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UiPath Automation Solution Architect Professional v1.0 Exam Sample Questions (Q143-Q148):

NEW QUESTION # 143
What are the differences between rule based and model based extractions?

A. The rub-based extraction uses methods like regex extractor and form extractor on semi-structured documents while the model based extraction uses the forma Al and machine learning on documents with fixed formal
B. The rule-based extraction is used for documents with a fixed format relies on rules (like regular expressions) and templates and ensures high accuracy for already known documents The model-based extraction is used tor semi-structured documents and relies on pre-trained models (like invoices receipts purchase orders etc) as well as on custom models
C. The model-based extraction is used for documents with a fixed format, relies on regular expressions and templates and ensures high accuracy for already known documents The rule-based extraction is used for semi-structured documents and relies on pre-trained models as we" as on custom models
D. The rule-based extraction uses methods like regex extractor and forms Al. on documents with a fared format, while the model-based extraction uses the machine learning extractor on semi structured documents

Answer: B

Explanation:
The rule-based extraction and the model-based extraction are two different methods of data extraction that target different types of documents. The rule-based extraction is suitable for structured documents that have a fixed format and layout, such as forms, tax returns, or certificates. This method relies on rules (such as regular expressions) and templates (such as position or occurrence patterns) to identify and extract the data of interest from the document. The rule-based extraction ensures high accuracy and speed for already known documents, but it requires manual configuration and maintenance of the rules and templates, and it cannot handle variations or changes in the document format. The model-based extraction is suitable for semi-structured documents that have varying formats and layouts, but contain similar types of information, such as invoices, receipts, or purchase orders. This method relies on pre-trained models (such as machine learning or artificial intelligence models) or custom models (such as user-defined models) to analyze and extract the data of interest from the document. The model-based extraction can handle variations and changes in the document format, and it can learn from feedback and improve over time, but it requires training data and validation, and it may not achieve the same level of accuracy and speed as the rule-based extraction for some documents. Reference:
Data Extraction Overview - UiPath Document Understanding
Document Processing with Improved Data Extraction | UiPath
Document Understanding - Machine Learning Extractor - UiPath

NEW QUESTION # 144
Which feature of UiPath Apps allows a user to create forms and components for user interfaces in applications?

A. Data Service
B. UiPath Studio
C. UiPath Orchestrator
D. App Builder

Answer: D

Explanation:
According to the UiPath documentation1, App Builder is a feature of UiPath Apps that allows a user to create forms and components for user interfaces in applications. App Builder is a low-code app development tool that enables users to design and publish custom apps using drag-and-drop controls, data bindings, conditional logic, and automation workflows. App Builder also provides a preview mode to test the app functionality and appearance before publishing. Users can create apps for various form factors and devices, such as desktop, mobile, web, or sidebar. App Builder also integrates with UiPath Studio, UiPath Orchestrator, and Data Service to leverage the power of automation and data management in the apps. Reference: 1: App Builder - UiPath Documentation Portal

NEW QUESTION # 145
How can the following situation be efficiency addressed?
A user receives a daily input file containing several items, which must be processed using the ACME application.
However, the processing should occur three days after obtaining the input file, not on the day the input file is provided.

A. Add the items in Orchestrator three days later after receiving the input file.
B. Add the items in Orchestrator Queue on the same day the input file was received and when getting one item from Orchestrator Queue check when it was added.
C. Add the items in Orchestrator Queue on the same day the input file was received and specify a postpone date for each item
D. Use Redis instead or Orchestrator Queue for this scenario.

Answer: C

Explanation:
According to the UiPath documentation, the postpone date is a property of the queue item that specifies the date and time when the item becomes available for processing1. This can be used to delay the execution of a queue item until a certain condition is met, such as a specific date or a dependency on another process2. By adding the items in Orchestrator Queue on the same day the input file was received and specifying a postpone date for each item, the user can ensure that the items will be processed using the ACME application only after three days, without having to check the date of each item or use a different queue system.
References:
Queues and Transactions - UiPath Documentation Portal1
How to get postponed date of queue item - Orchestrator - UiPath Community Forum3

NEW QUESTION # 146
Which of the following is true about long-running workflow?

A. There is a limit actions a job can wait for at a time.
B. Persistence points (Wait and Resume activities) can be used within the body of a Each activity.
C. Long-running activities (Walt and Resume activities) can be used in any workflow inside the solution.
D. All variables used in the scope of a long-running activity must be serializable.

Answer: D

Explanation:
A long-running workflow is a type of automation process that requires logical fragmentation or human intervention, such as invoice processing or performance reviews1. Long-running workflows are designed as Orchestration Processes in Studio, using the Persistence and Intelligent.OCR package2. This package contains activities that enable the workflow to suspend and resume execution based on certain conditions, such as waiting for a job, a queue item, a form task, or an external task to be completed1. These activities are called persistence points, and they create checkpoints in the workflow where the process state is saved and restored2. In order for the persistence points to work properly, all the variables used in the scope of a long-running activity must be serializable, meaning that they can be converted into a format that can be stored and retrieved3. Non-serializable variables, such as browser or application objects, cannot be used in long-running workflows, as they would cause errors or inconsistencies3.

NEW QUESTION # 147
Which package needs to be installed in order for the Taxonomy Manager wizard to appear in the top ribbon of the UiPath Studio?

A. UiPath.Documentunderstanding.ML.Activities package
B. UiPath.OCR.Activities package
C. UiPath.MLServices.Activities package
D. UiPath.IntelligentOCR.Activities package

Answer: D

Explanation:
The Taxonomy Manager wizard in UiPath Studio appears when the UiPath.IntelligentOCR.Activities package is installed. This package is part of UiPath's Document Understanding framework, which allows developers to define, manage, and categorize document fields and types. The Taxonomy Manager is a crucial tool in this process, enabling the creation and editing of taxonomy for document classification and data extraction tasks. Installing this package enables the Taxonomy Manager feature in the Studio ribbon, facilitating the development of document processing workflows.
Reference:
UiPath Document Understanding Guide: Taxonomy Manager
UiPath Marketplace: IntelligentOCR Activities

NEW QUESTION # 148
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