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- Activities of Daily Living and Environment Recognition Using Mobile DevicesPublication . Ferreira, José M.; Pires, Ivan; Marques, Gonçalo; Garcia, Nuno M.; Zdravevski, Eftim; Lameski, Petre; Flórez-Revuelta, Francisco; Spinsante, Susanna; Xu, LinaThe recognition of Activities of Daily Living (ADL) using the sensors available in off-the-shelf mobile devices with high accuracy is significant for the development of their framework. Previously, a framework that comprehends data acquisition, data processing, data cleaning, feature extraction, data fusion, and data classification was proposed. However, the results may be improved with the implementation of other methods. Similar to the initial proposal of the framework, this paper proposes the recognition of eight ADL, e.g., walking, running, standing, going upstairs, going downstairs, driving, sleeping, and watching television, and nine environments, e.g., bar, hall, kitchen, library, street, bedroom, living room, gym, and classroom, but using the Instance Based k-nearest neighbour (IBk) and AdaBoost methods as well. The primary purpose of this paper is to find the best machine learning method for ADL and environment recognition. The results obtained show that IBk and AdaBoost reported better results, with complex data than the deep neural network methods.
- An Overview of Blockchain Integration with Robotics and Artificial IntelligencePublication . Lopes, Vasco; Alexandre, LuísBlockchain technology is growing everyday at a fast-passed rhythm and it's possible to integrate it with many systems, namely Robotics with AI services. However, this is still a recent field and there isn't yet a clear understanding of what it could potentially become. In this paper, we conduct an overview of many different methods and platforms that try to leverage the power of blockchain into robotic systems, to improve AI services or to solve problems that are present in the major blockchains, which can lead to the ability of creating robotic systems with increased capabilities and security. We present an overview, discuss the methods and conclude the paper with our view on the future of the integration of these technologies.
- An Overview of Blockchain Integration with Robotics and Artificial IntelligencePublication . Lopes, Vasco; Alexandre, LuísBlockchain technology is growing everyday at a fast-passed rhythm and it is possible to integrate it with many systems, namely Robotics with AI services. However, this is still a recent field and there is not yet a clear understanding of what it could potentially become. In this paper, we conduct an overview of many different methods and platforms that try to leverage the power of blockchain into robotic systems, to improve AI services, or to solve problems that are present in the major blockchains, which can lead to the ability of creating robotic systems with increased capabilities and security. We present an overview, discuss the methods, and conclude the paper with our view on the future of the integration of these technologies.
- Análise de sentimento em artigos de opiniãoPublication . Silva, Fatima; Silvano, Purificação; Leal, António; Oliveira, Fátima; Brazdil, Pavel; Cordeiro, João; Oliveira, DéboraO estudo apresentado realiza-se na interface entre a linguística e as ciências da computação, tendo como objetivo fazer a análise computacional de artigos de opinião na área da economia e finanças, seguindo o quadro teórico da análise de sentimento. Os principais objetivos do trabalho são i) determinar a orientação do sentimento, positivo ou negativo, e a intensidade dessa orientação através da anotação da polaridade do léxico, com incidência nos nomes e adjetivos, nos segmentos em que ocorre a expressão da opinião, e ii) verificar se um léxico específico para a área de economia e finanças tem vantagens na atribuição automática de sentimento sobre um léxico geral. Para atingir esses objetivos, foiselecionado um corpus de 45 textos, analisado em duas fases por anotadores com formação distinta. Primeiro, uma amostra de 10 textos foi obtida e anotada pelos investigadores da área de linguística, coautores deste artigo, com o objetivo de desenvolver um modelo linguístico para determinar a orientação e intensidade da polaridade de termos em artigos de opinião e extrair termos de léxico relevantes para esta área de estudo. Em seguida, um conjunto de 35 textos foi anotado por estudantes universitários, seguindo o método utilizado na primeira amostra. Com base na anotação linguística, a equipa das ciências da computação procurou determinar até que ponto um léxico de sentimento geral para a língua portuguesa – SentiLex - é suficiente para caracterizar o sentimento de uma frase de maneira satisfatória ou se o EconoLex, um léxico específico de sentimento, seria mais eficaz. O léxico específico inclui termos e expressões multipalavra relevantes para o domínio da economia e finanças e para a língua portuguesa, e foi elaborado pelos autores deste estudo. Os dados foram analisados usando uma metodologia mista, qualitativa e quantitativa. Os resultados obtidos permitem-nos considerar os seguintes itens como contributos desta investigação: i) a elaboração do modelo de anotação linguística adotado para a análise da orientação e da intensidade da polaridade do léxico, em especial dos nomes e adjetivos; ii) o papel central, ainda que não exclusivo, dos adjetivos para a determinação da polaridade do sentimento nos segmentos opinativos dos artigos do corpus; iii) o desenvolvimento de um novo léxico de sentimento específico português para a área da economia e finanças; iv) a melhoria do desempenho computacional do EconoLex⨁SentiLex em relação ao SentiLex no que se refere ao desempenho na caracterização automática de sentimento. Apesar destes resultados positivos, há algumas limitações que constituem os elementos a desenvolver na continuidade deste trabalho interdisciplinar, nomeadamente a análise linguística mais detalhada das classes gramaticais estudadas, a consideração de outros elementos/estruturas linguísticas determinantes para a caracterização do sentimento em SN/ frase, o alargamento do corpus, o aumento do léxico específico do domínio e a afinação dos métodos automáticos de identificação de termos de sentimento em textos de opinião e determinação da sua intensidade.
- Analysis and Simulation of Drainage Capacity of Urban Pipe NetworkPublication . Gomes, R.; Vellando, P.; Sousa, J.; Sá Marques, A.; Muranho, JoãoIn the last decades the urban area of Leiria (Portugal) has spread quickly and the impervious surfaces increased significantly, mostly because of the type of pavements used (asphalt and Portuguese cobblestone) and the area occupied by buildings. One of the major problems is related to the recurrent floods in Leiria’s downtown during periods of higher rainfall intensity, which affect the economic activities, the environment and the residents’ lives. The urban area benefits from a large drainage network, but in some zones it has low performance, due to the degradation of the infrastructure and the successive located interventions occurred in the last decades (for network expansion and rehabilitation works). To minimize the flooding impacts in Leiria’s downtown, the municipality intends to build an underground pipeline (a length of 1.5 kilometres, with a 2.0 metres diameter and 0.2% slope) to convey the runoff by gravity from Leiria’s downtown to the river. This paper presents an integrated study of the urban catchment and the drainage network capacity using the Storm Water Management Model (SWMM). This study included the analysis of the solution for different rainfall intensities (corresponding to different return periods) to assess its performance and, when required, suggest additional recommendations.
- Android Library for Recognition of Activities of Daily Living: Implementation Considerations, Challenges, and SolutionsPublication . Pires, Ivan; Teixeira, Maria Cristina Canavarro; Pombo, Nuno; Garcia, Nuno M.; Flórez-Revuelta, Francisco; Spinsante, Susanna; Goleva, Rossitza; Zdravevski, EftimBackground: Off-the-shelf-mobile devices have several sensors available onboard that may be used for the recognition of Activities of Daily Living (ADL) and the environments where they are performed. This research is focused on the development of Ambient Assisted Living (AAL) systems, using mobile devices for the acquisition of the different types of data related to the physical and physiological conditions of the subjects and the environments. Mobile devices with the Android Operating Systems are the least expensive and exhibit the biggest market while providing a variety of models and onboard sensors. Objective: This paper describes the implementation considerations, challenges and solutions about a framework for the recognition of ADL and the environments, provided as an Android library. The framework is a function of the number of sensors available in different mobile devices and utilizes a variety of activity recognition algorithms to provide a rapid feedback to the user. Methods: The Android library includes data fusion, data processing, features engineering and classification methods. The sensors that may be used are the accelerometer, the gyroscope, the magnetometer, the Global Positioning System (GPS) receiver and the microphone. The data processing includes the application of data cleaning methods and the extraction of features, which are used with Deep Neural Networks (DNN) for the classification of ADL and environment. Throughout this work, the limitations of the mobile devices were explored and their effects have been minimized. Results: The implementation of the Android library reported an overall accuracy between 58.02% and 89.15%, depending on the number of sensors used and the number of ADL and environments recognized. Compared with the results available in the literature, the performance of the library reported a mean improvement of 2.93%, and they do not differ at the maximum found in prior work, that based on the Student’s t-test. Conclusion: This study proves that ADL like walking, going upstairs and downstairs, running, watching TV, driving, sleeping and standing activities, and the bedroom, cooking/kitchen, gym, classroom, hall, living room, bar, library and street environments may be recognized with the sensors available in off-the-shelf mobile devices. Finally, these results may act as a preliminary research for the development of a personal digital life coach with a multi-sensor mobile device commonly used daily.
- Anonymized Data Assessment via Analysis of Variance: An Application to Higher Education EvaluationPublication . Ferrão, Maria Eugénia; Prata, Paula; Fazendeiro, PauloThe assessment of the utility of an anonymized data set can be operational-ized by the determination of the amount of information loss. To investigate the possible degradation of the relationship between variables after anony-mization, hence measuring the loss, we perform an a posteriori analysis of variance. Several anonymized scenarios are compared with the original data. Differential privacy is applied as data anonymization process. We assess data utility based on the agreement between the original data structure and the anonymized structures. Data quality and utility are quantified by standard metrics, characteristics of the groups obtained. In addition, we use analysis of variance to show how estimates change. For illustration, we apply this ap-proach to Brazilian Higher Education data with focus on the main effects of interaction terms involving gender differentiation. The findings indicate that blindly using anonymized data for scientific purposes could potentially un-dermine the validity of the conclusions.
- Application of Lifelong Learning with CNNs to Visual Robotic Classification TasksPublication . Zacarias, Abel; Alexandre, LuísThe field of robotics is becoming continuously more important, due to the impact it can bring to our everyday life. A long standing problem with neural network learning is the catastrophic forgetting when one tries to use the same network to learn more than one task. In this paper we present results of the application of a method to avoid catastrophic forgetting while using Convolutional Neural Networks (CNNs) to some visual recognition tasks relevant to the field of robotics. The results show that with this method a robot can learn new tasks without forgetting the previous learned tasks. Results also showed that if we applied this method, the performance on isolated tasks increases and it is better to use it than train a CNN in an isolated way (single task). We use for our experiments two well known data sets, namely, Olivetti Faces and Fashion-MNIST.
- Application of texture analysis to muscle MRI: 1-What kind of information should be expected from texture analysis?Publication . Certaines, Jacques De; Larcher, Thibaut; Duda, Dorota; Azzabou, Noura; Eliat, Pierre-Antoine; Escudero, Luis M.; Pinheiro, Antonio M. G.; Yang, Guanyu; Coatrieux, Jean-Louis; Snezkho, Eduard; Shukelovich, Alexey; Pereira, Manuela; Lerski, RichardSeveral previous clinical or preclinical studies using computerized texture analysis of MR Images have demonstrated much more clinical discrimination than visual image analysis by the radiologist. In muscular dystrophy, a discriminating power has been already demonstrated with various methods of texture analysis of magnetic resonance images (MRI-TA). Unfortunately, a scale gap exists between the spatial resolutions of histological and MR images making a direct correlation impossible. Furthermore, the effect of the various histological modifications on the gray level of each pixel is complex and cannot be easily analyzed. Consequently, clinicians will not accept the use of MRI-TA in routine practice if TA remains a “black box” without clinical correspondence at a tissue level. A goal therefore of the multicenter European COST action MYO-MRI is to optimize MRI-TA methods in muscular dystrophy and to elucidate the histological meaning of MRI textures.
- Applications of artificial immune systems to computer security: A surveyPublication . Fernandes, Diogo A. B.; Freire, Mario; Fazendeiro, Paulo; Inácio, Pedro R. M.For the last two decades, artificial immune systems have been studied in various fields of knowledge. They were shown to be particularly effective tools at detecting anomalous behavior in the security domain of computer systems. This article introduces the principles of artificial immune systems and surveys several works applying such systems to computer security problems. The works herein discussed are summarized and open issues are pointed out afterwards, elaborating on a novel applicability of these systems to cloud computing environments.