3D print selfie

Sony Music Communications Inc. started selling the 3-D Print Figure product last year in which a figure is sculpted using full-color 3-D scanners. To create the figure, the scanner first obtains data through the scanning of a person from head to toe.

Then a computer models the data and outputs images through a 3-D printer using color ink, special bonding materials and white plaster powder. The price for a figure ranges from ¥49,000 to ¥120,000 ($600–$1500), depending on the size. According to Yosuke Takuma, who planned this business for Sony Music Communications, these 3-D figures are popular among people who want to mark such special occasions as weddings and matriculation ceremonies.

Koji Iwabuchi and his wife Yumi visited the studio from Suginami Ward, Tokyo, to order figures to commemorate their 20th wedding anniversary. “It’s like photography at the end of the Edo period as we cannot move at all,” Koji Iwabuchi said. “It’s interesting to feel like Ryoma Sakamoto. In the future, it might become an ordinary thing, but it’s fun that few people have experienced this,” he said. Ryoma Sakamoto (1836-1867) is known as the subject of some famous photos from that time.

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Hyphenation of color compounds

In computer technology, the golden rule for hyphenation of new technology terms is to write them as separate words when they are first coined, as hyphenated words when they are widely used in the technology community, and as monolexemic terms when the terms are widely used by the general population. For example, in the Sixties we had electronic mail, in the Seventies we had e-mail, and around 1993 when the Arpanet was commercialized and renamed to Internet everybody went on email.

This rule is pretty simple to remember. For color compounds the situation is a little sticky, because if changed significantly in the 16th Edition of The Chicago Manual of Style. According to rule 7.85, section 1, under colors (page 375), the new rule is that in the manner of most other such compounds, compound adjectives formed with color words are now hyphenated when they precede a noun. They remain open when they follow the noun.

Examples:

• emerald-green tie
• reddish-brown flagstone
• blue-green algae
• snow-white dress
• black-and-white print

but

• his tie is emerald green
• the stone is reddish brown
• the water is blue green
• the clouds are snow white
• the truth is not black and white

While we are at it, rule 7.76 regarding the capitalization of “web” and “Internet” also changed. Chicago now prefers web, website, web page, and so forth—with a lowercase w. But capitalize World Wide Web and Internet.

Since files are now more important than colors, Chicago prefers to present abbreviations for file formats in full capitals. Therefore, write PDF instead of pdf, even when usually we use the latter when we actually specify file names.

More Chicago capitalization examples:

• Macintosh; PC; personal computer
• hypertext transfer protocol (HTTP); a transfer protocol; hypertext
• Internet protocol (IP); the Internet; the net; an intranet
• the Open Source Initiative (the corporation); open-source platforms
• the World Wide Web Consortium; the World Wide Web; the web; a website; a web page

Returning to the opening, although nobody younger than 21 years of age has ever experienced a world without email, on page 380 the over twenty-one-year-old white-haired Chicago people still prefer e-mail and e-book.

Glass brain flythrough

This video gives viewers a colorful peek into the complex workings of the human brain as it thinks. In this case, we are “flying through” the brain of a volunteer who is been asked to simply open and close her eyes and hands, National Geographic reports. This 3D brain visualization was created by researchers at the University of California (UC), San Francisco, and UC San Diego with a combination of technologies, including an MRI scan, EEG and diffusion tensor imaging, a process that reveals tissue layout. Known as the Glass Brain, the imaging technology works in real time and may be used to learn more about how the human mind processes information.

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Traps in big data analysis

When I was a student, I had chosen mathematical statistics as one of my majors. At the time, the hot topics were robust statistics, non-parametric methods and optimal stopping times. Descriptive statistics was not part of the curriculum (PowerPoint did not yet exist and there was no need for meaningless 3-D pie charts).

In the student houses I lived, there were always medical students at the end of their studies who had to get a doctorate. Residencies were grueling and at that time the least effort thesis was to punch in some historical medical data. On their way home from the clinic, these students would spend part of the night in the empty punch card rooms, for about 6 months.

Thereafter, they would bring the punch cards to the data center and get 10 to 20 centimeters of SAS printout—and the desperation of not knowing how to get from hundreds of cryptic tables to a one hundred page thesis.

Many of them ended up knocking on my door with the printout and scratching their head. Because in the data center the students could not tell what analyses they needed—after all, there never was an experimental design—the data center people just ran all and every function available in SAS. Classical garbage-in garbage-out.

So, I had to tell the students to stare at the data and come up with a few hypotheses, then use the ANOVA routines to confirm them and the regression routines to do a few nice graphs.

Unfortunately, after all these years we are not much better off. Indeed, now we have to deal also with "big data hubris," the often implicit assumption that big data are a substitute for, rather than a supplement to, traditional data collection and analysis. Now we have tools like Google Correlate that allow us to correlate tons of apples with megatons of oranges.

A recent interesting paper by David Lazer et al. is a nice summary of how big data analysis allows us to create more statistical garbage: Lazer D, Kennedy R, King G, Vespignani A. Big data. The parable of Google Flu: traps in big data analysis. Science. 2014 Mar 14;343(6176):1203-5. doi: 10.1126/science.1248506. PubMed PMID: 24626916.

The authors conclude: "Big data offer enormous possibilities for understanding human interactions at a societal scale, with rich spatial and temporal dynamics, and for detecting complex interactions and nonlinearities among variables. We contend that these are the most exciting frontiers in studying human behavior. However, traditional 'small data' often offer information that is not contained (or containable) in big data, and the very factors that have enabled big data are enabling more traditional data collection. The Internet has opened the way for improving standard surveys, experiments, and health reporting. Instead of focusing on a 'big data revolution,' perhaps it is time we were focused on an 'all data revolution,' where we recognize that the critical change in the world has been innovative analytics, using data from all traditional and new sources, and providing a deeper, clearer understanding of our world."