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NEW QUESTION: 1
Which three needs can be met with an IBM Worklight-only application approach? (Choose three.)
A. offline use
B. app store presence
C. personalization driven by IBM Web Content Manager content
D. access to mobile native features
E. authentication management
F. use of existing IBM WebSphere Portal environment
Answer: A,B,D

NEW QUESTION: 2
The specific technique for identifying a problem, discovering the causes that lead to it, and developing preventive actions is:
A. Root cause analysis
B. Use of quality checklists
C. Inspection
D. Use of matrix diagrams
Answer: A

NEW QUESTION: 3
WLANクライアントベンダー向けのどのシスコプログラムが、自社のデバイスがCisco WLANインフラストラクチャと相互運用可能であることを保証するのに役立ちますか。
A. CCMP
B. WLSE
C. CCX
D. ASDM
Answer: C
Explanation:
説明/参照：
Explanation:
IEEEおよび業界標準では、Wi-Fi無線と無線LANインフラストラクチャとの相互運用方法が定義されており、Wi-Fi CERTIFIED™シールによって相互運用性が保証されています。ただし、モバイルコンピュータに依存している多くの組織にとって、Wi-Fi CERTIFIEDだけでは不十分です。これらの組織は、モバイルコンピュータがシスコの無線LANインフラストラクチャと相互運用し、セキュリティ、モビリティ、サービス品質、およびネットワーク管理を強化するためのシスコの無線LANのイノベーションをサポートすることを保証する必要があります。シスコ互換シールは、組織が求めていることを保証します。
モバイルコンピュータは、Cisco Compatible Extensions（CCX）と呼ばれるプログラムを通じてCisco Compatibleシールを獲得します。 Wi-Fi認証プログラム、CCXのように：
CCX仕様は、Wi-Fi認証に使用されているもののスーパーセットです。実際、デバイス、またはデバイス内のWi-Fi無線がWi-Fi CERTIFIEDでない限り、デバイスはCCXの認定を受けることはできません。
http://www.digikey.com/Web%20Export/Supplier%20Content/Laird_776/PDF/laird-wireless-value-cisco-compatible-extenstion.pdf？redirected = 1

NEW QUESTION: 4
Business owners at your company have given you a database of bank transactions. Each row contains the user ID, transaction type, transaction location, and transaction amount. They ask you to investigate what type of machine learning can be applied to the data. Which three machine learning applications can you use? (Choose three.)
A. Supervised learning to predict the location of a transaction.
B. Unsupervised learning to predict the location of a transaction.
C. Reinforcement learning to predict the location of a transaction.
D. Clustering to divide the transactions into N categories based on feature similarity.
E. Unsupervised learning to determine which transactions are most likely to be fraudulent.
F. Supervised learning to determine which transactions are most likely to be fraudulent.
Answer: A,D,E
Explanation:
Fraud is not a feature, so unsupervised, location is given so supervised, Clustering can be done looking at the done with same features.