Recently articles in Newspapers, University News Bulletins and Scientific Literature report about negative aspects of the wellbeing of students caused by COVID-19 epidemic. Half of the students have mental problems and don't participate in the teaching learning process anymore. In the Netherlands, Universities are surveyed by questionnaires, researching the mental health problems of students. In this paper we focus on students of Delft University of Technology. It proved from surveys, that many students complain about loneliness, fear, sleep deprivation and lack of study motivation. In this paper we report about experiments at the Faculty of Electrical Engineering, Mathematics and Computer Science, how students can be activated, motivated and socialized via study activities presented at the website of one of the Study Societies and via study-buddy groups. Students were personally invited to take part in discussions via a Forum, to enroll in group activities and to visit special lectures. A special COVID-19 didactics has been developed to stimulate students to make assignments in Calculus and Programing via Massive Open Online Courses developed in the framework EdX, an online learning destination and MOOC provider.

The areas of many cities in the Netherlands are covered by a network of stationary sensors, measuring special components of air pollution such as CO2, NO2, PM2.5 and PM10. The pollution with fine dust along roads, surrounding and crossing the city is primarily related to traffic density. To measure traffic density, we used a license plate recognizer based on a special Neural Network Neocognitron, analyzing the video footage of surveillance cameras along the roads. We also studied the onset and offset of traffic density to predict traffic density, using the first recorded sparse traffic data. In cooperation with MIT Senseable City Lab the Technical University of Delft has developed special mobile, low cost sensors to measure air pollution. These mobile sensors are integrated with stationary sensors to a heterogeneous sensor network and enable measurement of air pollution out of the reach of the stationary sensor network..

The INTERSPEECH 2021 Computational Paralinguistics Challenge addresses four different problems for the first time in a research competition under well-defined conditions: In the COVID-19 Cough and COVID-19 Speech Sub-Challenges, a binary classification on COVID-19 infection has to be made based on coughing sounds and speech; in the Escalation Sub- Challenge, a three-way assessment of the level of escalation in a dialogue is featured; and in the Primates Sub-Challenge, four species vs background need to be classified. We describe the Sub-Challenges, baseline feature extraction, and classifiers based on the 'usual' COMPARE and BoAW features as well as deep unsupervised representation learning using the AUDEEP toolkit, and deep feature extraction from pre-trained CNNs using the DEEP SPECTRUM toolkit; in addition, we add deep end-to-end sequential modelling, and partially linguistic analysis.

The Corona crisis limits the mobility of people and it proves that many people have an increased body mass index. A lot of people want to increase their fitness and to boost their immune system. There is a run-on fitness schools and fitness equipment for the home environment. At fitness schools, fitness coaches are available for personalized instructions and supervision. Fitness in the home environment lacks personalized instruction and supervision and can cause serious injuries. In this paper a digital coach will be introduced providing digital support and supervision. The digital coach offers personalized fitness program, supervises athletes during fitness exercises and provides a supporting system concerning injuries. A prototype of the developed system can be downloaded as an app on a smart phone.

Social media play an important role in crisis events. People in crisis events can report their observations of the crisis environment, and their mental and physical state. They can ask for help or assistance via Twitter. Some studies report, that some or a lot of compassion, concern and empathy is involved. Verification of this thesis was the main concern of our research. We analyzed huge datasets of Tweets available via Internet of recorded messages posted during natural disaster events. We detected many emotional tweets characterized by keywords. Emotional keywords were extracted and composed in an emotional dictionary, to be used for future flooding disasters.

Current route planners on smart phones or special routing devices try to minimize the traveling time. But many users are no longer interested in the shortest route in time but they prefer a healthier route. In many smart cities there is a centralized distributed network of sensors measuring the pollution in a city on different locations for different time of the day. In this paper we present a routing App computing the less polluted route along the streets using the measurement of the eco sensors. The council of a smart city takes care of the health of their citizens. The developed routing App enables travelers with lung diseases to choose a healthy route. The routing algorithm is based on a special variant of the well-known Ant Based Control routing algorithm. To combine data measuring pollution and shortest traveling time, we solved a special multi-parameter problem. In some experiments we performed a user test of the routing App on different time and location.

In designing a course a teacher defines the educational goals, selects the teaching material and the way of assessment and finally defines a didactic model. In this didactic model the teacher defines his way of teaching taking into account the different ways of learning. Students starting an academic study interact with the educational or teaching learning environment. Students define their own study goals, they are supposed to have the right capabilities to finish the study successfully and are able to set themselves into action. But an important driving force is the affective component. Successful students like their study, enjoy their life at the university and interactions with fellow students but are afraid to fail for exams, dislike the aloneness, angry at failing systems. In this paper, we present well-known and new didactic models with special attention for affective components. We present a system to assess the emotional state of students. The system has been tested using a management game, where a crisis team composed of students reduce the negative impact of flooding in the city of Prague. The results of the experiment are described in this paper.