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Copyright of Machine Tool & Hydraulics is the property of Guangzhou Mechanical Engineering Research Institute (GMERI) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Aiming at the characteristics of short pulse time and high instantaneous dose rate of pulsed X-ray, a TLD-based few-channel spectrometer is studied. In this paper, the basic structure and principle of the spectrometer are introduced, the absorption plates and detectors of the spectrometer are selected. The energy response matrix of the few-channel spectrometer for single energy photons of different energies is simulated by Monte Carlo method and its influence on the energy resolution of the spectrometer is analyzed. The maximum entropy method is used to verify the pulsed X-ray spectrum resolution. The results show that the TLD-based few-channel spectrometer can be used to measure short pulse and high dose rate pulse X-ray energy spectrum, and it is also suitable for other high dose rate radiation fields.

Copyright of Journal of Isotopes is the property of Journal of Isotopes Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Chinese Journal of Explosives & Propellants is the property of Chinese Journal of Explosives & Propellants Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Ensuring a reliable mine ventilation network is one of the primary strategies to achieve the required air volume at the operating point of a mine quarry. Taking a uranium mine ventilation network as the research object, this paper firstly analyzes the radon concentration distribution in the tunnel under different ventilation parameters and estimates the total ventilation volume required for the ventilation tunnel. Then, using the path entropy theory, air flow transmission path, network flow rate, and radon concentration variation are combined to derive the definition of wind path entropy characterizing the wind performance of uranium mine ventilation. Finally, combined with the maximum entropy theory, a network reliability model that considers the mesoscopic centrality of the network topology to weigh the wind path entropy is proposed, and the model is worked out and analyzed. The experimental results show that the increase of the path length from the human wind entrance makes the probability of transporting radon in each path uneven, the reliability of the end nodes of the network decreases, and the increase of the inlet and return air paths is beneficial to improve the network reliability. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Railway Science & Engineering is the property of Journal of Railway Science & Engineering Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Bearing is the property of Bearing Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Sardinops melanostictus and Scomber japonicus, as the main associated species in the northwest Pacific Ocean, are of great scientific significance for the management and sustainable use of fishery resources to study their potential habitat distribution and differences in response to environmental changes in this area. The fishery data of S. melanostictus and S. japonicus in the northwest Pacific Ocean from May to November in 2017-2021 were used, combined with sea surface temperature (SST), sea surface salinity (SSS), sea surface height (SSH ), chlorophyll-a (Chl. a), eddy kinetic energy (EKE ), and water temperature at different depths (50, 100, 150, 200 m) to construct a maximum entropy model. According to the response curves of the two to the key environmental factors of each month, the inter-month changes of the key factors on the potential habitats of S. melanostictus and S. japonicus were obtained, and the map of potential habitat distribution from May to November for S. melanostictus and S. japonicus was stimulated. The key factors affecting the change of suitable habitats from June and August to October were SSH, SST, and Chi. a, and their suitable ranges were not much different. The results show that the potential habitat changes of S. melanostictus and S. japonicus are consistent with the actual operating location, and with the increase of months, and they all show a trend of moving first to the northeast and turning back in the southwest direction, and their potential habitat positions overlap widely in each month. The key factors affecting the change of suitable habitat in May, July and November are different. The key factors affecting the change of suitable habitat in May, July and November are different, and the key factors of S. melanostictus are SSH, EKE, SST, the key factors in July are SSH, SST, Chl. a. The key factors in November are EKE, SST, Chl. a, while the key factors of S. japonicus are SSH, EKE, Chl. a in May, and the key factors in July are SST and Chl. a, SSS, while the key factors in November are SSH, SST, Chl. a, and the suitable range of environmental factors varies from month to month. In addition, as the number of months increases, the optimal habitat area of S. japonicus gradually decreases northward, with a minimum area in July and November, while the optimal habitat area of S. melanostictus tends to increase, extending to the area north of 37° north latitude in November. The study showed the changes of SSH, SST and Chi. a have an important impact on the distribution of potential habitats of S. japonicus and S. melanostictus in the northwest Pacific Ocean, and EKE and SSS are the main causes for the difference in the distribution of potential habitats. [ABSTRACT FROM AUTHOR]

Because the traditional image segmentation algorithm had the defects of poor noise resistance and low iteration speed, in order to improve the quality of image segmentation, a whale optimization algorithm (WOA) with reverse learning strategy and a two-dimensional maximum entropy image segmentation method were proposed, and the WOA algorithm was optimized by nonlinear adjustment combining Sobol sequence, adaptive weight coefficient and convergence factor. The optimal threshold of the target image was obtained and segmented. Compared with the original WOA algorithm in the test function, the improved algorithm has better convergence and faster convergence speed. When the improved algorithm is applied to the lawn background, the peak signal-to-noise ratio value of the segmented image is increased by 5. 2% and 3. 5% respectively compared with the other two contrast algorithms, and increased by 3. 6% and 2. 2% respectively under the sky background. The improved algorithm can improve the quality of the segmented image, reflecting the advantages of the algorithm. [ABSTRACT FROM AUTHOR]

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Railway Science & Engineering is the property of Journal of Railway Science & Engineering Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Harbin Institute of Technology. Social Sciences Edition / Haerbin Gongye Daxue Xuebao. Shehui Kexue Ban is the property of Harbin Institute of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Computer Engineering & Applications is the property of Beijing Journal of Computer Engineering & Applications Journal Co Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Based on the constructal theory, a heat dissipation optimization model for discrete square column heating devices on thermal conduction bases in 2D jet channels was established. With the total longitudinal section area and the discrete heat source height as constraints, the maximum temperature and entropy production rate of the system were taken as optimization objectives, and the length ratio of each heating device was taken as the optimization variables in the geometry design. The effects of the jet velocity and the heating device spacing on the constructal optimization of the heating device were analyzed. When the jet velocity and the heating device spacing are fixed, there will exist optimal length ratios to minimize the maximum temperature and the entropy production rate of the system, but the optimal length ratios corresponding to different jet velocities and different heating devices spacings are different. The results provide a theoretical guidance for the thermal design of square column heating devices. [ABSTRACT FROM AUTHOR]

Copyright of Chinese Journal of Computational Mechanics / Jisuan Lixue Xuebao is the property of Chinese Journal of Computational Mechanics Editorial Office, Dalian University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of China Sciencepaper is the property of China Sciencepaper and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Piezoelectrics & Acoustooptics is the property of Piezoelectric & Acoustooptic and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Harbin Institute of Technology. Social Sciences Edition / Haerbin Gongye Daxue Xuebao. Shehui Kexue Ban is the property of Harbin Institute of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Given the problem of three-sources uncertainty in aero engine degradation process and the assumption of normal distribution of measurement error m existing research, a Wiener process aero engine residual useful life time (RLJL) prediction method with logistic distribution of measurement error was proposed. Firstly, the performance degradation model was established when t he measurement error obeys the logistics distribution, and the accurate mathematical expression of the RLJL distribution was given under the first arrival time. Secondly,in order to improve the utilization of monitoring parameters, a key parameter screening method based on Spearman coefficient was given. Lastly, in view of the lack of historical data and prior information, a parameter estimation method based on maximum entropy unscented particle filtering and conditional expectation maximization algorithm was adopted. Meanwhile after new performance degradation data was obtained, the model parameters could be adaptively updated. With MSE as the evaluation index, the experimental results show that the MSE value of this method is 1:3.25, and the MSE value is 16.12 lower than that of traditional method, which can effectively imp rove the prediction accuracy and the engine utilization and safety. [ABSTRACT FROM AUTHOR]

Copyright of China Sciencepaper is the property of China Sciencepaper and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper developed a causality modeling algorithm based on maximum information transfer entropy to solve the problem that traditional causality algorithms were difficult to accurately analyze non-linear data with a lot of noise.Firstly,it used the maximum information coefficient to detect the correlation between time series trends of non-linear data,and weaken the effect of noise on the correlation between variables.Secondly,it eliminated weakly related variables based on screening factors,and calculated the transfer entropy between strong correlations using stochastic empirical valuation thereby reducing the calculation amount of transfer entropy.Finally,it transferred entropy determined causal direction,formed a one-way causal network that supported link traceability.It tested analysis of the algorithm using classic chemical process data sets.Test results show that,compared with existing algorithms,this algorithm can locate abnormal variables.The stability of this algorithm for modeling high-dimensional data of more than 12 dimensions is higher than 85%,and the accuracy rate of causality can reach83.33%.The actual modeling effect of this algorithm is better than the comparison algorithms,and it can detect and locate industrial control system abnormalities. [ABSTRACT FROM AUTHOR]

In this paper, the maximum entropy model (Maxent) and geographic information system ( ArcGIS 10.3) softwares were used to predict the potential distribution areas of four Litsea species under the current and future climate conditions of China ( 2061 - 2080), and to analyze and classify their suitable habitats. The results were as follows: Litsea cubeba was widely distributed in the south to the Yangtze Hiver in China, and under the future climate with two ( HCP2.6, HCP8.5) carhon dioxide concentrations, during 2061-2080 the suitable anca for its distribution was reduced by 4.9%and 0.5%, respectively; L. coreana was mainly distributed in central and northern subtropical regions of China, and under the climate scenarios with two carbon dioxide concentrations, in 2061-2080 the total suitable area would be increased by 5.6% and 4.5%, respectively; L. greennumiana was mainly distributed in the south subtropical regions of China; L. mollis was widely distributed in the subtropical region. Under the future climate HCP2. 6 scenarios, the suitable area of the two species would be shrinked by 1.0% and 3.3%, respectively, and under the climale HCP8.5, the suitable area of the two species would be shrinked by 5.6% and 8.3%, respectively. These results reveal that due lo different ecological requirements, Litsea species will have different distributional responses to the future climate. the introduction and cultivation of Litsea species should consider the influences of climale change. [ABSTRACT FROM AUTHOR]

Aiming at the problem of multi-attribute decision making， two-tuple semantic information in the form of vector is integrated and an information aggregation method of vector-type two-tuple semantic density weighted averaging (V-TDWA) operator is proposed. Firstly， the basic idea of the vector-type two-tuple semantic weighted operator and its synthetic operators are introduced， and then their properties are analyzed. Secondly， based on the density of information distribution， the clustering problem of the vector-type two-tuple semantic information is discussed， and a clustering method based on vector similarity is given. Based on the clustering group， the maximum entropy value method is used to solve the density weight of different clustering groups. Finally， an example is given to briefly explain the application of the vector-type two-tuple semantic density aggregation operator. [ABSTRACT FROM AUTHOR]

An ecological niche model of creative industry was developed on the basis of the geographic characteristics of creative industry parks and 23 factors associated with the environment of cities were selected. The maximum entropy model (MaxEnt) was applied to determine the contribution of each factor and identify 8 major contributing factors. The fuzzy membership was applied to study the effect of environmental factors on the creative industry. The model results were integrated with the weight of environmental factors to get the suitability of creative industry and to produce predictive maps of site suitability. Then， based on the GIS spatial analysis， the cities were categorized into four zones， including unsuitable， low-suitable， moderatly-suitable， and highly-suitable regions， whose suitability ranges from low to high. The results showed that highly-suitable regions are mostly located in the eastern coastal provinces and provincial cities in China and that the predicted results are similar to the actual ones， which confirms the high reliability of the model. [ABSTRACT FROM AUTHOR]

The effects of the state parameters of projectiles at muzzle on the dispersion of projectiles are analyzed. Based on the six-degree-of-freedom ballistic equations, the sparse grid numerical integration (SGNI) method is used to obtain the characteristic paramerers of projectiles dispersion considering the error factors of system parameters and the state parameters of projectile at muzzle. The probability distribution of projectiles dispersion is obtained by using the the maximum entropy method. The test examples show that the results obtained by the SGNI method are in good agreement with those obtained by Monte Carlo method, and verify its effectiveness. In addition, an engineering example of 155 mm gun-howitzer is ananlyzed, and the the relation between single state parameter error and multi-state parameter error and the projectiles dispersionis established, which can be provided as reference for the overall design cosidering the dispersion of projectiles. [ABSTRACT FROM AUTHOR]

Copyright of Chinese Journal of Computational Mechanics / Jisuan Lixue Xuebao is the property of Chinese Journal of Computational Mechanics Editorial Office, Dalian University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Nowadays, UAV (unmanned aerial vehicle) remote sensing has been widely used in various research fields, due to its incomparable advantages over traditional satellite remote sensing, such as lower cost, fast image access, and high spatial resolution, and so on. But most of the vegetation indices are constructed based on visible bands and near-infrared bands of satellite remote sensing images, and few of them are constructed only based on visible-light bands. Thus, it is necessary to construct a universal vegetation index that is suitable for the visible-light bands of UAV images. According to the analysis of the spectral characteristics of 6 kinds of typical features based on regions of interest in visible-light images from UAV images, this paper proposed a new vegetation index based on red, green and blue bands, named Excess green-red-blue difference index (EGRBDI). The formula of EGRBDI was that the sum value between the square of 2 times green band and the product of red and blue bands divided the difference value of them. The value range of EGRBDI was the interval [-1, 1]. To determine the accuracy and reliability of EGRBDI, 18 kinds of vegetation indices had been studied in this paper, such as CIVE GLI, ExG, and so on. The overlap between different object types was obtained by calculating the mean value and 1-fold standard deviation of vegetation indices. The results showed that EGRBDI, GLI, ExG, g, CIVE, RGBVI, and V-MSAVI had no overlap between vegetation and non-vegetation information, while other vegetation indices appeared the different degree of overlap. Moreover, EGRBDI effectively enlarged the identification range of vegetation information and reduced the identification range of non-vegetation information. When the grey histogram of vegetation index existed distinct bimodal peaks, the corresponding discrimination performance of ground features was relatively strong. Therefore, the quantized interval of gray histograms should be normalized to the interval [0, 255] for the comparative analysis between the indices. Results of the analysis concluded that EGRBDI, GLI, ExG, g, CIVE, RGBVI, and V-MSAVI had distinct bimodal-peak characteristics and scarcely appeared thorn peaks in the histogram, but the others had either no obvious bimodal peaks or obvious thorn peaks. To determine the thresholds of vegetation information identification, the bimodal histogram method and the maximum entropy method were used to determine the threshold of each vegetation index and got the optimal threshold of each vegetation index by the precision comparison method. The accuracy evaluation results revealed that GBRI and ExB obtained higher classification accuracy by the maximum entropy method than the bimodal histogram method. WI and VEG had the same accuracy between the two methods, and the other 15 indices did better on the bimodal histogram method. Therefore, the maximum entropy method was used to determine the thresholds of GBRI and ExB, while the other indices used the bimodal histogram method to determine their thresholds in this paper. Through the comparative analysis of the experimental results, it could be found that EGRBDI was generally better than the other 18 algorithms and had a great advantage in the case of the low vegetation coverage, which had a total accuracy of 97.67% and a Kappa coefficient of 0.9415. Another 3 UAV images had been used to extract vegetation information of top 5 higher precision indices to further verify the suitability in the area of various ground subjects and used 400 random points to evaluate the vegetation extraction accuracy. The accuracy of the vegetation and non-vegetation information was not less than 90%. The total accuracy in the 3 study areas was higher than 93%. Additionally, the Kappa coefficient was greater than 0.85. The results showed that EGRBDI had been less affected by ground subjects and shadows, and it had better applicability, reliability, and accuracy of vegetation extraction. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Drainage & Irrigation Machinery Engineering / Paiguan Jixie Gongcheng Xuebao is the property of Editorial Department of Drainage & Irrigation Machinery Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper used a piecewise complex multi-scale fuzzy entropy to increase the recognition rate. It proposed piecewise coarse graining and calculating complex multi-scale fuzzy entropy. It could solve the problem of missing data and calculating inaccurate entropy. This paper constructed an IGWO-SVM classification model which used cosine nonlinear convergence factor and dynamic and static position. To prove the validity of the algorithms, the paper performed the simulation experiment. Comparing the EEG emotion recognition rate with several common SVM optimization models in the public DEAP database, the results show that the average recognition rates of valance, arousal, dominance and liking are 87. 27%, 87. 81 %, 89. 06% and 87. 58% in proposed model, which is higher than other algorithms. Comparing the classification of valance and arousal under high/ low liking, experiments show that the recognition rate is higher when the liking is lower. [ABSTRACT FROM AUTHOR]

Copyright of Chinese Journal of Computational Mechanics / Jisuan Lixue Xuebao is the property of Chinese Journal of Computational Mechanics Editorial Office, Dalian University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Harbin University of Science & Technology is the property of Journal of Harbin University of Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Soochow Journal of Political Science is the property of Soochow Journal of Political Science and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of China Mechanical Engineering is the property of Editorial Board of China Mechanical Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The plant leaf image is taken as the research target, and the improved particle swarm optimization algorithm is used to optimize the optimal threshold vector of maximum entropy threshold segmentation. Although the traditional maximum entropy segmentation method has many advantages, it also has problems such as slow algorithm operation and insufficient precision. The Improved Particle Swarm Optimization(IPSO) proposed in this paper improves the problem that the traditional particle swarm optimization algorithm is easy to fall into local optimum, and has the characteristics of fast convergence and high precision. Aiming at the problem of blade overlap in plant leaf image segmentation, the RGB image is converted into HSV(Hue, Saturation, Value) image and the V vector is extracted, the fitness function of the maximum entropy thresholding method is optimized by IPSO algorithm. The experiment compares the maximum entropy value with the running time of the algorithm. The results show that the segmentation accuracy and convergence efficiency of the proposed method are greatly improved. It shows that the proposed method is superior to the traditional maximum entropy method. Therefore, the method can segment the plant leaf image more efficiently and has strong practicability in engineering. [ABSTRACT FROM AUTHOR]

Word segmentation is a basic work of natural language processing, which has a great influence on the subsequent work of it. The recognition of abbreviated case-auxiliary words is one of the most difficult and important technologies of Tibetan word segmentation. Through dissecting the existing recognition methods of abbreviated case-auxiliary words, this paper analyzed the characteristics of Tibetan words, pointedly proposed recognition algorithm of Tibetan abbreviated case-auxiliary words rules, add-restore algorithm and the maximum entropy models feature template, then the methods of recognizing abbreviated case-auxiliary words based on the rules, it obtained add-restore methods and the maximum entropy model. The experimental data shows that the accuracy, recall rate and F1 value of the method is 99.26% , 96.47% , and 97.85% respectively, which shows an obvious progress than that of the existing methods. [ABSTRACT FROM AUTHOR]

Handeliodendron bodinieri was a rare and endangered endemic single species genus plant only in karst areas of southwestern China, and it was also an excellent species of rocky desertification control, furthermore, its seed oil had higher value in nutrition, health care and industry. However, due to the lack of recognition of the related traits of H. bodinieri germplasm resources, the planting and popularization of H. bodinieri was restricted to some extent. Therefore, it was necessary to scientifically evaluate seed and seed oil traits of H. bodinieri from different provenances in order to guide the selection of good provenance and breeding. To improve the accuracy of evaluation results and optimum selection evaluation method, a new comprehensive evaluation model was constructed in this study. Fourteen indices related to seed and seed oil of H. bodinieri including seed length, seed diameter, single seed weight, 1 000- grain weight of seed, seed kernel rate, seed oil content, unsaturated fatty acid compositions of seed oil and so on were selected and determined. Five provenances of Leye of Guangxi, Tianlin of Guangxi, Fengshan of Guangxi, Huanjiang of Guangxi and Dushan of Guizhou were evaluated and sorted by four single evaluation methods of principal component analysis, factor analysis, maximizing deviation method, entropy weight method. The evaluation results of four single methods above were evaluated and sorted by three combination evaluation methods of mean, Borda and Copeland. Final evaluation rank was determined after all these methods had passed the Kendall's coefficient of concordance test. Spearman rank correlation coefficient was used to analyze the correlation between the final evaluation rank and four single methods evaluation ranking, and the best single evaluation method was selected at last. The results are showed following: Although there are some differences in the ranking of provenance evaluation in four single evaluation methods, they have passed the Kendall's coefficient of concordance test; all the three combination methods evaluation rank values are the same. Final evaluation ranking of provenance from high to low is Fengshan of Guangxi, Leye of Guangxi, Dushan of Guizhou, Huanjiang of Guangxi and Tianlin of Guangxi. Spearman rank correlation coefficient between final evaluation ranking and evaluation ranking of principal component analysis, factor analysis, maximum deviation method and entropy weight method are 1.00, 0.90, 1.00 and 0.90 respectively, and all correlations have reached a significant level (P < 0.05); the weight value of 1 000 - grain weight of seed obtained by principal component analysis and entropy weight method is listed in the first place of all indices. Therefore, the comprehensive evaluation model based on four single evaluation methods and three combination evaluation methods can provide scientific and reasonable ranking results for the seed and seed oil traits of H. bodinieri in multiple provenances. From the perspective of ease, convenience and effectiveness, the entropy method is the optimal single evaluation method for seed and seed oil traits of H. bodinieri, the most important index in the evaluation is 1 000 - grain weight of seed, and seed and oil traits of H. bodinieri in Fengshan of Guangxi provenance are the best. The research results provide a theoretical basis for efficient utilization of germplasm resources of H. bodinieri, and it also provides a new idea for the comprehensive evaluation of seed and oil field. [ABSTRACT FROM AUTHOR]

While the intelligent systems need parameter modeling, users often face the dilemma of scarce modeling samples.This paper proposed a BN parameter learning method-constrained data maximum entropy(CDME) algorithm for the modeling of BN parameters under the small data sets. In the case of estimating BN parameters by using small data sets, it transformed the qualitative expert knowledge into inequality constraints for the sake of generating candidate parameter sets by Bootstrap algorithm. Then it estimated the BN parameters in the light of the maximum entropy principle. The experimental results show that CDME algorithm learning effects are similar to the classical MLE algorithm when the modeling data size is sufficient. However, when the data size is limited, the parameters of BN can be modeled by using the CDME, and the learnt accuracy is superior to MLE or QMAP algorithm. It also applied CDME to a real fault diagnosis while the data set was relatively scarce. The results of the diagnosis reasoning demonstrate that the presented parameter learning approach is effective. The CDME parameter learning algorithm provides a new modeling way for BN parameter under the small data sets. [ABSTRACT FROM AUTHOR]

Importance measure for input random variables is a necessary component of safety evaluation and optimization design in engineering. In this paper, a new importance measure for multivariate output is introduced by combining notions of the moment-independent importance measure and the variance-based importance measure synthetically. The new measure is based on the multivariate probability integration transformation (PIT), in which the uncertainty of the multivariate output is represented in the form of its joint cumulative distribution function (CDF). Compared with variance-based measures, the new measure can take into account both of the uncertainty and the correlation information in the multivariate output. Compared with moment-independent measures, the solution procedure of new measure is more simple because the variability of the joint CDF is measured by variances.In this paper, maxi mum entropy method based on fractional moments and Nataf transformation are proposed to reduce model calls when the joint CDF is calculated. The calculation cost is saved without decreasing its accuracy. A numerical example and an engineering example are given to show the reasonableness of the proposed measure and the efficiency of the algorithm. [ABSTRACT FROM AUTHOR]

Fishing data are the basement of fisheries science research, but currently the source of fishing data is extraordinarily scarce, and data quality is poor in some aspects. Satellite low light sensors can detect the light-fishing vessels at night, however, its application in pelagic fishery has been limited by the lack of an algorithm for extracting the location and brightness of operating pelagic light-fishing vessels. An examination of operating pelagic light-fishing vessels features in the day/night band (DNB) image, which was from the visible infrared imaging radiometer suite (VIIRS) on the Suomi National Polar-orbiting Partnership (NPP) satellite, indicated that the features were a list of nonadjacent bright spots. In order to identify the operating pelagic light-fishing vessels from VIIRS/DNB accurately, we designed a set of identification algorithm for operating pelagic light-fishing vessels according to the light radiation characteristics of its fishing gathering lamps in NPP/VIIRS low light image. Before applying the identification algorithm, a data pre-processing step was adopted through radiation stretch and noise reduction by adaptive Wiener filter to prepare the data for further analysis and use. A spike median index (SMI) was used to enlarge the radiation difference between operating pelagic light-fishing vessel pixels and background pixels. On the basis of this, an adaptive threshold segmentation method called the maximum entropy (MaxEnt) method was used to extract the bright spot pixels, and generated a list of candidate operating pelagic light-fishing vessels detections. The candidate pixels were then filtered to remove the false identification bright spot pixels distributed near the operating pelagic light-fishing vessel pixels, and illuminated by the high-power fishing gathering lamps by a local spike detection (LSD) algorithm. A validation study was conducted at a night with weak lunar illuminance on May 24, 2015 which was selected randomly, using the vessel monitoring system (VMS) data of Chinese operating light-seiners vessels on the high seas of Northwest Pacific Ocean light seine fishing ground and the result of VIIRS/DNB image visual interpretation. The validation result showed that the identification algorithm detected 27 operating pelagic light-fishing vessels on the high seas of Northwest Pacific Ocean light seine fishing ground, and the number of operating pelagic light-fishing boats and their distribution were entirely consistent with the result of VIIRS/DNB image visual interpretation; the VMS data had the record of 25 operating pelagic light-fishing vessels among the total 27 vessels, and their distribution was nearly the same with the result of identification algorithm and VIIRS/DNB image visual interpretation. The identification algorithm worked well when lunar illuminance was weak and its identification accuracy was above 92%. The identification algorithm not only avoided the subjectivity and uncertainty of certain threshold segmentation, but also removed the false identification bright spot pixels near the operating pelagic light-fishing vessel pixels, which were illuminated by the high-power fishing gathering lamps. Detection of operating pelagic light-fishing vessels based on VIIRS/DNB imaging data can provide up-to-date activity and change information of operating pelagic light-fishing vessels for pelagic light-fishing industry, which meets the need of fishing boat's daily monitoring, and has a wide application prospect in fishing effort estimation, research of central fishing ground spatial-temporal distribution and change, and fishery forecast and management. [ABSTRACT FROM AUTHOR]

This paper explores the problem of insurer's decision on optimal deductible contract design, from the insurer's perspective of maximization the expected welfare in an uncertain environment. By describing the subjective judgment of the insurer about the insured's private information as fuzzy variables, and devising the contract as a vector with two dimensions: premium variable and deductible amount variable, a new fuzzy deductible contract model is built, the equivalent model and a sufficient condition are presented. A necessary condition of the optimal contract strategies is obtained on the basis of optimal control theory. A numerical example is presented, which illustrates the effectiveness of the proposed model. [ABSTRACT FROM AUTHOR]

The hesitant fuzzy projection method is studied. The vectors of alternative, positive and negative ideal point are defined. A projection measure method is proposed, in which the attribute values are in the form of hesitant fuzzy set. A new relative closeness degree formula based on positive and negative ideal point is presented. By Jaynes' maximum entropy principle and alternatives' fair competition, a mathematical model is constructed to obtain the attribute weights. In the last, a numerical example is given to verify the effectivity and feasibility of the proposed method. [ABSTRACT FROM AUTHOR]

The problem of seeking weights of decision-makers and attributes is studied in multi-attribute group decision making with interval grey numbers. For avoiding conflict between subjective weights and objective ones computed from attributes' values given by decision makers, the comprehensive weights are calculated by combining subjective weights and objective ones, where objective weights of attributes are obtained by using the maximum entropy model under the constrains of grey relation degree between the optimal project and every one. While, based on the degree of group consensus and information distribution, the weights of decision-makers are obtained by the maximum entropy thought and grey relation degree between every decision maker's comprehensive evaluations and average group evaluations. Finally, an aggregation approach of group decision making with interval grey numbers is presented. The numerical example is proved to verify the proposed method is more reasonable than other methods. [ABSTRACT FROM AUTHOR]

Research on objective index weight configuration in the field of multiple attribute decision making is conducted in this paper. Evaluating objects are divided into different grey categories according to essential natural characteristics by grey correlation clustering method. Maximum entropy configuration model of objective index weight is built based on the similarity of natural characteristics difference in the same grey category and the diversity of natural characteristics difference of the different grey categories. In case study, comparative analysis with other methods is conducted. The results demonstrate that the model in this paper is feasible and effective. So, a new solution to objective index weight configuration in the field of multiple attribute decision making is put forward. [ABSTRACT FROM AUTHOR]

In view of that the rational exchange protocol was a dynamic game model, under complete imperfect information dynamic game, this paper introduced the maximum entropy principle to solve the problem of strategy behavior inference of rational party. Based on information entropy, this paper extended a rational exchange protocols model in which a new fairness description was given combined with a desired payoff function and an expected equilibrium. In addition, it constructed a new rational exchange protocol based on the maximum entropy principle, which was proved secure and fair. Meanwhile, made analysis of the exchange process by game tree. Results show that the proposed protocol can achieve expected equilibrium. Without the participation of the trusted third party, the protocol can achieve rational fairness and be beautifully adapted to the real environment. [ABSTRACT FROM AUTHOR]

To group battle object rapidly and exactly, consider battle situation as a dynamic open system in terms of information exchange and with the dissipative structure theory, in which "ordered" status could appear. On these grounds, established the OG-Brusselator mode for battle object grouping and improved the algorithm MEC, then proposed the concept of fairway lengthways-cut based on the fairway crosscut to unify dimensions of two elements: the distance between objects and their direction of movement, and set them together with the memberships of object to grouping center as the measurable positive and negative entropy indicators respectively that affecting the clarity of relationship between object and group, then proposed object grouping algorithm DS-MEOC using OG-Brusselator to control the iteration. The experiment and analysis of air targets grouping proved that DS-MEOC is effective, feasible and could provide more reasonable object grouping program as compared with MEC. [ABSTRACT FROM AUTHOR]

A new dynamic prediction model of load of urban traffic sites during snow disaster is presented. The model overcomes the shortcomings of traditional Markov Chain method. Considering the dynamic changes of passengers' preferences and the interaction of traffic sites, the author establishes the maximum entropy model of distribution of passengers during snow disaster, and on this basis a method of calculating the load rate of traffic sites is presented, with which the dynamic changes of the load of traffic sites can be deduced. This provides a reference for the relevant departments to make response measures. Finally, a ease is used to compare the method with the Markov chain method, and the result shows that the method the author presented is better. [ABSTRACT FROM AUTHOR]

Two-dimensional percolation lattices are used to describe urban wireless propagation environment, and random walks are employed to model radio wave propagation. The probability that a generic ray undergoes certain number of collisions at specific spatial location is derived from the Bernoulli equiprobable experiments and the maximum entropy principle. After a probabilistic model of electromagnetic wave propagation is constructed,the analytic closed form of mean received power of electromagnetic rays undergoing random walks at each location is obtained in 2-dimensional channels,which obeys an exponential function of distance. Numerical analysis is used to discuss the precision of the analytic form, which is very satisfied in very wide ranges of parameters. The dependence of received power on geometrical parameters of lattices is also investigated. The results are validated by comparison with experimental data, and the theoretic results correspond well with the experimental data. [ABSTRACT FROM AUTHOR]