215 research outputs found
Staff perceptions of patient safety culture in general surgery departments in Turkey
Background: The first step towards establishing and improving patient safety culture in hospitals is measuring patient safety culture perceptions of staff. Few studies have examined the perception of patient safety culture in general surgery departments.Objectives: The objective of this study was to evaluate patient safety culture and patient safety grade in general surgery departments and to examine the relation between the patient safety culture and the patient safety grade.Methods: This study examined patient safety culture and patient safety grades of 124 staff in seven surgery departments of a hospital in Turkey. The staff completed the hospital survey on patient safety culture and answered questions about their professionalcharacteristics. One-way ANOVA, Independent-samples t test, corrected chi-square test, multiple correspondence analysis and Eta co-efficient were used in statistical analyses.Results: The patient safety dimension of “teamwork within units” had the highest mean and percentage of positive responses. The “frequency of events reported” and “non-punitive response to errors” had the lowest means and percentages of positive responses.Participants with resident or nurse positions, < age 31 years, with < 6 years of professional experience, and 60 or more work hours/week, had significantly more negative perceptions of patient safety culture than other participants. Patient safety grades and the dimensions of “management support for patient safety” and “overall perceptions of patient safety” had significantly high Eta coefficients.Conclusion: Frequency of events reported and non-punitive responses to errors should be improved, and participants’ characteristics should be considered at improvement efforts in general surgery departments. The dimesions with low means suggest opportunitiesfor improvement.Keywords: Patient safety culture, Turkey, general surgery, multiple correspondence analysis
Improved recommendation of photo-taking locations using virtual ratings
We consider the task of collaborative recommendation of photo-taking locations. We use datasets of geotagged photos. We map their locations to a location grid using a geohashing algorithm, resulting in a user x location implicit feedback matrix. Our improvements relative to previous work are twofold. First, we create virtual ratings by spreading users' preferences to neighbouring grid locations. This makes the assumption that users have some preference for locations close to the ones in which they take their photos. These virtual ratings help overcome the discrete nature of the geohashing. Second, we normalize the implicit frequency-based ratings to a 1-5 scale using a method that has been found to be useful in music recommendation algorithms. We demonstrate the advantages of our approach with new experiments that show large increases in hit rate and related metrics
A comparison of calibrated and intent-aware recommendations
Calibrated and intent-aware recommendation are recent approaches to recommendation that have apparent similarities. Both try, to a certain extent, to cover the user's interests, as revealed by her user profile. In this paper, we compare them in detail. On two datasets, we show the extent to which intent-aware recommendations are calibrated and the extent to which calibrated recommendations are diverse. We consider two ways of defining a user's interests, one based on item features, the other based on subprofiles of the user's profile. We find that defining interests in terms of subprofiles results in highest precision and the best relevance/diversity trade-off. Along the way, we define a new version of calibrated recommendation and three new evaluation metrics
El-Keşşāf'ta Gizli İ tizāl: ez-Zemaḫşerī'nin Tefsir Mukaddimesi Üzerinden Ḫalḳu'l-Ḳur ān Tartışmaları
Hicrî 7. ve 8. yüzyıl ilmî çevrelerinde dile getirilen iddialardan biri, Mu tezile’nin geç dönem
temsilcilerinden ez-Zemaḫşerī’nin, el-Keşşāf adlı tefsirinde i tizālī fikirleri gizli bir şekilde
işlediğidir. Bu iddia, tefsir faaliyetleri içinde, ez-Zemaḫşerī’nin gizli i tizālī fikirlerini açığa
çıkarmak ya da tefsiri bu fikirlerden tecrit etmek gibi bir uğraşıyı ortaya çıkarmış; ayrıca elKeşşāf üzerine yazılan şerh ve haşiye eserlerinde, ez-Zemaḫşerī’nin i tizālī fikirleri
tartışılmıştır. Benzer bir tartışmada, ez-Zemaḫşerī’nin el-Keşşāf’ın mukaddimesinin ilk
cümlelerine Kur’an’ın yaratılmış olduğu fikrine referansla Mu tezilī öğretiyi veciz bir üslupla
yerleştirdiği iddia edilmiş; ayrıca ilk cümlede Kur’an’a atıfla ḫaleḳa fiilini kullandığı ve daha
sonra o fiili değiştirdiği rivayeti dillendirilmiştir. Bu makale, şarihlerin görüşleri üzerinden ezZemaḫşerī ve el-Keşşāf’ın mukaddimesi hakkında ileri sürülen söz konusu iddiaları tetkik
etme amacındadır
İslâm İlimler Tarihinde Muhâkemât Geleneği: Tefsir Hâşiyeleri Merkezli Bir Deneme
Although the origin of writing tafsīrs (commentaries) and hāshiyas (marginalias)
goes back to the early period of Islam, it was not widespread before the 7th century
hijra. e fact that this genre gained prevalence can be seen as the result of a number of factors. e first of these was that as the main sources of Islamic knowledge
had been written by this period, there was now a need to correctly understand
and interpret them. e second factor was the emergence of summary texts from
the Madrasah education as well as the tradition of discussing and explaining
them. And the third factor was the need to gain continuity of thought through a
main text. Another type of writing that can be considered to be part of this genre
(tafsīrs and hāshiyas) is the study of muhākamāt (adjudications), which was the
result of a search for solutions to eradicate disagreements between authors and
commentators or between commentators and hāshiya writers. In these works, the
authors arbitrate disagreements between scholars and try to determine whether
their arguments are accurate or inaccurate. Starting most probably with Avicenna’s
al-Insāf, muhākamāt writings soon became a common genre in all other Islamic
disciplines. is literature is important for the late Islamic literary tradition, allowing us to observe the dynamism and continuity of Islamic disciplines. is article
aims to examine the muhākamāt tradition in the context of three important tafsīrs,
al-Kashshāf by Zamakhsharī, Anwār al-Tanzīl by Baydāwī and al-Bahr al-Muhīt
by Abū Hayyān
Subprofile aware diversification of recommendations
A user of a recommender system is more likely to be satisfied by one or more of the recommendations if each individual recommendation is relevant to her but additionally if the set of recommendations is diverse. The most common approach to recommendation diversification uses re-ranking: the recommender system scores a set of candidate items for relevance to the user; it then re-ranks the candidates so that the subset that it will recommend achieves a balance between relevance and diversity. Ordinarily, we expect a trade-off between relevance and diversity: the diversity of the set of recommendations increases by including items that have lower relevance scores but which are different from the items already in the set. In early work, the diversity of a set of recommendations was given by an aggregate of their distances from one another, according to some semantic distance metric defined on item features such as movie genres. More recent intent-aware diversification methods formulate diversity in terms of coverage and relevance of aspects. The aspects are most commonly defined in terms of item features. By trying to ensure that the aspects of a set of recommended items cover the aspects of the items in the user’s profile, the level of diversity is more personalized. In offline experiments on pre-collected datasets, intent-aware diversification using item features as aspects sometimes defies the relevance/diversity trade-off: there are configurations in which the recommendations exhibits increases in both relevance and diversity. In this thesis, we present a new form of intent-aware diversification, which we call SPAD (Subprofile-Aware Diversification). In SPAD and its variants, the aspects are not item features; they are subprofiles of the user’s profile. We present a number of different ways to extract subprofiles from a user’s profile. None of them is defined in terms of item features. Therefore, SPAD and its variants are useful even in domains where item features are not available or are of low quality. On several pre-collected datasets from different domains (movies, music, books, social network), we compare SPAD and its variants to intent-aware methods in which aspects are item features. We also compare them to calibrated recommendations, which are related to intent-aware recommendations. We find on these datasets that SPAD and its variants suffer even less from the relevance/diversity trade-off: across all datasets, they increase both relevance and diversity for even more configurations than other approaches. Moreover, we apply SPAD to the task of automatic playlist continuation (APC), in which relevance is the main goal, not diversity. We find that, even when applied to the task of APC, SPAD increases both relevance and diversity
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