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Access to care for women reporting postnatal complications in the occupied Palestinian territory: a cross-sectional study
No full textPostnatal care is an important component of maternal health, especially for the treatment of complications
after delivery. However, only a third of women receive postnatal care in the occupied Palestinian territory (oPt). The
aim in this study was to assess the factors that contributed to women not receiving postnatal care despite the
manifestation of symptoms Poverty is an important barrier to postnatal care for women and contributes to the inequity in the
provision of services to these women. Better accessibility of postnatal care for women in the Gaza Strip might be due
to the presence of several international humanitarian agencies that provide services to people living in this region,
and the small size of the Gaza Strip increasing accessibility to clinics for women. More eff orts are needed to address
women’s health needs in the postnatal perio
Environmental study of spring water quality in the Zarqa natural reserve (Beitillu Village / West Ramallah
No full textThe attitude of Filastin Newspaper towards the "Buraq Uprising 1929" and its implications
No full textMarj Rahet battle 64 HC/684 AC : A study of narrators and historians from the second to the fourth century of Hijra
No full textتقييم شراكة القطاعين العام و الخاص لإدارة الطاقة و الحمأة في محطة مأدبا لمعالجة المياه العادمة - حالة دراسية
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Mussels wandering optimization algorithm based training of artificial neural networks for pattern classification
No full textTraining an artificial neural network (ANN) is an optimization task since it is desired to find optimal neurons‘ weight of a neural network in an iterative training process. Traditional training
algorithms have some drawbacks such as local minima and its slowness. Therefore, evolutionary algorithms are utilized to train neural networks to
overcome these issues. This research tackles the ANN training by adapting Mussels Wandering Optimization (MWO) algorithm. The proposed method tested and verified by training an ANN with well-known benchmarking problems. Two criteria used to evaluate the proposed method were overall
training time and classification accuracy. The obtained results indicate that MWO algorithm is on par or better in terms of classification accuracy and convergence training time
Informative Provenance for Repurposed Data: A Case Study using Clinical Research Data
No full textThe task repurposing of heterogeneous, distributed data for originally unintended research objectives
is a non-trivial problem because the mappings required may not be precise. A particular case is
clinical data collected for patient care being used for medical research. The fact that research
repositories will record data differently means that assumptions must be made as how to transform of
this data. Records of provenance that document how this process has taken place will enable users of
the data warehouse to utilise the data appropriately and ensure that future data added from another
source is transformed using comparable assumptions. For a provenance-based approach to be
reusable and supportable with software tools, the provenance records must use a well-defined model
of the transformation process. In this paper, we propose such a model, including a classification of
the individual ‘sub-functions’ that make up the overall transformation. This model enables
meaningful provenance data to be generated automatically. A case study is used to illustrate this
approach and an initial classification of transformations that alter the information is create