16,666 research outputs found
Optimal realizations of floating-point implemented digital controllers with finite word length considerations.
The closed-loop stability issue of finite word length (FWL) realizations is
investigated for digital controllers implemented in floating-point arithmetic.
Unlike the existing methods which only address the effect of the mantissa bits
in floating-point implementation to the sensitivity of closed-loop stability,
the sensitivity of closed-loop stability is analysed with respect to both the
mantissa and exponent bits of floating-point implementation. A computationally
tractable FWL closed-loop stability measure is then defined, and the method of
computing the value of this measure is given. The optimal controller realization
problem is posed as searching for a floating-point realization that maximizes
the proposed FWL closed-loop stability measure, and a numerical optimization
technique is adopted to solve for the resulting optimization problem. Simulation
results show that the proposed design procedure yields computationally efficient
controller realizations with enhanced FWL closed-loop stability performance
Development of Solid State Electrolytes for Li-Metal Based High Capacity Battery
NASA future missions demand safe, high specific energy (>400 Wh/kg) batteries. Current state-of-the-art (SOA) lithium-ion batteries (LIBs) can only provide ~150-200 Wh/kg in energy capacity, which is unable to meet NASA's future energy goals, and also pose safety issues due to the use of liquid flammable electrolyte. There are intense on-going development activities to increase battery energy density. The use of Li metal as an anode material has emerged as one highly attractive option for achieving high-energy, next generation batteries. This is because Li has many advantages. It is the lightest metal, but also has the highest theoretical capacity. It also has the lowest potential, which boosts whole cell voltage, and Li metal is 100% active material and requires no binder. Thus, Li metal is an ideal anode material for high energy battery chemistries. Lithium metal based advanced battery chemistries are envisioned to be mission enhancing and, in many cases, mission enabling for future space and aeronautic applications. However, the reliable use of this exceptionally high capacity anode in a commercial rechargeable battery has not been achieved due to safety and reliability concerns resulting from thermal runaway and short-circuit issues due to dendritic growth on the Li metal anode from lithium plating during charge-discharge cycles. A solid state electrolyte, such as garnet/ceramic or solid polymer nanocomposite electrolyte, is a promising approach to make Li metal safely cycling. The solid state electrolyte is non-flammable and eliminates leakage and fire hazard by replacing the liquid flammable electrolyte. However, the low-ionic conductivity and high interfacial impedance are the key issues to be overcome. In this presentation, the research activities on solid state electrolyte development funded by the NASA Advanced Energy Storage System program and by the NASA Center Innovative Fund will be presented, and the progress and results will be also discussed
Fundamental Investigation of Si Anode in Li-Ion Cells
Silicon is a promising and attractive anode material to replace graphite for high capacity lithium ion cells since its theoretical capacity is approximately 10 times of graphite and it is an abundant element on earth. However, there are challenges associated with using silicon as Li-ion anode due to the significant first cycle irreversible capacity loss and subsequent rapid capacity fade during cycling. In this paper, cyclic voltammetry and electrochemical impedance spectroscopy are used to build a fundamental understanding of silicon anodes. The results show that it is difficult to form the SEI film on the surface of Si anode during the first cycle, the lithium ion insertion and de-insertion kinetics for Si are sluggish, and the cell internal resistance changes with the state of lithiation after electrochemical cycling. These results are compared with those for extensively studied graphite anodes. The understanding gained from this study will help to design better Si anodes
Fundamental Investigation of Silicon Anode in Lithium-Ion Cells
Silicon is a promising and attractive anode material to replace graphite for high capacity lithium ion cells since its theoretical capacity is ~10 times of graphite and it is an abundant element on Earth. However, there are challenges associated with using silicon as Li-ion anode due to the significant first cycle irreversible capacity loss and subsequent rapid capacity fade during cycling. Understanding solid electrolyte interphase (SEI) formation along with the lithium ion insertion/de-insertion kinetics in silicon anodes will provide greater insight into overcoming these issues, thereby lead to better cycle performance. In this paper, cyclic voltammetry and electrochemical impedance spectroscopy are used to build a fundamental understanding of silicon anodes. The results show that it is difficult to form the SEI film on the surface of a Si anode during the first cycle; the lithium ion insertion and de-insertion kinetics for Si are sluggish, and the cell internal resistance changes with the state of lithiation after electrochemical cycling. These results are compared with those for extensively studied graphite anodes. The understanding gained from this study will help to design better Si anodes, and the combination of cyclic voltammetry with impedance spectroscopy provides a useful tool to evaluate the effectiveness of the design modifications on the Si anode performance
Developing a Supply Chain Strategy for a Midsize Resturant Chain
In this paper, we develop a supply chain strategy for a growing midsize restaurant chain. Based on a case research of The HoneyBaked Ham Company of Ohio, we propose that an integrated approach should be applied to handle the challenges presented in the midsize restaurant distribution system. Specifically, we focus on action plans for mitigating inefficiencies found in the previous supply chain of HBH. As the success of supply chain management has increasingly become part of the competitive advantage of many firms, our work provides managerial insights to practitioners and researchers in the area of chain restaurant management where supply chain is often overlooked as a standard "back-office" function
PPGAN: Privacy-preserving Generative Adversarial Network
Generative Adversarial Network (GAN) and its variants serve as a perfect
representation of the data generation model, providing researchers with a large
amount of high-quality generated data. They illustrate a promising direction
for research with limited data availability. When GAN learns the semantic-rich
data distribution from a dataset, the density of the generated distribution
tends to concentrate on the training data. Due to the gradient parameters of
the deep neural network contain the data distribution of the training samples,
they can easily remember the training samples. When GAN is applied to private
or sensitive data, for instance, patient medical records, as private
information may be leakage. To address this issue, we propose a
Privacy-preserving Generative Adversarial Network (PPGAN) model, in which we
achieve differential privacy in GANs by adding well-designed noise to the
gradient during the model learning procedure. Besides, we introduced the
Moments Accountant strategy in the PPGAN training process to improve the
stability and compatibility of the model by controlling privacy loss. We also
give a mathematical proof of the differential privacy discriminator. Through
extensive case studies of the benchmark datasets, we demonstrate that PPGAN can
generate high-quality synthetic data while retaining the required data
available under a reasonable privacy budget.Comment: This paper was accepted by IEEE ICPADS 2019 Workshop. This paper
contains 10 pages, 3 figure
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Software project process management maturity and project performance: An examination of Taiwan\u27s software companies
Researchers and practitioners argue that an inadequate software development process is one critical factor accounting for high project failure rates. a result, the Capability Maturity Model (CMM) was introduced by the Software Engineering Institute as a guideline for advancing project maturity and improving the odds of project success. To investigate the effectiveness of applying the principles of the CMM, a survey was conducted of 196 Information System managers in Taiwan. The results indicate that a more mature software development process reduces the extent of certain risks experienced during the project development and enables better project performance. Managerial implications regarding the CMM are described
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