Ontology-Based Semantic Approach for Communication in Engineering Design Evaluation

Author(s):  
Pei Zhan ◽  
Uma Jayaram ◽  
Sankar Jayaram

The primary objective of this paper is to conceptualize and develop an approach using semantics to integrate engineering applications for design evaluations. Our approach, coined OADE (Ontology-based Adaptive Design Evaluation), will have as components representation tools, ontology builders, ontology projecting tools, custom tools, and communication tools. In the proposed integration framework, ontologies in different domains will be built and integrated with the domain-specific applications. Semantics will be represented in domain-specific ontology and translated using ontology projection. The process of ontology projection calculates the similarities between concepts related to diverse viewpoints and then translates them. A design decision can thus be described using the common concepts across the diverse entities.

Author(s):  
Pei Zhan ◽  
Uma Jayaram ◽  
Sankar Jayaram ◽  
OkJoon Kim ◽  
Lijuan Zhu

This work seeks to create a semantic approach that uses ontologies for sharing knowledge related to product data in CAD/CAE applications and for integrating the design evaluation information that these applications individually provide. Our overall approach is coined OADE, Ontology-based Adaptive Design Evaluation. This paper reports on a piece of our ongoing work in this area. The key contributions of this paper include methods for the design of knowledge representation in product design and analysis, population of product data semantics, creation of ontology mapping methods and mapping representations, and mapping of product data semantics to the target application. The mapping method finds matching concepts between different ontologies based on three basic concept relation types: composition, inheritance, and attribute. A prototype implementation is being created using technologies such as OWL (representation tool), Jena (ontology builder), and Prote´ge´ (ontology editor) to demonstrate the approach for integrating a parametric CAD system, custom virtual assembly application, and an ergonomics engineering application. An example is given in this paper to illustrate how this approach can help integration between a product design application and an assembly simulation analysis application. The significance of this work is that it will provide the capability to create, share, and exchange knowledge for solving design evaluation challenges involving multiple applications and multiple viewpoints. A design decision can thus be described using the common concepts across the diverse entities.


Author(s):  
Pei Zhan ◽  
Uma Jayaram ◽  
OkJoon Kim ◽  
Lijuan Zhu

This paper presents a semantic approach that uses ontologies to share knowledge related to product data in CAD/CAE applications and for integrating the design evaluation information that these applications individually provide. Our overall approach is the ontology-based adaptive design evaluation, also coined as OADE. This paper reports a piece of our ongoing work in the area of knowledge representation and ontology mapping methods. Here we design ontologies for representing product design and analysis, instantiate a source ontology with the product data, create formal ontology mapping methods, and then apply these methods to transfer the product data from the source ontology to the target one. A prototype implementation has been created using technologies such as OWL (representation language), JENA (ontology API), and PROTÉGÉ (ontology editor) to demonstrate the approach for integrating product design and assembly simulation analysis applications. This work is significant because heuristic methods based on geometry attributes, composition, and inheritance for determining mapped concepts in engineering ontologies is still very new, and not much work has been done in this area. This work will lead to the ability to create, share, and exchange knowledge for solving design evaluation challenges involving multiple applications and viewpoints.


1999 ◽  
Vol 11 (4) ◽  
pp. 218-228 ◽  
Author(s):  
Michael J. Scott ◽  
Erik K. Antonsson

Author(s):  
Sikata Nanda ◽  
Rabi Narayan Dhar

Background: Nutritional status of adolescent girls are different from the younger children and older adults. In the tribal population they are more neglected in comparison to boys because of limited resources and health care facilities. In the present study we have done assessment of nutritional status of adolescent girls in the Dongria Kondh tribe in Odisha. Methods: Dongria Kondh’ residing in Rayagada district of Odisha, having its maximum concentration was studied. Bissam Cuttack block was selected randomly as the study area. Moreover, coincidently majority of the study population resided in the block having villages like Kurli, Khambesi, Hundijali, Muthesi, Khajuri, Mundabali and Uppar Gandatallli which are situated as a distance of 5000 ft height above sea level. 89 adolescent girls were considered to assess the nutritional status of tribal adolescent girls of Dongria Kondh tribe to study the different factors associated with the nutritional status of the girls and to suggest remedial measures for integrated development of the adolescent girls. Results: Most of the girls (81%) were from nuclear family. All girls belonged to low socio economic status. The energy intake was adequate only in 35% of study subjects. The protein intake was adequate in only 38% of study subjects. The common types of food consumed was rice, ragi and seasonal fruits and all were non vegetarian. Conclusions: The widespread problem of poverty, illiteracy, malnutrition, absence of sanitary living condition, ignorance of cause of disease still are the contributing factors for the deplorable condition prevailing amongst the adolescent girls of the tribal group. As they are future mothers, improvement of nutritional status should be the primary objective. 


2019 ◽  
Author(s):  
Esther X.W. Wu ◽  
Gwenisha J. Liaw ◽  
Rui Zhe Goh ◽  
Tiffany T.Y. Chia ◽  
Alisia M.J. Chee ◽  
...  

AbstractAttention is a critical cognitive function, allowing humans to select, enhance, and sustain focus on information of behavioral relevance. Attention contains dissociable neural and psychological components. Nevertheless, some brain networks support multiple attentional functions. Connectome-based Predictive Models (CPM), which associate individual differences in task performance with functional connectivity patterns, provide a compelling example. A sustained attention network model (saCPM) successfully predicted performance for selective attention, inhibitory control, and reading recall tasks. Here we constructed a visual attentional blink (VAB) model (vabCPM), comparing its performance predictions and network edges associated with successful and unsuccessful behavior to the saCPM’s. In the VAB, attention devoted to a target often causes a subsequent item to be missed. Although frequently attributed to attentional limitations, VAB deficits may attenuate when participants are distracted or deploy attention diffusely. Participants (n=73; 24 males) underwent fMRI while performing the VAB task and while resting. Outside the scanner, they completed other cognitive tasks over several days. A vabCPM constructed from these data successfully predicted VAB performance. Strikingly, the network edges that predicted better VAB performance (positive edges) predicted worse selective and sustained attention performance, and vice versa. Predictions from the saCPM mirrored these results, with the network’s negative edges predicting better VAB performance. Furthermore, the vabCPM’s positive edges significantly overlapped with the saCPM’s negative edges, and vice versa. We conclude that these partially overlapping networks each have general attentional functions. They may indicate an individual’s propensity to diffusely deploy attention, predicting better performance for some tasks and worse for others.Significance statementA longstanding question in psychology and neuroscience is whether we have general capacities or domain-specific ones. For such general capacities, what is the common function? Here we addressed these questions using the attentional blink (AB) task and neuroimaging. Individuals searched for two items in a stream of distracting items; the second item was often missed when it closely followed the first. How often the second item was missed varied across individuals, which was reflected in attention networks. Curiously, the networks’ pattern of function that was good for the AB was bad for other tasks, and vice versa. We propose that these networks may represent not a general attentional ability, but rather the tendency to attend in a less focused manner.


Humaniora ◽  
2015 ◽  
Vol 6 (3) ◽  
pp. 418
Author(s):  
Deni Setiawan ◽  
Timbul Haryono ◽  
M. Agus Burhan

Carnival clothing is one form of artists’ creativities in fine art, created in various functions. Those functions are viewed based on utility value and the purpose that consistently are embedded in an art work. In addition, several functions of carnival clothing were constructed on the basis of social and cultural conditions that are effective in a certain place. Each and every type of clothing raises perception to everyone else who sees it. Promotion of fashion style and industry through carnival clothing results in diverse perceptions acceptable to the viewers. Audience’s perceptions are also not apart from the key functions, social ones, and the physical ones of those carnival clothings themselves. Those three functions are the common ones of each art work created as communication tool with everyone else. The carnival clothings are communication tools of the fashion designer to the customers, communication between one customer and another one. On the carnival clothing there are also sources of knowledge science, history, technology, and many other explainable meanings. Through carnival clothings, the detectable issues in physical and non-physical structures are identifiable as well as they play role as the space to make more exploration on the dynamics of a community culture. This article aims to answer the functions of carnival clothing, using aesthetic approach, through the theory of clothing functions Roland Barthes and Edmund Burke Feldman’s art functions. 


Author(s):  
Xianping Du ◽  
Onur Bilgen ◽  
Hongyi Xu

Abstract Machine learning for classification has been used widely in engineering design, for example, feasible domain recognition and hidden pattern discovery. Training an accurate machine learning model requires a large dataset; however, high computational or experimental costs are major issues in obtaining a large dataset for real-world problems. One possible solution is to generate a large pseudo dataset with surrogate models, which is established with a smaller set of real training data. However, it is not well understood whether the pseudo dataset can benefit the classification model by providing more information or deteriorates the machine learning performance due to the prediction errors and uncertainties introduced by the surrogate model. This paper presents a preliminary investigation towards this research question. A classification-and-regressiontree model is employed to recognize the design subspaces to support design decision-making. It is implemented on the geometric design of a vehicle energy-absorbing structure based on finite element simulations. Based on a small set of real-world data obtained by simulations, a surrogate model based on Gaussian process regression is employed to generate pseudo datasets for training. The results showed that the tree-based method could help recognize feasible design domains efficiently. Furthermore, the additional information provided by the surrogate model enhances the accuracy of classification. One important conclusion is that the accuracy of the surrogate model determines the quality of the pseudo dataset and hence, the improvements in the machine learning model.


2019 ◽  
Vol 21 (Supplement_6) ◽  
pp. vi183-vi183
Author(s):  
Jacques Grill ◽  
Gwenael Le Teuff ◽  
Karsten Nysom ◽  
Klas Blomgren ◽  
Darren Hargrave ◽  
...  

Abstract BACKGROUND Diffuse intrinsic pontine glioma (DIPG) is one of the most devastating brain neoplasms. Despite 50 years of clinical trials, no improvement of survival has been observed and most children die within 2 years of diagnosis. Only radiotherapy transiently controls disease progression. METHODS/AIMS: BIOMEDE was conceived as a randomized multi-arm multi-stage program (drop-the-loser adaptive design). It started with an open-label phase-II trial comparing three drugs (everolimus, dasatinib, erlotinib) combined with irradiation, allocated according to the presence of their specific targets) with a planned sample size of 250 patients. A stereotactic biopsy was performed at diagnosis to centrally confirm the diagnosis of DIPG (presence of histone H3K27M mutation or loss of K27 trimethylation) and assess biomarkers/targets (PTEN-loss, EGFR-overexpression). Targeted therapies were started concomitantly with radiotherapy and were continued until disease progression. The main objective of the study was to compare the efficacy of randomized groups in terms of overall survival (OS). RESULTS At the 3rd interim analysis, based on 193 randomized patients among the 230 study patients, the IDMC concluded that the study was unlikely to meet its primary objective even if 250 patients were randomized. The median OS from the time of randomization was 10.9, 9.5 and 9 months for everolimus, dasatinib and erlotinib, respectively, which is comparable to historical controls. The median number of courses administered was 7, 5.5 and 6 respectively. Treatment was discontinued due to toxicity in 2%, 13%, and 15%, respectively. No biopsy-related death was reported and diagnostic yield was excellent, with only 5 non-informative biopsies. CONCLUSION BIOMEDE shows the feasibility of biologically-driven treatment in DIPG on a large international scale. Based on the better toxicity profile and the slightly better efficacy, although not statistically significant, the steering committee proposed that everolimus should be used as the control arm for the next step, BIOMEDE 2.0.


2018 ◽  
Vol 140 (10) ◽  
Author(s):  
Murtuza Shergadwala ◽  
Ilias Bilionis ◽  
Karthik N. Kannan ◽  
Jitesh H. Panchal

Many decisions within engineering systems design are typically made by humans. These decisions significantly affect the design outcomes and the resources used within design processes. While decision theory is increasingly being used from a normative standpoint to develop computational methods for engineering design, there is still a significant gap in our understanding of how humans make decisions within the design process. Particularly, there is lack of knowledge about how an individual's domain knowledge and framing of the design problem affect information acquisition decisions. To address this gap, the objective of this paper is to quantify the impact of a designer's domain knowledge and problem framing on their information acquisition decisions and the corresponding design outcomes. The objective is achieved by (i) developing a descriptive model of information acquisition decisions, based on an optimal one-step look ahead sequential strategy, utilizing expected improvement maximization, and (ii) using the model in conjunction with a controlled behavioral experiment. The domain knowledge of an individual is measured in the experiment using a concept inventory, whereas the problem framing is controlled as a treatment variable in the experiment. A design optimization problem is framed in two different ways: a domain-specific track design problem and a domain-independent function optimization problem (FOP). The results indicate that when the problem is framed as a domain-specific design task, the design solutions are better and individuals have a better state of knowledge about the problem, as compared to the domain-independent task. The design solutions are found to be better when individuals have a higher knowledge of the domain and they follow the modeled strategy closely.


Author(s):  
Rajesh Radhakrishnan ◽  
Daniel A. McAdams

Abstract Engineering design models are aids that provide the designer with the ability to visualize the form and predict the nature and behavior of any product. In each stage of design, these models are used to predict the result of, or guide, design specifications, at a time when the design can still be changed with minimal negative impact. To ensure the downstream validity of these specifications or decisions, the designer must construct models that have sufficient accuracy and resolution. Determining the goodness of a model for a particular design decision or specification is a fundamental and pervasive question in engineering. Though fast to construct, and generally inexpensive, models based on estimation and approximation may not provide information of sufficient quality to make an accurate evaluation. In contrast, the crispness and depth of information gained from detailed computational analysis or experimental trials may come at too great an expense. Hence, a key aspect of model construction in design is deciding whether a model is appropriate for a particular design specification or evaluation considering accuracy and cost factors. This paper explores the application of utility theory to the model construction problem. We also discuss how estimated model accuracy affects the confidence of selecting a particular model. We present this research through application to a racecar sway bar.


Sign in / Sign up

Export Citation Format

Share Document