• The main purpose of conversion and validation is to ensure values have been properly sanitized before updating model data.

    转换和验证的主要目的是确保在更新模型数据之前已经经过了正确的无害处理。

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  • By placing the validation in the data instance, the model should validate itself rather than rely on the server to validate the information.

    模型将验证置于数据实例中以实现自我验证,而不是依赖服务器验证信息。

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  • The next step is to identify and model the data elements such as incoming orders, manufacturing data, and validation data.

    接下来的步骤是确定数据元素并且为其建模,比如到来的订单,生产数据和验证数据。

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  • Then, we'll show you how to utilize JSF conversion and validation to ensure that the collected data is appropriate for the model.

    然后,我们将展示如何利用jsf转换和验证确保收集的数据对于模型是适合的。

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  • Most of the data binding frameworks include a certain inherent level of validation (assuring, for instance, that the content model of elements is matched) just by their design.

    大多数数据绑定框架仅按照其设计包含某个固有的验证级别(例如,确保元素的内容模型是匹配的)。

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  • Validation: in the data model, include the routines that can validate the data that forms the instance of the data object.

    验证:在数据模型中,包含验证数据对象实例的数据的例程。

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  • If you like, you can add Ruby code to perform extra validation within an application model, enforce data relationships, or trigger other actions.

    如果您愿意,您可以添加ruby代码来在应用程序模型中执行额外的验证,加强数据关联,或者触发其他操作。

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  • Using ValidationRule keeps validation processing separate from the data model and ViewControllers.

    使用ValidationRule使验证处理同数据模型和ViewController分隔开。

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  • It makes sense, then, that conversion and validation processes happen before component data is bound to your backing bean model in the update model data lifecycle phase.

    因此,在更新模型数据生命周期阶段中,在组件数据被绑定到backingbean模型之前进行转换和验证处理是有道理的。

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  • The presentation layer can call the validation logic on the data provided by a form before passing it to the domain model.

    展示层可以调用验证逻辑对表单提供的数据进行验证,然后再将该数据传递给域模型。

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  • For the Rich Web Application Backplane, you will use an XML data model, where the model consists of the core data, validation system, constraints, and actions.

    对于RichWebApplication Backplane,您将使用XML数据模型,其中模型包括核心数据、验证系统、约束和动作。

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  • Seven rules are added in InfoSphere data Architect V7.5.3 for dimensional physical data model validation.

    在InfoSphereDataArchitectV7.5.3中添加了七个规则,均可用于多维物理数据模型验证。

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  • During execution, data is collected on the actual execution times per executable element, thus allowing validation of the real-time execution against the scheduling algorithm defined in the model.

    在执行期间,在每一个可执行元素的实际执行过程中都会收集数据,根据模型中所定义的安排规则来确认实际的执行时间。

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  • This release adds support for new SQL Server 2008 data mining features including holdout and cross-validation, a new Document Model wizard, and improvements to existing wizards.

    此版本添加了新的SQLServer 2008数据挖掘功能支持,包括维持和交叉验证、新的文档模型向导和对现有向导的改进。

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  • Once defined in partial classes like below, these validation methods will automatically be enforced anytime we write code to update our data model objects in an application.

    一旦在部分类中像如下这样添加了的话,这些验证方法将会在应用程序中更新数据模型时自动的触发。

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  • This important conclusion is difficult to get from regional studies that often use unselected data for the model validation.

    在区域性研究中因经常使用未经选择的资料作为模型确认值,因而很难获得这一重要的结论。

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  • This approach lets you perform custom validation of data fields and associate custom templates to tables or data fields in the data model.

    这个方法可让您执行资料栏位的自订验证,以及关联自订范本与资料模型中的资料表或资料栏位。

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  • Last through the model data and real data processing, validation of the methods in dealing with converted-wave residual static correction is effective.

    最后通过对模型数据和实际数据的处理,验证了方法对于处理转换波剩余静校正是有效果的。

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  • You can define valid data in the model, or you can add validation to operations that you perform on an entity or data service.

    您可以在模型中定义有效资料,也可以在实体或资料服务上执行的作业中加入验证。

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  • Shows how to customize and extend data validation in the data model.

    示范如何自订并扩充资料模型中的资料验证。

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  • Shows how to customize and extend data field validation in the data model.

    说明如何自订及扩充资料模型中的资料栏位验证。

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  • According to mass movement, self-organization and specific hub behavior comparison, experiential data, theory description and field data were used for the model verification and validation.

    应用数据对比方法,从群体行为、自组织行为与特定行为特性三个方面进行了模型验证。

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  • A validation provider provides validation logic for the data model.

    验证提供程序为数据模型提供验证逻辑。

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  • Testing results indicate that the error between calculated and tested data doesn't exceed 5%. The correctness and validation of the simulation model is demonstrated.

    实验表明,仿真结果与实验值误差不超过5%,从而验证了仿真模型的正确性和有效性。

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  • The results showed a good agreement between the isotherm determined by frontal analysis and inverse method, and the adsorption data which confirmed the validation of the model selected.

    实验结果表明:采用前沿分析法和逆向法确定的吸附等温线与吸附数据吻合很好,验证了所选模型的合理性。

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  • The validation of the model based on measured data shows that the model tallies with the actual situation.

    讨论了概化模型的两种理想过程的解,基于实测数据对解式进行了验证,结果表明概化模型是合理的。

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  • The validation with different data sets involving variety, sowing date, and nitrogen application rate showed that this model had a good predictability and practicability.

    通过不同品种氮肥处理试验建立模型,利用不同品种播期试验资料对模型进行了初步检验,表明模型具有较好的预测性和适用性。

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  • Then, the calibration and validation of TOPOG model was done using the meteorological and hydrological data measured at the outlet of the watershed in 2001 and 2002.

    然后,用祁连山排露沟小流域2001年、2002年的气象和水文数据对改进后的TOPOG模型进行率定和检验。

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  • Then, the calibration and validation of TOPOG model was done using the meteorological and hydrological data measured at the outlet of the watershed in 2001 and 2002.

    然后,用祁连山排露沟小流域2001年、2002年的气象和水文数据对改进后的TOPOG模型进行率定和检验。

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