基于Reason模型的SIF-Q260型电子小肠镜故障原因分析

根据武汉大学中南医院内窥镜中心SIF-Q260型小肠镜故障率高且维修成本高的情况,应用Reason模型,从环境影响、不安全监督、不安全行为前兆及不安全行为4个层面分析造成SIF-Q260小肠镜故障的原因,针对各个层面故障原因,从定期培训以规范内窥镜的洗消及使用、设置专人管理内窥镜并定期对内窥镜使用洗消的规范性进行监督及评价、完善内窥镜监管系统3方面拟定改进措施,堵住系统“漏洞”,为内窥镜质量控制措施的制定提供依据,可预防和减少内窥镜故障的发生。

Progress in Neural NLP:Modeling,Learning,and Reasoning

Natural language processing(NLP)is a subfield of artificial intelligence that focuses on enabling computers to understand and process human languages.In the last five years,we have witnessed the rapid development of NLP in tasks such as machine translation,question-answering,and machine reading comprehension based on deep learning and an enormous volume of annotated and unannotated data.In this paper,we will review the latest progress in the neural network-based NLP framework(neural NLP)from three perspectives:modeling,learning,and reasoning.In the modeling section,we will describe several fundamental neural network-based modeling paradigms,such as word embedding,sentence embedding,and sequence-to-sequence modeling,which are widely used in modern NLP engines.In the learning section,we will introduce widely used learning methods for NLP models,including supervised,semi-supervised,and unsupervised learning;multitask learning;transfer learning;and active learning.We view reasoning as a new and exciting direction for neural NLP,but it has yet to be well addressed.In the reasoning section,we will review reasoning mechanisms,including the knowledge,existing non-neural inference methods,and new neural inference methods.We emphasize the importance of reasoning in this paper because it is important for building interpretable and knowledgedriven neural NLP models to handle complex tasks.At the end of this paper,we will briefly outline our thoughts on the future directions of neural NLP.

Model for Bidding and Tendering with Bill of Quantities Based on Bid-Winning Estimate at Reasonable Low Price

The possibility and rationality of introducing an bid-winning estimate based on a reasonable low price into construction bidding mode with bill of quantities were analyzed by setting up a model for bidding and tendering, and the functions of the estimate of reasonable low price in the bidding were revealed. On this basis, a new bidding mode of the project with bill of quantities was pro- posed. The application of the new mode will be advantageous to the promotion of the bill of quantities in China.

A Knowledge-reuse Based Intelligent Reasoning Model for Worsted Process Optimization

The textile process planning is a knowledge reuse process in nature, which depends on the expert’s knowledge and experience. It seems to be very difficult to build up an integral mathematical model to optimize hundreds of the processing parameters. In fact, the existing process cases which were recorded to ensure the ability to trace production steps can also be used to optimize the process itself. This paper presents a novel knowledge-reuse based hybrid intelligent reasoning model (HIRM) for worsted process optimization. The model architecture and reasoning mechanism are respectively described. An applied case with HIRM is given to demonstrate that the best process decision can be made, and important processing parameters such as for raw material optimized.

CONVERSE REASONING FOR FULL DEPRESSION-FEATURE MODEL AND PROCESS

A new approach, namely, 'defining protrusion-feature withdepression-parameter' is advanced, which focuses on the shortcomings of protrusion-featurealteration method; The full depression-feature model is built up, and a basic converse reasoningiterative algorithm for machining process is given. The detailed examination has been implemented onthe feature-based modeling system for light industry product (QJFMS) and the converse reasoning onfixture-based machining process is achieved.

Flatness predictive model based on T-S cloud reasoning network implemented by DSP

The accuracy of present flatness predictive method is limited and it just belongs to software simulation. In order to improve it, a novel flatness predictive model via T-S cloud reasoning network implemented by digital signal processor(DSP) is proposed. First, the combination of genetic algorithm(GA) and simulated annealing algorithm(SAA) is put forward, called GA-SA algorithm, which can make full use of the global search ability of GA and local search ability of SA. Later, based on T-S cloud reasoning neural network, flatness predictive model is designed in DSP. And it is applied to 900 HC reversible cold rolling mill. Experimental results demonstrate that the flatness predictive model via T-S cloud reasoning network can run on the hardware DSP TMS320 F2812 with high accuracy and robustness by using GA-SA algorithm to optimize the model parameter.

Universal triple I fuzzy reasoning algorithm of function model based on quotient space

Aiming at the deficiencies of analysis capacity from different levels and fuzzy treating method in product function modeling of conceptual design, the theory of quotient space and universal triple I fuzzy reasoning method are introduced, and then the function modeling algorithm based on the universal triple I fuzzy reasoning method is proposed. Firstly, the product function granular model based on the quotient space theory is built, with its function granular representation and computing rules defined at the same time. Secondly, in order to quickly achieve function granular model from function requirement, the function modeling method based on universal triple I fuzzy reasoning is put forward. Within the fuzzy reasoning of universal triple I method, the small-distance-activating method is proposed as the kernel of fuzzy reasoning; how to change function requirements to fuzzy ones, fuzzy computing methods, and strategy of fuzzy reasoning are respectively investigated as well; the function modeling algorithm based on the universal triple I fuzzy reasoning method is achieved. Lastly, the validity of the function granular model and function modeling algorithm is validated. Through our method, the reasonable function granular model can be quickly achieved from function requirements, and the fuzzy character of conceptual design can be well handled, which greatly improves conceptual design.

Bayesian Network Model of Product Information Diffusion and Reasoning of Influence

Information diffusion on social media has become a key strategy in people’s daily interactions. This paper studies consumers’ participation in the product information diffusion, and analyzes the complexity of information diffusion which is affected by many factors. Prior investigations of information diffusion have primarily focused on the composition of diffusion networks with independent factors and the intricacy of the process has not been completely evaluated. The majority of prior investigations have focused on strategies and the moving forces in social media processes and the determination of influential seed nodes, with few evaluations conducted about the factors affecting consumers’ choices in information diffusion. In this study, a Bayesian network model of product information diffusion was created to examine the links between factors and consumer deportment. It revealed how those factors had an impact on each other and on consumer deportment choice. The innovation of the thesis is reflected in the exploration and analysis of the specific communication path of product information diffusion, which provides a better marketing idea and practical method for the development of mobile e-commerce. The research findings can help identify the quantitative relationships between the factors affecting the process of product information diffusion and user behavior.

变电运行人因事故分析的拟REASON模型

REASON模型是航空事故调查与分析的理论模型之一,引入进来并建立了变电运行人因事故分析的拟REASON模型,提出了事故链上的六个要素,包括环境、信息、组织、危险点、监护人、操作人。分别针对这六个要素提出防止变电运行人因事故发生的具体措施,并指出各方面安全措施的协调是追求"事故零目标"的必然要求。所提模型对变电运行人因事故分析具有重要的指导意义。

基于FTA-Reason的施工作业高空坠落风险预控研究

为了对施工作业中高空坠落风险进行预控,采用故障树法对施工作业高空坠落事故进行了故障树的构建、分析,继而通过对经典Reason模型进行改造,建立了施工作业高空坠落事故的预控模型,包括组织因素、安全监督、操作条件、安全行为的前提以及安全行为5个防御层次。在风险预控的过程中,通过运用建立的施工作业高空坠落风险模型,可以对施工作业中的高空坠落风险进行针对性地预控,为施工安全风险管理提供参考。

Reason模型在空中交通管制中的应用

指出了Reason模型及人的因素分析与分类系统的不足,提出对Reason模型进行修正的思路;结合中国民航业的实际情况,构建了空中交通管制不安全事件的分析框架;对防御系统失效、不安全行为、不安全行为的条件、管理失效4个层次的缺陷进行了论述,并给予详细的实证分析。研究有助于调查分析民航空管行业不安全事件中的原因以及为空管安全管理中的危险识别提供依据。

基于Reason模型的航空器事故调查分析软件设计

通过对航空器事故进行分析与研究,从而提出相应的改进措施,对于减少飞行事故、保障飞行安全具有重要意义。在现有航空器事故分析的基础上,提出了基于Reason模型的航空器事故调查分析软件设计。在分析Reason模型基本概念的基础上,详细介绍了该软件的系统结构、软件的界面和相应的操作步骤与方法,并结合实际的案例介绍了该软件在分析航空器事故调查方面的优势。该软件对于调查分析民航业不安全事件中的人为因素具有一定的借鉴作用。

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.

REASON模型在航空维修事故调查中的应用

分析和运用Reason模型,从系统安全角度对一起典型航空维修事故案例,按照事件链因果逻辑展开调查分析,构建出事故致因分析模型。

食品安全事件的影响因素及治理路径——基于REASON模型的QCA分析

本文基于REASON模型,构造“监管主体、监管过程、监管环境、监管对象”的监管闭环,探寻食品安全事件发生的逻辑链条。首先,建立“环节分布—责任主体”的组合分析框架,从9989个食品安全事件统计分析入手,提炼出8个高发节点。其次,筛选出60个案例进行模糊集定性比较分析,得到8个食品安全事件的影响因素——日常监管、多元主体参与、检测水平、质量控制、宣传教育、风险控制、企业或个人行为、环节分布安全隐患,验证了“不安全的行为”是食品安全事件的直接因素。再次,通过条件变量的组合探究路径,从影响因素及监管的维度入手,根据“行为—原因—实践”的逻辑链条总结食品安全治理的5条路径,回答“如何监管”及“监管谁”的问题。

基于Reason模型的医疗器械不良事件的影响因素研究

目的探讨在用医疗器械不良事件的影响因素。方法基于文献分析法,在CNKI、万方等数据库检索相关文献273篇,并采用其中74篇作为证据文献;应用Reason模型,从组织影响、不安全监督、不安全的行为前提和不安全的行为方面分析不良事件成因。结果结合证据文献的案例分析,对学者分析的导致医疗器械不良事件的原因进行归纳,并构建了医疗器械不良事件影响因素的Reason致因模型。结论医疗器械不良事件的影响因素映射为产品在组织管理、临床试验监管、产品设计、物流管理和临床使用环节中出现的"漏洞"中的隐形失效,应该加强医疗器械上市前可靠性要求和临床使用风险管控。

Reason模型在肝癌介入术病人围术期护理安全管理中的应用分析

目的:探讨Reason模型在肝癌介入术病人围术期护理安全管理中的应用效果。方法:应用Reason模型对2020年6月-2021年6月22例次肝癌介入术病人围术期护理安全不良事件进行回顾性分析,从不安全行为、不安全性前提、不安全监督、组织管理4个方面分析原因并制定解决方案,比较方案实施前后护理安全不良事件发生率。结果:实施Reason模型后肝癌介入术病人围术期护理安全不良事件发生率为0.135%,显著低于实施前的0.586%(P<0.05)。结论:基于Reason模型的管理有利于深度挖掘护理管理问题,降低护理安全不良事件发生率,有助于改变医护人员对不良事件上报的态度,保障病人安全。

基于Reason模型给药错误不良个案分析

由于护生在临床实习阶段缺乏经验,与护生相关的护理不良事件频频发生。Reason提出的组织事故模型指出,在不良事件中,虽有一部分来自个人的疏忽或技术的不良,但是更大部分来自系统、程序、工作环境中的潜藏失误。本文运用Reason模型,对一例护生临床实习期间经历的护理给药错误不良事件进行分析,寻找出事件背后潜在的环境与组织漏洞,并提出相关对策,以避免类似事件再次发生。

基于Reason模型的精神科护理不良事件分析及对策探讨

目的运用Reason模型分析医院护理不良事件发生的原因,提出相应的改进措施及管理对策。方法应用Reason模型对本院2016年—2018年上报的118例护理不良事件进行回顾性分析。结果118例不良事件中,不良事件居前3位的依次为患者跌倒(44.07%)、患者冲动伤人(24.58%)、自伤(10.17%);Ⅲ、Ⅳ级占不良事件的74.58%;白班期间不良事件发生频率最高(45.76%),其次为大夜班(27.97%);≤5年工作年限的护士与66.10%的不良事件有关,其中83.33%的Ⅱ级以上不良事件与≤5年工作年限的护士相关。结论医院护理不良事件的发生既有护理人员因素、患者身体因素等,又有时间特点及系统管理等。护理管理者应在完善精神科护理制度流程的基础上,不断加强重点人群的培训,提供安全的工作环境,最大限度地避免或降低护理不良事件的发生,保障患者安全。

Nitrogen Management Evaluated by Models Combined with GIS-A Case Study of Jiangsu Croplands,China,in 2000

The objective of this study is to provide scientific guidance for optimizing agricultural field nitrogen management that is based on the evaluation of current nitrogen application practice in Jiangsu Province, China, in 2000. The agricultural nitrogen models, consist of the soil mineralization model, the organic manure nitrogen releasing model, and the nitrogenous fertilizer use efficiency model. These models combined with the geographic information system technique were used to describe the spatial variability of nitrogen released from soil and organic manure and to identify its contributing factors. The comparison of the nitrogen fertilizer amount required by croplands, which was simulated by the models with the actual nitrogen fertilizer applied rate, was used to evaluate the current nitrogen application. The results showed that nitrogen was excessively applied in 71.8% croplands, given that the actual crop yield was desired. The excessive nitrogen amounted to 760 kiloton, accounting for 41.5% of the total nitrogen applied. Given that the actual highest yield was desired, nitrogen was reduced in 64.3% croplands. The total shortage of nitrogen was about 800 kiloton. Low use efficiency of nitrogen fertilizer was found in Taihu Lake area, Nanjing-Zhenjiang hilly area, and Xuzhou area, whereas the east beach area of Jiangsu showed an obvious deficiency of nitrogen fertilizer inputs. A balance of nitrogen fertilizer in Jiangsu croplands between excessive and deficient application areas would greatly benefit economic and environmental advantages.