Recent Submissions

  • Statistical model and taxonomy of devices for assessing the level of VR penetration in the development of applications

    Arce, Brenda; Sanchez, Cynthia; Barrientos, Alfredo; Villalta, Rosario (International Institute of Informatics and Systemics, IIIS, 2018)
    Acceso restringido temporalmente
  • Wearable technology model to control and monitor hypertension during pregnancy

    Lopez, Betsy Diamar Balbin; Aguirre, Jimmy Alexander Armas; Coronado, Diego Antonio Reyes; Gonzalez, Paola A.; betsybalbin@gmail.com; jimmy.armas@upc.pe; diegoreyes1212@gmail.com; paola.gonzalez@dal.ca (IEEE Computer Society, 2018-06-27)
    In this paper, we proposed a wearable technology model to control and monitor hypertension during pregnancy. We enhanced prior models by adding a series of health parameters that could potentially prevent and correct hypertension disorders in pregnancy. Our proposed model also emphasizes the application of real-time data analysis for the healthcare organization. In this process, we also assessed the current technologies and systems applications offered in the market. The model consists of four phases: 1. The health parameters of the patient are collected through a wearable device; 2. The data is received by a mobile application; 3. The data is stored in a cloud database; 4. The data is analyzed on real-time using a data analytics application. The model was validated and piloted in a public hospital in Lima, Peru. The preliminary results showed an increased-on number of controlled patients by 11% and a reduction of maternal deaths by 7%, among other relevant health factors that allowed healthcare providers to take corrective and preventive actions.
  • Simulation of suicide tendency by using machine learning

    Calderon-Vilca, Hugo D.; Wun-Rafael, William I.; Miranda-Loarte, Roberto; pcsihcal@upc.edu.pe; pcsihcal@upc.edu.pe; pcsihcal@upc.edu.pe (IEEE Computer Society, 2018-07)
    Suicide is one of the most distinguished causes of death on the news worldwide. There are several factors and variables that can lead a person to commit this act, for example, stress, self-esteem, depression, among others. The causes and profiles of suicide cases are not revealed in detail by the competent institutions. We propose a simulation with a systematically generated dataset; such data reflect the adolescent population with suicidal tendency in Peru. We will evaluate three algorithms of supervised machine learning as a result of the algorithm C4.5 which is based on the trees to classify in a better way the suicidal tendency of adolescents. We finally propose a desktop tool that determines the suicidal tendency level of the adolescent.
  • A new software development model: Innovation through mobile application with UCD

    Espinoza, Jorge; Loarte, Pamela; Espinoza, Carlos; Paz, Freddy; Arenas, Juan; jeespinozam@pucp.pe (Springer Verlag, 2018)
    Pursuit of innovation projects with the absent of a methodology to follow hampers the development of the software product as its complexity grows since the freedom of its own advancement is confused with the lack of order on it. Traditional and agile methodologies do not adapt to this kind of projects therefore, in this paper we aim to design a model that incorporates characteristics of both of them to get a solution of a need found in society. In this study, we focus on the construction of a mobile application that answer to the lack of a system that integrates pharmaceutical products from different establishment through the appliance of usability concept with the UCD (User centered design) approach. In this case we only detail about four of the seven stages proposed in the model developed with its techniques, tools and activities conducted. Results obtained show that the model proposed achieve the expectative and its use is not limited to just mobile applications but to any kind of software project.
    Acceso restringido temporalmente
  • Master data management maturity model for the microfinance sector in Peru

    Vásquez Zúñiga, Daniel; Kukurelo Cruz, Romina; Raymundo Ibañez, Carlos; Dominguez, Francisco; Moguerza, Javier; u201213730@upc.edu.pe (Association for Computing Machinery, 2018)
    The microfinance sector has a strategic role since they facilitate integration and development of all social classes to sustained economic growth. In this way the actual point is the exponential growth of data, resulting from transactions and operations carried out with these companies on a daily basis, becomes imminent. Appropriate management of this data is therefore necessary because, otherwise, it will result in a competitive disadvantage due to the lack of valuable and quality information for decision-making and process improvement. The Master Data Management (MDM) give a new way in the Data management, reducing the gap between the business perspectives versus the technology perspective In this regard, it is important that the organization have the ability to implement a data management model for Master Data Management. This paper proposes a Master Data management maturity model for microfinance sector, which frames a series of formal requirements and criteria providing an objective diagnosis with the aim of improving processes until entities reach desired maturity levels. This model was implemented based on the information of Peruvian microfinance organizations. Finally, after validation of the proposed model, it was evidenced that it serves as a means for identifying the maturity level to help in the successful of initiative for Master Data management projects.
    Acceso restringido temporalmente
  • Quality data extraction methodology based on the labeling of coffee leaves with nutritional deficiencies

    Jungbluth, Adolfo; Yeng, Jon Li; U201311506@upc.edu.pe (Association for Computing Machinery, 2018-04)
    Nutritional deficiencies detection for coffee leaves is a task which is often undertaken manually by experts on the field known as agronomists. The process they follow to carry this task is based on observation of the different characteristics of the coffee leaves while relying on their own experience. Visual fatigue and human error in this empiric approach cause leaves to be incorrectly labeled and thus affecting the quality of the data obtained. In this context, different crowdsourcing approaches can be applied to enhance the quality of the data extracted. These approaches separately propose the use of voting systems, association rule filters and evolutive learning. In this paper, we extend the use of association rule filters and evolutive approach by combining them in a methodology to enhance the quality of the data while guiding the users during the main stages of data extraction tasks. Moreover, our methodology proposes a reward component to engage users and keep them motivated during the crowdsourcing tasks. The extracted dataset by applying our proposed methodology in a case study on Peruvian coffee leaves resulted in 93.33% accuracy with 30 instances collected by 8 experts and evaluated by 2 agronomic engineers with background on coffee leaves. The accuracy of the dataset was higher than independently implementing the evolutive feedback strategy and an empiric approach which resulted in 86.67% and 70% accuracy respectively under the same conditions.
    Acceso restringido temporalmente
  • Master data management maturity model for the successful of mdm initiatives in the microfinance sector in Peru

    Vásquez D. (Association for Computing Machinery, 2018-04)
    The microfinance sector has a strategic role since they facilitate integration and development of all social classes to sustained economic growth. In this way the actual point is the exponential growth of data, resulting from transactions and operations carried out with these companies on a daily basis, becomes imminent. Appropriate management of this data is therefore necessary because, otherwise, it will result in a competitive disadvantage due to the lack of valuable and quality information for decision-making and process improvement. The Master Data Management (MDM) give a new way in the Data management, reducing the gap between the business perspectives versus the technology perspective In this regard, it is important that the organization have the ability to implement a data management model for Master Data Management. This paper proposes a Master Data management maturity model for microfinance sector, which frames a series of formal requirements and criteria providing an objective diagnosis with the aim of improving processes until entities reach desired maturity levels. This model was implemented based on the information of Peruvian microfinance organizations. Finally, after validation of the proposed model, it was evidenced that it serves as a means for identifying the maturity level to help in the successful of initiative for Master Data management projects.
  • Implementación de una herramienta de integración de varios tipos de interacción humano-computadora para el desarrollo de nuevos sistemas multimodales

    Alzamora M. (International Institute of Informatics and Systemics, IIIS, 2018)
    Las personas interactúan con su entorno de forma multimodal. Esto es, con el uso simultaneo de sus sentidos. En los últimos años, se ha buscado una interacción multimodal humano-computador desarrollando nuevos dispositivos y usando diferentes canales de comunicación con el fin de brindar una experiencia de usuario interactiva más natural. Este trabajo presenta una herramienta que permite la integración de diferentes tipos de interacción humano computador y probarlo sobre una solución multimodal.
    Acceso abierto
  • Desarrollo de aplicaciones para personas con discapacidad motora utilizando Emotiv Epoc

    Vega A. (International Institute of Informatics and Systemics, IIIS, 2018-01-01)
    Personas con discapacidad motora presentan inconvenientes en el desarrollo de actividades tales como caminar, correr, comer. Además, en su mayoría, la visión y el intelecto no se ven afectados. Estas deficiencias no le permiten al manipular dispositivos tecnológicos que podrían ayudarlo a mejorar su calidad de vida como los smartphones. Presentamos una solución que permite superar esta limitación apoyada en la tecnología Brain Computer Interface).
    Acceso abierto
  • Implementation and customization of a smart mirror through a facial recognition authentication and a personalized news recommendation algorithm

    Garcia, Ivette Cristina Araujo; Salmon, Eduardo Rodrigo Linares; Riega, Rosario Villalta; Padilla, Alfredo Barrientos; U201213830@upc.edu.pe; U201214377@upc.edu.pe; rosario.villalta@upc.edu.pe (Institute of Electrical and Electronics Engineers Inc., 2018-04-09)
    In recent years the advancement of technologies of information and communication (technology ICTs) have helped to improve the quality of people's lives. The paradigm of internet of things (IoT, Internet of things) presents innovative solutions that are changing the style of life of the people. Because of this proposes the implementation of a smart mirror as part of a system of home automation, with which we intend to optimize the time of people as they prepare to start their day. This device is constructed from a reflective glass, LCD monitor, a Raspberry Pi 3, a camera and a platform IoT oriented cloud computing, where the information is obtained to show in the mirror, through the consumption of web services. The information is customizable thanks to a mobile application, which in turn allows the user photos to access the mirror, using authentication with facial recognition and user information to predict the news to show according to your profile. In addition, as part of the idea of providing the user a personalized experience, the Smart Mirror incorporates a news recommendation algorithm, implemented using a predictive model, which uses the algorithm, naive bayes.
  • Personal data protection maturity model for the micro financial sector in Peru

    Garcia, Arturo; Calle, Luis; Raymundo, Carlos; Dominguez, Francisco; Moguerza, Javier M.; u91099@upc.edu.pe; u201110732@upc.edu.pe; carlos.raymundo@upc.pe; javier.moguerza@urjc.es (Institute of Electrical and Electronics Engineers Inc., 2018-06-27)
    The micro financial sector is a strategic element in the economy of developing countries since it facilitates the integration and development of all social classes and let the economic growth. In this point is the growth of data is high every day in sector like the micro financial, resulting from transactions and operations carried out with these companies on a daily basis. Appropriate management of the personal data privacy policies is therefore necessary because, otherwise, it will comply with personal data protection laws and regulations and let take quality information for decision-making and process improvement. The present study proposes a personal data protection maturity model based on international standards of privacy and information security, which also reveals personal data protection capabilities in organizations. Finally, the study proposes a diagnostic and tracing assessment tool that was carried out for five companies in the micro financial sector and the obtained results were analyzed to validate the model and to help in success of data protection initiatives.
  • Full-fledged semantic indexing and querying model designed for seamless integration in legacy RDBMS

    Tekli, Joe; Chbeir, Richard; Traina, Agma J.M.; Traina, Caetano; Yetongnon, Kokou; Ibanez, Carlos Raymundo; Al Assad, Marc; Kallas, Christian; joe.tekli@lau.edu.lb (Elsevier B.V., 2018-09)
    In the past decade, there has been an increasing need for semantic-aware data search and indexing in textual (structured and NoSQL) databases, as full-text search systems became available to non-experts where users have no knowledge about the data being searched and often formulate query keywords which are different from those used by the authors in indexing relevant documents, thus producing noisy and sometimes irrelevant results. In this paper, we address the problem of semantic-aware querying and provide a general framework for modeling and processing semantic-based keyword queries in textual databases, i.e., considering the lexical and semantic similarities/disparities when matching user query and data index terms. To do so, we design and construct a semantic-aware inverted index structure called SemIndex, extending the standard inverted index by constructing a tightly coupled inverted index graph that combines two main resources: a semantic network and a standard inverted index on a collection of textual data. We then provide a general keyword query model with specially tailored query processing algorithms built on top of SemIndex, in order to produce semantic-aware results, allowing the user to choose the results' semantic coverage and expressiveness based on her needs. To investigate the practicality and effectiveness of SemIndex, we discuss its physical design within a standard commercial RDBMS allowing to create, store, and query its graph structure, thus enabling the system to easily scale up and handle large volumes of data. We have conducted a battery of experiments to test the performance of SemIndex, evaluating its construction time, storage size, query processing time, and result quality, in comparison with legacy inverted index. Results highlight both the effectiveness and scalability of our approach.
  • SemIndex: Semantic-Aware Inverted Index

    Universidad Peruana de Ciencias Aplicadas (UPC) (Springer International Publishing, 2015-02-10)
    This paper focuses on the important problem of semanticaware search in textual (structured, semi-structured, NoSQL) databases. This problem has emerged as a required extension of the standard containment keyword based query to meet user needs in textual databases and IR applications. We provide here a new approach, called SemIndex, that extends the standard inverted index by constructing a tight coupling inverted index graph that combines two main resources: a general purpose semantic network, and a standard inverted index on a collection of textual data. We also provide an extended query model and related processing algorithms with the help of SemIndex. To investigate its effectiveness, we set up experiments to test the performance of SemIndex. Preliminary results have demonstrated the effectiveness, scalability and optimality of our approach.
    Acceso abierto