The Raytheon Company is a major American defense contractor and industrial corporation with core manufacturing concentrations in weapons and military and commercial electronics. It was previously involved in corporate and special-mission aircraft until early 2007. Raytheon is the world's largest producer of guided missiles.Established in 1922, the company reincorporated in 1928 and adopted its present name in 1959. The company has around 63,000 employees worldwide and annual revenues of approximately US$25 billion. More than 90% of Raytheon's revenues were obtained from military contracts and, as of 2012, it was the fifth-largest military contractor in the world, and is the fourth largest defense contractor in the United States by revenue.Raytheon's headquarters moved from Lexington, Massachusetts to Waltham, Massachusetts in 2003. The company was previously headquartered in Cambridge, Massachusetts from 1922 to 1928, Newton, Massachusetts from 1928 to 1941, Waltham from 1941 to 1961, Lexington from 1961 to 2003, and back to Waltham from 2003 onwards. Wikipedia.
Raytheon Co. and The University Of Texas System | Date: 2016-11-10
A controlled release nanoparticulate matter delivery system includes a plurality of thermoresponsive modules containing a respective nanoparticulate matter. Each thermoresponsive module is selectively operable in at least one of a heating mode that releases the nanoparticulate matter and a cooling mode that inhibits release of the nanoparticulate matter. A control module is in electrical communication with the plurality of thermoresponsive modules. The control module is configured to determine a temperature of each thermoresponsive module and to select the at least one heating mode and cooling mode based on the temperature. The heating and cooling mode may be selected in response to a desired dosing profile and/or a biometric condition.
Raytheon Co. | Date: 2016-12-05
A system and methods are disclosed for securely booting a processing system using a three step secure booting process. Several embodiments are presented, wherein upon power-on-reset, the first boot step uses a secure boot device comprising of a programmable device or an FPGA which boots up first, validates its configuration file and then validates the processor(s) configuration data before presenting the configuration data to the processor(s). This enables validation of pre-boot information, such as the Reset Control Word and pre-boot processor configuration data. The second and third boot steps validate the internal secure boot code and external boot code respectively using one or more of secure validation techniques, such as encryption/decryption, Key mechanisms, privilege checking, pointer hashing or signature correlation schemes. This results in an end-to-end secure boot process for a variety of architectures, such as single processor systems, synchronous and asynchronous multiprocessing systems, single core systems and multi-core processing systems.
Raytheon Co. | Date: 2016-06-23
Discussed herein are apparatuses, systems, and methods for sharpening multi-spectral image data using panchromatic image data. A method can include using a Householder transform in such sharpening.
Raytheon Co. and Hypres Inc. | Date: 2016-11-18
A magnetic random access memory (MRAM) array including: a plurality of MRAM cells arranged in an array configuration, each comprising a first type nTron and a magnetic memory element; a wordline select circuit comprising of a second type nTron to drive a plurality of parallel wordlines; and a plurality of bitline select circuits, each comprising of said second type nTron for writing to and reading from a column of memory cells in the array and each capable of selecting a single MRAM cell for a memory read or write operation, wherein the second nTron has a higher current drive than the first nTron.
Raytheon Co. | Date: 2017-01-04
In one embodiment, a method for scheduling in a high-performance computing (HPC) system includes receiving a call from a management engine that manages a cluster of nodes in the HPC system. The call specifies a request including a job for scheduling. The method further includes determining whether the request is spatial, compact, or nonspatial and noncompact. The method further includes, if the request is spatial, generating one or more spatial combinations of nodes in the cluster and selecting one of the spatial combinations that is schedulable. The method further includes, if the request is compact, generating one or more compact combinations of nodes in the cluster and selecting one of the compact combinations that is schedulable. The method further includes, if the request is nonspatial and noncompact, identifying one or more schedulable nodes and generating a nonspatial and noncompact combination of nodes in the cluster.
Raytheon Co. | Date: 2017-03-08
Disclosed herein are energetic compositions and methods of making thereof. A composition includes hydrazinium nitroformate (HNF) particles dispersed in a polymeric binder and a bonding agent bonded to a surface of at least a portion the HNF particles. The bonding agent disclosed is a Lewis acid.
Raytheon Co. | Date: 2017-02-22
A method for computing a cross-correlation between a first sequence and a second sequence includes: generating a first index vector based on the first sequence, the first index vector including a plurality of first elements, the first index vector excluding indices of zero valued elements of the first sequence; generating a second index vector based on the second sequence, the second index vector including a plurality of second elements, the second index vector excluding indices of zero valued elements of the second sequence; computing, on a processor, a plurality of pairwise differences between each of first elements of the first index vector and each of the second elements of the second index vector; and binning, on the processor, the plurality of pairwise differences to generate the cross-correlation of the first sequence and the second sequence.
Agency: GTR | Branch: EPSRC | Program: | Phase: Research Grant | Award Amount: 4.56M | Year: 2016
Today we use many objects not normally associated with computers or the internet. These include gas meters and lights in our homes, healthcare devices, water distribution systems and cars. Increasingly, such objects are digitally connected and some are transitioning from cellular network connections (M2M) to using the internet: e.g. smart meters and cars - ultimately self-driving cars may revolutionise transport. This trend is driven by numerous forces. The connection of objects and use of their data can cut costs (e.g. allowing remote control of processes) creates new business opportunities (e.g. tailored consumer offerings), and can lead to new services (e.g. keeping older people safe in their homes). This vision of interconnected physical objects is commonly referred to as the Internet of Things. The examples above not only illustrate the vast potential of such technology for economic and societal benefit, they also hint that such a vision comes with serious challenges and threats. For example, information from a smart meter can be used to infer when people are at home, and an autonomous car must make quick decisions of moral dimensions when faced with a child running across on a busy road. This means the Internet of Things needs to evolve in a trustworthy manner that individuals can understand and be comfortable with. It also suggests that the Internet of Things needs to be resilient against active attacks from organised crime, terror organisations or state-sponsored aggressors. Therefore, this project creates a Hub for research, development, and translation for the Internet of Things, focussing on privacy, ethics, trust, reliability, acceptability, and security/safety: PETRAS, (also suggesting rock-solid foundations) for the Internet of Things. The Hub will be designed and run as a social and technological platform. It will bring together UK academic institutions that are recognised international research leaders in this area, with users and partners from various industrial sectors, government agencies, and NGOs such as charities, to get a thorough understanding of these issues in terms of the potentially conflicting interests of private individuals, companies, and political institutions; and to become a world-leading centre for research, development, and innovation in this problem space. Central to the Hub approach is the flexibility during the research programme to create projects that explore issues through impactful co-design with technical and social science experts and stakeholders, and to engage more widely with centres of excellence in the UK and overseas. Research themes will cut across all projects: Privacy and Trust; Safety and Security; Adoption and Acceptability; Standards, Governance, and Policy; and Harnessing Economic Value. Properly understanding the interaction of these themes is vital, and a great social, moral, and economic responsibility of the Hub in influencing tomorrows Internet of Things. For example, a secure system that does not adequately respect privacy, or where there is the mere hint of such inadequacy, is unlikely to prove acceptable. Demonstrators, like wearable sensors in health care, will be used to explore and evaluate these research themes and their tension. New solutions are expected to come out of the majority of projects and demonstrators, many solutions will be generalisable to problems in other sectors, and all projects will produce valuable insights. A robust governance and management structure will ensure good management of the research portfolio, excellent user engagement and focussed coordination of impact from deliverables. The Hub will further draw on the expertise, networks, and on-going projects of its members to create a cross-disciplinary language for sharing problems and solutions across research domains, industrial sectors, and government departments. This common language will enhance the outreach, development, and training activities of the Hub.
Guha S.,Raytheon Co.
Physical Review Letters | Year: 2011
Attaining the ultimate (Holevo) limit to the classical capacity of a quantum channel requires the receiver to make joint measurements over long code-word blocks. For a pure-state channel, we show that the Holevo limit can be attained by a receiver that uses a multisymbol unitary transformation on the quantum code word followed by separable projective measurements. We show a concatenated coding and joint-detection architecture to approach the Holevo limit. We then construct some of the first concrete examples of codes and structured joint-detection receivers for the lossy bosonic channel, which can achieve fundamentally higher (superadditive) capacity than conventional receivers that detect each modulation symbol individually. We thereby pave the way for research into codes and structured receivers for reliable communication data rates approaching the Holevo limit. © 2011 American Physical Society.
Agency: NSF | Branch: Cooperative Agreement | Program: | Phase: CISE RESEARCH RESOURCES | Award Amount: 6.00M | Year: 2015
GENI, the Global Environment for Network Innovations, is a suite of research infrastructure that spans facilities across the United States. GENI aims to transform experimental research in networking and distributed systems, as well as emerging research into very large social-technical systems, by providing a suite of infrastructure for at scale experiments in future internets. Nationwide experiments began in Summer 2010. In the intervening five years, GENI has shown rapid growth in adoption by experimental researchers and is now expanding to over 50 GENI-enabled campuses. In addition, via programs such as Campus CyberInfrastructure and US Ignite, GENI technologies are being actively used to advance national science capabilities and to imagine and design next generation applications that address national priorities. Via commercialization of technologies such as Software Defined Networking and Network Function Virtualization GENI has had a significant economic impact.
This project supports the transition of GENI from a building phase overseen by the GENI Program Office (GPO) to an operational status managed by community organizations. As part of the project, the GPO will broadly engage the U.S. computer systems research community to develop a community consensus-based plan for transition. In conjunction with NSF the organizational structure identified by this plan will be established and GENI operations transferred with the project supporting operational expenses during the transition period.