In today‟s fierce competitive world, entrepreneurship has taken an upswing because business owners are facing a technological challenge in which uniqueness and particularity are key elements to detour rivals. In this essence, entrepreneurs have to go by not only developing business plans but also a deep analysis of their environment.
Business plans for entrepreneurs can take different models depending on the party that will evaluate its elements based on its requirements. However, there exists a basic format that most entrepreneurs follow. Because of time constraints, business owners are urging its usefulness and so are the investors. Business plans are all about nailing down the business idea into writing and analysis, while this seems a feasible task; there are plenty of external and internal research to be set set in order to accomplish it. Within these measures in place, there exists a quick yet effective model that could carry on the thought and set the startup business into action.
The model is called business plan canvas; it is based on the CUSB model that serve both the business owner and or the investor to better catch on the business idea and understand its objectives and requirements starting by the customer, the non satisfied need, the solution, and the benefits to be offered. It is also a model that helps the potential entrepreneur to sell his thoughts in order to get some funds, counseling, and a road map to follow for his future business endeavor.
هناك عوامل عديدة تؤثر في البنية الشكلية للم ا ركز الحضرية التي تشهد تحولات وبصورة مستمرة ومع
توسع المدينة ونموها تفقد هذه الم ا ركز لمقومات بنيتها الحضرية المتكاملة بسبب تلك التحولات الحاصلة
ضمنه وبصورة ديناميكية من اضافات وتغيرات في النمط الحضري الذي يتشكل من عدة نماذج معمارية
جديدة مؤثرة ولأجل ذلك جاء البحث لايضاح اثر هذه العلاقة بين النمط الحضري والنموذج المعماري
وتحولاته في تكاملية البنية ا
This paper proposes a new methodology for improving network security by introducing an optimised hybrid intrusion detection system (IDS) framework solution as a middle layer between the end devices. It considers the difficulty of updating databases to uncover new threats that plague firewalls and detection systems, in addition to big data challenges. The proposed framework introduces a supervised network IDS based on a deep learning technique of convolutional neural networks (CNN) using the UNSW-NB15 dataset. It implements recursive feature elimination (RFE) with extreme gradient boosting (XGB) to reduce resource and time consumption. Additionally, it reduces bias toward
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