5 research outputs found

    Hypnosis in pediatrics: applications at a pediatric pulmonary center

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    BACKGROUND: This report describes the utility of hypnosis for patients who presented to a Pediatric Pulmonary Center over a 30 month period. METHODS: Hypnotherapy was offered to 303 patients from May 1, 1998 – October 31, 2000. Patients offered hypnotherapy included those thought to have pulmonary symptoms due to psychological issues, discomfort due to medications, or fear of procedures. Improvement in symptoms following hypnosis was observed by the pulmonologist for most patients with habit cough and conversion reaction. Improvement of other conditions for which hypnosis was used was gauged based on patients' subjective evaluations. RESULTS: Hypnotherapy was associated with improvement in 80% of patients with persistent asthma, chest pain/pressure, habit cough, hyperventilation, shortness of breath, sighing, and vocal cord dysfunction. When improvement was reported, in some cases symptoms resolved immediately after hypnotherapy was first employed. For the others improvement was achieved after hypnosis was used for a few weeks. No patients' symptoms worsened and no new symptoms emerged following hypnotherapy. CONCLUSIONS: Patients described in this report were unlikely to have achieved rapid improvement in their symptoms without the use of hypnotherapy. Therefore, hypnotherapy can be an important complementary therapy for patients in a pediatric practice

    ВыявлСниС источников заимствования для Π΄ΠΎΠΊΡƒΠΌΠ΅Π½Ρ‚Π° с использованиСм ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ дистрибутивной сСмантики

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    This paper is about method for identifying sources of plagiarism for a document, using a model of distributive semantics to form a set of queries to a search engine. The main ways of revealing plagiarisms and their sources are considered. It shows how to select queries from the document to search for sources using a vector space built on a large body of texts using the Word2Vec tool. The results of method's work are presented.Π’ ΡΡ‚Π°Ρ‚ΡŒΠ΅ ΠΏΡ€Π΅Π΄Π»ΠΎΠΆΠ΅Π½ ΠΌΠ΅Ρ‚ΠΎΠ΄ выявлСния источников заимствований для Π΄ΠΎΠΊΡƒΠΌΠ΅Π½Ρ‚Π°, ΠΈΡΠΏΠΎΠ»ΡŒΠ·ΡƒΡŽΡ‰ΠΈΠΉ модСль дистрибутивной сСмантики для формирования мноТСства запросов ΠΊ поисковой машинС. РассмотрСны основныС способы выявлСния заимствований ΠΈ ΠΈΡ… источников. Показано, ΠΊΠ°ΠΊ Π²Ρ‹Π΄Π΅Π»ΠΈΡ‚ΡŒ ΠΈΠ· Π΄ΠΎΠΊΡƒΠΌΠ΅Π½Ρ‚Π° запросы для поиска источников, ΠΈΡΠΏΠΎΠ»ΡŒΠ·ΡƒΡ Π²Π΅ΠΊΡ‚ΠΎΡ€Π½ΠΎΠ΅ пространство, построСнноС Π½Π° большом корпусС тСкстов ΠΏΡ€ΠΈ ΠΏΠΎΠΌΠΎΡ‰ΠΈ инструмСнта Word2Vec. ΠŸΡ€ΠΈΠ²Π΅Π΄Π΅Π½Ρ‹ Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚Ρ‹ Ρ€Π°Π±ΠΎΡ‚Ρ‹ ΠΌΠ΅Ρ‚ΠΎΠ΄Π°

    ВыявлСниС источников заимствования для Π΄ΠΎΠΊΡƒΠΌΠ΅Π½Ρ‚Π° с использованиСм ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ дистрибутивной сСмантики

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    This paper is about method for identifying sources of plagiarism for a document, using a model of distributive semantics to form a set of queries to a search engine. The main ways of revealing plagiarisms and their sources are considered. It shows how to select queries from the document to search for sources using a vector space built on a large body of texts using the Word2Vec tool. The results of method's work are presented.Π’ ΡΡ‚Π°Ρ‚ΡŒΠ΅ ΠΏΡ€Π΅Π΄Π»ΠΎΠΆΠ΅Π½ ΠΌΠ΅Ρ‚ΠΎΠ΄ выявлСния источников заимствований для Π΄ΠΎΠΊΡƒΠΌΠ΅Π½Ρ‚Π°, ΠΈΡΠΏΠΎΠ»ΡŒΠ·ΡƒΡŽΡ‰ΠΈΠΉ модСль дистрибутивной сСмантики для формирования мноТСства запросов ΠΊ поисковой машинС. РассмотрСны основныС способы выявлСния заимствований ΠΈ ΠΈΡ… источников. Показано, ΠΊΠ°ΠΊ Π²Ρ‹Π΄Π΅Π»ΠΈΡ‚ΡŒ ΠΈΠ· Π΄ΠΎΠΊΡƒΠΌΠ΅Π½Ρ‚Π° запросы для поиска источников, ΠΈΡΠΏΠΎΠ»ΡŒΠ·ΡƒΡ Π²Π΅ΠΊΡ‚ΠΎΡ€Π½ΠΎΠ΅ пространство, построСнноС Π½Π° большом корпусС тСкстов ΠΏΡ€ΠΈ ΠΏΠΎΠΌΠΎΡ‰ΠΈ инструмСнта Word2Vec. ΠŸΡ€ΠΈΠ²Π΅Π΄Π΅Π½Ρ‹ Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚Ρ‹ Ρ€Π°Π±ΠΎΡ‚Ρ‹ ΠΌΠ΅Ρ‚ΠΎΠ΄Π°
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