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Liu W.,Systems Center Pacific Pacific | Hsu L.,Systems Center Pacific Pacific | Kagan J.,Systems Center Pacific Pacific | Bloom J.,American Society of Engineering Education ASEE
2014 Oceans - St. John's, OCEANS 2014 | Year: 2015

We present experimental data showing how the power output of a sediment microbial fuel cell (MFC) can be dramatically increased by recirculating a dilute 1% mud solution between a settling tank and anode chamber with and without carbon granules. This enables both greater power output and MFC operation out of the mud. With carbon granules added to the bottom of the 125 ml anode chamber, power outputs of 1.3 mW were achieved with total anode surface areas of 77 cm2 (graphite chips) and an anode displaced volume of 31 cc. This equates to a volumetric energy density of 1.2 W per ft3 of anode volume. © 2014 IEEE.

Liang Q.,Cloud Security | Rubin S.H.,Systems Center Pacific Pacific
International Journal of Information and Decision Sciences | Year: 2012

This paper applies randomisation theory to the problem of selecting software test cases for software systems and applications in order to overcome the high costs incurred in testing componentised systems of systems (SoS). We have used a corner point semantics, which can approximate a proof of correctness – termed a pseudo-proof of correctness. Test cases for each component are designed to be mutually orthogonal, or randomised. Integration testing is performed through a composition of the test cases for components with some value-added test cases to cover integration aspects of the system. Integration testing is also designed in such a way that the testing algorithm is written in randomised form. In this paper, we present a theoretical framework for randomising test design for component and integration testing. We also show a meta heuristic algorithm based on the framework to be used with test design methodologies that are randomisation-friendly. The advantages offered by such randomisation are ever present in the algorithm, programming language, integration, and workflow design. © 2012 Inderscience Enterprises Ltd.

McLauchlan L.,Texas A&M University-Kingsville | Mehrubeoglu M.,Texas A&M University-Corpus Christi | Durham J.,Systems Center Pacific Pacific
ASEE Annual Conference and Exposition, Conference Proceedings | Year: 2013

Problem based learning has been shown to increase student excitement and attention which will increase student understanding of course material and concepts. With the high cost of large scale underwater, land and air vehicles, the use of modeling and simulation capabilities becomes more important for university programs. Autonomous Unmanned Vehicle (AUV) Workbench was developed at the Naval Postgraduate School as a modeling and simulation environment to enable physics based real time simulation of autonomous vehicles, such as unmanned surface vehicles (USV), unmanned underwater vehicles (UUV) and unmanned aerial vehicles (UAV). Vehicle missions can also be replayed for further study. 1-5 At Texas A&M University-Kingsville and Texas A&M University-Corpus Christi, a lab exercise for multiple vehicles has been created for the students to illustrate waypoint navigation and control for unmanned surface and air vehicles. Two versions were developed, an abbreviated version for the freshman students in introductory courses at the two universities, and a more extensive one for the senior students at Texas A&M University-Kingsville. By enabling a visual representation of the effects of the control algorithm in the simulated actions, freshman students gain a larger scale understanding of more advanced theoretical concepts that they will learn during their junior and senior years, thereby allowing the students to gain insights into how the theory in various undergraduate classes may be used in applications. The seniors in the undergraduate linear controls course at Texas A&M University-Kingsville can investigate different controllers such as Proportional Integral Derivative (PID) in the AUV Workbench environment, thus enabling students to see how the control of the vehicle is affected as the controller is varied. System-of-Systems Engineering (SOSE) necessitates an increased sharing and interoperability of information. In support of mission-driven SOSE, a critical need exists to support science and technology research and education that provide increased coordination of activities supporting mission driven SOSE. The AUV Workbench simulation environment enhances the student's understanding of modeling systems which in turn helps to continue addressing this need at the university educational level. © American Society of Engeneering Education, 2013.

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