Monday, December 22, 2014

Acquisition Update: Second C-27J Joins Coast Guard Fleet


C-27J
CG-2707 arrives at Elizabeth City, North Carolina, Dec. 18. U.S. Coast Guard photo.

December 19, 2014 - The Coast Guard C-27J Asset Project Office in Elizabeth City, North Carolina, received the second C-27J into the fleet Dec. 18, 2014.


The aircraft is the second C-27J to complete regeneration at the 309th Aerospace Maintenance and Regeneration Group’s facility in Tucson, Arizona. Regeneration is the process by which planes held in long-term preservation are reactivated and cleared for flight. Based on its inspections and examination of maintenance documentation, the regeneration team completed repairs required for the plane to be certified as airworthy.

APO personnel have been flying the first C-27J since delivery last month, conducting initial training flights, proficiency flights and pilot standardization flights. The aircraft recently flew to Air Station Sacramento, California, on a validation flight, confirming the engine fuel burn rates and advertised range that the aircraft can reach California from North Carolina in a single flight.

With the delivery of the second aircraft at the APO, additional pilot and aircrew training will commence.

The Coast Guard will regenerate 13 C-27Js under this project, with expected delivery of the third aircraft this spring.

U.S. Navy Flies Supersonic With Gevo ATJ

Englewood CO December 22, 2014 - The U.S. Navy, Naval Air Systems Command (NAVAIR), and Gevo, Inc. (GEVO), the world's only commercial producer of renewable isobutanol, announced today the first successful "alcohol-to-jet" (ATJ) supersonic flight at the Naval Air Warfare Center in Patuxent River, Md. This is the first aviation test program to comprehensively test and evaluate the performance of a 50/50 ATJ blend in supersonic (above Mach 1) afterburner operations - a critical test to successfully clear the F/A-18 for ATJ operations through its entire flight envelope.
The U.S. Navy is exploring alternative fuels that can serve as drop-in replacements to petroleum, as the availability of additional fuel sources can increase resiliency for operational commanders and help reduce U.S. dependence on fossil fuels. The Navy Fuels Team at Patuxent River is leading the Navy's test and qualification efforts of alternative fuel sources. The F/A-18 testing is a significant milestone leading to a military specification (MIL-SPEC). This MIL-SPEC would allow for commercial supply of ATJ fuel to the Navy and Marines Corps.
Gevo's ATJ is produced at its demo biorefinery in Silsbee, TX, using isobutanol produced at its Luverne, MN, fermentation facility. Gevo is currently operating its Luverne plant in Side-by-Side operational mode, whereby isobutanol is being produced in one of the facility's four fermenters, while the other three fermenters are dedicated to ethanol production. The isobutanol that Gevo is producing is meeting product specifications for direct drop-in applications, as well as for use as a feedstock for the Silsbee biorefinery to produce hydrocarbons such as ATJ.
"We're extremely proud to have contributed to the U.S. Navy's successful ATJ test flights," said Patrick Gruber, Gevo's Chief Executive Officer. "These flights represent an accumulation of over four years of hard work involving innovative testing with multiple players and years of research. Together, we have proven that ATJ fuel is a viable alternative for both military and commercial applications. This is a great accomplishment for Gevo and the biofuels industry; we've validated that the isobutanol that we are successfully producing at Luverne, is an affordable, clean-burning, U.S.-made, drop-in fuel, that can also be further processed into direct replacement hydrocarbon products, such as ATJ fuel."
The F/A-18 Hornet is a single-and two-seat, twin engine, multi-mission fighter/attack aircraft that can operate from either aircraft carriers or land bases. Its engine thrust from 36,000 pounds to 44,000 pounds utilizing two General Electric F414 turbo-fan engines.

Carestream Health is First Company to Receive U.S. Navy Certification to Implement Medical Image Management Systems

Carestream Vue PACS (Photo: Business Wire)
Carestream Vue PACS (Photo: Business Wire)

Rochester December 22, 2014 - Carestream is now the first company approved to provide the latest Picture Archiving and Communications Systems (PACS) for use in U.S. Navy medical facilities as a result of meeting some of the most stringent product security requirements for the Navy’s DIACAP certification process.
Carestream has received an official ATO (Authorization to Operate) from The Department of Defense (DoD) Information Assurance Certification and Accreditation Process (DIACAP) that enables the Navy to implement Carestream’s Vue PACS at any Naval Medical Treatment Facility across the globe. DIACAP is a process by which information systems are tested and certified for compliance with DoD security requirements and accredited for operation.
PACS are used by hospitals, clinics and medical practices to store, manage and access patient medical images and information. As the only PACS now DIACAP approved to reside on a U.S. Navy network, Carestream’s Vue PACS can support multi-site reading of diagnostic exams and sharing of radiology information to help physicians determine the best treatment for each patient’s condition.
While security testing of new systems typically occurs in a lab environment, Carestream’s PACS—along with its cardiology PACS feature—was successfully tested in an extremely complex environment at one of the largest DoD hospitals that performs more than 300,000 radiology exams a year. Carestream’s native reporting application—a voice recognition and reporting feature that allows remote reading by radiologists, which expedites the delivery of radiology reports and helped eliminate transcription costs—was also included in the Navy’s field testing process.
With the diagnostic viewing capabilities of Carestream’s Vue PACS, users can consolidate the reading of all medical imaging exams onto a single platform, which can boost productivity while simplifying operations and support. Its scalable, Web-enabled platform integrates smoothly with complex environments and complies with XDS, HL7, DICOM and IHE standards.
Carestream Vue PACS offers radiology reading tools such as MPR, MIP, MinIP, volume rendering, tissue definition, vessel tracking and cardiac analysis. The PACS can automatically register 3D imaging data sets (such as MR and CT) to help highlight subtle changes in anatomy and improve clinical collaboration. Vue PACS also provides lesion management as a native clinical tool that can simplify the comparison process between different data sets and supports oncology follow-up with bookmarking and tracking of general anatomy over time.
As part of Carestream’s “Knowing Matters” customer strategy, Carestream’s Vue portfolio of healthcare IT solutions is designed to offer greater value and insight for clinicians, foster collaboration, control costs and streamline dataflow. The company's Vue solutions amplify the clinical, business and IT value of radiology services.
Carestream’s X-ray products and healthcare IT systems are used by the U.S. Government’s Veterans Integrated Service Networks, the U.S. Army and U.S. Air Force, as well as by many foreign governments around the world.
The company regularly receives high marks for the performance of its Vue PACS for use in radiology, cardiology and mammography, and some of the most well-known hospitals and national healthcare systems have implemented Carestream’s PACS.

Navy Awards Contract for Ranger Dismantling



Washington December 22, 2014 - The Navy awarded a contract, Dec. 22, for the towing and dismantling of the decommissioned aircraft carrier Ranger (CV 61) to International Shipbreaking Ltd. 
Under the contract, the company will be paid $0.01, a price that reflects the net price proposed by International Shipbreaking, Inc., which considered the estimated proceeds from the sale of the scrap metal to be generated from dismantling. 
This is not a sales contract, it is a procurement contract; $0.01 is the lowest price the Navy could possibly have paid the contractor for towing and dismantling the ship.
The ship will be towed from the Navy's inactive ships maintenance facility in Bremerton, Washington, to International Shipbreaking, Ltd.'s ship dismantling facility in Brownsville, Texas, for complete dismantling and recycling. 
The ship is expected to depart Bremerton via tow in January or February, and arrive in Brownsville after four to five months. The ship is too large for passage through the Panama Canal and must be towed around South America.
Ranger was the third Forrestal-class aircraft carrier to be built. The ship was laid down Aug. 2, 1954, by Newport News Shipbuilding & Drydock Co., Newport News, Virginia, and commissioned at the Norfolk Naval Shipyard, Aug. 10, 1957. Ranger was the only ship of the Forrestal class to spend its entire career in the Pacific. The ship made a total of 22 Western Pacific deployments, was an active participant in the Vietnam War, and was the only West Coast-based carrier to deploy in support of Operation Desert Storm. 
Ranger was decommissioned July 10, 1993, after more than 35 years of service. It served as a retention asset for potential future reactivation until stricken from the Naval Vessel Register, March 8, 2004, and redesigned for donation. After eight years on donation hold, the USS Ranger Foundation was unable to raise the necessary funds to convert the ship into a museum or to overcome the physical obstacles of transporting her up the Columbia River to Fairview, Oregon. As a result, Ranger was removed from the list of ships available for dismantling and designated for dismantling. 
While there are many veterans with strong desires that the Navy not scrap the ship they served on, there were no states, municipalities or nonprofit organizations with a viable plan seeking to save the ship. The Navy cannot donate a vessel unless the application fully meets the Navy's minimum requirements for donation, and cannot retain inactive ships indefinitely.


U.S. Navy Awards General Dynamics $498 Million for Mobile Landing Platform Afloat Forward Staging Base

San Diego December 22, 2014 - The U.S. Navy has awarded General Dynamics NASSCO a $498 million contract for the detail design and construction of the Mobile Landing Platform (MLP) Afloat Forward Staging Base (AFSB). NASSCO is a wholly owned subsidiary of General Dynamics.
Under this option, NASSCO will provide the detail design and construction efforts to build the second AFSB of the Mobile Landing Platform-class ships. The work will be performed at NASSCO's San Diego shipyard and is scheduled to be completed by March 2018.
The MLP AFSB is a flexible platform and a key element in the Navy's large-scale airborne mine countermeasures mission. With accommodations for 250 personnel and a large helicopter flight deck, the MLP AFSB will provide a highly capable, innovative and affordable asset to the Navy and Marine Corps.

Accenture Awarded $19.8 Million Contract to Enhance Navy Enterprise Resource Planning System

The U.S. Department of the Navy has awarded Accenture Federal Services five task orders under an indefinite-delivery, indefinite-quantity (IDIQ) contract to provide information technology support and training for the Navy Enterprise Resource Planning (ERP) system. Each task order has a one-year period of performance. The total value of all five task orders is $19.8 million.
“Navy ERP is an important system in the Navy’s business systems portfolio. It meets critical fleet supply needs, provides financial visibility and improved auditability, and delivers more accurate information for better decision-making. We are proud to be selected to help the Navy sustain the system”
Accenture is helping support, maintain and improve the Navy ERP system, built on the SAP® ERP application, for the Naval Supply Systems Command’s (NAVSUP) Business Systems Center (BSC) in Mechanicsburg, Pa. NAVSUP delivers information technology solutions with specific emphasis on logistics and financial-related products and services for the Navy, U.S. Department of Defense, Military Services and other federal agencies.
Work under the task orders includes supporting the financial and supply chain systems, providing technical system development and enhancements, and delivering functional training support to system users.
Navy ERP is an integrated financial and business management system that manages more than 50 percent of the Navy’s total obligation authority, with more than 68,000 users worldwide. The system is integral to achieving the Navy’s goal of producing auditable financial statements in compliance with U.S. Department of Defense and Navy audit guidance.
“Navy ERP is an important system in the Navy’s business systems portfolio. It meets critical fleet supply needs, provides financial visibility and improved auditability, and delivers more accurate information for better decision-making. We are proud to be selected to help the Navy sustain the system,” said Vince Vlasho, who leads Accenture’s work with the Navy.
Accenture also supports the Navy with comprehensive audit readiness services and IT effectiveness evaluations for the Navy as well as program management and engineering services for the Space and Naval Warfare Systems Center Pacific.
Accenture Federal Services is a U.S. company, with offices in Arlington, Va., and is a wholly owned subsidiary of Accenture LLP. Accenture’s federal business has served every cabinet-level department and 30 of the largest federal organizations with clients at defense, intelligence, public safety and civilian agencies.

In One Aspect of Vision, Computers Catch up to Primate Brain

Newest computer neural networks can identify visual objects as well as the primate brain. MIT.

By Anne Trafton 

December 18, 2014 - For decades, neuroscientists have been trying to design computer networks that can mimic visual skills such as recognizing objects, which the human brain does very accurately and quickly.
Until now, no computer model has been able to match the primate brain at visual object recognition during a brief glance. However, a new study from MIT neuroscientists has found that one of the latest generation of these so-called “deep neural networks” matches the primate brain.
Because these networks are based on neuroscientists’ current understanding of how the brain performs object recognition, the success of the latest networks suggest that neuroscientists have a fairly accurate grasp of how object recognition works, says James DiCarlo, a professor of neuroscience and head of MIT’s Department of Brain and Cognitive Sciences and the senior author of a paper describing the study in the Dec. 18 issue of the journal PLoS Computational Biology.
“The fact that the models predict the neural responses and the distances of objects in neural population space shows that these models encapsulate our current best understanding as to what is going on in this previously mysterious portion of the brain,” says DiCarlo, who is also a member of MIT’s McGovern Institute for Brain Research.
This improved understanding of how the primate brain works could lead to better artificial intelligence and, someday, new ways to repair visual dysfunction, adds Charles Cadieu, a postdoc at the McGovern Institute and the paper’s lead author.
Other authors are graduate students Ha Hong and Diego Ardila, research scientist Daniel Yamins, former MIT graduate student Nicolas Pinto, former MIT undergraduate Ethan Solomon, and research affiliate Najib Majaj.
Inspired by the brain
Scientists began building neural networks in the 1970s in hopes of mimicking the brain’s ability to process visual information, recognize speech, and understand language.
For vision-based neural networks, scientists were inspired by the hierarchical representation of visual information in the brain. As visual input flows from the retina into primary visual cortex and then inferotemporal (IT) cortex, it is processed at each level and becomes more specific until objects can be identified. 
To mimic this, neural network designers create several layers of computation in their models. Each level performs a mathematical operation, such as a linear dot product. At each level, the representations of the visual object become more and more complex, and unneeded information, such as an object’s location or movement, is cast aside.
“Each individual element is typically a very simple mathematical expression,” Cadieu says. “But when you combine thousands and millions of these things together, you get very complicated transformations from the raw signals into representations that are very good for object recognition.”
For this study, the researchers first measured the brain’s object recognition ability. Led by Hong and Majaj, they implanted arrays of electrodes in the IT cortex as well as in area V4, a part of the visual system that feeds into the IT cortex. This allowed them to see the neural representation — the population of neurons that respond — for every object that the animals looked at.
The researchers could then compare this with representations created by the deep neural networks, which consist of a matrix of numbers produced by each computational element in the system. Each image produces a different array of numbers. The accuracy of the model is determined by whether it groups similar objects into similar clusters within the representation.
“Through each of these computational transformations, through each of these layers of networks, certain objects or images get closer together, while others get further apart,” Cadieu says.
The best network was one that was developed by researchers at New York University, which classified objects as well as the macaque brain.
More processing power
Two major factors account for the recent success of this type of neural network, Cadieu says. One is a significant leap in the availability of computational processing power. Researchers have been taking advantage of graphical processing units (GPUs), which are small chips designed for high performance in processing the huge amount of visual content needed for video games. “That is allowing people to push the envelope in terms of computation by buying these relatively inexpensive graphics cards,” Cadieu says.
The second factor is that researchers now have access to large datasets to feed the algorithms to “train” them. These datasets contain millions of images, and each one is annotated by humans with different levels of identification. For example, a photo of a dog would be labeled as animal, canine, domesticated dog, and the breed of dog.
At first, neural networks are not good at identifying these images, but as they see more and more images, and find out when they were wrong, they refine their calculations until they become much more accurate at identifying objects.
Cadieu says that researchers don’t know much about what exactly allows these networks to distinguish different objects.
“That’s a pro and a con,” he says. “It’s very good in that we don’t have to really know what the things are that distinguish those objects. But the big con is that it’s very hard to inspect those networks, to look inside and see what they really did. Now that people can see that these things are working well, they’ll work more to understand what’s happening inside of them.”
The high performance of the latest computer models “is exciting not just as an engineering feat, but it also gives us better computational tools for modeling how biological brains work, including the human brain,” says Nikolaus Kriegeskorte, a principal investigator in the United Kingdom’s Medical Research Council Cognition and Brain Sciences Unit, who was not part of the research team. “Along with two other recent studies, this work suggests that the deep learning models solve the complex task of visual recognition in ways somewhat similar to biological brains.”
DiCarlo’s lab now plans to try to generate models that can mimic other aspects of visual processing, including tracking motion and recognizing three-dimensional forms. They also hope to create models that include the feedback projections seen in the human visual system. Current networks only model the “feedforward” projections from the retina to the IT cortex, but there are 10 times as many connections that go from IT cortex back to the rest of the system.
This work was supported by the National Eye Institute, the National Science Foundation, and the Defense Advanced Research Projects Agency.