Helsinki, Finland

Helsinki Metropolia University of Applied science is one of the largest and the most international University of Applied science in Finland. The university has four fields of study: technology, health care and social services, economics and business administration, and culture, all of which are also taught in English.The students number some 16,000 and the staff about 1,200. Wikipedia.

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Agency: Cordis | Branch: H2020 | Program: IA | Phase: SCC-1-2016-2017 | Award Amount: 21.72M | Year: 2016

mySMARTLife project aims at the development of an Urban Transformation Strategy to support cities in the definition of transition models, as a suitable path to reach high level of excellence in its development process, addressing the main city challenges and progressing to the smart people and smart economy concepts. The main instrument to achieve this very ambitious strategy will be the definition of the Advanced Urban Planning, consisting of an integrated approach of the planned city interventions on the basis of a rigorous impact assessment, an active citizen engagement in the decision-making process and a structured business approach, from the city business model perspective, to the economic framework for big companies and local SMEs and Start-Ups. Nantes (France), Hamburg (Germany) and Helsinki (Finland) are the lighthouse cities and Varna (Bulgaria), Bydgoszcz (Poland), Rijeka (Croatia) and Palencia (Spain) the followers. All of them will be involved in the overall project development assuming different and complementary roles. Energy and Climate mitigation plans in the lighthouse cities are completely compliant with the objectives of Covenant of Mayors initiative, as it is reflected; first regarding the early participation of the cities in Covenant of Mayors and second, considering the ambition of their SEAPs, that were submitted, evaluated, approved and are monitored by Covenant of Mayors. Aligned with these objectives, the commitment of the lighthouses is the deployment of a big set of large scale interventions and at least two years of data collection to make a depth analysis of the results, calculating standard KPIs, evaluating the associated impacts and disseminating the results. Followers will be very close to this demonstration, collaborating in the definition and deployment, analysing the problem from the point of view of their own city challenges and extracting knowledge, best practices and lessons learnt for a further replication.

Measuring and modeling pH in concentrated aqueous solutions in an accurate and consistent manner is of paramount importance to many R&D and industrial applications, including RO desalination. Nevertheless, unified definitions and standard procedures have yet to be developed for solutions with ionic strength higher than ~0.7M, while implementation of conventional pH determination approaches may lead to significant errors. In this work a systematic yet simple methodology for measuring pH in concentrated solutions (dominated by Na+/Cl-) was developed and evaluated, with the aim of achieving consistency with the Pitzer ion-interaction approach. Results indicate that the addition of 0.75M of NaCl to NIST buffers, followed by assigning a new standard pH (calculated based on the Pitzer approach), enabled reducing measured errors to below 0.03 pH units in seawater RO brines (ionic strength up to 2M). To facilitate its use, the method was developed to be both conceptually and practically analogous to the conventional pH measurement procedure. The method was used to measure the pH of seawater RO retentates obtained at varying recovery ratios. The results matched better the pH values predicted by an accurate RO transport model. Calibrating the model by the measured pH values enabled better boron transport prediction. A Donnan-induced phenomenon, affecting pH in both retentate and permeate streams, was identified and quantified. © 2014 Elsevier Ltd.

Agency: Cordis | Branch: FP7 | Program: CP-IP | Phase: SST.2012.3.1-4. | Award Amount: 15.65M | Year: 2012

European cities face four main mobility problems: congestion, land use , safety and environment. One of the main causes of such problems is the car-ownership rate. The centres of large cities address this issue combining efficient mass transits with car restriction policies but peripheral areas and smaller cities remain dominated by private cars. CityMobil has demonstrated how automating road vehicles can lead to different transport concepts, from partly automated car-share schemes through CyberCars and PRT, to BRT which can make urban mobility more sustainable. However CityMobil has also highlighted three main barriers to the deployment of automated road vehicles: the implementation framework, the legal framework and the unknown wider economic effect. The CityMobil2 goal is to address these barriers and finally to remove them. To smooth the implementation process CityMobil2 will remove the uncertainties which presently hamper procurement and implementation of automated systems. On one hand CityMobil2 features 12 cities which will revise their mobility plans and adopt wherever they will prove effective automated transport systems. Then CityMobil2 will select the best 5 cases (among the 12 cities) to organise demonstrators. The project will procure two sets of automated vehicles and deliver them to the five most motivated cities for a 6 to 8 months demonstration in each city. To change the legal framework CityMobil2 will establish a workgroup with scientists, system builders, cities, and the national certification authorities. The workgroup will to deliver a proposal for a European Directive to set a common legal framework to certify automated transport systems. Finally an industrial study will assess the industrial potential of automated systems on European economy and any eventual negative effect and make a balance of them.

Makela P.,Finnish National Institute for Health and Welfare | Havio M.,Helsinki Metropolia University of Applied Sciences | Seppa K.,University of Tampere
Addiction | Year: 2011

Aims The present study aimed to evaluate the frequency and the target group of alcohol screening and brief interventions in health-care settings and how well this level of activity reflects public opinion. Design A general population survey. Setting and participants A random sample of Finns aged 15-69 years with a 74% response rate (n=2725). Measurements Frequency counts were used to evaluate the level of activity. Logistic regression models were used to examine which groups were asked and advised about alcohol use and which groups considered it useful. Findings More than 90% had positive attitudes towards being asked about their alcohol use. Of those who had been in contact with health care (n=2062) in the 12 months before the survey, 33.3% had been asked about their alcohol use, being most often men, young, heavy drinkers and those of high socio-economic status. Thirty-seven per cent of those who had been asked were given advice, being most often heavy drinkers and those with a normal body mass index. However, 50% of heavy drinkers who had been asked about their alcohol use had not been advised about it. Of those who had been advised, 71.9% considered it useful, especially older subjects, and also including heavy episodic drinkers, although less than others. Conclusions In Finland, the frequency of health-care professionals asking and giving advice on alcohol is relatively low. However, public opinion towards these discussions is positive. Our results encourage the support and uptake of systematic screenings and brief interventions in health-care settings. © 2011 The Authors, Addiction © 2011 Society for the Study of Addiction.

Kullaa J.,Aalto University | Kullaa J.,Helsinki Metropolia University of Applied Sciences
Mechanical Systems and Signal Processing | Year: 2010

Sensor fault can be detected and corrected in a multichannel measurement system with enough redundancy using solely the measurement data. A single or multiple sensors can be estimated from the remaining sensors if training data from the functioning sensor network are available. The method is based on the minimum mean square error (MMSE) estimation, which is applied to the time history data, e.g. accelerations. The faulty sensor can be identified and replaced with the estimated sensor. Both spatial and temporal correlation of the sensors can be utilized. Using the temporal correlation is justified if the number of active structural modes is larger than the number of sensors. The disadvantages of the temporal model are discussed. Experimental multichannel vibration measurements are used to verify the proposed method. Different, and also simultaneous, sensor faults are studied. The effects of environmental variability and structural damage are discussed. © 2009 Elsevier Ltd. All rights reserved.

Metsala E.,Helsinki Metropolia University of Applied Sciences | Vaherkoski U.,Helsinki Metropolia University of Applied Sciences
Scandinavian Journal of Caring Sciences | Year: 2014

Aims: Medication safety is a part of quality of care and patient safety. Old age brings many challenges for safe use of medication. In order to improve the prerequisites of medication safety in acute care of the elderly, we systematically reviewed studies to find out what kind of medication errors happen in elderly acute care. Methods: Cinahl, Medline, Cochrane, JBI Connect+ databases and Finnish healthcare databases Medic and Ohtanen were used in the search. The search was performed using both MeSH terms and keywords by the option 'search all text'. The original keywords were pharmacy or drugs, medical error or deviation and their Finnish synonyms. These keywords were united to the terms elderly, nursing or acute care or intensive care. Studies published between 2001 and 2011 were chosen. Results: Medication errors mentioned in the studies were associated with (i) nursing competence, (ii) prescription- and patient-related factors, (iii) medication work organisation and nursing process and (iv) safety culture. This paper presents several practical implications for improving medication safety in the acute care of the elderly. Limitations: The grey literature was not included because the authors wanted to limit to the best-quality research. In some studies, elderly acute care was not their exact context or the elderly formed only a part of study population. This may have undermined some types of medication errors typical to elderly acute care. Conclusions: To improve the prerequisites of medication, safety in acute care of the elderly management of the medication process should be improved. Also, cooperation within the medical team in making the medical care plans and checking out the medication of the elderly people should be improved. This is an important topic of lifelong education for nurses and other healthcare staff as well. © 2013 Nordic College of Caring Science. Published by Blackwell Publishing Ltd.

Kullaa J.,Aalto University | Kullaa J.,Helsinki Metropolia University of Applied Sciences
Mechanical Systems and Signal Processing | Year: 2013

In structural health monitoring (SHM) and control, the structure can be instrumented with an array of sensors forming a redundant sensor network, which can be utilized in sensor fault diagnosis. In this study, the objective is to detect, identify, and quantify a sensor fault using the structural response data measured with the sensor network. Seven different sensor fault types are investigated and modelled: bias, gain, drifting, precision degradation, complete failure, noise, and constant with noise. The sensor network is modelled as a Gaussian process and each sensor in the network is estimated in turn using the minimum mean square error (MMSE) estimation The sensor fault is identified and quantified using the multiple hypothesis test utilizing the generalized likelihood ratio (GLR). The proposed approach is experimentally verified with an array of accelerometers assembled on a wooden bridge. Different sensor faults are simulated by modifying a single sensor. The method is able to detect a sensor fault, identify and correct the faulty sensor, as well as identify and quantify the fault type. © 2013 Elsevier Ltd.

Kullaa J.,Helsinki Metropolia University of Applied Sciences
Mechanical Systems and Signal Processing | Year: 2016

Virtual sensing techniques use information available from a limited set of physical sensors together with the finite element model to calculate an estimate of the quantity of interest. In structural dynamics applications, analytical mode shapes from the finite element model are typically used as a basis to estimate the response at unmeasured locations by an expansion algorithm. An alternative is to model only the interesting part of the structure using substructuring techniques, in which the natural modes are replaced by component modes consisting of a selected number of fixed interface modes plus the interface constraint modes. They are mutually independent and compose a valid subspace for estimating the unmeasured response. If the number of interface degrees of freedom is large, interface reduction is applied. The main advantage of the proposed approach is that the modelling effort can be substantially decreased, because only part of the structure is modelled and the modelling uncertainties, non-linearities, or changes in the omitted structure can be ignored. The method is validated by numerical simulations of three different structures under unknown excitation. Different types and locations of virtual sensors are studied. Also, the effects of noise and model errors are investigated. The most accurate estimation is obtained if the virtual sensor is located away from the interface and close to a physical sensor. © 2016 Elsevier Ltd.

Taavitsainen V.-M.,Helsinki Metropolia University of Applied Sciences
Journal of Chemometrics | Year: 2010

This study introduces both ridge and partial least squares (PLS) regression based rational function regression techniques. The results of four different cases are compared to those obtained using other regression techniques. The results are mostly favorable, and the proposed method should be considered as a noteworthy alternative in nonlinear modeling. © 2010 John Wiley & Sons, Ltd.

Taavitsainen V.-M.,Helsinki Metropolia University of Applied Sciences
Chemometrics and Intelligent Laboratory Systems | Year: 2013

Rational functions appear in many theoretical formulae in chemistry, chemical engineering, and biochemistry. However, rational functions have not been used much in empirical multivariate modeling. This study is a continuation to developments in [1] and [3]. In this study, the focus is on empirical modeling using rational function in a case study of estimating the kinetics of esterification of ethanol with acetic acid. The results are compared with those obtained by traditional mechanistic modeling using nonlinear parameter estimation. The motivation for the approach is to find good models with less effort. Currently, developing and testing different mechanistic kinetic models are time consuming, and in spite of the effort, the performance of the resulting candidate models can be virtually the same. An alternative approach is to use empirical generic models. In this study, this approach is shown to require less effort than the mechanistic modeling approach. The proposed method is based on modeling the reaction rate by an empirical second order rational function. The rational function is first transformed into a linear form which is used to estimate the unknown model parameters using ridge regression. After this, the linear model is back-transformed into the original rational form which is then used for calculating both the fitted values and the predicted values. Finally, the estimated rational function for the rate expression is used to solve numerically the system of differential equations corresponding to the reaction kinetics. The data is obtained from [4], and it consists of several batch reactions between ethanol and acetic acid with different initial concentrations. Six of the eight batches are used for model estimation, and two of these are omitted for model validation (prediction). The results are very promising, and both the fitted and the predicted values are comparable to those obtained using traditional mechanistic modeling with nonlinear parameter estimation. It also seems that the method is able to take into account the non-ideal behavior of the reactants. The proposed method offers a flexible and fast method for developing kinetic models for reactor design and control, even in cases where the kinetic rate expression is not known by theory. © 2012 Elsevier B.V.

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