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61. Al-Saff/Firm Ranks

61. Al-Saff/Firm Ranks

I/We begin by the Blessed Name of Allah

The Immensely Merciful to all, The Infinitely Compassionate to everyone.

61:01
a. Whatever is within the celestial realm and within the terrestrial world is Glorifying Allah
– The One and Only God,
b. for HE is The Almighty, The All-Wise.

61:02
a. O The Faithful!
b. Why do you say things that you do not do as well as you will not do?

61:03
a. It is severely hateful and most despicable with Allah that you say things and then do not do
them.

61:04
a. Surely, Allah loves those brave men who fight for HIS Cause,
b. ranged in firm ranks and full formations as if they were one well-compacted solid structure.

61:05
a. And remember when Moses said to his people:
b. ‘O My Community People!
c. Why do you hurt me by belying my Mission and my Message, while you know well that I am Allah’s Messenger’ assigned to you?
d. But when they deviated from the Path of Allah, Allah made their hearts deviate from HIS Path.
e. And Allah does not guide a people who have chosen to be misguided and are defiantly
disobedient.

61:06
a. And remember when Jesus, son of Mary, proclaimed:
b. ‘O Descendants of Jacob!
c. I am a Messenger of Allah assigned to you,
d. confirming the Message of the Torah, sent before me to Moses, and bringing good news of a Messenger to come after me, whose name will be Ahmed’ - most praised.
e. Yet when he – Ahmed/Muhammad – came to them with clear proofs of his Divine Mission,...

الدور الوسيط للإبداع الإداري في العلاقة بين التسويق الإلكتروني وجودة الخدمات المصرفية على البنوك التجارية العاملة بالمملكة العربية السعودية (الراجحي، العربي، ساب)

هدفت الدراسة إلى التعرف على الدور الوسيط للإبداع الإداري في العلاقة بين التسويق الإلكتروني وجودة الخدمات المصرفية على البنوك التجارية العاملة بالمملكة العربية السعودية (الراجحي، العربي، ساب). وتمثلت مشكلة الدراسة في السؤال الرئيس التالي: هل الإبداع الإداري يتوسط العلاقة بين التسويق الإلكتروني وجودة الخدمات المصرفية بالبنوك التجارية العاملة بالمملكة العربية السعودية (الراجحي، العربي، ساب) ؟ استخدم المنهج الوصفي، تم استخدام اسلوب الحصر الشامل، وصممت استبانة لجمع البيانات، تم بناء نموذج الدراسة وفرضياته اعتماداً على أدبيات الدارسة. تم توزيع عدد 205 استبانة، حيث بلغت نسبة البيانات الصالحة للتحليل 100%. وكذلك تم الاعتماد على نمذجة المعادلة البنائية (SEM) وفيها استخدم برنامج Amos)) وتم استخدام اختبار ألفا كرونباخ للاعتمادية واستخدام أسلوب تحليل المسار لاختبار فرضيات الدارسة. توصلت الدراسة الي وجود توسط جزئي للإبداع الإداري في العلاقة بين التسويق الإلكتروني وجودة الخدمات المصرفية. اوصت الدراسة بان على المصارف التجارية الاهتمام بالإبداع الإداري ودعم العاملين لتقديم الأفكار الجديدة وتطوير العمل بتلقائية ويسر. وضرورة ان تقدم المصارف خدمات مصرفية ترضى العملاء. الكلمات المفتاحية: التسويق الإلكتروني، الترويج، الإبداع الإداري، المصارف.

A Framework for Software Defect Prediction Using Ensemble Learning

The development of high-quality software at lower cost has always been the main concern of the developers as well as of the users. Eliminating the defects in software at the initial development stage can increase quality and reduce the overall cost. Testing only those modules which are likely to be defective are helpful for development team to manage and use resources effectively. Many machine learning-based frameworks have been proposed for the prediction of software defects in initial development stage however accuracy evaluation of proposed techniques on benchmark datasets was lacked. In this research, we proposed a framework for the prediction of software defects using ensemble learning and feature selection techniques by using WEKA. The accuracy of the proposed model has been evaluated by using publicly available cleaned NASA datasets. Moreover, the results have been compared with the widely used advanced classification techniques. The Proposed framework consists of five stages. First stage is dealing with the extraction of relevant dataset. Second stage is dealing with variants of base classifiers and selection. The base classifiers include: ?Decision Tree (DT), K-nearest neighbor (kNN), Naive Bayes (NB), Random forest (RF) and Support Vector Machine (SVM)?. Pre-processing and feature selection have been done in third stage. In fourth stage, we used stacking technique to create an ensemble of the classifier-variants, which have performed well in third stage. Fifth stage deals with the results and performance evaluation by using different measures including: ?Precision, Recall, F-measure, Accuracy, MCC and ROC?.
Asian Research Index Whatsapp Chanel
Asian Research Index Whatsapp Chanel

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