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<article article-type="research-article" dtd-version="1.3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xml:lang="ru"><front><journal-meta><journal-id journal-id-type="publisher-id">caht</journal-id><journal-title-group><journal-title xml:lang="ru">Научный вестник МГТУ ГА</journal-title><trans-title-group xml:lang="en"><trans-title>Civil Aviation High Technologies</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">2079-0619</issn><issn pub-type="epub">2542-0119</issn><publisher><publisher-name>Moscow State Technical University of Civil Aviation (MSTU CA)</publisher-name></publisher></journal-meta><article-meta><article-id custom-type="elpub" pub-id-type="custom">caht-1085</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>Транспорт</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>Transport</subject></subj-group></article-categories><title-group><article-title>ПРИМЕНЕНИЕ ДВУХПАРАМЕТРИЧЕСКОЙ МОДЕЛИ IRT ДЛЯ ОЦЕНКИ ВЕРОЯТНОСТНЫХ ХАРАКТЕРИСТИК ОБНАРУЖЕНИЯ ЗАПРЕЩЕННЫХ ПРЕДМЕТОВ ОПЕРАТОРАМИ ДОСМОТРОВОЙ ТЕХНИКИ</article-title><trans-title-group xml:lang="en"><trans-title>TWO-PARAMETER IRT MODEL APPLICATION TO ASSESS PROBABILISTIC CHARACTERISTICS OF PROHIBITED ITEMS DETECTION BY AVIATION SECURITY SCREENERS</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Волков</surname><given-names>А. К.</given-names></name><name name-style="western" xml:lang="en"><surname>Volkov</surname><given-names>A. K.</given-names></name></name-alternatives><bio xml:lang="ru"><p>аспирант,</p><p>г. Ульяновск</p></bio><bio xml:lang="en"><p>Postgraduate Student,</p><p>Ulyanovsk</p></bio><email xlink:type="simple">oabuvauga@mail.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Айдаркин</surname><given-names>Д. В.</given-names></name><name name-style="western" xml:lang="en"><surname>Aidarkin</surname><given-names>D. V.</given-names></name></name-alternatives><bio xml:lang="ru"><p>кандидат технических наук, доцент, доцент,</p><p>г. Ульяновск</p></bio><bio xml:lang="en"><p>Candidate of Technical Sciences, Associate Professor,</p><p>Ulyanovsk</p></bio><email xlink:type="simple">aidarkin.dv@yandex.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Волков</surname><given-names>А. К.</given-names></name><name name-style="western" xml:lang="en"><surname>Volkov</surname><given-names>A. K.</given-names></name></name-alternatives><bio xml:lang="ru"><p>аспирант,</p><p>г. Ульяновск</p></bio><bio xml:lang="en"><p>Postgraduate Student,</p><p>Ulyanovsk</p></bio><email xlink:type="simple">oabuvauga@mail.ru</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>Ульяновский институт гражданской авиации</institution><country>Россия</country></aff><aff xml:lang="en"><institution>Ulyanovsk Civil Aviation Institute</institution><country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2017</year></pub-date><pub-date pub-type="epub"><day>30</day><month>06</month><year>2017</year></pub-date><volume>20</volume><issue>3</issue><fpage>100</fpage><lpage>109</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Волков А.К., Айдаркин Д.В., Волков А.К., 2017</copyright-statement><copyright-year>2017</copyright-year><copyright-holder xml:lang="ru">Волков А.К., Айдаркин Д.В., Волков А.К.</copyright-holder><copyright-holder xml:lang="en">Volkov A.K., Aidarkin D.V., Volkov A.K.</copyright-holder><license xml:lang="ru" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>Данная работа распространяется под лицензией Creative Commons Attribution 4.0.</license-p></license><license xml:lang="en" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>This work is licensed under a Creative Commons Attribution 4.0 License.</license-p></license></permissions><self-uri xlink:href="https://avia.mstuca.ru/jour/article/view/1085">https://avia.mstuca.ru/jour/article/view/1085</self-uri><abstract><p>В статье проанализированы существующие подходы к оценке эффективности деятельности операторов досмотровой техники и представлены их недостатки. Основным недостатком является сложность реализации рекомендаций ИКАО относительно учета влияния факторов сложности теневого рентгеновского изображения при подготовке и оценке эффективности обнаружения запрещенных предметов операторами. Под факторами сложности теневого рентгеновского изображения понимаются специфические свойства рентгеновского изображения, которые влияют на способность к обнаружению запрещенных предметов операторами досмотровой техники. В качестве наиболее важных факторов сложности выделяются следующие: геометрические характеристики запрещенного предмета, изменение ориентации запрещенного предмета, наложение на запрещенный предмет обычных предметов, сложность содержимого багажа или ручной клади, схожесть цветовой гаммы запрещенных и обычных предметов в багаже или ручной клади.Предложена одномерная двухпараметрическая модель IRT и соответствующий критерий подготовленности операторов. В рамках предложенной модели вероятностные характеристики обнаружения оператора рассматриваются как функции от таких параметров, как разности уровня подготовки и уровня сложности изображений, а также меры ответственности и структурированности профессиональных знаний оператора. С помощью предложенной модели можно рассматривать две характеристические функции: во-первых, характеристическую функцию уровня подготовленности, которая описывает способности оператора по интерпретации рентгеновских изображений различной трудности; во-вторых, характеристическую функцию трудности рентгеновского изображения, которая описывает возможности операторов с различным уровнем подготовки интерпретировать рентгеновское изображение определенного уровня сложности. Предложенный комплексный критерий оценки уровня подготовленности оператора позволяет оценить его профессиональную пригодность с учетом не только среднего уровня подготовленности, но и возможной его дисперсии. Важной особенностью применения логистических функций моделей IRT является необходимость предварительного отбора тестовых изображений. Тестовые изображения должны отбираться в порядке возрастания их трудности с учетом влияния различных факторов.Предложенная модель может найти применение как в области совершенствования методов подготовки операторов досмотровой техники, так и при решении задач повышения эффективности функционирования систем досмотра.</p></abstract><trans-abstract xml:lang="en"><p>The modern approaches to the aviation security screeners’ efficiency have been analyzedand, certain drawbacks have been considered. The main drawback is the complexity of ICAO recommendations implementation concerning taking into account of shadow x-ray image complexity factors during preparation and evaluation of prohibited items detection efficiency by aviation security screeners. Х-ray image based factors are the specific properties of the x-ray image that influence the ability to detect prohibited items by aviation security screeners. The most important complexity factors are: geometric characteristics of a prohibited item; view difficulty of prohibited items; superposition of prohibited items byother objects in the bag; bag content complexity; the color similarity of prohibited and usual items in the luggage.The one-dimensional two-parameter IRT model and the related criterion of aviation security screeners’ qualification have been suggested. Within the suggested model the probabilistic detection characteristics of aviation security screeners are considered as functions of such parameters as the difference between level of qualification and level of x-ray images complexity, and also between the aviation security screeners’ responsibility and structure of their professional knowledge. On the basis of the given model it is possible to consider two characteristic functions: first of all, characteristic function of qualification level which describes multi-complexity level of x-ray image interpretation competency of the aviation security screener; secondly, characteristic function of the x-ray image complexity which describes the range of x-ray image interpretation competency of the aviation security screeners having various training levels to interpret the x-ray image of a certain level of complexity. The suggested complex criterion to assess the level of the aviation security screener qualification allows to evaluate his or her competency taking into account not only the average level qualification, but its possible variance. The important feature of implementing IRT models logistic functions is the necessity of preliminary selection of test images. Test x-ray images have to be selected in the ascending order of their complexity taking into consideration the influence of various factors.The suggested model may be applied both in the field of improving of aviation security screeners’ training methods to provide screening procedures, and while solving problems of increasing the efficiency of the screening system functioning.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>вероятность обнаружения опасных предметов</kwd><kwd>оператор досмотровой техники</kwd><kwd>оценка профессиональной подготовленности</kwd><kwd>сложность рентгеновского изображения</kwd></kwd-group><kwd-group xml:lang="en"><kwd>probability of prohibited items detection</kwd><kwd>aviation security screeners</kwd><kwd>competency assessment</kwd><kwd>x-ray images complexity</kwd></kwd-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Michel S., Mendes M., de Ruiter J.C., Ger Koomen C.M., Schwaninger A. 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