Using symbolic prominence to help design feature subsets for topic classification and clustering of natural human-human conversations

2005 ◽  
Author(s):  
Constantinos Boulis ◽  
Mari Ostendorf
Keyword(s):  
Design Feature ◽  
Classification And Clustering

scholarly journals Connectivity as a Design Feature for Industry 4.0 Production Equipment: Application for the Development of an In-Line Metrology System

2021 ◽  
Vol 11 (3) ◽  
pp. 1312
Author(s):  
Ana Pamela Castro-Martin ◽  
Horacio Ahuett-Garza ◽  
Darío Guamán-Lozada ◽  
Maria F. Márquez-Alderete ◽  
Pedro D. Urbina Coronado ◽  
...  
Keyword(s):  
Industry 4.0 ◽  
Design Feature ◽  
Production Equipment ◽  
Smart Manufacturing ◽  
Process Data ◽  
Industrial Sectors ◽  
Advanced Manufacturing Technologies ◽  
Manufacturing Technologies ◽  
Equipment Application ◽  
The Impact

Industry 4.0 (I4.0) is built upon the capabilities of Internet of Things technologies that facilitate the recollection and processing of data. Originally conceived to improve the performance of manufacturing facilities, the field of application for I4.0 has expanded to reach most industrial sectors. To make the best use of the capabilities of I4.0, machine architectures and design paradigms have had to evolve. This is particularly important as the development of certain advanced manufacturing technologies has been passed from large companies to their subsidiaries and suppliers from around the world. This work discusses how design methodologies, such as those based on functional analysis, can incorporate new functions to enhance the architecture of machines. In particular, the article discusses how connectivity facilitates the development of smart manufacturing capabilities through the incorporation of I4.0 principles and resources that in turn improve the computing capacity available to machine controls and edge devices. These concepts are applied to the development of an in-line metrology station for automotive components. The impact on the design of the machine, particularly on the conception of the control, is analyzed. The resulting machine architecture allows for measurement of critical features of all parts as they are processed at the manufacturing floor, a critical operation in smart factories. Finally, this article discusses how the I4.0 infrastructure can be used to collect and process data to obtain useful information about the process.

scholarly journals Graph contextualized attention network for predicting synthetic lethality in human cancers

2021 ◽  
Author(s):  
Yahui Long ◽  
Min Wu ◽  
Yong Liu ◽  
Jie Zheng ◽  
Chee Keong Kwoh ◽  
...  
Keyword(s):  
Synthetic Lethality ◽  
Critical Role ◽  
Design Feature ◽  
Cost Effective ◽  
Attention Network ◽  
New Genes ◽  
Lab Experiments ◽  
Proposed Model ◽  
Multiple Feature ◽  
Wet Lab

Abstract Motivation Synthetic Lethality (SL) plays an increasingly critical role in the targeted anticancer therapeutics. In addition, identifying SL interactions can create opportunities to selectively kill cancer cells without harming normal cells. Given the high cost of wet-lab experiments, in silico prediction of SL interactions as an alternative can be a rapid and cost-effective way to guide the experimental screening of candidate SL pairs. Several matrix factorization-based methods have recently been proposed for human SL prediction. However, they are limited in capturing the dependencies of neighbors. In addition, it is also highly challenging to make accurate predictions for new genes without any known SL partners. Results In this work, we propose a novel graph contextualized attention network named GCATSL to learn gene representations for SL prediction. First, we leverage different data sources to construct multiple feature graphs for genes, which serve as the feature inputs for our GCATSL method. Second, for each feature graph, we design node-level attention mechanism to effectively capture the importance of local and global neighbors and learn local and global representations for the nodes, respectively. We further exploit multi-layer perceptron (MLP) to aggregate the original features with the local and global representations and then derive the feature-specific representations. Third, to derive the final representations, we design feature-level attention to integrate feature-specific representations by taking the importance of different feature graphs into account. Extensive experimental results on three datasets under different settings demonstrated that our GCATSL model outperforms 14 state-of-the-art methods consistently. In addition, case studies further validated the effectiveness of our proposed model in identifying novel SL pairs. Availability Python codes and dataset are freely available on GitHub (https://github.com/longyahui/GCATSL) and Zenodo (https://zenodo.org/record/4522679) under the MIT license.

scholarly journals An MEA-Tuning Method for Design of the PID Controller

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Yongli Zhang ◽  
Lijun Zhang ◽  
Zhiliang Dong
Keyword(s):  
Pid Controller ◽  
Industrial Process ◽  
Optimal Solution ◽  
Design Feature ◽  
Parameter Tuning ◽  
Parallel Structure ◽  
Evolutionary Information ◽  
Tuning Method ◽  
Efficiency And Effectiveness ◽  
Global Optimal

The optimization and tuning of parameters is very important for the performance of the PID controller. In this paper, a novel parameter tuning method based on the mind evolutionary algorithm (MEA) was presented. The MEA firstly transformed the problem solutions into the population individuals embodied by code and then divided the population into superior subpopulations and temporary subpopulations and used the similar taxis and dissimilation operations for searching the global optimal solution. In order to verify the control performance of the MEA, three classical functions and five typical industrial process control models were adopted for testing experiments. Experimental results indicated that the proposed approach was feasible and valid: the MEA with the superior design feature and parallel structure could memorize more evolutionary information, generate superior genes, and enhance the efficiency and effectiveness for searching global optimal parameters. In addition, the MEA-tuning method can be easily applied to real industrial practices and provides a novel and convenient solution for the optimization and tuning of the PID controller.

scholarly journals Effect of infrastructure design on commons dilemmas in social−ecological system dynamics

2015 ◽  
Vol 112 (43) ◽  
pp. 13207-13212 ◽  
Author(s):  
David J. Yu ◽  
Murad R. Qubbaj ◽  
Rachata Muneepeerakul ◽  
John M. Anderies ◽  
Rimjhim M. Aggarwal
Keyword(s):  
Design Feature ◽  
Irrigated Agriculture ◽  
Small Scale ◽  
Qualitative Behavior ◽  
Central Feature ◽  
Social Ecological ◽  
Vital Functions ◽  
The Face ◽  
Design Characteristics ◽  
Shared Infrastructure

The use of shared infrastructure to direct natural processes for the benefit of humans has been a central feature of human social organization for millennia. Today, more than ever, people interact with one another and the environment through shared human-made infrastructure (the Internet, transportation, the energy grid, etc.). However, there has been relatively little work on how the design characteristics of shared infrastructure affect the dynamics of social−ecological systems (SESs) and the capacity of groups to solve social dilemmas associated with its provision. Developing such understanding is especially important in the context of global change where design criteria must consider how specific aspects of infrastructure affect the capacity of SESs to maintain vital functions in the face of shocks. Using small-scale irrigated agriculture (the most ancient and ubiquitous example of public infrastructure systems) as a model system, we show that two design features related to scale and the structure of benefit flows can induce fundamental changes in qualitative behavior, i.e., regime shifts. By relating the required maintenance threshold (a design feature related to infrastructure scale) to the incentives facing users under different regimes, our work also provides some general guidance on determinants of robustness of SESs under globalization-related stresses.

scholarly journals A Design Feature-based Approach for Product Remanufacturability Assessment and Analysis

Procedia CIRP ◽  
2016 ◽  
Vol 53 ◽  
pp. 15-20 ◽  
Author(s):  
S.K. Ong ◽  
H.C. Fang ◽  
A.Y.C. Nee
Keyword(s):  
Design Feature ◽  
Feature Based

scholarly journals Classification and clustering

1978 ◽  
Vol 27 (3) ◽  
pp. 287
Author(s):  
Gian-Carlo Rota
Keyword(s):  
Classification And Clustering
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