Dynamic Bayesian network for semantic place classification in mobile robotics

In this paper, the problem of semantic place categorization in mobile robotics is addressed by considering a time-based probabilistic approach called dynamic Bayesian mixture model (DBMM), which is an improved variation of the dynamic Bayesian network. More specifically, multi-class semantic classification is performed by a DBMM composed of a mixture of heterogeneous base classifiers, using geometrical features computed from 2D laserscanner data, where the sensor is mounted on-board a moving robot operating indoors. Besides its capability to combine different probabilistic classifiers, the DBMM approach also incorporates time-based (dynamic) inferences in the form of previous class-conditional probabilities and priors. Extensive experiments were carried out on publicly available benchmark datasets, highlighting the influence of the number of time-slices and the effect of additive smoothing on the classification performance of the proposed approach. Reported results, under different scenarios and conditions, show the effectiveness and competitive performance of the DBMM.

Secure and Privacy-aware Data Collection and Processing in Mobile Health Systems

Healthcare systems have assimilated information and communication technologies in order to improve the quality of healthcare and patient's experience at reduced costs. The increasing digitalization of people's health information raises however new threats regarding information security and privacy. Accidental or deliberate data breaches of health data may lead to societal pressures, embarrassment and discrimination. Information security and privacy are paramount to achieve high quality healthcare services, and further, to not harm individuals when providing care. With that in mind, we give special attention to the category of Mobile Health (mHealth) systems. That is, the use of mobile devices (e.g., mobile phones, sensors, PDAs) to support medical and public health. Such systems, have been particularly successful in developing countries, taking advantage of the flourishing mobile market and the need to expand the coverage of primary healthcare programs. Many mHealth initiatives, however, fail to address security and privacy issues. This, coupled with the lack of specific legislation for privacy and data protection in these countries, increases the risk of harm to individuals. The overall objective of this thesis is to enhance knowledge regarding the design of security and privacy technologies for mHealth systems. In particular, we deal with mHealth Data Collection Systems (MDCSs), which consists of mobile devices for collecting and reporting health-related data, replacing paper-based approaches for health surveys and surveillance. This thesis consists of publications contributing to mHealth security and privacy in various ways: with a comprehensive literature review about mHealth in Brazil; with the design of a security framework for MDCSs (SecourHealth); with the design of a MDCS (GeoHealth); with the design of Privacy Impact Assessment template for MDCSs; and with the study of ontology-based obfuscation and anonymisation functions for health data.

Agent based risk patient management

This paper explores the role of information and communication technologies in managing risk and early discharge patients, and suggests innovative actions in the area of E-Health services. Treatments of chronic illnesses, or treatments of special needs such as cardiovascular diseases, are conducted in long-stay hospitals, and in some cases, in the homes of patients with a follow-up from primary care centre. The evolution of this model is following a clear trend: trying to reduce the time and the number of visits by patients to health centres and derive tasks, so far as possible, toward outpatient care. Also the number of Early Discharge Patients (EDP) is growing, thus permiting a saving in the resources of the care center. The adequacy of agent and mobile technologies is assessed in light of the particular requirements of health care applications. A software system architecture is outlined and discussed. The major contributions are: first, the conceptualization of multiple mobile and desktop devices as part of a single distributed computing system where software agents are being executed and interact from their remote locations. Second, the use of distributed decision making in multiagent systems, as a means to integrate remote evidence and knowledge obtained from data that is being collected and/or processed by distributed devices. The system will be applied to patients with cardiovascular or Chronic Obstructive Pulmonary Diseases (COPD) as well as to ambulatory surgery patients. The proposed system will allow to transmit the patient's location and some information about his/her illness to the hospital or care centre

Plan de negocios Bicigo app

La gran cantidad de personas interesadas actualmente en cuidar de su salud por medio de la Bicicleta, es una tendencia que cada vez toma más fuerza y por esto, se tomara como ventaja que la ciudad de Bogotá con sus últimos alcaldes han decidió apoyar el uso de esta. Aplicación para realizar grupos de ciclistas y poder salir cualquier día de la semana acompañado de más personas por un tema de transporte pero también de ocio. El objetivo es que las personas que no utilizan la bicicleta por miedo a salir solos, puedan unirse a diferentes grupos y hacer bici paseos por la ciudad, también contemplamos el hecho de que existen personas que quieren montar bicicleta como aficionados, es decir que salen por la carreteras aledañas a la capital pero muchas veces no tienen grupo con quien rodar. Queremos para el año 2020, lograr ser una de las aplicaciones de Bicicletas más exitosa de la ciudadanía de Bogotá, siendo una de las aplicaciones que mas apoya el uso diario y deportivo de la bicicleta. Nuestra aplicación ofrece el servicio principalmente de reunir gente y hacer paseos con diferentes personas haciendo uso de las bicicletas, dentro de la ciudad como ocio y transporte se realizarían en la mañana y noches, pero así mismo realizar grupos para hacer uso de la bicicleta por carreteras, es decir más como modo profesional o aficionado. Nuestra aplicación cuenta con una interface para seleccionar el tipo de bici usuario y segundo por donde o a donde quiere dirigirse para así mismo mostrarle las rutas cercanas a él. Nuestra característica principal es la unión de diferentes grupos, personas y entidades para hacer uso de la Bicicleta, tenemos una plataforma interactiva y fácil de usar, tan fácil que cualquier persona que no esté inmersa en el mundo de los Smartphone o aplicaciones pueda aprender a usarla. Unas de las ventajas con las que cuento es que desde muy joven me ha gustado montar en bicicletas y es así como decido crear una aplicación ya que compañeros, familiares y conocidos no salían a montar bicicleta solo conmigo, preferían que fuese un grupo más grande. Así mismo cuento con 3 compañeros de la universidad Javeriana que son programadores y ellos me van a brindar apoyo con la programación de la aplicación, y una compañera cercana a mí que estudio diseño industrial y me brindara apoyo con el diseño e imagen corporativa de la aplicación. Cuento con planta física para ubicar la oficina de nuestra empresa. Esta aplicación va dirigida principalmente a los habitantes de la ciudad de Bogotá, interesados en el cuidado de su salud combinado con medio de transporte, y personas correspondientes al estrato 2 en adelante, ya que son las personas que normalmente hacen uso de la bicicleta o que son personas potenciales para empezar hacer uso de la bicicleta. . La ciudad de Bogotá cuenta con 8’037.732 habitantes y este proyecto va ser desarrollado en toda la ciudad, toca tener en cuenta que la ciudad esta mesclada entre la diferente estratificación, no dirigimos a los estratos 2 y 3 que tenga la posibilidad de tener su Bicicleta y un celular tipo Smartphone, para los estratos 4, 5 y 6 sabemos que tiene la facilidad de obtener una bicicleta y ellos son nuestro usuario potencial el cual generaríamos un cambio y tomarían su bicicleta para hacer ejercicio como ocio y como medio de transporte. En cuanto a la proyección financiera para la aplicación, como se mencionó anteriormente, contamos con una gran ventaja, ya que la inversión requerida será menor debido a la propiedad con la que cuento para llevar a cabo el proyecto. Una propiedad de 60 metros cuadrados para empezar, la cual cuenta con salas de reunión y auditorio, un parqueaderos exteriores. Al hacer la calculación se va tener en cuenta el pago de un arriendo sin importan que sea de nuestra propiedad y así poder evidenciar realmente como es el estado financiero y no subsidiarla. Por otro lado, la inversión en efectivo que se necesitara será aproximadamente de $100.000.000 que serán $50.000.000 de mis padres y el restante saldrán de mis ahorros, Javier Amortegui Babativa, los cuales serán distribuidos para adecuación de planta, equipos y sistemas $17.616.880, para publicidad y mercadeo: $30.000.000, creación de la aplicación $34.000.000, sistemas IOS + Android $421.600, Gastos de composición empresarial y bancarios $11.000.000 y por último se va tener un provisión para imprevistos por el restante $6.961.520. Nuestras proyecciones de ventas han sido basadas en aplicaciones similares con un mismo formato de lucro con el tema de bicicletas pero no con la misma idea de negocio, nuestras proyecciones de ventas estimadas serán de $20.000.000 a $25.000.000 los primeros 3 meses, mientras tomamos fuerza en el mercado.

mHealth-based Methods for Neuromotor Assessment and Rehabilitation

Recent years observed massive growth in wearable technology, everything can be smart: phones, watches, glasses, shirts, etc. These technologies are prevalent in various fields: from wellness/sports/fitness to the healthcare domain. The spread of this phenomenon led the World-Health-Organization to define the term 'mHealth' as "medical and public health practice supported by mobile devices, such as mobile phones, patient monitoring devices, personal digital assistants, and other wireless devices". Furthermore, mHealth solutions are suitable to perform real-time wearable Biofeedback (BF) systems: sensors in the body area network connected to a processing unit (smartphone) and a feedback device (loudspeaker) to measure human functions and return them to the user as (bio)feedback signal. During the COVID-19 pandemic, this transformation of the healthcare system has been dramatically accelerated by new clinical demands, including the need to prevent hospital surges and to assure continuity of clinical care services, allowing pervasive healthcare. Never as of today, we can say that the integration of mHealth technologies will be the basis of this new era of clinical practice. In this scenario, this PhD thesis's primary goal is to investigate new and innovative mHealth solutions for the Assessment and Rehabilitation of different neuromotor functions and diseases. For the clinical assessment, there is the need to overcome the limitations of subjective clinical scales. Creating new pervasive and self-administrable mHealth solutions, this thesis investigates the possibility of employing innovative systems for objective clinical evaluation. For rehabilitation, we explored the clinical feasibility and effectiveness of mHealth systems. In particular, we developed innovative mHealth solutions with BF capability to allow tailored rehabilitation. The main goal that a mHealth-system should have is improving the person's quality of life, increasing or maintaining his autonomy and independence. To this end, inclusive design principles might be crucial, next to the technical and technological ones, to improve mHealth-systems usability.

Robust Adaptive Control with Applications to Multi-Agent Systems and Mobile Robotics

This thesis deals with robust adaptive control and its applications, and it is divided into three main parts. The first part is about the design of robust estimation algorithms based on recursive least squares. First, we present an estimator for the frequencies of biased multi-harmonic signals, and then an algorithm for distributed estimation of an unknown parameter over a network of adaptive agents. In the second part of this thesis, we consider a cooperative control problem over uncertain networks of linear systems and Kuramoto systems, in which the agents have to track the reference generated by a leader exosystem. Since the reference signal is not available to each network node, novel distributed observers are designed so as to reconstruct the reference signal locally for each agent, and therefore decentralizing the problem. In the third and final part of this thesis, we consider robust estimation tasks for mobile robotics applications. In particular, we first consider the problem of slip estimation for agricultural tracked vehicles. Then, we consider a search and rescue application in which we need to drive an unmanned aerial vehicle as close as possible to the unknown (and to be estimated) position of a victim, who is buried under the snow after an avalanche event. In this thesis, robustness is intended as an input-to-state stability property of the proposed identifiers (sometimes referred to as adaptive laws), with respect to additive disturbances, and relative to a steady-state trajectory that is associated with a correct estimation of the unknown parameter to be found.

Progetto DERNetSoft: design e sviluppo di un'app mobile per un futuro più sostenibile

Da anni ormai siamo inconsapevolmente "in guerra" con la natura. Sfruttiamo e sprechiamo risorse naturali senza alcuna considerazione per le conseguenze. Le città sono considerate le principali fonti dei problemi ambientali e la regolamentazione del consumo energetico urbano è fondamentale per affrontare il cambiamento climatico globale. DERNetSoft Inc, start-up californiana, ha intravisto il problema come un’opportunità per creare un proprio business il cui scopo è quello di contribuire a costruire un futuro a basse emissioni di carbonio, fornendo un servizio tecnologico scalabile e conveniente per consentire la riduzione delle emissioni di gas a effetto serra a livello mondiale. Per farlo vengono utilizzati i concetti di DER Energy e Aggregation Energy. Nel volume di tesi si affrontano e descrivono la progettazione di un’applicazione mobile, multipiattaforma, sviluppata con il framework React Native. L’app sviluppata è supportata da un’architettura basata su dei micro servizi implementati tramite il cloud di Google. La principale funzionalità dell’applicazione sviluppata è quella di notificare gli utenti di un evento ELRP che, attraverso incentivi economici, promuove la riduzione del consumo energetico durante i periodi di forte stress o emergenza della rete elettrica.

Performance Analysis of 5G based Positioning in Railway Applications

Rail transportation has significant importance in the future world. This importance is tightly bounded to accessible, sustainable, efficient and safe railway systems. Precise positioning in railway applications is essential for increasing railway traffic, train-track control, collision avoidance, train management and autonomous train driving. Hence, precise train positioning is a safety-critical application. Nowadays, positioning in railway applications highly depends on a cellular-based system called GSM-R, a railway-specific version of Global System for Mobile Communications (GSM). However, GSM-R is a relatively outdated technology and does not provide enough capacity and precision demanded by future railway networks. One option for positioning is mounting Global Navigation Satellite System (GNSS) receivers on trains as a low-cost solution. Nevertheless, GNSS can not provide continuous service due to signal interruption by harsh environments, tunnels etc. Another option is exploiting cellular-based positioning methods. The most recent cellular technology, 5G, provides high network capacity, low latency, high accuracy and high availability suitable for train positioning. In this thesis, an approach to 5G-based positioning for railway systems is discussed and simulated. Observed Time Difference of Arrival (OTDOA) method and 5G Positioning Reference Signal (PRS) are used. Simulations run using MATLAB, based on existing code developed for 5G positioning by extending it for Non Line of Sight (NLOS) link detection and base station exclusion algorithms. Performance analysis for different configurations is completed. Results show that efficient NLOS detection improves positioning accuracy and implementing a base station exclusion algorithm helps for further increase.

Grant-Free Access for Massive IoT Based on Interference Cancellation and Massive MIMO

Recent years have witnessed an increasing evolution of wireless mobile networks, with an intensive research work aimed at developing new efficient techniques for the future 6G standards. In the framework of massive machine-type communication (mMTC), emerging Internet of Things (IoT) applications, in which sensor nodes and smart devices transmit unpredictably and sporadically short data packets without coordination, are gaining an increasing interest. In this work, new medium access control (MAC) protocols for massive IoT, capable of supporting a non-instantaneous feedback from the receiver, are studied. These schemes guarantee an high time for the acknowledgment (ACK) messages to the base station (BS), without a significant performance loss. Then, an error floor analysis of the considered protocols is performed in order to obtain useful guidelines for the system design. Furthermore, non-orthogonal multiple access (NOMA) coded random access (CRA) schemes based on power domain are here developed. The introduction of power diversity permits to solve more packet collision at the physical (PHY) layer, with an important reduction of the packet loss rate (PLR) in comparison to the number of active users in the system. The proposed solutions aim to improve the actual grant-free protocols, respecting the stringent constraints of scalability, reliability and latency requested by 6G networks.

[almost An Autobiography: A Study Of Social Scientists In Health Based On The Lattes Curriculum].

Among the various ways of adopting the biographical approach, we used the curriculum vitaes (CVs) of Brazilian researchers who work as social scientists in health as our research material. These CVs are part of the Lattes Platform of CNPq - the National Council for Scientific and Technological Development, which includes Research and Institutional Directories. We analyzed 238 CVs for this study. The CVs contain, among other things, the following information: professional qualifications, activities and projects, academic production, participation in panels for the evaluation of theses and dissertations, research centers and laboratories and a summarized autobiography. In this work there is a brief review of the importance of autobiography for the social sciences, emphasizing the CV as a form of autobiographical practice. We highlight some results, such as it being a group consisting predominantly of women, graduates in social sciences, anthropology, sociology or political science, with postgraduate degrees. The highest concentration of social scientists is located in Brazil's southern and southeastern regions. In some institutions the main activities of social scientists are as teachers and researchers with great thematic diversity in research.

Phylogenetics, Ancestral State Reconstruction, And A New Infrafamilial Classification Of The Pantropical Ochnaceae (medusagynaceae, Ochnaceae S.str., Quiinaceae) Based On Five Dna Regions.

Ochnaceae s.str. (Malpighiales) are a pantropical family of about 500 species and 27 genera of almost exclusively woody plants. Infrafamilial classification and relationships have been controversial partially due to the lack of a robust phylogenetic framework. Including all genera except Indosinia and Perissocarpa and DNA sequence data for five DNA regions (ITS, matK, ndhF, rbcL, trnL-F), we provide for the first time a nearly complete molecular phylogenetic analysis of Ochnaceae s.l. resolving most of the phylogenetic backbone of the family. Based on this, we present a new classification of Ochnaceae s.l., with Medusagynoideae and Quiinoideae included as subfamilies and the former subfamilies Ochnoideae and Sauvagesioideae recognized at the rank of tribe. Our data support a monophyletic Ochneae, but Sauvagesieae in the traditional circumscription is paraphyletic because Testulea emerges as sister to the rest of Ochnoideae, and the next clade shows Luxemburgia+Philacra as sister group to the remaining Ochnoideae. To avoid paraphyly, we classify Luxemburgieae and Testuleeae as new tribes. The African genus Lophira, which has switched between subfamilies (here tribes) in past classifications, emerges as sister to all other Ochneae. Thus, endosperm-free seeds and ovules with partly to completely united integuments (resulting in an apparently single integument) are characters that unite all members of that tribe. The relationships within its largest clade, Ochnineae (former Ochneae), are poorly resolved, but former Ochninae (Brackenridgea, Ochna) are polyphyletic. Within Sauvagesieae, the genus Sauvagesia in its broad circumscription is polyphyletic as Sauvagesia serrata is sister to a clade of Adenarake, Sauvagesia spp., and three other genera. Within Quiinoideae, in contrast to former phylogenetic hypotheses, Lacunaria and Touroulia form a clade that is sister to Quiina. Bayesian ancestral state reconstructions showed that zygomorphic flowers with adaptations to buzz-pollination (poricidal anthers), a syncarpous gynoecium (a near-apocarpous gynoecium evolved independently in Quiinoideae and Ochninae), numerous ovules, septicidal capsules, and winged seeds with endosperm are the ancestral condition in Ochnoideae. Although in some lineages poricidal anthers were lost secondarily, the evolution of poricidal superstructures secured the maintenance of buzz-pollination in some of these genera, indicating a strong selective pressure on keeping that specialized pollination system.

Ihwg-μnir: A Miniaturised Near-infrared Gas Sensor Based On Substrate-integrated Hollow Waveguides Coupled To A Micro-nir-spectrophotometer.

A miniaturised gas analyser is described and evaluated based on the use of a substrate-integrated hollow waveguide (iHWG) coupled to a microsized near-infrared spectrophotometer comprising a linear variable filter and an array of InGaAs detectors. This gas sensing system was applied to analyse surrogate samples of natural fuel gas containing methane, ethane, propane and butane, quantified by using multivariate regression models based on partial least square (PLS) algorithms and Savitzky-Golay 1(st) derivative data preprocessing. The external validation of the obtained models reveals root mean square errors of prediction of 0.37, 0.36, 0.67 and 0.37% (v/v), for methane, ethane, propane and butane, respectively. The developed sensing system provides particularly rapid response times upon composition changes of the gaseous sample (approximately 2 s) due the minute volume of the iHWG-based measurement cell. The sensing system developed in this study is fully portable with a hand-held sized analyser footprint, and thus ideally suited for field analysis. Last but not least, the obtained results corroborate the potential of NIR-iHWG analysers for monitoring the quality of natural gas and petrochemical gaseous products.

Can We Predict The Clinical Outcomes Of Genitourinary Trauma Patients And Offer Them An Evidence-based Support? The Case For Telemedicine Network.

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Iis--integrated Interactome System: A Web-based Platform For The Annotation, Analysis And Visualization Of Protein-metabolite-gene-drug Interactions By Integrating A Variety Of Data Sources And Tools.

High-throughput screening of physical, genetic and chemical-genetic interactions brings important perspectives in the Systems Biology field, as the analysis of these interactions provides new insights into protein/gene function, cellular metabolic variations and the validation of therapeutic targets and drug design. However, such analysis depends on a pipeline connecting different tools that can automatically integrate data from diverse sources and result in a more comprehensive dataset that can be properly interpreted. We describe here the Integrated Interactome System (IIS), an integrative platform with a web-based interface for the annotation, analysis and visualization of the interaction profiles of proteins/genes, metabolites and drugs of interest. IIS works in four connected modules: (i) Submission module, which receives raw data derived from Sanger sequencing (e.g. two-hybrid system); (ii) Search module, which enables the user to search for the processed reads to be assembled into contigs/singlets, or for lists of proteins/genes, metabolites and drugs of interest, and add them to the project; (iii) Annotation module, which assigns annotations from several databases for the contigs/singlets or lists of proteins/genes, generating tables with automatic annotation that can be manually curated; and (iv) Interactome module, which maps the contigs/singlets or the uploaded lists to entries in our integrated database, building networks that gather novel identified interactions, protein and metabolite expression/concentration levels, subcellular localization and computed topological metrics, GO biological processes and KEGG pathways enrichment. This module generates a XGMML file that can be imported into Cytoscape or be visualized directly on the web. We have developed IIS by the integration of diverse databases following the need of appropriate tools for a systematic analysis of physical, genetic and chemical-genetic interactions. IIS was validated with yeast two-hybrid, proteomics and metabolomics datasets, but it is also extendable to other datasets. IIS is freely available online at: http://www.lge.ibi.unicamp.br/lnbio/IIS/.

Cluster Analysis To Identify Elderly People's Profiles: A Healthcare Strategy Based On Frailty Characteristics.

The new social panorama resulting from aging of the Brazilian population is leading to significant transformations within healthcare. Through the cluster analysis strategy, it was sought to describe the specific care demands of the elderly population, using frailty components. Cross-sectional study based on reviewing medical records, conducted in the geriatric outpatient clinic, Hospital de Clínicas, Universidade Estadual de Campinas (Unicamp). Ninety-eight elderly users of this clinic were evaluated using cluster analysis and instruments for assessing their overall geriatric status and frailty characteristics. The variables that most strongly influenced the formation of clusters were age, functional capacities, cognitive capacity, presence of comorbidities and number of medications used. Three main groups of elderly people could be identified: one with good cognitive and functional performance but with high prevalence of comorbidities (mean age 77.9 years, cognitive impairment in 28.6% and mean of 7.4 comorbidities); a second with more advanced age, greater cognitive impairment and greater dependence (mean age 88.5 years old, cognitive impairment in 84.6% and mean of 7.1 comorbidities); and a third younger group with poor cognitive performance and greater number of comorbidities but functionally independent (mean age 78.5 years old, cognitive impairment in 89.6% and mean of 7.4 comorbidities). These data characterize the profile of this population and can be used as the basis for developing efficient strategies aimed at diminishing functional dependence, poor self-rated health and impaired quality of life.