Effects of the digital subtitling software on the subtitling process : A survey among Finnish professional television subtitlers

Tutkielma käsittelee suomalaisten televisiotekstittäjien ammatillisuutta, käännösprosessia ja digitaalisten tekstitysohjelmien vaikutuksia tekstitysprosessiin ammattitekstittäjien näkökulmasta. Suomen television digitalisoituminen on aiheuttanut mullistuksia myös tekstitysalalla kun tekstitettävä kuvamateriaali on ryhdytty toimittamaan käännöstoimistoille ja tekstittäjille digitaalisena. Teoriaosuudessa käsitellään käännös- ja tekstitystutkimusta sekä koulutusta Suomessa, ammattitaitoa ja ammatillisuutta sekä kääntämisen apukeinoja. Tekstittäminen esitellään erikoistuneena kääntämisen muotona. On kuitenkin myös huomioitava, että kääntäminen on yksi vaihe tekstitysprosessissa. Teoriaosuus päättyy suomalaisten televisiotekstittäjien arjen ja työkentän nykytilanteen käsittelyyn – tekstittäjät työskentelevät monenlaisilla työehdoilla ja laadun kriteerit saatetaan joutua arvioimaan uudelleen. Empiirisen osan alussa esitetään, että suomalaisia televisiotekstittäjiä on haastateltu yllättävän vähän, ja Jääskeläisen ajatuksiin nojaten mainitaan, että tekstittämisen alalla on vielä paljon tutkimatta – etenkin suomalaisesta tekstitysprosessista löytyy tutkittavaa. Tutkimuskohde on ammatikseen televisioon tekstityksiä tekevät kääntäjät. Suomalaiselle tekstitykseen erikoistuneelle käännöstoimistolle työskenteleville tekstittäjille lähetettiin alkutalvesta 2008 kyselylomake, jolla kartoitettiin sekä monivalintakysymyksillä että avoimilla kysymyksillä heidän ammatillisuuttaan, työmenetelmiään, käännös- ja tekstitysprosessiaan, ammattiylpeyttään ja -identiteettiään, ajanhallintaansa, sekä heidän käyttämäänsä digitaalista tekstitysohjelmaa. Tutkimuksessa kävi ilmi, että lähes kolmanneksella vastaajista on ammatistaan neutraali tai jopa negatiivinen käsitys. Näitä tekstittäjiä yhdistää se seikka, että kaikilla on alle 5 vuotta kokemusta alalta. Valtaosa vastanneista on kuitenkin ylpeitä siitä, että toimivat suomen kielen ammattilaisina. Tekstitysprosessi oli lomakkeessa jaettu esikatseluvaiheeseen, käännösvaiheeseen, ajastamisvaiheeseen ja korjauskatseluvaiheeseen. Tekstittäjät pyydettiin mm. arvioimaan tekstitysprosessinsa kokonaiskestoa. Kestoissa ilmeni suuria eroavaisuuksia, joista ainakin osa korreloi kokemuksen kanssa. Runsas puolet vastaajista on hankkinut digitaalisen tekstitysohjelmiston käyttöönsä ja osa ajastaa edelleen käännöstoimistossa muun muassa ohjelmiston kalleuden vuoksi. Digitaalisen ohjelmiston myötä tekstitysprosessiin ja työkäytänteisiin on tullut muutoksia, kun videonauhureista ja televisioista on siirrytty pelkän tietokoneen käyttöön. On mahdollista tehdä etätyötä kaukomailta käsin, kääntää ja ajastaa lomittain tai tehdä esiajastus ja kääntää sitten. Digitaalinen tekniikka on siis mahdollistanut tekstitysprosessin muuttumisen ja vaihtoehtoiset työmenetelmät, mutta kaikista menetelmistä ei välttämättä ole tekstittäjälle hyötyä. Perinteinen tekstitysprosessi (esikatselu, repliikkijakojen merkitseminen käsikirjoitukseen, kääntäminen ja repliikkien laadinta, korjaukset ja tarkastuskatselu) vaikuttaa edelleen tehokkaimmalta. Vaikka työkäytänteet eroavat toisistaan, kokonaiskäsitys on se, että digitalisoitumisen alkukangertelujen jälkeen tekstittäjien työskentely on tehostunut.

Effect of waiting time on health outcomes and service utilization : A prospective randomized study on patients admitted to hospital for hip or knee replacement

Although the principle of equal access to medically justified treatment has been promoted by official health policies in many Western health care systems, practices do not completely meet policy targets. Waiting times for elective surgery vary between patient groups and regions, and growing problems in the availability of services threaten equal access to treatment. Waiting times have come to the attention of decision-makers, and several policy initiatives have been introduced to ensure the availability of care within a reasonable time. In Finland, for example, the treatment guarantee came into force in 2005. However, no consensus exists on optimal waiting time for different patient groups. The purpose of this multi-centre randomized controlled trial was to analyse health-related quality of life, pain and physical function in total hip or knee replacement patients during the waiting time and to evaluate whether the waiting time is associated with patients health outcomes at admission. This study also assessed whether the length of waiting time is associated with social and health services utilization in patients awaiting total hip or knee replacement. In addition, patients health-related quality of life was compared with that of the general population. Consecutive patients with a need for a primary total hip or knee replacement due to osteoarthritis were placed on the waiting list between August 2002 and November 2003. Patients were randomly assigned to a short waiting time (maximum 3 months) or a non-fixed waiting time (waiting time not fixed in advance, instead the patient followed the hospitals routine practice). Patients health-related quality of life was measured upon being placed on the waiting list and again at hospital admission using the generic 15D instrument. Pain and physical function were evaluated using the self-report Harris Hip Score for hip patients and a scale modified from the Knee Society Clinical Rating System for knee patients. Utilization measures were the use of home health care, rehabilitation and social services, physician visits and inpatient care. Health and social services use was low in both waiting time groups. The most common services used while waiting were rehabilitation services and informal care, including unpaid care provided by relatives, neighbours and volunteers. Although patients suffered from clear restrictions in usual activities and physical functioning, they seemed primarily to lean on informal care and personal networks instead of professional care. While longer waiting time did not result in poorer health-related quality of life at admission and use of services during the waiting time was similar to that at the time of placement on the list, there is likely to be higher costs of waiting by people who wait longer simply because they are using services for a longer period. In economic terms, this would represent a negative impact of waiting. Only a few reports have been published of the health-related quality of life of patients awaiting total hip or knee replacement. These findings demonstrate that, in addition to physical dimensions of health, patients suffered from restrictions in psychological well-being such as depression, distress and reduced vitality. This raises the question of how to support patients who suffer from psychological distress during the waiting time and how to develop strategies to improve patients initiatives to reduce symptoms and the burden of waiting. Key words: waiting time, total hip replacement, total knee replacement, health-related quality of life, randomized controlled trial, outcome assessment, social service, utilization of health services

Automatic Lameness Detection in a Milking Robot : Instrumentation, measurement software, algorithms for data analysis and a neural network model

The aim of this thesis is to develop a fully automatic lameness detection system that operates in a milking robot. The instrumentation, measurement software, algorithms for data analysis and a neural network model for lameness detection were developed. Automatic milking has become a common practice in dairy husbandry, and in the year 2006 about 4000 farms worldwide used over 6000 milking robots. There is a worldwide movement with the objective of fully automating every process from feeding to milking. Increase in automation is a consequence of increasing farm sizes, the demand for more efficient production and the growth of labour costs. As the level of automation increases, the time that the cattle keeper uses for monitoring animals often decreases. This has created a need for systems for automatically monitoring the health of farm animals. The popularity of milking robots also offers a new and unique possibility to monitor animals in a single confined space up to four times daily. Lameness is a crucial welfare issue in the modern dairy industry. Limb disorders cause serious welfare, health and economic problems especially in loose housing of cattle. Lameness causes losses in milk production and leads to early culling of animals. These costs could be reduced with early identification and treatment. At present, only a few methods for automatically detecting lameness have been developed, and the most common methods used for lameness detection and assessment are various visual locomotion scoring systems. The problem with locomotion scoring is that it needs experience to be conducted properly, it is labour intensive as an on-farm method and the results are subjective. A four balance system for measuring the leg load distribution of dairy cows during milking in order to detect lameness was developed and set up in the University of Helsinki Research farm Suitia. The leg weights of 73 cows were successfully recorded during almost 10,000 robotic milkings over a period of 5 months. The cows were locomotion scored weekly, and the lame cows were inspected clinically for hoof lesions. Unsuccessful measurements, caused by cows standing outside the balances, were removed from the data with a special algorithm, and the mean leg loads and the number of kicks during milking was calculated. In order to develop an expert system to automatically detect lameness cases, a model was needed. A probabilistic neural network (PNN) classifier model was chosen for the task. The data was divided in two parts and 5,074 measurements from 37 cows were used to train the model. The operation of the model was evaluated for its ability to detect lameness in the validating dataset, which had 4,868 measurements from 36 cows. The model was able to classify 96% of the measurements correctly as sound or lame cows, and 100% of the lameness cases in the validation data were identified. The number of measurements causing false alarms was 1.1%. The developed model has the potential to be used for on-farm decision support and can be used in a real-time lameness monitoring system.