Type-I ion outflow from the high latitude ionosphere

The aim of this thesis is to study type-I ion outflows in the high latitude ionosphere. Type-I ion outflows are characterized by strong perpendicular electric fields, enhanced and anisotropic ion temperatures and low electron densities below 300 km, indicating small amounts of hard particle precipitation. We scanned data from the EISCAT Madrigal database over a period of 10 years (January 2000 - December 2010). We checked the colour plots of the field-aligned experiments ran with the UHF, the VHF and the ESR radars. Data from the type-I candidates have then been analyzed using a matlab program. Type-I ion outflows have been divided into two categories: non-continuous and continuous, depending on the temperature ratio profile. Continuous outflows have been detected with the ESR radar and only at high altitudes ( > 400 km) with the VHF radar. We suggest different ion heating mechanisms at different locations and altitudes. Type-I ion outflows have been detected only in the evening sector with the UHF and VHF radars, but both in the morning and evening sectors with the ESR radars, suggesting that particle precipitations may be of relevance to trigger these outflows. A third type of ion outflows has been identified showing a fast changing temperature ratio profile. When possible we checked the presence of naturally enhanced ion acoustic lines (NEIALs) during type-I ion outflows, 4 outflow events have been analyzed. We found NEIALs during 1 outflow event, suggesting that the proposed theories in the literature about the NEIAL generation mechanisms should be discussed in the future or other mechanisms are needed to fulfill the requirement of a temperature ratio less than 1

Using authentic texts for grammar exercises for a minority language

Source at http://www.ep.liu.se/index.en.asp.This paper presents an ATICALL (Authentic Text ICALL) system with automatic visual input enhancement activities for training complex inflection systems in a minority language. We have adapted the freely available VIEW system which was designed to automatically generate activities from any web content. Our system is based on finite state transducers (FST) and Constraint Grammar, originally built for other purposes. The paper describes ways of handling ambiguity in the target form in the exercises, and ways of handling the challenges for VIEW posed by authentic text, typical for a minority language: variations in orthography, and large proportion of nonnormative forms.</p

Suoidne-varra-bleahkka-mála-bihkka-senet-dielku 'hay-blood-ink-paint-tar-mustard-stain' -Should compounds be lexicalized in NLP?

Source at http://ceur-ws.org/Vol-2769/paper_49.pdf. CEUR Workshop Proceedings home page at http://ceur-ws.org/Vol-2769/.Lexicalizing compounds, in addition to treating them dynamically, is a key element in giving us idiomatic translations and detecting compound errors. We present and evaluate an e-dictionary (NDS) and a grammar checker (GramDivvun) for North Sámi. We achieve a coverage of 98% for NDSqueries and of 96% for compound error detection in GramDivvun

Mii *eai leat gal vuollánan -- Vi *ha neimen ikke gitt opp: En hybrid grammatikkontroll for å rette kongruensfeil

Machine learning is the dominating paradigm in natural language processing nowadays. It requires vast amounts of manually annotated or synthetically generated text data. In the GiellaLT infrastructure, on the other hand, we have worked with rule-based methods, where the linguistis have full control over the development the tools. In this article we uncover the myth of machine learning being cheaper than a rule-based approach by showing how much work there is behind data generation, either via corpus annotation or creating tools that automatically mark-up the corpus. Earlier we have shown that the correction of grammatical errors, in particular compound errors, benefit from hybrid methods. Agreement errors, on the other other hand, are to a higher degree dependent on the larger grammatical context. Our experiments show that machine learning methods for this error type, even when supplemented by rule-based methods generating massive data, can not compete with the state-of-the-art rule-based approach.Maskinlæringsteknikker der lingvistisk ekspertise ikke brukes dominerer språkteknologi nå til dags. Dette krever at man merker opp en stor datamengde manuelt på forhånd. I GiellaLT-infrastrukturen har man der- imot jobbet med regelbaserte metoder der lingvisten har kontroll over hvordan verktøyene fungerer. Det er ikke bare tekniske årsaker for metodevalget. Kunnskapsøkning om samisk grammatikk, kvalitetssikring og kontrollerbarhet (verktøyene gjør det de skal gjøre også ifølge menneskelige standard) ligger bak preferansen om å jobbe regelbasert. I denne artikkelen vil vi forsøke å avdekke myten om at maskinlæring blir billigere enn regelbaserte metoder. Likevel tror vi at maskinlæringsmetoder kan være nyttige der vi ønsker større dekning av feilretting. Vi viser at maskinlæringsmodeller som har tilgang til små datameng- der (i dette tilfelle for små språk) er avhengig av gode regelbaserte verktøy som erstatning for manuell oppmerking

Mii *eai leat gal vuollánan – Vi *ha neimen ikke gitt opp

Machine learning is the dominating paradigm in natural language processing nowadays. It requires vast amounts of manually annotated or synthetically generated text data. In the GiellaLT infrastructure, on the other hand, we have worked with rule-based methods, where the linguistis have full control over the development the tools. In this article we uncover the myth of machine learning being cheaper than a rule-based approach by showing how much work there is behind data generation, either via corpus annotation or creating tools that automatically mark-up the corpus. Earlier we have shown that the correction of grammatical errors, in particular compound errors, benefit from hybrid methods. Agreement errors, on the other other hand, are to a higher degree dependent on the larger grammatical context. Our experiments show that machine learning methods for this error type, even when supplemented by rule-based methods generating massive data, can not compete with the state-of-the-art rule-based approach

Type-I ion outflow from the high latitude ionosphere

The aim of this thesis is to study type-I ion outflows in the high latitude ionosphere. Type-I ion outflows are characterized by strong perpendicular electric fields, enhanced and anisotropic ion temperatures and low electron densities below 300 km, indicating small amounts of hard particle precipitation. We scanned data from the EISCAT Madrigal database over a period of 10 years (January 2000 - December 2010). We checked the colour plots of the field-aligned experiments ran with the UHF, the VHF and the ESR radars. Data from the type-I candidates have then been analyzed using a matlab program. Type-I ion outflows have been divided into two categories: non-continuous and continuous, depending on the temperature ratio profile. Continuous outflows have been detected with the ESR radar and only at high altitudes ( > 400 km) with the VHF radar. We suggest different ion heating mechanisms at different locations and altitudes. Type-I ion outflows have been detected only in the evening sector with the UHF and VHF radars, but both in the morning and evening sectors with the ESR radars, suggesting that particle precipitations may be of relevance to trigger these outflows. A third type of ion outflows has been identified showing a fast changing temperature ratio profile. When possible we checked the presence of naturally enhanced ion acoustic lines (NEIALs) during type-I ion outflows, 4 outflow events have been analyzed. We found NEIALs during 1 outflow event, suggesting that the proposed theories in the literature about the NEIAL generation mechanisms should be discussed in the future or other mechanisms are needed to fulfill the requirement of a temperature ratio less than 1

Using authentic texts for grammar exercises for a minority language

This paper presents an ATICALL (Authentic Text ICALL) system with automatic visual input enhancement activities for training complex inflection systems in a minority language. We have adapted the freely available VIEW system which was designed to automatically generate activities from any web content. Our system is based on finite state transducers (FST) and Constraint Grammar, originally built for other purposes. The paper describes ways of handling ambiguity in the target form in the exercises, and ways of handling the challenges for VIEW posed by authentic text, typical for a minority language: variations in orthography, and large proportion of nonnormative forms.</p

Rules Ruling Neural Networks – Neural vs. Rule-Based Grammar Checking for a Low Resource Language

Peer reviewe

Suoidne-varra-bleahkka-mála-bihkka-senet-dielku 'hay-blood-ink-paint-tar-mustard-stain' -Should compounds be lexicalized in NLP?

Lexicalizing compounds, in addition to treating them dynamically, is a key element in giving us idiomatic translations and detecting compound errors. We present and evaluate an e-dictionary (NDS) and a grammar checker (GramDivvun) for North Sámi. We achieve a coverage of 98% for NDSqueries and of 96% for compound error detection in GramDivvun

Revisiting geomagnetic activity at auroral latitudes: No need for regular quiet curve removal for geomagnetic activity indices based on hourly data

The main objective of our study is to determine if the regular quiet daily curve (QDC) subtraction is a necessary procedure in quantifying the irregular geomagnetic variations at auroral latitudes. We define the hourly ΔH index, the absolute hour-to-hour deviation in nT of the hourly geomagnetic horizontal component, which assigns each sample to sample deviation as geomagnetic activity without separating the ‘regular’ and ‘irregular’ parts of the daily magnetic field evolution. We demonstrate that the hourly gradient of the regular Sq variation is very small with respect to the irregular part, and a bulk of the nominal daily variation is actually part of the variation driven by solar wind and interplanetary magnetic field and traditionally classified as irregular. Therefore, attempts to subtract QDC can lead to a larger error, often caused by residual deviations between the used different mathematical and methodological tools and corresponding presumptions themselves. We show that ΔH provides the best and most consistent results at most timescales with the highest effective resolution among the studied indices. We also demonstrate that the ΔH index may equally be useful as a quick-look near real-time index of space weather, and as a long-term index derived from hourly magnetometer data for space climate studies