Research Brief

Approved for public release; distribution is unlimited

System Qualities Ontology, Tradespace and Affordability (SQOTA) Project Phase 5

Motivation and Context: One of the key elements of the SERC's research strategy is transforming the practice of systems engineering and associated management practices- "SE and Management Transformation (SEMT)." The Grand Challenge goal for SEMT is to transform the DoD community 's current systems engineering and management methods, processes, and tools (MPTs) and practices away from sequential, single stovepipe system, hardware-first ,document-driven, point- solution, acquisition-oriented approaches; and toward concurrent, portfolio and enterprise-oriented, hardware-software-human engineered, model-driven, set-based, full life cycle approaches.This material is based upon work supported, in whole or in part, by the U.S. Department of Defense through the Office of the Assistant Secretary of Defense for Research and Engineering (ASD(R&E)) under Contract H98230-08-D-0171 and HQ0034-13-D-0004 (TO 0060).This material is based upon work supported, in whole or in part, by the U.S. Department of Defense through the Office of the Assistant Secretary of Defense for Research and Engineering (ASD(R&E)) under Contract H98230-08-D-0171 and HQ0034-13-D-0004 (TO 0060)

Deep Learning Based Malware Classification Using Deep Residual Network

The traditional malware detection approaches rely heavily on feature extraction procedure, in this paper we proposed a deep learning-based malware classification model by using a 18-layers deep residual network. Our model uses the raw bytecodes data of malware samples, converting the bytecodes to 3-channel RGB images and then applying the deep learning techniques to classify the malwares. Our experiment results show that the deep residual network model achieved an average accuracy of 86.54% by 5-fold cross validation. Comparing to the traditional methods for malware classification, our deep residual network model greatly simplify the malware detection and classification procedures, it achieved a very good classification accuracy as well. The dataset we used in this paper for training and testing is Malimg dataset, one of the biggest malware datasets released by vision research lab of UCSB

Proceedings, MSVSCC 2019

Old Dominion University Department of Modeling, Simulation & Visualization Engineering (MSVE) and the Virginia Modeling, Analysis and Simulation Center (VMASC) held the 13th annual Modeling, Simulation & Visualization (MSV) Student Capstone Conference on April 18, 2019. The Conference featured student research and student projects that are central to MSV. Also participating in the conference were faculty members who volunteered their time to impart direct support to their students’ research, facilitated the various conference tracks, served as judges for each of the tracks, and provided overall assistance to the conference. Appreciating the purpose of the conference and working in a cohesive, collaborative effort, resulted in a successful symposium for everyone involved. These proceedings feature the works that were presented at the conference. Capstone Conference Chair: Dr. Yuzhong Shen Capstone Conference Student Chair: Daniel Pere

Enhancing Set-Based Design To Engineer Resilience For Long-Lived Systems

At the heart of Set-Based Design is the concept that down-select decisions are deferred until sufficient information is available to make a decision, i.e., a set of possible solutions is maintained. Due to the extended service lives of many of our current and future systems, the horizon for accurately predicting the system’s requirement is shorter than the service life, so the needed information to down-select to a single optimized solution is unavailable at the time of fielding. Set-Based Design can, however, be extended to explicitly carry a set of possible solutions past the point of the initial fielding of the system by considering changeability, as enabled through designed-in reserve capacity to accommodate additional volume, weight, power, cooling, and computer performance. Proposed is an analytical framework that enhances Set-Based Design to engineer resilient systems with cost-effective post-production growth capability by means of reserve capacity and illustrate it through a case study

Integrating the Department of Defense military services' technology development programs to improve time, cost, and technical quality parameters

E organizations currently do not provide for or permit any substantial degree of synergistic teaming, integration, or technology leveraging. As a result, technology development for each of the SR, DD(X), and FCS programs has failed to achieve schedule efficiency, cost effectiveness, and technical proficiency. To enable a successful development of these systems in particular and to prevent DoD system acquisition programs from failing to achieve the aforementioned parameters, a leveraged technology development strategy is needed. This thesis examined the potential for inter-service technology development and identified opportunities to leverage the development of common, critical technologies across the three services within the DoD in general and across the SR, DD(X), and FCS programs in particular. The findings of this study show that through careful planning and coordinated technology transition, DoD acquisition programs can indeed leverage the technology development efforts of the three services within the DoD. The identified technology leveraging opportunities will enable significant cost savings and schedule efficiency to the Space Radar, DD(X), and Future Combat Systems programs and help ensure deployment of these critical defense capabilitieshttp://archive.org/details/integratingdepar109453639Northrop Grumman Space Technology author (civilian).Approved for public release; distribution is unlimited

Post-Westgate SWAT : C4ISTAR Architectural Framework for Autonomous Network Integrated Multifaceted Warfighting Solutions Version 1.0 : A Peer-Reviewed Monograph

Police SWAT teams and Military Special Forces face mounting pressure and challenges from adversaries that can only be resolved by way of ever more sophisticated inputs into tactical operations. Lethal Autonomy provides constrained military/security forces with a viable option, but only if implementation has got proper empirically supported foundations. Autonomous weapon systems can be designed and developed to conduct ground, air and naval operations. This monograph offers some insights into the challenges of developing legal, reliable and ethical forms of autonomous weapons, that address the gap between Police or Law Enforcement and Military operations that is growing exponentially small. National adversaries are today in many instances hybrid threats, that manifest criminal and military traits, these often require deployment of hybrid-capability autonomous weapons imbued with the capability to taken on both Military and/or Security objectives. The Westgate Terrorist Attack of 21st September 2013 in the Westlands suburb of Nairobi, Kenya is a very clear manifestation of the hybrid combat scenario that required military response and police investigations against a fighting cell of the Somalia based globally networked Al Shabaab terrorist group.Comment: 52 pages, 6 Figures, over 40 references, reviewed by a reade

Fiber optic control system integration

A total fiber optic, integrated propulsion/flight control system concept for advanced fighter aircraft is presented. Fiber optic technology pertaining to this system is identified and evaluated for application readiness. A fiber optic sensor vendor survey was completed, and the results are reported. The advantages of centralized/direct architecture are reviewed, and the concept of the protocol branch is explained. Preliminary protocol branch selections are made based on the F-18/F404 application. Concepts for new optical tools are described. Development plans for the optical technology and the described system are included

A survival prediction model for colorectal cancer patients

Dissertação de mestrado integrado em Biomedical EngineeringThe importance of making predictions in health is mainly linked to the decision-making process. Make survival predictions accurately is a very difficult task for healthcare professionals and a major concern for patients. On the one hand, it can help physicians decide between palliative care or other medical practice for a patient. On the other hand, the notion of remaining lifetime could help patients in the realization of dreams. However, the prediction of survivability is directly related to the experience of health professionals and their ability to memorize. Most decisions are made based on probability and statistics, but these are based on large groups of people and may not be suitable to predict what will happen in particular cases. Consequently, the use of machine learning techniques have been explored in healthcare. Their ability to help solve diagnostic and prognosis problems has been increasingly exploited. The main contribution of this work is a prediction tool of survival of patients with cancer of the colon and/or rectum, after treatment and a few years after treatment. The characteristics that distinguishes it is the balance between the number of required inputs and their performance in terms of prediction. The tool is compatible with mobile devices, includes a online learning component that allows for automatic recalculation and flexibly of the prediction models, by adding new cases. The tool aims to facilitate the access of healthcare professionals for instruments that enrich their practice and improve their results. This increases the productivity of healthcare professionals, enabling them to make decisions faster and with a lower error rate.A importância de fazer previsões na área da saúde está sobretudo ligada ao processo de tomada de decisão. Fazer previsões de sobrevivência de forma precisa é uma tarefa muito difícil para os profissionais de saúde e uma grande preocupação para os pacientes. Por um lado, pode ajudar os médicos a decidir entre cuidados paliativos ou outra prática médica para um paciente. Por outro lado, a noção do tempo de vida remanescente poderia ajudar os pacientes na concretização de sonhos. No entanto, este tipo de previsão está diretamente relacionada com a experiência do profissional de saúde e da sua capacidade de memorizar. A maior parte das decisões são tomadas com base em probabilidades e estatística, mas estas têm como base grandes grupos de pessoas, podendo não ser adequadas para prever o que vai acontecer em casos particulares. Por conseguinte, a utilização de técnicas de machine learning têm sido exploradas na área da saúde. A sua capacidade para ajudar a resolver problemas de diagnóstico e prognóstico tem sido cada vez mais explorada. A principal contribuição deste trabalho é uma ferramenta de previsão da sobrevida de pacientes com cancro do cólon e/ou do reto, após o tratamento e alguns anos após o tratamento. As características que a distingue são o equilíbrio entre o número de entradas necessárias e o seu desempenho a nível da previsão. A ferramenta, compatível com dispositivos móveis, possui uma componente de aprendizagem em tempo real que permite recalcular de forma automática e evolutiva os modelos usados para fazer a previsão, através da adição de novos casos. A ferramenta tem como propósito facilitar o acesso dos profissionais de saúde a instrumentos capazes de enriquecer a sua prática e melhorar os seus resultados. Esta aumenta a produtividade dos profissionais de saúde, permitindo que estes tomem decisões mais rapidamente e com uma taxa de erro menor

U.S. Unmanned Aerial Vehicles (UAVS) and Network Centric Warfare (NCW) impacts on combat aviation tactics from Gulf War I through 2007 Iraq

Unmanned, aerial vehicles (UAVs) are an increasingly important element of many modern militaries. Their success on battlefields in Afghanistan, Iraq, and around the globe has driven demand for a variety of types of unmanned vehicles. Their proven value consists in low risk and low cost, and their capabilities include persistent surveillance, tactical and combat reconnaissance, resilience, and dynamic re-tasking. This research evaluates past, current, and possible future operating environments for several UAV platforms to survey the changing dynamics of combat-aviation tactics and make recommendations regarding UAV employment scenarios to the Turkish military. While UAVs have already established their importance in military operations, ongoing evaluations of UAV operating environments, capabilities, technologies, concepts, and organizational issues inform the development of future systems. To what extent will UAV capabilities increasingly define tomorrow's missions, requirements, and results in surveillance and combat tactics? Integrating UAVs and concepts of operations (CONOPS) on future battlefields is an emergent science. Managing a transition from manned- to unmanned and remotely piloted aviation platforms involves new technological complexity and new aviation personnel roles, especially for combat pilots. Managing a UAV military transformation involves cultural change, which can be measured in decades.http://archive.org/details/usunmannedaerial109454211Turkish Air Force authors.Approved for public release; distribution is unlimited