AN APPROXIMATE REASONING METHOD IN DEZERT-SMARANDACHE THEORY

With the increment of focal elements number in discernment framework,the computation amount in Dezert-Smarandache Theory (DSmT) will exponentially go up. This has been the bottleneck problem to block the wide application and development of DSmT. Aiming at this difficulty,in this paper,a kind of fast approximate reasoning method in hierarchical DSmT is proposed. Presently,this method is only fit for the case that there are only singletons with assignment in hyper-power set. These singletons in hyper-power set are forced to group through bintree or tri-tree technologies. At the same time,the assignments of singletons in those different groups corresponding to each source are added up respectively,in order to realize the mapping from the refined hyper-power set to the coarsened one. And then,two sources with the coarsened hyper-power set are combined together according to classical DSm Combination rule (DSmC) and Proportional Conflict Redistribution rule No. 5 (PCR5). The fused results in coarsened framework will be saved as the connecting weights between father and children nodes. And then,all assignments of singletons in different groups will be normalized respectively. Tree depth is set,in order to decide the iterative times in hierarchical system. Finally,by comparing new method with old one from different views,the superiority of new one over old one is testified well.

Modeling and Characterization of Vegetation, Aquatic and Mineral Surfaces Using the Theory of Plausible and Paradoxical Reasoning from Satellite Images: Case of the Toumodi-Yamoussoukro-Tiébissou Zone in V Baoulé(Côte d’Ivoire)

In this paper, the theory of plausible and paradoxical reasoning of Dezert- Smarandache (DSmT) is used to take into account the paradoxical charac-ter through the intersections of vegetation, aquatic and mineral surfaces. In order to do this, we developed a classification model of pixels by aggregating information using the DSmT theory based on the PCR5 rule using the ∩NDVI, ∩MNDWI and ∩NDBaI spectral indices obtained from the ASTER satellite images. On the qualitative level, the model produced three simple classes for certain knowledge (E, V, M) and eight composite classes including two union classes characterizing partial ignorance ({E,V}, {M,V}) and six classes of intersection of which three classes of simple intersection (E∩V, M∩V, E∩M) and three classes of composite intersection (E∩{M,V}, M∩{E,V}, V∩{E,M}), which represent paradoxes. This model was validated with an average rate of 93.34% for the well-classified pixels and a compliance rate of the entities in the field of 96.37%. Thus, the model 1 retained provides 84.98% for the simple classes against 15.02% for the composite classes.

Risk assessment of water security in Haihe River Basin during drought periods based on D-S evidence theory

The weights of the drought risk index （DRI）, which linearly combines the reliability, resiliency, and vulnerability, are difficult to obtain due to complexities in water security during drought periods. Therefore, drought entropy was used to determine the weights of the three critical indices. Conventional simulation results regarding the risk load of water security during drought periods were often regarded as precise. However, neither the simulation process nor the DRI gives any consideration to uncertainties in drought events. Therefore, the Dempster-Shafer （D-S） evidence theory and the evidential reasoning algorithm were introduced, and the DRI values were calculated with consideration of uncertainties of the three indices. The drought entropy and evidential reasoning algorithm were used in a case study of the Haihe River Basin to assess water security risks during drought periods. The results of the new DRI values in two scenarios were compared and analyzed. It is shown that the values of the DRI in the D-S evidence algorithm increase slightly from the original results of Zhang et al. （2005）, and the results of risk assessment of water security during drought periods are reasonable according to the situation in the study area. This study can serve as a reference for further practical application and planning in the Haihe River Basin, and other relevant or similar studies.

Land Cover Classification with Multi-source Data Using Evidential Reasoning Approach

Land cover classification is the core of converting satellite imagery to available geographic data.However,spectral signatures do not always provide enough information in classification decisions.Thus,the application of multi-source data becomes necessary.This paper presents an evidential reasoning (ER) approach to incorporate Landsat TM imagery,altitude and slope data.Results show that multi-source data contribute to the classification accuracy achieved by the ER method,whereas play a negative role to that derived by maximum likelihood classifier (MLC).In comparison to the results derived based on TM imagery alone,the overall accuracy rate of the ER method increases by 7.66% and that of the MLC method decreases by 8.35% when all data sources (TM plus altitude and slope) are accessible.The ER method is regarded as a better approach for multi-source image classification.In addition,the method produces not only an accurate classification result,but also the uncertainty which presents the inherent difficulty in classification decisions.The uncertainty associated to the ER classification image is evaluated and proved to be useful for improved classification accuracy.

Powell dynamic identification of displacement parameters of indeterminate thin-walled curve box based on FCSE theory

The FCSE controlling equation of pinned thinwalled curve box was derived and the indeterminate problem of continuous thin-walled curve box with diaphragm was solved based on flexibility theory. With Bayesian statistical theory,dynamic Bayesian error function of displacement parameters of indeterminate curve box was founded. The corresponding formulas of dynamic Bayesian expectation and variance were deduced. Combined with one-dimensional Fibonacci automatic search scheme of optimal step size,the Powell optimization theory was utilized to research the stochastic identification of displacement parameters of indeterminate thin-walled curve box. Then the identification steps were presented in detail and the corresponding calculation procedure was compiled. Through some classic examples,it is obtained that stochastic performances of systematic parameters and systematic responses are simultaneously deliberated in dynamic Bayesian error function. The one-dimensional optimization problem of the optimal step size is solved by adopting Fibonacci search method. And the Powell identification of displacement parameters of indeterminate thin-walled curve box has satisfied numerical stability and convergence,which demonstrates that the presented method and the compiled procedure are correct and reliable.During parameters鈥？iterative processes,the Powell theory is irrelevant with the calculation of finite curve strip element（FCSE） partial differentiation,which proves high computation effciency of the studied method.

Interaction of Photoactive[Fe(CN)_6]^(4-) with TiO_2 Anatase(101) Surface:A Periodic Density Functional Theory Study

The plane-wave pseudopotential function method, based on density-functional theory, has been used to calculate the adsorption, electronic band structures, orbitals and optical absorption spectrum of [Fe（CN）6]^4- on TiOz anatase（101） surface. Our calculations reveal that the surface-modified anatase system has large adsorption energy and a much narrower band gap. [Fe（CN）6]^4- adsorption on the （101） surface could lead to a large red shift of the anatase optical absorption threshold, which extends into a visible region significantly. The calculated results are in agreement with the experiment and other theoretical studies reasonably. It is very important for the understanding and further development ofphotovoltaic materials that are active under visible light.

QUALITATIVE REASONING BY COMPUTING WITH WORDS IN HERRERA-MARTíNEZ’S LINGUISTIC MODEL

Most of modern systems for information retrieval, fusion and management have to deal with more and more qualitative information （by linguistic labels） besides information expressed quantitatively （by numbers）, since human reports are better and easier expressed in natural language than with numbers. In this paper, Herrera-Martfnez＇s 2-Tuple linguistic representation model is extended for reasoning with uncertain and qualitative information in Dezert-Smarandache Theory （DSmT） framework, in order to overcome the limitations of current approaches, i.e., the lack of precision in the final results of linguistic information fusion according to 1-Tuple representation （ q1 ）- The linguistic information which expresses the expert＇s qualitative beliefs is expressed by means of mixed 2 Tuples （equidistant linguistic labels with a numeric biased value）. Together with the 2-Tuple representation model, some basic operators are presented to carry out the fusion operation among qualitative information sources. At last, through simple example how 2-Tuple qualitative DSmT-based （q2 DSmT） fusion rules can be used for qualitative reasoning and fusion under uncertainty, which advantage is also showed by comparing with other methods.

On the Motivation and Reasons of Popularity of Parody in Network Language From the Perspective of Conceptual Integration Theory

The Conceptual Integration Theory was first formally put forward in 1997 by Fauconnier and Turner. According to it, there is a conceptual blending network comprised of four mental spaces： Input space Ⅰ, Input space Ⅱ, generic space, and blended space. In the process of blending, common information or structures from input spaces are projected to the ＂generic space＂. Meanwhile, through partially cross-space mapping, those structures are selectively projected to the ＂blended space＂. By means of composition, completion, and elaboration, consequently ＂emergent structure＂ comes into being from the development of blending. This theory instantly became a fresh power in cognitive research field. With the rapid development of network technology and the popularization of the internet, network language makes tremendous progresses and spreads quickly, which reflects the social and cultural development. The uniqueness and effectiveness of network language creation, to a great extent, relies on various rhetorical devices, among which parody is frequently used and plays an important role. In recent years, studies about network language somehow concentrate a lot on the construction, word transformation, and features of network vocabulary, and cognitive analysis on the mechanism of parody in network language is rather limited and requires further exploration. This paper tends to probe into the motivation and the reasons ofparody＇s popularity in network language through some examples in light of Conceptual Integration Theory in hope of a better comprehension, appreciation, and application of parody in network language

Cosmological parameters for spatially flat dust filled Universe in Brans-Dicke theory

We have investigated late time acceleration for a spatially fiat dust filled Universe in Brans- Dicke theory in the presence of a positive cosmological constant A. Expressions for Hubble＇s constant, luminosity distance and apparent magnitude have been obtained for our model. The theoretical results are compared with observed values of the latest 287 high redshift （0.3 ≤ z ≤1.4） Type Ia supernova data taken from the Union 2.1 compilation to estimate present values of matter and dark energy parame- ters, （Ωm）0 and （ΩA）0. We have also estimated the present value of Hubble＇s constant H0 in light of an updated sample of Hubble parameter measurements including 19 independent data points. The results are found to be in good agreement with recent astrophysical observations. We also calculated various physical parameters such as matter and dark energy densities, present age of the Universe and decelera- tion parameter. The value for Brans-Dicke-coupling constant ω is set to be 40 000 based on accuracy of solar system tests and recent experimental evidence.

Comparative Studies of 1,4-Bis[2-(4-Pyridyl)ethenyl]-benzene Using Density Functional Theory

The optimized molecular structure and harmonic vibrational frequencies of a 1,4-bis [ 2-（4-pyridyl）ethenyl]- benzene（BPENB） molecule were calculated via five popular density functional theory（DFI＇） methods. On the basis of the comparison between calculated and experimental results, it is concluded that the B3PW91 and B3LYP methods are superior to the others in optimizing structures, and the BPW91 method reproduces the observed fundamental fre-quencies most satisfactorily.

On the “Reasonable” Handling of Personal Information Disclosed According to the Law

The model for protection of personal information dis-closed according to the law has changed from indirect protection to direct protection.The indirect protection model for traditional repu-tation rights and privacy rights was not enough to meet the practical needs of governance.However;due to the ambiguity in the application of the“reasonable”processing requirements,the direct protection model centered on Article 27 of the Personal Information Protection Law also is not enough to effectively respond to practical disputes.The essence of the problem is to resolve the tension between informa-tion circulation and risk control and reshape the legal order for the protection of personal information disclosed according to the law.The determination of“reasonable”should be centered on the scenario theory and holism interpretation and carried out by using the interpre-tation technique of the dynamic system under Article 998 of the Civil Code.With the support of scenario-based discussions and comparative propositions,the crawling and tag extraction of personal information.disclosed according to the law should be considered as reasonable processing;profiling and automated decision-making should not be covered in the scope of reasonable processing,in principle;for behav-iors such as correlation analysis,elements like information subject,identifiability and sensitivity should be comprehensively considered to draw open and inclusive conclusions in individual cases.

基于模糊Petri网的引航员作业舒适度评价

为提高引航员的作业舒适度,提出一种基于模糊Petri网(FPN)的模糊推理算法(FRA)下的组合评价方法。首先,针对作业舒适度影响因子的不确定性信息,建立多因素耦合的FPN拓扑结构;然后,采用博弈论组合赋权法确定最优组合权重,提出融合层间相关性判断临界重要性、层次分析法和FRA,建立基于主客观权重的FRA,通过迭代求解库所可信度和状态矩阵;最后,结合上海港船舶引航的场景数据,基于FPN的FRA应用,评价引航员作业舒适度。结果表明:环境与引航设备是影响其作业舒适度的关键因素,冬季和夏季的引航作业舒适度评价等级对应“较不舒适”,其中,5月份为“较舒适”。所提方法充分体现系统舒适度影响因素的耦合特性。

再论思政课为什么讲道理及如何讲道理

思政课是高校落实立德树人根本任务的关键课程,思政课的本质属性、育人目标和创新要求决定了“讲道理”的必然性、主要内容以及方式方法。新形势下,高校思政课既要讲好事关党和国家发展的宏观道理,又要讲好有关个人成长成才与自由而全面发展的微观道理。这就要求高校思政课要结合马克思主义的立场观点方法把道理讲深、融合时代背景和“四史”教育把道理讲透、联系生活实际把道理讲活,真正做到启智润心、激扬斗志。

再论受教育权——基于“理由束”方法论的分析视角

对于“何为受教育权”这一问题,既有的受教育权方法论并未提供有效的应答策略。描述性方法论界定的受教育权概念缺少区分性和普遍性特征,评价性方法论因无力解决并不稳定的教育价值立场问题而使得受教育权概念陷入正当性“陷阱”。对此,在理由论的基础上,受教育权可被视为依附于一束理由的“要求”。在该“理由束”中,结合欧洲人权法院相关判决,受教育者的自我实现是初级内在理由,平等接受教育为次级内在理由,而包括国家干预在内的其他理由则构成外在理由;受教育权的初级和次级内在理由属于立法范畴的理由,又因无法在立法上穷尽外在理由,所以外在理由被分配至司法范畴。

情理司法抑或经权司法:立足宋代的理论与实践辨正

情理司法通常被作为传统中国司法的代表性模式来讨论,但这种学术概括存在时空局限和理论缺憾。在时空上,情理司法说主要提炼自明清司法实践,难以融贯解释此前,尤其是宋代的司法模式。在理论上,它难以解释情理司法源于何种理论及其在整个国家司法制度中的功能、作用和旨趣等核心问题,还会带来理论误导和价值遮蔽。追根溯源,情理司法根源于传统经学中的经权理论。传统经权理论在宋代获得了实质性发展,从中可以提炼出义统经权、权即是经、情时而权、圣贤行权等创新性命题。宋代士大夫官僚作为新经权理论的倡导者和推动者,将其引入司法实践,形成了具有时代特色的经权司法模式,并呈现为怀法用权、缘情用权、相时用权三种运行机制。宋代经权司法是在守法的前提下,因个案之情、理、时等因素而行权裁判,目的是补救机械守法裁判之弊,让司法合于中道价值。由于经权司法主要体现为缘情理而行权,所以常被称为情理裁判,进而被概括为情理司法。正本清源而言,宋元明清时期的经权司法是儒家经学影响司法实践的典型形式,与汉唐时期的春秋决狱共同构成了帝制时期传统司法中的救弊型司法,二者均属于特别司法模式。

消费者网络购物意向分析--理性行为理论与计划行为理论的比较

基于理性行为理论和计划行为理论提出了消费者网络购物意向的模型,研究表明,相对于理性行为理论,计划行为理论能更好地解释消费者网络购物意向。行为态度、知觉行为控制对网购意向有明显影响,但是主观规范的影响不显著。研究发现消费者过去网络购物行为对网购意向有重要影响,而且这种影响要远远大于行为态度和知觉行为控制对网购意向的影响。

理性行动-社会认同整合性集体行动模型

为探究理性行动理论和社会认同理论两大社会心理学宏论对于个体集体行动参与倾向的共同解释力,以"中日撞船事件"为考察蓝本向天津市431名大学生被试进行调查研究,结果发现:效能和社会规范作为态度和行动倾向的中介变量,在不同情境下对行动倾向的作用不同,符合理性行动原则;内部动机作为态度和效能、社会规范之间的中介变量,并受到学校认同和国家认同的直接或间接影响,支持了社会认同理论对遵从规范行为的解释;回归分析验证了不同水平认同对行动倾向作用程度的差异,整合模型则揭示了其具体的作用路径和影响机制。结论:理性行动理论与社会认同理论可彼此互补成为集体行动参与的整合性解释框架。

基于动态常识推理与多维语义特征的幽默识别

随着社交媒体的飞速发展,幽默识别任务受到研究者广泛关注。其目标是判断给定文本是否具有幽默表达。现有方法主要基于幽默产生理论,采用规则或神经网络模型提取多种幽默相关特征,如不一致性、情感和语音等。然而,这些方法未充分捕捉文本内部的情感特征,忽视了隐含在幽默文本中的情感表达,影响了幽默识别的准确性。为解决此问题,该文提出了CMSOR方法,以动态常识和多维语义特征为驱动。首先,利用外部常识信息从文本中动态推理说话者的隐式情感表达;然后,引入WordNet词典计算词级语义距离,捕捉不一致性,并计算模糊性特征;最后,基于这三个特征维度构建幽默语义,实现幽默识别。实验证明,CMSOR模型相对于当前基准模型在三个公开数据集上的识别性能均有显著提升。

一种快速DSmT-DS近似推理融合方法

该文对Dempster-Shafer(DS)理论以及Dezert-Smarandache理论(DSm T)进行了深入研究,为了能够在仅需较低计算复杂度的前提下得到更加精确的融合结果,提出一种新的快速DSm T-DS近似推理融合方法。该方法针对超幂集空间仅单子焦元具有信度赋值的情况,将超幂集空间拆分映射成元素为各单子焦元和其补集的二元集合的新的超幂集空间,并求出每个补集的信度赋值;再运用Dezert-Smarandache框架中的第5条比例冲突分配规则(DSm T+PCR5)在新的超幂集空间的二元集合子空间下对多证据源进行融合,得到各单子焦元的融合结果;然后通过归一化处理求得各单子焦元的信度赋值。通过理论分析得出该文方法的融合结果是介于Dezert-Smarandache框架中的第5条比例冲突分配规则(DSm T+PCR5)及Dempster-Shafer(DS)框架下的Dempster组合规则之间。该文方法在需要较低计算复杂度的前提下,可以得到优于Dempster组合规则的近似融合结果。最后通过多个角度与已有方法进行对比,验证了该文方法的优越性。

一种基于多传感器时间-空间信息融合的红外小目标识别方法

为了提高强干扰条件下的红外弱小目标识别的可靠性 ,提出了一种基于多传感器时间 空间信息融合的红外小目标识别方法 ,并采用D S证据合成理论对来自多个红外双波段成像传感器的实际图像信息进行了仿真融合计算 .