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Supporting Semantic Capture during Kinesthetic Teaching of Collaborative Industrial Robots

Industrial robot systems being deployed today do not contain domain knowledge to aid robot operators in setup and operational use. To gather such knowledge in a robotic context requires mechanisms for entering and capturing semantic data. Such mechanisms would allow a system to gradually build a working vocabulary while interacting with the environment and operators, valuable for the bootstrapping

Performance overhead comparison between hypervisor and container based virtualization

The current virtualization solution in the Cloud widely relies on hypervisor-based technologies. Along with the recent popularity of Docker, the container-based virtualization starts receiving more attention for being a promising alternative. Since both of the virtualization solutions are not resource-free, their performance overheads would lead to negative impacts on the quality of Cloud services

A Linearization Technique for Differential OTAs

This brief presents an operational transconductance amplifier (OTA) linearization technique that is applied to a low-noise amplifier (LNA) and an OTA-C filter. Simulations show the effectiveness of the proposed technique on the LNA, whose noise and gain performance remain unaffected while the linearity is significantly improved. Measurements of the 80-MHz fourth order Butterworth OTA-C filter are

Convex envelopes for fixed rank approximation

A convex envelope for the problem of finding the best approximation to a given matrix with a prescribed rank is constructed. This convex envelope allows the usage of traditional optimization techniques when additional constraints are added to the finite rank approximation problem. Expression for the dependence of the convex envelope on the singular values of the given matrix is derived and global

Fixed point algorithms for detection of parabolic events

In this paper we show how to convert the problem of estimating delay, slope and curvature of a parabolic event into a frequency estimation problem. Two dimensional data (time and offset) is converted into samples on a two-dimensional manifold embedded in a three-dimensional spaced. To conduct frequency estimation on this manifold we design general domain Hankel matrices and make use of a fixed poi

Cytokine evaluation in untreated and radioimmunotherapy-treated tumors in an immunocompetent rat model

The tumor microenvironment can act so as to stimulate or reject tumor cells. Among the determining factors are cytokines produced, for example, by infiltrating immune cells, tumor cells, and fibroblasts. External radiotherapy has been shown to be able to activate an immune response against tumor cells with cytokine signaling as an important part of the activation. The aim of this study was to eval

Utilizing Massive MIMO for the Tactile Internet: Advantages and Trade-offs

Controlling robots in real-time over a wireless inter- face present fundamental challenges for forthcoming fifth gen- eration wireless networks. Mission critical real-time applications such as telesurgery over the tactile Internet require a commu- nication link that is both ultra-reliable and low-latency, and that simultaneously serving multiple devices and applications. Wireless performance requi

Fast hyperbolic Radon transform represented as convolutions in log-polar coordinates

The hyperbolic Radon transform is a commonly used tool in seismic processing, for instance in seismic velocity analysis, data interpolation and for multiple removal. A direct implementation by summation of traces with different moveouts is computationally expensive for large data sets. In this paper we present a new method for fast computation of the hyperbolic Radon transforms. It is based on usi

A 20-GHz Bandwidth Power Amplifier for Phased Array 5G New Radio Transmitters

A 27-47-GHz differential cascode power amplifier for millimeter-wave 5G new radio applications is presented. The PA is a three-stage design using inductively coupled impedance transformers with 31-dB nominal power gain. A device periphery ratio of 1:2:6 is adopted for predriver, driver, and final stage, respectively. A gain equalization technique was used in the interstage transformers to obtain t

Improved Functional MRI Activation Mapping in White Matter Through Diffusion-Adapted Spatial Filtering

Brain activation mapping using functional MRI (fMRI) based on blood oxygenation level-dependent (BOLD) contrast has been conventionally focused on probing gray matter, the BOLD contrast in white matter having been generally disregarded. Recent results have provided evidence of the functional significance of the white matter BOLD signal, showing at the same time that its correlation structure is hi

Spectral Characterization of Functional MRI Data on Voxel-Resolution Cortical Graphs

The human cortical layer exhibits a convoluted morphology that is unique to each individual. Conventional volumetric fMRI processing schemes take for granted the rich information provided by the underlying anatomy. We present a method to study fMRI data on subject-specific cerebral hemisphere cortex (CHC) graphs, which encode the cortical morphology at the resolution of voxels in 3-D. Using graph

Encoding contexts are incidentally reinstated during competitive retrieval and track the temporal dynamics of memory interference

The ability to remember an episode from our past is often hindered by competition from similar events. For example, if we want to remember the article a colleague recommended during the last lab-meeting, we may need to resolve interference from other article recommendations from the same colleague. This study investigates if the contextual features specifying the encoding episodes are incidentally

Learning of Parameters in Behavior Trees for Movement Skills

Reinforcement Learning (RL) is a powerful mathematical framework that allows robots to learn complex skills by trial-and-error. Despite numerous successes in many applications, RL algorithms still require thousands of trials to converge to high-performing policies, can produce dangerous behaviors while learning, and the optimized policies (usually modeled as neural networks) give almost zero expla

Fundamental Bounds on Cloaking Based on Convex Optimization

A convex optimization framework over contrast current density is developed to calculate fundamental bounds on the performance of linear passive cloaks. The formulation uses the method of moments applied to the electric field integral equation while using extincted power as the optimized metric. The presented results show that high cloaking efficiency requires cloaks made of low-loss and high-contr

Identification of cardiac afterload dynamics from data

The prospect of ex vivo functional evaluation of donor hearts is considered. Particularly, the dynamics of a synthetic cardiac afterload model are compared to those of normal physiology. A method for identification of continuous-time transfer functions from sampled data is developed and verified against results from the literature. The method relies on exact gradients and Hessians obtained through

Prevention of ischemic myocardial contracture through hemodynamically controlled DCD

Purpose—Ischemic myocardial contracture (IMC) or ‘‘stoneheart’’ is a condition with rapid onset following circulatory death. It inhibits transplantability of hearts donated uponcirculatory death (DCD). We investigate the effectiveness of hemodynamic normalization upon withdrawal of life-sustaining therapy (WLST) in a large-animal controlled DCD model, with the hypothesis that reduction in cardiac