Abstract
Este artigo tem como objetivo identificar os desafios, as barreiras e as aprendizagens com a atividade de remanufatura. Por meio de uma busca realizada na internet foram encontradas empresas de diferentes regiões do país que operam no setor. Desse modo, como procedimento de coleta, foi adotado o estudo de casos múltiplos e, como técnica de coleta, foi utilizada a entrevista semiestruturada, uma vez que a intenção era obter dos entrevistados o relato sobre o seu dia a dia e o seu ambiente de negócio na remanufatura. Os resultados mostraram que a atividade é carente de incentivos por parte do poder público. Outro ponto que prejudica é o custo da logística reversa. Há, ainda, a falta de locais apropriados na fase de descarte dos materiais, cujas condições de reaproveitamento no processo não são mais viáveis. Destarte, o estudo permitiu conhecer um pouco mais da remanufatura por meio do que as empresas contatadas vivenciam no mercado.

Abstract
Noting recent advances in the field of image classification, where convolutional neural networks (CNNs) are used to classify images with high precision. This paper proposes a method of classifying breathing sounds using CNN, where it is trained and tested. To do this, a visual representation of each audio sample was made that allows identifying resources for classification, using the same techniques used to classify images with high precision.For this we used the technique known as Mel Frequency Cepstral Coefficients (MFCCs). For each audio file in the dataset, we extracted resources with MFCC which means we have an image representation for each audio sample. The method proposed in this article obtained results above 74%, in the classification of respiratory sounds used in the four classes available in the database used (Normal, crackles, wheezes, Both).

Abstract

Abstract
Generation Z is expected to be a dominant demographic and economic group. Cyber-waviness, constant reliance on smart devices that allows them to be always connected are among some of their intrinsic characteristics. The combination of this reality with the ever-changing technological environment is compelling retailers to reshape their business strategies, to meet this group desires and expectations and to foster their engagement. Augmented reality (AR) is emerging as a technological solution that pleases both consumers and retailers. This paper aims to answer two main questions: (1) How does generation Z evaluate an AR experience? (2) Which attributes/benefits do they value or not during an AR experience? Drawing on a qualitative methodology – content analysis of 34 interviewees – we discuss six main dimensions the potential customer value of the relationship between them and AR experiences under retailer context.

Abstract

Abstract
This paper addresses a hierarchical framework for the energy resources and network expansion planning of an Energy Distribution Company (EDC) that supplies its downward Active Industrial MicroGrids (AIMGs) with hot water and/or steam and electricity through its district heating and electric grid, respectively. The main contribution of this paper is that the proposed model considers AIMGs' electricity transactions with each other and/ or other customers through the EDC's electric main grid and investigates the impacts of these transactions on the expansion planning problem. The solution methodology is another contribution of this paper that tries to trade-off between accuracy and computational burden. The proposed framework uses a three-stage iterative heuristic optimization algorithm that considers different uncertainties of the planning and operational parameters. At the first stage, the algorithm determines the characteristics of energy system facilities for different stochastic parameter scenarios. At the second stage, the feasibility and optimality of AIMGs' electric transactions are evaluated and the optimal scheduling energy resources in normal states are determined. Finally, at the third stage, different demand response alternatives, load shedding and the AIMGs' electric transaction interruptions for contingent conditions are decided. The proposed method is applied to 9-bus, 33-bus and 123-bus IEEE test systems. Further, a full search algorithm is used to evaluate the quality of solutions of the proposed algorithm. The introduced algorithm reduced the total costs for the 9-bus, 33-bus and 123-bus system about 18.645%, 9.658%, and 4.849% with respect to the costs of custom expansion planning exercises, respectively.