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Performance Improvement of a Phase Space Detection Algorithm for Electrocardiogram Wave Morphology Classification

An algorithm based on embedding phase space signal was developed by the authors in previous works. The algorithm detects the characteristic points of the waves of a multilead electroacardiogram (ECG). In the present work, the parameters of this algorithm are optimized to improve its performance. The algorithm uses 2 configurable parameters to obtain the phase spacethe dimension of the phase space

HEp-2 Staining Pattern Classification

Classifying images of HEp-2 cells from indirect immunofluorescence has important clinical applications. We have developed an automatic method based on random forests that classifies an HEp-2 cell image into one of six classes. The method is applied to the data set of the ICPR 2012 contest. The previously obtained best accuracy is 79.3% for this data set, whereas we obtain an accuracy of 97.4%. The

Privacy, Security and Trust in Cloud Computing: The Perspective of the Telecommunication Industry

The telecommunication industry has been successful in turning the Internet into a mobile service and stimulating the creation of a new set of networked, remote services. Most of these services now run or are supported by cloud computing platforms. Embracing cloud computing solutions is fundamental for the telecommunication industry to remain competitive. However, there are many legal, regulatory,

Physical and biological properties of bioaerosol

Bioaerosols include bacterial cells and spores, viruses, pollen, fungi, algae, detritus, allergens and cell fragments. Bioaerosol particles are usually a small fraction of all aerosol particles in our surroundings, but their impact can be critical. They are a means for transmission of disease, they cause allergic reactions and they have effects on the global climate, ecology and biodiversity. This

Software risk analysis in medical device development

The purpose of risk management in the development of safety-critical software is to eliminate or reduce harmful behaviour. In health-care it is essential to manage risk related to software due to its increased use in medical devices and other computer systems. This paper presents some of the experiences gained from an ongoing case study at a large hospital in Sweden. The study focuses on identific

Practical Robust Two-View Translation Estimation

Outliers pose a problem in all real structure from motion systems. Due to the use of automatic matching methods one has to expect that a (sometimes very large) portion of the detected correspondences can be incorrect. In this paper we propose a method that estimates the relative translation between two cameras and simultaneously maximizes the number of inlier correspondences. Traditionally, outlie

Online Spike Detection in Cloud Workloads

We investigate methods for detection of rapid workload increases (load spikes) for cloud workloads. Such rapid and unexpected workload spikes are a main cause for poor performance or even crashing applications as the allocated cloud resources become insufficient. To detect the spikes early is fundamental to perform corrective management actions, like allocating additional resources, before the spi

Generalized Roof Duality for Pseudo-Boolean Optimization

The number of applications in computer vision that model higher-order interactions has exploded over the last few years. The standard technique for solving such problems is to reduce the higher-order objective function to a quadratic pseudo-boolean function, and then use roof duality for obtaining a lower bound. Roof duality works by constructing the tightest possible lower-bounding submodular fun

Using a Gaussian Channel Twice

The problem of communicating one bit over a memoryless Gaussian channel with an energy constraint is discussed. It is assumed that the channel is allowed to be used only two times. An ideal feedback channel is also supposed available. The optimal feedback strategy and the bit-error probability are derived. It is shown that feedback gives a significant performance gain and that the optimal strategy

Increasing Time-Efficiency and Accuracy of Robotic Machining Processes Using Model-Based Adaptive Force Control

Machining processes in the industry of today are rarely performed using industrial robots. In the cases where robots are used, machining is often performed using position control with a conservative feed-rate, to avoid excessive process forces. There is a great benefit in controlling the process forces instead, so as to improve the time-efficiency by applying the maximum allowed force, and thus re

Robustness of the Moore-Greitzer Compressor Model's Surge Subsystem with New Dynamic Output Feedback Controllers

This work presents an extension of a design procedure for dynamic output feedback design for systems with nonlinearities satisfying quadratic constraints. In this work we used an axial gas compressor model described by the 3-state Moore-Greitzer compressor model (MG) that has some challenges for output feedback control design (Planovsky and Nikolaev 1990), (Rubanova 2013). The more general constra

Improving minimum flow rate in wireless mesh networks by effective placement of directional antennas

For some time, directional antennas have been considered to solve connectivity and interference issues in wireless networks. Several scenarios have been presented and often the conclusions drawn are positive, showing increase in capacity. However, to date there has been no effort to assess a holistic picture of the benefit/cost tradeoff and previous work mainly concerns either link scheduling or a

Color-Based Detection Robust to Varying Illumination Spectrum

In color-based detection methods, varying illumination often causes problems, since an object may be perceived to have different colors under different lighting conditions. In the field of color constancy this is usually handled by estimating the illumination spectrum and accounting for its effect on the perceived color. In this paper a method for designing a robust classifier is presented, i.e.,

A Model-Based Framework for Flexible Safety-Critical Software Development - A Design Study

This paper presents the findings from a design study of a model-based framework for safety-critical software development, called SimPal. The objective of the study was to better understand the necessary properties of such a framework and to learn more about the challenges of realizing it. Our research approach can be labeled as design research, which means that we try to answer our research questi

Enhancement of Human Operator's Perceptual Sensitivity for Telesurgical Systems via Polytopic System Approach

A suturing including knot tying is one of the more difficult operations to learn in telesurgical systems. Apprentice surgeons commonly suffer from suture breakage or knot failure. The difficulty, generally, comes from the absence of feedback of interaction force cues in a medical device (e.g., a needle and a thread) . Even if there is haptic feedback to the operator, the operator may have a diffic

Modeling and Identification of Position and Temperature Dependent Friction Phenomena without Temperature Sensing

This paper investigates both positional dependence in systems with friction and the influence an increase in temperature has on the friction behavior. The positional dependence is modeled with a Radial Basis Function network and the temperature dependence is modeled as a first order system with the power loss due to friction as input, eliminating the need for temperature sensing. The proposed meth