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Tiedon rooli työelämässä on kasvanut merkittävästi, ja ihmisen suorittamat työtehtävät painottuvatkin kasvavissa määrin tietotyötehtäviin. Työntekijöiltä odotetaan parempaa kykyä tiedon hyödyntämiseen ja sen omaksumiseen. Työntekijöiden osaamiseen ja asiantuntijuuteen liittyvä tieto voi olla kuitenkin haastavaa hyödyntää ja omaksua tiedon ollessa luonteeltaan hiljaista. Samalla työntekijöiden työympäristö on muutoksessa. Koronapandemia on sysännyt työnantajaorganisaatiot niin muualla maailmassa kuin Suomessakin suosimaan etätyötä pääasiallisena työnjärjestämistapana. Hiljaisen tiedon jakaminen etätyöympäristössä näyttäytyy kuitenkin vähän tutkittuna aihealueena. Tämä tutkielma pyrkiikin vastaamaan kyseiseen tutkimusaukkoon tutkimalla työntekijöiden välistä hiljaisen tiedon jakamista tietointensiivisessä ja tiimiperusteisessa etätyöympäristössä. Tutkimus on toteutettu tapaustutkimuksena, jonka kohteena on Suomessa toimivan kansainvälisen suuryhtiön HR-yksikkö. Tutkielma on luonteeltaan monimenetelmällinen. Tutkielmaa varten on kerätty sähköisellä kyselylomakkeella määrällinen tutkimusaineisto ja teemahaastatteluin laadullinen tutkimusaineisto. Tutkielman päätutkimusaineistona toimii kerätty laadullinen aineisto määrällisen aineiston toimiessa päätutkimusaineiston tukena. Tutkimuskohteen työntekijöiden välinen hiljaisen tiedon jakaminen etätyössä näyttäytyy tutkielman tulosten perusteella yksilöllisempään hiljaisen tiedon jakamiseen painottuneena. Työntekijöiden toiminta on yksilösuoritteisempaa, vapaamuotoisemman ja kollektiivisemman hiljaisen tiedon jakamisen ollessa etätyössä vähäisempää. Hiljaista tietoa arvostetaan, mutta sitä samalla arvotetaan ja sen määrällistä kuormittavuutta tiedon saajille varotaan. Työntekijöiden välinen yhteenkuuluvuus on tutkimustulosten mukaan osaltaan jakautunutta, mutta toisaalta viitteitä vahvasta yhteenkuuluvuudesta niin tiimien sisällä ja tiimien välillä on kuitenkin myös havaittavissa. Työntekijöiden välinen luottamus on tulosten perusteella vahvaa vaikkakin tiimien välillä on havaittavissa raja-aitoja, vähäisempää hiljaisen tiedon jakamista, ja tiimien sekä niiden jäsenten tuntemattomuutta. Kollektiivisempaa jakamista ja yhdessä työskentelyä kaivataan tulosten perusteella enemmän, ryhmä- ja lähityöskentelyn näyttäytyessä työntekijöille helpompana hiljaisen tiedon vapaamuotoisen ja kollektiivisen jakamisen toteutumisen suhteen. Jatkotutkimustarpeiksi voidaan mainita työntekijöiden välisen hiljaisen tiedon jakamisen tutkiminen eri kohdeorganisaation etätyökontekstissa, ja työntekijöiden ja esihenkilöiden välisen hiljaisen tiedon jakamisen tutkiminen etätyökontekstissa. Lisäksi myös mielenkiintoisena jatkotutkimustarpeena näyttäytyy hiljaisen tiedon jakamisen ilmeneminen hybridimallisessa työympäristössä.

Digitalization activities have been in process for several years covering most business areas. Enterprises around the globe have been preparing their digital transition by the deployment of novel ICT and IoT systems to strengthen their operational functions on many levels. It is envisioned that most businesses will benefit largely from digitalization. This applies also to research and education sector, where the universities are in role to show the way forward. Specifically, the campuses with ICT, cellular network technology and software research units are probably in the frontline to innovate and pilot sophisticated education and research environments. Utilization of data collected from specific surroundings by sensors, devices, machines, vehicles and individuals is increasingly in the focus of developing new services and applications in campuses. The discussion of data based services and applications has been increasing in recent years and emergence of specific data operators has been anticipated. Prior to the development of services and applications, it is important to specify the platforms for data management process for appropriate handling of data. A proper data management process consists of collection, warehousing, processing, refining and sharing of data while not forgetting privacy and security. Stakeholders like universities, business parks or cities are considering to initiate data operator activity by bringing open data available for service and application developers. Subsequently, another aspect with the data operator is the operation of network infrastructure. The campus discussed in this article has deployed 5G and IoT-sensor test network with edge and cloud computing functionality for research purposes. Complementary functionality like network management will be integrated in the next phase of network infrastructure development. In this paper we define the requirements on how to develop digital smart campus environment for data management and network infrastructure operations to establish an operative 5G/IoT network for research purposes. The requirement evaluation is done based on practical campus network use case in progress. Establishment of experimental 5G/IoT operative functions on campus enables to accelerate procreation of research based innovations specifically when the environment is open for enterprises, developers and innovators like the in the campus presented here. The innovations are piloted in the campus surroundings and the most promising ones are up-scaled to develop city governance or to offer services for smart city inhabitants. The most successful innovations will be scaled nationally and globally. Subsequently, a locally operated experimental 5G/IoT network infrastructure on campus advances to find novel approaches in telecom regulation and models for future telecom market which is foreseen to change significantly.

In engine exhaust particle measurements, the sample is usually warm. Sample temperature needs to decrease before it can be measure with real-time aerosol measurement instruments. By decreasing the sample temperature, there is possibility to have condensation and/or nucleation of water, sulphuric compound and VOC. When the aim of the research is to study solid exhaust particles this problem is typically handled with a dilution system that decreases the temperature and vapor pressures in two dilution stages including thermal treatment. However with low-emission vehicles, this might also lower the particle concentration below instrument detection limit. Also, despite the controlled temperature profile dilution might still affect the size, composition and structure of particles, and uncertainty in dilution factor might decrease the measurement accuracy. To avoid these issues a new version of the Electrical Low Pressure Impactor ELPI+T was developed for high temperature, low concentration measurement. In this system, the detector part, impactor, is heated to a sample temperature up to 180C, see Figure 1. This allows high temperature tailpipe aerosol measurement without dilution, without sample cooling and without VOC condensation. In other words, the particles are measured as they exist in the tailpipe. Figure 1. Operating principle of the High Temperature ELPI+T. Impactor is heated to be able to operate with high temperature sample The system was tested with a 2-litre passenger car engine that was modified for natural gas fuel, known to produce very low particle emissions. In the test setup, the exhaust gas composition was made adjustable by adding methane, propane, ethane and ethene to tailpipe-extracted side flow to mimic large bore engine (ship / power plant) emission composition. The developed High Temperature ELPI+T was used to measure the particle size distribution and concentration from tailpipe environment before catalysts. A bimodal particle number size distribution was detected, one mode at below 10 nm particle size range and the other mode at around 30 nm, see Figure 2. A volume-weighed size distribution also shows a large particle mode at around 750 nm. In this presentation, we describe the HT-ELPI+T and the engine and exhaust conditioning setup and present the particle measurement results from the system. We also discuss about the detected particles and their origin and present comparison results from other instruments (EEPS, SMPS and gravimetric filter measurement) that simultaneously measured diluted exhaust. Figure 2. Number size distribution measured with HT-ELPI+T.

In common engine exhausts particle measurements the sample temperature must be decreased to suitable level for measurement instrument, but when doing so there is a risk of water, sulfuric compound and VOC condensation and even nucleation. When the aim of the research is to study solid exhaust particles, this problem is typically handled with a dilution system that decreases the temperature and vapor pressures in two dilution stages including thermal treatment. However with low-emission vehicles this might also lower the particle concentration below instrument detection limit. Also, despite the controlled temperature profile dilution might still affect the size, composition and structure of particles, and uncertainty in dilution factor might decrease the measurement accuracy. To avoid these issues a new version of the Electrical Low Pressure Impactor ELPI+ was developed for high temperature, low concentration measurement. In this system the detector part, impactor, is heated to a high temperature up to 180C. This allows high temperature tailpipe aerosol measurement without dilution, without sample cooling and without VOC condensation. In other words, the particles are measured as they exist in the tailpipe. The system was tested with a 2-litre passenger car engine that was modified for natural gas fuel, known to produce very low particle emissions. In the test setup the exhaust gas composition was made adjustable by adding methane, propane, ethane and ethene to tailpipe-extracted side flow to mimic large bore engine (ship / power plant) emission composition. The developed High Temperature ELPI+ was used to measure the particle size distribution and concentration from tailpipe environment before catalysts. A two-mode particle size distribution was detected, one mode at below 10 nm particle size range and the other mode at around 30 nm. A volume-weighed distribution also shows a large particle mode at around 750 nm. In this presentation we describe the HT-ELPI+ and the engine and exhaust conditioning setup and present the particle measurement results from the system. We also discuss about the detected particles and their origin and present comparison results from other instruments that simultaneously measured diluted exhaust.