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International Conference on Advanced Information and Communication Technologies (AICT)

作者： Vladislav Pariy Khrystyna Lipianina-Honcharenko Ruslan Brukhanskyi Anatoliy Sachenko Fedir Tkachyk Dmytro Lendiuk Department for Information Computer Systems and Control West Ukrainian National University Ternopil Ukraine Department of Business Analytics and Innovative Engineering West Ukrainian National University Ternopil Ukraine Research Institute for Intelligent Computer Systems West Ukrainian National University Ternopil Ukraine Department of Informatics and Teleinformatics Kazimierz Pulaski University of Technology and Humanities in Radom Radom Poland Department of Taxes and Fiscal Policy West Ukrainian National University Ternopil Ukraine

This article is devoted to the development of Intelligent Verbal Interaction Methods with Non-Player Characters in Metaverse Applications. The creation of a character model using MetaHuman Creator and the implementation of dialogue animation are considered. The construction of answers based on text analysis and their submission to the chat window is described. The system has been tested and found to be stable and have a satisfactory response time of approximately 2 seconds. The results show the successful implementation of methods of verbal interaction with non-game characters in metaverse, which can be useful for further research and development in this area.

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Constrained Optimization with Decision-Dependent Distributions

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IEEE Transactions on Automatic control 2025年

作者： Wang, Zifan Liu, Changxin Parisini, Thomas Zavlanos, Michael M. Johansson, Karl H. KTH Royal Institute of Technology Division of Decision and Control Systems School of Electrical Engineering and Computer Science Sweden Digital Futures StockholmSE-10044 Sweden East China University of Science and Technology Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of Education Shanghai200237 China Imperial College London Department of Electrical and Electronic Engineering LondonSW7 2AZ United Kingdom Aalborg University Department of Electronic Systems Denmark University of Trieste Department of Engineering and Architecture Italy Duke University Department of Mechanical Engineering and Materials Science DurhamNC United States

In this paper we deal with stochastic optimization problems where the data distributions change in response to the decision variables. Traditionally, the study of optimization problems with decision-dependent distributions has assumed either the absence of constraints or fixed constraints. This work considers a more general setting where the constraints can also dynamically adjust in response to changes in the decision variables. Specifically, we consider linear constraints and analyze the effect of decision-dependent distributions in both the objective function and constraints. Firstly, we establish a sufficient condition for the existence of a constrained equilibrium point, at which the distributions remain invariant under retraining. Moreover, we propose and analyze two algorithms: repeated constrained optimization and repeated dual ascent. For each algorithm, we provide sufficient conditions for convergence to the constrained equilibrium point. Furthermore, we explore the relationship between the equilibrium point and the optimal point for the constrained decision-dependent optimization problem. Notably, our results encompass previous findings as special cases when the constraints remain fixed. To show the effectiveness of our theoretical analysis, we provide numerical experiments on both a market problem and a dynamic pricing problem for parking based on real-world data. © 1963-2012 IEEE.

关键词： Optimization algorithms

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Distributed Computation of Exact Average Degree and Network Size in Finite Number of Steps under Quantized Communication

arXiv

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arXiv 2022年

作者： Rikos, Apostolos I. Charalambous, Themistoklis Hadjicostis, Christoforos N. Johansson, Karl H. The Division of Decision and Control Systems KTH Royal Institute of Technology StockholmSE-100 44 Sweden The Department of Electrical and Computer Engineering University of Cyprus Nicosia1678 Cyprus

We consider the problems of computing the average degree and the size of a given network in a distributed fashion under quantized communication. We present two distributed algorithms which rely on quantized operation (i.e., nodes process and transmit quantized messages), and are able to calculate the exact solutions in a finite number of steps. Furthermore, during the operation of our algorithms, each node is able to determine in a distributed manner whether convergence has been achieved and thus terminate its operation. To the best of the authors’ knowledge these algorithms are the first to find the exact solutions under quantized communication (i.e., there is no error in the final calculation). Additionally, note that our network size calculation algorithm is the first in the literature which calculates the exact size of a network in a finite number of steps without introducing a final error. This error in other algorithms can be either due to quantization or asymptotic convergence. In our case, no error is introduced since the desired result is calculated in the form of a fraction involving a quantized numerator and a quantized denominator. Finally, we demonstrate the operation of our algorithms and their potential advantages. © 2022, CC BY.

关键词： Errors

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control of an Autonomous Energy Complex with Renewable Energy Sources, taking into account the Type of Input Information Uncertainty 4

Control of an Autonomous Energy Complex with Renewable Energ...

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4th International Conference on control in Technical systems, CTS 2021

作者： Simankov, Vladimir S. Buchatskiy, Pavel Yu. Shopin, Andrey V. Teploukhov, Semen V. Buchatskaya, Victoria V. Department of Computer Technologies and Information Security Kuban State Technological University Krasnodar Russia Department of Automated Systems of Processing Information and Control Adyghe State University Maykop Russia Department of Applied Mathematics Information Technology and Information Security Adyghe State University Maykop Russia

ISBN: (纸本)9781665424547

This article discusses the management of autonomous energy complex with renewable energy within the smart grid solutions in terms of different types of input data uncertainty. On the basis of the theory of fuzzy logic and a fuzzy situational network, an approach has been developed that allows one to calculate the type of uncertainty of the input information, and then select the most appropriate mathematical model and control strategy for AEC with RES. © 2021 IEEE.

关键词： Smart power grids

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Distributed Optimal Data Allocation in Finite Time with Efficient Communication and Transmission Stopping over Dynamic Networks

Distributed Optimal Data Allocation in Finite Time with Effi...

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IEEE Conference on Decision and control

作者： Apostolos I. Rikos Christoforos N. Hadjicostis Karl H. Johansson Division of Decision and Control Systems KTH Royal Institute of Technology Stockholm Sweden Digital Futures Stockholm Sweden Department of Electrical and Computer Engineering University of Cyprus Nicosia Cyprus

ISBN: (数字)9781665467612

ISBN: (纸本)9781665467629

In this paper, we focus on the problem of data sharing over a wireless computer network (i.e., a wireless grid). Given a set of available data, we present a distributed algorithm, which operates over a dynamically changing network and allows each node to calculate the optimal allocation of data in a finite number of time steps. We show that our proposed algorithm (i) converges to the optimal solution in finite time with very high probability, and (ii) once the optimal solution is reached, each node is able to cease transmissions without needing knowledge of a global parameter such as the network diameter. Furthermore, our algorithm (i) operates exclusively with quantized values (i.e., each node processes and transmits quantized information), (ii) relies on event-driven updates, and (iii) calculates the optimal solution in the form of a quantized fraction which avoids errors due to quantization. Finally, we demonstrate the operation, performance, and potential advantages of our algorithm over random dynamic networks.

关键词： Wireless communication Knowledge engineering Quantization (signal) Heuristic algorithms Distributed databases Dynamic scheduling computer networks

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control of Reaction-Diffusion Processes Under Communication Delays

Control of Reaction-Diffusion Processes Under Communication ...

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European control Conference (ECC)

作者： Luca Ballotta Juncal Arbelaiz Vijay Gupta Luca Schenato Mihailo R. Jovanović Delft Center for Systems and Control Delft University of Technology Delft The Netherlands Department of Mechanical and Aerospace Engineering Center for Statistics and Machine Learning Princeton University Princeton NJ USA Elmore Family School of Electrical and Computer Engineering Purdue University West Lafayette IN USA Department of Information Engineering University of Padova Padova Italy Ming Hsieh Department of Electrical and Computer Engineering University of Southern California Los Angeles CA USA

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

In this paper we investigate the design of optimal spatially distributed controllers for a linear and spatially invariant reaction-diffusion process over the real line. The controller receives state measurements from different spatial locations with non-negligible delays. In this set-up and for the class of proportional spatially invariant state feedback controllers, the optimal control synthesis problem is equivalent to a feedback gain optimization for a spatially distributed delay system. We show that the spatial locality of optimal feedback gains is affected not only by diffusion and reaction coefficients, but also by the parameter representing communication time-delay that causes a sharp flattening of the control gains. In the expensive control regime, the optimal controller is solved analytically, yielding some practical design guidelines.

关键词： State feedback Delay systems Design methodology Process control Optimal control Europe Delays

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CoNi-MPC: Cooperative Non-inertial Frame Based Model Predictive control

arXiv

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arXiv 2023年

作者： Zhang, Baozhe Chen, Xinwei Li, Zhehan Beltrame, Giovanni Xu, Chao Gao, Fei Cao, Yanjun Huzhou Institute of Zhejiang University Huzhou313000 China State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou310027 China The Chinese University of Hong Kong Shenzhen518172 China Department of Computer Engineering and Software Engineering Poly-technique Montreal Canada

This paper presents a novel solution for UAV control in cooperative multi-robot systems, which can be used in various scenarios such as leader-following, landing on a moving base, or specific relative motion with a target. Unlike classical methods that tackle UAV control in the world frame, we directly control the UAV in the target coordinate frame, without making motion assumptions about the target. In detail, we formulate a nonlinear model predictive controller of a UAV, referred to as the agent, within a non-inertial frame (i.e., the target frame). The system requires the relative states (pose and velocity), the angular velocity and the accelerations of the target, which can be obtained by relative localization methods and ubiquitous MEMS IMU sensors, respectively. This framework eliminates dependencies that are vital in classical solutions, such as accurate state estimation for both the agent and target, prior knowledge of the target motion model, and continuous trajectory re-planning for some complex tasks. We have performed extensive simulations to investigate the control performance with varying motion characteristics of the target. Furthermore, we conducted real robot experiments, employing either simulated relative pose estimation from motion capture systems indoors or directly from our previous relative pose estimation devices outdoors, to validate the applicability and feasibility of the proposed approach. © 2023, CC BY.

关键词： Unmanned aerial vehicles (UAV)

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Matrix Completion over Finite Fields: Bounds and Belief Propagation Algorithms

arXiv

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arXiv 2023年

作者： Soleymani, Mahdi Liu, Qiang Mahdavifar, Hessam Balzano, Laura Halıcıoglu Data Science Institute University of California San Diego United States The State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou310027 China The Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor United States

We consider the low rank matrix completion problem over finite fields. This problem has been extensively studied in the domain of real/complex numbers, however, to the best of authors' knowledge, there exists merely one efficient algorithm to tackle the problem in the binary field, due to Saunderson et al. [1]. In this paper, we improve upon the theoretical guarantees for the algorithm provided in [1]. Furthermore, we formulate a new graphical model for the matrix completion problem over the finite field of size q, Fq, and present a message passing (MP) based approach to solve this problem. The proposed algorithm is the first one for the considered matrix completion problem over finite fields of arbitrary size. Our proposed method has a significantly lower computational complexity, reducing it from O(n2r+3) in [1] down to O(n2) (where, the underlying matrix has dimension n × n and r denotes its rank), while also improving the performance. Copyright © 2023, The Authors. All rights reserved.

关键词： Message passing

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Optimizing machine learning algorithms to enhance blood donation for liver patients: a case study

Optimizing machine learning algorithms to enhance blood dona...

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7th IET Smart Cities Symposium (SCS 2023)

作者： Maad M. Mijwil El-Sayed M. El-kenawy Indu Bala Mohammad Aljanabi Mostafa Abotaleb Abdelhameed Ibrahim Computer Techniques Engineering Department Baghdad College of Economic Sciences University Baghdad Iraq Department of Communications and Electronics Delta Higher Institute of Engineering and Technology Egypt School of Electrical and Electronics Engineering Lovely Professional University Punjab India Department of Computer Aliraqia University Baghdad Iraq Department of System Programming South Ural State University Chelyabinsk Russia Computer Engineering and Control Systems Department Faculty of Engineering Mansoura University Mansoura Egypt

Blood is vital for transporting oxygen, nutrients, and hormones to all body parts as it circulates through arteries and veins. It removes carbon dioxide, regulates body temperature, and maintains the body's immune system. Individuals constantly need blood and its derivatives to save their lives and improve their health through medical treatments and surgical operations. Liver diseases are one of the diseases that affects the health of individuals and requires blood to continue living. These diseases cause significant damage to people's health, and early diagnosis plays a crucial role in saving lives. In this paper, machine learning algorithms (support vector machine and random forest) are involved in detecting liver diseases and determining whether donors are suitable to donate blood from blood values. This paper is applied research that found that the performance measures of the random forest algorithm achieved excellent performance in identifying suitable people to donate blood.

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Suppressing the endemic equilibrium in SIS epidemics: A state dependent approach

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IFAC-PapersOnLine 2021年第15期54卷 163-168页

作者： Yuan Wang Sebin Gracy Hideaki Ishii Karl Henrik Johansson Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology and Digital Futures Stockholm Sweden Department of Computer Science Tokyo Institute of Technology Yokohama Japan

This paper considers the susceptible-infected-susceptible (SIS) epidemic model with an underlying network structure and focuses on the effect of social distancing to regulate the epidemic level. We demonstrate that if each subpopulation is informed of its infection rate and reduces interactions accordingly, the fraction of the subpopulation infected stays below half for all time instants. To this end, we first modify the basic SIS model by introducing a state dependent parameter representing the frequency of interactions between subpopulations. Thereafter, we show that for this modified SIS model, the spectral radius of a suitably-defined matrix being not greater than one causes all the agents, regardless of their initial sickness levels, to converge to the healthy state; assuming non-trivial disease spread, the spectral radius being greater than one leads to the existence of a unique endemic equilibrium, which is also asymptotically stable. Finally, by leveraging the aforementioned results, we show that the fraction of (sub)populations infected never exceeds half.

关键词： Epidemic processes Infection reduction Characterization of endemic equilibrium Suppressing endemic equilibrium

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