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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Shang, Jun Zhang, Hanwen Zhou, Jing Chen, Tongwen Tongji University Shanghai Research Institute for Intelligent Autonomous Systems National Key Laboratory of Autonomous Intelligent Unmanned Systems Frontiers Science Center for Intelligent Autonomous Systems Department of Control Science and Engineering Shanghai200092 China University of Science and Technology Beijing Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education School of Automation and Electrical Engineering Beijing100083 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 1H9 Canada

ISBN: (纸本)9798350316339

This study addresses linear attacks on remote state estimation within the context of a constrained alarm rate. Smart sensors, which are equipped with local Kalman filters, transmit innovations instead of raw measurements through a wireless communication network. This transmission is vulnerable to malicious data interception and manipulation by attackers. The aim of this research is to identify the optimal attack strategy that degrades the system performance while adhering to stealthiness constraints. A notable innovation of this paper is the direct association of the attack's stealthiness with the alarm rate, diverging from traditional approaches that rely on the covariance of the innovation or the Kullback-Leibler divergence, which are conventional metrics that have been extensively explored in previous studies. Our findings reveal that the optimal attack strategy exhibits some structural characteristics in systems of low dimensions. The performance of the proposed attack strategy is demonstrated through numerical examples. © 2024 IEEE.

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Optimal Linear Deception Attacks on Remote State Estimation with Constrained Alarm Rates: A Low-Dimensional Case

Optimal Linear Deception Attacks on Remote State Estimation ...

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IEEE Conference on Decision and Control

作者： Jun Shang Hanwen Zhang Jing Zhou Tongwen Chen Department of Control Science and Engineering Shanghai Research Institute for Intelligent Autonomous Systems National Key Laboratory of Autonomous Intelligent Unmanned Systems and Frontiers Science Center for Intelligent Autonomous Systems Tongji University Shanghai China Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing China Department of Electrical and Computer Engineering University of Alberta Edmonton AB Canada

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

This study addresses linear attacks on remote state estimation within the context of a constrained alarm rate. Smart sensors, which are equipped with local Kalman filters, transmit innovations instead of raw measurements through a wireless communication network. This transmission is vulnerable to malicious data interception and manipulation by attackers. The aim of this research is to identify the optimal attack strategy that degrades the system performance while adhering to stealthiness constraints. A notable innovation of this paper is the direct association of the attack’s stealthiness with the alarm rate, diverging from traditional approaches that rely on the covariance of the innovation or the Kullback–Leibler divergence, which are conventional metrics that have been extensively explored in previous studies. Our findings reveal that the optimal attack strategy exhibits some structural characteristics in systems of low dimensions. The performance of the proposed attack strategy is demonstrated through numerical examples.

关键词： Wireless communication Measurement Technological innovation System performance Kalman filters State estimation intelligent sensors

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Operational strategies for a photovoltaic-thermal system integrated with an electric air-to-water heat pump

Operational strategies for a photovoltaic-thermal system int...

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International Conference on Energy Transition in the Mediterranean Area (SyNERGY MED)

作者： Giuseppe Russo Andreas V. Olympios Chandan Pandey Annamaria Buonomano Christos N. Markides Department of Chemical Engineering Clean Energy Processes (CEP) Laboratory and Sargent Centre for Process Systems Engineering Imperial College London UK Department of Industrial Engineering University of Naples Federico II Naples Italy Department of Electrical and Computer Engineering PV Technology Laboratory University of Cyprus Nicosia Cyprus PHAETHON Centre of Excellence for Intelligent Efficient and Sustainable Energy Solutions Nicosia Cyprus

ISBN: (数字)9798350375923

ISBN: (纸本)9798350375930

In this study, operational strategies are investigated for an air-based photovoltaic-thermal (PV-T) system integrated with a domestic air-to-water heat pump. The PV-T system is used to simultaneously generate electricity and heat ambient air, which serves as the heat source for the heat pump. By utilising a variable-speed fan to regulate airflow, the PV-T system outlet temperature is adjusted, and the focus is on how different outlet temperatures impact the PVT system electrical and thermal efficiency, heat pump performance, and overall electricity requirements for heating. The performance of the integrated system is assessed for a case study of a household application in north Italy. The optimal PV-T outlet temperature is found to be between 30 – 35 °C, resulting in only 5% less electricity production than an equivalent PV system with equal nominal electricity capacity, while reducing overall electricity required for heating by over 15% compared to PV-integrated heat pumps.

关键词： Photovoltaic systems Fans Temperature Heat pumps Electricity Buildings Water heating Production Temperature control Resistance heating

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Accurately predicting anticancer peptide using an ensemble of heterogeneously trained classifiers

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Informatics in Medicine Unlocked 2023年 42卷

作者： Azim, Sayed Mehedi Sabab, Noor Hossain Nuri Noshadi, Iman Alinejad-Rokny, Hamid Sharma, Alok Shatabda, Swakkhar Dehzangi, Iman Center for Computational and Integrative Biology Rutgers University Camden 08102 NJ United States Department of Computer Science and Engineering United International University Plot 2 United City Madani Avenue BaddaDhaka 1212 Bangladesh Department of Bioengineering University of California Riverside 92507 CA United States BioMedical Machine Learning Lab The Graduate School of Biomedical Engineering The University of New South Wales (UNSW Sydney) Sydney NSW 2052 Australia UNSW Data Science Hub UNSW Sydney Sydney NSW 2052 Australia Health Data Analytics Program AI-enabled Processes Research Centre Macquarie University Sydney 2109 Australia Institute for Integrated and Intelligent Systems Griffith University Brisbane Australia Laboratory for Medical Science Mathematics RIKEN Center for Integrative Medical Sciences Yokohama 230-0045 Japan Department of Computer Science Rutgers University Camden 08102 NJ United States

The use of therapeutic peptides for the treatment of cancer has received tremendous attention in recent years. Anticancer peptides (ACPs) are considered new anticancer drugs which have several advantages over chemistry-based drugs including high specificity, strong tumor penetration capacity, and low toxicity level for normal cells. Due to the rise of experimentally verified bioactive peptides, several in silico approaches became imperative for the investigation of the characteristics of ACPs. In this paper, we proposed a new machine learning tool named iACP-RF that uses a combination of several sequence-based features and an ensemble of three heterogeneously trained Random Forest classifiers to accurately predict anticancer peptides. Experimental results show that our proposed model achieves an accuracy of 75.9% which outperforms other state-of-the-art methods by a significant margin. We also achieve 0.52, 75.6%, and 76.2% in terms of Matthews Correlation Coefficient (MCC), Sensitivity, and Specificity, respectively. iACP-RF as a standalone tool and its source code are publicly available at: https://***/MLBC-lab/iACP-RF. © 2023 The Authors

关键词： Anticancer peptides Ensemble learning Feature extraction Heterogeneous classifiers Machine learning Random Forest

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Agent technology for coordinating UAV target tracking

Agent technology for coordinating UAV target tracking

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9th International Conference on Knowledge-Based intelligent Information and engineering systems, KES 2005

作者： Park, Jisun Fullam, Karen K. Han, David C. Suzanne Barber, K. Laboratory for Intelligent Processes and Systems Electrical and Computer Engineering Department University of Texas Austin United States

This paper illustrates three agent technologies deployed in the Unmanned Aerial Vehicle (UAV) target tracking domain. These capabilities enable: (1) coordination of the tracking of multiple targets among a set of UAVs, (2) identification of the best subset of assigned UAVs from which to collect location information, and (3) evaluation of location information accuracy. These capabilities aid the efficient and effective collection and verification of target location information. © Springer-Verlag Berlin Heidelberg 2005.

关键词： Unmanned vehicles

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Autonomy as decision-making control

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7th International Workshop on Agent Theories Architectures and Languages, ATAL 2000

作者： Barber, K. Suzanne Martin, Cheryl E. Laboratory for Intelligent Processes and Systems University of Texas at Austin Department of Electrical and Computer Engineering 201 East 24th Street ACE 5.402 Austin TX 78712 United States

Autonomy is a very complex concept. This discussion develops a definition for one dimension of autonomy: decision-making control. The development of this definition draws salient features from previous work. Each stag...

ISBN: (纸本)3540424229

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Autonomy as decision-making control

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7th International Workshop on Agent Theories Architectures and Languages, ATAL 2000

作者： Suzanne Barber, K. Martin, Cheryl E. The Laboratory for Intelligent Processes and Systems The University of Texas at Austin Department of Electrical and Computer Engineering 201 East 24th Street ACE 5.402 AustinTX United States

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Tracing Dependencies of Strategy Selections in Agent Design 17

Tracing Dependencies of Strategy Selections in Agent Design

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17th National Conference on Artificial Intelligence, AAA1 2000

作者： Lam, Dung N. Barber, K.S. The Laboratory for Intelligent Processes and Systems Department of Electrical and Computer Engineering ENS 240 University of Texas at Austin AustinTX78712-1084 United States

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Visualization of radial basis function networks

Visualization of radial basis function networks

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International Joint Conference on Neural Networks (IJCNN)

作者： A. Agogino J. Ghosh C. Martin Laboratory for Artificial Neural Systems Department of Electrical and Computer Engineering University of Texas Austin Austin TX USA Laboratory for Intelligent Processes and Systems Department of Electrical and Computer Engineering University of Texas Austin Austin TX USA

Presents a method for the 3D visualization of the structure of radial basis function networks. This method allows the visualization of basis function characteristics (centers and widths) along with second level weights. Network properties can be displayed simultaneously with the training data or test data in the same input space. Principal component analysis is used to transform the input data so that its most salient dimensions can be visualized. This method also allows changes made while graphically editing the network structure, in transformed space, to be projected back into the original input space.

关键词： Radial basis function networks Data visualization Neural networks Network topology Laboratories Training data Bonding intelligent systems Artificial intelligence intelligent structures

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The classification and specification of a domain independent agent architecture 11th

The classification and specification of a domain independent...

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11th International Conference on Industrial and engineering Applications of Artificial Intelligence and Expert systems, IEA/AIE 1998

作者： Goel, A. Barber, K.S. The Laboratory for Intelligent Processes and Systems The Department of Electrical and Computer Engineering ENS 240 The University of Texas at Austin AustinTX78712-1084 United States

ISBN: (纸本)3540645829

The use of multi-agent systems to model and control complex domains is increasing. The application of multi-agent systems to distributed real-world domains motivates the development of domain independent agent architectures to foster the re-use of existing research. A domain independent agent architecture is defined as a set of representations, reasoning mechanisms and algorithms that can be used to define the behavior of an agent. Ideally, a classification method for agent architectures should ease the process of requirements matching between domains and architectures by allowing system designers to understand the relationship between domains and architectures. This paper presents the need for a classification schema and proposes a starting point for future discussion. The Sensible Agent architecture is then introduced within the classification schema. Sensible Agents perceive, process, and respond based on an understanding of both local and system goals. The core capabilities and internal architecture of a Sensible Agent is given as an example of how accurate specifications can help foster the re-use of research. © Springer-Verlag Berlin Heidelberg 1998.

关键词： Multi agent systems

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