Data Mining in Promoting Flight Safety

The incredible rapid development to huge volumes of air travel, mainly because of jet airliners that appeared to the sky in the 1950s, created the need for systematic research for aviation safety and collecting data about air traffic. The structured data can be analysed easily using queries from databases and running theseresults through graphic tools. However, in analysing narratives that often give more accurate information about the case, mining tools are needed. The analysis of textual data with computers has not been possible until data mining tools have been developed. Their use, at least among aviation, is still at a moderate level. The research aims at discovering lethal trends in the flight safety reports. The narratives of 1,200 flight safety reports from years 1994 – 1996 in Finnish were processed with three text mining tools. One of them was totally language independent, the other had a specific configuration for Finnish and the third originally created for English, but encouraging results had been achieved with Spanish and that is why a Finnish test was undertaken, too. The global rate of accidents is stabilising and the situation can now be regarded as satisfactory, but because of the growth in air traffic, the absolute number of fatal accidents per year might increase, if the flight safety will not be improved. The collection of data and reporting systems have reached their top level. The focal point in increasing the flight safety is analysis. The air traffic has generally been forecasted to grow 5 – 6 per cent annually over the next two decades. During this period, the global air travel will probably double also with relatively conservative expectations of economic growth. This development makes the airline management confront growing pressure due to increasing competition, signify cant rise in fuel prices and the need to reduce the incident rate due to expected growth in air traffic volumes. All this emphasises the urgent need for new tools and methods. All systems provided encouraging results, as well as proved challenges still to be won. Flight safety can be improved through the development and utilisation of sophisticated analysis tools and methods, like data mining, using its results supporting the decision process of the executives.Lentoliikenne kasvoi huomattavasti 1950-luvulla pääasiassa suihkumatkustajakoneiden myötä, mikä aiheutti poikkeamatietojen järjestelmällisen keräämisen ja tutkimuksen tarpeen. Määrämuotoinen tieto voidaan helposti analysoida tietokantakyselyillä esittäen tulokset käyttäen graafisia työkaluja, mutta tekstianalyysiin, jonka avulla tapauksista saadaan usein tarkempia tietoja, tarvitaan louhintatyökaluja. Tekstimuotoisen tiedon automaattinen analysointi ei ole ollut mahdollista ennen louhintatyökalujen kehittämistä. Silti niiden käyttö, ainakin ilmailun piirissä, on edelleen vähäistä. Tutkimuksen tarkoituksena oli havaita vaarallisia kehityskulkuja lentoturvallisuusraporteissa. 1 200 lentoturvallisuusraportin selostusosiot vuosilta 1994 –1996 käsiteltiin kolmella tekstinlouhintatyökalulla. Yksi näistä oli täysin kieliriippumaton, toisessa oli lisäosa, jossa oli mahdollisuus käsitellä suomen kieltä ja kolmas oli rakennettu alun perin ainoastaan englanninkielisen tekstin louhintaan, mutta espanjan kielellä saavutettujen rohkaisevien tulosten pohjalta päätettiin kokeilla myös suomenkielistä tekstiä. Lento-onnettomuuksien määrä liikenteeseen nähden on vakiintumassa maailmanlaajuisesti katsottuna ja turvallisuustaso voidaan katsoa tyydyttäväksi. Kuitenkin liikenteen kasvaessa myös onnettomuuksien määrä lisääntyy vuosittain, mikäli lentoturvallisuutta ei kyetä parantamaan. Turvallisuustiedon kerääminen ja raportointijärjestelmät ovat jo saavuttaneet huippunsa. Analysoinnin parantaminen on avain lentoturvallisuuden parantamiseen. Lentoliikenteen on ennustettu kasvavan 5 – 6 prosenttia vuodessa seuraavien kahden vuosikymmenen ajan. Samana aikana lentoliikenne saattaa kaksinkertaistua jopa vaatimattomimpien talouskasvuennusteiden mukaan. Tällainen kehitys asettaa lentoliikenteen päättäjille yhä kasvavia paineita kiristyvän kilpailun, polttoaineiden hinnannousun ja liikenteen kasvun aiheuttaman onnettomuuksien määrän vähentämiseksi. Tämä korostaa uusien menetelmien ja työkalujen kiireellistä tarvetta. Kaikilla louhintajärjestelmillä saatiin rohkaisevia tuloksia mutta ne nostivat samalla esille haasteita, jotka tulisi vielä voittaa. Lentoturvallisuutta voidaan vielä parantaa käyttämällä tässä esille tuotuja analyysimenetelmiä ja –työkaluja kuten tiedonlouhintaa ja soveltamalla näin saatuja tuloksia johdon päätöksenteon tukena.Siirretty Doriast

Natural Language Processing for aviation safety reports: from classification to interactive analysis

International audienceIn this paper we describe the different NLP techniques designed and used in collaboration between the CLLE-ERSS research laboratory and the CFH / Safety Data company to manage and analyse aviation incident reports. These reports are written every time anything abnormal occurs during a civil air flight. Although most of them relate routine problems, they are a valuable source of information about possible sources of greater danger. These texts are written in plain language, show a wide range of linguistic variation (telegraphic style overcrowded by acronyms or standard prose) and exist in different languages, even for a single company/country (although our main focus is on English and French). In addition to their variety, their sheer quantity (e.g. 600/month for a large airline company) clearly requires the use of advanced NLP and text mining techniques in order to extract useful information from them. Although this context and objectives seem to indicate that standard NLP techniques can be applied in a straightforward manner, innovative techniques are required to handle the specifics of aviation report text and the complex classification systems. We present several tools that aim at a better access to this data (classification and information retrieval), and help aviation safety experts in their analyses (data/text mining and interactive analysis). Some of these tools are currently in test or in use both at the national and international levels, by airline companies as well as by regulation authorities (DGAC, EASA , ICAO)

Differentiating Legislative from Nonlegislative Rules: An Empirical and Qualitative Analysis

The elusive distinction between legislative rules and nonlegislative rules has frustrated courts, motivated voluminous scholarly debate, and ushered in a flood of litigation against administrative agencies. In the absence of U.S. Supreme Court guidance on the proper demarcating line, circuit courts have adopted various tests to ascertain a rule’s proper classification. This Note analyzes all 241 cases in which a circuit court has used one or more of the enunciated tests to differentiate legislative from nonlegislative rules. These opinions come from every one of the thirteen circuits and span the period of the early 1950s through 2018. This Note identifies six different tests that courts have employed in this effort and offers a qualitative and empirical analysis of each. The qualitative analysis explains the underlying premise of the tests, articulates their merits and shortcomings, and considers how courts have applied them to particular disputes. The empirical portion of this Note uses regression analysis to ascertain how using or rejecting one or more of the tests affects a court’s determination of whether the rule is legislative or nonlegislative. This Note classifies the different tests into two categories: public-focused tests and agency-focused tests. These two categories are defined by a principle that permeates administrative law jurisprudence: achieving a proper balance between efficient agency rulemaking and maintaining a proper check against unconstrained agency action. These two categories thus defined, this Note proposes a balanced approach that incorporates elements of both categories to identify and refine the proper test

Free and inexpensive teaching materials for industrial arts courses

Thesis (Ed.M.)--Boston Universit

Special Libraries, May-June 1945

Volume 36, Issue 5https://scholarworks.sjsu.edu/sla_sl_1945/1004/thumbnail.jp