Talvi arktisen taiteen ja muotoilun luonnonvarana

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Kuerin matkassa: paikkaperustainen taideteos ympäristökonfliktissa

This article discusses a socially-engaged environmental art titled Kuer’s Journey and a related video work. The art work was created in the summer of 2018in collaboration with the Art Äkäslompolo art event. According to local wishes, the event critically considered the plan for the Hannukainen iron ore minetargeted next to the Äkäslompolo village near the Pallas-Yllästunturi National Park. Kuer’s Journey was carried out using an art-based action research approach to create a dialogic space and situation that serves as a tool for decolonisation and cultural revitalisation, while increasing community resilienceand adaptation, in inevitable environmental and cultural change in the Arctic. At the core of the article is the concept of Arctic art, which is used to reflecton the encounter between Western contemporary art practices and northern ecocultures and ways of knowing

Vehicle Collision Detection based on Synthetic Data using Deep Learning

Computer vision and deep learning methods that process visual data have considerably improved during the last decade. This progress has also affected the development of so-called autonomous vehicles, which are able to act independently in the traffic. One notable hindrance facing any deep learning application is the amount of quality data that is available. Data means the corpus of information from which the models learn new skills. Lack of good data is often the most significant hurdle a deep learning project faces. When considering autonomous vehicles and traffic generally, this problem is particularly evident in a collision context, as there is very little accident data available for public use and research, particularly when the data should be both consistent and of good quality. This thesis presents a solution in which real data is substituted with data that is generated in a video game environment. The solution proposed in this thesis can learn collision detection by looking at the synthetic data and then apply the learned information in detecting real collisions. The presented solution consists of three phases. The first two phases are object detection and object tracking which are used to identify and follow vehicles moving the video footage using deep learning. Information obtained in these phases is then transferred to the third phase, a collision detector, which attempts to infer if the tracked vehicle is moving normally or if it is participating in a collision. Initial results indicate a promising although limited connection between synthetic and real-world data, and the proposed model is able to slightly surpass the performance of a trivial baseline. However, the generated synthetic training data is not entirely representative of its real-world counterpart, which results in some of the collision events being very difficult to detect properly.Konenäkö ja visuaalista dataa käsittelevät koneoppimismenetelmät ovat kehittyneet merkittävästi kuluneen vuosikymmenen aikana. Tämä edistys on myös näkynyt myös niin kutsuttujen autonomisten ajoneuvojen tuotekehityksessä, eli kehitettäessä liikennevälineitä, jotka kykenevät toimimaan liikenteessä itsenäisesti. Eräs merkittävä hidaste mille tahansa koneoppimisen sovellutukselle on saatavilla olevan laadukkaan datan määrä. Datalla tarkoitetaan sitä tietoaineistoa, jonka avulla koneoppimisen mallit oppivat uusia taitoja. Laadukkaan aineiston puute on usein merkittävin este, jonka moni koneoppimiseen liittyvä projekti kohtaa. Autonomisista ajoneuvoista sekä yleisesti liikenteestä puhuttaessa edellä mainittu koskee erityisesti onnettomuuksia, joista ei juurikaan ole tarjolla yhdenmukaista ja hyvälaatuista dataa julkista käyttöä ja tutkimusta varten. Tämä opinnäytetyö esittelee ratkaisun, jossa todellinen onnettomuusdata korvataan videopeliympäristössä luodulla datalla. Tutkielmassa esiteltävä ratkaisu kykenee oppimaan törmäyksen tunnistuksen keinotekoisesta datasta ja sen jälkeen soveltamaan opittua tietoa todellisiin törmäyksiin. Tutkielman ratkaisu koostuu kolmesta erillisestä osa-alueesta. Kaksi ensimmäistä osa-aluetta ovat kohteiden tunnistaminen ja seuranta, joiden avulla jäljitetään videoaineistossa liikkuvia ajoneuvoja. Tiedot liikkuvista ajoneuvoista siirretään törmäyksiä tunnistavalle mallille, joka pyrkii päättelemään, liikkuuko seurattava ajoneuvo normaalisti vai onko se osallisena törmäyksessä. Mallinnukset tuottavat lupaavia tuloksia, mutta yhteys keinotekoisen ja todellisen datan välillä jää osin vaillinaiseksi. Esitetty törmäyksiä tunnistava malli onnistuu hienoisesti parantamaan tuloksia verrattuna triviaaliin vertailukohtamalliin. Keinotekoinen data ei kuitenkaan täysin vastaa todellisia törmäyksiä, mistä johtuen mallin on erittäin vaikea tunnistaa joitakin törmäystilanteita täsmällisesti

Analysis of Usability Cost-Benefit Models

There are few development organizations that have fully integrated usability activities as an integral part of their product development projects. One reason for this is that the benefits of better usability are not visible for the management. In this paper, the characteristics of selected published usability cost-benefit models are analyzed. These models have different approaches for identifying, approaching and categorizing the costs and benefits of usability. The analyzed models provide general guidelines for estimating the costs and benefits of usability but in most cases provide only little details. It is proposed that the business type of development organization and the type of the developed product as variables could be taken into account when analyzing the benefits of better usability

Arctic Arts with Pride:Discourses on Arctic Arts, Culture and Sustainability

There has been growing interest in Arctic arts and culture as well as in sustainability among artists, researchers, and policy makers. However, until recently, the comprehension of Arctic arts and culture within the framework of sustainable development has remained vague. In this study, by analysing diverse debates from the Arctic Arts Summit 2019 in Rovaniemi, we investigate how the arts and culture sector promotes Arctic sustainability. An analysis of abstracts, conclusions, blogs and newspaper articles reflecting the presentations, art events, exhibitions and dialogues showed that the discourse on sustainability is organised around five themes: (1) global politics and ecological crises as part of the cultural politics of the Arctic; (2) indigenous and non-indigenous Arctic arts and culture; (3) ‘handmade’ and the material culture of the Arctic; (4) place-making, revitalisation and regional development; and (5) economy and sustainability. These partly interlinked themes have relevance for policy making, defining principles for arts and culture funding, artistic practice and research on the Arctic. In addition, education and artistic training are important for all of the five themes; therefore, resources for educational institutions are crucial for the sustainable future of the Arctic. Arts, culture and education have the potential to empower people in the Arctic, increase cultural pride, educate and inform global audiences and create connectedness between the past, present and future. Arts, culture and education contribute to Arctic sustainability