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Voiceprint authentication provides great con- venience to users in many application scenarios. However, it easily suffers from spoofing attacks including speech synthesis, speech conversion and speech replay. Liveness detection is an effective way to resist these attacks. But existing methods suffer from many disadvantages, such as extra deployment costs due to precise data collection, environmental disturbance, high computational overhead and operational complexity. A uniform platform that can offer Voiceprint Authentication as a Service (VAaS) over the cloud is also lacked. Hence, it is imperative to design an economic and effective method for liveness detection in voiceprint authentication. In this paper, we propose a novel liveness detection method named LiVoAuth for voiceprint authentication. It applies a randomly generated vector se- quence as Liveness Detection Mode (LDM), corresponding to a random challenge code used for authentication. We implement LiVoAuth and conduct a series of user studies to evaluate its performance in terms of accuracy, stability, efficiency, security, and user acceptance. Experimental re- sults demonstrate its advantages compared with cutting- edge methods.

This research aimed to analyze the User Experience analysis of the Zoom Meeting application according to the perspectives of lecturers and students during online learning in the new normal era because the Zoom application is considered to have numerous outstanding features. The population in this research were 2 lecturers and 123 students of the Bachelor of Elementary School Teacher Education Study Program in the 2021/2022 academic year in Bali. The purposive sampling technique was used along with the questionnaire and in-depth interview. As a result, the attractiveness, clarity, efficiency, and stimulation aspects scale got the average positive result from the questionnaire because the value obtained was more than 0.8. Furthermore, the average questionnaire scale was neutral for the accuracy and novelty aspects because the values obtained were from -0.8 to 0.8. Therefore, the accuracy aspect has the lowest value compared to other aspects. It was also verified from the data obtained from the in-depth interview results, which showed various problems and obstacles experienced by users in terms of the accuracy of the Zoom Meeting application when used as an online learning medium, i.e., difficulties in conducting disciplinary assessments and conducting lectures that required practical skills. Although Zoom has many benefits for online learning, it still has several limitations that must be addressed by lecturers, students, and Zoom developers.

As many countries experience the emergence of new waves of Covid-19, many governments around the world have reminded their citizens of the need for an engaging intervention that could improve compliance with Covid-19 safe behaviors using the media general public or social media. In the face of the serious threat of Covid-19, immunity issues are currently the subject of various research and studies. A promising approach is to use video game culture to educate and train citizens to healthily adopt eating habits to strengthen the immune system. The objective of this study is to develop a prototype of a serious game (SG) on how to strengthen the immune defenses in order to be able to fight a coronavirus infection and to constitute an antivirus barrier. After defining the learning objectives by interviewing the stakeholders, we searched the scientific literature to establish the relevant theoretical bases. The learning contents have been validated by biology teachers. The learning mechanisms were then determined based on the learning objectives. The obtained experimental results show that 92% of the participants in the study have appreciated the quality of the scenario and the way in which the concept of interaction between the different game elements was presented.

Using standard handheld interfaces for VR locomotion may not provide a believable self-motion experience and can contribute to unwanted side effects such as motion sickness, disorientation, or increased cognitive load. This paper demonstrates how using a seated leaning-based locomotion interface --HeadJoystick-- in VR ground-based navigation affects user experience, usability, and performance. In three within-subject studies, we compared controller (touchpad/thumbstick) with a more embodied interface ("HeadJoystick") where users moved their head and/or leaned in the direction of desired locomotion. In both conditions, users sat on a regular office chair and used it to control virtual rotations. In the first study, 24 participants used HeadJoystick versus Controller in three complementary tasks including reach-the-target, follow-the-path, and racing (dynamic obstacle avoidance). In the second study, 18 participants repeatedly used HeadJoystick versus Controller (8 one-minute trials each) in a reach-the-target task. To evaluate potential benefits of different brake mechanisms, in the third study 18 participants were asked to stop within each target area for one second. All three studies consistently showed advantages of HeadJoystick over Controller: we observed improved performance in all tasks, as well as higher user ratings for enjoyment, spatial presence, immersion, vection intensity, usability, ease of learning, ease of use, and rated potential for daily and long-term use, while reducing motion sickness and task load. Overall, our results suggest that leaning-based interfaces such as HeadJoystick provide an interesting and more embodied alternative to handheld interfaces in driving, reach-the-target, and follow-the-path tasks, and potentially a wider range of scenarios.

BukuWarung has been known as a MSME’s bookkeeping application in Indonesia. As the features developed, there were disappointed responses from Playstore reviews, social media, and research interviews who complained about the usability aspect of this application, thus triggering the desire for users to stop using the application. This condition motivates the author to assess the impact level of usability in aspects of Effectiveness, Efficiency, and Satisfaction on user retention. This study used a partial least square–structural equation model method. The total of 248 user samples was obtained using simple random sampling and voluntary response techniques. The research uses CSUQ, as well as questions for user retention. For data testing used Ms. Excel and SmartPLS version 3.3.3. According to the measurement model, 7 of 22 all variables were deleted. This study proves that Effectiveness, Efficiency, and Satisfaction have a positive and significant effect of up to 74.8% on user retention. However, the size of influence and relative influence is weak on user retention. User retention indicators affected by usability are increasing purchases as tenure grows, customer referrals, and premium prices. The implication for BukuWarung is to conduct usability testing on each feature.

Spreadsheet-based tools provide a simple yet effective way of calculating values, which makes them the number-one choice for building and formalizing simple models for budget planning and many other applications.A cell in a spreadsheet holds one specific value and gives a discrete, overprecise view of the underlying model. Therefore, spreadsheets are of limited use when investigating the immanent uncertainties of such models and answering what-if questions. Existing extensions typically require a complex modeling process that cannot be smoothly embedded in a tabular layout.In Fuzzy Spreadsheet, a cell can hold and display the distribution of values. This integrated uncertainty handling immediately conveys sensitivity and robustness information. The fuzzification of the cells enables calculations not only with precise values but with distributions, and probabilities. We conservatively added and carefully crafted visuals to maintain the look and feel of a traditional spreadsheet while facilitating what-if analyses.Given a user-specified reference cell, Fuzzy Spreadsheet automatically extracts and visualizes contextually relevant information, such as impact, uncertainty, and degree of neighborhood, for the selected and related cells.To evaluate its usability and the perceived mental effort required, we conducted a user study.The results show that our approach outperforms traditional spreadsheets in terms of answer correctness, response time, and perceived mental effort for almost all tasks tested.

Previous research emphasizes the importance of well-being in old age and its association with positive mental and physical health at earlier stages of aging during midlife. Acceptance and Commitment Therapy has the potential to support positive aging processes. This study examines the feasibility and acceptability of a new unguided eHealth ACT module in a population from 40 years onwards. Data was collected at two measurement points in time (before and after completion of the ACT module). In total three-hundred and thirteen participants (range=40-75 years; Mean(SD)=54 years (8.3); 76% female) had eight weeks access to the ACT module and responded to the feasibility questionnaire, upon completion of the module. Logged data (time spent online per session and in total, number of attended sessions) was also analyzed. Of the respondents, 76% reported a completion rate of 75%-100%. On average 3.5 hours (SD= 6.4) per week were spent on the module and practicing the ACT skills. The mean evaluation of the module was 7.4 (SD = 1.2, range=1-10). Approximately 80% of the participants rated each session as (very) good. Absence of guidance was marked as a limitation. The results indicate good feasibility and acceptance of this unguided eHealth module. This is a promising result as this is, to our knowledge, the first study applying an eHealth ACT module to the general population in the context of positive aging. The effectiveness results will be addressed in a future paper.

Secure and usable user authentication is the first line of defense against cyber attacks on smart end-user devices. Advanced hacking techniques pose severe threats to the traditional authentication systems based on the password/PIN/fingerprint. We propose MagAuth, a secure and usable two-factor authentication scheme with commercial off-the-shelf (COTS) wrist wearables with magnetic strap bands to enhance the security and usability of password-based authentication for mobile touchscreen devices. In MagAuth, a user enrolls a self-chosen unlock pattern or touch gesture into his touchscreen device by performing it with the same hand the magnetic wrist wearable is on. The chosen unlock pattern or touch gesture serves as the first authentication factor, and the user's behavioral features manifested in the magnetic field changes during his finger movement correspond to the second factor. The user can unlock his touchscreen device only when both authentication factors can be validated. Comprehensive user experiments confirm the high security and usability of MagAuth. In particular, MagAuth achieves an average true-positive rate up to 96.3% and a false-positive rate no larger than 8.4%. Moreover, we show that MagAuth is highly resilient to various attacks.

As smart devices are increasingly getting deployed in distinct scenarios it is important to examine how the various demands of these practical uses will affect the dynamics of protection. This study provides an outline of the connection among the various security threats, specifications, implementations, and network safety as well as an overview. In addition, a few of the device communication services are often overviewed, evaluating the protection mechanisms. The Internet of Things (IoT) has been a focal point in the previous few years. On analysis, here are several kinds of problems and difficulties with the tremendous ability of the IoT. For IoT technologies, applications, and networks, cybersecurity is one of the crucial challenges. This study discusses the work advancement of IoT to examine every main part of IoT, and finds how some safety problems and concerns have to be recognized and discusses them momentarily. To secure information privacy, professional conduct, honesty, encryption, intrusion detection, and capability to recognize as well as versatility, interoperability, and usability, reliable and usable IoT protection is needed to be brought into account. In terms of certain realities, new IoT approaches from the scientific, educational and industrial sectors are presented and addressed by analyzing a few of the current study in the IoT field Depending on the results of this report, it is important to develop and implement suitable IoT applications that can ensure integrity, security, and honesty in interconnected conditions.

Preventive maintenance practices have been proven to reduce maintenance costs in many industries. In the mining industry, preventive maintenance is the main form of maintenance, especially for mobile equipment. With the increase of sensor data and the installation of wireless infrastructure within underground mines, predictive maintenance practices are beginning to be applied to the mining equipment maintenance process. However, for the transition from preventive to predictive maintenance to succeed, researchers must first understand the maintenance process implemented in mines. In this paper, we conducted interviews with 15 maintenance experts from 7 mining sites (6 gold, 1 diamond) across East-Canada to investigate the maintenance planning process currently implemented in Canadian mines. We documented experts’ feedback on the process, their expectations regarding the introduction of predictive maintenance in mining, and the usability of existing computerized maintenance management software (CMMS). From our results, we compiled a summary of actual maintenance practices and showed how they differ from theoretical practices. Finally, we list the Key Performance Indicators (KPIs) relevant for maintenance planning and user requirements to improve the usability of CMMS.

With the emergence of sophisticated bionic prostheses for upper limb amputees, the selection of the most appropriate device for each individual might become a challenge. Owing to the cost and complexity of such devices and the required time to learn their usage, it would be relevant to facilitate access to a wide range of them for intensive testing in ecological environments. In this paper, we report the development of a virtual reality setup that emulates three representative bionic prostheses and their key grasp selection methods. Twelve able-bodied participants and one transradial amputee participated in a study whose objective was to assess the influence of this setup in quantifying the perceived usability of the virtualised devices, and thus to guide a better-informed selection process of a preferred device based on the most suitable grip selection method for each individual. Results show that the user learning curve with the three simulated devices and their perceived usability was different, and that this had an influence on the final device selection. In particular, more than half of the users changed their favorite device after the experiment in virtual reality. In sum, this paper provides a proof of concept that virtual reality is a valuable tool to support a better-informed selection process of an upper limb myoelectric prosthesis that is personalized to individual preferences and capabilities by mediating its learning phase.

Any organization that intends to use component-based software development, like outsourcing software, must first evaluate existing components against system requirements to find the best fit among many alternatives. As a result, there should be a mechanism to help with decision-making. Our proposed methodology tries to select the best alternative among available components, using the best decision-making approach. As an integrated method for order preference, the methodology in this paper uses two well-known criterion decision-making procedures, namely Analytic Hierarchy Process (AHP) and Simple Additive Weighting (SAW). By analyzing and selecting the optimal solution among a variety of Out Sourcing (OS) modules, the new model design makes the decision-making process easier. We evaluated two software attributes and predicted which was more effective. In this case, the advantage of utilizing AHP is that it allows the developer to evaluate the structure of the OS selection problem and calculate weights for the chosen criteria. After that, the SAW technique is used to calculate the alternatives ratings for OS components. The integration strategy used in our model and the resulting preference indication, which is produced as an explicit numeric value.

Revisões de literatura são utilizadas para levantamento de evidências de intervenções na área de saúde. Estudos têm apresentado problemas relacionados à busca de bibliografia para levantamento de evidência na Análise do Comportamento. O objetivo do presente estudo foi avaliar a utilização de uma plataforma de currículos acadêmicos (Plataforma Lattes) para busca de artigos fundamentados na Análise do Comportamento que se relacionavam com temas da área de saúde. Uma busca foi realizada para as áreas do conhecimento por meio dos descritores “Psicologia da Saúde” e “Análise do Comportamento”. Os currículos encontrados na Plataforma Lattes foram explorados para busca de artigos publicados nos últimos cinco anos. O uso de um repositório de currículos acadêmicos mostrou-se uma ferramenta possível para levamento de literatura — evidências.

This study aims to analyze the users´ perception regarding the innovations of the individual public transportation in Federal District, focused on Uber company. Throughout Brazil, the individual public transportation was known as monopolized by taxi service. The lack of competition led to low service of service. However, with the technological development, private companies started to develop competitive and innovative forms for entering the market. Through the tool for multi-criterion analysis was verified the user perception in regard to the service provided by Uber. The survey of data was carried out in two ways. First, through group discussion with experts in transport of UnB and subsequently through the implementation of forms with the service users, through targeted dissemination carried out by social networks and via email. For analysis of the data the Multi-criteria Methodology for Supporting the Constructivist Decision (MCDA-C) was used, so that the qualitative data could be quantified. This methodology allows the consideration from the experts´ view of the experts for, from them, understand the users´. The survey results showed how the innovative processes that aim to raise the quality of care and implementation of individual transportation services in the Federal District are relevant to users.

Abstract. Background: The Systematic Tailored Assessment for Responding to Suicidality (STARS) is a client-centered, psychosocial needs-based assessment protocol. This semistructured interview obtains client prioritized indicators that contribute to suicidality and informs commensurate care responses for preventing suicide. Aim: To pilot the feasibility, client-centeredness, and usability of the STARS protocol, including clinicians' perceptions of ease of use; content validity; and administration within the community setting. Method: A convenience sample of clinicians who undertook assessment and/or intervention with suicidal persons and had used STARS between mid-2016 and early 2017 completed an online survey assessing feasibility, client-centeredness, and usability of STARS. Results: Of the 51 clinicians who entered the survey, 42 (82.3%; aged 25–74; 69% female) completed it. Overall, perceptions of feasibility and usability of STARS were positive, particularly regarding client-centeredness of the protocol and confidence in information obtained for screening suicidality and informing needs-based priority responses. Limitations: The pilot findings are limited by the use of a small convenience sample and the low completion rate of clinicians with STARS training. Conclusion: STARS was perceived as a feasible and useful psychosocial needs-based assessment protocol. Suggestions for improving STARS, training requirements, and application to diverse populations are outlined.

E-learning can address some of the unmet needs of learners and educational communities; however, not all learners and educators accept e-learning as a delivery modality. This research endeavored to study the factors which affect e-learning acceptance among Iranian post-graduate students using the Davis Technology Acceptance Model (TAM) and to identify the changes which would facilitate their improved acceptance and subsequent wider use of e-learning. This descriptive-correlation study was conducted by surveying 320 Iranian postgraduate students using a self-reporting questionnaire. Structural equation modeling was used for data analysis through LISREL software. Results revealed sufficient validity and reliability of the TAM among Iranian postgraduate medical students. Perceived ease of use, perceived usefulness of e-learning, students’ attitudes toward e-learning, and the intention to use e-learning positively affected e-learning’s acceptance (p < 0.05) among Iranian postgraduate students. According to the results, attitudes toward e-learning have more predictive power than other TAM constructs. Therefore, emphasis on students’ favorable attitudes toward e-learning can be effective in accelerating its acceptance and will progress students’ learning outcomes.

In multiple coordinated views (MCVs), visualizations across views update their content in response to users' interactions in other views. Interactive systems provide direct manipulation to create coordination between views, but are restricted to limited types of predefined templates. By contrast, textual specification languages enable flexible coordination but expose technical burden. To bridge the gap, we contribute Nebula, a grammar based on natural language for coordinating visualizations in MCVs. The grammar design is informed by a novel framework based on a systematic review of 176 coordinations from existing theories and applications, which describes coordination by demonstration, i.e., how coordination is performed by users. With the framework, Nebula specification formalizes coordination as a composition of user- and coordination-triggered interactions in origin and destination views, respectively, along with potential data transformation between the interactions. We evaluate Nebula by demonstrating its expressiveness with a gallery of diverse examples and analyzing its usability on cognitive dimensions.

The challenge to incorporate usability evaluation values and practices into agile development process is not only persisting but also systemic. Notable contributions of researchers have attempted to isolate and close the gaps between both fields, with the aim of developing usable software. Due to the current absence of a reference model that specifies where and how usability activities need to be considered in the agile development process. This paper proposes a model for identifying appropriate usability evaluation methods alongside the agile development process. By using this model, the development team can apply usability evaluations at the right time at the right place to get the necessary feedback from the end-user. Verification of the proposed model was conducted using the focus group method by experts from industry domain.

Android overlay enables one app to draw over other apps by creating an extra View layer atop the host View, which nevertheless can be exploited by malicious apps (malware) to attack users. To combat this threat, prior countermeasures concentrate on restricting the capabilities of overlays at the OS level while sacrificing overlays usability; recently, the overlay mechanism has been substantially updated to prevent a variety of attacks, which however can still be evaded by considerable adversaries. To address these shortcomings, a more pragmatic approach is to enable early detection of overlay-based malware during the app market review process, so that all the capabilities of overlays can stay unchanged. For this purpose, in this paper we first conduct a large-scale comparative study of overlay characteristics in benign and malicious apps, and then implement the OverlayChecker system to automatically detect overlay-based malware for one of the worlds largest Android app stores. In particular, we have made systematic efforts in feature engineering, UI exploration, emulation architecture, and run-time environment, thus maintaining high detection accuracy (97% precision and 97% recall) and short per-app scan time (1.7 minutes) with only two commodity servers, under an intensive workload of 10K newly submitted apps per day.

SIMPONIK is one of the websites developed by the Furniture and Wood Processing Industry Polytechnic to answer the challenges during online learning due to covid 19 and the large number of guests visiting because it is located in an Industrial Estate. To improve the website's service and user experience, there must be testing of the website's usability. The purpose of this study is to test the usability of the SIMPONIK website as a basis for improving the appearance and services available on the website. This study uses the System Usability Scale (SUS) method by distributing questionnaires to 100 respondents. From the results of this study, the SUS score was 76,025, which means the SUS category is acceptable (71-100). Although the results are categorized as acceptable, there must be improvements must be made, especially in terms of practicality and convenience for users.

This study sought to investigate the usability of artificial intelligence (AI) for the improvement of records management activities at the Council for Scientific and Industrial Research (CSIR) in South Africa. Usability of AI and intelligent robotic machines for the management of records plays a crucial role in ensuring that records management activities are improved and managed effectively and efficiently. However, usability issues are critical in many AI systems, where human intelligence (HI) works with the system to work out and apply results (as with speech system). The convergent mixed methods research approach was applied and data were collected using interviews and questionnaires techniques. A questionnaire was administered to three professional repositories and indexers, two archives’ technicians and one data librarian. Interviews were conducted with one portfolio manager and one records manager. Data were analysed thematically and statistically and presented using tables and figures. AI has the capability to replace records practitioners since it can perform activities performed by records practitioners. This transition can have a negative impact on the usability of AI to improve the records management activities at the CSIR. The study revealed that AI and intelligent robotic machines can be used in the improvement of records management activities and can manage records effectively at the CSIR. The study proposed a framework on the usability of AI for the improvement of records management activities at the CSIR. It is hoped that the framework proposed will serve as a guideline on the usability of AI for the improvement of records management activities in the archives and records management sector.

The Internet of Things (IoT) has been growing over the past few years due to its flexibility and ease of use in real-time applications. The IoT’s foremost task is ensuring that there is proper communication between different types of applications and devices, and that the application layer protocols fulfill this necessity. However, as the number of applications grows, it is necessary to modify or enhance the application layer protocols according to specific IoT applications, allowing specific issues to be addressed, such as dynamic adaption to network conditions and interoperability. Recently, several IoT application layer protocols have been enhanced and modified according to application requirements. However, no existing survey articles have focused on these protocols. In this article, we survey traditional and recent advances in IoT application layer protocols, as well as relevant real-time applications and their adapted application layer protocols for improving performance. As changing the nature of protocols for each application is unrealistic, machine learning offers means of making protocols intelligent and able to adapt dynamically. In this context, we focus on providing open challenges to drive IoT application layer protocols in such a direction.

Humans are embarking on a new era of space exploration with the plan of sending crewed spacecraft to the Moon, Mars, and beyond. Extravehicular activities (EVAs) will be an essential part of the scientific activities to be carried out in these missions, and they will involve extensive geological fieldwork. These EVAs entail many challenges as real-time support from ground control cannot be provided to astronauts. Hence, new human–machine interfaces are urgently needed to enhance mission autonomy for astronauts and reduce ground communication dependability for real-time operations. This study introduces an Augmented Reality (AR) Internet of Things tool for astronauts to carry out geological activities. It proposes a theoretically-informed user-centred design method supported by expert feedback and an evaluation method. The tool was assessed via questionnaires and semi-structured interviews with European Space Agency (ESA) astronauts and geological field activities experts. Content analysis of the interviews revealed that user satisfaction was the first most mentioned (32% of 139 quotes) usability aspect. Key design factors identified were: displaying solely important information in the field of view while adjusting it to the user's visual acuity, easy usage, extensibility, and simplicity. User interaction was the second most mentioned (24% of 139 quotes) usability aspect, with voice seen as the most intuitive input. Finally, this research highlights important factors determining the usability and operational feasibility of an AR tool for analogue training missions and provides a foundation for future design iterations and an eventual integration of AR into the spacesuit's visor.

The increased availability of quantitative historical datasets has provided new research opportunities for multiple disciplines in social science. In this article, we work closely with the constructors of a new dataset, CGED-Q (China Government Employee Database-Qing), that records the career trajectories of over 340,000 government officials in the Qing bureaucracy in China from 1760 to 1912. We use these data to study career mobility from a historical perspective and understand social mobility and inequality. However, existing statistical approaches are inadequate for analyzing career mobility in this historical dataset with its fine-grained attributes and long time span, since they are mostly hypothesis-driven and require substantial effort. We propose CareerLens, an interactive visual analytics system for assisting experts in exploring, understanding, and reasoning from historical career data. With CareerLens, experts examine mobility patterns in three levels-of-detail, namely, the macro-level providing a summary of overall mobility, the meso-level extracting latent group mobility patterns, and the micro-level revealing social relationships of individuals. We demonstrate the effectiveness and usability of CareerLens through two case studies and receive encouraging feedback from follow-up interviews with domain experts.

In this paper, we provide the design and implementation of UOIT, a text entry method optimized for smartwatches. UOIT uses only one page where a user can see and tap directly for entry without any additional actions, such as zoom-in/zoom-out and swipes, which are required in the existing entry methods. To fully utilize the constrained screen space and to address the "fat finger" problem, we use a technique called "drawing-like typing", which reduces the 26 small alphabetic keys into 13 large keys with a dual input property. To evaluate the performance of UOIT, we conducted two user studies while varying the learning period. In the short-term experiments (i.e., two days), we observed a fast learning curve of users when using the UIOT keyboard. Moreover, with the long-term experiments (i.e., a month), we show that users can type as fast as QWERTY keyboard but with much less errors. Moreover, UOIT outperforms the state-of-the-art keyboard in both speed and error rate.

Resumen: Este documento presenta la evaluación realizada de la Herramienta EC para medir la economía circular en el sector turís􀆟co, con enfoque en hotelería y restauración. La evaluación se realiza con un test de usabilidad y la Herramienta EC es evaluada por cinco expertos en el sector y en las tres provincias de la Comunidad Valenciana. Los resultados muestran que la experiencia de los evaluadores varía según la dimensión analizada, pero ofrecen ideas de mejora en cada una de ellas que son fáciles de incorporar. Evaluadores de la Herramienta EC: Bartolomé Marco Lajara (Universidad de Alicante) Luis Martínez Cháfer (Universitat Jaume I) Luis Miret Pastor (Universitat Politècnica de València) Joaquín Sánchez Planelles (Universitat Politècnica de València) Francisco Puig Blanco (Universitat de València), La investigación incluida en esta comunicación ha sido financiada por la Agencia Valenciana de la Innovación, en el marco del proyecto "Creación de una Plataforma de Innovación para el Impulso e Implementación de una Estrategia de Economía Circular en el Sector Turístico de la Comunidad Valenciana" (INNACC/2021/49), coordinado por Marival Segarra Oña (Universitat Politècnica de València).

This paper reports on research being conducted under the National Research Council of Canada’s Aging in Place Program. The objective of this program is to evaluate and assist in the adaptation of assistive technologies for older adults living at home. The aims are to produce guidelines and prototypes needed to design safe, usable, and affordable aging in place technology solutions for virtual care. In preparation for this initiative, relevant findings are presented from a scoping review of the literature. Additionally, we present the framework for surveying older adults’ perspectives on their lived experiences with virtual care and digital technologies during the COVID-19 pandemic, which drove uptake of virtual care, particularly in critical areas such as cardiac rehabilitation. Here we discuss the target population for surveillance and describe the survey design, validation, and sampling approach that could achieve the widest range of perspectives; identify gaps, barriers, and challenges. Additionally, we explore remote usability assessment methods available for aging in place technology co-design and evaluation efforts., 9th International Conference, ITAP 2023, Held as Part of the 25th HCI International Conference, HCII 2023, July 23–28, 2023, Copenhagen, Denmark, Series: Lecture Notes in Computer Science

As relações humanas, são permeadas pelo uso de artefatos que influenciam as ações e o modo do homem interagir com o mundo ao seu redor. A teoria ator-rede, entende que o ser humano possui uma relação simétrica com os artefatos que utiliza, sendo que ambos são agentes sociais capazes de influenciar um ao outro. Diante disso, discute-se qual seria o papel do designer, no que tange construir métodos capazes de suprir a demanda envolvendo o Design Atitudinal e o Design Emocional, visando preencher esta lacuna que ultrapassa a funcionalidade e a usabilidade dos artefatos, os quais precisam trazer também satisfação ao ser humano ao ponto de gerar a sensação de habitabilidade do artefato utilizado no seu dia a dia.

In the rapid development of technology, almost all activities are carried out online, activities become timeless so that many students have difficulty in managing time between lectures and other activities. So that students must be able to organize their activity schedule, record tasks and activities that must be completed. One of the efforts that can be made is to use colega products which are technology products to remind activities. The purpose of this research is to redesign the Colega mobile application interface that is suitable and easy to use based on student needs to increase the level of usability with the learner-centered design method., this method is a design process that focuses on the needs of learner, by performing 5 stages, namely Specify the context of use, Specify user requirements, Product design solution, and Evaluate against user requirements. The product developed using this method, the principle of this method is a collaboration that allows learner to develop, test, and analyze their ideas for the product to be made. Interface design and interaction testing using the System Usability Scale. the results of usability testing on the interface obtained a value of 60.62 to 78.12. With the test results obtained an increase in value in the usability aspect. So it can be concluded that the usability value falls into the good and acceptable category.

Usability refers to the system's functionality by the user, allowing the system to be used with ease of learning, efficiency in carrying out tasks and satisfaction. The article presents the design and development of an online course about structural mathematics concepts with a project-based learning approach. With this study, we intend, through the development of an online course, to explore the contribution of project-based learning to approach mathematical structural concepts. The methodological option was development research, fulfilling the following phases of the protocol: (1) preliminary investigation, (2) theoretical embedding, (3) empirical testing and (4) documentation, analysis and reflection on process and outcomes. We started with an exploratory analysis aimed at identifying a group of teachers' knowledge about structural mathematical concepts and the potential of a project-based learning to support students in apprehending these concepts. Based on the data obtained, the design and development of the online course were carried out. Then, heuristic evaluation tests were conducted with experts and usability tests with the target audience to assess the adoption of the online course. The online course was designed to involve teachers in learning mathematics concepts through a project methodology. In the preliminary investigation, all teachers showed interest in knowing the project learning methodology and identified concepts that, from their practice, are usually difficult for their students. In the heuristic evaluation test with the experts, linguistic, structural and course content corrections were made. The results allow us to say that the online course with the project- based learning approach responded to the target audience's needs, arousing their interest in using project learning in teaching mathematics structural concepts.

International audience; Objective: Two tools are currently available in the literature to evaluate the usability of medication alert systems, the instrument for evaluating human factors principles in medication-related decision support alerts (I-MeDeSA) and the tool for evaluating medication alerting systems (TEMAS). This study aimed to compare their convergent validity, perceived usability, usefulness, strengths, and weaknesses, as well as users' preferences.Method: To evaluate convergent validity, two experts mapped TEMAS' items against I-MeDeSA's items with respect to the usability dimensions they target. To assess perceived usability, usefulness, strengths, and weaknesses of both tools, staff with expertise in their medication alerting system were asked to use French versions of the TEMAS and I-MeDeSA. After the use of each tool, participants were asked to complete the System Usability Scale (SUS) and answer questions about the understandability and usefulness of each tool. Finally, participants were asked to name their preferred tool. Numeric scores were statistically compared. Free-text responses were analyzed using an inductive approach.Results: Forty-five participants from 10 hospitals took part in the study. In terms of convergent validity, I-MeDeSA focuses more on the usability of the graphical user interface while TEMAS considers a wider range of usability principles. Both tools have a fair level of perceived usability (I-MeDeSA' SUS score = 61.85 and TEMAS' SUS score = 62.87), but results highlight that revisions are necessary to both tools to improve their usability. Participants found TEMAS more useful than I-MeDeSA (t = -3.63, p =.005) and had a clear preference for TEMAS to identify problems in formative evaluation (39 of 45; 0.867, p

Virtual reality (VR) users interact with virtual objects using motion-tracked controllers. While many devices utilise abstract button pushes for interactions, some allow for limited finger tracking by estimating finger positions based on sensors. In this study, the Vive Wands and the Valve Index controllers were compared in three tasks: direct interaction with objects (throwing), tool usage (bow) and indirect control of a character (remote-control). Forty-four participants completed each task with both devices and rated the usability of the device after each task. Results showed only differences in preference for the remote-control task. Some participants noted that using the thumbstick of the Index instead of the touchpad of the Wands controller felt more natural in this task. However, performance did not differ between devices in any task. Therefore, future research should not only compare designs of controllers but also consider assets and interactions, as there may be preference and performance differences for certain combinations.

This study aims to explore the usability of the virtual robotics programming curriculum (VRP-C) for robotics programming teaching. Pre-service computer science (CS) teachers were trained for robotics programming teaching by using VRP-C in a scientific education activity. After training, views of the participants were revealed by using a scale and an evaluation form consisting of open-ended questions. Results show that VRP-C is compatible with the curriculum for robotics programming teaching in schools, and pre-service CS teachers tend to use VRP-C in their courses. They think that VRP-C will be beneficial for robotics programming teaching in terms of content, functionality, and cost. Compatibility, visual design, feedback, time management, fiction, gamification, and cost are the characteristics that increase the usability of VRP-C. VRP-C can be used as an online tool for robotics programming training due to the necessity of transition to distance education because of the COVID-19 pandemic.

Usability is considered a major success factor for current and future decision support systems. Such systems are increasingly used to assist human decision-makers in high-stakes tasks in complex domains such as health care, jurisdiction or finance. Yet, many if not most expert systems—especially in health care—fail to deliver the degree of quality in terms of usability that its expert users are used to from their personal digital consumer products. In this article, we focus on clinical decision support systems (CDSS) as an example for how important a human-centered design approach is when designing complex software in complex contexts. We provide an overview of CDSS classes, discuss the importance of systematically exploring mental models of users, and formulate challenges and opportunities of future design work on CDSS. We further provide a case study from a current research project to illustrate how we used codesign as a practical approach to produce usable software in a real-world context.Practical Relevance: We make a point for usability to be considered a major success factor and non-negotiable characteristic of expert software. With software evolving into virtual coworkers in terms of supporting human decision-making in complex, high-risk domains, the necessity of and demand for systems that are unambiguously understandable and interpretable for their expert users have never been higher. We show that this is a real-world problem with high practical relevance by describing our work in the domain of clinical decision support systems (CDSS) as an example. We introduce the topic and a classification of CDSS. Thus, we highlight a conceptual framework of how to approach complex domains from a technology designer’s point of view. We continue by explaining why usability must be regarded as a major goal in software development. We derive challenges and opportunities that may well be transferred to other domains. Finally, be including a real-world example from our own professional work we propose a practical approach towards taking the challenges and exploiting the associated opportunities.

Brain-computer interface (BCI) performance is often impacted due to the inherent non-stationarity in the recorded EEG signals coupled with a high variability across subjects. This study proposes a novel method using Logistic Regression with Tangent Space-based Transfer Learning (LR-TSTL) for motor imagery (MI)-based BCI classification problems. The single-trial covariance matrix (CM) features computed from the EEG signals are transformed into a Riemannian geometry frame and tangent space features are computed by considering the lower triangular matrix. These are then further classified using the logistic regression model to improve classification accuracy. The performance of LR-TSTL is tested on healthy subjects’ dataset as well as on stroke patients’ dataset. As compared to existing within-subject learning approaches the proposed method gave an equivalent or better performance in terms of average classification accuracy (78.95±11.68%), while applied as leave-one-out cross-subject learning for healthy subjects. Interestingly, for the patient dataset LR-TSTL significantly (p

Benefiting from the rapid development of communication technology and Internet of Things (IoT) devices, crowdsensing is on the rise. Sensor data from IoT devices can be requested for data analysis and utilization, however, the collected data of an object from multiple devices are usually different. Therefore, how to extract the most reliable data from numerous data has become an important topic, and truth discovery receives great attention. These collected data often contain personal sensitive information, if users’ privacy cannot be protected, many users are unwilling to contribute their data, and the usability of the published data will be greatly reduced. In this article, a robust privacy-preserving truth discovery scheme is proposed to simultaneously achieve the reliability and privacy of data. Specifically, the data are collected and encrypted before it is sent from the user. Compared with the existing works, there are two additional benefits, trusted third party and noncolluding platforms are not necessary anymore, hence the robustness is improved and single-point failure bottlenecks are eliminated. Besides, the proposed RPPTD is secure against many known attacks in open wireless networks, and the human-factor-aware differential aggregation attack. Finally, the performance evaluation indicates that our scheme is efficient and suitable for the practical environment.

OBJECTIVE Innovative strategies are needed to reduce young adult drinking. Real-time feedback via mobile health (mHealth) technology (e.g., smartphone devices/apps) may facilitate moderate drinking, yet requires evidence of feasibility, acceptability, and usability. METHOD Young adults reporting frequent heavy drinking (N = 99, Mage = 23, 51% male) participated in a manualized, brief, motivational interview on recent typical and peak blood alcohol concentration (BAC), then were randomized to use 1 of the 3 forms of technology: (a) smartphone breathalyzer device/app; (b) app that estimates BAC based on factors including sex, weight, number/types of drinks over time; or (c) self-text messaging after each drink. Technologies were tested initially in small-group laboratory alcohol self-administration sessions. Participants then completed a 2-week field test wherein they had free access to all three technologies. Participants reported on usability and acceptability. RESULTS Laboratory alcohol self-administration did not differ significantly by technology condition. The smartphone breathalyzer and BAC estimator app had favorable acceptability and usability. Participants used at least one form of technology on 67% of drinking days in the field period. In exploratory analyses, alcohol use during the field period was significantly lower than the baseline including a decrease of nearly one drink per drinking day. CONCLUSIONS These findings support the feasibility of research combining lab and field methods to test moderate drinking technologies in young adults. Findings further support the acceptability and usability of these technologies, along with young adults' openness to using them. Exploratory results suggest potential efficacy of combined mobile technology intervention to be tested in subsequent controlled studies. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Deep Learning (DL) techniques allow ones to train models from a dataset to solve tasks. DL has attracted much interest given its fancy performance and potential market value, while security issues are amongst the most colossal concerns. However, the DL models may be prone to the membership inference attack, where an attacker determines whether a given sample is from the training dataset. Efforts have been made to hinder the attack but unfortunately, they may lead to a major overhead or impaired usability. In this paper, we propose and implement DAMIA, leveraging Domain Adaptation (DA) as a defense aginist membership inference attacks. Our observation is that during the training process, DA obfuscates the dataset to be protected using another related dataset, and derives a model that underlyingly extracts the features from both datasets. Seeing that the model is obfuscated, membership inference fails, while the extracted features provide supports for usability. Extensive experiments have been conducted to validates our intuition. The model trained by DAMIA has a negligible footprint to the usability. Our experiment also excludes factors that may hinder the performance of DAMIA, providing a potential guideline to vendors and researchers to benefit from our solution in a timely manner.

BACKGROUND: This project is the first formal usability review of the hybrid electronic medical registry (HEMR) since its implementation in 2012 METHODS: A synchronous usability evaluation by novice operators was followed by a survey of veteran users. The usability evaluation was done by moderated think-aloud interview while completing tasks for a mock patient. The veteran survey was paper-based and focused on satisfaction of the system RESULTS: A total of 141 comments on system errors were identified by the novice doctors. These consisted of 123 unique problems, of which three were hardware faults and were thus excluded. The identified issues were categorised into errors of control (27%), minimalist (21%), error (17%), match (13%), flexibility, visibility and consistency (9% each), and history (4%). Every unique usability violation was evaluated by the three experts who agreed that 82 of the 141 errors (58%) were valid and applicable. The other 59 items were rejected, not only because of the inability to reproduce some errors or programme shortcomings, but also because a series of "hurdles" were purposely included in the software to decrease cognitive dissonance and reduce error by the users. The survey of veteran users showed high levels of contentment with the system with regards to efficiency, satisfaction and preference CONCLUSION: Despite many usability complaints by novices, almost half of them were rejected. Although usability in electronic health systems is important, it can often be sacrificed for more imperative aims such as safety, error filtering and clinical decision support

Browser extensions are widely used nowadays to customize users' browsers with more functionalities, meanwhile introduce potential risks due to escalated privileges. Existing security mechanisms, such as Same Origin Policy and Content Security Policy, do not apply to browser extensions that can read and write on web applications at any time. In spite of the state-of-art industrial efforts that rely on centralized management to inspect and detect malicious behaviors massively, the detection-based method cannot analyze fast-evolving behaviors of malicious browser extensions. To this end, we adopt a novel approach to protect users from malicious browser extensions, where we consider the problem of malicious extensions on the side of web applications. From a high level point of view, web developers are allowed to specify sensitive parts in a web application by using our provided software enclave. With our proposed WebEnclave extension installed, when users visit a web application, sensitive information required for the web application to work normally is sealed into an isolated world locally that malicious extensions cannot access. Extensive evaluation of our built prototype shows it can effectively protect user secrets from malicious extensions with negligible performance overhead and usability inconvenience. We also publish source codes for public use.

Teachers' professional development plays a significant role in the sustainability of quality education. However, providing sustainable professional development programs is difficult because of various challenges, such as insufficient government policies, a scarcity of qualified personnel and training opportunities, lack of access and resources, etc. The COVID-19 epidemic has further intensified the problem and adversely harmed schoolteachers’ interest, motivation, and involvement. In such situations, technology can play a positive role in carrying out sustainable educational activities. However, little focus has been paid to the use of technology for the sustainable professional development of teachers, particularly in the under developing countries. Due to its unique qualities, mobile learning is receiving much attention as an essential component to impart sustainable education to teaching professionals. It represents a paradigm shift in ongoing professional development, particularly for teachers who are constrained by time, resources, and travel requirements. Mobile learning is an alternate and complementary technique to enhance teachers' professional development, allowing them to work, learn, and attain their full potential. To meet the sustainable development goal of teachers’ education, in [1] we have provided a framework for teachers' continuous professional development (CPD). Based on that, we have also developed a mobile App to provide training and ongoing support to teachers’ professionals. This study evaluates the usability of our mobile App for the sustainable development of teachers. Usability characteristics of usefulness, efficiency, and satisfaction are measured using a usability testing approach. 107 elementary school instructors took part in the study. Participants in the study performed eight usability tasks in the same room using the researcher's internet bandwidth. The participants' time and completion rate were recorded. A post-test questionnaire followed usability tasks. After the usability activities, participants completed a System Usability Scale questionnaire to assess overall satisfaction with the training app and gain a broad picture of the program. The application achieved a 100% completion rate for all tasks, indicating an extremely effective, efficient, and sustainable system. Moreover, the satisfaction percentage was also found to be 84.1 percent, which is considered highly satisfactory.

Cognitive impairment is one of the most common non-motor features of Parkinson's disease (PD). The aim of the present study was to evaluate the feasibility and acceptability/usability of a protocol using a non-immersive virtual reality tele-cognitive app, performed remotely in a sample of Italian patients with PD.Non-demented patients with mild PD were included in the study. Patients performed the cognitive rehabilitation in a remote way, at home (three training sessions lasting 20 min/week for 6 weeks) using the NeuroNation app, downloaded for free on the patients' smartphones. The usability and feasibility of the tele-cognitive rehabilitation program were assessed with the System Usability Scale (SUS) and the Goal Attainment Scaling (GAS).Sixteen patients (9 men and 7 women; mean age 58.4 ± 8.3 years; mean disease duration 4.6 ± 2.1 years) were included in the study. At the end of the study, the mean SUS was 83.4 ± 11.5. The GAS score recorded at the end of the study (65.6 ± 4.2) was significantly higher than at baseline (38.5 ± 2.4; P-value0.001).In our sample, good feasibility and usability were observed for a 6-week cognitive rehabilitation protocol based on the non-immersive virtual reality tele-cognitive app NeuroNation. Our data support the usefulness of cognitive rehabilitation performed in a remote way in PD patients.

The aim of this work was to evaluate the usability of a single-page, patient-completed, condition-specific prompt list, the Patient Concerns Inventory (PCI-HN), to risk-stratify for poor health-related quality of life (HRQOL). Data were collected between 2008 and 2017. The main dataset comprised 310 patients first completing the PCI-HN and University of Washington Quality of Life questionnaire (UW-QOLv4) between 2012 and 2017. Another 201 patients first completing the PCI-HN between 2008 and 2011 provided a second dataset for independent validation. Subsequent completions of the PCI-HN in both groups and the distress thermometer (DT) were also used as further validation datasets. Associations between PCI-HN items selected by patients and a range of UW-QOLv4 outcomes were explored using conventional logistic regression and Chi-squared automated interaction detection (CHAID) analyses. One quarter of patients reported less than good HRQOL, range 26–29% across the four datasets. Several individual items from within the PCI-HN were predictive of adverse outcomes. The total number of items selected was also predictive. The single-sheet prompt list enables clinicians to identify patients at high risk of poor HRQOL. This simple approach has the potential to be integrated into routine clinical practice.

Context based API recommendation is an important way to help developers find the needed APIs effectively and efficiently. For effective API recommendation, we need not only a joint view of both structural and textual code information, but also a holistic view of correlated API usage in control and data flow graph as a whole. Unfortunately, existing API recommendation methods exploit structural or textual code information separately. In this work, we propose a novel API recommendation approach called APIRec-CST (API Recommendation by Combining Structural and Textual code information). APIRec-CST is a deep learning model that combines the API usage with the text information in the source code based on an API Context Graph Network and a Code Token Network that simultaneously learn structural and textual features for API recommendation. We apply APIRec-CST to train a model for JDK library based on 1,914 open-source Java projects and evaluate the accuracy and MRR (Mean Reciprocal Rank) of API recommendation with another 6 open-source projects. The results show that our approach achieves respectively a top-1, top-5, top-10 accuracy and MRR of 60.3%, 81.5%, 87.7% and 69.4%, and significantly outperforms an existing graph-based statistical approach and a tree-based deep learning approach for API recommendation. A further analysis shows that textual code information makes sense and improves the accuracy and MRR. The sensitivity analysis shows that the top-k accuracy and MRR of APIRec-CST are insensitive to the number of APIs to be recommended in a hole. We also conduct a user study in which two groups of students are asked to finish 6 programming tasks with or without our APIRec-CST plugin. The results show that APIRec-CST can help the students to finish the tasks faster and more accurately and the feedback on the usability is overwhelmingly positive.

This case study explores concepts and methodologies in user interface (UI) and user experience (UX) design with a view to increasing information retention and memorisation through the inclusion of human-centred design principles. It focuses on the participants’ individual context, mental state and abilities. In emergencies, visual perception and situation awareness may be restricted due to the impact of sensory symptoms (panic, tunnel vision or limited motor skills), thus calling for a linear course of action. This applied research project, ‘Floodscape’, is a mobile application designed to educate its user about possible inundation zones resulting from a tsunami. Ongoing user engagement through interactive simulation is the prime focus of the initial (dormant) state of the app. In case of an actual tsunami the app registers the event and adapts its UI accordingly. Crucial life-saving wayfinding information will then be displayed in a contextual manner considering contrast, typography, limited user attention and ease of use.

Medical personnel usually write and design documents that inform physicians or patients about procedures or therapies. Document design, however, requires skills that are not normally applied, resulting in information that is often not used properly. This article describes a project developed by the Alberta Colorectal Cancer Screening Program. The goal was to help patients better prepare for their colonoscopies. The process started with an analysis of the existing documents, and the development of performance specifications based on the literature on legibility, reading comprehension, memorization and use of information, plain language, visual perception, page layout, and image use. The project included an iterative process of prototyping and testing that resulted in 23 design criteria. Each iteration was tested with users to ensure ease of use, completeness of information, and accuracy and clarity to facilitate adoption. The project helped reduce practice variation regarding bowel preparation in the province of Alberta, Canada. This project illustrates how information design can help healthcare organizations provide patient-centred care. Information design helps patients engage in their own caring process, by providing information that people can use, understand and apply. After 15 months of use, the document has been downloaded more than 48,000 times, suggesting a good physician reception.

Federated learning enables collaborative deep learning over multiple clients without sharing their local data, and it becomes increasingly popular due to the good balance between data privacy and model usability. Generally, it faces the heavy communication overhead when a large number of clients are involved and the low convergence rate incurred by non-IID data. However, few existing solutions cannot simultaneously address the communication and statistic challenges. In this paper, we propose a computation and communication efficient federated learning via adaptive sampling. By capturing different data distribution among clients, we utilize the concept of self-paced learning to adaptively adjust thresholds to filter training data for each client and also to select suitable clients to be involved in each global learning round. We prove its correctness through theoretical analysis and also evaluate its performance through experimental evaluations on real-world datasets. Detailed experimental results show that it can effectively reduce the communication cost while achieving the good trade-off between accuracy and efficiency.

Most robotic systems designed for mass manufacturing are optimized for a specific type of product. They generally lack the ability to adapt to low-volume customized products. In this article, we present a system based on a modular design for manufacturing personalized medical stent graft implants. The concept is based on learning-by-demonstration by integrating real-time 3-D vision, multirobot collaboration, and personalization to guide the robots to learn and execute tasks continuously with adaptation to different implant geometry. The system is optimized to generate customized and collision-free paths for efficient object manipulation and task completion. We show that the system is generalizable to different stent graft designs and the proposed multirobot system can seamlessly work together with high efficiency without collisions. The results have also suggested its usability for other manipulation tasks, especially for flexible production of customized products where bimanual or multirobot cooperation is required.

Facial authentication has become more and more popular on personal devices. Due to the ease of use, it has great potential to be widely deployed for web-service authentication in the near future whereby people can easily log on to online accounts from different devices without memorizing lengthy passwords. However, the growing number of attacks on machine learning especially the Deep Neural Networks (DNN) which is commonly used for facial recognition, imposes big challenges on the successful roll-out of such web-service face authentication. Although there have been studies on defending some machine learning attacks, we are not aware of any specific effort devoted to the web-service facial authentication setting. In this paper, we first demonstrate a new data poisoning attack which does not require to have any knowledge of the server-side and just needs a handful of malicious photo injections to enable an attacker to easily impersonate the victim in the existing facial authentication systems. We then propose a novel defensive approach called DEFEAT that leverages deep learning techniques to automatically detect such attacks. We have conducted extensive experiments on real datasets and our experimental results show that our defensive approach achieves more than 90% detection accuracy.