Satisfaction and Consumption Emotions of Library Users at a Public University in Mexico: A Case Study

Libri ◽  
2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Blanca-Lidia Miranda-Valencia

Abstract Consumption emotions are not always considered when satisfaction with library services is assessed. In this research, consumption emotions perceived by users of eight different libraries of a Mexican higher education institution are identified when using library services. Laros and Steenkamp. 2005. “Emotions in Consumer Behavior: A Hierarchical Approach.” Journal of Business Research 58: 1437–45. https://doi.org/10.1016/j.jbusres.2003.09.013 hierarchical scale was used to assess library users’ consumption emotions. The relationship between those emotions and the users’ satisfaction is then established and analyzed using both descriptive statistics analysis and an entropy-oriented machine learning approach. The first approach suggests that users feel more positive consumption emotions (contentment and happiness) than negative emotions (anger). The entropy analysis shows that the identified consumption emotions have a great prediction power over the satisfaction level that users will manifest. This research contributes to the issue of satisfaction assessment by including library users’ consumption emotions in Mexico.

2018 ◽  
Vol 74 (2) ◽  
pp. 210-224 ◽  
Author(s):  
Jernej Jevšenak ◽  
Sašo Džeroski ◽  
Saša Zavadlav ◽  
Tom Levanič

2019 ◽  
Vol 1 (1) ◽  
pp. 32-44
Author(s):  
Joseph Simonian ◽  
Chenwei Wu ◽  
Daniel Itano ◽  
Vyshaal Narayanam

2019 ◽  
Vol 487 (4) ◽  
pp. 5062-5069 ◽  
Author(s):  
Mariah G MacDonald

ABSTRACT The ‘radius valley’ is a relative dearth of planets between two potential populations of exoplanets, super-Earths and mini-Neptunes. This feature appears in examining the distribution of planetary radii, but has only ever been characterized on small samples. The valley could be a result of photoevaporation, which has been predicted in numerous theoretical models, or a result of other processes. Here, we investigate the relationship between planetary radius and orbital period through two-dimensional kernel density estimator and various clustering methods, using all known super-Earths (R < 4.0RE). With our larger sample, we confirm the radius valley and characterize it as a power law. Using a variety of methods, we find a range of slopes that are consistent with each other and distinctly negative. We average over these results and find the slope to be $m=-0.319^{+0.088}_{-0.116}$. We repeat our analysis on samples from previous studies. For all methods we use, the resulting line has a negative slope, which is consistent with models of photoevaporation and core-powered mass-loss but inconsistent with planets forming in a gas-poor disc


2020 ◽  
Vol 86 ◽  
pp. 01025
Author(s):  
Arlinta C. Barus ◽  
Marianna Simanjuntak ◽  
Verawati Situmorang

Indonesia is a country which is rich of various traditional cultures and values. One of its representation is traditional woven clothes (well known in Indonesian as kain tenun) which is wide spread throughout Indonesian regions. To support the traditional woven industry, as a relevancy to the industry 4.0 era, we develop DiTenun which is a multiplatform application that is able to produce new motifs of traditional woven intelligently using machine learning approach. The presence of the apps aims to support the growth of traditional weaving industry particularly the small and medium scale ones. The dissemination of the apps is very challenging as traditional woven centers are mostly located in rural area where the digital world has been rarely accessed. In this paper, we present “Ulos” as a case study in the utilization of DiTenun. The implementation of the sustainability of the Ulos industry by DiTenun needs to be adjusted to the development of the industrial era 4.0. Ulos is a traditional woven cloth from Batak tribe, which is located in several rural regions surrounding Toba highland in North Sumatera Utara province. The workflow for producing an item that is marketable is to produce woven fabrics with motifs that have been produced by smart devices. The results of DiTenun can have an impact on the technology produced and on the social life and culture of the weavers. The study shows how DiTenun is designed to support Ulos weavers in creating new motifs of Ulos and to support the economy of relevant small and medium scale industry of Ulos.


Author(s):  
Eisha Akanksha

Abnormal level of stress is the root indicator factor to have significant impact over the health of heart and there is a close relationship between the stress levels with heart rate. Review of the existing literature showcase that there has been various work that has been carried out towards investigation of considering heart rate with an internet-of-things (IoT) system. Apart from this, existing system doesnt offer any instantaneous solution where certain intimation is offered in real-time to the user with wearables as a solution to control the stress condition. Therefore, the current paper introduces a novel framework where the sampled heart rates of the patients are captured by IoT deivices. The aggregated data are further forwarded to the cloud analytic system that uses correlation to extract the appropriate message. The system after being applied with teh machine learning approach could further extract the elite outcome followed by forwarding the contextual data to teh user. Using an analytical modelliig, the proposed system shows that it offers better accuracy and reduced processing time when compared with other machine learning approach and thereby it proves to be cost effective solution in IoT system over medical case study.


2021 ◽  
Vol 2042 (1) ◽  
pp. 012070
Author(s):  
Tobias Kramer ◽  
Veronica Garcia-Hansen ◽  
Sara Omrani Vahid M. Nik ◽  
Dong Chen

Abstract This paper presents an alternative workflow for thermal comfort prediction. By using the leverage of Data Science & AI in combination with the power of computational design, the proposed methodology exploits the extensive comfort data provided by the ASHRAE Global Thermal Comfort Database II to generate more customised comfort prediction models. These models consider additional, often significant input parameters like location and specific building characteristics. Results from an early case study indicate that such an approach has the potential for more accurate comfort predictions that eventually lead to more efficient and comfortable buildings.


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