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Knowledge Acquisition, Representation, Processing & Presentation (KARPP)

Knowledge Acquisition, Representation, Processing & Presenta...

IEEE International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision Support (CogSIMA)

作者： Kenneth J. Hintz James Llinas Kari Sentz Mechanical and Aerospace Engineering Dept. State University of NY at Buffalo Buffalo NY USA Industrial and Systems Engineering Dept. State University of NY at Buffalo Buffalo NY USA Computer Computational and Statistical Sciences Division Los Alamos National Laboratory Los Alamos NM USA

ISBN: (数字)9798350362817

ISBN: (纸本)9798350362824

Knowledge Acquisition, Representation, Processing, & Presentation (KARPP) is a new system level approach to the acquisition and aggregation of mission-valued and qualified situation knowledge for use by a decision maker. KARPP is decomposed into a service oriented architecture (SOA) of knowledge aggregation services (KAS) with well-defined inputs and outputs which are implemented in hidden processes. The transfer of knowledge from one KAS to another is through a qualified knowledge request (QKR) which results in an aggregated knowledge response (AKR). The notion of qualified knowledge is introduced to specify the knowledge that is needed by a requesting KAS as well as the knowledge quality attributes and the magnitude of those qualities which are required to meet mission needs. The goals of this approach are to provide an architectural framework for realizing managed, adaptive fusion processing capabilities, and to integrate the sensor/database control and data acquisition with the fusion-based data processing which will maximize the expected knowledge value rate (EKVR) provided to mission managers.

关键词： Knowledge acquisition Data acquisition Process control Data processing Service-oriented architecture

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MDI-QKD with resource-efficient polarization compensation

MDI-QKD with resource-efficient polarization compensation

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2023 Optical Fiber Communications Conference and Exhibition, OFC 2023

作者： Bedroya, Olinka Li, Chenyang Wang, Wenyuan Hu, Jianyong Lo, Hoi-Kwong Qian, Li University of Toronto Centre for Quantum Information and Quantum Control Dept. of Physics TorontoONM5S 3G4 Canada University of Toronto Centre for Quantum Information and Quantum Control Dept. of Electrical & Computer Engineering TorontoONM5S 3G4 Canada University of Hong Kong Department of Physics Pokfulam Hong Kong 100 College St TorontoON1M5G 1L5 Canada

ISBN: (纸本)9781957171180

We implemented MDI-QKD with a novel polarization compensation scheme using discarded bits without reducing the key-sharing cycle or demanding additional resources. Polarization drift was maintained below 0.13 rad over a 40 km unisolated fibre spool for four hours, and the average secret key rate generated was 7.45×10-6bits per pulse. © 2023 The Author(s).

关键词： Polarization

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Evaluation of Deep Training and Adapting Algorithms in Medical with De-Noising EEG 3

Evaluation of Deep Training and Adapting Algorithms in Medic...

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3rd International Conference on Advance Computing and Innovative Technologies in engineering, ICACITE 2023

作者： Abdulwahid, Ali Hadi Karetla, Girija Rani Ganesh, K.V.B. Kumar, A Suresh Radha, K. Shivakumar, K. Southern Technical University Engineering Technical College Control and Automation Engineering Department Basra Iraq Western Sydney University School of Computer Data and Mathematical Sciences Australia Koneru Lakshmaiah Education Foundation KL Business School Guntur Andhra Pradesh India Graphic Era Deemed to Be University Department of CSE India St. Martin's Engineering College Dept. of IT Secunderabad Telangana India SR University School of Computer Science and Artificial Intelligence Warangal Telangana India

ISBN: (纸本)9798350399264

An electroencephalogram that was captured with electrodes placed can easily get contaminated with a variety of artifacts. Here is a comparative of various electroencephalogram (EEG) de-noising techniques. Three alternative techniques are used to eliminate five different kinds of noise, and also the outcomes are evaluated. These three methods are just the Least Mean Square (LMS) technique, the Connected Neural Network, and also the Recursive Least-square (RLS) adaptable algorithm (FCNN). Period charts of the actual EEG signal, the noise EEG signal, and thus the predicted EEG signal are used to display the results. RRMSE and signal-to-noise ratio were utilized to compare the effectiveness of the 3 de-noising strategies in this study. Investigating the model parameters in this case, we discover the FCNN forecasts a better outcome compared to the other two methods. © 2023 IEEE.

关键词： Electroencephalography

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The Continuous-Time Weighted-Median Opinion Dynamics

arXiv

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arXiv 2024年

作者： Han, Yi Chen, Ge Dörfler, Florian Mei, Wenjun Dept. of Mechanics and Engineering Science Peking University Beijing China Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing China Automatic Control Laboratory ETH Zurich Zurich Switzerland

Opinion dynamics models are important in understanding and predicting opinion formation processes within social groups. Although the weighted-averaging opinion-update mechanism is widely adopted as the micro-foundation of opinion dynamics, it bears a non-negligibly unrealistic implication: opinion attractiveness increases with opinion distance. Recently, the weighted-median mechanism has been proposed as a new microscopic mechanism of opinion exchange. Numerous advancements have been achieved regarding this new micro-foundation, from theoretical analysis to empirical validation, in a discretetime asynchronous setup. However, the original discrete-time weighted-median model does not allow for "compromise behavior" in opinion exchanges, i.e., no intermediate opinions are created between disagreeing agents. To resolve this problem, this paper propose a novel continuous-time weighted-median opinion dynamics model, in which agents' opinions move towards the weighted-medians of their out-neighbors' opinions. It turns out that the proof methods for the original discrete-time asynchronous model are no longer applicable to the analysis of the continuous-time model. In this paper, we first establish the existence and uniqueness of the solution to the continuoustime weighted-median opinion dynamics by showing that the weighted-median mapping is contractive on any graph. We also characterize the set of all the equilibria. Then, by leveraging a new LaSalle invariance principle argument, we prove the convergence of the continuous-time weighted-median model for any initial condition and derive a necessary and sufficient condition for the convergence to *** Codes 91D30(Primary) 93A16(Secondary) Copyright © 2024, The Authors. All rights reserved.

关键词： Dynamics

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Service Oriented Architecture For Knowledge Acquisition and Aggregation

Service Oriented Architecture For Knowledge Acquisition and ...

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IEEE International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision Support (CogSIMA)

ISBN: (数字)9798350362817

ISBN: (纸本)9798350362824

Situation management involves the acquisition and dissemination of knowledge to effect situation awareness and assessment. In a companion paper, the concept of Knowledge Acquisition, Representation, Processing, & Presentation (KARPP) system has been introduced. In that paper, it was proposed to manage an adaptive data fusion process including the decomposition of a sensor and database knowledge acquisition and aggregation system into a service oriented architecture (SOA) of knowledge aggregation services (KAS) with standards-based inputs and outputs which are implemented in hidden processes. This paper reviews current approaches to SOA and expands the KARPP architecture into a taxonomy of required and support services as well as discusses particulars of a self-organizing implementation of KARPP in a dynamic SOA of microservices. In addition to a taxonomy of services, a self-documenting approach is introduced to allow for preplanned product improvement (PPI) and incremental development as well as the concept of a Knowledge Aggregation System Service broker.

关键词： Adaptive systems Reviews Databases Knowledge acquisition Taxonomy Microservice architectures Data integration

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A Visual Servoing Strategy for Coastline Tracking using an Unmanned Aerial Vehicle

A Visual Servoing Strategy for Coastline Tracking using an U...

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Mediterranean Conference on control and Automation (MED)

作者： Sotirios N. Aspragkathos George C. Karras Kostas J. Kyriakopoulos Control Systems Lab School of Mechanical Engineering National Technical University of Athens Athens Greece Dept. of Computer Science and Telecommunications University of Thessaly Lamia Greece

ISBN: (数字)9781665406734

ISBN: (纸本)9781665406741

In this paper, an Image-based Visual Servo (IBVS) control strategy for the autonomous surveillance of coastlines using an octocopter aerial vehicle is proposed. The implemented strategy is focused on the vision-based detection and tracking of dynamic coastlines and in the presence of waves while flying in low altitudes. For this purpose, a Deep Neural Network (DNN) for the detection of the coastline is employed. The DNN is ac-companied by an analytical formulation of an Extended Kalman Filter (EKF), which considers an approximate periodical wave motion model to provide an online estimate of the coastline motion directly in image space. The estimated feedback is provided to an appropriately formulated IBVS tracking controller for the autonomous guidance of the octocopter along the coastline, ensuring the latter is always kept inside the camera’s field of view. The efficacy of the proposed scheme is demonstrated via a set of comparative outdoor experiments using an octocopter flying along the coastline on various weather and beach settings.

关键词： Visualization Tracking Trajectory planning Surveillance Neural networks Estimation Visual servoing

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A Deep Reinforcement Learning Motion control Strategy of a Multi-rotor UAV for Payload Transportation with Minimum Swing

A Deep Reinforcement Learning Motion Control Strategy of a M...

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Mediterranean Conference on control and Automation (MED)

作者： Fotis Panetsos George C. Karras Kostas J. Kyriakopoulos School of Mechanical Engineering Control Systems Lab National Technical University of Athens Athens Greece Dept. of Computer Science and Telecommunications University of Thessaly Lamia Greece

ISBN: (数字)9781665406734

ISBN: (纸本)9781665406741

This paper addresses the problem of controlling a multirotor UAV with a cable-suspended load. In order to ensure the safe transportation of the load, the swinging motion, induced by the strongly coupled dynamics, has to be minimized. Specifically, using the Twin Delayed Deep Deterministic Policy Gradient (TD3) Reinforcement Learning algorithm, a policy Neural Network is trained in a model-free manner which navigates the vehicle to the desired waypoints while, simultaneously, compensating for the load oscillations. The learned policy network is incorporated into the cascaded control architecture of the autopilot by replacing the common PID position controller and, thus, communicating directly with the inner attitude one. The performance of the proposed policy is demonstrated through a comparative simulation and experimental study while using an octorotor UAV.

关键词： Navigation Attitude control Transportation Reinforcement learning Water pollution Autopilot Sensors

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Multi-layer network modelling of genomic and transcriptomic data to investigate the response to checkpoint inhibitors in NSCLC

Multi-layer network modelling of genomic and transcriptomic ...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Davide Mascolo Lorenzo Farina Manuela Petti MSc Program in Data Science Sapienza University of Rome Rome Italy Dept. of Computer Control and Management Engineering Sapienza University of Rome Rome Italy

Recent innovations and developments in molecular biology and biotechnology have made it possible to acquire and store large omics datasets. In particular genomics, transcriptomics and the study of their relationship represent the key elements to understand how genotype influences phenotype. In this work we investigate the potential of multi-layer network modeling in integrating genomic and transcriptomic data of 152 advanced non-small cell lung cancer (NSCLC) patients treated with anti-PD-(L)1 therapy. For the transcriptomic layer, we performed differential expression and differential co-expression analyses in order to identify a subset of key genes in differentiating responder patients from non-responders. Adding to the genomic-transcriptomic model other three layers related to immune, myeloid and curated immunotherapy-based literature signatures we obtained a 5-layer Patient Similarity Network. The application of Similarity Network Fusion algorithm revealed a statistically significant stratification of patients (p-value ≤ 0.05) which allows the identification of two clusters characterized by patients responding and not responding to immunotherapy.

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An Intelligent Battery Management System for an Electric Vehicle Powered by Solar PV Array

An Intelligent Battery Management System for an Electric Veh...

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International Universities Power engineering Conference (UPEC)

作者： Ali Falih Challoob Nur Azzammudin Bin Rahmat Vigna K. Ramachandaramurthy Nagham Saeed Amjad Jaleel Humaidi Institute of Power Engineering Universiti Tenaga Nasional Strategic Planning Centre Malaysia School of Computing and Engineering University of West London London United Kingdom Control and Systems Eng. Dept. University of Technology Baghdad Iraq

ISBN: (数字)9798350379730

ISBN: (纸本)9798350379747

Implementing a Battery Management System (BMS) in Electric Vehicles (EVs) offers several benefits that enhance the efficiency, security, and durability of the vehicle's battery system. The BMS oversees and controls the performance of each cell in the battery pack, guaranteeing that they function within predetermined voltage and temperature thresholds to maintain safety. In this paper, an intelligent BMS for an EV model powered by a solar PV array was proposed using a fuzzy logic (FL) controller. The proposed method was applied to EVs consisting of four Lithium-ion batteries. The simulation results are achieved using MATLAB/Simulink software. The estimation of the state of charge (SOC) for each battery was used as input to the FL which controls the discharging/ charging mode for each battery via power semiconductor switches. Three different scenarios are used to verify the suggested method. A full control FL operation was obtained, and the batteries were protected successfully against overcharging and over-discharging.

关键词： Fuzzy logic Lithium-ion batteries Battery management systems Electric vehicles Threshold voltage Software Temperature control State of charge MATLAB Voltage control

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Analysis of Equilibrium Point and Genetic Algorithm Design of Observer-Based PID controller for Membrane Bioreactor

Analysis of Equilibrium Point and Genetic Algorithm Design o...

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2021 International Automatic control Conference, CACS 2021

作者： Changsila, Yanita Banjerdpongchai, David Intelligent Control Automation of Process Systems Research Unit Dept. of Electrical Engineering Faculty of Engineering Chulalongkorn University 254 Phayathai Road Pathumwan Bangkok10330 Thailand

ISBN: (纸本)9781665444125

The operation of most wastewater treatment systems is an open-loop system. There is limited feedback control of membrane bioreactors (MBR) which makes it impossible to regulate the quality of the treated water. The objectives of this paper are twofold. First, we analyze the equilibrium point of the MBR nonlinear model. Second, we utilize output feedback control with state observer and design optimal PID controllers. We determine the optimum equilibrium point and derive a linearized model of MBR. Then, we design the state observer to estimate the non-measurable state using the pole placement method. Both the measurable output and estimated state are fed back through PID controller. The objectives of PID control consist of stabilization and performance improvement. Genetic Algorithm is applied to find the optimal PID parameters that minimize the integral of absolute error and satisfy the specified time-domain criteria. We apply the observer-based PID controller to the linearized model of MBR. Numerical results demonstrate the design of PID controller and the improvement of the closed-loop response and quality of the treated water. © 2021 IEEE

关键词： Bioreactors

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