Modeling People and Places with Internet Photo Collections

Posted on May 15, 2012 by admin

Understanding the world from the sea of online photos

DAVID CRANDALL, SCHOOL OF INFORMATICS AND COMPUTING, INDIANA UNIVERSITY

NOAH SNAVELY, DEPARTMENT OF COMPUTER SCIENCE, CORNELL UNIVERSITY

Computational photography often considers sets of photos taken by a single user in a single setting, but the popularity of online social media sites has created a social aspect to photo collections as well. Photo-sharing sites such as Flickr and Facebook contain vast amounts of latent information about our world and human behavior. Our recent work has involved building automatic algorithms that analyze large collections of imagery in order to understand and model people and places at a global scale. Geotagged photographs can be used to identify the most photographed places on Earth, as well as to infer the names and visual representations of these places. At a local scale, we can build detailed three-dimensional models of a scene by combining information from thousands of two-dimensional photographs taken by different people and from different vantage points. One key representation for many of these tasks is a network: a graph linking photos by visual similarity or other measures.

http://queue.acm.org/detail.cfm?id=2212756

Controlling Queue Delay

Posted on May 8, 2012 by admin

A modern AQM is just one piece of the solution to bufferbloat.

KATHLEEN NICHOLS, POLLERE INC.

VAN JACOBSON, PARC

Nearly three decades after it was first diagnosed, the “persistently full buffer problem,” recently exposed as part of bufferbloat,^6,7 is still with us and made increasingly critical by two trends. First, cheap memory and a “more is better” mentality have led to the inflation and proliferation of buffers. Second, dynamically varying path characteristics are much more common today and are the norm at the consumer Internet edge. Reasonably sized buffers become extremely oversized when link rates and path delays fall below nominal values.

http://queue.acm.org/detail.cfm?id=2209336

Bufferbloat: Dark Buffers in the Internet

Revisiting Network I/O APIs: The netmap Framework

The Robustness Principle Reconsidered

A Guided Tour through Data-center Networking

Posted on May 7, 2012 by admin

A good user experience depends on predictable performance within the data-center network.

DENNIS ABTS, BOB FELDERMAN, GOOGLE

The magic of the cloud is that it is always on and always available from anywhere. Users have come to expect that services are there when they need them. A data center (or warehouse-scale computer) is the nexus from which all the services flow. It is often housed in a nondescript warehouse-sized building bearing no indication of what lies inside. Amidst the whirring fans and refrigerator-sized computer racks is a tapestry of electrical cables and fiber optics weaving everything together—the data-center network. This article provides a “guided tour” through the principles and central ideas surrounding the network at the heart of a data center — the modern-day loom that weaves the digital fabric of the Internet.

http://queue.acm.org/detail.cfm?id=2208919

Enterprise Grid Computing - Paul Strong - http://queue.acm.org/detail.cfm?id=1080877

Cooling the Data Center - Andy Woods - http://queue.acm.org/detail.cfm?id=1737963

Improving Performance on the Internet - Tom Leighton - http://queue.acm.org/detail.cfm?id=1466449

Realtime Computer Vision with OpenCV

Posted on April 23, 2012 by admin

Mobile computer-vision technology will soon become as ubiquitous as touch interfaces.

KARI PULLI, NVIDIA RESEARCH

ANATOLY BAKSHEEV, ITSEEZ

KIRILL KORNYAKOV, ITSEEZ

VICTOR ERUHIMOV, ITSEEZ

Computer vision is a rapidly growing field devoted to analyzing, modifying, and high-level understanding of images. Its objective is to determine what is happening in front of a camera and use that understanding to control a computer or robotic system, or to provide people with new images that are more informative or esthetically pleasing than the original camera images. Application areas for computer-vision technology include video surveillance, biometrics, automotive, photography, movie production, Web search, medicine, augmented reality gaming, new user interfaces, and many more.

http://queue.acm.org/detail.cfm?id=2206309

Idempotence Is Not a Medical Condition

Posted on April 15, 2012 by admin

An essential property for reliable systems

PAT HELLAND

The definition of distributed computing can be confusing. Sometimes, it refers to a tightly coupled cluster of computers working together to look like one larger computer. More often, however, it refers to a bunch of loosely related applications chattering together without a lot of system-level support.

http://queue.acm.org/detail.cfm?id=2187821

BASE: An Acid Alternative

A co-Relational Model of Data for Large Shared Data Banks

Testable System Administration

A System is not a Product

Posted on April 13, 2012 by admin

Stopping to smell the code before wasting time reentering configuration data

GEORGE V. NEVILLE-NEIL, NEVILLE-NEIL CONSULTING

Every once in a while, I come across a piece of good code and like to take a moment to recognize this fact, if only to keep my blood pressure low before my yearly medical checkup.

http://queue.acm.org/detail.cfm?id=2187657

CPU DB: Recording Microprocessor History

Posted on April 7, 2012 by admin

With this open database, you can mine microprocessor trends over the past 40 years.

ANDREW DANOWITZ, KYLE KELLEY, JAMES MAO, JOHN P. STEVENSON, MARK HOROWITZ, STANFORD UNIVERSITY

In November 1971, Intel introduced the world’s first single-chip microprocessor, the Intel 4004. It had 2,300 transistors, ran at a clock speed of up to 740 KHz, and delivered 60,000 instructions per second while dissipating 0.5 watts. The following four decades witnessed exponential growth in compute power, a trend that has enabled applications as diverse as climate modeling, protein folding, and computing real-time ballistic trajectories of angry birds. Today’s microprocessor chips employ billions of transistors, include multiple processor cores on a single silicon die, run at clock speeds measured in gigahertz, and deliver more than 4 million times the performance of the original 4004.

http://queue.acm.org/detail.cfm?id=2181798

A Conversation with Steve Furber

Real-World Concurrency

The Price of Performance

Your Mouse is a Database

Posted on March 29, 2012 by admin

Web and mobile applications are increasingly composed of asynchronous and realtime streaming services and push notifications.

ERIK MEIJER

Among the hottest buzzwords in the IT industry these days is “big data,” but the “big” is something of a misnomer: big data is not just about volume, but also about velocity and variety:

http://queue.acm.org/detail.cfm?id=2169076

Security: Computing in an Adversarial Environment

Posted on March 26, 2012 by admin

Thursday, April 12, 2012 at 2:00 PM EDT/1:00 PM CDT/11:00 AM PDTSecurity is inherently different from other aspects of computing due to the presence of an adversary. As a result, identifying and addressing security vulnerabilities requires a different mindset from traditional engineering. Proper security engineering—or the lack of it!—affects everything from website scripts to supply chain management to electronic health records to social networks to mobile phones…and the list goes on. Security is further complicated by the translation of social notions—such as identity and trust— into an online world. Worse, security itself is often viewed by both developers and users as the adversary! This learning webinar will introduce the fundamentals of security, describe the security mindset, and highlight why achieving security is difficult.

What you’ll learn:

The security mindset – what it is, why it’s needed
The social side of security – usability, adoption, identity, trust
A deeper dive on insider threat as a case study – what it is, how to detect it, how to prevent it

Presenter:
Carrie Gates, Senior Vice President and Director of Research, CA Labs
Dr. Gates has opened new avenues for collaboration in the field of cyber security for CA Technologies by leveraging government programs that further research between CA Labs and academia. She has given over 20 invited talks internationally, authored more than 40 peer-reviewed publications related to information security, and co-authored an amendment on cloud security research for the America Competes Act that was signed into law in December 2010. In October 2010, Dr. Gates was recognized for her work with a Women of Influence award from CSO magazine.Moderator:

Christopher W. Clifton, Associate Professor of Computer Science, Purdue University
Dr. Clifton works on data privacy, particularly with respect to analysis of private data. This includes privacy-preserving data mining, data de-identification and anonymization, and limits on identifying individuals from data mining models. He also works more broadly in data mining, including data mining of text and data mining techniques applied to interoperation of heterogeneous information sources. Christopher also works on database support for widely distributed and autonomously controlled information, particularly issues related to data privacy. Prior to joining Purdue in 2001, Dr. Clifton was a principal scientist in the Information Technology Division at the MITRE Corporation. Before joining MITRE in 1995, he was an assistant professor of computer science at Northwestern University.

Attendance for this webinar is free. Space is limited.This webcast provided by:

http://learning.acm.org/webinar/current

Managing Technical Debt

Posted on March 26, 2012 by admin

Managing Technical Debt

Shortcuts that save money and time today can cost you down the road.

ERIC ALLMAN

In 1992, Ward Cunningham published a report at OOPSLA (Object-oriented Programming, Systems, Languages, and Applications)² in which he proposed the concept of technical debt. He defines it in terms of immature code: “Shipping first-time code is like going into debt.” Technical debt isn’t limited to first-time code, however. There are many ways and reasons (not all bad) to take on technical debt.

http://queue.acm.org/detail.cfm?id=2168798