A decision support system for selective cleaning

[Abstract]

2

The quality of environmental data analysis and propagation of errors are heavily affected by the representativity of the initial sampling design [CRE 93, DEU 97, KAN 04a, LEN 06, MUL07]. Geostatistical methods such as kriging are related to field samples, whose spatial distribution is crucial for the correct detection of the phenomena. Literature about the design of environmental monitoring networks (MN) is widespread and several interesting books have recently been published [GRU 06, LEN 06, MUL 07] in order to clarify the basic principles of spatial sampling design (monitoring networks optimization) based on Support Vector Machines was proposed. Nonetheless, modelers often receive real data coming from environmental monitoring networks that suffer from problems of non-homogenity (clustering). Clustering can be related to the preferential sampling or to the impossibility of reaching certain regions.

On the Condition Monitoring of Induction machines

The research of condition monitoring of electric motors has been wide for several decades. The research and development at universities and in industry has provided means for the predictive condition monitoring. Many different devices and systems are developed and are widely used in industry, transportation and in civil engineering. In addition, many methods are developed and reported in scientific arenas in order to improve existing methods for the automatic analysis of faults. The methods, however, are not widely used as a part of condition monitoring systems. The main reasons are, firstly, that many methods are presented in scientific papers but their performance in different conditions is not evaluated, secondly, the methods include parameters that are so case specific that the implementation of a systemusing such methods would be far from straightforward. In this thesis, some of these methods are evaluated theoretically and tested with simulations and with a drive in a laboratory. A new automatic analysis method for the bearing fault detection is introduced. In the first part of this work the generation of the bearing fault originating signal is explained and its influence into the stator current is concerned with qualitative and quantitative estimation. The verification of the feasibility of the stator current measurement as a bearing fault indicatoris experimentally tested with the running 15 kW induction motor. The second part of this work concentrates on the bearing fault analysis using the vibration measurement signal. The performance of the micromachined silicon accelerometer chip in conjunction with the envelope spectrum analysis of the cyclic bearing faultis experimentally tested. Furthermore, different methods for the creation of feature extractors for the bearing fault classification are researched and an automatic fault classifier using multivariate statistical discrimination and fuzzy logic is introduced. It is often important that the on-line condition monitoring system is integrated with the industrial communications infrastructure. Two types of a sensor solutions are tested in the thesis: the first one is a sensor withcalculation capacity for example for the production of the envelope spectra; the other one can collect the measurement data in memory and another device can read the data via field bus. The data communications requirements highly depend onthe type of the sensor solution selected. If the data is already analysed in the sensor the data communications are needed only for the results but in the other case, all measurement data need to be transferred. The complexity of the classification method can be great if the data is analysed at the management level computer, but if the analysis is made in sensor itself, the analyses must be simple due to the restricted calculation and memory capacity.

Performance of noninvasive ventilation algorithms on ICU ventilators during pressure support: a clinical study.

To evaluate the impact of noninvasive ventilation (NIV) algorithms available on intensive care unit ventilators on the incidence of patient-ventilator asynchrony in patients receiving NIV for acute respiratory failure. Prospective multicenter randomized cross-over study. Intensive care units in three university hospitals. Patients consecutively admitted to the ICU and treated by NIV with an ICU ventilator were included. Airway pressure, flow and surface diaphragmatic electromyography were recorded continuously during two 30-min periods, with the NIV (NIV+) or without the NIV algorithm (NIV0). Asynchrony events, the asynchrony index (AI) and a specific asynchrony index influenced by leaks (AIleaks) were determined from tracing analysis. Sixty-five patients were included. With and without the NIV algorithm, respectively, auto-triggering was present in 14 (22%) and 10 (15%) patients, ineffective breaths in 15 (23%) and 5 (8%) (p = 0.004), late cycling in 11 (17%) and 5 (8%) (p = 0.003), premature cycling in 22 (34%) and 21 (32%), and double triggering in 3 (5%) and 6 (9%). The mean number of asynchronies influenced by leaks was significantly reduced by the NIV algorithm (p < 0.05). A significant correlation was found between the magnitude of leaks and AIleaks when the NIV algorithm was not activated (p = 0.03). The global AI remained unchanged, mainly because on some ventilators with the NIV algorithm premature cycling occurs. In acute respiratory failure, NIV algorithms provided by ICU ventilators can reduce the incidence of asynchronies because of leaks, thus confirming bench test results, but some of these algorithms can generate premature cycling.

Soins intégrés: comment accompagner un changement de culture [Integrated care: how to support a culture change?].

The primary care center at Lausanne University Hospital trains residents to new models of integrated care. The future GPs discover new forms of collaboration with nurses, pharmacists or social workers. The collaboration model includes seeing patients together or delegating care to other providers, with the aim of improving the efficiency of a patient-centered care approach. The article includes examples of integrated care in consultation for travelers, victims of violence, pharmacist medication adherence counseling, medicosocial team work for alcohol use disorders and nurse practitioners' primary care for asylum seekers.

Offering planning with support of roadmapping in project business

Tämän tutkielman tavoitteena on tutkia kuinka roadmapping-tekniikkaa voidaan käyttää tarjonnan suunnittelun tukena uusien tuotteiden valmistamisen yhteydessä. Työ koostuu teoreettisesta ja käytännönläheisestä osasta. Teoreettinen runko on luotu selventämään kuinka tämän hetkisen tutkimus- ja kehitys projektit lopulta muodostavat tulevaisuuden tarjoaman. Menestyksekkään tuotetarjoaman luominen vaatii, sekä uusien teknologioiden kehittämistä, että markkinoilla olevien asiakkaiden tarpeiden ymmärtämistä. Asiakassuuntaisten tuotteiden kehittäminen vaatii toimintaympäristöstä ja asiakasrajapinnasta tulevien signaalien tunnistamista ja niiden ohjaamista tuote- ja teknologia platformeille. Strategia luodaan tukemaan päätöksentekoa prosessin eri vaiheissa. Yrityskohtainen osio koostuu analyysistä, joka on tehty teetetyn kyselyn ja haas-tattelujen pohjalta. Osana analyysia ovat Major project-yksikön tämänhetkinen tarjonnansuunnitteluprosessi, strategian soveltaminen, informaation kerääminen ja priorisointi, portfolionhallinta ja roadmap-tekniikan käyttö. Ratkaisussa on esitet-ty tarjonnan suunnitteluprosessi ja siihen liittyvät kriittiset komponentit. Roadmapping-tekniikkaaon luotu yhdistämään toimintaympäristö, tuotteet ja teknologia toisiinsa. Toimintaympäristö ja tuotteet on yhdistetty myös linked-grids-tekniikan avulla.

Project SKY-EYE: applying UAVs to forest fire fighter support and monitoring

Peer reviewed

Assessing technology-based spin-offs from university support units

This paper takes a regional studies approach to assess spin-offs from a university-based technology transfer network. We first detect the regional objectives, inputs and outputs needed to assess spin-offs from support programmes. We then provide evidence on regional mechanisms for firm creation. We analyse spin-offs created at Catalan universities and find that many efficient spin-offs have formal technology transfer agreements, and emerge from technology-oriented universities. We also find that higher innovation levels and experience from the parent university are associated with higher efficiency, which is positively related to future fundamental profitability. Finally, we propose regional policy making and research directions.

Personalized drug administrations using Support Vector Machine

The decision-making process regarding drug dose, regularly used in everyday medical practice, is critical to patients' health and recovery. It is a challenging process, especially for a drug with narrow therapeutic ranges, in which a medical doctor decides the quantity (dose amount) and frequency (dose interval) on the basis of a set of available patient features and doctor's clinical experience (a priori adaptation). Computer support in drug dose administration makes the prescription procedure faster, more accurate, objective, and less expensive, with a tendency to reduce the number of invasive procedures. This paper presents an advanced integrated Drug Administration Decision Support System (DADSS) to help clinicians/patients with the dose computing. Based on a support vector machine (SVM) algorithm, enhanced with the random sample consensus technique, this system is able to predict the drug concentration values and computes the ideal dose amount and dose interval for a new patient. With an extension to combine the SVM method and the explicit analytical model, the advanced integrated DADSS system is able to compute drug concentration-to-time curves for a patient under different conditions. A feedback loop is enabled to update the curve with a new measured concentration value to make it more personalized (a posteriori adaptation).

Patient-ventilator asynchrony during noninvasive pressure support ventilation and neurally adjusted ventilatory assist in infants and children.

OBJECTIVES: To document the prevalence of asynchrony events during noninvasive ventilation in pressure support in infants and in children and to compare the results with neurally adjusted ventilatory assist. DESIGN: Prospective randomized cross-over study in children undergoing noninvasive ventilation. SETTING: The study was performed in a PICU. PATIENTS: From 4 weeks to 5 years. INTERVENTIONS: Two consecutive ventilation periods (pressure support and neurally adjusted ventilatory assist) were applied in random order. During pressure support (PS), three levels of expiratory trigger (ETS) setting were compared: initial ETS (PSinit), and ETS value decreased and increased by 15%. Of the three sessions, the period allowing for the lowest number of asynchrony events was defined as PSbest. Neurally adjusted ventilator assist level was adjusted to match the maximum airway pressure during PSinit. Positive end-expiratory pressure was the same during pressure support and neurally adjusted ventilator assist. Asynchrony events, trigger delay, and cycling-off delay were quantified for each period. RESULTS: Six infants and children were studied. Trigger delay was lower with neurally adjusted ventilator assist versus PSinit and PSbest (61 ms [56-79] vs 149 ms [134-180] and 146 ms [101-162]; p = 0.001 and 0.02, respectively). Inspiratory time in excess showed a trend to be shorter during pressure support versus neurally adjusted ventilator assist. Main asynchrony events during PSinit were autotriggering (4.8/min [1.7-12]), ineffective efforts (9.9/min [1.7-18]), and premature cycling (6.3/min [3.2-18.7]). Premature cycling (3.4/min [1.1-7.7]) was less frequent during PSbest versus PSinit (p = 0.059). The asynchrony index was significantly lower during PSbest versus PSinit (40% [28-65] vs 65.5% [42-76], p < 0.001). With neurally adjusted ventilator assist, all types of asynchronies except double triggering were reduced. The asynchrony index was lower with neurally adjusted ventilator assist (2.3% [0.7-5] vs PSinit and PSbest, p < 0.05 for both comparisons). CONCLUSION: Asynchrony events are frequent during noninvasive ventilation with pressure support in infants and in children despite adjusting the cycling-off criterion. Compared with pressure support, neurally adjusted ventilator assist allows improving patient-ventilator synchrony by reducing trigger delay and the number of asynchrony events. Further studies should determine the clinical impact of these findings.

Cross-Border Innovation Support Platform for the SMEs: The Case of St. Petersburg Corridor Region

Työssä tutkitaan eri mekanismeja rajojen ylittävään innovaatioiden edistämiseen pienten ja keskisuurten yritysten näkökulmasta. Case ympäristönä on Kaakkois-Suomen ja Luoteis-Venäjän alueeli Pietarin Corridor. Tavoitteena on löytää tarkemmat määritykset ja rajauksetnäille mekanismeille. Teoriassa muodostettiin viitekehys rajojen ylittävälle innovaatioiden edistämismallille. Mallin pohjalta toteutettiinhaastattelututkimus, joka suoritettiin case-ympäristössä. Haastattelujoukko koostui yritysten edustajista, tutkimus-henkilöstöstä sekä julkisista toimijoista. Innovaatiojärjestelmä oli avoin uusille toimintamenetelmille.Menetelmien toteuttamistapa kuitenkin jakoi mielipiteitä. Toimijoiden välille tarvitaan parempaa yhteistyötä ja tämän kautta selkeämpää kommunikointia yritysten suuntaan. Innovaatioiden edistämiseen ehdotetaan Innovation Relay Centre tyyppisen toiminnan laajentamista Corridorin alueelle sekä sen käyttämän teknologioiden välittämismallin sekä kansainvälisen verkoston hyödyntämistä. Edistämisen tukena tulisi käyttää innovaatiotietokanta-työkalua.