还有两天这周就结束了 ，也就是该离开glu的日子了，概括一下在glu工作的这段时间，两个字形容就是辛苦，做了很多事情，对于自己来说应该是很丰富的一段工作经历，至于为什么要离开，很多理由吧，冲动过了，纠结过了，还是要继续往前看哇。过来glu的这一年多，就像个吃不饱的娃，骨子里却又较劲的要死，做了很多工作，其实还想继续做更多，但是是时候休息一下，给自己充充电了，适当的调节可能才能走得更远，看过一篇文章讲为什么不需要职业规划，也是以后的事情谁知道，计划赶不上变化，但是控制不住的想很多规划很多，工作在哪里都是一样的干，只是要放下自己的title，离开这个一点点建立起来的团队，有些舍不得，默默的希望每个人都能有更好的发展吧。

    于是过了这周我就是个彻彻底地的自由人了，终于可以好好的睡两天了，学校的课也结束了，炫耀一下原来可以重新拥有暑假的幸福，其实这段假期要做什么早已经被排满了，太多想做的事情终于盼来了时间，怎么能再错过。ok，生活还是要继续的～～～

 留个图吧 纪念一下从2008-11-19 至 2010-07-23 的glu生活。

 

这篇文章看过很多次了，有需求的时候反复看还是很有必要的

 

 

太阳的东升西落，地球运行的轨道，潮起潮落，月亮的阴阳圆缺，春夏秋冬的更替，一切都是那么的有规律。其实在人类的心灵里也存在着许多规律，然而却很少有人了解它们。以下是十四项心理定律，你可以应用它们在任何的领域里。无论是销售沟通、还是设立目标、时间管理、领导组织都可以应用这些原理和定律。-psytopic.com

    1、坚信定律

    当你对某件事情抱着百分之一万的相信，它最后就会变成事实。

    2、期望定律

    期望定律告诉我们，当我们怀着对某件事情非常强烈期望的时候，我们所期望的事物就会出现。

    3、情绪定律

    情绪定律告诉我们，人百分之百是情绪化的。即使有人说某人很理性，其实当这个人很有“理性”地思考问题的时候，也是受到他当时情绪状态的影响，“理性地思考”本身也是一种情绪状态。所以人百分之百是情绪化的动物，而且任何时候的决定都是情绪化的决定。

    4、因果定律

    任何事情的发生，都有其必然的原因。有因才有果。换句话说，当你看到任何现象的时候，你不用觉得不可理解或者奇怪，因为任何事情的发生都必有其原因。你今天的现状结果是你过去种下的因导致的结果。

    5、吸引定律

    当你的思想专注在某一领域的时候，跟这个领域相关的人、事、物就会被你吸引而来。

    6、重复定律

    任何的行为和思维，只要你不断的重复就会得到不断的加强。在你的潜意识当中，只要你能够不断地重复一些人、事、物，它们都会在潜意识里变成事实。

    7、累积定律

    很多年轻人都曾梦想做一番大事业，其实天下并没有什么大事可做，有的只是小事。一件一件小事累积起来就形成了大事。任何大成就或者大灾难都是累积的结果。

    8、辐射定律
    当你做一件事情的时候，影响的并不只是这件事情的本身，它还会辐射到相关的其他领域。任何事情都有辐射作用。

    9、相关定律

    相关定律告诉我们：这个世界上的每一件事情之间都有一定的联系，没有一件事情是完全独立的。要解决某个难题最好从其他相关的某个地方人手，而不只是专注在一个困难点上。

    在加拿大艾伯塔省有一名高中女生最近发出豪言壮语：到25岁，她一定会成为百万富翁！她近日接到美国收视率极高的奥普拉电视台的邀请，将到该台的脱口秀节目上与观众分享她的致富理念和经验。

    现年17岁的斯考吉从小就看比尔·盖兹的书，并研究《财富》杂志每年所列全球最富有的100个人，发现其中有95%以上的人从小就有发财的欲望，57%的全球巨富在16岁之前就想到了开自己的公司，3%的全球巨富在未成年之前已做过至少一桩生意。她得出结论：要想致富，就必须从小有赚钱的意识。

    小斯考吉在股票投资上有一个小经验，例如斯考吉专盯一家钢铁企业的股票。当这家企业股票下跌到每股四美元以下时，某证券营业点门口的摩托车就会很多，过一段时间股价就会涨回去。等这家股票涨至每股八美元左右时，该营业点门口的摩托车又会多起来，接下去，该股票必跌。她经过调查发现，工人们不愿意看到该厂股票下跌，每次股价较低时，都来自发地买进一些股票，从而带动整个股价上升；等到升至一定高位，工人们又抛售股票，致使该股股价回落。摩托车是工人们往返证券营业点的工具。于是，斯考吉只要根据营业点门口的摩托车数量就能决定买进或抛售了。

    亲爱的各位朋友，你明白了吗？小斯考吉给我们做了一个有趣的相关定律的例证。

    10、专精定律

    专精定律告诉我们，只有专精在一个领域，这个领域才能有所发展。所以无论你做任何的行业都要把做该行业的最顶尖为目标，只有当你能够专精的时候，你所做的领域才会出类拔萃地成长。

    11、替换定律

    替换定律就是说，当我们有一项不想要的记忆或者是负面的习惯，我们是无法完全去除掉，只能用一种新的记忆或新的习惯去替换他。

    12、惯性定律

    任何事情只要你能够持续不断去加强它，它终究会变成一种习惯。

    13、显现定律

    显现定律就是说，当我们持续寻找、追问答案的时候，它们最终都必将显现。

    14、需求定律

    任何人做任何事情都是带有一种需求。尊重并满足对方的需求，别人才会尊重我们的需求。

来源：世界经理人

 

 

      周末上课刚学的一个用法，在我看来用在这里刚刚好，是不是每到一个周期，很多事情就要变动一下？好多事情想不清楚，好多事情担心会朝自己预想的发站，担心是没有任何抵抗力的，虽然很多事情都想到了，并不是没有准备，但每每事情按照自己的预期发展的时候，无奈无法避免，也许还掺杂着一些失落。不想写太多的文字，总觉得以后看到的时候或多或少也是会困扰的，就到这里吧。

 

 

 

 

 

 

 

 

 

 

今年需要达成的内容：

1）背会新概念3，4册课文

2）通过GCT考试

3）学习flash制作

 

Definition of quality

    Before we can measure quality, we need to understand and define what quality is exactly. Quality is commonly interpreted as something that can be judged but not measured and as indefinable because quality means many different things to many different people. Such a vague understanding of the concept quality obviously could not be helpful to professionals attempting to quantify it. Therefore, the workable definition of quality was created as the conformance of a product to the customers’ requirements.

^Top^

Measurement theory

    Scientific advancement is made through the observation of data resulting in new theories and affirmation or refutation of these theories based upon new data, thus making measurement of that data crucial to scientific progress.

    The first component of a measurement is it scale, the four levels of scales are nominal scale, ordinal scale, interval scale, and ratio scale.

    Nominal scale classifies or categorizes the attribute being measured. An example of this would be the classifications male and female. The nominal scale doesn’t allow for comparisons to be made or mathematical operations to be preformed. So the expression male > female or male < female are invalid. As well, it is impossible to subtract a female from a male. The key requirement of the nominal scale is that each data item can fit into only one category.

    Ordinal scale is vary similar to the nominal scale except categories can be ordered and comparisons can be made. An example of this would be customer satisfaction surveys which often require an answer of completely dissatisfied, somewhat dissatisfied, neutral, somewhat satisfied, or completely satisfied. In such a case, there is a natural order to the scale unlike nominal scales. However like nominal scales mathematical operations still can’t be performed.

    Interval scale indicates exact differences between measurement points unlike the previous two scales. Only the mathematical operations add and subtract can be applied to an interval scale because the zero point on the scale has been arbitrarily decided upon. For example the temperature 20 degrees is hotter than 10 degrees but 20 degrees may not be twice as hot as 10 degrees. The key requirement of the interval scale is that units be clearly defined.

    Ratio scale is the highest level of measurement much the same as interval scales except zero is a non-arbitrary point allowing mathematical operations such as division. Examples of ratio scale measurements are weight and length.

    The next important component is the quality of measurements taken. The two facets of measurement quality are reliability and validity. First reliability, which simply means how repeatable the results are and low reliability indicates that many random errors are occurring during measurement. Second, the concept of validity, which means the metric measures what it intended to measure. Errors in validity, called systematic errors, are usually experienced because not all factors were taken into account when the metric was designed.

    The next component of measurement is causality. The cause and effect relationship has three requirements:

1. cause precedes effect in time or by logic.
2. shown cause and effect relationship
3. direct constant relationship

    When the relationship between variables can be graphed and a line of best fit can be found, however be careful of extreme and inaccurate data values. When defining a casual relationship be sure to watch for the following spurious relationships.

    CASE 1
        Z causes changes in X
        Z causes changes in Y
        X is perceived to causes changes in Y or vice versa and Z is overlooked

    CASE 2
        X causes changes in Z
        Z causes changes in Y
        X is perceived to causes changes in Y and Z is overlooked

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Many metrics

    Most metrics in software quality assurance fall under one of two categories, product metrics and process metrics.

    Product metrics are for describing characteristics of product such as it’s size, complexity, features, and performance. Several common product metrics are mean time to failure, defect density, customer problem, and customer satisfaction metrics.

• Mean time to failure metric is, to put it plainly, the average time the product runs before experiencing a crash, which is important for systems like air traffic control that are required to have no more than a few seconds of down time in a full year.
• Defect density metric refers to number of imperfections per:
  • Lines of code
  • Function definitions
  • Lines on input screens
• Customer problem metric is a measure of problems customers have encountered with the product over the total usage of the product. This metric takes into account that multiple instances of the product can be used at the same time, which effectively multiplies the length of time the product has been in operation by the number of product licenses.
• Customer satisfaction metric is generally a survey asking customers to rate their satisfaction with the product and/or it’s features on a five-point scale.

Process metrics are strictly for evaluating & improving the effectiveness of development and maintenance processes. Some common process metrics are defect arrival pattern, backlog management index, fix quality, and fix response time metrics.

• Defect arrival pattern metric is a combination of the rate at which defects are reported and the growth of these rates through out the process being measured.
• Backlog management index metric measures the effectiveness of the process by comparing the number of problems that arrive to the number of fixes during a specified period.
• Fix quality metric measures the number of defective fixes compared to the number of successful fixes. A fix is defective when either it doesn’t repair the problem reported or it repairs the problem but introduces new defects into the product.
• Fix response time metric refers to the time between when a problem is reported and the time a fixed is issued.