Results 91 to 100 of about 3,367,660 (262)
ABSTRACT Background and need As the WHO Global Traditional Medicine Strategy 2025–2034 encourages countries to consider integrating traditional, complementary and integrative medicine (TCIM) into health systems, there is a need to clarify the principal scientific, regulatory, ethical, and governance challenges involved. Renewed global attention to TCIM,
Abdul‐Basit Abdul‐Samed +3 more
wiley +1 more source
Classification of Arabic Documents with Five Classifier Models Using Machine Learning
Automated document classification is becoming important and highly required for many applications, particularly in light of the exponential increase of Arabic-language internet documents. Text classification is a big data issue and an essential aspect of
Esraa Najjar +2 more
doaj +1 more source
ABSTRACT The Flourishing Scale (FS) scores have demonstrated acceptable psychometric properties in general adult populations, but no previous research has validated its use among natural disaster survivors. This study examined the reliability, validity, and measurement invariance of a Mexican dialect Spanish translation of the FS in 289 Mexican ...
Scott Marshall +3 more
wiley +1 more source
Patient Centring in CT: An International Survey of Clinical Practice and Future Directions
An international survey of 321 radiographers from 43 countries found vertical mis‐centring below the CT isocentre is the most frequent positioning error. Only 34% had access to automated centring systems and 17% used them consistently. Substantial knowledge gaps exist regarding radiation dose and CT number variability, highlighting the need for ...
Yasser H. Hadi +9 more
wiley +1 more source
Teknik, Metode, dan Ideologi Penerjemahan Istilah Kuliner Nusantara ke Dalam Bahasa Arab
This study aims to describe the application of techniques, methods, and ideologies of translation in Indonesian culinary terms into Arabic. The data in this study are the lingual units of Nusantara culinary terms in Indonesian and their translations into
Hidayat Muhammad Sidiq +5 more
doaj +1 more source
Detection of Text Lines of Handwritten Arabic Manuscripts using Markov Decision Processes
In a character recognition systems, the segmentation phase is critical since the accuracy of the recognition depend strongly on it. In this paper we present an approach based on Markov Decision Processes to extract text lines from binary images of Arabic
Youssef Boulid +2 more
doaj +1 more source
A cross‐sectional survey of 1274 adults residing in Iraq found a median radiation‐related knowledge score of 5/10 and a median attitude score of 17/25. Only 18% correctly identified that MRI does not use ionizing radiation, while 36% recognized that a spiral CT scan may involve radiation equivalent to 100–800 conventional X‐rays.
Walid Al‐Qerem +5 more
wiley +1 more source
Institutional Fragility and E‐Business Adoption: A Study of SMEs in a Conflict‐Affected Economy
ABSTRACT This study examines e‐business adoption among SMEs in Yemen, a conflict‐affected and institutionally fragile economy. Drawing on a mixed‐methods design, it combines Partial Least Squares Structural Equation Modelling (PLS‐SEM) with qualitative interviews to analyse how war and firm size moderate the effects of key adoption drivers and barriers.
Ahmed Abdullah +5 more
wiley +1 more source
Abstract Forcible displacement due to war and persecution has reached unprecedented heights across the globe. The mental health impact of trauma and displacement on refugee communities is profound. Although there are several evidence‐based therapies that are efficacious in reducing symptoms of posttraumatic stress disorder and depression in refugees ...
Angela Nickerson +4 more
wiley +1 more source
Memory-based vocalization of Arabic [PDF]
The problem of vocalization, or diacritization, is essential to many tasks in Arabic NLP. Arabic is generally written without the short vowels, which leads to one written form having several pronunciations with each pronunciation carrying its own meaning(
Kübler, Sandra, Mohamed, Emad
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