Bac kground:
Failure is the state or condition of not meeting a desirable or intended objective, and may be viewed as the opposite of success; students always have a question "Why did I get this grade. On the contrary success leads towards new sources of earning, in fact there are a lot of interacting factors play such extrinsic and extrinsic to reach success.
Objec t i ves :
To explore internal and external factors causing students failure in medical college and to reconnoiter factors improve academic performance.
Methods: A cross-sectional study, conducted in Al Kindy College of Medicine, for the period from November 8th 2012 to May 1st 2013. Formal ethical considerations were obtained about participation and methodology. A sample of 152 students were included and classified according to their year in the college, a questionnaires about students opinion, include a lot of factors in the all fields of educational process and socio-demographic linked with final outcome of the students.
Resul t s : success was more in females, fifth year (83%), student wellness (78%), practical teaching method (75%), regularity in attendees (80%), all lecture attendees (85%), 3-5 family number (78%), 6-10 studying hours (82%), and 25 reading hours weekly (100%), also result of student opinion about crowded weekly schedule (80%), daily quizzes influence (76%), comprehensive material (85%), long lecture duration (74%), headache as cause of failure (23%), consult doctors if there is health problem (88%), and internet uses (72%). These result come in consistent with international studies and researches.
Conc lus ions : applying new techniques in medical education good health monitoring can improve students' academic outcome.
ملخص البحث:
ان الله تعالى هو الذي خلق جميع المخلوقات ، والذي بيده الموت والحياة وان كل هذه المخلوقات تحتاج الى اوامر ، وهذه الاوامر الالهية وجهها الله لعبادة بوساطة انبياءه ( عليهم السلام) فكانوا هم اول المستسلمين والمنقادين لأوامره ، فجاءت الآيات الكريمة مخاطبة للأنبياء واقوامهم بشكل عام ولنبينا محمد (r) بشكل خاص.
اما عن المضمون البحثي فقد جاءت مادته مقسمة الى ثل
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Dust is a frequent contributor to health risks and changes in the climate, one of the most dangerous issues facing people today. Desertification, drought, agricultural practices, and sand and dust storms from neighboring regions bring on this issue. Deep learning (DL) long short-term memory (LSTM) based regression was a proposed solution to increase the forecasting accuracy of dust and monitoring. The proposed system has two parts to detect and monitor the dust; at the first step, the LSTM and dense layers are used to build a system using to detect the dust, while at the second step, the proposed Wireless Sensor Networks (WSN) and Internet of Things (IoT) model is used as a forecasting and monitoring model. The experiment DL system
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