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NEW QUESTION: 1
あなたはCisco ASA9.0ファイアウォールの管理者であり、ファイアウォール管理者のActive DirectoryグループがASAの設定へのフルアクセス権を持っていることを保証する任務があります。ファイアウォール演算子Active Directoryグループはアクセスのより限定されたレベルを持つ必要があります。
どのステートメントはこれらのアクセスレベルを設定する方法を説明しますか。
A. 特権レベル15のアクセス権を持つようにファイアウォール管理者グループを設定するには、Ciscoディレクトリエージェントを使用します。また、特権レベル6のアクセス権を持つようにファイアウォールOperatorsグループを構成します。
B. AAAサーバとしてのACSによって、Cisco ASA CLIに認証と認可のためのTACACS+を使用します。 ファイアウォールOperatorsグループはACS CLIコマンド許可セットを構成します。レベル15のアクセスをファイアウォール管理者グループのメンバーに割り当てられるように構成します。
C. AAAサーバとしてACSによって、Cisco ASA CLIに認証と認可のためのRADIUSを使用します。ファイアウォールOperatorsグループはACS CLIコマンド許可セットを構成します。レベル15のアクセスをファイアウォール管理者グループのメンバーに割り当てられるように構成します。
D. Active DirectoryグループのメンバーシップはCisco ASA CLIにアクセスするための決定要因として使用することはできません。
Answer: B
NEW QUESTION: 2
A bank is developing a loan application system with business rules. An application developer adds a ruleset parameter loanReport of type LoanReport which contains the ?valid? attribute. The application developer needs to initialize the ruleset parameter ?loanReport? and set default value of the valid attribute to ?true? with ILOG Rule Language (IRL) code. How should the application developer do this?
A. Set the default value of the loanReport parameter to: new LoanReport(valid=true)
B. Add an Action task node in the ruleflow, and enter the IRL code to set the default value.
C. In the transition that links Start node to the first rule task, enter the IRL code to set the default value.
D. Add a rule task node in the ruleflow and in its Initial Action section enter Business Action Language (BAL) and edit the IRL translation.
Answer: B
NEW QUESTION: 3
ストリーミングデータを分析するAPIパイプラインを構築する必要があります。パイプラインは次を実行します。
*視覚的なテキスト認識
*音声転写
* 感情分析
* 顔検出
どのAzure Cognitive Servicesをパイプラインで使用する必要がありますか？
A. カスタム音声サービス
B. ビデオインデクサー
C. テキスト分析
D. Face API
Answer: B
Explanation:
Explanation
Azure Video Indexer is a cloud application built on Azure Media Analytics, Azure Search, Cognitive Services (such as the Face API, Microsoft Translator, the Computer Vision API, and Custom Speech Service). It enables you to extract the insights from your videos using Video Indexer video and audio models described below:
Visual text recognition (OCR): Extracts text that is visually displayed in the video.
Audio transcription: Converts speech to text in 12 languages and allows extensions.
Sentiment analysis: Identifies positive, negative, and neutral sentiments from speech and visual text.
Face detection: Detects and groups faces appearing in the video.
References:
https://docs.microsoft.com/en-us/azure/media-services/video-indexer/video-indexer-overview
Topic 1, Contoso Case Study: 1
Overview
Contoso. Ltd. has an office in New York to serve its North American customers and an office in Paris to serve its European customers.
Existing Environment
Contoso. Ltd. has an office in New York to serve its North American customers and an office in Paris to serve its European customers.
Infrastructure
Each office has a small data center that hosts Active Directory services and a few off-the-shelf software solutions used by internal users.
The network contains a single Active Directory forest that contains a single domain named contoso.com.
Azure Active Directory (Azure AD) Connect is used to extend identity management to Azure.
The company has an Azure subscription. Each office has an Azure ExpressRoute connection to the subscription. The New York office connects to a virtual network hosted in the US East 2 Azure region. The Paris office connects to a virtual network hosted in the West Europe Azure region.
The New York office has an Azure Stack Development Kit (ASDK) deployment that is used for development and testing.
Current Business Model
Contoso has a web app named Bookings hosted in an App Service Environment (ASE). The ASE is in the virtual network in the East US 2 region. Contoso employees and customers use Bookings to reserve hotel rooms.
Data Environment
Bookings connects to a Microsoft SQL Server database named hotelDB in the New York office.
The database has a view named vwAvailability that consolidates columns from three tables named Hotels, Rooms, and RoomAvailability. The database contains data that was collected during the last 20 years.
Problem Statements
Contoso identifies the following issues with its current business model:
* European users report that access to Bookings is slow, and they lose customers who must wait on the phone while they search for available rooms.
* Users report that Bookings was unavailable during an outage in the New York data center for more than 24 hours.
Requirements
Contoso identifies the following issues with its current business model:
*European users report that access to Bookings is slow, and they lose customers who must wait on the phone while they search for available rooms.
Business Goals
*Users report that Bookings was unavailable during an outage in the New York data center for more than 24 hours.
Contoso wants to provide a new version of the Bookings app that will provide a highly available, reliable service for booking travel packages by interacting with a chatbot named Butler.
Contoso plans to move all production workloads to the cloud.
Technical Requirements
Contoso identifies the following technical requirements:
*Data scientists must test Butler by using ASDK.
*Whenever possible, solutions must minimize costs.
*Butler must greet users by name when they first connect.
*Butler must be able to handle up to 10.000 messages a day.
*Butler must recognize the users' intent based on basic utterances.
*All configurations to the Azure Bot Service must be logged centrally.
*Whenever possible, solutions must use the principle of least privilege.
*Internal users must be able to access Butler by using Microsoft Skype for Business.
*The new Bookings app must provide a user interface where users can interact with Butler.
*Users in an Azure AD group named KeyManagers must be able to manage keys for all Azure Cognitive Services.
*Butler must provide users with the ability to reserve a room, cancel a reservation, and view existing reservations.
*The new Bookings app must be available to users in North America and Europe if a single data center or Azure region fails.
*For continuous improvement, you must be able to test Butler by sending sample utterances and comparing the chatbot's responses to the actua intent.
NEW QUESTION: 4
:Which of the following can you use to create a router interface?
A. Create a VLAN and enable loopback mode.
B. Create a VLAN and assign ports to it.
C. None of these.
D. Create a VLAN, assign ports to it, and assign an IPX net ID.
Answer: D