Research on the applicable problems of the rules of the exclusion of the illegal evidences

With the full implementation of the Code of Criminal Procedure, the application of the rules of the exclusion of the illegal evidences is more inclined to the protection of the human rights. However, in the process of the implementation of the new laws, the problems in view of the rules of the exclusion of the illegal evidences are also prominent, which are mainly reflected in the ambiguity of the scope of the application, the start of the program of the exclusion, and the formalization the trial certificates and other aspects. Therefore, in this article, the author starts from the concept of the illegal evidences, and expounds the principles of the exclusion and the abilities of the evidences, and especially explores the abilities of the evidences and the probative forces. From the differences between the two, the author strictly proves the virtualization of the standards, in order to provide the positive solutions for strengthening the exclusionary procedure of the illegal evidences.

A new fusion approach based on distance of evidences

Based on the framework of evidence theory, data fusion aims at obtaining a single Basic Probability Assignment (BPA) function by combining several belief functions from distinct information sources. Dempster’s rule of combination is the most popular rule of combinations, but it is a poor solution for the management of the conflict between various information sources at the normalization step. Even when it faces high conflict information, the classical Dempster-Shafer’s (D-S) evidence theory can involve counter-intuitive results. This paper presents a modified averaging method to combine conflicting evidence based on the distance of evidences; and also gives the weighted average of the evidence in the system. Numerical examples showed that the proposed method can realize the modification ideas and also will provide reasonable results with good convergence efficiency.

New weighting factors assignment of evidence theorybased one vidence distance

Evidence theory has been widely used in the information fusion for its effectiveness of the uncertainty reasoning. However, the classical DS evidence theory involves counter-intuitive behaviors when the high conflict information exists. Based on the analysis of some modified methods, Assigning the weighting factors according to the intrinsic characteristics of the existing evidence sources is proposed, which is determined on the evidence distance theory. From the numerical examples, the proposed method provides a reasonable result with good convergence efficiency. In addition, the new rule retrieves to the Yager's formula when all the evidence sources contradict to each other completely.

Modification of evidence theory based on feature extraction

Although evidence theory has been widely used in information fusion due to its effectiveness of uncertainty reasoning, the classical DS evidence theory involves counter-intuitive behaviors when high conflict information exists. Many modification methods have been developed which can be classified into the following two kinds of ideas, either modifying the combination rules or modifying the evidence sources. In order to make the modification more reasonable and more effective, this paper gives a thorough analysis of some typical existing modification methods firstly, and then extracts the intrinsic feature of the evidence sources by using evidence distance theory. Based on the extracted features, two modified plans of evidence theory according to the corresponding modification ideas have been proposed. The results of numerical examples prove the good performance of the plans when combining evidence sources with high conflict information.

An Evidence Combination Method based on DBSCAN Clustering

Dempster-Shafer(D-S)evidence theory is a key technology for integrating uncertain information from multiple sources.However,the combination rules can be paradoxical when the evidence seriously conflict with each other.In the paper,we propose a novel combination algorithm based on unsupervised Density-Based Spatial Clustering of Applications with Noise(DBSCAN)density clustering.In the proposed mechanism,firstly,the original evidence sets are preprocessed by DBSCAN density clustering,and a successfully focal element similarity criteria is used to mine the potential information between the evidence,and make a correct measure of the conflict evidence.Then,two different discount factors are adopted to revise the original evidence sets,based on the result of DBSCAN density clustering.Finally,we conduct the information fusion for the revised evidence sets by D-S combination rules.Simulation results show that the proposed method can effectively solve the synthesis problem of high-conflict evidence,with better accuracy,stability and convergence speed.

Reflection of the supplemem and correction of the defective evidences

Since the implementation of the rules of the supplement and correction of the defective evidences, there are many problems in the practice. The actual investigations and researches also feedback that the judges also have a lot of problems in the face of the definition of the meaning of the defective evidences, the correction application, and the degree restrictions. Behind this reflects the contradiction between the stress of the prosecution organs in the criminal detection and the deepening of the resisting mechanism in the court. And the litigation structure of the ＂division of responsibilities among three authorities＂ and the trial mode of ＂the centralism of the book records of the cases＂ exacerbated this opposition. On the basis of clarifying the origin and the meanings of the defective evidences, the author of this paper analyzes the essence and its harm of the rule. Through the reflections of the problems existing in the practice, the author further defines the two types of the ＂defects＂ that shall not be allowed to correct.

限缩法定犯适用的证明困境及其出路

在法定犯时代,为避免刑法过度适用减损国家治理整体效果,刑法学界提出了司法限缩方案,希望通过激活违法性认识的适用、严格审查前置的违法性、实质判断法益侵害程度来实现出罪减责。上述主张忽略了司法证明对构成要件的反向制约作用。违法性认识证明困难,决定其应作为责任要素,而非故意要素。行政监管的专业性和复杂性决定了,片面强调司法认定的独立性,否定行政鉴定与行政认定证据资格,不具有现实性。应区分关于专门性问题的报告和行政机关处理决定或意见,对前者参照司法鉴定意见予以规制,将后者归入辅助资料。将个人法益受到侵害作为法定犯构罪的前提,与增设法定犯特别是抽象危险犯立法目的不相适应。抽象危险和具体损害,只有通过反向刑事推定方可建立可转换的联系,从而实现积极出罪。

Target recognition based on modified combination rule

Evidence theory is widely used in the field of target recognition. The invalidation problem of this theory when dealing with highly conflict evidences is a research hotspot. Several alternatives of the combination rule are analyzed and compared. A new combination approach is proposed. Calculate the reliabilities of evidence sources using existing evidences. Construct reliabilities judge matrixes and get the weights of each evidence source. Weight average all inputted evidences. Combine processed evidences with D-S combination rule repeatedly to identify a target. The application in multi-sensor target reeognition as well as the comparison with typical alternatives all validated that this approach can dispose highly conflict evidences efficiently and get reasonable reeognition results rapidly.

Milling Fault Detection Method Based on Fault Tree Analysis and Hierarchical Belief Rule Base

Expert knowledge is the key to modeling milling fault detection systems based on the belief rule base.The construction of an initial expert knowledge base seriously affects the accuracy and interpretability of the milling fault detection model.However,due to the complexity of the milling system structure and the uncertainty of the milling failure index,it is often impossible to construct model expert knowledge effectively.Therefore,a milling system fault detection method based on fault tree analysis and hierarchical BRB(FTBRB)is proposed.Firstly,the proposed method uses a fault tree and hierarchical BRB modeling.Through fault tree analysis(FTA),the logical correspondence between FTA and BRB is sorted out.This can effectively embed the FTA mechanism into the BRB expert knowledge base.The hierarchical BRB model is used to solve the problem of excessive indexes and avoid combinatorial explosion.Secondly,evidence reasoning(ER)is used to ensure the transparency of the model reasoning process.Thirdly,the projection covariance matrix adaptation evolutionary strategies(P-CMA-ES)is used to optimize the model.Finally,this paper verifies the validity model and the method’s feasibility techniques for milling data sets.

Interactive-Adaptive Combination Rule

Aiming at the invalidation of DS theory dealing with the evidence in a high conflict and reducing confidence level of DSm theory processing a low conflict,this paper proposes an interactive-adaptive combination rule. Adopting the angle similarity based on hyper-power set as the weight of generalized Dempster rule and PCR rule,the new rule adaptively processes various evidence combination issues. In this way,the rule can obtain not only the better fusion of decision making effect in a low conflict,but also the solution to the synthesis in a high conflict. Simulation analysis demonstrates the validity and applicability from this rule of combination.

A New Prediction System Based on Self-Growth Belief Rule Base with Interpretability Constraints

Prediction systems are an important aspect of intelligent decisions.In engineering practice,the complex system structure and the external environment cause many uncertain factors in the model,which influence the modeling accuracy of the model.The belief rule base(BRB)can implement nonlinear modeling and express a variety of uncertain information,including fuzziness,ignorance,randomness,etc.However,the BRB system also has two main problems:Firstly,modeling methods based on expert knowledge make it difficult to guarantee the model’s accuracy.Secondly,interpretability is not considered in the optimization process of current research,resulting in the destruction of the interpretability of BRB.To balance the accuracy and interpretability of the model,a self-growth belief rule basewith interpretability constraints(SBRB-I)is proposed.The reasoning process of the SBRB-I model is based on the evidence reasoning(ER)approach.Moreover,the self-growth learning strategy ensures effective cooperation between the datadriven model and the expert system.A case study showed that the accuracy and interpretability of the model could be guaranteed.The SBRB-I model has good application prospects in prediction systems.

Operational effectiveness evaluation based on the reduced conjunctive belief rule base

To address the issue of rule premise combination explosion in the construction of the traditional complete conjunctive belief rule base(BRB),this paper introduces an orthogonal design method to reduce the conjunctive BRB.The reasoning method based on reduced conjunctive BRB is designed with the help of the conversion technology from conjunctive BRB to disjunctive BRB.Finally,the operational mission effectiveness evaluation is taken as an example to verify the proposed method.The results show that the method proposed in this paper is feasible and effective.

A Processor Performance Prediction Method Based on Interpretable Hierarchical Belief Rule Base and Sensitivity Analysis

The prediction of processor performance has important referencesignificance for future processors. Both the accuracy and rationality of theprediction results are required. The hierarchical belief rule base (HBRB)can initially provide a solution to low prediction accuracy. However, theinterpretability of the model and the traceability of the results still warrantfurther investigation. Therefore, a processor performance prediction methodbased on interpretable hierarchical belief rule base (HBRB-I) and globalsensitivity analysis (GSA) is proposed. The method can yield more reliableprediction results. Evidence reasoning (ER) is firstly used to evaluate thehistorical data of the processor, followed by a performance prediction modelwith interpretability constraints that is constructed based on HBRB-I. Then,the whale optimization algorithm (WOA) is used to optimize the parameters.Furthermore, to test the interpretability of the performance predictionprocess, GSA is used to analyze the relationship between the input and thepredicted output indicators. Finally, based on the UCI database processordataset, the effectiveness and superiority of the method are verified. Accordingto our experiments, our prediction method generates more reliable andaccurate estimations than traditional models.

基于循证证据的麻醉科处方前置审核规则精细化设置及效果评价

目的 优化麻醉科处方前置审核规则,提高审方质量和合理用药水平。方法 统计并分析2023年4月1日至30日青岛大学附属医院(以下简称“我院”)处方前置审核系统中麻醉科的住院医嘱,对不合理用药问题进行分类统计与循证查询,结合我院现执行的《麻醉科临床路径用药规范》,对审核规则进行精细化设置,并建立审核管理与沟通反馈流程。对规则精细化设置后(2023年5-12月)与设置前(2023年4月)的每月审核医嘱总数、预审弹窗医嘱数、系统拦截率、系统审核后医师修改率、药师审核率、医嘱合理率进行比较,对设置后与设置前(2022年5-12月)的麻醉科次均药费进行环比比较。结果 麻醉科不合理用药问题主要包括适应证不适宜、给药途径不适宜、用法用量不适宜、配伍不适宜、特殊人群用药问题、围手术期不合理用药问题。规则精细化设置后,麻醉科预审弹窗医嘱数随时间延长明显减少,经过不断完善后逐步达到平稳状态。与设置前比较,规则精细化设置后系统拦截率显著提高(P<0.001),系统审核后医师修改率显著提高(P<0.001),药师审核率显著下降(P<0.001);2023年5-12月医嘱合理率与月份存在线性趋势(P<0.001)。设置后与设置前相比,麻醉科次均药费由平均720.72元下降至平均528.21元,降幅为26.71%。结论 基于循证证据精细化设置麻醉科处方前置审核规则,可显著提高处方审核质量,促进合理用药,节约患者医疗费用。

刑事诉讼中经验法则的运用机理及规范路径

运用于刑事诉讼中的经验法则根据来源、功能指向以及运用路径的不同,可以分为源于逻辑判断的经验法则与源于生活情理的经验法则、用于审查判断证据的经验法则与用于认定案件事实的经验法则、依附运用的经验法则与独立运用的经验法则。经验法则在实践中面临着显示度欠缺、盖然性程度模糊以及与个案适配度不彰等风险,阻滞了司法证明的精密化发展。经验法则应以高盖然性、亚规则性以及可视性为其内在属性,以事实推论为运用场域,以激活自由心证为内在使命。在遵循证据裁判原则的前提下,经验法则的运用应通过强化控辩双方的证成及证伪、落实裁判文书的说理及示明,推进其独立价值的实现。《刑事诉讼法》的修改应围绕经验法则“何处用”以及“如何用”的问题,加大经验法则的比重、细化经验法则的运用。

基于多元线路特征因素融合的电压暂降严重程度评估

现有电压暂降严重程度评估方法未充分考虑多元线路特征因素对输电线路故障概率的影响,评估结果存在较大误差。由此,文中提出了基于多元线路特征因素融合的电压暂降严重程度评估方法。首先,基于线路历史故障数据,采用关联规则量化多元线路特征因素对线路故障的影响程度进行研究。然后,通过改进D-S证据理论融合多元线路特征因素建立准确的线路年故障概率模型,并采用基于最大熵模型的故障点法评估节点的电压暂降量。最后,提出了一种同时考虑系统侧电压暂降严重程度和用户敏感设备耐受特性的综合电压暂降严重程度指标,用于评估节点电压暂降严重程度。基于实际电能质量监测数据进行验证,并与未充分考虑线路特征因素的评估案例进行比较,结果表明所提方法能有效提升电压暂降严重程度评估的准确性。

胸痹中医古籍证据的评价、推荐及辨证规律研究

目的:运用中医古籍证据评价方法对中医古籍中治疗胸痹的方剂证据进行系统评价和推荐,并总结其辨证规律。方法:文献来自第5版《中华医典》及中国中医科学院中医药信息研究所开发的“国医典藏”数据库。对1911年(包括1911年)以前治疗胸痹的古方进行收集、筛选,应用《中医古籍防治证据评价分级量表》(胸痹)进行评价与分级,用拟定的推荐标准进行证据推荐。结果:最终纳入155条治疗胸痹的中医古籍证据,其中31条证据被评价为高等级证据,65条证据被评为中等级证据,59条证据被评为低等级证据。遵循“以方测证”思维方法,可得胸痹的证型为寒凝心脉(34.19%)、气滞心脉(23.87%)、瘀血痹阻(16.13%)、痰浊凝滞(9.68%)、心阳不足(5.81%)、心气不足(4.52%)、心阴亏虚(3.87%)及心阳痹阻(1.94%)。源自《金匮要略》的人参汤、茯苓杏仁甘草汤、瓜蒌薤白半夏汤、枳实薤白桂枝汤、瓜蒌薤白白酒汤,《太平惠民和剂局方》的苏合香丸、失笑散,《正体类要》的归脾汤8条古籍证据进行强推荐,乌头赤石脂丸、丹参饮、血府逐瘀汤、橘枳姜汤4条古籍证据进行弱推荐,其他古籍证据暂不推荐。结论:《金匮要略》是治疗胸痹的经典古籍,具有完备的辨证论治体系;化痰法和活血法是治疗胸痹的基本治法,瓜蒌薤白三方、血府逐瘀汤等是治疗胸痹的重要方剂。

基于改进证据理论的冲突证据融合方法

为解决证据理论中Dempster组合规则融合高度冲突证据效果不佳的问题,提出一种同时考虑证据重要性与可靠性的综合权重生成方法和基于加权复数基本概率分配函数的证据融合方法。以提高证据融合结果的收敛性能和诊断精度为目标,建立相应的优化证据融合模型。实验结果表明,所提方法能够有效识别并处理证据冲突,克服证据加权融合过程中剩余信度被完全抛弃的问题,获得更好的融合结果和更快的收敛速度,提高诊断精度。

涉案资金分析报告定案证据转化路径探讨

当前经济犯罪案件中资金量日益庞大、资金流向越发复杂隐蔽,厘清涉案资金相关情况成为案件办理的关键一环,在此背景下,涉案资金分析报告在引导侦查、证明犯罪事实、提升诉讼效率等方面的作用愈发受到重视。但受限于非法定证据种类、无规范操作标准、无法定审查规则等原因,涉案资金分析报告作为定案证据的效力难以充分发挥。解决这一问题,可以坚持问题导向,从以审判为中心的诉讼制度改革下证据裁判原则对证据的要求出发,明确涉案资金分析报告虽暂不具备法定证据形式,但依然有可能作为定案证据发挥证据效能,路径是切实结合证明力和证据能力两个证据的基本要求进行有效转化。

中国式亲属拒证制度的法治路径研究

亲属拒证制度不应局限于庭审阶段的近亲属免于强制出庭作证。2012年《刑事诉讼法》增设的亲属免证制度既是对法治文化传统所蕴含的“容隐”观念的扬弃,也是对当下社会治理需要的回应。然而,不论是古代亲属拒证权从民间观念到法律权利的法律规制进程,还是曾经片面追究实体真实等思维藩篱下废除亲属拒证制度,既不符合限制自由以实现自由的形式法治,也不符合法律给予人行为指引的实质法治。当前局限于庭审阶段的亲属免证制度并未充分达成法治应有之义,依赖司法矫治而孤立社会自我规训,导致社会治理成本不断上升等问题。在《刑事诉讼法》新一轮修订背景下系统设计中国式亲属拒证制度,须建立在权属主体为亲属—被告人“双主体”的基础上,明确亲属拒证权适用案件范围的四种例外与内容范围的适度扩大,并通过修订《刑法》妨碍司法类犯罪中关于亲属的规定,以实现刑事实体法与程序法法秩序的统一。