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.     

Dynamic modeling and active control of a strap-on launch vehicle

Dynamic modeling and active control of a strap-on launch vehicle are studied in this paper. In the dynamic modeling, the double-compatible free-interface modal synthesis method is used to establish dynamic model of the system, and its model precision is compared with those of finite element method(FEM), fixedinterface modal synthesis method and free-interface modal synthesis method. In the active control, the swing angle of rocket motor is used as design variable, and the control law design based on the model of mass center motion is adopted to validate the system. Simulation results indicate that the double-compatible model synthesis method can properly approximate the FEM which is used as the benchmark solution, and the model precision of the double-compatible modal synthesis method is obviously higher than those of the fixed-interface and freeinterface modal synthesis methods. Based on the control law design, the deflection of mass center of the launch vehicle is very small.     

Online fault diagnosis of modern process industry system based on color-spectrum

This paper proposes a new method to diagnose the system fault of the process industry based on the monitor data set of distributed control system (DCS). Firstly, it defines a homeomorphism product space named color phase space which is a Cartesian product of two-dimensional Euclidean space and three-dimensional color phase space. Secondly, it maps the DCS data to the color phase space in order to get a system color-spectrum which displays the inherent relationship of the whole system. Then, it diagnoses the system fault by observing the color change on the color-spectrum depending on the physiological characteristics that human’s eyes are more sensitive for the color change than data change.     

The ambivalence of ridesharing

Ridesharing is quite a popular topic of discussion among transport authority personnel. It is perceived to be a viable alternative to classical modes of transportation, and receives a great deal of political support from transport planners. However, not much objective information is available on ridesharing behaviors. We use travel survey data to study the evolution of the ridesharing market in an urban area. Our study is based on data from four large-scale OD surveys conducted in the Greater Montreal Area (1987, 1993, 1998 and 2003). In the latest survey conducted in Montreal, car passengers were asked to identify the driver who gave them the opportunity to travel in this way. Their answers were classified according to the type of driver; for instance, a member of their household, a neighbor or a co-worker. We use this information to calibrate a model matching car passengers and car drivers belonging to the same household. This will be referred to as IHHR (intra-household ridesharing). Preliminary results reveal that approximately 70% of all trips made by car passengers are the result of IHHR. Furthermore, around 15% of those trips are questionable, in that they were exclusively generated for another individual’s purposes, consequently generating an additional trip for the journey back home. Moreover, this percentage increased over time. Objective data regarding ridesharing and its evolution in an urban area will undoubtedly help decision makers gain a clearer profile of this means of travel and help to realign attitudes on the issue.

The role of paratransit: some reflections based on the experience of residents’ coach services in Hong Kong

Paratransit refers to urban transport services “somewhere between private passenger transport and conventional public transport in terms of cost and quality of service” [Rimmer (1980), Paratransit: A commentary. Environ. Plan. A 12, 937–944]. Since the 1980s, a new form of paratransit—residents’ coach, which provides exclusive transport services to residents living in private housing estates—has emerged in Hong Kong. What was the background underlying the emergence and subsequent growth of residents’ coach services? Also, what was the role of residents’ coach in the public transport system of Hong Kong? With the completion of more railway extensions, should residents’ coach services be replaced? If so, what are the potential impacts on people’s life? This paper addresses the above research questions through a large-scale questionnaire survey that examined not only people’s modal choice but also their residential choice, socio-economic background and attitudes. The findings suggest that transport policy makers should pay more attention to examine new forms of paratransit and the ways of integrating them into the overall public transport system, both spatially and temporally. It is only through the development of an efficient and multi-modal transport system can the maximum potential of paratransit in filling the transport gap between conventional mass transit and private cars be realized.     

Experimental study of lightweight expanded polystyrene aggregate concrete containing silica fume and polypropylene fibers

We developed a new structural lightweight concrete by totally or partially replacing coarse and fine aggregates in high performance concrete by expanded polystyrene (EPS) beads. In this work,the sizes of EPS bead were 1.0,2.5 and 6.3 mm. Lightweight EPS concretes with a wide range of concrete densities and compressive strengths were successfully developed. Compressive strength,splitting tensile strength,shrinkage,and water absorption were examined. Additionally,fine silica fume (SF) and polypropylene (PP) f...     

Method for workspace calculation of 6R serial manipulator based on surface enveloping and overlaying

Aiming at the workspace calculation problem of multi-joint serial manipulators, a surface enveloping and overlaying (SEO) method is presented to identify and visualize the manipulator workspace. The SEO method is composed of two stages: the first stage is to choose reference points of the manipulator and calculate their boundary surfaces using the nth enveloping method; the second stage is to overlay these boundary surfaces to identify the final workspace. The SEO method is basically a combination of the analytic method and the numerical method. By delineating the graphic representation of the workspace step by step, the SEO method is easy to analyze the existence and the shape of voids and holes. The basic theory of the SEO method and formulas for workspace calculation are presented based on a 6R serial manipulator. By showing the workspace calculation results, the SEO method is proved working correctly.     

Fuzzy optimization of storage space allocation in a container terminal

A fuzzy optimization model of storage space allocation is proposed, and a rolling-planning method is derived. The model takes the uncertainty of departure time of import containers and arrival time of export containers into account. For each planning horizon, the problem is decomposed into two levels: the first level minimizes the unbalanced workloads among blocks using hybrid intelligence algorithm; based on block workloads allocated in the above level, the second level minimizes the number of blocks to which the same group of import containers are split. Numerical results show that the model reduces workload imbalance, and speeds up the vessel loading and discharging process.     

Initial conditions of impact dynamics

The effects of the initial conditions of impact dynamics equations are investigated numerically and experimentally. The inadequacies of previous studies on initial conditions are pointed out. Then a coefficient of velocity jump at the moment of impact is introduced, and the experiments for the mental rods are implemented to validate the appending constraints modeling methods for impact process. The comparisons between the experimental and simulated results at different coefficients are used to study the effects of the velocity jump conditions to the numerical simulation. The results indicate that the physical velocity response of bodies during impact is smooth; the different values of velocity jump only have small effects on numerical oscillation of velocity response, and they have no effects on the time history of impact force.     

GNN-CRC: Discriminative Collaborative Representation-Based Classification via Gabor Wavelet Transformation and Nearest Neighbor

Collaborative representation-based classification (CRC) is a distance based method, and it obtains the original contributions from all samples to solve the sparse representation coefficient. We find out that it helps to enhance the discrimination in classification by integrating other distance based features and/or adding signal preprocessing to the original samples. In this paper, we propose an improved version of the CRC method which uses the Gabor wavelet transformation to preprocess the samples and also adapts the nearest neighbor (NN) features, and hence we call it GNN-CRC. Firstly, Gabor wavelet transformation is applied to minimize the effects from the background in face images and build Gabor features into the input data. Secondly, the distances solved by NN and CRC are fused together to obtain a more discriminative classification. Extensive experiments are conducted to evaluate the proposed method for face recognition with different instantiations. The experimental results illustrate that our method outperforms the naive CRC as well as some other state-of-the-art algorithms.