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41st Computing in Cardiology Conference (CinC)

作者： Firoozabadi, Reza Gregg, Richard E. Zengo, Beth Babaeizadeh, Saeed Philips Healthcare Adv Algorithm Res Ctr Andover MA USA

ISBN: (纸本)9781479943463

In this paper, we present a novel algorithm to evaluate the quality of ECG recordings. Our algorithm is designed to help clinicians in rapid selection of good quality ECG segments from long recordings collected by an ECG monitoring device such as a 12-lead bedside monitor. With some adjustments, we used the Computing in Cardiology Challenge 2011 database in order to compare the performance of our algorithm to the published results. The challenge was aimed to develop near real-time algorithms in mobile phones and provide feedback on quality of the ECGs for interpretation to the users who are mostly laypersons with little knowledge of ECG interpretation. Our algorithm generates a noise score which is a combination of two parameters: a high-frequency noise measure which accounts for the muscle noise and other fast changing artifacts, and a baseline wander noise measure quantifying the low-frequency noise. The training dataset (set A) with reference quality assessments was used to determine an optimum threshold on the ROC curve for classification of acceptable and unacceptable segments. The algorithm was then evaluated on the test dataset (set B) with undisclosed annotations. Our method achieved maximum accuracy of 93.9% on the training dataset and an accuracy of 90.2% on the test dataset, placing itself among the top 10 performers who participated in the challenge.

关键词： electrocardiography medical signal processing real-time systems sensitivity analysis 12-lead ECG recording ROC curve automatic real-time quality assessment baseline wander noise measure electrocardiogram high-frequency noise measure low-frequency noise mobile phones muscle noise real-time algorithms Abstracts Accuracy Classification algorithms Gold Lead Muscles Noise

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Traveling Waves in the Human EEG during Voluntary Hand Movements

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Neuroscience and Behavioral Physiology 2015年第9期45卷 1043-1054页

作者： Belov, D.R. Stepanova, P.A. Kolodyazhnyi, S.F. Department of Higher Nervous Activity and Psychophysiology St. Petersburg State University St. Petersburg Russian Federation

The trajectories of EEG traveling waves linked with movements of the right hand in a defined direction were recorded. A rectangle of 28 electrodes was positioned above the sensorimotor cortex, with seven electrodes in each row. A two-dimensional center-out reaching task was used. Targets appeared at the edge of the screen at random time intervals of 0.5–2.5 sec, with equal probabilities of appearing at the left, right, top, or bottom. The task was to use a joystick to move the cursor to touch the target, moving the cursor in one direction from the center to the edge. EEG traces were analyzed from the appearance of the target until it was touched. Spontaneous EEG waves showed phase anticipation in a local area of the left sensorimotor cortex and the posterior central parietal cortex on downward cursor movement (pulling movement of hand on joystick) as compared with the resting state and movements in the other three directions. time smoothing of phase shift data using a sliding mean revealed otherwise cryptic constant components in the EEG resembling summation of evoked potentials. © 2015, Springer Science+Business Media New York.

关键词： electroencephalogram movement decoding reaching task real-time algorithms traveling (spreading) wave

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From Closing Triangles to Higher-Order Motif Closures for Better Unsupervised Online Link Prediction 21

From Closing Triangles to Higher-Order Motif Closures for Be...

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30th ACM International Conference on Information and Knowledge Management (CIKM)

作者： Rossi, Ryan A. Rao, Anup Kim, Sungchul Koh, Eunyee Ahmed, Nesreen K. Wu, Gang Adobe Res San Francisco CA 94107 USA Intel Labs Santa Clara CA USA

ISBN: (纸本)9781450384469

This paper introduces higher-order link prediction methods based on the notion of closing higher-order network motifs. The methods are fast and efficient for real-time ranking and link prediction-based applications such as online visitor stitching, web search, and online recommendation. In such applications, real-time performance is critical. The proposed methods do not require any explicit training data, nor do they derive an embedding from the graph data, or perform any explicit learning. Most existing unsupervised methods with the above desired properties are all based on closing triangles (common neighbors, Jaccard similarity, and the ilk). In this work, we develop unsupervised techniques based on the notion of closing higher-order motifs that generalize beyond closing simple triangles. Through extensive experiments, we find that these higher-order motif closures often outperform triangle-based methods, which are commonly used in practice. This result implies that one should consider other motif closures beyond simple triangles. We also find that the "best" motif closure depends highly on the underlying network and its structural properties. Furthermore, all methods described in this work are fast for link prediction-based applications requiring real-time performance. The experimental results indicate the importance of closing higher-order motifs for unsupervised link prediction. Finally, these new higher-order motif closures can serve as a basis for studying and developing better unsupervised real-time link prediction and ranking methods.

关键词： Motif closure higher-order motif closure unsupervised link prediction network motifs graphlets real-time algorithms higher-order link prediction online algorithms

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Decomposing Two-Stage Stochastic Scheduling Problems on a continuous-time basis via Slot Similarity 22

Decomposing Two-Stage Stochastic Scheduling Problems on a co...

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22nd World Congress of the International Federation of Automatic Control (IFAC)

作者： Montes, Daniel Pitarch, Jose Luis de Prada, Cesar Univ Valladolid Dept Syst Engn & Automat Control Valladolid Spain Univ Politecn Valencia Inst Univ Automat & Informat Ind Ai2 Valencia Spain Univ Valladolid Inst Sustainable Proc Valladolid Spain

ISBN: (纸本)9781713872344

Incorporating uncertainty into process scheduling by explicitly considering future forecasts is crucial for achieving optimal and feasible solutions in practice. However, the complexity of two-stage stochastic scheduling formulations increases exponentially with the number of scenarios, making it difficult to solve large-scale problems in real-time using mathematical programming, which is often necessary for production-maintenance scheduling. This is where decomposition strategies on a scenario basis can be advantageous. Recently, the authors developed a method for decomposing two-stage scheduling problems (TSSPs) formulated on a discrete-time basis using the Similarity Index. This paper extends this concept to TSSPs formulated on a continuous-time basis by fuzzifying discrete decisions among slots instead of time periods, and incorporating the progressive-hedging algorithm to manage non-anticipativity in continuous decisions. The proposed algorithm is tested in a case study of a multiproduct plant consisting of a single processing unit from the literature. Results show that the proposed decomposition algorithm solves the problem faster than the monolithic formulation. Copyright (c) 2023 The Authors.

关键词： Efficient strategies for large-scale complex systems Modelling and decision-making in complex systems Two-Stage Stochastic Scheduling Decomposition Algorithm real-time algorithms scheduling and programming

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Towards a Robust, real-time Face Processing System using CUDA-enabled GPUs

Towards a Robust, Real-time Face Processing System using CUD...

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16th International Conference on High Performance Computing (HiPC 2009)

作者： Sharma, Bharatkumar Thota, Rahul Vydyanathan, Naga Kale, Amit Siemens Corp Technol Bangalore Karnataka India

ISBN: (纸本)9781424449217

Processing of human faces finds application in various domains like law enforcement and surveillance, entertainment (interactive video games), information security, smart cards etc. Several of these applications are interactive and require reliable and fast face processing. A generic face processing system may comprise of face detection, recognition, tracking and rendering. In this paper, we develop a GPU accelerated real-time and robust face processing system that does face detection and tracking. Face detection is done by adapting the Viola and Jones algorithm that is based on the Adaboost learning system. For robust tracking of faces across real-life illumination conditions, we leverage the algorithm proposed by Thota and others, that combines the strengths of Adaboost and an image based parametric illumination model. We design and develop optimized parallel implementations of these algorithms on graphics processors using the Compute Unified Device Architecture (CUDA), a C-based programming model from NVIDIA. We evaluate our face processing system using both static image databases as well as using live frames captured from a firewire camera under realistic conditions. Our experimental results indicate that our parallel face detector and tracker achieve much greater detection speeds as compared to existing work, while maintaining accuracy. We also demonstrate that our tracking system is robust to extreme illumination conditions.

关键词： Parallel computing face detection face tracking graphics processors real-time algorithms

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Fast Allan Variance (FAVAR) and Dynamic Fast Allan Variance (D-FAVAR) algorithms for both Regularly and Irregularly Sampled Data

Fast Allan Variance (FAVAR) and Dynamic Fast Allan Variance ...

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Modeling, Estimation and Control Conference (MECC)

作者： Maddipatla, Satya Prasad Haeri, Hossein Jerath, Kshitij Brennan, Sean Penn State Univ University Pk PA 16802 USA Univ Massachusetts Lowell Lowell MA 01854 USA

This work develops algorithms demonstrating fast implementations of Allan variance (AVAR) for regularly and irregularly sampled signals. AVAR is a technique first developed to study the frequency stability of atomic clocks. Typical AVAR algorithms calculate changes in means between differently-sized groupings of data and thus are useful in many data aggregation processes: to select the appropriate window length or timescales for estimating a signal's moving average, to find the minimum variance of a signal, or to estimate the change in variance of a signal with complex noise contributions as a function of the number of collected data points. Unfortunately, AVAR typically involves very large signal lengths, yet the typical time required to compute AVAR increases quickly with the length of the time-series data. This paper presents a recursive algorithm inspired by the Fast Fourier Transform (FFT), specifically data organization into power-of-two groupings. This enables a fast AVAR implementation, called FAVAR, shown first for regularly sampled data. The results show a computational speed increase of three orders of magnitude versus typical AVAR calculations for data lengths often used with AVAR. Next, the FAVAR algorithm is extended to compute AVAR of irregularly sampled data by modeling these data as weighted but regularly sampled data clusters. Finally, this work analyzes Dynamic Allan variance implementations of FAVAR, called D-FAVAR, wherein AVAR is calculated at every timestep to capture window-varying statistical properties of the data stream. The recursion methods used in FAVAR, when extended to compute D-FAVAR, further increase computational speed by an additional factor of ten compared to computing the FAVAR at every timestep. They result in approximately four orders of magnitude speed improvements versus repeated calculation of AVAR with typical methods. These fast algorithms are demonstrated on signals that illustrate classical Allan variance curves, and th

关键词： Allan variance Dynamic Allan variance real-time algorithms

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Detection of Glucose Sensor Faults in an Artificial Pancreas via Whiteness Test on Kalman Filter Residuals 19

Detection of Glucose Sensor Faults in an Artificial Pancreas...

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19th IFAC Symposium on System Identification (SYSID)

作者： Manzoni, Eleonora Rampazzo, Mirco Del Favero, Simone Univ Padua Dept Informat Engn Via G Gradenigo 6-B I-35131 Padua Italy

Continuous Glucose Monitoring (CGM) sensors are key components in an artificial pancreas, an emerging tool for type 1 diabetes treatment. Malfunctioning of this component might reduce the efficacy of glucose control achieved by the system and even pose the safety of the patient at risk. Therefore, accurate and prompt detection of these anomalies is an important problem. This paper investigates a model-based method to detect CGM failures. Based on an individualized linear model of the subject, identified on hystorical data, the method predicts future glucose concentration through a one-step ahead Kalman predictor. The correct functioning of the system is then monitored using two different criteria: the first checks the magnitude of prediction residuals. The second checks the whiteness of the residuals through a correlogram test. The effectiveness of the two criteria is investigated and compared by performing tests on an in-silico dataset obtained by means of UVA/Padova Type 1 Diabetes simulator, accepted by the US Food and Drug Administration as a substitute of animal testing prior to artificial pancreas clinical trials on humans. Copyright (C) 2021 The Authors.

关键词： Fault detection and diagnosis Biomedical system modeling simulation and visualization Artificial pancreas or organs Statistical methods/signal analysis for FDI real-time algorithms scheduling programming

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Smart Cities: Parking Monitoring through Smart Cameras

Smart Cities: Parking Monitoring through Smart Cameras

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IEEE International Conference on Communications (IEEE ICC)

作者： Leone, Giuseppe Riccardo Moroni, Davide Pieri, Gabriele Natl Res Council Italy CNR Inst Informat Sci & Technol ISTI Pisa Italy

ISBN: (纸本)9781728123738

One of today's major problems in medium to large cities is pollution caused by urban traffic. There are various factors that negatively affect this problem. First of all, the constant increase in vehicles, and at the same time the reduction, for budget reasons, of the number of free parking areas more or less easily reached. Moreover, due to global events such as the economic crisis, there is a general reduction in the efficiency of local public transport. In this research, we present an approach to this problem that exploits the greater availability of IT structures and devices. The solution presented offers the possibility of improving one of the most burdensome aspects, namely the traffic generated by cars looking for a parking space through an integrated and automatic management of employment levels. The procedure is based on wireless smart cameras for monitoring public outdoor parking areas. The main strengths of this solution lie in the independence and scalability of the proposed architecture. Independence is ensured by the node's modus operandi, in which processing is performed on board the intelligent camera without the need for a video stream or operator intervention. Scalability can be achieved by designing low-cost nodes that can be connected in a sensor network that does not require high installation costs. Moreover, the possibility of making such processing nodes autonomous through the use of a photovoltaic panel allows them to be installed in even more flimsy situations.

关键词： real-time algorithms Embedded systems Intelligent sensors Wireless Sensor Networks Smart cities Smart cameras Vision sensors

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Handling traffic loads in a smart junction by social priorities

Handling traffic loads in a smart junction by social priorit...

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IEEE International Conference on Microwaves, Antennas, Communications and Electronic Systems (COMCAS)

作者： Fine, Zohar Brayer, Eran Proshtisky, Idan Barzilai, Orly Voloch, Nadav Steiner, Orna Lavi Coll Acad Studies Or Yehuda Israel

ISBN: (纸本)9781538695494

Smart junctions are the subject of many researches in the past few years. This research deals with the case of a smart intersection, handling traffic loads while taking into consideration different aspects of social prioritization. While learning the problem of traffic and its flow in an optimal way to save time and fuel for all travelers on the way, giving preference to urgent cases (dilemmas) and different types of vehicles (size and number of passengers), creates a more morally accurate picture of the traffic as a human interface. An example of such priority at the junction could be a woman in labor in a private vehicle, that is not formally prioritized since it is not an emergency vehicle. Traffic lights around the world are based on orderly programming of passage between the different traffic directions. The technology that measures the amount of traffic can change the duration of green light that is activated or even skip an instance of passage in case of sensor detection of an empty lane. Our research and system, presented in this paper, unlike all other systems, is not based on a specific order of traffic flow at the junction, but reopens each sample and analyzes the junction by its passenger data, prioritizing the social aspect of the vehicle's travelers. The system performs each sampling in a certain time period by the physical aspect of the vehicle and uses a prioritization system, which performs a parametric calculation of these social aspects. The system checks all the possibilities of allowing green light for larger traffic and considers the criteria for prioritizing a traffic load. The algorithm that was developed for this system can calculate each green time according to real-time data of the junction's vehicles and chooses the optimal traffic route, accordingly.

关键词： Smart Junction Internet of Things (IoT) real-time algorithms social dilemmas in IoT

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A Distributed Framework for real time Path Planning in Practical Multi-agent Systems

A Distributed Framework for Real Time Path Planning in Pract...

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20th World Congress of the International-Federation-of-Automatic-Control (IFAC)

作者： Abdelkader, Mohamed Jaleel, Hassan Shamma, Jeff S. King Abdullah Univ Sci & Technol Phys Sci & Engn Thuwal Saudi Arabia King Abdullah Univ Sci & Technol Comp Elect & Math Sci & Engn CEMSE Div Thuwal Saudi Arabia

We present a framework for distributed, energy efficient, and real time implementable algorithms for path planning in multi-agent systems. The proposed framework is presented in the context of a motivating example of capture the flag which is an adversarial game played between two teams of autonomous agents called defenders and attackers. We start with the centralized formulation of the problem as a linear program because of its computational efficiency. Then we present an approximation framework in which each agent solves a local version of the centralized linear program by communicating with its neighbors only. The premise in this work is that for practical multi-agent systems, real time implementability of distributed algorithms is more crucial then global optimality. Thus, instead of verifying the proposed framework by performing offline simulations in MATLAB, we run extensive simulations in a robotic simulator V-REP, which includes a detailed dynamic model of quadrotors. Moreover, to create a realistic scenario, we allow a human operator to control the attacker quadrotor through a joystick in a single attacker setup. These simulations authenticate that the proposed framework is real time implementable and results in a performance that is comparable with the global optimal solution under the considered scenarios. (C) 2017, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Cooperative systems Coordination of multiple vehicle systems Control under communication constraints real-time control real-time algorithms scheduling and programming

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