Behavior monitoring and behavioral exchange: an approach from geospatial technologies involving gamification techniques

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Variation in Haemodynamic Monitoring for Major Surgery in European Nations: Secondary Analysis of the EuSOS Dataset

BACKGROUND: The use of cardiac output monitoring may improve patient outcomes after major surgery. However, little is known about the use of this technology across nations. METHODS: This is a secondary analysis of a previously published observational study. Patients aged 16 years and over undergoing major non-cardiac surgery in a 7-day period in April 2011 were included into this analysis. The objective is to describe prevalence and type of cardiac output monitoring used in major surgery in Europe. RESULTS: Included in the analysis were 12,170 patients from the surgical services of 426 hospitals in 28 European nations. One thousand four hundred and sixteen patients (11.6 %) were exposed to cardiac output monitoring, and 2343 patients (19.3 %) received a central venous catheter. Patients with higher American Society of Anesthesiologists (ASA) scores were more frequently exposed to cardiac output monitoring (ASA I and II, 643 patients [8.6 %]; ASA III-V, 768 patients [16.2 %]; p < 0.01) and central venous catheter (ASA I and II, 874 patients [11.8 %]; ASA III-V, 1463 patients [30.9 %]; p < 0.01). In elective surgery, 990 patients (10.8 %) were exposed to cardiac output monitoring, in urgent surgery 252 patients (11.7 %) and in emergency surgery 173 patients (19.8 %). A central venous catheter was used in 1514 patients (16.6 %) undergoing elective, in 480 patients (22.2 %) undergoing urgent and in 349 patients (39.9 %) undergoing emergency surgery. Nine hundred sixty patients (7.9 %) were monitored using arterial waveform analysis, 238 patients (2.0 %) using oesophageal Doppler ultrasound, 55 patients (0.5 %) using a pulmonary artery catheter and 44 patients (2.0 %) using other technologies. Across nations, cardiac output monitoring use varied from 0.0 % (0/249 patients) to 27.5 % (19/69 patients), whilst central venous catheter use varied from 5.6 % (7/125 patients) to 43.2 % (16/37 patients). CONCLUSIONS: One in ten patients undergoing major surgery is exposed to cardiac output monitoring whilst one in five receives a central venous catheter. The use of both technologies varies widely across Europe.

Fat Mass Index Performs Best in Monitoring Management of Obesity in Prepubertal Children

An early and accurate recognition of success in treating obesity may increase the compliance of obese children and their families to intervention programs. This observational, prospective study aimed to evaluate the ability and the time to detect a significant reduction of adiposity estimated by body mass index (BMI), percentage of fat mass (%FM), and fat mass index (FMI) during weight management in prepubertal obese children.

The monitoring of rammed earth experimental walls and characterization of rammed earth samples

RESTAPIA 2012 - Int. Conf. on Rammed Earth Conservation, Valencia, 21-23 June 2012

Enhancing physical activity coaching through personalized motivational strategies and self-adaptive goal-setting: development of self-adaptive processes in a monitoring and coaching smartphone application

Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica

Monitoring antibiotics in the environment. Study of Quinoxaline derivatives bioactivity

Dissertação para obtenção do Grau de Doutor em Química Sustentável

Lightweight monitoring of transactional memory programs

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Multivariate analysis applied to clinical analysis data

Dissertação para obtenção do Grau de Mestre em Engenharia e Gestão Industrial

Service-oriented infrastructure to support the control, monitoring and management of a shop floor system

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores

Monitoring and modelling of membrane bioreactors for wastewater treatment incorporating 2D fluorescence spectroscopy

Dissertação para obtenção do Grau de Doutor em Engenharia Química e Bioquímica, Especialidade em Engenharia Bioquímica

Development of a satellite based PM10 concentration product for urban areas

Dissertação para obtenção do Grau de Doutor em Engenharia do Ambiente

Hole cleaning performance monitoring during the drilling of directional wells

During drilling operation, cuttings are produced downhole and must be removed to avoid issues which can lead to Non Productive Time (NPT). Most of stuck pipe and then Bottom-Hole Assembly (BHA) lost events are hole cleaned related. There are many parameters which help determine hole cleaning conditions, but a proper selection of the key parameters will facilitate monitoring hole cleaning conditions and interventions. The aim of Hole Cleaning Monitoring is to keep track of borehole conditions including hole cleaning efficiency and wellbore stability issues during drilling operations. Adequate hole cleaning is the one of the main concerns in the underbalanced drilling operations especially for directional and horizontal wells. This dissertation addresses some hole cleaning fundamentals which will act as the basis for recommendation practice during drilling operations. Understand how parameters such as Flowrate, Rotation per Minute (RPM), Rate of Penetration (ROP) and Mud Weight are useful to improve the hole cleaning performance and how Equivalent Circulate Density (ECD), Torque & Drag (T&D) and Cuttings Volumes coming from downhole help to indicate how clean and stable the well is. For case study, hole cleaning performance or cuttings volume removal monitoring, will be based on real-time measurements of the cuttings volume removal from downhole at certain time, taking into account Flowrate, RPM, ROP and Drilling fluid or Mud properties, and then will be plotted and compared to the volume being drilled expected. ECD monitoring will dictate hole stability conditions and T&D and Cuttings Volume coming from downhole monitoring will dictate how clean the well is. T&D Modeling Software provide theoretical calculated T&D trends which will be plotted and compared to the real-time measurements. It will use the measured hookloads to perform a back-calculation of friction factors along the wellbore.

Wearable monitoring system for assistance dogs

Despite the recent progresses in robotics, autonomous robots still have too many limitations to reliably help people with disabilities. On the other hand, animals, and especially dogs, have already demonstrated great skills in assisting people in many daily situations. However, dogs also have their own set of limitations. For example, they need to rest periodically, to be healthy (physically and psychologically), and it is difficult to control them remotely. This project aims to “augment” the Assistance dog, by developing a system that compensates some of the dog weaknesses through a robotic device mounted on the dog harness. This specific study, involved in the COCHISE project, focuses on the development of a system for the monitoring of dogs activity and physiological parameters.

Health-related quality of life in patients with Chagas disease

INTRODUCTION: Chagas disease (ChD) is a chronic illness related to significant morbidity and mortality that can affect the quality of life (QoL) of infected patients. However, there are few studies regarding QoL in ChD. The objectives of this study are to construct a health-related QoL (HRQoL) profile of ChD patients and compare this with a non-ChD (NChD) group to identify factors associated with the worst HRQoL scores in ChD patients. METHODS: HRQoL was investigated in 125 patients with ChD and 21 NChD individuals using the Medical Outcomes Study 36-item Short-Form (SF-36) and the Minnesota Living with Heart Failure Questionnaire (MLWHFQ). Patients were submitted to a standard protocol that included clinical examination, ECG, Holter monitoring, Doppler echocardiogram and autonomic function tests. RESULTS: HRQoL scores were significantly worse among the ChD group compared to the NChD group in the SF-36 domains of physical functioning and role-emotional and in the MLWHFQ scale. For the ChD group, univariate analysis showed that HRQoL score quartiles were associated with level of education, sex, marital status, use of medication, functional classification and cardiovascular and gastrointestinal symptoms. In the multivariate analysis, female sex, fewer years of education, single status, worst functional classification, presence of cardiovascular and gastrointestinal symptoms, associated illnesses, Doppler echocardiographic abnormalities and ventricular arrhythmia detected during Holter monitoring were predictors of lower HRQoL scores. CONCLUSIONS: ChD patients showed worse HRQoL scores compared to NChD. For the ChD group, sociodemographic and clinical variables were associated with worst scores.

Social-media monitoring for cold-start recommendations

Generating personalized movie recommendations to users is a problem that most commonly relies on user-movie ratings. These ratings are generally used either to understand the user preferences or to recommend movies that users with similar rating patterns have rated highly. However, movie recommenders are often subject to the Cold-Start problem: new movies have not been rated by anyone, so, they will not be recommended to anyone; likewise, the preferences of new users who have not rated any movie cannot be learned. In parallel, Social-Media platforms, such as Twitter, collect great amounts of user feedback on movies, as these are very popular nowadays. This thesis proposes to explore feedback shared on Twitter to predict the popularity of new movies and show how it can be used to tackle the Cold-Start problem. It also proposes, at a finer grain, to explore the reputation of directors and actors on IMDb to tackle the Cold-Start problem. To assess these aspects, a Reputation-enhanced Recommendation Algorithm is implemented and evaluated on a crawled IMDb dataset with previous user ratings of old movies,together with Twitter data crawled from January 2014 to March 2014, to recommend 60 movies affected by the Cold-Start problem. Twitter revealed to be a strong reputation predictor, and the Reputation-enhanced Recommendation Algorithm improved over several baseline methods. Additionally, the algorithm also proved to be useful when recommending movies in an extreme Cold-Start scenario, where both new movies and users are affected by the Cold-Start problem.