usage context
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2021 ◽  
Vol 2022 (1) ◽  
pp. 166-186
Author(s):  
Mahsa Saeidi ◽  
McKenzie Calvert ◽  
Audrey W. Au ◽  
Anita Sarma ◽  
Rakesh B. Bobba

Abstract End users are increasingly using trigger-action platforms like If-This-Then-That (IFTTT) to create applets to connect smart-home devices and services. However, there are inherent implicit risks in using such applets—even non-malicious ones—as sensitive information may leak through their use in certain contexts (e.g., where the device is located, who can observe the resultant action). This work aims to understand to what extent end users can assess this implicit risk. More importantly we explore whether usage context makes a difference in end-users’ perception of such risks. Our work complements prior work that has identified the impact of usage context on expert evaluation of risks in IFTTT by focusing the impact of usage context on end-users’ risk perception. Through a Mechanical Turk survey of 386 participants on 49 smart-home IFTTT applets, we found that participants have a nuanced view of contextual factors and that different values for contextual factors impact end-users’ risk perception differently. Further, our findings show that nudging the participants to think about different usage contexts led them to think deeper about the associated risks and raise their concern scores.


2021 ◽  
Vol 12 (5) ◽  
pp. 41-53
Author(s):  
Armaya’u Zango Umar ◽  
Jaejoon Lee

Software product line engineering is a paradigm for developing a family of software products from a repository of reusable assets rather than developing each individual product from scratch. In featureoriented software product line engineering, the common and the variable characteristics of the products are expressed in terms of features. Using software product line engineering approach, software products are produced en masse by means of two engineering phases: (i) Domain Engineering and, (ii) Application Engineering. At the domain engineering phase, reusable assets are developed with variation points where variant features may be bound for each of the diverse products. At the application engineering phase, individual and customized products are developed from the reusable assets. Ideally, the reusable assets should be adaptable with less effort to support additional variations (features) that were not planned beforehand in order to increase the usage context of SPL as a result of expanding markets or when a new usage context of software product line emerges. This paper presents an exploration research to investigate the properties of features, in the code-asset implemented using Object-Oriented Programming Style. In the exploration, we observed that program elements of disparate features formed unions as well as intersections that may affect modifiability of the code-assets. The implication of this research to practice is that an unstable product line and with the tendency of emerging variations should aim for techniques that limit the number of intersections between program elements of different features. Similarly, the implication of the observation to research is that there should be subsequent investigations using multiple case studies in different software domains and programming styles to improve the understanding of the findings.


2021 ◽  
Author(s):  
Mojtaba Arezoomand ◽  
Jesse Austin-Breneman

Abstract Engineers must consider the usage context of a product in order to both predict its technical performance and model customer preferences. An emerging body of work in Decision-based Design (DBD) has elaborated various approaches for modeling the usage context in order to better predict customer choice behavior and select optimal product attributes. Building on this prior work, this study proposes a new method for formulating DBD problems in which product attribute values can change contextual factors. Results from a vehicle design case study demonstrate the utility of the proposed method for understanding how phenomena such as the rebound effect and induced travel demand connect system-level outcomes to design changes. This study suggests that the Design for Coupled Usage Contexts framework is a promising tool to further explore as a way to support designers making decisions which involve these types of mechanisms. Further exploration should include additional case studies to investigate other coupling mechanisms and design tasks.


2021 ◽  
Vol 64 (2) ◽  
pp. 705-714
Author(s):  
Zhilin Zhao ◽  
Fang Cheng

HighlightsA LightGBM regression model for predicting tractor usage rates was established based on warranty data and considering agricultural tractors’ usage context (region and season) and was then interpreted using SHAP.The field reliability of tractors was estimated based on the usage of failed and unfailed tractors, after unfailed tractors’ usage was imputed using the LightGBM regression model.The proposed methodology was validated by predicting warranty claims using estimated reliability parameters.The proposed methodology was demonstrated using warranty data from a tractor manufacturing company in China.Abstract. Warranty data provide a valuable source of information for assessing the reliability of products in operation (called the field reliability). However, warranty data consist of failure information only. The unavailability of usage data for unfailed products makes it difficult to estimate the reliability of durable products such as agricultural tractors, for which usage is a greater concern than age for reliability analysis. Several studies have proposed methods to address this problem, but they did not include information on the usage context. This study proposes a methodology to estimate the field reliability of agricultural tractors from warranty data considering the tractors’ usage context. First, by taking features representing tractors’ usage context as the input, a usage rate regression model was established using a light gradient boosting machine (LightGBM). The usage of unfailed tractors was then generated. Finally, parametric estimates of the tractors’ reliability were determined based on the usage of failed and unfailed tractors. By interpreting the LightGBM model using SHapley Additive exPlanations (SHAP), it was found that tractors that were used more days in October and April had higher predicted usage rates. To validate the effectiveness of the proposed methodology, the estimated reliability parameters were used to predict the warranty claims of six types of tractors. The results showed that the proposed methodology performed the best in four cases and close to the best in two other cases when compared with two other baseline methods. The proposed methodology was demonstrated using warranty data from an agricultural tractor manufacturing company in China and can be applied to improve understanding of tractor reliability. Keywords: Field reliability, LightGBM, SHAP, Usage context, Warranty data.


Author(s):  
Yali Fan ◽  
Zhen Tu ◽  
Tong Li ◽  
Hancheng Cao ◽  
Tong Xia ◽  
...  

2020 ◽  
Vol 11 (3) ◽  
pp. 91-121
Author(s):  
Vânia Rosa Pereira ◽  
Daniel Andrés Rodriguez ◽  
Sonia Maria Viggiani Coutinho ◽  
Diogo Victor Santos ◽  
José Antônio Marengo

We sought to identify priorities and adaptation opportunities for water security across the various Brazilian biomes. With ever-growing demand and water-usage, future climate scenarios suggest that further water resources management constraints are to be endured throughout the next two decades. The unbalance between high-quality water demand and availability in a multisectoral usage context (e.g., domestic, industry, agribusiness) highlights the socio-ecological Nexus+ concept's relevance. In this context, the political and cross-institutional articulation and flexibility play a significant role in steering adaptative actions. These challenges in defining action plans, adequately addressed at a multiscale level with inherent climatic uncertainties, are yet to be overcome in Brazilian water resources management.  


2020 ◽  
Vol 12 (1) ◽  
pp. 74-86
Author(s):  
Hannah Biermann ◽  
Philipp Brauner ◽  
Martina Ziefle

AbstractIn increasingly digitized working and living environments, human-robot collaboration is growing fast with human trust toward robotic collaboration as a key factor for the innovative teamwork to succeed. This article explores the impact of design factors of the robotic interface (anthropomorphic vs functional) and usage context (production vs care) on human–robot trust and attributions. The results of a scenario-based survey with N=228 participants showed a higher willingness to collaborate with production robots compared to care. Context and design influenced the trust attributed to the robots: robots with a technical appearance in production were trusted more than anthropomorphic robots or robots in the care context. The evaluation of attributions by means of a semantic differential showed that differences in robot design were less pronounced for the production context in comparison to the care context. In the latter, anthropomorphic robots were associated with positive attributes. The results contribute to a better understanding of the complex nature of trust in automation and can be used to identify and shape use case-specific risk perceptions as well as perceived opportunities to interacting with collaborative robots. Findings of this study are pertinent to research (e.g., experts in human–robot interaction) and industry, with special regard given to the technical development and design.


2020 ◽  
Vol 738 ◽  
pp. 139790 ◽  
Author(s):  
Pamela Dominutti ◽  
Thiago Nogueira ◽  
Adalgiza Fornaro ◽  
Agnès Borbon
Keyword(s):  

2020 ◽  
Vol 30 (5) ◽  
pp. 1329-1351
Author(s):  
Jinyoung Min ◽  
Youngjin Yoo ◽  
Hyeyoung Hah ◽  
Heeseok Lee

PurposeRather than viewing social network technology (SNT) as a mere tool to access a networked audience, we emphasize its role as both a means and a social actor to help verify people’s self-images in an online social context.Design/methodology/approachDrawing upon self-verification theory, this study investigates a mechanism of how users are willing to use SNTs continuously through the cognitive and affective reactions on two different SNTs. Structural equation modeling was used via data collected from 320 Facebook and 313 Twitter users.FindingsOur results demonstrated that Facebook users regard it only as a useful tool for presenting self-images, while Twitter users are likely to feel an emotional attachment to technology as a social actor when ideal self-verification is gained, and that different types of SNTs create differential contexts for self-verification.Research limitations/implicationsThis study suggests a new lens to understand SNT’s role as a social actor in the self-verification process, further identifying the SNT context in which SNT takes different roles.Practical implicationsIn a certain SNT usage context, users are attached to SNTs, suggesting SNT providers consider features that enable SNT users to fulfill their own self-verification motives.Originality/valueThis study explores the roles of SNTs from a self-verification perspective. Our conceptualization of technology as a self-verifying social actor can further extend existing discussions on the role of SNT in response to self-verifying needs, while also promoting the continued use of SNTs in the future.


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