We run this, and naturally, it fails.
我们运行这个，当然，它失败。
If we run this program, we get something like Figure 13.
如果运行该程序，就会得到类似图13的结果。
However, when we run this test, we do not get the outcome we expect.
然而，当我们运行这个测试类时，我们没有得到所期望的输出。
When we run this procedure from DB2 command line processor (CLP), it returns the location NEW YORK for department 10.
当我们在DB2的命令行处理器(CLP)中运行这个过程时，它对部门10会返回位置NEWYORK。
If we run this project again as outlined above, we will see that we can now navigate through Ecore and Generator EMF models (see Figure 8).
如果我按上面介绍的方法重新运行此项目，我们将发现现在可以浏览ecore和GeneratorEMF模型(见图8)。
For our example, the bodies of all the update methods just contain a print statement. When we run this example we get the following output.
为了我们的例子，所有更新方法的函数体仅包含一个打印语句。
Note that we pass this method two parameters: the value we want to replace (Scriptign) and the replacement text (Scripting). After we run this command $a will be equal to this
注意我们传递给这个方法两个参数：我们想要替换的值(Scriptign)及用来替换的文本(Scripting)。
We watched him go out on a run the first time and wondered how long this weird obsession would last.
我们看着他第一次出去跑步，想知道这种奇怪的痴迷会持续多久。
We run all day, and this makes us tired.
我们每天都会跑步，这使得我们很很累。
Prior to implementation, the customer's attitude was, "We run our business on this data."
在实现之前，客户的看法是，“我们在这些数据上运行我们的业务。”
To deploy and run this solution, we need to create an actual implementation that is consistent with the architectural and design decisions captured in the model.
为了部署和运行这个方案，我们需要创建一个实际的执行，它与模型中获取的结构性和设计决定相协调。
In the following sections, we will write some parallel programs and run them on this cluster.
在接下来的几节中，我们将编写一些并行程序，并在这个集群上运行这些并行程序。
Next we will run this application.
接下来我们将运行这个应用程序。
This is different from how we run projects, and very different from the RUP approach.
这与我们运作项目的方式截然不同，并且与RUP 方法也有着巨大的差异。
But suppose we were to run this code on the tree shown in Figure 1, where the branches are represented as circles, with their values in the center, and the leaves are represented as squares.
但是假设我们要在图1所示的树上运行这段代码，其中树的分支都用圆形表示，值在中心，叶子用正方形表示。
We need much more gas to run this type of machine.
我们需要更多的汽油来发动这一款机器。
This is why when we are inattentive, our imaginations run wild and will inevitably create many problems for us.
这就是为什么当我们不留神，我们的想象力就像脱缰的野马，不可避免地为我们带来许多问题。
So that's the only change we need to make there and watch what happens when we actually run this.
那就是我们需要改变的，并且当我们运行它，会发生什么事情。
In this section, we set up and run a scheduler to periodically discover services from Oracle Application Server.
在此部分，我们将设置并运行调度程序，以定期发现OracleApplicationServer中的服务。
This state machine will run, and we can test it using the BPC explorer.
此状态机将能够运行，我们可以使用BPCExplorer测试它。
To run this scenario, we used the same clustered configuration as in config 4 above, except that we used multiple standby servers as follows.
要运行这个场景，我们使用上面的配置4中的集群配置，但在这里我们使用多个备用服务器，如下所示。
To run this scenario, we set up a Domino cluster with three servers with the following configuration
为了运行这个场景，我们设置了一个具有3 个服务器的Domino集群，其配置如下
When we click Start this time, WEKA will run this test data set through the model we already created and let us know how the model did.
当我们这次单击Start时，WEKA将会贯穿我们已经创建的这个模型运行测试数据集并会让我们知道模型的情况。
We point this out to demonstrate how well LPARs work on the p670, and that we were able to run multiple, diverse activities on this machine and still achieve these dramatic test results.
我们指出这一点是为了说明LPAR在p 670上工作得是如此之好，以至于我们可以在这台机器上同时运行多种操作，仍然能够得出令人惊讶的测试结果。
On the schedule TAB we indicated this task was to run only once at 23:00 on May 29th, 2003, and then we clicked on add to add the task to the list of scheduled tasks.
在Schedule标签页上，我们指定该任务只能在2003年5月29日23：00运行一次，然后点击add将该任务添加到计划任务列表中。
Now we can run the application. In your favorite web browser, invoke this url.
现在我们可以运行范例应用程序。
At this point, we are ready to run the clustering algorithm.
至此，我们已经可以运行这个群集算法了。
We run really fast so they let us on the team this year.
我们跑得快，所以他们今年让我们如入队。
If we set up this script to run hourly, we should get a fairly accurate estimate of emissions.
如果我们设定这个脚本每小时运行一次，我们将能获得一个相当精确的排放量评估值。
If we set up this script to run hourly, we should get a fairly accurate estimate of emissions.
如果我们设定这个脚本每小时运行一次，我们将能获得一个相当精确的排放量评估值。
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