Midair gestural interaction has gained a lot of attention over the past decades, with numerous attempts to apply midair gestural interfaces with large displays (and TVs), interactive walls, and smart meeting rooms. These attempts, reviewed in numerous studies, utilized differing gestural techniques for the same action making them inherently incomparable, which further makes it difficult to summarize recommendations for the development of midair gestural interaction applications. Therefore, the aim was to take a closer look at one common action, translation, that is defined as dragging (or moving) an entity to a predefined target position while retaining the entity&#x2019;s size and rotation. We compared performance and subjective experiences (participants&#x2009;&#x3d;&#x2009;30) of four midair gestural techniques (i.e., by fist, palm, pinch, and sideways) in the repetitive translation of 2D objects to short and long distances with a large display. The results showed statistically significant differences in movement time and error rate favoring translation by palm over pinch and sideways at both distances. Further, fist and sideways gestural techniques showed good performances, especially at short and long distances correspondingly. We summarize the implications of the results for the design of midair gestural interfaces, which would be useful for interaction designers and gesture recognition researchers.

Vera Remizova

Yulia Gizatdinova

Veikko Surakka

Midair Gestural Techniques for Translation Tasks in Large-Display Interaction

Gender classification from human face images has attracted researchers over the past decade. It has great impact in different fields including defense, human-computer interaction, surveillance industry, and mobile applications. Many methods and techniques have been proposed depending on clear digital images and complex feature extraction preprocessing. However, most recent critical real systems use thermal cameras. This paper has the novelty of utilizing thermal images in gender classification. It proposes a unique approach called IRT_ResNet that adopts residual network (ResNet) model with different layer configurations: 18, 50, and 101. Two different datasets of thermal images have been leveraged to train and test these models. The proposed approach has been compared with convolutional neural network (CNN), principal component analysis (PCA), local binary pattern (LBP), and scale invariant feature transform (SIFT). The experimental results show that the proposed model has higher overall classification accuracy, precision, and F-score compared to the other techniques.

Alyaa J. Jalil

Naglaa M. Reda

Infrared Thermal Image Gender Classifier Based on the Deep ResNet Model

Software startups work in an uncertain environment with limited resources. Thus, user experience (UX) practices can help startups in their product development process and provide greater chances of survival for these companies. It is necessary to know what UX practices software startups have used, how they are using them, and their effects on the organization. Therefore, this paper aims to present a systematic mapping study (SMS) conducted through search engines and snowballing to identify UX practices used in software startups. The papers&#x2019; analysis identified thirty-six UX practices used by startups for product validation, design, and evaluation. However, the most emergent result extracted from the analysis was that only two of these practices were specified for software startups; in contrast, the others could be applied to various company types. In addition, several functions and ways of generating customer value through UX were identified.

Guilherme Corredato Guerino

Marcos de Assump&#xe7;&#xe3;o

Thiago Jos&#xe9; da Silva

Laura Hokkanen

Renato Balancieri

Gislaine Camila Lapasini Leal

User Experience Practices in Software Startups: A Systematic Mapping Study

The honeyword system is a password cracking detection technique that aims to improve the security of hashed passwords by making password cracking simpler to detect. Many honeywords (false passwords) accompany the sugarword (true password) to form the sweetwords (false and true passwords) for every user. If the attacker signs in using a honeyword, a silent alarm trigger shows that the honeyword system might be compromised. Many honeyword generation techniques are presented; each one has a flaw in the generating process, a lack of support for all honeyword characteristics, and a slew of honeyword problems. The harmony search algorithm (HSA), a metaheuristic intelligence algorithm inspired by music, is used in this article to offer a novel method for generating honeyword. The suggested honeyword generation technique will enhance the generating process, enhance honeyword characteristics, and address prior approaches&#x2019; shortcomings. This paper will show several previous honeyword generation techniques, explain the suggested one, discuss the experimental findings, and compare the new honeyword generation method with the previous ones.

Yasser A. Yasser

Ahmed T. Sadiq

Wasim AlHamdani

A Proposed Harmony Search Algorithm for Honeyword Generation

The usability evaluation of educational games is an important task, especially for children. By applying Jakob Nielsen&#x2019;s ten heuristics, most of the HCI designs can be evaluated, but when educational games are involved, where the user being observed is a child between the ages of six and eight, many questions arise. Is the observer trained well enough to observe the child&#x2019;s reactions to the game with regard to its memorability, learnability, ease of use, and enjoyment? Will it be necessary for the observer to have a training session exploring the game before evaluating a child? Our research suggests that a training module designed to train an untrained facilitator (observer) in how to evaluate four usability dimensions (learnability, memorability, ease of use, and enjoyment) would be very useful. The usability evaluation data was collected by observing users playing generic educational games, using the Mann&#x2013;Whitney U test, which was conducted by two groups of observers, one trained and one untrained. This was then reviewed, and a distinct difference was found between the results of evaluations in the two groups, thus validating the importance of training for an observer.

Marwan Alshar&#x2019;e

Ali Albadi

Malik Mustafa

Noman Tahir

Marya Al Amri

A Framework of the Training Module for Untrained Observers in Usability Evaluation Motivated by COVID-19: Enhancing the Validity of Usability Evaluation for Children&#x2019;s Educational Games

In our contemporary digital society, the smartphone is at the center of a powerful technological revolution affecting multiple domains. In the context of higher learning, the use of smartphones among students has been an area of interest. Previous studies on smartphone use and academic performance have generally focused on measuring the impact that smartphone use has on the academic performance of students. The purpose of this study is to examine the extent to which gender differences and the experience of a particular learning environment contributes to the use of smartphones for academic purposes. Data were collected through the use of a standardized self-report questionnaire completed by 300 first-year and 203 fourth-year undergraduate students from the University of Botswana. Our analysis is guided by the following specific objectives: first, to explore gender and the patterns of smartphone use for academic purposes; second, to appraise the contributing value of the experience of a learning environment on the use of smartphones to enhance academic achievement; and third, to examine smartphone use and its possible contribution to the performance outcome of students. Overall, we argue that the use of a smartphone for academic purposes is partly influenced by the extent to which a student is familiar with or understands the multiple contexts that shape his/her learning environment. For further studies in the field of smartphone use and academic performance, we suggest using multiple methods of data collection to uncover how students attach meanings to the use of smartphones and the role of smartphone use in improving their academic performance outcomes.

Gabriel Faimau

Kelebogile Tlhowe

Omphile Tlhaolang

Smartphone Use, Experience of Learning Environment, and Academic Performance among University Students: A Descriptive Appraisal

Social recommender systems, such as &#x201C;Who to follow&#x201D; on Twitter, utilize approaches that recommend friends of a friend or interest-wise similar people. Such algorithmic approaches have been criticized for resulting in filter bubbles and echo chambers, calling for diversity-enhancing recommendation strategies. Consequently, this article proposes a social diversification strategy for recommending potentially relevant people based on three structural positions in egocentric networks: dormant ties, mentions of mentions, and community membership. In addition to describing our analytical approach, we report an experiment with 39 Twitter users who evaluated 72 recommendations from each proposed network structural position altogether. The users were able to identify relevant connections from all recommendation groups. Yet, perceived familiarity had a strong effect on perceptions of relevance and willingness to follow-up on the recommendations. The proposed strategy contributes to the design of a people recommender system, which exposes users to diverse recommendations and facilitates new social ties in online social networks. In addition, we advance user-centered evaluation methods by proposing measures for subjective perceptions of people recommendations.

Ekaterina Olshannikova

Erjon Skenderi

Thomas Olsson

Sami Koivunen

Jukka Huhtam&#xe4;ki

Utilizing Structural Network Positions to Diversify People Recommendations on Twitter

Cultivating in greenhouses constitutes a fundamental tool for the development of high-quality crops with a high degree of profitability. Prediction and control models guarantee the correct management of environment variables, for which fuzzy inference systems have been successfully implemented. The purpose of this review is determining the various relationships in fuzzy inference systems currently used for the modelling, prediction, and control of humidity in greenhouses and how they have changed over time to be able to develop more robust and easier to understand models. The methodology follows the PRISMA work guide. A total of 93 investigations in 4 academic databases were reviewed; their bibliometric aspects, which contribute to the objective of the investigation, were extracted and analysed. It was finally concluded that the development of models based in Mamdani fuzzy inference systems, integrated with optimization and fuzzy clustering techniques, and following strategies such as model-based predictive control guarantee high levels of precision and interpretability.

Sebastian-Camilo Vanegas-Ayala

Julio Bar&#xf3;n-Velandia

Daniel-David Leal-Lara

A Systematic Review of Greenhouse Humidity Prediction and Control Models Using Fuzzy Inference Systems

About this journal

Advances in Human-Computer Interaction is an interdisciplinary journal that publishes theoretical and applied papers covering the broad spectrum of interactive systems.

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Advances in Human-Computer Interaction maintains an Editorial Board of practicing researchers from around the world, to ensure manuscripts are handled by editors who are experts in the field of study.

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Advances in Human-Computer Interaction - Table of contents 2022

Advances in Human-Computer Interaction | Hindawi

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Advances in Human-Computer Interaction is an interdisciplinary journal that publishes theoretical and applied papers covering the broad spectrum of interactive systems.

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Advances in Human-Computer Interaction