Objective: determine the effectiveness of an education program on youth's level of awareness towards
household waste control.
Methodology: A Quazi-experimental study was conducted. Non-probability (quota sample) of (80) young
persons is selected from Baghdad Governorate. They are divided into two equal groups of (40) subjects for the
study group which is exposed to the household waste control educational program. The remaining is the
control group which is not exposed to the educational program.
Results: The findings of the study indicated that youth of the study group have got benefits from the
implementation of the educational program towards household waste control and change has occurred to
their awareness towards such control.
Recommendations: The study recommends that the role of television upon youth's awareness can be
activated through presenting the household waste control educational program which may facilitate to bring
the information for long distance area and increase wide-range awareness of youth.
في هذا العصر - الذي داهمت في الأخطار لغة الفصاحة والبيان - يبقى القرآن الكريم أعظم حافظ للغة السليمة ، وأكبر معين لأهلها للحفاظ على ثرائها وبلاغتها ، فهي باقية ببقائه ما بقي الليل والنهار .
وهذا البحث يدور حول حفظ القرآن الكريم وأثره على لغة الطفل، ويتكون من مقدمة : وفيها بيان أهمية الموضوع ، وخطة البحث ، ومنهجه، وثلاثة مباحث:
المبحث الأول : فضل حفظ القرآن الكريم ، وفوائد حفظه إجمالاً ، والمبحث الثاني :
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Prediction of daily rainfall is important for flood forecasting, reservoir operation, and many other hydrological applications. The artificial intelligence (AI) algorithm is generally used for stochastic forecasting rainfall which is not capable to simulate unseen extreme rainfall events which become common due to climate change. A new model is developed in this study for prediction of daily rainfall for different lead times based on sea level pressure (SLP) which is physically related to rainfall on land and thus able to predict unseen rainfall events. Daily rainfall of east coast of Peninsular Malaysia (PM) was predicted using SLP data over the climate domain. Five advanced AI algorithms such as extreme learning machine (ELM), Bay
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