Statistical data analyses to elucidate the causes and improve the countermeasures for preventing train accidents in Japan

We investigate train accident data in Japan to elucidate the causes and improve the countermeasures for reducing the number of train accidents. We deal with statistical data on train accidents in the last 15 years, including frequency, types such as derailment and crash, causes and consequences. We review the historical trend of train accidents by applying a statistical modeling approach dealing with both serious accident data and total number of accidents. Probability distributions for explaining this train accident data are shown. We show the results of quantitative data analyses on the train accidents, that occurred at the ground‐level crossing and the relationship among utility type of railway company, equipment at the crossing and consequences of the accidents. Probabilistic mathematical models are used in the analyses. Finally, we try to evaluate the effectiveness of the countermeasures for preventing train accidents.     

带结构风险最小化的最优区间回归模型辨识

针对来自模型结构、参数以及测量数据的不确定性等因素,传统的辨识方法获取的是确定性数学模型的点输出,其鲁棒性差,易受外界干扰.因此,采用区间输出比点输出更易于实际问题的研究.基于复杂系统的不确定性测量数据以及系统参数的不确定性,提出了最优区间回归模型辨识的一种新方法,该方法将逼近误差的L∞范数思想与结构风险最小化理论相结合,建立求解区间模型的最优化问题,应用线性规划独立求解区间模型的上界和下界模型.该方法在保证模型辨识精度的同时,其泛化性能得到进一步提高.实验分析表明,提出的方法对来自噪声以及参数不确定性的数据,可以从区间模型的辨识精度和泛化性能之间取其平衡.     

Statistical safety analysis of maintenance management process of excavator units

Within this paper, the process of statistical safety analysis has been presented, which involves the following steps: formulation of basic principles of statistical safety analysis, initial events analysis, accident sceneries progress analysis, risk calculation, and risk calculation results analysis. On this basis, it has been concluded that the bucket wheel excavator SRs 1200×24/4×0(400kW)+VR safety criteria is the mechanism for the hoist of rotor s arrow failure modes, because in that case whole bucket wh...     

软件项目风险应对措施优选的区间模型及其算法

针对软件项目风险应对计划中风险应对措施的优选问题,提出一种区间优化模型.该模型基于项目视角,以风险应对成本和风险水平最小化为目标,结合考虑风险管理者的风险偏好,选出满意的风险应对措施组合.考虑到风险概率和风险损失等参数难以给出精确值,模型采用区间数来表示风险概率和风险损失信息.针对模型的求解,利用区间数距离定义和区间数排序规则,给出一种迭代求解算法.案例分析表明了该模型和算法的有效性和可操作性.     

基于设备可靠性分析的最优投资策略

定义了设备可靠性的概念,给出了设备可靠性的评价模型,对化工设备在固定时间内运行的可靠性进行了分析,提出了设备投资的最优化策略的数学模型和求解策略。结合实例给出了如何在满足系统可靠性要求的前提下实现设备最优投资的策略,并计算出了所需备用设备的最小数量。结果表明此策略可以广泛应用于工程实践中。     

Sensitivity analysis and comparison of algorithms in preventive maintenance and replacement scheduling optimization models

In this research, new optimization models are developed to determine the optimal preventive maintenance and replacement schedules in repairable and maintainable systems. The objective is to determine a plan of actions for each component in the system while minimizing the total cost and maximizing overall system reliability over the planning horizon. Experimental results of a sensitivity analysis on the optimization models are presented and evaluated. These experiments investigate the effect of the parameters on the structure of optimal preventive maintenance and replacement schedules in multi-component systems. Two factorial design experiments based on the cost associated with maintenance and replacement activities and reliability characteristic parameters are constructed and analyzed. In addition, a comprehensive experiment is designed to analyze and compare the efficiency and accuracy of the exact and metaheuristic algorithms.     

Software maintenance: An approach to impact analysis of objects change

The maintenance of a software system requires a tool for impact analysis and the propagation of change. This paper presents a knowledge-based model for both. This model is generic because it is not based on any language or design method. Therefore, it can be applied on the basis of ‘problem’ to be solved. It also captures four life-cycle phases: requirement, specification, design and programming. We also provide a domain-specific view that allows the dependency analysis of fine-grain objects. Two kinds of dependencies are identified: inter-phase dependencies, these are dependency relations between the objects of the one phase and another; and intra-phase dependencies, these are dependency relations between the objects of the same phase. In order to validate this model, we also present a prototype based on two life-cycle phases: design and programming.     

一种改进的PDRR模型

PDRR模型是一个最常用的网络安全模型，该模型把网络体系结构划分为防护、检测、响应、恢复四个部分。文章通过论述PDRR模型所采用的网络安全技术，提出了对该模型的改进——以风险分析为核心的安全模型。     

Fuzzy risk analysis of flood disasters based on diffused-interior-outer-set model

Floods are indeed one of the most serious natural hazards for human societies, especially in China. In this paper, we firstly introduce the interior-outer-set model (IOSM) based on information diffusion theory in detail. Then taking consideration its deficiencies, we represent the diffused-interior-outer-set model (DIOSM) to obtain the possibility-probability distribution (PPD). Based on the PPD, we analyze and calculate the risk results. To illustrate the procedure of the proposed method, we apply DIOSM to describe the flood disaster risk quantitatively in China by using statistical data respectively, such as the time of floods, the number of the deaths as well as the economic losses each year from 1990 to 2009. The outcomes of this research offer new insights and moreover new possibility to carry out an efficient way for various future flood disaster prevention and mitigation.     

Using the BCD model for risk analysis: An influence diagram based approach

In this paper, we are interested in addressing risk analysis. We propose an influence diagram-based approach that focuses on a Benefit, Cost, Deficit (BCD) model. The BCD model is proposed for studying the intentional deviant behaviors of human operators in a system. In this model, the consequences of human actions are analyzed with respect to three parameters: benefit, cost and deficit. Our approach aims to expand the BCD model by integrating factors, such as those related to the organization of the system in question, that influence human operator actions. In addition, the approach considers multiple criteria that are related, for example, to safety and productivity. To build a model that evaluates the risk induced by human actions in a system and analyzes the impact of the different factors, we use influence diagrams. Influence diagrams are probabilistic graphical models that can deal with uncertainty and with incomplete and imprecise information. Influence diagrams also represent the interdependencies between the different variables of the studied problem. In addition, contrary to Bayesian networks, influence diagrams can rank a set of actions by providing information on which action carries the greatest risk or the most benefits. We applied this approach to a case study of an industrial rotary press, but it can also be used in other problems and sectors.     

基于指标相关性的网络运维质量评估模型

传统网络运维评估方法存在两方面的问题：一是在指标选取、权重指定等关键步骤过于依赖领域专家经验,难以得到精确全面的评估结果;二是通信设备用户数量不断增加带来了海量的数据,数据又来自多个厂家以及多种设备,传统方法处理此类海量异构数据的效率较低。为了解决这些问题,提出基于指标间互相关性的指标选取方法。该方法着眼于评估过程中指标选取步骤,通过比较指标数据序列间的相关性强弱,对原始指标集进行分类,在各个簇中选择代表性指标完成关键指标体系的构建;另外,结合无人工参与的数据处理方法、权重确定方法建立了网络运维质量评估模型。在实验中,所提方法选取的指标对人工指标的覆盖率为72.2%,并且比人工指标的信息重叠率少31%。所提方法能够有效减少人力参与,且评估结果对告警有较好的预测准确率。     

银行资产流动性模型及预测和优化控制

根据银行资产量、偿付期信息及其相互关系建立了分布参数模型，刻画了银行资产流动性的动态规律，提出了解决流动性信息统计因费时、费力、滞后期长而不具实用价值问题的一种方法。在考虑经济波动对银行资产流动性影响的情况下，利用银行资产的分布参数模型进行了资产量、资产收益(或成本)和收益风险的预测，并在动态地平衡收益与风险的基础上探讨了资产流动性结构的优化控制。     

Infinite horizon cancer treatment model with isoperimetrical constraint: existence of optimal solutions and numerical analysis

In this paper, a class of infinite horizon optimal control problems with a mixed control-state isoperimetrical constraint, also interpreted as a budget constraint, is considered. The underlying dynamics is assumed to be affine-linear in control. The crucial idea which is followed in this paper is the choice of a weighted Sobolev space as the state space. For this class of problems, we establish an existence result and apply it to a bilinear model of optimal cancer treatment with an isoperimetrical constraint including the overall amount of drugs used during the whole therapy horizon. A numerical analysis of this model is provided by means of open source software package OCMat, which implements a continuation method for solving discounted infinite horizon optimal control problems.     

An analysis of the equilibrium of migration models for biogeography-based optimization

Motivated by the migration mechanisms of ecosystems, various extensions to biogeography-based optimization (BBO) are proposed here. As a global optimization method, BBO is an original algorithm based on the mathematical model of organism distribution in biological systems. BBO is an evolutionary process that achieves information sharing by biogeography-based migration operators. In BBO, habitats represent candidate problem solutions, and species migration represents the sharing of features between candidate solutions according to the fitness of the habitats. This paper generalizes equilibrium species count results in biogeography theory, explores the behavior of six different migration models in BBO, and investigates performance through 23 benchmark functions with a wide range of dimensions and diverse complexities. The performance study shows that sinusoidal migration curves provide the best performance among the six different models that we explored. In addition, comparison with other biology-based optimization algorithms is investigated, and the influence of the population size, problem dimension, mutation rate, and maximum migration rate of BBO are also studied.     

An empirical study on the implementation and evaluation of a goal-driven software development risk management model

ContextBuilding a quality software product in the shortest possible time to satisfy the global market demand gives an enterprise a competitive advantage. However, uncertainties and risks exist at every stage of a software development project. These can have an extremely high influence on the success of the final software product. Early risk management practice is effective to manage such risks and contributes effectively towards the project success.ObjectiveDespite risk management approaches, a detailed guideline that explains where to integrate risk management activities into the project is still missing. Little effort has been directed towards the evaluation of the overall impact of a risk management method. We present a Goal-driven Software Development Risk Management Model (GSRM) and its explicit integration into the requirements engineering phase and an empirical investigation result of applying GSRM into a project.MethodWe combine the case study method with action research so that the results from the case study directly contribute to manage the studied project risks and to identify ways to improve the proposed methodology. The data is collected from multiple sources and analysed both in a qualitative and quantitative way.ResultsWhen risk factors are beyond the control of the project manager and project environment, it is difficult to control these risks. The project scope affects all the dimensions of risk. GSRM is a reasonable risk management method that can be employed in an industrial context. The study results have been compared against other study results in order to generalise findings and identify contextual factors.ConclusionA formal early stage risk management practice provides early warning related to the problems that exists in a project, and it contributes to the overall project success. It is not necessary to always consider budget and schedule constraints as top priority. There exist issues such as requirements, change management, and user satisfaction which can influence these constraints.     

An application for the fracture characterisation of quasi-brittle materials taking into account fracture process zone influence

The paper introduces a Java application programmed for the advanced determination of the fracture characteristics of silicate-based materials failing in a quasi-brittle manner. The tool reconstructs the progress of a quasi-brittle fracture from the measured load–displacement curve and the knowledge of basic mechanical properties of the material. The main contribution of the proposed approach is that it takes the characteristics of the Fracture Process Zone (FPZ, particularly its extent, i.e. its size and shape) evolving at the tip of the propagating crack during the failure process into account and incorporates them into the fracture-mechanical parameter evaluation procedure(s). This approach is expected to substantially diminish the influence of the test specimen’s size/shape and the test geometry on the values of the parameters of nonlinear fracture models determined from the records of fracture tests on laboratory specimens. The application implements a developed technique for estimation of the size and shape of the FPZ. The technique is based on an amalgamation of several modelling concepts dealing with the failure of structural materials, i.e. multi-parameter linear elastic fracture mechanics, classical nonlinear fracture models for concrete (equivalent elastic crack and cohesive crack models), and the plasticity approach. The knowledge of the FPZ’s extent is employed for the relation of a part of the entire work of fracture to its characteristics within the presented approach. The verification and validation of the developed technique is performed via numerical simulations using the authors’ own computational code based on physical discretization of continuum and selected sets of experimental evidence published in the literature. Reasonable agreement is observed between the outputs of the presented semi-analytical technique and both the simulation results and the experimental data.     

Theory of planning behavior (TPB) and customer satisfaction in the continued use of e-service: An integrated model

This study has devoted much effort to developing an integrated model designed to predict and explain an individual’s continued use of online services based on the concepts of the expectation disconfirmation model and the theory of planned behavior. Empirical data was collected from a field survey of Cyber University System (CUS) users to verify the fit of the hypothetical model. The measurement model indicates the theoretical constructs have adequate reliability and validity while the structured equation model is illustrated as having a high model fit for empirical data. Study’s findings show that a customer’s behavioral intention towards e-service continuance is mainly determined by customer satisfaction and additionally affected by perceived usefulness and subjective norm. Generally speaking, the integrated model can fully reflect the spirit of the expectation disconfirmation model and take advantage of planned behavior theory. After consideration of the impact of systemic features, personal characteristics, and social influence on customer behavior, the integrated model had a better explanatory advantage than other EDM-based models proposed in prior research.     

An analysis of the length of hospital stay for cataract patients in Japan using the discrete-type proportional hazard model

We analyze the length of hospital stays of patients hospitalized for cataract and related diseases (Diagnosis Related Groups (DRG) 2041) in Japan, utilizing the data pertaining to 3436 patients on whom one-eye lens operations are performed. We use the discrete-type proportional hazard model to analyze variables that may affect the length of stay.     

Global sensitivity analysis of yield output from the water productivity model

This study includes a global sensitivity analysis of the water productivity model AquaCrop. The study rationale consisted in a comprehensive evaluation of the model and the formulation of guidelines for model simplification and efficient calibration. The global analysis comprehended a Morris screening followed by a variance-based Extended Fourier Amplitude Sensitivity Test (EFAST) under diverse environmental conditions for maize, winter wheat and rice. The analysis involved twenty-two different climate-crop-soil-meteorology combinations. The main objectives were to distinguish the model's influential and non-influential parameters, and to examine the yield output sensitivity. For the AquaCrop model, a number of non-influential parameters could be identified. Making these parameters fixed would be a step towards model simplification. Also, a list of influential parameters was identified. Despite the dependence of parameter ranking on environmental conditions, guiding principles for priority parameters were formulated for calibration in diverse conditions, valuable to model users. For this model that focuses on modelling yield response to water, parameters describing crop responses to water stress were not often among those showing highest sensitivity. Instead, particular root and soil parameters, relevant in the determination of water availability, were influential under various conditions and merit attention during calibration. The considerations made in this study about sensitivity analysis method (Morris vs. EFAST), prior parameter ranges, target functions and ranking variation according to environmental conditions can be extrapolated to other conditions and models, if done with the necessary precaution.