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.

Microgrid frequency control using multiple battery energy storage system (BESSs)

The work is a report of research on using multiple inverters of Battery Energy Storage Systems with angle droop controllers to share real power in an isolated micro grid system consisting of inertia based Distributed Generation units and variable load. The proposed angle droop control method helps to balance the supply and demand in the micro grid autonomous mode through charging and discharging of the Battery Energy Storage Systems while ensuring that the state of charge of the storage devices is within safe operating conditions. The proposed method is also studied for its effectiveness for frequency control. The proposed control system is verified and its performance validated with simulation software MATLAB/SIMULINK.

On the Cubicity of Interval Graphs

A k-cube (or ``a unit cube in k dimensions'') is defined as the Cartesian product R-1 x . . . x R-k where R-i (for 1 <= i <= k) is an interval of the form [a(i), a(i) + 1] on the real line. The k-cube representation of a graph G is a mapping of the vertices of G to k-cubes such that the k-cubes corresponding to two vertices in G have a non-empty intersection if and only if the vertices are adjacent. The cubicity of a graph G, denoted as cub(G), is defined as the minimum dimension k such that G has a k-cube representation. An interval graph is a graph that can be represented as the intersection of intervals on the real line - i. e., the vertices of an interval graph can be mapped to intervals on the real line such that two vertices are adjacent if and only if their corresponding intervals overlap. We show that for any interval graph G with maximum degree Delta, cub(G) <= inverted right perpendicular log(2) Delta inverted left perpendicular + 4. This upper bound is shown to be tight up to an additive constant of 4 by demonstrating interval graphs for which cubicity is equal to inverted right perpendicular log(2) Delta inverted left perpendicular.

QTL analysis of ergot resistance in sorghum

Sorghum ergot, caused predominantly by Claviceps africana Frederickson, Mantle, de Milliano, is a significant threat to the sorghum industry worldwide. The objectives of this study were firstly, to identify molecular markers linked to ergot resistance and to two pollen traits, pollen quantity (PQ) and pollen viability (PV), and secondly, to assess the relationship between the two pollen traits and ergot resistance in sorghum. A genetic linkage map of sorghum RIL population R931945-2-2 x IS 8525 (resistance source) was constructed using 303 markers including 36 SSR, 117 AFLP™, 148 DArT™ and two morphological trait loci. Composite interval mapping identified nine, five, and four QTL linked to molecular markers for percentage ergot infection (PCERGOT), PQ and PV, respectively, at a LOD >2.0. Co-location/linkage of QTL were identified on four chromosomes while other QTL for the three traits mapped independently, indicating that both pollen and non pollen-based mechanisms of ergot resistance were operating in this sorghum population. Of the nine QTL identified for PCERGOT, five were identified using the overall data set while four were specific to the group data sets defined by temperature and humidity. QTL identified on SBI-02 and SBI-06 were further validated in additional populations. This is the first report of QTL associated with ergot resistance in sorghum. The markers reported herein could be used for marker-assisted selection for this important disease of sorghum.

Effect of defoliation interval and height on the growth and quality of Arachis pintoi cv. Amarillo

The effect of defoliation on Amarillo (Arachis pintoi cv. Amarillo) was studied in a glasshouse and in mixed swards with 2 tropical grasses. In the glasshouse, Amarillo plants grown in pots were subjected to a 30/20°C or 25/15°C temperature regime and to defoliation at 10-, 20- or 30-day intervals for 60 days. Two field plot studies were conducted on Amarillo with either irrigated kikuyu (Pennisetum clandestinum) in autumn and spring or dryland Pioneer rhodes grass (Chloris gayana) over summer and autumn. Treatments imposed were 3 defoliation intervals (7, 14 and 28 days) and 2 residual heights (5 and 10 cm for kikuyu; 3 and 10 cm for rhodes grass) with extra treatments (56 days to 3 cm for both grasses and 21 days to 5 cm for kikuyu). Defoliation interval had no significant effect on accumulated Amarillo leaf dry matter (DM) at either temperature regime. At the higher temperature, frequent defoliation reduced root dry weight (DW) and increased crude protein (CP) but had no effect on stolon DW or in vitro organic matter digestibility (OMD). On the other hand, at the lower temperature, frequent defoliation reduced stolon DW and increased OMD but had no effect on root DW or CP. Irrespective of temperaure and defoliation, water-soluble carbohydrate levels were higher in stolons than in roots (4.70 vs 3.65%), whereas for starch the reverse occured (5.37 vs 9.44%). Defoliating the Amarillo-kikuyu sward once at 56 days to 3 cm produced the highest DM yield in autumn and sprong (582 and 7121 kg/ha DM, respectively), although the Amarillo component and OMD were substantially reduced. Highest DM yields (1726 kg/ha) were also achieved in the Amarillo-rhodes grass sward when defoliated every 56 days to 3 cm, although the Amarillo component was unaffected. In a mixed sward with either kikuyu or rhodes grass, the Amarillo component in the sward was maintained up to a 28-day defoliation interval and was higher when more severely defoliated. The results show that Amarillo can tolerate frequent defoliation and that it can co-exist with tropical grasses of differing growth habits, provided the Amarillo-tropical grass sward is subject to frequent and severe defoliation.

Laboratory information management software for genotyping workflows: Applications in high throughput crop genotyping

Background: With the advances in DNA sequencer-based technologies, it has become possible to automate several steps of the genotyping process leading to increased throughput. To efficiently handle the large amounts of genotypic data generated and help with quality control, there is a strong need for a software system that can help with the tracking of samples and capture and management of data at different steps of the process. Such systems, while serving to manage the workflow precisely, also encourage good laboratory practice by standardizing protocols, recording and annotating data from every step of the workflow Results: A laboratory information management system (LIMS) has been designed and implemented at the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) that meets the requirements of a moderately high throughput molecular genotyping facility. The application is designed as modules and is simple to learn and use. The application leads the user through each step of the process from starting an experiment to the storing of output data from the genotype detection step with auto-binning of alleles; thus ensuring that every DNA sample is handled in an identical manner and all the necessary data are captured. The application keeps track of DNA samples and generated data. Data entry into the system is through the use of forms for file uploads. The LIMS provides functions to trace back to the electrophoresis gel files or sample source for any genotypic data and for repeating experiments. The LIMS is being presently used for the capture of high throughput SSR (simple-sequence repeat) genotyping data from the legume (chickpea, groundnut and pigeonpea) and cereal (sorghum and millets) crops of importance in the semi-arid tropics. Conclusions: A laboratory information management system is available that has been found useful in the management of microsatellite genotype data in a moderately high throughput genotyping laboratory. The application with source code is freely available for academic users and can be downloaded from http://www.icrisat.org/bt-software-d-lims.htm

Modeling dynamic demand response using Monte Carlo simulation and interval mathematics for boundary estimation

With the rapid development of various technologies and applications in smart grid implementation, demand response has attracted growing research interests because of its potentials in enhancing power grid reliability with reduced system operation costs. This paper presents a new demand response model with elastic economic dispatch in a locational marginal pricing market. It models system economic dispatch as a feedback control process, and introduces a flexible and adjustable load cost as a controlled signal to adjust demand response. Compared with the conventional “one time use” static load dispatch model, this dynamic feedback demand response model may adjust the load to a desired level in a finite number of time steps and a proof of convergence is provided. In addition, Monte Carlo simulation and boundary calculation using interval mathematics are applied for describing uncertainty of end-user's response to an independent system operator's expected dispatch. A numerical analysis based on the modified Pennsylvania-Jersey-Maryland power pool five-bus system is introduced for simulation and the results verify the effectiveness of the proposed model. System operators may use the proposed model to obtain insights in demand response processes for their decision-making regarding system load levels and operation conditions.

Simple software processes and tests improve the reliability and usefulness of a model.

Models are abstractions of reality that have predetermined limits (often not consciously thought through) on what problem domains the models can be used to explore. These limits are determined by the range of observed data used to construct and validate the model. However, it is important to remember that operating the model beyond these limits, one of the reasons for building the model in the first place, potentially brings unwanted behaviour and thus reduces the usefulness of the model. Our experience with the Agricultural Production Systems Simulator (APSIM), a farming systems model, has led us to adapt techniques from the disciplines of modelling and software development to create a model development process. This process is simple, easy to follow, and brings a much higher level of stability to the development effort, which then delivers a much more useful model. A major part of the process relies on having a range of detailed model tests (unit, simulation, sensibility, validation) that exercise a model at various levels (sub-model, model and simulation). To underline the usefulness of testing, we examine several case studies where simulated output can be compared with simple relationships. For example, output is compared with crop water use efficiency relationships gleaned from the literature to check that the model reproduces the expected function. Similarly, another case study attempts to reproduce generalised hydrological relationships found in the literature. This paper then describes a simple model development process (using version control, automated testing and differencing tools), that will enhance the reliability and usefulness of a model.

Breedcow and Dynama software redevelopment

The project renewed the Breedcow and Dynama software making it compatible with modern computer operating systems and platforms. Enhancements were also made to the linkages between the individual programs and their operation. The suite of programs is a critical component of the skill set required to make soundly based plans and production choices in the north Australian beef industry.

Interval Data Classification under Partial Information: A Chance-Constraint Approach

This paper presents a Chance-constraint Programming approach for constructing maximum-margin classifiers which are robust to interval-valued uncertainty in training examples. The methodology ensures that uncertain examples are classified correctly with high probability by employing chance-constraints. The main contribution of the paper is to pose the resultant optimization problem as a Second Order Cone Program by using large deviation inequalities, due to Bernstein. Apart from support and mean of the uncertain examples these Bernstein based relaxations make no further assumptions on the underlying uncertainty. Classifiers built using the proposed approach are less conservative, yield higher margins and hence are expected to generalize better than existing methods. Experimental results on synthetic and real-world datasets show that the proposed classifiers are better equipped to handle interval-valued uncertainty than state-of-the-art.

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.

The complete validated mitochondrial genome of the silver gemfish Rexea solandri (Cuvier, 1832) (Perciformes, Gempylidae)

The silver gemfish Rexea solandri is an important economic resource but vulnerable to overfishing in Australian waters. The complete mitochondrial genome sequence is described from 1.6 million reads obtained via next generation sequencing. The total length of the mitogenome is 16,350 bp comprising 2 rRNA, 13 protein-coding genes, 22 tRNA and 2 non-coding regions. The mitogenome sequence was validated against sequences of PCR fragments and BLAST queries of Genbank. Gene order was equivalent to that found in marine fishes.

NEESTIMATOR v2: re-implementation of software for the estimation of contemporary effective population size (N-e) from genetic data

NeEstimator v2 is a completely revised and updated implementation of software that produces estimates of contemporary effective population size, using several different methods and a single input file. NeEstimator v2 includes three single-sample estimators (updated versions of the linkage disequilibrium and heterozygote-excess methods, and a new method based on molecular coancestry), as well as the two-sample (moment-based temporal) method. New features include the following: (i) an improved method for accounting for missing data; (ii) options for screening out rare alleles; (iii) confidence intervals for all methods; (iv) the ability to analyse data sets with large numbers of genetic markers (10000 or more); (v) options for batch processing large numbers of different data sets, which will facilitate cross-method comparisons using simulated data; and (vi) correction for temporal estimates when individuals sampled are not removed from the population (Plan I sampling). The user is given considerable control over input data and composition, and format of output files. The freely available software has a new JAVA interface and runs under MacOS, Linux and Windows.

Information sharing in distance collaboration: A software engineering perspective

Information sharing in distance collaboration: A software engineering perspective, QueenslandFactors in software engineering workgroups such as geographical dispersion and background discipline can be conceptually characterized as "distances", and they are obstructive to team collaboration and information sharing. This thesis focuses on information sharing across multidimensional distances and develops an information sharing distance model, with six core dimensions: geography, time zone, organization, multi-discipline, heterogeneous roles, and varying project tenure. The research suggests that the effectiveness of workgroups may be improved through mindful conducts of information sharing, especially proactive consideration of, and explicit adjustment for, the distances of the recipient when sharing information.

Assessing the effectiveness of High Intensity Interval Training (HIIT) for smoking cessation in women: HIIT to quit study protocol

Background: Smoking and physical inactivity are major risk factors for heart disease. Linking strategies that promote improvements in fitness and assist quitting smoking has potential to address both these risk factors simultaneously. The objective of this study is to compare the effects of two exercise interventions (high intensity interval training (HIIT) and lifestyle physical activity) on smoking cessation in female smokers. Method/design: This study will use a randomised controlled trial design. Participants: Women aged 18–55 years who smoke ≥ 5 cigarettes/day, and want to quit smoking. Intervention: all participants will receive usual care for quitting smoking. Group 1 - will complete two gym-based supervised HIIT sessions/week and one home-based HIIT session/week. At each training session participants will be asked to complete four 4-min (4 × 4 min) intervals at approximately 90 % of maximum heart rate interspersed with 3- min recovery periods. Group 2 - participants will receive a resource pack and pedometer, and will be asked to use the 10,000 steps log book to record steps and other physical activities. The aim will be to increase daily steps to 10,000 steps/day. Analysis will be intention to treat and measures will include smoking cessation, withdrawal and cravings, fitness, physical activity, and well-being. Discussion: The study builds on previous research suggesting that exercise intensity may influence the efficacy of exercise as a smoking cessation intervention. The hypothesis is that HIIT will improve fitness and assist women to quit smoking.