Search results for "MARK"
showing 10 items of 10630 documents
Predictive Model Markup Language (PMML) Representation of Bayesian Networks: An Application in Manufacturing
2018
International audience; Bayesian networks (BNs) represent a promising approach for the aggregation of multiple uncertainty sources in manufacturing networks and other engineering systems for the purposes of uncertainty quantification, risk analysis, and quality control. A standardized representation for BN models will aid in their communication and exchange across the web. This article presents an extension to the predictive model markup language (PMML) standard for the representation of a BN, which may consist of discrete variables, continuous variables, or their combination. The PMML standard is based on extensible markup language (XML) and used for the representation of analytical models…
Online fitted policy iteration based on extreme learning machines
2016
Reinforcement learning (RL) is a learning paradigm that can be useful in a wide variety of real-world applications. However, its applicability to complex problems remains problematic due to different causes. Particularly important among these are the high quantity of data required by the agent to learn useful policies and the poor scalability to high-dimensional problems due to the use of local approximators. This paper presents a novel RL algorithm, called online fitted policy iteration (OFPI), that steps forward in both directions. OFPI is based on a semi-batch scheme that increases the convergence speed by reusing data and enables the use of global approximators by reformulating the valu…
Prediction-Based Assembly Assistance System
2020
This paper presents the design of a prediction-based assembly assistance system for manual operations and the results obtained on the data collected from experiments of assembling a customizable product. We integrated into the proposed system a Markov predictor improved with a padding mechanism whose role is to recommend the next assembly step and to detect the worker’s errors. The predictor is trained with correct assembly patterns and tested with real assembly/manufacturing data. The proposed predictor improves the coverage and, thus, there is a significantly higher number of assembly steps which are correctly correlated with the real intentions of the workers.
Adaptation, coordination, and local interactions via distributed approachability
2017
This paper investigates the relation between cooperation, competition, and local interactions in large distributed multi-agent\ud systems. The main contribution is the game-theoretic problem formulation and solution approach based on the new framework\ud of distributed approachability, and the study of the convergence properties of the resulting game model. Approachability\ud theory is the theory of two-player repeated games with vector payoffs, and distributed approachability is here presented for\ud the first time as an extension to the case where we have a team of agents cooperating against a team of adversaries under local\ud information and interaction structure. The game model turns i…
Stable layer-building strategy to enhance cold-spray-based additive manufacturing
2020
Abstract Cold spray (CS) has recently become one of the popular additive manufacturing (AM) processes for its advantages: high-forming efficiency, low temperature, and no phase changing of materials. These advantages may make CS able to form large volume objects and possibly directly iterate with material-removing processes to become a hybrid AM process. Current research proposes using a bulk-based volume-forming strategy (e.g. a tessellation-based method) for volume building. Although it can form 3D volumes, the control of the process is difficult and it has limitations in forming complex 3D near-net-shapes with acceptable accuracy. This also conflicts with the basic principle of AM, where…
Metaheuristic procedures for the lexicographic bottleneck assembly line balancing problem
2015
The goal of this work is to develop an improved procedure for the solution of the lexicographic bottleneck variant of the assembly line balancing problem (LB-ALBP). The objective of the LB-ALBP is to minimize the workload of the most heavily loaded workstation, followed by the workload of the second most heavily loaded workstation and so on. This problem-recently introduced to the literature (Pastor, 2011)-has practical relevance to manufacturing facilities. We design, implement and fine-tune GRASP, tabu search (TS) and scatter search (SS) heuristics for the LB-ALBP and show that our procedures are able to obtain solutions of a quality that outperforms previous approaches. We rely on both s…
Conceptual Key Competency Model for Smart Factories in Production Processes
2020
Abstract Background and Purpose: The aim of the study is to develop a conceptual key competency model for smart factories in production processes, focused on the automotive industry, as innovation and continuous development in this industry are at the forefront and represent the key to its long-term success. Methodology: For the purpose of the research, we used a semi-structured interview as a method of data collection. Participants were segmented into three homogeneous groups, which are industry experts, university professors and secondary education teachers, and government experts. In order to analyse the qualitative data, we used the method of content analysis. Results: Based on the anal…
Emotional Design: Discovering Emotions Across Cars’ Morphologies
2020
The primary focus behind the overall design involves shifting from a designer-centric concept to a user-centric one. In essence, cars are utilitarian from an engineering point of view and symbolic-emotional from a social point of view. The modern car retains a strong social position and also generates vivid emotions. The tellability of a car is the priority when communicating with a customer. As a result, this paper proposes a computational approach towards studying the relationship between car morphology and the aforementioned produced emotions. Emotions are considered self-measurable and physiologically distinct. Each car is thus self-evaluated emotionally by a panel of potential users. T…
A Comprehensive Survey of Indoor Localization Methods Based on Computer Vision
2020
Computer vision based indoor localization methods use either an infrastructure of static cameras to track mobile entities (e.g., people, robots) or cameras attached to the mobile entities. Methods in the first category employ object tracking, while the others map images from mobile cameras with images acquired during a configuration stage or extracted from 3D reconstructed models of the space. This paper offers an overview of the computer vision based indoor localization domain, presenting application areas, commercial tools, existing benchmarks, and other reviews. It provides a survey of indoor localization research solutions, proposing a new classification based on the configuration stage…
Extreme Learning Machines for Data Classification Tuning by Improved Bat Algorithm
2018
Single hidden layer feed forward neural networks are widely used for various practical problems. However, the training process for determining synaptic weights of such neural networks can be computationally very expensive. In this paper we propose a new learning algorithm for learning the synaptic weights of the single hidden layer feedforward neural networks in order to reduce the learning time. We propose combining the upgraded bat algorithm with the extreme learning machine. The proposed approach reduces the number of evaluations needed to train a neural network and efficiently finds optimal input weights and the hidden biases. The proposed algorithm was tested on standard benchmark clas…