scholarly journals Evaluation Framework for User Experience in 5G Systems: On Systematic Rateless-Coded Transmissions

IEEE Access ◽  
2016 ◽  
Vol 4 ◽  
pp. 9108-9118 ◽  
Author(s):  
Ke Xiong ◽  
Yu Zhang ◽  
Pingyi Fan ◽  
Hong-Chuan Yang
2016 ◽  
Vol null (53) ◽  
pp. 283-296
Author(s):  
Hyun Duk Suh ◽  
Jun, Soo-Jin ◽  
Sun-gu Cho ◽  
Young-mi Shin ◽  
Eun-soo Cha

2019 ◽  
Vol 9 (16) ◽  
pp. 3307
Author(s):  
Ji Hyoun Lim ◽  
Ye Lim Rhie ◽  
Jaehyun Park

The user experience (UX) concept has widely been adopted in the field of development and evaluation of products and services. One reason behind this emerging trend is the limitation in traditional usability evaluation methods (UEMs), which emphasizes performance measures such as task completion time and error rate. To overcome the limitation, users’ perceived value must be set to reflect users’ various experiences. In order to address this issue, this study proposes a network analysis-based method to investigate a value structure to assess the level of user experience in using a product. Gesture interaction on a smart TV is used as a case study to demonstrate the process of obtaining a quantified value structure from the transcriptions of users’ in-depth interview. A major contribution of this study lies in the transformation from qualitative data to a quantified value structure. Product or service designers, in the industrial field, can develop value structure based on network analysis when evaluating their design alternatives within a properly fitted evaluation framework.


Author(s):  
Tatenda D. Kavu ◽  
Kuda Dube ◽  
Peter G. Raeth ◽  
Gilford T. Hapanyengwi

Researchers have worked on-finding e-commerce recommender systems evaluation methods that contribute to an optimal solution. However, existing evaluations methods lack the assessment of user-centric factors such as buying decisions, user experience and user interactions resulting in less than optimum recommender systems. This paper investigates the problem of adequacy of recommender systems evaluation methods in relation to user-centric factors. Published work has revealed limitations of existing evaluation methods in terms of evaluating user satisfaction. This paper characterizes user-centric evaluation factors and then propose a user-centric evaluation conceptual framework to identify and expose a gap within literature. The researchers used an integrative review approach to formulate both the characterization and the conceptual framework for investigation. The results reveal a need to come up with a holistic evaluation framework that combines system-centric and user-centric evaluation methods as well as formulating computational user-centric evaluation methods. The conclusion reached is that, evaluation methods for e-commerce recommender systems lack full assessment of vital factors such as: user interaction, user experience and purchase decisions. A full consideration of these factors during evaluation will give birth to new types of recommender systems that predict user preferences using user decision-making process profiles, and that will enhance user experience and increase revenue in the long run.


Sensors ◽  
2020 ◽  
Vol 20 (15) ◽  
pp. 4284 ◽  
Author(s):  
Jessica Lindblom ◽  
Beatrice Alenljung

The coexistence of robots and humans in shared physical and social spaces is expected to increase. A key enabler of high-quality interaction is a mutual understanding of each other’s actions and intentions. In this paper, we motivate and present a systematic user experience (UX) evaluation framework of action and intention recognition between humans and robots from a UX perspective, because there is an identified lack of this kind of evaluation methodology. The evaluation framework is packaged into a methodological approach called ANEMONE (action and intention recognition in human robot interaction). ANEMONE has its foundation in cultural-historical activity theory (AT) as the theoretical lens, the seven stages of action model, and user experience (UX) evaluation methodology, which together are useful in motivating and framing the work presented in this paper. The proposed methodological approach of ANEMONE provides guidance on how to measure, assess, and evaluate the mutual recognition of actions and intentions between humans and robots for investigators of UX evaluation. The paper ends with a discussion, addresses future work, and some concluding remarks.


Author(s):  
Hee-Jin Lee ◽  
Joon-Sang Lee ◽  
Eunkyoung Jee ◽  
Doo-Hwan Bae

The worldwide mobile software market has grown dramatically since feature phones became popular in the early 1990s. In practice, mobile usability — which can be defined for a resource-constrained device in two ways, namely, User eXperience (UX) and User Interface (UI) — has been regarded as the key to gaining superiority in terms of both market share and customer loyalty. Unfortunately, de facto standards for software design and the development process, such as Unified Modeling Language (UML) and Rational Unified Process (RUP), do not seem to promote mobile usability in a systematic manner in practice. This paper proposes a systematic and generalizable approach to modeling and evaluating the properties of mobile usability, herein treating it as a first-class software quality from the perspective of software engineering. We devise a UX evaluation framework for mobile usability, which we call UX Evaluation Framework (UEF) throughout this paper. A UX is specified by inter-scene interactions between users and terminals of software products using Extended Menu Navigation Viewpoints (EMNVs); then, a model checker, NuSMV, is adopted to observe whether the EMNV model meets a set of given UX properties. Importantly, the analysis and design of RUP is extended to support the co-design of UX and UI so that major roles, activities and artifacts in the UX and UI can be explicitly monitored and controlled by stakeholders. Through case studies, we demonstrate that UEF works properly to treat software products that prioritize mobile usability. Consequently, UEF plays a key role in filling the gap between two research disciplines to address usability: software engineering and human–computer interactions.


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