The Intersection of Privacy by Design and Behavioral Economics: Nudging Users towards Privacy-Friendly Choices

This paper conducts a comprehensive review of existing research on Privacy by Design (PbD) and behavioral economics, explores the intersection of Privacy by Design (PbD) and behavioral economics, and how designers can leverage “nudges” to encourage users towards privacy-friendly choices. We analyze the limitations of rational choice in the context of privacy decision-making and identify key opportunities for integrating behavioral economics into PbD. We propose a user-centered design framework for integrating behavioral economics into PbD, which includes strategies for simplifying complex choices, making privacy visible, providing feedback and control, and testing and iterating. Our analysis highlights the need for a more nuanced understanding of user behavior and decision-making in the context of privacy, and demonstrates the potential of behavioral economics to inform the design of more effective PbD solutions.

Feature extraction of partial discharge in low-temperature composite insulation based on VMD-MSE-IF

Low-temperature composite insulation is commonly applied in high-temperature super-conducting apparatus while partial discharge(PD)is found to be an important indicator to reveal insulation statues.In order to extract feature parameters of PD signals more effectively,a method combined variational mode decomposition with multi-scale entropy and image feature is proposed.Based on the simulated test platform,original and noisy signals of three typical PD defects were obtained and decomposed.Accordingly,relative moments and grayscale co-occurrence matrix were employed for feature extraction by K-modal component diagram.Afterwards,new PD feature vectors were obtained by dimension reduction.Finally,effectiveness of different feature extraction methods was evaluated by pattern recognition based on support vector machine and K-nearest neighbour.Result shows that the proposed feature extraction method has a higher recognition rate by comparison and is robust in processing noisy signals.

Skin-integrated stretchable actuators toward skin-compatible haptic feedback and closed-loop human-machine interactions

Skin-integrated haptic interfaces that can relay a wealth of information from the machine to the human are of great interest.However,existing haptic devices are not yet able to produce haptic cues that are compatible with the skin.In this work,we present the stretchable soft actuators for haptic feedback,which can match the perception range,spatial resolution,and stretchability of the skin.Pressure-amplification structures are fabricated using a scalable self-assembly process to ensure an output pressure beyond the skin perception threshold.Due to the minimized device size,the actuator array can be fabricated with a sufficiently high spatial resolution,which makes the haptic device applicable for skin locations with the highest spatial acuity.A haptic feedback system is demonstrated by employing the developed soft actuators and highly sensitive pressure sensors.Two proof-ofconcept applications are developed to illustrate the capability of transferring information related to surface textures and object shapes acquired at the robot side to the user side.

The Paradigm of Power Bounded High-Performance Computing

Modern computer systems are increasingly bounded by the available or permissible power at multiple layers from individual components to data centers.To cope with this reality,it is necessary to understand how power bounds im-pact performance,especially for systems built from high-end nodes,each consisting of multiple power hungry components.Because placing an inappropriate power bound on a node or a component can lead to severe performance loss,coordinat-ing power allocation among nodes and components is mandatory to achieve desired performance given a total power bud-get.In this article,we describe the paradigm of power bounded high-performance computing,which considers coordinated power bound assignment to be a key factor in computer system performance analysis and optimization.We apply this paradigm to the problem of power coordination across multiple layers for both CPU and GPU computing.Using several case studies,we demonstrate how the principles of balanced power coordination can be applied and adapted to the inter-play of workloads,hardware technology,and the available total power for performance improvement.

Data Center Power System Stability-Part II: System Modeling and Analysis

This is the second part of a two-part paper on stability study of data center power systems by impedance-based methods.As the basis for this application,Part I[1]developed new impedance models for power supplies that are the most dominant loads in data centers.This second part presents system modeling and analysis methods that can support practical data center power system design to ensure stability.The proposed methods comprise:1)building distribution network modeling by impedance scaling;2)system modeling and model reduction based on equivalent source impedance;3)system stability analysis in the sequence domain to include zero-sequence dynamics;and 4)expansion of system models and analyses to account for network asymmetry and uneven loading.These methods are used to characterize practical resonance problems observed in data centers,explain their root causes,and develop solutions.For systems using Y-connected power supply units(PSUs),the zero sequence is identified as the weakest link and the first to become unstable.The expanded system model and analysis reveal a new,differential-mode instability that is responsible for high frequency resonances.To guarantee system stability,new impedance-based product and system design specifications are developed based on sufficient conditions derived from the Nyquist stability criterion.Laboratory and field measurements are presented to substantiate the proposed methods and conclusions.

Data Center Power System Stability-Part I: Power Supply Impedance Modeling

This two-part paper presents methods to predict,characterize and ensure the stability of data center power systems based on impedance analysis.The work was motivated by recent power system resonance incidents in new data centers.Part I presents new input impedance models for single-phase power supply units(PSUs)to enable this application.Existing impedance models of single-phase PSU cannot meet the requirements of this application because they exclude DC voltage control that affects system stability at low frequency,or are in a dq reference frame that cannot handle the complexity of data center power systems.The developed new models include DC bus dynamics and are directly in the phase domain to simplify system stability analysis,avoiding the need for multiple-input-multiple-output(MIMO)system models and the generalized Nyquist criterion that are difficult to apply but necessary with dq-frame models.Both the converter and system level models also include the coupled current response that is characteristic of AC-DC converters and important for system stability at low frequency.The simple form of the models and system stability analysis directly in the phase domain also make it possible to develop new PSU design methods and performance specifications that together will ensure the stability of new data center power systems.The developed models are validated by laboratory measurements and are used in Part II of the work to study data center power system stability.