Contemporary Human-computer Interaction Research Articles

Human-Computer Interaction in Cloud Systems

As cloud computing continues to revolutionize the landscape of modern computing, the intersection of human-computer interaction (HCI) within cloud systems has become increasingly vital. This study aims to explore and analyze the evolving relationship between HCI principles and cloud computing environments. It investigates the various dimensions of HCI in cloud systems, encompassing user experience design, interface usability, accessibility, and collaboration paradigms. The paper begins by providing a comprehensive overview of HCI fundamentals, emphasizing their significance in the context of cloud computing. It delves into the unique challenges and opportunities presented by cloud environments, such as distributed computing, virtualization, and scalability concerns, and examines their implications forHCI design. Furthermore, the study investigates contemporary HCI methodologies and techniques tailored specifically for cloud systems, including adaptive interfaces, multi-platform compatibility, and responsive design principles. It discusses how these approaches aim to optimize user interaction, enhance productivity, and facilitate seamless user experiences across diverse devices and environments.

A CNN-LSTM based ensemble framework for in-air handwritten Assamese character recognition

In-air handwriting is a contemporary human computer interaction (HCI) technique which enables users to write and communicate in free space in a simple and intuitive manner. Air-written characters exhibit wide variations depending upon different writing styles of users and their speed of articulation, which presents a great challenge towards effective recognition of linguistic characters. So, in this paper we have proposed an ensemble model for in-air handwriting recognition which is based on convolutional neural network (CNN) and a long short-term memory neural network (LSTM-NN). The method collaborates overall character trajectory appearance modeling and temporal trajectory feature modeling for efficient recognition of varied types of air-written characters. In contrast to two-dimensional handwriting, in-air handwriting generally involves writing of characters interlinked by a continuous stroke, which makes segregation of intended writing activity from insignificant connecting motions an intricate task. So, a two-stage statistical framework is incorporated in the system for automatic detection and extraction of relevant writing segments from air-written characters. Identification of writing events from a continuous stream of air-written data is accomplished by formulating a Markov Random Field (MRF) model, while the segmentation of writing events into meaningful handwriting segments and redundant parts is performed by implementation of a Mahalanobis distance (MD) classifier. The proposed approach is assessed on an air-written character dataset comprising of Assamese vowels, consonants and numerals. The experimental results connote that our hybrid network can assimilate more information from the air-writing patterns and hence offer better recognition performance than the state-of-the-art approaches.

More-Than Human Centred Design: Considering Other Things

This paper responds to contemporary design contexts that frequently contain complex interdependencies of human and non-human actants. To adequately represent these perspectives requires a shift towards More-Than Human Centred Design. The Internet of Things (IoT) is one context that demonstrates this need. The ‘things’ within such networks transcend their physical forms and extend to include algorithms, humans, data, business models, etc. and each imports independent-but-interdependent motivations and perspectives. Therefore, we use the IoT to clarify our proposition and to convey our three contributions. First, we review the expanding corpus of contemporary Human–Computer Interaction research that seeks to expand the notion of Human Centred Design by moving beyond the dominant anthropocentric perspective. Second, we introduce a novel design metaphor, ‘constellations’, which allows both the interdependencies and independent perspectives to be considered. Third, we provide an account of a speculative design to demonstrate how it may be put into practice.

Identification of Human Emotions via Univariate and Multivarite Multiscale Entropy

This work analyzes the emotions of human in terms of complexity. This analysis is achieved by applying both univariate and multivariate multiscale entropy methods on a multimodal dataset. Most of the contemporary human-computer interaction systems are unable to identify human affective states. So, the benefit of analyzing human emotions is to fill this gap by detecting human affective states. The univariate and multivariate multiscale entropy analysis curves obtained using multimodal dataset show differences in terms of complexity among different affective states, which can be used for emotion detection and classification for machine vision applications.

Behavioral and emotional consequences of brief delays in human–computer interaction

It was thought that computer-performance-related problems in human–computer interaction (HCI) would become negligible with the constant increase in computing power. However, despite major advances in computer technology, contemporary HCI is still characterized by brief delays in computer responsiveness caused, for example, by background processes or network delays. Research on long system-response times (SRTs) indicates that delays may have negative behavioral and emotional consequences. However, there are fundamental differences between previously researched long SRTs and delays as they occur in contemporary HCI, such as different timings and occurrence probabilities. Therefore the previous research is not necessarily applicable to modern HCIs. We developed a paradigm aimed at mimicking important aspects of contemporary HCI to empirically test the effects of sporadic brief delays with an average duration of 1.6 s. Results showed performance decrements in the response directly following a delay in terms of increased reaction times and error rates. Furthermore, blocks in which delays occurred were less liked than blocks without delays, suggesting that delays may affect the emotional state. The data provide evidence that delays cause a significant deterioration of performance, and indicates that delays in contemporary HCI may negatively affect work productivity, work satisfaction, and health-and-safety. Suggestions for HCI design and the relationship to user interruption are discussed.

Why Research-Oriented Design Isn’t Design-Oriented Research: On the Tensions Between Design and Research in an Implicit Design Discipline

Human–computer interaction (HCI) is the discipline concerned with the design, evaluation, and implementation of interactive computing systems. Unlike many empirical sciences, HCI researchers do not typically solely study existing technologies, styles of interaction, or interface solutions. On the contrary, one of the core activities in contemporary HCI is to design new technologies – in the form of software and hardware prototypes – that act as vehicles through which HCI researchers’ ideas materialize and take on concrete form. Despite this situation, there is a very modest discussion in the discipline on the role of design as an activity in the research process; whether or not HCI could in fact be better understood as a design discipline than as an empirical science; and if, and if so how, the design element in HCI goes with its empirical claims.

Assessing users' subjective quality of experience with the world wide web: an exploratory examination of temporal changes in technology acceptance

Contemporary information technology—(IT)-related research has focused on use or user acceptance as a key dependent measure for valuing IT. By understanding the determinants of IT use, we gain descriptive information about successful IT, and prescriptive information for better deploying IT resources and improving their utility. Although there are several competing theories regarding IT use, research findings often cite their inability to account for temporal changes in usage behaviors. Furthermore, contemporary human–computer interaction perspectives often focus on the robust and growing literature surrounding usability and likeability; however, few studies have provided insight into the components of, or antecedents to, the utility dimension. This research attempts to address these gaps by introducing the construct of users'quality of experience as a potential mediator between the determinants of use and actual usage behaviors and their outcomes. A pilot survey concerning Internet usage generated potentially relevant items which were later refined into a questionnaire assessing each item's relative importance to perceptions of quality of experience. Initial indications suggest 10 of the items represent a temporally stable and unidimensional construct. Findings are also interpreted within the context of IT and cognitive/behavioral science perspectives, further providing for face validity of the quality of experience construct.