A new oil spill detection algorithm based on Dempster-Shafer evidence theory

Features of oil spills and look-alikes in polarimetric synthetic aperture radar(SAR)images always play an important role in oil spill detection.Many oil spill detection algorithms have been implemented based on these features.Although environmental factors such as wind speed are important to distinguish oil spills and look-alikes,some oil spill detection algorithms do not consider the environmental factors.To distinguish oil spills and look-alikes more accurately based on environmental factors and image features,a new oil spill detection algorithm based on Dempster-Shafer evidence theory was proposed.The process of oil spill detection taking account of environmental factors was modeled using the subjective Bayesian model.The Faster-region convolutional neural networks(RCNN)model was used for oil spill detection based on the convolution features.The detection results of the two models were fused at decision level using Dempster-Shafer evidence theory.The establishment and test of the proposed algorithm were completed based on our oil spill and look-alike sample database that contains 1798 image samples and environmental information records related to the image samples.The analysis and evaluation of the proposed algorithm shows a good ability to detect oil spills at a higher detection rate,with an identifi cation rate greater than 75%and a false alarm rate lower than 19%from experiments.A total of 12 oil spill SAR images were collected for the validation and evaluation of the proposed algorithm.The evaluation result shows that the proposed algorithm has a good performance on detecting oil spills with an overall detection rate greater than 70%.

An Improved CREAM Model Based on DS Evidence Theory and DEMATEL

Cognitive Reliability and Error Analysis Method(CREAM)is widely used in human reliability analysis(HRA).It defines nine common performance conditions(CPCs),which represent the factors thatmay affect human reliability and are used to modify the cognitive failure probability(CFP).However,the levels of CPCs are usually determined by domain experts,whichmay be subjective and uncertain.What’smore,the classicCREAMassumes that the CPCs are independent,which is unrealistic.Ignoring the dependence among CPCs will result in repeated calculations of the influence of the CPCs on CFP and lead to unreasonable reliability evaluation.To address the issue of uncertain information modeling and processing,this paper introduces evidence theory to evaluate the CPC levels in specific scenarios.To address the issue of dependence modeling,the Decision-Making Trial and Evaluation Laboratory(DEMATEL)method is used to process the dependence among CPCs and calculate the relative weights of each CPC,thus modifying the multiplier of the CPCs.The detailed process of the proposed method is illustrated in this paper and the CFP estimated by the proposed method is more reasonable.

THE COMBINATION PREDICTION OF TRANSMEMBRANE REGIONS BASED ON DEMPSTER-SHAFER THEORY OF EVIDENCE

Transmembrane proteins are some special and important proteins in cells. Because of their importance and specificity, the prediction of the transmembrane regions has very important theoretical and practical significance. At present, the prediction methods are mainly based on the physicochemical property and statistic analysis of amino acids. However, these methods are suitable for some environments but inapplicable for other environments. In this paper, the multi-sources information fusion theory has been introduced to predict the transmembrane regions. The proposed method is test on a data set of transmembrane proteins. The results show that the proposed method has the ability of predicting the transmembrane regions as a good performance and powerful tool.

Multi-VMs Intrusion Detection for Cloud Security Using Dempster-shafer Theory

Cloud computing provides easy and on-demand access to computing resources in a configurable pool.The flexibility of the cloud environment attracts more and more network services to be deployed on the cloud using groups of virtual machines(VMs),instead of being restricted on a single physical server.When more and more network services are deployed on the cloud,the detection of the intrusion likes Distributed Denialof-Service(DDoS)attack becomes much more challenging than that on the traditional servers because even a single network service now is possibly provided by groups of VMs across the cloud system.In this paper,we propose a cloud-based intrusion detection system(IDS)which inspects the features of data flow between neighboring VMs,analyzes the probability of being attacked on each pair of VMs and then regards it as independent evidence using Dempster-Shafer theory,and eventually combines the evidence among all pairs of VMs using the method of evidence fusion.Unlike the traditional IDS that focus on analyzing the entire network service externally,our proposed algorithm makes full use of the internal interactions between VMs,and the experiment proved that it can provide more accurate results than the traditional algorithm.

Application of the Dempster-Shafer Theory to the Classification of Pixels from Aster Satellite Images and Spectral Indices

In this paper, it is proposed to apply the Dempster-Shafer Theory (DST) or the theory of evidence to map vegetation, aquatic and mineral surfaces with a view to detecting potential areas of observation of outcrops of geological formations (rocks, breastplates, regolith, etc.). The proposed approach consists in aggregating information by using the DST. From pretreated Aster satellite images (geo-referencing, geometric correction and resampling at 15 m), new channels were produced by determining the spectral indices NDVI, MNDWI and NDBaI. Then, the DST formalism was modeled and generated under the MATLAB software, an image segmented into six classes including three absolute classes (E,V,M) and three classes of confusion ({E,V}, {M,V}, {E,M}). The control on the land, based on geographic coordinates of pixels of different classes on said image, has made it possible to make a concordant interpretation thereof. Our contribution lies in taking into account imperfections (inaccuracies and uncertainties) related to source information by using mass functions based on a simple support model (two focal elements: the discernment framework and the potential set of belonging of the pixel to be classified) with a normal law for the good management of these.

基于Dempster-Shafer证据理论的航空发动机磨损状况融合诊断

本文利用Dempster-Shafer证据理论对滑油光谱分析得到的铜、铁、银3种元素含量进行融合诊断,从而达到对航空发动机磨损状况更为准确的判断,同时也提高了发动机工作的可靠性。通过对实测的两组样本数据进行融合诊断分析,发现3种元素的融合诊断结果比单一元素诊断结果更准确、可信度更高。第一组样本数据诊断正确的概率从37.05%提高到76.52%,第二组样本数据诊断正确的概率从69.59%提高到96.26%。

Structural damage assessment using improved Dempster-Shafer data fusion algorithm

As an efficient tool in handling uncertain issues, Dempster-Shafer evidence theory has been increasingly used in structural health monitoring and damage detection. In applications, however, Dempster-Shafer evidence theory sometimes leads to counter-intuitive results. In this study, a new fusion algorithm of evidence theory is put forward to address various counter-intuitive problems and manage the reliability difference of the evidence. The proposed algorithm comprises the following aspects:(1) Dempster's combination rule is generalized by introducing the concept of evidence ullage. The new rule allows classical Dempster's rule and can resolve counter-intuitive problems cause by evidence conflict and evidence compatibility;(2) a reliability assessing method based on a priori and posterior knowledge is proposed. Compared with conventional reliability assessment, the proposed method can reflect the actual evidence reliabilities and can efficiently reduce decision risk. Numerical examples confirm the validity and utility of the proposed algorithm. In addition, an experimental investigation on a spatial truss structure is carried out to illustrate the identified ability of the proposed approach. The results indicate that the fusion algorithm has no strict request on the accuracy and consistency of evidence sources and can efficiently enhance diagnostic accuracy.

A Renormalizable Theory of Quantum Gravity: Renormalization Proof of the Gauge Theory of Volume Preserving Diffeomorphisms

Inertial and gravitational mass or energy momentum need not be the same for virtual quantum states. Separating their roles naturally leads to the gauge theory of volume-preserving diffeomorphisms of an inner four-dimensional space. The gauge-fixed action and the path integral measure occurring in the generating functional for the quantum Green functions of the theory are shown to obey a BRST-type symmetry. The related Zinn-Justin-type equation restricting the corresponding quantum effective action is established. This equation limits the infinite parts of the quantum effective action to have the same form as the gauge-fixed Lagrangian of the theory proving its spacetime renormalizability. The inner space integrals occurring in the quantum effective action which are divergent due to the gauge group’s infinite volume are shown to be regularizable in a way consistent with the symmetries of the theory demonstrating as a byproduct that viable quantum gauge field theories are not limited to finite-dimensional compact gauge groups as is commonly assumed.

人工智能医疗侵权纠纷中的责任承担与举证分配

涉及人工智能医疗技术的民事医疗纠纷中的侵权责任与举证分配已成为愈发重要的法学课题。不同国家对于人工智能侵权责任的分配机制是不同的。在我国,人工智能医疗侵权责任具有医疗损害责任与产品责任两种属性。根据实体法上的法律要件分类进行举证责任的分配是民事案件的一般规则。鉴于人工智能医疗存在技术上的特殊性与证据偏在的情形,有必要对其适用危险领域理论的举证责任分配规则。法院需要在人工智能医疗纠纷中根据具体情形进行举证责任的倒置与举证责任的减轻;同时,法院也可依当事人申请进行证据调查活动,通过文书提出命令等手段平衡双方当事人的证据收集能力。

Temporal evidence combination method for multi-sensor target recognition based on DS theory and IFS

In order to effectively deal with the conflict temporal evidences without affecting the sequential and dynamic characteristics in the multi-sensor target recognition(MSTR) system at the decision making level, this paper proposes a Dempster-Shafer(DS) theory and intuitionistic fuzzy set(IFS) based temporal evidence combination method(DSIFS-TECM). To realize the method,the relationship between DS theory and IFS is firstly analyzed. And then the intuitionistic fuzzy possibility degree of intuitionistic fuzzy value(IFPD-IFV) is defined, and a novel ranking method with isotonicity for IFV is proposed. Finally, a calculation method for relative reliability factor(RRF) is designed based on the proposed ranking method. As a proof of the method, numerical analysis and experimental simulation are performed. The results indicate DSIFS-TECM is capable of dealing with the conflict temporal evidences and sensitive to the changing of time. Furthermore, compared with the existing methods, DSIFS-TECM has stronger ability of anti-interference.

Privacy-preserving Distributed Location Proof Generating System

The rapid development of location-based service(LBS) drives one special kind of LBS, in which the service provider verifies user location before providing services. In distributed location proof generating schemes, preventing users from colluding with each other to create fake location proofs and protecting user's location privacy at the same time, are the main technical challenges to bring this kind of LBS into practical. Existing solutions tackle these challenges with low collusion-detecting efficiency and defected collusion-detecting method. We proposed two novel location proof generating schemes, which inversely utilized a secure secret-sharing scheme and a pseudonym scheme to settle these shortcomings. Our proposed solution resists and detects user collusion attacks in a more efficient and correct way. Meanwhile, we achieve a higher level of location privacy than that of previous work. The correctness and efficiency of our proposed solution is testified by intensive security analysis, performance analysis, as well as experiments and simulation results.

一类决策模型的payoff-proof纳什均衡解

研究1种基于线性规划约束的多人决策模型。首先,运用线性规划和对偶理论给出了纳什均衡点存在的充分必要条件,进而证明了在这种模型下的纳什均衡点可以在多项式时间内求解。其次,在原有的纳什均衡定义的基础上,定义了1个强均衡的概念—payoff-proof纳什均衡,并对前述模型研究了payoff-proof纳什均衡的性质和存在性。

Performance analysis of blockchain for civil aviation business data based on M/G/1 queuing theory

An Ethereum blockchain based on proof of stake ( PoS) consensus mechanism is used to achieve the data sharing within the civil aviation service platform for both airport group management and passengers. Considering the Gas consumption of Ethereum, the dynamic batch-service capacity constraint by the Block Gas Limit and the priority mechanism depending on the different Gas Price of transactions, M/ G/1 queuing theory with batch-service is used to construct the service model of transactions confirmation process in the proposed blockchain system, where the effects of transactions arrival rate, block capacity, service rate and number of nodes on the average confirmation time of transactions with different priority are analyzed, and eventually a performance analysis model of blockchain for civil aviation business data is proposed. The simulation results prove the usability and accuracy of the model, which can provide both theoretical basis for data sharing of civil aviation using Ethereum blockchain and the further optimization of transactions confirmation time.

从实践应用到证据法定:大数据证据的理论证成与规则建构

伴随着大数据时代的到来,大数据证据在司法实践中的证明价值愈加凸显。在肯定大数据证据实践证明价值的同时,囿于大数据证据在我国证据法地位的缺失、证据审查判断规则的缺位,使得大数据证据在法庭审查判断时表现混乱、在法庭质证时辩护效率低下,导致证据裁判规则规范侦查行为的价值功能失灵。从大数据证据的内生应用逻辑出发,大数据证据成为独立证据具有实践基础,包括大数据证据改变了传统证据的司法认知路径,推动了印证证明模式向综合验证模式的转向;大数据证据成为独立证据具有现实基础,包括电子数据无法与大数据证据等同、书证难以包容大数据证据、鉴定意见与大数据证据存在明显区分以及大数据证据与勘验、检查笔录和证人证言等法定证据类型存在诸多区别;大数据证据成为独立证据具有法理基础,从程序法的角度可以发现我国法定证据的分类存在着与取证型侦查行为密切相关的司法逻辑,即一种取证型侦查行为的诞生便会产生一种相对应的证据分类,结合当前我国新型犯罪侦查治理的需要,基于大数据搜索、大数据挖掘等新的取证型大数据侦查行为的出现,大数据证据成为独立证据类型也同样符合我国基于取证型侦查行为的诞生而伴生新的证据类型的法理基础。从大数据证据的真实性审查、合法性审查、科学性审查以及关联性审查等方面建构我国大数据证据的审查判断规则;以印证证明为基础,建构证据与证据之间、证据与案件事实之间、事实与事实之间,及其证据、事实与数据之间“网状式验证”的综合验证规则;以及建构包括绝对排除、相对排除为内容的大数据证据排除规则,可以有效推动我国大数据证据的基本理论证成与证据应用规则的完善。

A Multi-Attribute Decision-Making Method Using Belief-Based Probabilistic Linguistic Term Sets and Its Application in Emergency Decision-Making

Probabilistic linguistic term sets(PLTSs)are an effective tool for expressing subjective human cognition that offer advantages in the field ofmulti-attribute decision-making(MADM).However,studies have found that PLTSs have lost their ability to accurately capture the views of decision-makers(DMs)in certain circumstances,such as when the DM hesitates between multiple linguistic terms or the decision information is incomplete,thus affecting their role in the decision-making process.Belief function theory is a leading streamof thought in uncertainty processing that is suitable for dealing with the limitations of PLTS.Therefore,the purpose of this study is to extend PLTS to incorporate belief function theory.First,we provide the basic concepts of the extended PLTS(i.e.,belief-based PLTS)through case analyses.Second,the aggregation operator of belief-based PLTS is defined with the ordered weighted average(OWA)-based soft likelihood function,which is improved by considering the reliability of the information source.Third,to measure the magnitude of different belief-based PLTSs,the belief interval of singleton is calculated,and the comparison method of belief-based PLTS is constructed based on probabilities.On the basis of the preceding discussion,we further develop an emergency decision framework that includes several novel techniques,such as attribute weight determination and decision information aggregation.Finally,the usefulness of the framework is demonstrated through a case study,and its effectiveness is illustrated through a series of comparisons.

多因素波动影响下事件状态的联系数表示研究

为研究在因素波动影响下事件状态变化和不同状态出现的可能性,本文将语义划分与集对分析联系数的多级状态对应,建立因素波动影响下的事件状态联系数表示方法。制定了单因素波动情况下事件状态联系数的构建方法,以单位因素区间对因素平面进行离散,分别计算各离散区域的联系数,综合所有联系数形成事件状态联系数。根据数值逻辑的或关系和联系数运算法则耦合单因素事件状态联系数得到2因素事件状态联系数。多因素通过切片法降维至2因素才可使用上述方法。本文证明了离散求解与整体求解的等价性,使用各语义划分面积比例计算联系数较离散法更为方便。实例中使用整体求解法计算了2因素事件状态联系数。最后说明了本文方法面临的问题、原因和解决方法。

Comparison of Layer-stacking and Dempster-Shafer Theory-based Methods Using Sentinel-1 and Sentinel-2 Data Fusion in Urban Land Cover Mapping

Data fusion has shown potential to improve the accuracy of land cover mapping,and selection of the optimal fusion technique remains a challenge.This study investigated the performance of fusing Sentinel-1(S-1)and Sentinel-2(S-2)data,using layer-stacking method at the pixel level and Dempster-Shafer(D-S)theory-based approach at the decision level,for mapping six land cover classes in Thu Dau Mot City,Vietnam.At the pixel level,S-1 and S-2 bands and their extracted textures and indices were stacked into the different single-sensor and multi-sensor datasets(i.e.fused datasets).The datasets were categorized into two groups.One group included the datasets containing only spectral and backscattering bands,and the other group included the datasets consisting of these bands and their extracted features.The random forest(RF)classifier was then applied to the datasets within each group.At the decision level,the RF classification outputs of the single-sensor datasets within each group were fused together based on D-S theory.Finally,the accuracy of the mapping results at both levels within each group was compared.The results showed that fusion at the decision level provided the best mapping accuracy compared to the results from other products within each group.The highest overall accuracy(OA)and Kappa coefficient of the map using D-S theory were 92.67%and 0.91,respectively.The decision-level fusion helped increase the OA of the map by 0.75%to 2.07%compared to that of corresponding S-2 products in the groups.Meanwhile,the data fusion at the pixel level delivered the mapping results,which yielded an OA of 4.88%to 6.58%lower than that of corresponding S-2 products in the groups.

行政赔偿诉讼证明责任分配的二元建构--兼评2022年行政赔偿司法解释第11、12条

行政赔偿诉讼的证明责任分配应当进行“原则+规范”的二元建构。原则层面,规范说具有普适性和明确性优势,值得采纳。规范层面,我国现行立法“原则与例外”式证明责任分配规则体系基本符合规范说的要求,但由于需要同时适用行政诉讼法与国家赔偿法,而两法本身存在逻辑冲突并伴随具体规则的差异,使得同时适用模式面临困境。对此,应打破两法并立的格局,确立国家赔偿法的唯一基础规范地位,并将司法解释的内容纳入其中,赋予其法律地位。

争点形成与疑点形成——辩护方证明责任的两种形态

随着“三项规程”的施行,争点与疑点范畴被引入刑事程序,在基本属性、作用方式与主要功能上存在差异。争点形成与疑点形成,是辩护方履行证明责任的两种形态,长久以来面临诸多误解。争点形成责任产生于英美法系,与证据提出相结合,成为举证责任的基本内容。疑点形成责任来源于大陆法系,与职权调查相匹配,被视为职权主义的必然产物。在我国规范层面,争点形成与疑点形成均得到体现,但在责任形态上存在变化。淡化证据提出责任,相对独立的争点形成责任初步形成。弱化职权主义,强疑点形成责任应运而生。改良后的争点形成责任和疑点形成责任,并存于我国刑事程序,其间存在转化可能,根据待证事项的不同,形成责任组合的层次性理论。

司法证明认知路径论的反思与展望

司法证明认知路径直接决定了司法证明活动的质量。当前,主流的认知路径论是印证证明理论。印证证明理论以一致性评价为内核,以真理融贯论、真理符合论、归纳推理与溯因推理为基础。在理论架构上,一致性评价指向模糊,且印证证明理论的基础过于杂糅。据此,印证证明理论无法有效指导司法实践。司法证明认知路径论应当从印证向证成转型与变革。认知证成路径与自由心证的司法语境相契合,并且有助于增强裁判的认知正当性。