80,467 research outputs found
Bidirectional optimization of the melting spinning process
This is the author's accepted manuscript (under the provisional title "Bi-directional optimization of the melting spinning process with an immune-enhanced neural network"). The final published article is available from the link below. Copyright 2014 @ IEEE.A bidirectional optimizing approach for the melting spinning process based on an immune-enhanced neural network is proposed. The proposed bidirectional model can not only reveal the internal nonlinear relationship between the process configuration and the quality indices of the fibers as final product, but also provide a tool for engineers to develop new fiber products with expected quality specifications. A neural network is taken as the basis for the bidirectional model, and an immune component is introduced to enlarge the searching scope of the solution field so that the neural network has a larger possibility to find the appropriate and reasonable solution, and the error of prediction can therefore be eliminated. The proposed intelligent model can also help to determine what kind of process configuration should be made in order to produce satisfactory fiber products. To make the proposed model practical to the manufacturing, a software platform is developed. Simulation results show that the proposed model can eliminate the approximation error raised by the neural network-based optimizing model, which is due to the extension of focusing scope by the artificial immune mechanism. Meanwhile, the proposed model with the corresponding software can conduct optimization in two directions, namely, the process optimization and category development, and the corresponding results outperform those with an ordinary neural network-based intelligent model. It is also proved that the proposed model has the potential to act as a valuable tool from which the engineers and decision makers of the spinning process could benefit.National Nature Science Foundation of China, Ministry of Education of China, the Shanghai Committee of Science and Technology), and the Fundamental Research Funds for the Central Universities
Enhancing Transportation Education through On-line Simulation using an Agent-Based Demand and Assignment Model
This research explores the effectiveness of using simulation as a tool for enhancing classroom learning in the Civil Engineering Department of the University of Minnesota at Twin Cities. The authors developed a modern transportation planning software package, Agent-based Demand and Assignment Model (ADAM), that is consistent with our present understanding of travel behavior, that is platform independent, and that is easy to learn and is thus usable by students. An in-class project incorporated ADAM and the performance of this education strategy was evaluated through pre-class survey, post-class survey, scores in the quiz focusing on travel demand modeling and final scores. Results showed that ADAM effectively enhanced students' self-reported understanding of transportation planning and their skills of forming opinions, evaluating projects and making judgments. Students of some learning styles were found to benefit more than others through simulation-based teaching strategy. Findings in this research could have significant implications for future practice of simulation-based teaching strategy.
A Quality Model for Actionable Analytics in Rapid Software Development
Background: Accessing relevant data on the product, process, and usage
perspectives of software as well as integrating and analyzing such data is
crucial for getting reliable and timely actionable insights aimed at
continuously managing software quality in Rapid Software Development (RSD). In
this context, several software analytics tools have been developed in recent
years. However, there is a lack of explainable software analytics that software
practitioners trust. Aims: We aimed at creating a quality model (called
Q-Rapids quality model) for actionable analytics in RSD, implementing it, and
evaluating its understandability and relevance. Method: We performed workshops
at four companies in order to determine relevant metrics as well as product and
process factors. We also elicited how these metrics and factors are used and
interpreted by practitioners when making decisions in RSD. We specified the
Q-Rapids quality model by comparing and integrating the results of the four
workshops. Then we implemented the Q-Rapids tool to support the usage of the
Q-Rapids quality model as well as the gathering, integration, and analysis of
the required data. Afterwards we installed the Q-Rapids tool in the four
companies and performed semi-structured interviews with eight product owners to
evaluate the understandability and relevance of the Q-Rapids quality model.
Results: The participants of the evaluation perceived the metrics as well as
the product and process factors of the Q-Rapids quality model as
understandable. Also, they considered the Q-Rapids quality model relevant for
identifying product and process deficiencies (e.g., blocking code situations).
Conclusions: By means of heterogeneous data sources, the Q-Rapids quality model
enables detecting problems that take more time to find manually and adds
transparency among the perspectives of system, process, and usage.Comment: This is an Author's Accepted Manuscript of a paper to be published by
IEEE in the 44th Euromicro Conference on Software Engineering and Advanced
Applications (SEAA) 2018. The final authenticated version will be available
onlin
Reverse Engineering Trimmed NURB Surfaces From Laser Scanned Data
A common reverse engineering problem is to convert several hundred thousand points
collected from the surface of an object via a digitizing process, into a coherent geometric
model that is easily transferred to a CAD software such as a solid modeler for either design
improvement or manufacturing and analysis. These data are very dense and make data-set
manipulation difficult and tedious. Many commercial solutions exist but involve time
consuming interaction to go from points to surface meshes such as BSplines or NURBS (Non
Uniform Rational BSplines). Our approach differs from current industry practice in that we
produce a mesh with little or no interaction from the user. The user can produce degree 2 and
higher BSpline surfaces and can choose the degree and number ofsegments as parameters to
the system. The BSpline surface is both compact and curvature continuous. The former
property reduces the large storage overhead, and the later implies a smooth can be created
from noisy data. In addition, the nature ofthe BSpline allows one to easily and smoothly alter
the surface, making re-engineering extremely feasible. The BSpline surface is created using
the principle ofhigher orders least squares with smoothing functions at the edges. Both linear
and cylindrical data sets are handled using an automated parameterization method. Also,
because ofthe BSpline's continuous nature, a multiresolutional-triangulated mesh can quickly
be produced. This last fact means that an STL file is simple to generate. STL files can also be
easily used as input to the system.Mechanical Engineerin
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Requirements for building information modeling based lean production management systems for construction
Smooth flow of production in construction is hampered by disparity between individual trade teams' goals and the goals of stable production flow for the project as a whole. This is exacerbated by the difficulty of visualizing the flow of work in a construction project. While the addresses some of the issues in Building information modeling provides a powerful platform for visualizing work flow in control systems that also enable pull flow and deeper collaboration between teams on and off site. The requirements for implementation of a BIM-enabled pull flow construction management software system based on the Last
Planner System™, called ‘KanBIM’, have been specified, and a set of functional mock-ups of the proposed system has been implemented and evaluated in a series of three focus group workshops. The requirements cover the areas of maintenance of work flow stability, enabling negotiation and commitment between teams, lean production planning with sophisticated pull flow control, and effective communication and visualization of flow. The evaluation results show that the system holds the potential to improve work flow and reduce waste by providing both process and product visualization at the work face
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