Philist: 一些乱七八糟的信息

Dumb and Dumpy: Can the German Shepherd Be Saved?

Fri, 28 Oct 2011 23:58:11 +0800

Once an icon, bad breeding has earned the German Shepherd a reputation for being sickly and dimwitted. In Germany, police have replaced them with the more aggressive Malinois. But one American breeder is trying to bring classic German Shepherds back.

Nokia launches Lumia 800 with F2.2 Carl Zeiss-branded lens

Thu, 27 Oct 2011 02:39:13 +0800

Phone maker Nokia has launched a range of Windows Phone-based models, including the Lumia 800 with Carl Zeiss-branded lens. The range-topping Lumia 800 includes an 8MP sensor that sits behind a 28mm equivalent lens with F2.2 maximum aperture. The phone's camera features include manual exposure and white balance control as well as continuous AF and dual LED flash. Video recording is only 720p30, however.

华西村之谜

Wed, 26 Oct 2011 15:43:59 +0800

很早就听说过华西村，据说是中国最牛的村子。领导吴仁宝很牛，靠搞乡镇企业发家，把一个小村子搞成全国最富有的村子。

后来慢慢就觉得有点奇怪——他们到底是做什么生意的，能够这样持续发达呢？要知道乡镇企业的热潮已经退去十几二十年了。

再后来看了吴晓波的《激荡三十年》，其中批露了华西村的一些内情：比如继任的村领导是吴仁宝的儿子，村民的股份其实是集体所有，个人并没有处置权——或者简单地说，在村内就是一个共产主义社会，全村经济由吴氏家庭经营，村民的生活资源由组织上统一分配，共同创造财富。

但是我仍然不知道他们是做什么生意的。

上周的《1／7》报道了华西村的30亿元高楼——一座328米的五星级酒店——建成开业。话说我实在不明白在这个苏北南小村建这样的酒店要如何盈利。虽然节目里有稍微提到说村子里在搞旅游业，去那里参观一下一个人要500块钱的门票，出得起500块门票的人住五星级酒店似乎也不奇怪。但是要赚回这30亿估计还是很困难。

后来看到网易这篇《华西村“样板村”的繁荣假面》总算大致明白了吴氏家族的生财之道——无非是吃政策饭而已。电视节目里一个细节也很说明问题：

在高楼酒店的开业庆典上，吴仁宝介绍这个楼为什么要造328米，就是因为北京最高的楼就是328米，他这是与中央保持高度一致！

开业第一天，全体村民被请去吃了一顿五星级的早餐，大家都很开心。一位大妈在家里接受采访时还笑开了花，无比自豪地介绍起他们家分得的大别墅，以及他们家也是酒店的股东之一什么的。然后我又注意到了一个细节：

每户村民“自愿”向酒店建设投资了一千万元。

结合前面说过的，村民虽然名义上很有钱，但实际上财富的控制权归“集体”所有，离开村子的人都必须净身出村。那么实际上村民即使不愿出这一千万，这钱他们也见不到，所以自然都“被自愿”了。

其实我在想，这个村子里未必没有比吴氏家族更有能力的人，只是他们囿于这个小村子，无法走出去。一千万在手，足以游遍全世界的高级酒店，又何须为区区一顿早餐而欢欣鼓舞。

其实你懂的，华西村就是中国式共产主义的缩影，整个中国，无非就是一个大一点的华西村。

The Limits of Variation

Mon, 24 Oct 2011 06:03:42 +0800

A few people were more than a little amused that I, the ultimate pixel-peeper, wrote an article demonstrating that all lenses and all cameras vary a bit; that you can’t find the ultimately sharpest lens. Each individual copy of a given lens is a little different from the other copies. A single copy will behave a little differently on different cameras. Even on the same camera, autofocus the same shot a dozen times and the results will be slightly different. (Don’t believe that? Put your camera on a tripod, single focus point, aim at a target. Look at the distance scale. Autofocus again. And again. You’ll see the camera is focusing a bit differently each time.) So people started asking me ”If there’s variation, then what’s the sense in taking all those measurements?”

There’s plenty of reason for all those measurements. They can be really useful once you stop looking for the exact place a given lens or camera should be and accept that there is range of acceptability. I’m not saying the manufacturer’s repair center stating “lens is within specifications” means it’s acceptable. (It may or may not be on your camera.) I’m saying it can be tested and evaluated to see if it really is acceptable.

In other words, we know that computerized analysis using Imatest or a similar program can show us a measureable difference exists between several lenses. But what does that mean? Can we tell when a difference is just the inevitable minor variation and when it’s a meaningful problem? The answer is yes. The vast majority of the time, anyway.

Determining What is Acceptable

In the last article I used a lot of graphs showing the Imatest results for multiple copies of the same lens, demonstrating how much variation there was between supposedly acceptable copies. I chose to use mostly prime lenses as examples because the patterns were nicely grouped and the outliers were obvious at a glance. Here’s a group of Canon 35mm f/1.4 lenses, for example, and there don’t appear to be any bad copies. It’s a nice, reasonably tight group of results. And knowing how other lenses look when they’re bad, I’d expect a bad lens to be hanging out down around the 500/300 area, well away from this group.

A test run of 28 copies of the Canon 35mm f/1.4 lens

So, the obvious assumption is these are all good lenses. But lets pretend I’m an OCD pixel peeper who’s paranoid that those two lenses at the lower left, the lowest scores of the group, might not be OK. Just because Roger says the group looks good doesn’t mean it is.

Luckily there is a way to help confirm that our grouping is acceptable. Subjective Quality Factor is a measurement developed by Ed Granger and K.N. Cupery in the 1970s for Kodak and used by Popular Photographer for their lens reviews. Basically, SQF uses a mathematical formula, taking the MTF data from the lens (which we get from these tests) to predict with good accuracy how sharp a print would be perceived at various sizes and distances.

I’m not going into detail about SQF (for a more thorough discussion, see Bob Atkins excellent article or the references below). The important part is that several experts have shown an SQF difference of less than 5 for a reasonably sized print is basically not detectable by human vision.

In the graph below I’ve added the SQF numbers for several of the lenses (we arbitrarily use SQF for 30cm height images) for both best and average resolution of the lenses. We could use a different image size and the absolute numbers would change, but not the difference between them (for reasonable image sizes).

The same test group with a few SQF numbers added

As you can see, the highest SQF (84/80) and the lowest (81/75) remain within 5 points of each other. Trying to pick the best lens out of this group (not even considering each will be slightly different on a different camera, slightly different every time it focuses on the same scene, etc.) is basically foolish: we can measure this small difference with the computer, but we couldn’t see it in the picture. However, any lens that tested much lower or to the left of our scattered pattern of good lenses would indeed be softer and you could tell it in a print.

And What Isn’t Acceptable

Unfortunately (for my sanity), all lenses aren’t primes with nice tight test patterns that make great examples. Below is a run of almost 100 copies of the Canon 24-70 f2.8 zoom lens tested at 70mm. Why so many? Because when I first tested two dozen copies they were a random smattering of results scattered around the chart. Data doesn’t make any sense? Get more data. Luckily we have a lot of lenses.

A large run of Canon 24-70 lenses at 70mm

But more data didn’t solve the problem either, it just gave me a big smattering of lens results. Zoom lenses do tend to have a bigger copy-to-copy variation spread than primes do, but this was ridiculous. Obviously the two lenses at the bottom left are bad and simple optical testing confirmed that. But what about the group of a half dozen just above the two bad ones? And that other group of a half dozen above those but still under 500 LP/PH? Optical testing wasn’t very helpful, they seemed OK shooting test charts. On the other hand, they didn’t look really sharp either.

SQF was really quite helpful in this situation. Let’s look at the same graph with some SQF numbers added. The very best result we got was an SQF of 85/84. If anything greater than a 5 point SQF would be visibly different, then we can draw a line between the lowest acceptable results and the highest unacceptable results, which I’ve done on the graph.

The truth is, in looking at the graph, that’s where I suspected the line would be — results above that line are fairly tightly grouped, those below it more scattered about. But I’ll admit I was hoping I was wrong, because being right meant we were going to send a whole lot of lenses in for factory service. I believed the SQF data, though, so the whole bunch went off to Canon.

Heading back to the mother ship, the bad actors from the test run above. And a few others.

But the proof is in the pudding. Nine of those lenses have come back from Canon. Below are the original test result in blue and the post-repair result in red for those nine copies. I’ve also left in the line from the previous graph that SQF said would be the acceptable cut-off for this lens at 70mm. Not all of them are back yet, but I think these 9 lenses make the point pretty clearly.

Test results for nine lenses pre and post repair, with the SQF suggested line of acceptability

As you can see, all of the lenses that were unacceptable by the SQF definition came back from repair in the acceptable range. So it does appears that a bit of pixel-peeping measurement, along with some mathematical calculations, really can give us a reasonable indication of what is just normal variation and what is a bad lens. (BTW, out of all the different Canon lenses, this the only one for which the bad lenses were not completely obvious at a glance. And even the bad lenses from this set all were perfectly fine at less than 55mm, they only had trouble at the long end.)

Of course, now you should be thinking “Roger, why would they just be having trouble at the long end?” and “Why were there so many bad copies of this one lens?” Well, you know me, I have major OCD and I just had to try to figure that out.

The 24-70 mystery

This part has little to do with optical testing, it’s about the Canon 24-70 lens specifically. And before I go further, please raise your right hand and repeat after me: “I do solemnly swear not to be an obnoxious fanboy and quote this article out of context for Canon-bashing purposes.” Because trust me on this: Canon faired very, very well in our testing, with only this one lens being an outlier. Other brands definitely are not better. This one got to be the example simply because we started testing Canon lenses first, and because we have more copies of them.

I mentioned in my last post that we found no lenses that got worse with age except “one zoom that doesn’t seem to be aging well” and this is the one I was talking about. Years ago when we started Lensrentals, I arbitrarily decided to sell every lens at two years old. I didn’t have a particular reason for 2 years rather than 1 or 3, it just seemed about right. But since I’d just made that call on my gut, one of the things we have looked at with every lens test was the age of copies tested versus their test results, to see if my assumption was correct.

For lens after lens there was no difference with age, so I was shocked when I looked at the results of the 24-70s. The vast majority of the bad lenses (and all of the really bad lenses) had over 20 rental weeks of use.

The difference in older copies (blue) is rather striking

All of our lenses rent with the same frequency. All of them get the same care. So what was different about 24-70s that made them have problems with aging when the other lenses didn’t? There is one thing that is somewhat different about 24-70 f2.8 zooms: they are both barrel extending (rather than internal) zooms and are rather heavy. Most barrel extending zooms are lighter. Maybe thousands of zoom twists was wearing something out.

Well, we might not be capable of repairing most lenses without the factory repair center to help, but we certainly are capable of taking them apart (especially when we know they have to go in to be fixed anyway, we’re real brave then) and looking around. What we found was rather interesting. In the zoom helicoid are several screws with plastic collars around them that keep the barrel tracking properly within it’s grooves:

The plastic collar (red arrow) around the screw keeps the lens tracking properly in the helicoid groove.

There are a number of such screw/collar assemblies in the lens. When we looked at some of the bad lenses, we saw several screws that seemed to be missing their collars. In several of the lenses, like the one shown below, we found the collar broken off and loose inside the lens.

Forceps being used to remove a collar that had come loose and wedged between sleeves of the lens barrel.

When you compare a fresh new collar with one we fished out of an older lens, it becomes pretty apparent they’ve worn down and eventually broken off from around the screw. We didn’t find missing collars in every bad copy we opened, but we did in most of them.

A missing collar or two could (I assume – I don’t know for certain) allow the internal barrel to not stay properly aligned as it tracks in and out with zooming. If it wasn’t properly aligned, it wouldn’t focus properly. Perhaps that explains why these lenses usually have trouble at 70mm and not throughout the entire range. Why 70mm and not 24mm? I have no idea. We did see a couple of lenses with problems at the wide end (and they were both sharp at 70mm), but not nearly as many and they were very clearly outliers.

Before you freak out about your personal 24-70, though, remember these are rental lenses. Probably every one gets more use in a year than yours does in a lifetime.

The Bigger Picture

For those of you into pixel peeping and “I demand a perfect copy” kind of stuff, I think this is the takeaway message:

Copy-to-copy variation is real, although barely detectable in actual photography. If you pixel peep you can find a difference that’s real, but not significant. Meaning you can see a small difference in test results, but couldn’t tell the difference in a print.

Bad lenses are usually massive outliers, easily detected at a glance (see the previous article for examples) or with the most rudimentary testing (like just taking some pictures) in the majority of cases.

There are some situations, like our Canon 24-70s, where a measured difference isn’t huge (at least compared to really bad lenses) but probably is significant enough to affect the sharpness of a print. While SQF isn’t the be-all, end-all measurement and has very real limitations, it can be a useful tool helping us to decide what is, and is not significant.

Finally, for those of you (and there are a couple of million of you) who own a Canon 24-70, please don’t go off the deep end because of this demonstration. Remember, these are rental lenses. They get used heavily an average of 90 days a year (and probably not as gently as you would use your own equipment). Plus they are shipped all over the country, an average of 20 round-trips a year. As I’ve always said, Lensrentals.com should be considered battle testing for photo equipment. Whatever can fail, will fail here. It doesn’t mean your copy is going to do this.

But if you have an older copy, and you feel it’s softer at 70mm than in the middle and short ranges, it probably is worth a trip to Canon for a checkup. It should be obvious from the graph above that it can be fixed quite effectively.

References:

Biedermann and Feng: ”Lens performance assessment by image quality criteria” in Image Quality: An Overview, Proc. SPIE Vol. 549, pp36-43 (1985)

Granger and Cupery: “An optical merit function (SQF) which correlates with subjective image judgments.” Photographic Science and Engineering, Vol. 16, no. 3, May-June 1973, pp. 221-230.

Hultgren, “Subjective quality factor revisited: a unification of objective sharpness measures”, Proc. SPIE 1249, 12 (1990)

An Addendum for Lensrentals Customers:

About two dozen people have bought Canon 24-70 lenses from our used lens sales page over the last year. Obviously the inspection we carried out when you bought the lens did not include the Imatest information we now obtain on the lens. If any of you have doubts about the sharpness of your lens at 70mm, we would be happy to test it for you. Please send us an email before you send us the lens, though, so we won’t wonder why a lens arrived in the day’s shipments that doesn’t register in our inventory.

Roger Cicala

Lensrentals.com

October, 2011

有板有眼：亚马逊与作者直接签约将怎样影响传统出版业？

Wed, 19 Oct 2011 16:12:10 +0800

问：亚马逊开始与作者直接签约，对传统出版业会造成什么影响？

@王冉：据纽约时报报道，亚马逊开始和作者直接签约了，并且准备向他们开放部分后台的数据。他们先是让传统书店无路可走，现在又要让出版社和经纪公司陷入四面楚歌。他们对世界的看法是：在图书领域，只有两个环节是不可或缺的——作者和读者，其它一切都可有可无。当然，他们真正想说的是：作者、读者和亚马逊。

答：亚马逊直接跟作者签约，书籍以电子版发行，亚马逊跟作者三七分账。这种模式像不像程序员为App Store开发应用？依托亚马逊这样的中间平台，作者就像程序员一样，写书就像写应用，作者自己掌控一切，并且获得比传统出版方式更高的回报。而出版社、各级图书发行商和书店这些传统出版产业的重要组成部分，在新的产业链条上不再具有任何价值，他们会被彻底剔除。这就是出版业的未来，但却不是所有人都乐见的未来。

美国书商协会（ ABA ）CEO Oren Teicher说：“亚马逊将整个图书出版业当作人质，开始是将零售商去中介化（disintermediate），现在则是出版商和作家。”其实传统出版业者并不否认电子化代表未来，他们更加担心的是亚马逊一家独大，完全掌控产业话语权。

回到亚马逊，过去的产业链条是作者-经纪人-出版社-亚马逊-读者，即使是纯电子书的发行，亚马逊只能跟出版社签约，每卖一本电子书，亚马逊分得30%，出版社从剩下的70%销售额中分25%给作者，相当于书价的17.5%。如果扣去经纪人的那份，剩下只有14.9%到作者手上。卖掉一本售价10美元的书，作者分得1.49美元。作者与亚马逊直接签约之后，产业链条缩短为作者-亚马逊-读者，就算图书价格降至3美元，作者仍可分得2.1美元，而且获得了对自己图书的完全掌控。

《经济学人》认为，出版商应该向风险资本家转型，他们负责发现潜在的畅销书作者，并投资（预付定金）。但无论如何，出版商主宰图书出版发行的好日子，终归将一去不复返。

“纸质书不会死亡”，这样的声音来自不同地方、不同群体，语气坚决而且包含情感。没错，纸质书信也不会死亡，你上一次把信投进邮筒是什么时候的事儿？

百度文库下载器绿色去广告版 --- 免登录，免积分

Wed, 19 Oct 2011 00:18:00 +0800

软件简介：
   相信大家都知道，百度文库有各式各样，各行各业的资料文档，这些资料文档可以在线浏览，但不能复制保存；如果要下载该文档，更需要您是百度注册用户，甚至有些重要文档，还需要有百度虚拟积分，所以，一般用户要下载百度文库的资料文档相当不容易。

       百度文库下载器是一个实用性强的小软件。有了它，一般用户都可以轻易从百度文库里下载到自己想要的资料了，无需用户登录，无需百度积分。不过，软件有个缺憾，就是不能下载保存原格式文件，所有下载到的文档都一律转换成文本（.txt），所以，在搜索时，最好选择（.txt）格式，这样会省去文档重新编辑的麻烦。

     免费软件，原版界面有广告框。本版是去广告版，无广告显示，而且经过重新压缩，体积仅有900多KB，原版2.6MB 。

下载： 百度文库下载器绿色去广告版（844 KB 解压密码：laolao8k）

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Comic for October 12, 2011

Wed, 12 Oct 2011 13:00:00 +0800

《桃姐》让港片返璞归真

Wed, 12 Oct 2011 05:11:40 +0800

果子李

桃姐，原名张春桃。家贫，13岁到李家做女仆。

70岁，中风，入院。醒后，要求主人辞退，搬进养老院。2年后，离开人世。

她终身未嫁。临终前，膝下无子女、无亲人，也不知是否有过心上人。

在芸芸众生的香港，桃姐只是个再普通不过的下人。

刘德华说，桃姐这个名字在香港已不多见了，属于已经过去的年代。

但这个真实的人、真实的...

总共有 22 条读者评论

火车上的中国人，令人拍案叫绝的纪实片

Mon, 10 Oct 2011 19:00:43 +0800

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Siri 是革命？会革了谁的命？

Mon, 10 Oct 2011 07:02:10 +0800

语音识别不是革命性的。多年前， IBM 的语音识别软件在 PC 上就有不错的识别率了。

基于语音识别，简单的智能分析和系统功能的调用也不算革命性的。无论是 Google 的 Voice Action ，还是 Vlingo 等独立的公司，做的都不错。

但是，从目前流出的视频看， Siri 并非这些已知技术的简单组合。

Siri 的智能程度更高

Vlingo 中你说 “Text Mike ，Messages How are you.” 。利用关键字的匹配就可以完成很多事情了。 Text 是命令， Messages 是关键字。匹配上这两个词，就知道给谁，发送什么内容了。

而 Siri 理解上下文。你问了北京的天气，再说：“ How about Shanghai ?” ，他知道你指的是天气。

一个更惊人的例子出现在 Siri 被苹果并购前的演示里。你说“ I like a romantic place for Italian food near my office”。

Siri 回答：” I am looking for a Italian restaurants which reviews say are romantic near your wok in San Jose…“

这个回答说明 Siri 听懂了 romantic 是个形容词。并且知道 near my office 是个地方。并且，找到了以前存储的用户的工作地点。并且，他知道怎么判断一个餐馆是否 romantic ！（去搜索 reviews ）

把同样的话对着 Android 的 Voice Action 或者 Vlingo 说一遍，你就知道 Siri 具有超越现有 Apps 的智能。

Siri 和系统的整合更加紧密

Siri 在并购前的版本整合了大量网络服务的 APIs 。比如 OpenTable，Tickets.com，Taxi Magic 等等。

而 Siri 被苹果收购了之后，他已经被整合为系统的一部分了。

在 iOS5 的 Siri 视频中，出现新短消息之后，交互由 Siri 发起。说明他已经常驻系统后台并且可以接管重要的系统功能了。（除了短消息还有天气，时钟，Maps 等等）

Siri 的团队？

判断 Siri 靠不靠谱的另一个角度是看看到底是谁在做？

2003 年美国国防部高级研究机构（DARPA）发起了一个相关的项目（ “enduring personalized cognitive assistant.”）。而 SRI（斯坦福研究院）负责这个项目的研究，项目被命名为 CALO 。这就是 Siri 的前身。

DARPA? 互联网的前身和 GPS 都源于 DARPA 的项目。

SRI 参与的创新？鼠标，互联网，无线通讯，超声波，机器人 AI ，语音识别等赫然在列。

Siri 被乔布斯看中？

2009 年 2 月， Siri 登陆 AppStore 。

2009 年 3 月，苹果收购 Siri 。价格不详。

2011 年 10 月，苹果发布和系统高度整合的 Siri 。（ DARPA 项目的 8 年之后）

(时间表来自 Mashable )

苹果收购 Siri 的决定之快，价格之高，和 iOS5 的整合之紧密，让人怀疑这是个高层决策。（收购价格不详，假设第二轮出让 10% 股份，在此之后 Siri 的估值不会低于 1.5 亿美金。苹果的并购很少超过这个数。）

这次并购展示了苹果对于新科技的超凡的预见能力。他总能发现那些真正会改变生活的技术。（比如电容多点触摸）

再一次，让人想起乔布斯。对他来说， Siri 可能不过是当年在帕罗奥多那里看到 Alto 情景的重演而已。（而最近几天的报道证实，乔布斯在病重期间一直参与苹果的决策。）

Siri 威胁了谁？

拥有 Siri 的 iPhone 4S 会威胁 Android ， WP7 等其他智能手机。但是，这并不是最重要的。

Siri 如果真的如苹果的广告那么好用，他会威胁到 Google 的命根子：搜索。

搜索不再是“搜索框，网站，功能，结果”的流程了。这个流程太慢，太复杂。

搜索变为 “ Siri 语音识别，智能分析，调用本地 Apps 或者网络 APIs ，整合所有结果为最合适的内容表现给用户”。

Siri 变为“入口”。所有的 Apps 和网络服务都在他的后面。

据说为了让 iPhone 使用 Google Maps ， Google 每年付给苹果 10 亿美金。相信没人会怀疑， Siri 最终会装在上亿台 iOS 设备上。

那时，有多少网络服务商，要为他的各种服务付出多少？

李楠

移动互联网/苹果/ERP/SAP。写过：「 iPhone 可有设计哲学」，「领先五年的迷思」，「以前没有 iPhone OS，以后没有 Mac OS」，「对社交说不」，「 MSNS ：移动社交网络」，「云书店，新阅读」⋯⋯

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