Browsing by Author "Neyem, Andres"

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    A Lessons-learned Mobile System for Construction Companies: Motivation and Design
    (2014) Ferrada Calvo, Ximena Veronica; Sepúlveda Fernández, Marcos Ernesto; Serpell Bley, Alfredo; Daniela Núñez; Neyem, Andres
    Construction projects are an important source of organizational knowledge. Though, it is common to find that most lessons learned in construction projects are lost because most companies never take care of collecting them. To change this situation, a mobile lesson-learned system application with interface for smartphones and web in a cloud environment is proposed. This article focuses on the design of a prototype of the system and the main characteristics of its architecture. It is concluded that the application of mobile technology on the field would facilitate the use of the system, been an appropriate tool for knowledge management. (C) 2014 The Authors. Published by Elsevier Ltd.
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    A Patterns System to Coordinate Mobile Collaborative Applications
    (2011) Neyem, Andres; Ochoa, Sergio F.; Pino, Jose A.
    Advances in wireless communication technologies and mobile computing devices open new possibilities to carry out computer-supported mobile collaborative work. However this opportunity brings also a number of challenges to designers, since collaborative applications supporting mobile activities involve requirements which are not present in stationary collaboration scenarios. For example, mobile collaborative applications should not use centralized components because it jeopardizes the autonomy required by mobile workers. In order to help designers to deal with these new requirements, this article presents a patterns system focused on the coordination support required for mobile collaborative work. Such patterns represent reusable designs that help reduce design risks, cost and time. The article also presents three mobile collaborative applications in which proposed patterns were included in their respective designs.
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    A reusable structural design for mobile collaborative applications
    (ELSEVIER SCIENCE INC, 2012) Neyem, Andres; Ochoa, Sergio F.; Pino, Jose A.; Dario Franco, Ruben
    Architecting mobile collaborative applications has always been a challenge for designers. However, counting on a structural design as a reference can help developers to reduce risks and efforts involved in system design. This article presents a reusable architecture which helps modeling the communication and coordination services required by mobile collaborative applications to support collaboration among users. This architecture has been used as a basis for the design of several mobile systems. Two of them are presented in this article to show the applicability of the proposal to real world collaborative systems. (C) 2011 Elsevier Inc. All rights reserved.
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    COMMUNICATION SUPPORT FOR MOBILE COLLABORATIVE WORK: AN EXPERIMENTAL STUDY
    (WORLD SCIENTIFIC PUBL CO PTE LTD, 2012) Messeguer, Roc; Medina, Esunly; Ochoa, Sergio F.; Pino, Jose A.; Neyem, Andres; Navarro, Leandro; Royo, Dolors
    Advances in mobile computing and wireless communication are easing the evolution from traditional nomadic work to computer-mediated mobile collaborative work. Technology allows efficient and effective interaction among mobile users and also provides access to shared resources available to them. However, the features and capabilities of the communication infrastructure supporting these activities influence the type of coordination and collaboration employed by mobile collaborative applications in real work scenarios. Developers of these applications are typically unaware of the constraints the communication infrastructure imposes on mobile collaborative systems, because they are not easy to foresee. That leads to a high probability of communication problems in otherwise fully functional mobile collaborative support applications. This paper presents an experimental study with real devices and networks on a realistic physical environment that shows how ad hoc networks can effectively support mobile collaborative work and the practical limitations. The paper analyzes several networking issues and determines how they influence mobile collaborative work in various interaction scenarios. The paper also presents the lessons learned in the study and provides recommendations to deal with some networking issues related to real-world ad hoc networks.
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    Deep Neural Networks on Mobile Healthcare Applications: Practical Recommendations
    (2018) Benedetto, Jose I.; Sanabria, Pablo; Neyem, Andres; Navon, Jaime; Poellabauer, Christian; Xia, Bryan (Ning)
    Deep learning has for a long time been recognized as a powerful tool in the field of medicine for making predictions or detecting abnormalities in a patient’s data. However, up until recently, hosting of these neural networks has been relegated to the domain of servers and powerful workstations due to the vast amount of resources they require. This trend has been steadily shifting in the recent years, and we are now beginning to see more and more mobile applications with similar capabilities. Deep neural networks hosted completely on mobile platforms are extremely valuable for providing healthcare services to remote areas without network connectivity. Yet despite this, there is very little information regarding the migration process of an existing server-based neural network to a mobile environment. In this work, we describe the various techniques and considerations that should be taken into account when developing a deep-learning enabled mobile application with offline support. We illustrate the above by providing a concrete example through our experience in migrating to mobile an in-house developed medical application for detecting early signs of traumatic brain injuries.
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    Empowering human anatomy education through gamification and artificial intelligence: An innovative approach to knowledge appropriation
    (WILEY, 2023) Castellano, Monica Stambuk; Contreras-McKay, Ignacio; Neyem, Andres; Farfan, Emilio; Inzunza, Oscar; Ottone, Nicolas E.; del Sol, Mariano; Alario-Hoyo, Carlos; Alvarado, Macarena Soto; Tubbs, R. Shane
    Gamification has appeared as an alternative educational methodology to traditional tools. Specifically, in anatomy teaching, multiple technological applications have emerged in response to the difficulties of accessing cadaveric material; however, there is insufficient information about the effects of these applications on the performance achieved by students, or about to the best way to adapt learning to meet their educational needs. In this study, we investigated how teaching human anatomy through a mobile gamified technological tool containing recommendation systems can be combined with a virtual assistant to improve the learning and academic performance of medical students in the Anatomy Department at the Universidad de La Frontera in Temuco, Chile and the Anatomy Department at the Pontificia Universidad Catolica de Chile. In total, 131 students participated in the experiment, which was divided into two case studies. The main findings led to the conclusion that gamified components support students in learning anatomy. In addition, the predictions and recommendations provided by the virtual assistant enabled the academic aspects that the students needed to improve to be extracted adequately. Future work is expected to support adaptive learning by incorporating new artificial intelligence in education elements that can generate personalized scenarios for studying anatomy based on the application.
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    Enhancing commit message quality in software capstone projects with generative AI
    (2024) Neyem, Andres; Rios-Letelier, Agustin; Cespedes-Arancibia, Kevin; Alcocer, Juan Pablo Sandoval; Mendoza, Marcelo
    Software Capstone Projects provide valuable hands-on experience for students in software development, and creating effective commit messages is an essential, though often challenging, part of this process. These messages playa key role in managing repositories, facilitating collaboration, and offering insights into the project's progression for mentors and managers. However, creating high-quality commit messages can be challenging, especially for novice developers. We introduce LetsCommit, a tool designed to improve the traditional Git commit command line interface. The tool utilizes three state-of-the-art Large Language Models (LLMs): GPT-3.5, GPT-4, and LLaMa-2, to provide commit message suggestions to students. Results from a user experience survey showed high satisfaction, indicating strong potential for incorporating LetsCommit into future projects. Beyond its technical applications, LetsCommit possesses transformative potential in the field of education. The iterative learning process it supports, coupled with real-time insights, reinforces good software development practices and enhances the overall learning experience. These findings highlight LetsCommit's substantial impact on software engineering education, setting the stage for further advancements.
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    Fostering the use of online learning resources: results of using a mobile collaboration tool based on gamification in a blended course
    (2023) Ramirez-Donoso, Luis; Perez-Sanagustin, Mar; Neyem, Andres; Alario-Hoyos, Carlos; Hilliger Carrasco, Isabel; Rojos, Felipe
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    Implementing Artificial Intelligence in Physiotherapy Education: A Case Study on the Use of Large Language Models (LLM) to Enhance Feedback
    (2024) Villagran, Ignacio; Hernandez, Rocio; Schuit, Gregory; Neyem, Andres; Fuentes-Cimma, Javiera; Miranda, Constanza; Hilliger, Isabel; Duran, Valentina; Escalona, Gabriel; Varas, Julian
    This article presents a controlled case study focused on implementing and using generative artificial intelligence, specifically large language models (LLMs), in physiotherapy education to assist instructors with formulating effective technology-mediated feedback for students. It outlines how these advanced technologies have been integrated into an existing feedback-oriented platform to guide instructors in providing feedback inputs and establish a reference framework for future innovations in practical skills training for health professions education. Specifically, the proposed solution uses LLMs to automatically evaluate feedback inputs made by instructors based on predefined and literature-based quality criteria and generates actionable textual explanations for reformulation. In addition, if the instructor requires, the tool supports summary generation for large sets of text inputs to achieve better student reception and understanding. The case study describes how these features were integrated into the feedback-oriented platform, how their effectiveness was evaluated in a controlled setting with documented feedback inputs, and the results of its implementation with real users through cognitive walkthroughs. Initial results indicate that this innovative implementation holds great potential to enhance learning and performance in physiotherapy education and has the potential to expand to other health disciplines where the development of procedural skills is critical, offering a valuable tool to assess and improve feedback based on quality standards for effective feedback processes. The cognitive walkthroughs allowed us to determine participants' usability decisions in the face of these new features and to evaluate the perceived usefulness, how this would integrate into their workload, and their opinion regarding the potential for the future within this teaching strategy. This article concludes with a discussion of the implications of these findings for practice and future research directions in this developing field.
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    Improving learning experiences in software engineering capstone courses using artificial intelligence virtual assistants
    (2022) Gonzalez, Luis A.; Neyem, Andres; Contreras-McKay, Ignacio; Molina, Danilo
    Students of Software Engineering Capstone Courses face situations and challenges that grant them valuable experiences. However, as this knowledge is acquired through real-life exposure, it is difficult to transmit it across different generations. To deal with this problem, it has been proposed that students record their learnings through a lesson learned model. But the question of how future students can best benefit from these records remains unanswered. This study addresses this problem through the use of Artificial Intelligence (AI) Virtual Assistant combined with a recommender system. Artificial Intelligence Virtual Assistants, as conversational chatbots, are a manifestation of AI via the simulation of conversation with human users. The technology has the potential to provide personalized service to a range of stakeholders. Thus, we seek to move this trend forward by now pushing these capabilities into the field of higher education. Consequently, we aim to assist software engineering students by leveraging collective knowledge to enhance learning experiences.
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    Mobile computing in urban emergency situations Improving the support to firefighters in the field
    (PERGAMON-ELSEVIER SCIENCE LTD, 2011) Monares, Alvaro; Ochoa, Sergio F.; Pino, Jose A.; Herskovic, Valeria; Rodriguez Covili, Juan; Neyem, Andres
    Communication support is a serious limitation for Latin American firefighters when they deal with emergency situations The insufficient number of radio channels and the impossibility to deliver digital information force firemen to improvise during response processes e g to make decisions using their experience and poor or null supporting information These improvised actions affect the time required to take control of an emergency and also affect the evolution of the crisis situation Provided most of Latin American fire companies are volunteer organizations communication solutions that could help to overcome these problems are usually expensive for them This article presents a low-cost mobile collaborative application which may be used in emergency situations to overcome most of the firefighters communication problems The application named MobileMap is the result of the research and development work conducted by the authors supported by a Chilean fire company during the last three years MobileMap allows ad hoc communication decisions support and collaboration among firefighters in the field using mobile devices This solution complements the radio communication systems Since the Inter actions supported by MobileMap are recorded it is possible to analyze such information after the crisis and learn for future emergencies The tool was evaluated in simulated and real scenarios and the obtained results are highly encouraging (C) 2010 Elsevier Ltd All rights reserved
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    Solving Task Scheduling Problems in Dew Computing via Deep Reinforcement Learning
    (2022) Sanabria Quispe, Pablo; Tapia, Tomás Felipe; Toro Icarte, Rodrigo; Neyem, Andres
    Due to mobile and IoT devices’ ubiquity and their ever-growing processing potential, Dew computing environments have been emerging topics for researchers. These environments allow resource-constrained devices to contribute computing power to others in a local network. One major challenge in these environments is task scheduling: that is, how to distribute jobs across devices available in the network. In this paper, we propose to distribute jobs in Dew environments using artificial intelligence (AI). Specifically, we show that an AI agent, known as Proximal Policy Optimization (PPO), can learn to distribute jobs in a simulated Dew environment better than existing methods—even when tested over job sequences that are five times longer than the sequences used during the training. We found that using our technique, we can gain up to 77% in performance compared with using human-designed heuristics.
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    The Iceberg Effect: Behind the User Interface of Mobile Collaborative Systems
    (GRAZ UNIV TECHNOLGOY, INST INFORMATION SYSTEMS COMPUTER MEDIA-IICM, 2011) Herskovic, Valeria; Ochoa, Sergio F.; Pino, Jose A.; Neyem, Andres
    Advances in mobile technologies are opening new possibilities to support collaborative activities through mobile devices. Unfortunately, mobile collaborative systems have been difficult to conceive, design and implement. These difficulties are caused in part by their unclear requirements and developers' lack of experience with this type of systems. However, several requirements involved in the collaborative back-end of these products are recurrent and should be considered in every development. This paper introduces a characterization of mobile collaboration and a framework that specifies a list of general requirements to be considered during the conception and design of a system in order to increase its probability of success. This framework was used in the development of two mobile collaborative systems, providing developers with a base of back-end requirements to aid system design and implementation. The systems were positively evaluated by their users.