Automatic semantic analysis of software requirements through machine learning and ontology approach

Nowadays, software requirements are still mainly analyzed manually, which has many drawbacks (such as a large amount of labor consumption, inefficiency, and even inaccuracy of the results). The problems are even worse in domain analysis scenarios because a large number of requirements from many users need to be analyzed. In this sense, automatic analysis of software requirements can bring benefits to software companies. For this purpose, we proposed an approach to automatically analyze software requirement specifications (SRSs) and extract the semantic information. In this approach, a machine learning and ontology based semantic role labeling (SRL) method was used. First of all, some common verbs were calculated from SRS documents in the E-commerce domain, and then semantic frames were designed for those verbs. Based on the frames, sentences from SRSs were selected and labeled manually, and the labeled sentences were used as training examples in the machine learning stage. Besides the training examples labeled with semantic roles, external ontology knowledge was used to relieve the data sparsity problem and obtain reliable results. Based on the SemCor and WordNet corpus, the senses of nouns and verbs were identified in a sequential manner through the K-nearest neighbor approach. Then the senses of the verbs were used to identify the frame types. After that, we trained the SRL labeling classifier with the maximum entropy method, in which we added some new features based on word sense, such as the hypernyms and hyponyms of the word senses in the ontology. Experimental results show that this new approach for automatic functional requirements analysis is effective.     

血清可溶性CD40配体对急性冠状动脉综合征的诊断

目的观察可溶性CD40配体(sCD40L)在急性冠状动脉综合征(ACS)、稳定型心绞痛及非冠心病患者血清中的变化,探讨其用于判断急性冠状动脉综合征的临床应用价值。方法选取我科2002年4月至2003年12月住院患者及部分随访患者共156例,其中急性冠状动脉综合征患者77例(包括急性心肌梗死患者37例,不稳定型心绞痛患者40例),稳定型心绞痛患者42例,非冠心病对照患者37例。应用ELISA法测定各组患者血清sCD40L水平并进行比较,ROC曲线分析sCD40L诊断急性冠状动脉综合征的临床价值。结果①急性冠状动脉综合征组患者血清sCD40L水平显著高于稳定型心绞痛患者和非冠心病患者(P<0.05),而急性冠状动脉综合征患者中急性心肌梗死和不稳定心绞痛患者之间没有显著性差异(P>0.05),稳定型心绞痛患者和非冠心病对照患者之间也没有显著性差异(P>0.05);②用sCD40L诊断急性冠状动脉综合征其ROC曲线下面积为0.773,灵敏度、特异度、准确率分别为82.8%、61.9%、85.7%。结论血清sCD40L水平升高代表着斑块的不稳定状态,对急性冠状动脉综合征的诊断有一定应用价值。     

不同治则方药对拟血管性痴呆鼠学习与记忆的作用

目的　探讨不同治则方药对拟血管性痴呆鼠学习与记忆能力的影响及其临床意义。方法　建立血管性痴呆模型 ,通过跳台试验测试其学习与记忆的能力并观测不同治则方药的作用。结果　用药组中健脑益智口服液组与涤痰汤组较金匮肾气丸组及桃红四物汤组能显著提高拟血管性痴呆鼠学习与记忆的能力 (P <0 .0 5 )。健脑益智口服液组与涤痰汤组之间无显著性差异 (P >0 .0 5 ) ,金匮肾气丸组与桃红四物汤组之间无显著性差异 (P>0 .0 5 )。结论　血管性痴呆的中医证侯可能以痰浊蒙蔽清窍为主 ,提示临床治疗血管性痴呆以涤痰开窍为主。     

螺旋桨低频宽带噪声影响参数研究与流—声多目标优化设计

文章以谱方法为理论基础,以条带法为数值求解方法,针对Sears力响应函数引入厚度修正,建立了螺旋桨低频宽带噪声理论预报方法.通过对比10叶模型螺旋桨水筒试验数据,验证了厚度修正的效果,厚度修正后总声级误差由2 dB减少至1.1 dB.文中利用厚度修正后的预报方法,从三个层次六个方面对影响螺旋桨低频宽带噪声的参数进行研究,并实现了流-声多目标优化设计:(1)单个螺旋桨影响参数灵敏度分析:①外半径型值对总声级影响较大,而内半径几乎没有影响.②利用Sobol灵敏度分析法对两个不同叶数螺旋桨的流场参数和螺旋桨参数进行研究发现:不同桨叶下各参数影响因子几乎一致,来流速度对于螺旋桨低频宽带总声级有最大贡献,约为30％的正效应,其次是湍流度约为22％的正效应,而湍流积分长度仅占7％的负效应.(2)单个螺旋桨流—声多目标优化设计研究:以NSGA-Ⅱ为优化算法,结合非定常面元法和低频宽带噪声预报方法,实现流-声多目标优化设计.(3)多个螺旋桨相对关系稳健性分析:对不同螺旋桨低频宽带噪声相对关系稳健性进行研究,分析湍流积分长度和湍流度变化的影响.该文的研究成果为下一步将低频宽带噪声纳入螺旋桨设计考核指标奠定了理论基础.     

Simulation of hydrodynamic performance of drag and double reverse propeller podded propulsors

The unsteady performance of drag and double reverse propeller podded propulsors in open water was numerically simulated using a computational fluid dynamics (CFD) method. A moving mesh method was used to more realistically simulate propulsor working conditions, and the thrust, torque, and lateral force coefficients of both propulsors were compared and analyzed. Forces acting on different parts of the propulsors along with the flow field distribution of steady and unsteady results at different advance coefficients were compared. Moreover, the change of the lateral force and the difference between the abovementioned two methods were mainly analyzed. It was shown that the thrust and torque results of both methods were similar, with the lateral force results having the highest deviation     

Study on collision between two ships using selected parameters in collision simulation

In the present analysis, several parameters used in a numerical simulation are investigated in an integrated study to obtain their influence on the process and results of this simulation. The parameters studied are element formulation, friction coefficient, and material model. Numerical simulations using the non-linear finite element method are conducted to produce virtual experimental data for several collision scenarios. Pattern and size damages caused by collision in a real accident case are assumed as real experimental data, and these are used to validate the method. The element model study performed indicates that the Belytschko-Tsay element formulation should be recommended for use in virtual experiments. It is recommended that the real value of the friction coefficient for materials involved is applied in simulations. For the study of the material model, the application of materials with high yield strength is recommended for use in the side hull structure.     

Epistemic-based investigation of the probability of hazard scenarios using Bayesian network for the lifting operation of floating objects

Owing to the increase in unprecedented accidents with new root causes in almost all operational areas, the importance of risk management has dramatically risen. Risk assessment, one of the most significant aspects of risk management, has a substantial impact on the system-safety level of organizations, industries, and operations. If the causes of all kinds of failure and the interactions between them are considered, effective risk assessment can be highly accurate. A combination of traditional risk assessment approaches and modern scientific probability methods can help in realizing better quantitative risk assessment methods. Most researchers face the problem of minimal field data with respect to the probability and frequency of each failure. Because of this limitation in the availability of epistemic knowledge, it is important to conduct epistemic estimations by applying the Bayesian theory for identifying plausible outcomes. In this paper, we propose an algorithm and demonstrate its application in a case study for a light-weight lifting operation in the Persian Gulf of Iran. First, we identify potential accident scenarios and present them in an event tree format. Next, excluding human error, we use the event tree to roughly estimate the prior probability of other hazard-promoting factors using a minimal amount of field data. We then use the Success Likelihood Index Method (SLIM) to calculate the probability of human error. On the basis of the proposed event tree, we use the Bayesian network of the provided scenarios to compensate for the lack of data. Finally, we determine the resulting probability of each event based on its evidence in the epistemic estimation format by building on two Bayesian network types: the probability of hazard promotion factors and the Bayesian theory. The study results indicate that despite the lack of available information on the operation of floating objects, a satisfactory result can be achieved using epistemic data.     

CFD-based method of determining form factor <Emphasis Type="Italic">k</Emphasis> for different ship types and different drafts

The value of form factor k at different drafts is important in predicting full-scale total resistance and speed for different types of ships. In the ITTC community, most organizations predict form factor k using a low-speed model test. However, this method is problematic for ships with bulbous bows and transom. In this article, a Computational Fluid Dynamics (CFD)-based method is introduced to obtain k for different type of ships at different drafts, and a comparison is made between the CFD method and the model test. The results show that the CFD method produces reasonable k values. A grid generating method and turbulence model are briefly discussed in the context of obtaining a consistent k using CFD.     

A simulation-based probabilistic design method for arctic sea transport systems

When designing an arctic cargo ship, it is necessary to consider multiple stochastic factors. This paper evaluates the merits of a simulation-based probabilistic design method specifically developed to deal with this challenge. The outcome of the paper indicates that the incorporation of simulations and probabilistic design parameters into the design process enables more informed design decisions. For instance, it enables the assessment of the stochastic transport capacity of an arctic ship, as well as of its long-term ice exposure that can be used to determine an appropriate level of ice-strengthening. The outcome of the paper also indicates that significant gains in transport system cost-efficiency can be obtained by extending the boundaries of the design task beyond the individual vessel. In the case of industrial shipping, this allows for instance the consideration of port-based cargo storage facilities allowing for temporary shortages in transport capacity and thus a reduction in the required fleet size / ship capacity.     

Experimental study on reflection coefficient of curved perforated plate

A set of experiments is carried out in a towing tank to study the effects of the curvature of perforated plates on the wave reflection coefficient (C _r ). The curvature of a perforated plate can be changed by rotating a reference perforated plate aboutits origin according to the parabolic equation y=?x ². A plunger-type wave maker is used to generate regular waves. The reflection coefficients are calculated using Goda and Suzuki’s (1976) method. The results are compared with those of vertical or sloped passive wave absorbers. The comparison shows that a perforated plate with a curved profile is highly efficient in terms of reducing the wave reflection coefficient. A correlation is established to estimate the reflection coefficient of curved perforated plates as a function of both flow and geometry characteristics.