126 research outputs found
1433 Effectiveness of ‘hearing conservation program’ in the lng industry – a qatar perspective
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Imaging the spread of reversible brain inactivations using fluorescent muscimol
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J Neurosci Methods. 2008 June 15; 171(1): 30–38
Privacy-Aware State Estimation based on Obfuscated Transformation and Differential Privacy: With applications to smart grids and supply chain economics
No full textWith the emergence of many modern automated systems around us that rely heavily on the private data collected from individuals, the problem of privacy-preserving data analysis is now gaining a significant attention in the field of systems and control. In this thesis, we investigate the privacy concerns of these systems arising in the process of state estimation - a well known and a widely studied concept in systems and control. Our work draws motivation from smart grids and supply chain economics, and hence, we study two different privacy problems in the context of state estimation and rely on cryptography to solve these challenges.In the first problem, we study the privacy challenges of state estimation in smart grids. Smart grids promise a more reliable, efficient, economically viable, and an environment-friendly electricity infrastructure for the future. State estimation in smart grids plays a vital role in system monitoring, reliable operation, automation, and grid stabilization. However, the power consumption data collected from the users during estimation can be privacy-sensitive. Furthermore, the topology of the grid can be exploited by malicious entities during state estimation to launch attacks without getting detected. Motivated by the essence of a secure state estimation process, we propose a weighted-least-squares estimation carried out batch-wise at repeated intervals where the resource-constrained clients utilize a malicious cloud for computation services. We exploit a highly efficient and verifiable obfuscation-based cryptographic solution to perform the computations of the estimation process securely in the presence of a malicious adversary. Simulation results demonstrate a high level of obscurity both in time and frequency domain making it difficult for the malicious adversary to interpret information about the original power consumption data of the consumers and the grid topology from the obfuscated datasets. Our second problem deals with the challenge of protecting a dynamical supply chain model while releasing the state sequences generated by the model for data aggregation to an external possible adversary. Releasing state samples generated by a dynamical system model with high accuracy for data aggregation and other statistical purposes can also be used for reverse engineering and estimating sensitive model parameters. Upon identification of the system model, the adversary may even use it for predicting sensitive data in the future. Hence, preserving a confidential dynamical process model is crucial for the survival of many industries. Motivated by the need to protect the system model as a trade secret, we propose a mechanism based on differential privacy to render such model identification techniques ineffective while preserving the utility of the state samples for data aggregation purposes. We deploy differential privacy by generating noise according to the sensitivity of the query and adding it to the state vectors at each time instant. We derive analytical expressions to quantify the bound on the sensitivity function and estimate the minimum noise level required to guarantee differential privacy. Furthermore, we present numerical analysis and characterize the privacy-utility trade-off that arises when deploying differential privacy. Simulation results demonstrate that through differential privacy, we achieve acceptable privacy level sufficient to mislead the adversary while still managing to retain high utility level of the state samples for data aggregation. Mechanical Engineering | Systems and Contro
The Role of High-Tech Capital Formation for Swedish Productivity Growth
Full text linkWhile using new data and standard growth-accounting techniques, this paper takes a closer look at the Swedish productivity revival in the second half of the 1990s. In particular, I find large total factor productivity growth in high-tech producing sectors and capital deepening associated with high-tech equipment elsewhere. In addition, for high-tech producers, high-tech capital deepening has as a rule contributed negatively to labor productivity growth - a result above all driven by large increases in hours worked in this sector. I also find that in the business sector, the contribution from high-tech capital deepening to labor productivity growth increased from about 1 percent 1994 to 9 percent 1999.
Evaluating Macroscopic DTA Models – For Who, When and How?
No full textOver the past few decades, transport authorities globally have resorted to transport models for testing policy interventions and simulating the results as part of the ex-ante analysis. Within the domains of traffic assignment, there is a greater focus on the dynamic representation of traffic, which has proved to be more accurate when compared to their static counterparts. This has put Dynamic Traffic Assignment (DTA) Models at the forefront of development. Departing from the classical traffic flow theories Macroscopic DTA’s simulates aggregated traffic analogous to the flow of fluids or gases. This aggregation enables high-speed computation with the ability to achieve a stable equilibrium state within feasible model run times. Due to the large number of Macroscopic DTA models developed worldwide, the model user is posed with the problem of using the correct model for the correct application. The current research aims to provide an answer to this problem through the design, development, and validation of an evaluation framework for Macroscopic DTA’s. The objective evaluation of the DTA’s is performed through certain Measures of Performances (MoPs). The subjective side of evaluation showcases the differences in importance associated with model features which vary from model users to application domains. Three macroscopic DTA models popular in the Netherlands are used for the application of the framework: the MARPLE (Model for Assignment and Regional Policy Evaluation), StreamLine: MaDAM (Macroscopic Dynamic Assignment Model), and StreamLine: eGLTM (event-based Generalized Link Transmission Model). From the results, it is observed that For a Strategic Planning application, both MARPLE and StreamLine: eGLTM proved to be better alternatives, as they performed exceedingly better in achieving a stable state of convergence. However, as the time horizons of application became smaller as is the case with Tactical and Operational planning, the final score for StreamLine: MaDAM improved substantially due to its accuracy involved in link-level propagation and queuing. The evaluation scores also showcase the fundamental trade-off between model complexity and computational speed was visible from the results. We can observe variations across model users, which validates our original hypothesis that the right choice of a model primary depends on the person using it and the application it is deployed for.Civil Engineering | Transport and Plannin
Investigations on the Performance of Metallic and Composite Body Armors
No full textAbstractBody armor systems made of various materials and exhibiting distinct ballistic energy absorption mechanisms need to be considered for improving ballistic performance and energy absorbing mechanism of body armor. Modern armor materials such as composites and fabrics replace high density metals and alloys which hindered mobility and offered less protection. Armors are designed to prevent penetrating threats and internal damage that penetration will produce to human torso. The interaction between armor and human torso should be considered for actual performance of armor and for evaluating quality of protective effectiveness of armor against non-penetrating threats. Hence, linear elastic analysis of curved metallic and composite armors with continuum model and discrete model for the human surrogate target has been considered
1/f noise in titanium doped aluminum thin film deposited by electron beam evaporation method and its dependence on structural variation with temperature
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