An experiment was carried out in pots under open field conditions in the fall seasons of 2017 and 2018 at the College of Agricultural Engineering Sciences, University of Baghdad, for improving field emergence and drought stress tolerance in sorghum. Three factors were studied. 1st factor was three cultivars (Inqath, Rabeh and Buhoth70). 2nd factor was primed and unprimed seed. 3rd factor was represented by the irrigation intervals every 2, 4 and 6 days. Randomized complete block design with four replicates was used. The results showed that Buhoth 70 cultivar had a significant superiority compared to others in traits of the first and final count of emergence, emergence energy and emergence rate index (54.2%, 26.7%, 1.747 and 70.7 % day-1 ) and (58.8%, 22.7%, 1.677 and 7..4 % day-1 ) in both seasons, respectively. The primed seeds had a significant superiority in comparison with unprimed seeds in the same traits above (74.6%, 21.1%, 1.746 and 77.1 % day-1 ) and (64.1%, 24.4%, 1.641 and 7... % day-1 ) in both seasons, respectively. The irrigation interval every 2 days had a significant superiority compared to others in the same traits above (74.6%, 2..7%, 1.746 and 70.2 % day-1 ) and (60.6%, 2...%, 1.616 and 77.4 % day-1 ) in both seasons, respectively. The interaction effect between priming seeds (by gibberellin and salicylic acids) and irrigation intervals was significant on all studied traits. The cultivars were varied in their ability to resist drought stress, and the primed seed has improved their performance to resist drought stress in both seasons. Therefore, it can be recommended planting of primed seeds of Buhoth70 cultivar under conditions of drought stress or not.
مستخلص البحث كان الهدف من البحث هو إعداد تمرينات خاصة لتطوير مهارة التصويب بالقفز بكرة السلة للشباب، إذ لوحظ ضعفاً ملموساً ولاسيما عند فئة الشباب في إحراز النقاط في مهارة التصويب بالقفز المحسوب بنقطتين وذلك لصعوبة أداءه إذ ان المدافعين أصبحوا متمكنين من قدراتهم فضلاً عن عامل الوقت عند الأداء يكاد يكون قليل جداً عند اتخاذ القرار. وقد اعتمد الباحثان في إعداد التمرينات مبدأ التدرج من السهل إلى الصعب والتنوع في
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Artificial Neural networks (ANN) are powerful and effective tools in time-series applications. The first aim of this paper is to diagnose better and more efficient ANN models (Back Propagation, Radial Basis Function Neural networks (RBF), and Recurrent neural networks) in solving the linear and nonlinear time-series behavior. The second aim is dealing with finding accurate estimators as the convergence sometimes is stack in the local minima. It is one of the problems that can bias the test of the robustness of the ANN in time series forecasting. To determine the best or the optimal ANN models, forecast Skill (SS) employed to measure the efficiency of the performance of ANN models. The mean square error and
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