The work concerns the concept of assisting software supporting the design process of a selected class of the CPS (Cyber-Physical System) - a tractor drive system. The task was carried out in a process-oriented convent...
详细信息
ISBN:
(纸本)9781643680217;9781643680200
The work concerns the concept of assisting software supporting the design process of a selected class of the CPS (Cyber-Physical System) - a tractor drive system. The task was carried out in a process-oriented convention. The paper presents the characteristics of individual stages of the design task - the design of the tractor transmission electronic unit treated as a design case. To the classic substantive-model-staged narration, the characteristics of existing, acquired, developed and used personal knowledge of designers have been added. Attention was paid to the process, product models, requirements and constraints, aspects of analysis and synthesis, automation tools, and wider contexts of particular issues. The material collected in terms of the personal knowledge served to create the concept of an assistive system for designers to improve the design process through more precise and problem-dedicated knowledge and design models management. The proposed concept is based on design knowledge modelling and can be applied in the design process of the CPS or its elements.
Visual reasoning between visual image and natural language description is a long-standing challenge in computer vision. While recent approaches offer a great promise by compositionality or relational computing, most o...
详细信息
ISBN:
(数字)9781728171685
ISBN:
(纸本)9781728171692
Visual reasoning between visual image and natural language description is a long-standing challenge in computer vision. While recent approaches offer a great promise by compositionality or relational computing, most of them are oppressed by the challenge of training with datasets containing only a limited number of images with ground-truth texts. Besides, it is extremely time-consuming and difficult to build a larger dataset by annotating millions of images with text descriptions that may very likely lead to a biased model. Inspired by the majority success of webly supervised learning, we utilize readily-available web images with its noisy annotations for learning a robust representation. Our key idea is to presume on web images and corresponding tags along with fully annotated datasets in learning with knowledge embedding. We present a two-stage approach for the task that can augment knowledge through an effective embedding model with weakly supervised web data. This approach learns not only knowledge-based embeddings derived from key-value memory networks to make joint and full use of textual and visual information but also exploits the knowledge to improve the performance with knowledge-based representation learning for applying other general reasoning tasks. Experimental results on two benchmarks show that the proposed approach significantly improves performance compared with the state-of-the-art methods and guarantees the robustness of our model against visual reasoning tasks and other reasoning tasks.
The overlapped rectangular non-symmetry and anti-packing model (ORNAM) is a kind of image representation model developed from the original non-overlapped one. Aimed at the difference of them, this paper proposes two m...
详细信息
In the world of wireless communication, there is a potential expansion in the field of digital communication and many new technologies and applications are growing every day. With the advancement in wireless communica...
详细信息
The proceedings contain 70 papers. The topics discussed include: softwareengineering in a data science future;automating performance anti-pattern detection and software refactoring in UML models;program state coverag...
ISBN:
(纸本)9781728105918
The proceedings contain 70 papers. The topics discussed include: softwareengineering in a data science future;automating performance anti-pattern detection and software refactoring in UML models;program state coverage: a test coverage metric based on executed program states;DeepLink: a code knowledge graph based deep learning approach for issue-commit link recovery;AVATAR: fixing semantic bugs with fix patterns of static analysis violations;exploring regular expression evolution;testing the message flow of android auto apps;and please help! a preliminary study on the effect of social proof and legitimization of paltry contributions in donations to OSS.
Model-Driven engineering (MDE) comprises the practice of systematically using models during software development. The high diversity of MDE assets (e.g., metamodels, models, model transformation engines, and design to...
详细信息
ISBN:
(纸本)9781728134390
Model-Driven engineering (MDE) comprises the practice of systematically using models during software development. The high diversity of MDE assets (e.g., metamodels, models, model transformation engines, and design tools) has raised a rich, diverse, and complex software ecosystem (SECO), where a collection of assets is governed by underlying rules and surrounded by a community of players. The lack of a deeper understanding on those relations has: (i) hampered the adoption of such paradigm by newcomers;(ii) increased the learning curve;(iii) prevented the community from exploiting their full potential;and (iv) inhibited the more essential benefits promoted by MDE, such as automation, reuse, productivity, maintainability, and time to market. In this context, this paper presents preliminary results of an investigation on MDE as a SECO. We compiled existing knowledge from literature joining independent research findings to provide an exploratory characterization of the technical dimension of such ecosystem. We also identified research gaps that motivate further investigation considering the relevance and potential of this topic for the forthcoming years.
knowledge Representation Learning (KRL), which is also known as knowledge Embedding, is a very useful method to represent complex relations in knowledge graphs. The low-dimensional representation learned by KRL models...
ISBN:
(数字)9781728195582
ISBN:
(纸本)9781728195599
knowledge Representation Learning (KRL), which is also known as knowledge Embedding, is a very useful method to represent complex relations in knowledge graphs. The low-dimensional representation learned by KRL models makes a contribution to many tasks like recommender system and question answering. Recently, many KRL models are trained using square loss or cross entropy loss based on Closed World Assumption (CWA). Although CWA is an easy way for training, it violates the link prediction task which exploits KRL. To overcome the drawback, in this paper, we introduce a new method, Type-based Prior Possibility Assumption (TPPA). TPPA calculates type based prior possibilities for missing triplets instead of zeros in the training process of KRL to weaken the bad influence of CWA. We compare TPPA with the baseline method CWA in ConvE and TuckER, two common frameworks for knowledge representation learning. The experiment results on FB15k-237 dataset show that TPPA based training method outperforms CWA based training method in link prediction task.
Pulse DC sintering (PDCS) systems, an effective way of producing sintered materials, are complex systems. They need to be modelled both electrically and thermally. Such a system can be controlled manually or automatic...
详细信息
A software Product Line (SPL) represents a set of systems sharing common and variable features. The varying features and respective elements (variability) enable differentiating products of a certain domain. Thus, man...
详细信息
ISBN:
(数字)9781728173030
ISBN:
(纸本)9781728173047
A software Product Line (SPL) represents a set of systems sharing common and variable features. The varying features and respective elements (variability) enable differentiating products of a certain domain. Thus, managing variability is a crucial activity for the success of SPL engineering, especially those based on UML due to a large amount of variability representation in different diagrams. There are few experiments in the literature to evaluate and to compare UML-based variability management approaches. In this paper, we analyze a subset of such approaches: SMarty (our approach), PLUS, and Razavian and Khosravi. We empirically compared them by conducting an experiment with more than 50 participants in terms of configuring SPL products and variability traceability among class and component diagram variable elements. We also analyzed the influence of the participants knowledge on the use of each approach and the amount of material consultation required for each variability management approach. In addition, we checked whether participants comprehend traceability capabilities of approaches. Results pointed out: SMarty is as effective as other studied approaches to configuring SPL specific products; the number of consultations on each approach instructional material did not influence effectiveness; and SMarty needs more participants previous knowledge on UML to configure SPL products.
In this paper, the spherical three-degree-of-freedom parallel manipulator has been called Agile Eye which is designed in *** as an analysis software for defining the constraints and variables. Then, forward kinematic ...
详细信息
暂无评论