Luis Quesada Quirós

Luis Quesada Quirós

Proyectos

Publicaciones

Scheduling of events through notifications in mobile devices

Descripción:

It is very common to interact with notifications every day with our mobile devices. Notifications have advantages and disadvantages. They bring information for the user, but they are also interruptions. In this study, the authors provide a solution for scheduling events through notifications. They created an application using the Google Calendar platform and the Swift programming language to respond to events through notifications. Then, the participants evaluated the application through the usability scale of the system (SUS), and the results were positive. The authors received excellent comments and feedback from the participants in the evaluation.

Tipo de publicación: Conference Paper

Publicado en: 2019 IV Jornadas Costarricenses de Investigación en Computación e Informática (JoCICI)

Standardized Questionnaires for User Experience Evaluation: A Systematic Literature Review

Descripción:

Standardized questionnaires are one of the methods used to evaluate User Experience (UX). Standardized questionnaires are composed of an invariable group of questions that users answer themselves after using a product or system. They are considered reliable and economical to apply. The standardized questionnaires most recognized for UX evaluation are AttrakDiff, UEQ, and meCUE. Although the structure, format, and content of each of the questionnaires are known in detail, there is no systematic literature review (SLR) that categorizes the uses of these questionnaires in primary studies. This SLR presents the eligibility protocol and the results obtained by reviewing 946 papers from four digital databases, of which 553 primary studies were analyzed in detail. Different characteristics of use were obtained, such as which questionnaire is used more extensively, in which geographical context, and the size of the sample used in each study, among others.

Tipo de publicación: Journal Article

Publicado en: 13th International Conference on Ubiquitous Computing and Ambient ‪Intelligence UCAmI 2019‬

Smart Meeting Room Management System Based on Real-Time Occupancy

Descripción:

This paper proposes the creation of a smart meeting room through the incorporation of a PIR sensor and an AWS IoT button that allows the booking system to reflect a more precise availability of meeting rooms according to the actual occupancy status. The Internet of Things (IoT) devices are controlled using a Wi-Fi module that allows them to connect to the REST web service and to integrate with the open source Meeting Room Booking System (MRBS). In order to evaluate the system a storyboard evaluation was conducted with 47 participants. All participants filled out the User Experience Questionnaires (UEQ), described the product using three words and expressed their opinion through open comments. Finally, 19 participants took part in a real-life simulation of the smart meeting room and evaluated the system using the UEQ questionnaire. Based on the positive acceptance reflected in the evaluations, results show that the proposed system is considered very attractive and useful by the participants.

Tipo de publicación: Conference Paper

Publicado en: 2019 IV Jornadas Costarricenses de Investigación en Computación e Informática (JoCICI)

User Experience Comparison of Intelligent Personal Assistants: Alexa, Google Assistant, Siri and Cortana

Descripción:

Natural user interfaces are becoming popular. One of the most common natural user interfaces nowadays are voice activated interfaces, particularly smart personal assistants such as Google Assistant, Alexa, Cortana, and Siri. This paper presents the results of an evaluation of these four smart personal assistants in two dimensions: the correctness of their answers and how natural the responses feel to users. Ninety-two participants conducted the evaluation. Results show that Alexa and Google Assistant are significantly better than Siri and Cortana. However, there is no statistically significant difference between Alexa and Google Assistant.

Tipo de publicación: Journal Article

Publicado en: 13th International Conference on Ubiquitous Computing and Ambient ‪Intelligence UCAmI 2019‬

Framework for Creating Audio Games for Intelligent Personal Assistants

Descripción:

Intelligent Personal Assistant (IPA) has experienced an important market growth, therefore, an increase in its development by having more people interested in devices that use this software. This opens possibilities for develop new games that people can be interested in. This article presents a framework proposal to create audio games using IPA enabled devices. In order to evaluate the framework, a prototype was designed and presented to 30 participants. The results obtained indicated that a 97.6% of the interviewees were attracted to the idea of playing a game using and IPA.

Tipo de publicación: Conference Paper

Publicado en: Advances in Human Factors in Wearable Technologies and Game Design

A Model Proposal for Augmented Reality Game Creation to Incentivize Physical Activity

Descripción:

Obesity and a sedentary lifestyle are relevant issues in today’s society. Even though different resources can be used to approach this problem, technology provides endless possibilities to fight against this problem. This article presents the results of a model to create augmented reality games where goals are achieved by doing physical activity (moving between different places). In order to evaluate the model, a prototype was built and presented to 50 participants. The results obtained indicated that an important percentage of the interviewees were attracted to the idea of playing a game to increase their physical activity.

Tipo de publicación: Conference Paper

Publicado en: Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 5: HEALTHINF, (BIOSTEC 2017)

UX Evaluation with Standardized Questionnaires in Ubiquitous Computing and Ambient Intelligence: A Systematic Literature Review

Descripción:

Standardized questionnaires are well-known, reliable, and inexpensive instruments to evaluate user experience (UX). Although the structure, content, and application procedure of the three most recognized questionnaires (AttrakDiff, UEQ, and meCUE) are known, there is no systematic literature review (SLR) that classifies how these questionnaires have been used in primary studies reported academically. This SLR seeks to answer five research questions (RQs), starting with identifying the uses of each questionnaire over the years and by geographic region (RQ1) and the median number of participants per study (how many participants is considered enough when evaluating UX?) (RQ2). This work also aims to establish whether these questionnaires are combined with other evaluation instruments and with which complementary instruments are they used more frequently (RQ3). In addition, this review intends to determine how the three questionnaires have been applied in the fields of ubiquitous computing and ambient intelligence (RQ4) and also in studies that incorporate nontraditional interfaces, such as haptic, gesture, or speech interfaces, to name a few (RQ5). Methods. A systematic literature review was conducted starting from 946 studies retrieved from four digital databases. The main inclusion criteria being the study describes a primary study reported academically, where the standardized questionnaire is used as a UX evaluation instrument in its original and complete form. In the first phase, 189 studies were discarded by screening the title, abstract, and keyword list. In the second phase, 757 studies were full-text reviewed, and 209 were discarded due to the inclusion/exclusion criteria. The 548 resulting studies were analyzed in detail. Results. AttrakDiff is the questionnaire that counts the most uses since 2006, when the first studies appeared. However, since 2017, UEQ has far surpassed AttrakDiff in uses per year. The contribution of meCUE is still minimal. Europe is the region with the most extended use, followed by Asia. Within Europe, Germany greatly exceeds the rest of countries (RQ1). The median number of participants per study is 20, considering the aggregated data from the three questionnaires. However, this median rises to 30 participants in journal studies while it stays in 20 in conference studies (RQ2). Almost 4 in 10 studies apply the questionnaire as the only evaluation instrument. The remaining studies used between one and five complementary instruments, among which the System Usability Scale (SUS) stands out (RQ3). About 1 in 4 studies analyzed belong to ubiquitous computing and ambient intelligence fields, in which UEQ increases the percentage of uses when compared to its general percentage, particularly in topics such as IoT and wearable interfaces. However, AttrakDiff remains the predominant questionnaire for studies in smart cities and homes and in-vehicle information systems (RQ4). Around 1 in 3 studies include nontraditional interfaces, being virtual reality and gesture interfaces the most numerous. Percentages of UEQ and meCUE uses in these studies are higher than their respective global percentages, particularly in studies using virtual reality and eye tracking interfaces. AttrakDiff maintains its overall percentage in studies with tangible and gesture interfaces and exceeds it in studies with nontraditional visual interfaces, such as displays in windshields or motorcycle helmets (RQ5).

Tipo de publicación: Journal Article

Publicado en: Advances in Human-Computer Interaction

A Mobile Application for Improving the Delivery Process of Notifications

Descripción:

t present, there are systems in charge of classifying and sending notifications to smart devices at different times. However, there are not many studies that demonstrate the effectiveness of these systems in real world settings. We propose a method that classifies and prioritizes notifications by analyzing only the content of the notification and the sender of the message. We also developed a system implementing this method. User diaries were used to analyze the behavior of the system in real world situations, and the results showed that the implemented system significantly reduces interruptions to users. Additionally, the user experience of the system was evaluated through the standardized questionnaire UEQ (User Experience Questionnaire). The results obtained were positive in most of the scales of this instrument, above the average according to UEQ benchmarks. However, aspects such as stimulation and creativity can be improved in the future to motivate users to use the system.

Tipo de publicación: Book Chapter

Publicado en: Advances in Intelligent Systems and Computing

Emotions Classifier based on Facial Expressions

Descripción:

Emotion recognition is important in the context of smart buildings and IoT, because it allows the environment to have a better notion of the mood of the humans who are present. With a view to developing such projects, in this article we analyze the performance of an emotion classifier that uses a convolutional neural network. Specifically, we focus on analyzing the impact of the epochs and batch size hyperparameters. To do this, we propose an experimental design with the following hypothesis: "The number of epochs that the model trains and the size of the batch given by iteration in each epoch influence the accuracy of an emotion classifier built from networks. convolutional neurons using the VGG16 architecture".

Tipo de publicación: Conference Paper

Publicado en: 2021 IEEE V Jornadas Costarricenses de Investigación en Computación e Informática (JoCICI)

Asynchronous Detection of Slowloris Attacks Via Random Forests

Descripción:

An asynchronous classifier of network flows was developed to detect Slowloris attacks. This classifier was implemented using random forests and its effectiveness was measured by the area under the ROC curve. These random forests were trained from a public dataset. We sought to minimize the number of necessary features that are required to analyze the flows satisfactorily. Finally, it was shown that the chosen features can be used individually to obtain reliable detections in the classifier, with two of the three individual features having an area under the curve greater than 0.95.

Tipo de publicación: Conference Paper

Publicado en: 2021 IEEE V Jornadas Costarricenses de Investigación en Computación e Informática (JoCICI)

Recognizing daily-life activities using sensor-collected data in a kitchen

Descripción:

This paper focuses on the recognition and classification of Activities of Daily Living (ADLs) that are carried out in a kitchen. To do this, a Recurrent Neural Network architecture of the Long-Short Term Memory (LSTM) type is implemented as a classifier. The ARAS dataset is used for training and evaluation. A classifier is obtained with an average value in the F1 metric of 95.33% for the chosen data set.

Tipo de publicación: Conference Paper

Publicado en: 2021 IEEE V Jornadas Costarricenses de Investigación en Computación e Informática (JoCICI)

User Experience in Communication and Collaboration Platforms: A Comparative Study Including Discord, Microsoft Teams, and Zoom

Descripción:

Due to the measures imposed to prevent the spread of the virus during the COVID-19 pandemic, how education and work communications are carried have changed. An increase in video conferencing and meeting applications is noticeable. In this research paper, we describe the results of a user experience evaluation of three widely used platforms: Discord, Microsoft Teams, and Zoom. Through the User Experience Questionnaire (UEQ) application, it was determined that Discord is better in aspects not related to tasks and provides an above-average UX. On the other hand, zoom excels when it comes to tasks, but in conjunction with Microsoft Teams, it delivers below-average UX.

Tipo de publicación: Book Chapter

Publicado en: Lecture Notes in Networks and Systems