Intelligent transportation systems for electric vehicles

Electric Vehicles market penetration is increasing, transforming transportation, creating 8 synergies among energy and transportation. From initial blockers, like purchase price, range, charging time, lifetime, and safety are all battery-driven handicaps. In this context smart energy management system plays an important role, where intelligent process plays an important role. This review akes into account the special issue dedicated to this topic at the end of 2018, try to identify major work performed in the last 3 years and identify major topics for the upcoming years.info:eu-repo/semantics/publishedVersio

Sharing health information using a blockchain

Data sharing in the health sector represents a big problem due to privacy and security issues. Health data have tremendous value for organisations and criminals. The European Commission has classified health data as a unique resource owing to their ability to enable both retrospective and prospective research at a low cost. Similarly, the Organisation for Economic Co-operation and Development (OECD) encourages member nations to create and implement health data governance systems that protect individual privacy while allowing data sharing. This paper proposes adopting a blockchain framework to enable the transparent sharing of medical information among health entities in a secure environment. We develop a laboratory-based prototype using a design science research methodology (DSRM). This approach has its roots in the sciences of engineering and artificial intelligence, and its primary goal is to create relevant artefacts that add value to the fields in which they are used. We adopt a patient-centric approach, according to which a patient is the owner of their data and may allow hospitals and health professionals access to their data.info:eu-repo/semantics/publishedVersio

Remote Monitor System for Alzheimer disease

Health Remote Monitoring Systems (HRMS) offer the ability to address health-care human resource concerns. In developing nations, where pervasive mobile networks and device access are linking people like never before, HRMS are of special relevance. A fundamental aim of this research work is the realization of technological-based solution to triage and follow-up people living with dementias so as to reduce pressure on busy staff while doing this from home so as to avoid all unnecessary visits to hospital facilities, increasingly perceived as dangerous due to COVID-19 but also raising nosocomial infections, raising alerts for abnormal values. Sensing approaches are complemented by advanced predictive models based on Machine Learning (ML) and Artificial Intelligence (AI), thus being able to explore novel ways of demonstrating patient-centered predictive measures. Low-cost IoT devices composing a network of sensors and actuators aggregated to create a digital experience that will be used and exposure to people to simultaneously conduct several tests and obtain health data that can allow screening of early onset dementia and to aid in the follow-up of selected cases. The best ML for predicting AD was logistic regression with an accuracy of 86.9%. This application as demonstrated to be essential for caregivers once they can monitor multiple patients in real-time and actuate when abnormal values occur.info:eu-repo/semantics/acceptedVersio

Disaster management in smart cities

The smart city concept, in which data from different systems are available, contains a multitude of critical infrastructures. This data availability opens new research opportunities in the study of the interdependency between those critical infrastructures and cascading effects solutions and focuses on the smart city as a network of critical infrastructures. This paper proposes an integrated resilience system linking interconnected critical infrastructures in a smart city to improve disaster resilience. A data-driven approach is considered, using artificial intelligence and methods to minimize cascading effects and the destruction of failing critical infrastructures and their components (at a city level). The proposed approach allows rapid recovery of infrastructures’ service performance levels after disasters while keeping the coverage of the assessment of risks, prevention, detection, response, and mitigation of consequences. The proposed approach has the originality and the practical implication of providing a decision support system that handles the infrastructures that will support the city disaster management system—make the city prepare, adapt, absorb, respond, and recover from disasters by taking advantage of the interconnections between its various critical infrastructures to increase the overall resilience capacity. The city of Lisbon (Portugal) is used as a case to show the practical application of the approach.info:eu-repo/semantics/publishedVersio

Calcium identification and scoring based on echocardiography. An exploratory study on aortic valve stenosis

Currently, an echocardiography expert is needed to identify calcium in the aortic valve, and a cardiac CT-Scan image is needed for calcium quantification. When performing a CT-scan, the patient is subject to radiation, and therefore the number of CT-scans that can be performed should be limited, restricting the patient’s monitoring. Computer Vision (CV) has opened new opportunities for improved efficiency when extracting knowledge from an image. Applying CV techniques on echocardiography imaging may reduce the medical workload for identifying the calcium and quantifying it, helping doctors to maintain a better tracking of their patients. In our approach, a simple technique to identify and extract the calcium pixel count from echocardiography imaging, was developed by using CV. Based on anonymized real patient echocardiographic images, this approach enables semi-automatic calcium identification. As the brightness of echocardiography images (with the highest intensity corresponding to calcium) vary depending on the acquisition settings, echocardiographic adaptive image binarization has been performed. Given that blood maintains the same intensity on echocardiographic images—being always the darker region—blood areas in the image were used to create an adaptive threshold for binarization. After binarization, the region of interest (ROI) with calcium, was interactively selected by an echocardiography expert and extracted, allowing us to compute a calcium pixel count, corresponding to the spatial amount of calcium. The results obtained from these experiments are encouraging. With this technique, from echocardiographic images collected for the same patient with different acquisition settings and different brightness, obtaining a calcium pixel count, where pixel values show an absolute pixel value margin of error of 3 (on a scale from 0 to 255), achieving a Pearson Correlation of 0.92 indicating a strong correlation with the human expert assessment of calcium area for the same images.info:eu-repo/semantics/publishedVersio

Data fusion and visualization towards city disaster management: Lisbon case study

INTRODUCTION: Due to the high level of unpredictability and the complexity of the information requirements, disaster management operations are information demanding. Emergency response planners should organize response operations efficiently and assign rescue teams to particular catastrophe areas with a high possibility of surviving. Making decisions becomes more difficult when the information provided is heterogeneous, out of date, and often fragmented. OBJECTIVES: In this research work a data fusion of different information sources and a data visualization process was applied to provide a big picture about the disruptive events in a city. This high-level knowledge is important for emergency management authorities. This holistic process for managing, processing, and analysing the seven Vs (Volume, Velocity, Variety, Variability, Veracity, Visualization, and Value) in order to generate actionable insights for disaster management. METHODS: A CRISP-DM methodology over smart city-data was applied. The fusion approach was introduced to merge different data sources. RESULTS: A set of visual tools in dashboards were produced to support the city municipality management process. Visualization of big picture based on different data available is the proposed work. CONCLUSION: Through this research, it was verified that there are temporal and spatial patterns of occurrences that affected the city of Lisbon, with some types of occurrences having a higher incidence in certain periods of the year, such as floods and collapses that occur when there are high levels of precipitation. On the other hand, it was verified that the downtown area of the city is the most affected area.info:eu-repo/semantics/publishedVersio

Keratoacanthoma-like nodules as first manifestation of metastatic epithelioid trophoblastic tumor

Cutaneous metastases are rarely the initial manifestation of a previously undiagnosed malignancy and keratoacanthoma-like lesions are a notoriously unusual presentation pattern of cutaneous dissemination of a primary tumor. Herein, we report a 40-year-old woman presenting to our dermatology department with multiple keratoacanthoma-like scalp nodules. Subsequent investigation determined it to be the first manifestation of a disseminated endometrial epithelioid trophoblastic tumor, eventually causing the patient's death. Epithelioid trophoblastic tumor, a rare form of gestational trophoblastic disease, is a recently described neoplasm whose cutaneous metastasis has not been previously reported in the literature

Identification of 'super-responders' to cardiac resynchronization therapy: the importance of symptom duration and left ventricular geometry

AIMS: Some patients show such an important clinical improvement and reverse remodelling after cardiac resynchronization therapy (CRT) that anatomy and function approach normal. These patients have been called 'super-responders'. The aim of our study was to identify predictors of becoming a super-responder after CRT. METHODS AND RESULTS: Eighty-seven consecutive patients who underwent CRT were prospectively studied. Before CRT and 6 months after, clinical and echocardiographic evaluation was performed. Patients with a decrease in New York Heart Association functional class >or=1, a two-fold or more increase of left ventricular ejection fraction (LVEF) or a final LVEF >45%, and a decrease in LV end-systolic volume >15% were classified as super-responders. There were 12% super-responders. At baseline, there were no significant differences between super-responders and the other patients, except for the fact that super-responders had significantly smaller mitral regurgitation and LV end-diastolic diameter (LVEDD) and a shorter duration of heart failure symptoms. Mitral regurgitation jet area, LVEDD, and duration of heart failure symptoms were correlated with this super-response. Moreover, an evolution of symptoms for <12 months was an independent predictor of super-response to CRT. CONCLUSION: Patients in earlier phases of the cardiomyopathy, with a less altered ventricular geometry, seem to have a greater probability of becoming super-responders

Cardiac resynchronization therapy is effective even in elderly patients with comorbidities

PURPOSE: The purpose of this study was to compare the effects of cardiac resynchronization therapy (CRT) in elderly patients (> or =65 years) with younger patients and to assess the impact of comorbidities in CRT remodeling response. METHODS: This is a prospective study of 87 consecutive patients scheduled for CRT who underwent clinical and echocardiographic evaluation before and 6 months after CRT. A reduction in left ventricular end-systolic volume (LVESV) > or =15% after CRT defined remodeling responders, and a reduction of at least one New York Heart Association class defined clinical responders. Multivariate analysis was used to identify independent predictors of non-response to CRT in terms of reverse remodeling. RESULTS: The mean age was 62 +/- 11 years, with 36 elderly patients (41%). The baseline QRS duration was 145 +/- 32 ms. After CRT, there were significant and similar improvements of left ventricular (LV) ejection fraction, LVESV, LV dP/dt, and mitral regurgitation jet area (JA) between elderly (> or =65 years) and younger (74 mm, and JA >10 cm(2) before CRT, but not comorbidities. CONCLUSION: This work suggests that being elderly is not an impediment to CRT success even in the presence of comorbidities

Data-driven approach for incident management in a smart city

Buildings in Lisbon are often the victim of several types of events (such as accidents, fires, collapses, etc.). This study aims to apply a data-driven approach towards knowledge extraction from past incident data, nowadays available in the context of a Smart City. We apply a Cross Industry Standard Process for Data Mining (CRISP-DM) approach to perform incident management of the city of Lisbon. From this data-driven process, a descriptive and predictive analysis of an events dataset provided by the Lisbon Municipality was possible, together with other data obtained from the public domain, such as the temperature and humidity on the day of the events. The dataset provided contains events from 2011 to 2018 for the municipality of Lisbon. This data mining approach over past data identified patterns that provide useful knowledge for city incident managers. Additionally, the forecasts can be used for better city planning, and data correlations of variables can provide information about the most important variables towards those incidents. This approach is fundamental in the context of smart cities, where sensors and data can be used to improve citizens’ quality of life. Smart Cities allow the collecting of data from different systems, and for the case of disruptive events, these data allow us to understand them and their cascading effects better.info:eu-repo/semantics/publishedVersio