Bagging, also known as Bootstrap aggregating, is an ensemble learning technique that helps to improve the performance and accuracy of machine learning algorithms. It is used to deal with bias-variance trade-offs and reduces the variance of a prediction model. Bagging avoids overfitting of data and is used for both regression and classification models, specifically for decision tree algorithms.
Yinyin Liu presents a model for object detection and localization, called Fast-RCNN. She will show how to introduce a ROI pooling layer into neon, and how to add the PASCAL VOC dataset to interface with model training and inference. Lastly, Yinyin will run through a demo on how to apply the trained model to detect new objects.
Bagging, also known as Bootstrap aggregating, is an ensemble learning technique that helps to improve the performance and accuracy of machine learning algorithms. It is used to deal with bias-variance trade-offs and reduces the variance of a prediction model. Bagging avoids overfitting of data and is used for both regression and classification models, specifically for decision tree algorithms.
Yinyin Liu presents a model for object detection and localization, called Fast-RCNN. She will show how to introduce a ROI pooling layer into neon, and how to add the PASCAL VOC dataset to interface with model training and inference. Lastly, Yinyin will run through a demo on how to apply the trained model to detect new objects.
Networks community detection using artificial bee colony swarm optimizationAboul Ella Hassanien
Community structure identification in complex networks has been an important research topic in recent years. Community detection can be viewed as an optimization problem in which an objective quality function that captures the intuition of a community as a group of nodes with better internal connectivity than external connectivity is chosen to be optimized. In this work Artificial bee
colony (ABC) optimization has been used as an effective optimization technique to solve the community detection problem with the advantage that the number of
communities is automatically determined in the process. However, the algorithm performance is influenced directly by the quality function used in the optimization
process. A comparison is conducted between different popular communities’ quality measures when used as an objective function within ABC. Experiments on real life networks show the capability of the ABC to successfully find an optimized community structure based on the quality function used.
This is about Comparative Analysis of Artificial Bee Colony and Improve Cuckoo Search algorithm, a thesis work done by us. Finally it is published on February-10-2015 on IJARAI. Here you will find the basic of ABC algorithm, ICS algorithm and the comparison between them.
إنشاء الاستعلامات الإجرائية
تشرح الأقسام الثلاثة المقبلة أنواع مختلفة من الاستعلامات الإجرائية:
استعلام تكوين جدول، استعلام إلحاقي، و استعلامات التحديث و الحذف.
غالبا ما تستخدم الاستعلامات الإجرائية للمساعدة في إدارة السجلات في قاعدة
البيانات. على سبيل المثال، يمكنك استخدام استعلام تحديد لاسترداد السجلات
لجميع المنتجات المتوقفة. يمكنك استخدام-تكوين جدول أو استعلام إلحاقي لأرشفة
تلك السجلات، ثم قم بتشغيل استعلام حذف على جدول المنتجات لإزالة سجلات
لتلك المنتجات.
إدارة السجلات
يمكنك إدارة السجلات في الجداول من خلال عرض ورقة البيانات. يشرح هذا القسم كيفية إضافة, تحديث, و حذف السجلات,
و أيضا كيفية البحث, الفرز, و تصفية السجلات عندما تحتاج الى العمل مع السجلات التي تناسب معايير مخصصة.
يشرح هذا القسم أيضا كيفية إلحاق سجلات الى جدول موجود.
Protect and maintain databases
حماية و صيانة قواعد البيانات
1. ضغط و اصلاح قاعدة البيانات تساعدنا في تحسين أداء قاعدة البيانات و اصلاح الملف عند حدوث المشاكل.
2. تشفير قاعدة البيانات بتطبيق كلمة مرور لتقييد الوصول, فقط المستخدمون الذين يعرفون كلمة المرور يستطيعون الوصول الى قاعدة البيانات.
3. العمل مع النسخ الاحتياطي.
4. دمج قواعد البيانات.
5. تقسيم قاعدة البيانات و هي خطوة تطبق خصيصا للمشاركة مع عدة مستخدمين.
Web Uygulama Güvenliğinde adını sıkça duyuran, OWASP Top 10'da 1. kategoride yer alan SQL Injection zaafiyetine dair detaylı bir incelemede bulunmak istedim.