual direct wave is introduced to make the engineering application more convenient. The effectiveness of the proposed method is evaluated experimentally by sparse transducer array of a rectangle, and the results reveal that selecting experimental data of smaller distance coefficient can effectively improve imaging accuracy. Moreover, the direct wave difference increases with the decrease of the distance coefficient, which implies that the imaging accuracy can be effectively improved by using the experimental data of the larger direct wave difference.

Calibration method to improve the accuracy of THz imaging and spectroscopy in reflection geometry

We introduce a novel method to accurately extract the optical parameters in terahertz reflection imaging. Our method builds on standard self-referencing methods using the reflected signal from the bottom of the imaging window material to further compensate for time-dependent system fluctuations and position-dependent variation in the window thickness. Our proposed method not only improves the accuracy, but also simplifies the imaging procedure and reduces measurement times.

Using single wavelength light to improve the synchronization accuracy of the White Rabbit system

We demonstrate a new synchronization method for the White Rabbit system. Signals are transmitted in a single mode fiber in both directions with the same light wavelength. Without the complex calibration process of the fiber asymmetry parameter, the new method reduces the effect of chromatic dispersion and improves the synchronization accuracy. The experiment achieves timing synchronization accuracy below 200 ps over 50 km fiber constructed by different companies＇ fiber spools. The proposed method would make White Rabbit technology immune to the chromatic dispersion of fiber links and can be applied to long distance synchronization.

A Way to Improve the Key Recovery Accuracy Based on Dynamic Programming

Key-recovery technology is often used by an adversary to attempt to recover the cryptographic key of an encryption scheme. The most obvious key-recovery attack is the exhaustive key-search attack. But modern ciphers often have a key space of size 2128 or greater, making such attacks infeasible with current technology. Cache-based side channel attack is another way to get the cryptographic key of an encryption scheme, but there are random noises in side channel attack. In order to reduce random errors, it is advisable to repeat the key recovery process many times. This paper is focused on the way to improve the key recovery accuracy by dealing with the key sequences obtained from the repeated Cache-based side channel attacks. To get the real key, private key bits from side channel attack are collected firstly. And then the key sequences are aligned using sequence alignment algorithms based on dynamic programming. The provided method of key recovery is universal, which is not limited to any cryptographic algorithm. The experiment shows that the proposed method has a good performance and a high availability when the error rate of the collected key bit is within a reasonable range.