DCS Corporation

Alexandria, VA, United States

DCS Corporation

Alexandria, VA, United States
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News Article | May 9, 2017
Site: www.prweb.com

DCS Corporation (DCS), a premier professional services firm that provides engineering, programmatic and technical support services to the Department of Defense and other customers focused on national security, was awarded a five-year prime contract to support the Tank Automotive Research, Development and Engineering Center (TARDEC). Under this prime contract, DCS will provide expertise to TARDEC on-site at the Tank-Automotive and Armaments Command (TACOM) and other CONUS and OCONUS locations; supporting lifecycle engineering, Field Service to ground vehicle PMs for Material Solution, Operations & Support. DCS will also provide engineering services to support the acquisition and development of survivability systems, military ground vehicle robotics, software development and Post Production Software Support (PPSS), electrical and electronics architectures, high voltage power electronics, information systems security, mechanical engineering, science and technology, research and development, security engineering, and systems engineering on projects within TARDEC, and projects managed and supported by TARDEC. DCS will be working with TARDEC groups that provide research and development for ground vehicle systems developing advanced technologies for Ground Vehicle Power and Mobility (GVPM) Ground System Survivability (GSS), Ground Vehicle Robotic (GVR), Ground Vehicle Simulation Laboratory (GVSL), Software Engineering Center (SEC), Center for Systems Integration (CSI) and Vehicle and Electronics Architecture (VEA). DCS is proud to support TARDEC’s research, development, engineering, sustainment and management of cutting edge manned and unmanned ground vehicle systems, and the capabilities critical to the Warfighter in the form of common, fully developed, supportable, and reliable systems that align with strategic and operational requirements. DCS is a strong advocate of designing and building “tomorrow’s capabilities within today’s budget.” For more information about the work we do for the U.S. Army, please visit: https://www.dcscorp.com/our-customers/us-army/.   About DCS DCS offers advanced technology, engineering and management solutions to Government agencies in the ground vehicle domain. The transformative ideas and entrepreneurial spirit that characterize our 1,000 plus employee-owners allow DCS to ensure the success of each client’s mission and actively contribute to the well-being of the Nation. To learn more about DCS, please visit https://www.dcscorp.com.


Rice V.J.,U.S. Army | Liu B.,DCS Corporation
Advances in Intelligent Systems and Computing | Year: 2017

Sustained attention is critical for military service members in operational environments. This study explored the relationship between sustained attention and mindfulness among military personnel and veterans (n = 247). Volunteers completed a sustained attention task (Integrated Visual and Auditory Continuous Performance Test), and two mindfulness surveys (Mindful Awareness and Attention Scale [MAAS] and the Five Facet Mindfulness Questionnaire [FFMQ]). Results revealed positive correlations between the MAAS and Full Scale Response Control Quotient (FSRCQ) and Full Scale Attention Quotient (FSAQ) scores. For the FFMQ, Acting with Awareness was positively correlated with the FSRCQ and FSAQ; Describing was correlated with FSRCQ; and Non-judging was correlated with FSAQ. Thus, increases in mindfulness were associated with increases in sustained visual and auditory attention, and certain facets of mindfulness were more closely aligned with sustained performance than others. These results suggest mindfulness training may assist with improving sustained attention, and that research in this area is warranted. © Springer International Publishing Switzerland 2017.


Rice V.J.,U.S. Army | Liu B.,DCS Corporation
Advances in Intelligent Systems and Computing | Year: 2017

Personal resilience refers to the ability to constructively adjust and move forward with ones’ life following tragic events or situations. However, few studies have examined the characteristics of highly resilient active duty military or veterans. This study examined the relationships between personal resiliency scores (The Resiliency Scale), demographics, general Self-Reported Health (SRH), and health symptomatology (Patient Health Questionnaire-15) among 263 U.S. active duty and veteran service members. Pearson Product-Moment Correlations, an Analysis of Variance, and Regression Analysis were used with a significance level of 0.05. Results showed that active duty service members were more resilient than the veterans in this population (p < 0.05). Findings also demonstrated that a higher education level, longer time on active duty, higher SRH, and lower symptomology were correlated with (p < 0.05) and contributed to greater resilience [F(4, 258) = 26.18, p < 0.01), R2 = 0.54]. These results demonstrate the importance of health and education, perhaps pointing toward a protective qualities that may also include longer service time. © Springer International Publishing Switzerland 2017.


Gordon S.M.,DCS Corporation | Lawhern V.,U.S. Army | Passaro A.D.,DCS Corporation | McDowell K.,U.S. Army
Journal of Neuroscience Methods | Year: 2015

Background: Blind source separation techniques have become the de facto standard for decomposing electroencephalographic (EEG) data. These methods are poorly suited for incorporating prior information into the decomposition process. While alternative techniques to this problem, such as the use of constrained optimization techniques, have been proposed, these alternative techniques tend to only minimally satisfy the prior constraints. In addition, the experimenter must preset a number of parameters describing both this minimal limit as well as the size of the target subspaces. New method: We propose an informed decomposition approach that builds upon the constrained optimization approaches for independent components analysis to better model and separate distinct subspaces within EEG data. We use a likelihood function to adaptively determine the optimal model size for each target subspace. Results: Using our method we are able to produce ordered independent subspaces that exhibit less residual mixing than those obtained with other methods. The results show an improvement in modeling specific features of the EEG space, while also showing a simultaneous reduction in the number of components needed for each model. Comparison with existing method(s): We first compare our approach to common methods in the field of EEG decomposition, such as Infomax, FastICA, PCA, JADE, and SOBI for the task of modeling and removing both EOG and EMG artifacts. We then demonstrate the utility of our approach for the more complex problem of modeling neural activity. Conclusions: By working in a one-size-fits-all fashion current EEG decomposition methods do not adapt to the specifics of each data set and are not well designed to incorporate additional information about the decomposition problem. However, by adding specific information about the problem to the decomposition task, we improve the identification and separation of distinct subspaces within the original data and show better preservation of the remaining data. © 2015 The Authors.


Passaro A.D.,DCS Corporation | CaitlinElmore L.,Baylor College of Medicine | Leising K.J.,Texas Christian University | Papanicolaou A.C.,University of Tennessee Health Science Center | Wright A.A.,University of Texas Health Science Center at Houston
Frontiers in Behavioral Neuroscience | Year: 2013

ontent-specific sub-systems of visual working memory (VWM) have been explored in many neuroimaging studies with inconsistent findings and procedures across experiments. The present study employed functional magnetic resonance imaging (fMRI) and a change detection task using a high number of trials and matched stimulus displays across object and location change (what vs. where) conditions. Furthermore, individual task periods were studied independently across conditions to identify differences corresponding to each task period. Importantly, this combination of task controls has not previously been described in the fMRI literature. Composite results revealed differential frontoparietal activation during each task period. A separation of object and location conditions yielded a distributed system of dorsal and ventral streams during the encoding of information corresponding to bilateral inferior parietal lobule (IPL) and lingual gyrus activation, respectively. Differential activity was also shown during the maintenance of information in middle frontal structures bilaterally for objects and the right IPL and left insula for locations. Together, these results reflect a domain-specific dissociation spanning several cortices and task periods. Furthermore, differential activations suggest a general caudal-rostral separation corresponding to object and location memory, respectively. © 2013 Passaro, Elmore, Ellmore, Leising, Papanicolaou and Wright.


Gordon S.M.,DCS Corporation | Franaszczuk P.J.,U.S. Army | Hairston W.D.,U.S. Army | Vindiola M.,DRC High Performance Technologies Group | McDowell K.,U.S. Army
Journal of Neuroscience Methods | Year: 2013

Detecting significant periods of phase synchronization in EEG recordings is a non-trivial task that is made especially difficult when considering the effects of volume conduction and common sources. In addition, EEG signals are often confounded by non-neural signals, such as artifacts arising from muscle activity or external electrical devices. A variety of phase synchronization analysis methods have been developed with each offering a different approach for dealing with these confounds. We investigate the use of a parametric estimation of the time-frequency transform as a means of improving the detection capability for a range of phase analysis methods. We argue that such an approach offers numerous benefits over using standard nonparametric approaches. We then demonstrate the utility of our technique using both simulated and actual EEG data by showing that the derived phase synchronization estimates are more robust to noise and volume conduction effects. © 2012 Elsevier B.V.


Rice V.,U.S. Army | Liu B.,DCS Corporation
Work | Year: 2016

BACKGROUND: Interest in resilience has increased in recent years. The U.S. military focus is on personal health and adaptation following exposure to battle, while the civilian interest centers on adjustments subsequent to disastrous events. Coping skills are also relevant, yet the relationships between coping and resilience are unclear. OBJECTIVE: This brief review examines personal resilience and individual coping strategies, exploring definitions of each, along with their potential relationships to one another. Their potential contributions within a work setting are described. METHODS: A literature review was conducted using search terms of resilience, resiliency, personal resilience, coping and resilient coping. RESULTS: Coping refers to one's using purposeful actions to handle life situations. Coping techniques can be functional or dysfunctional and the situations one copes with may be acute or long term, severe or minor. Resilience refers to positive and functional handling of oneself and ones' life, referring to the ability to recover, recuperate, and regenerate following tragic events. CONCLUSIONS: While coping and resilience are related to one another, they are distinct concepts. Positive coping techniques may contribute to resilience. However, which coping techniques improve resilience, and in what circumstances, are questions for future research. © 2016 - IOS Press and the authors.


News Article | November 7, 2016
Site: www.prnewswire.com

ALEXANDRIA, Va., Nov. 7, 2016 /PRNewswire-USNewswire/ -- Under their joint venture (DMJV), DCS and Millennium Corporation, announced today it received three competitively awarded task orders to support U.S. Army sensors and night vision work. Work on the task orders will be performed...


Hoffman C.,U.S. Navy | Giallorenzi T.G.,DCS Corporation | Slater L.B.,U.S. Navy
Applied Optics | Year: 2015

The Naval Research Laboratory (NRL) was established in Washington, DC in 1923 and is the corporate laboratory for the U.S. Navy and Marine Corps. Today NRL is a world-class research institution conducting a broad program of research and development (R&D), including many areas of optical science and technology. NRL is conducting cutting-edge R&D programs to explore new scientific areas to enable unprecedented Navy capabilities as well as improving current technologies to increase the effectiveness of Navy and other Department of Defense systems. This paper provides a broad overview of many of NRL's achievements in optics. Some of the remaining articles in this feature issue will discuss NRL's most recent research in individual areas, while other articles will present more detailed historical perspectives of NRL's research concerning particular scientific topics. © 2015 Optical Society of America.


Cerkez P.S.,DCS Corporation
Proceedings - Applied Imagery Pattern Recognition Workshop | Year: 2013

Semagrams are a subset of steganography. When a message is transmitted in a non-textual format, (i.e., in the visual content of an image), it is referred to as a semagram. While semagrams are relatively easy to create (as shown in published papers covering hiding techniques), detecting a hidden message in or embedded as an image-based semagram is a greater magnitude of difficultly than typical digital steganography. US Patents issued based on semagram technology show that this feature has been exploited in the copyright/watermarking world to increase protection. In a semagram, the image is the message and they work well for simple messages and dead drops. Attacks on semagrams are primarily visual examinations of artifacts. In the counter-espionage world, the rule of the thumb is that there is always a message hidden in an image or graphic, it is simply up to the steganalyst to find it. In short, detecting semagrams is a matter of recognizing patterns of patterns that represent a hidden message within an image. This presentation provides a brief summary of the technology underlying semagrams, present a short non-technical discussion of the technology used in the attack on semagrams, followed by a discussion on current work and planned future implementations of the proven semagram detection ANN. It will focus on extending the ANN to other domains (e.g., non-visual spectrums, multi/cross spectrum correlation, scene identification, image classification) and efforts to improve the processing speed and throughput via parallel/distributed methods. © 2013 IEEE.

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