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IEEE Conference on Decision and Control

作者： Junyao Hou Siyuan Liu Xiang Yin Majid Zamani Department of Automation Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University Shanghai China Division of Decision and Control Systems KTH Royal Institute of Technology Stockholm Sweden Department of Computer Science University of Colorado Boulder CO USA Department of Computer Science LMU Munich Munich Germany

Opacity is an important information-flow security property which characterizes the plausible deniability of certain “secret behaviors” in dynamical systems. In this paper, we study the problem of synthesizing controllers enforcing a notion of opacity over discrete-time control systems with continuous state sets. In this paper, we develop an abstraction-based approach to tackle the controller synthesis problem. Specifically, we adopt a notion of approximate opacity which is suitable for continuous-space control systems. We propose a notion of approximate initial-state opacity preserving alternating simulation relation which characterizes the closeness between two systems in terms of opacity preservation. We show that, based on this new notion of system relation, one can synthesize an opacity-enforcing controller for the abstract system which is finite and then refine it back to enforce opacity over the original control system. Finally, we present a method for constructing opacity-preserving finite abstractions for discrete-time control systems under some stability properties. Our results are illustrated on a two-room temperature control problem.

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eVision: Forecasting the spread of Tuberculosis in India with Deep Learning

eVision: Forecasting the spread of Tuberculosis in India wit...

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International Conference on Computational science and Computational Intelligence (CSCI)

作者： Juan Zuluaga Michael Castillo Divya Syal Andres Calle Navid Shaghaghi Department of Bioengineering (BIOE) Computer Science & Engineering (CSEN) Ethical Pragmatic & Intelligent Computing (EPIC) Laboratory in collaboration with the Healthcare Innovation & Design (HID) Program Information Systems & Analytics (ISA) and Mathematics & Computer Science (MCS) Santa Clara University Santa Clara California USA

Humanity has battled tuberculosis for all of recorded history. Some studies estimate that Mycobacterium tuberculosis may have been around as long as 3 million years but it was only in 1834 when Johann Schonlein officially presented the characteristics of it. Even though the TB epidemic has touched all corners of the world, Africa and Asia are the regions that currently suffer the worst consequences. The purpose of this study is to construct a model within the eVision forecasting environment, capable of forecasting the trend of Tuberculosis cases in India, as India is the country that accounts for the largest percentage of TB cases and deaths worldwide. And being able to make predictions for India may also lead to successful results for other regions in Asia and Africa. In order to do so, this study presents different test cases that show the effectiveness of the model, varying the number of steps for each one of the data sets created. It's important to note, that these data sets are combinations of data gathered from the states with the most TB cases in India in the last years, as well as the total data for India, and supplemental data from Google Trends, as a way to facilitate the machine learning model. Even though the final results were respectable compared to past research done on India and other countries, the model nevertheless has a limitation on the number of weeks ahead which the predictions are still considered to be good; with 7 weeks being the optimal result.

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Search Space Analysis of Recurrent Spiking and Continuous-time Neural Networks

Search Space Analysis of Recurrent Spiking and Continuous-ti...

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International Joint Conference on Neural Networks (IJCNN)

作者： M. Ventresca B. Ombuki Systems Design Engineering and member of the Pattern Analysis and Machine Intelligence Laboratory University of Waterloo Waterloo ONT Canada Department of Computing and Information Science University of Guelph Guelph ONT Canada Computer Science Department Brock University Saint Catharines ONT Canada

The problem of designing recurrent continuous-time and spiking neural networks is NP-Hard. A common practice is to utilize stochastic searches, such as evolutionary algorithms, to automatically construct acceptable networks. The outcome of the stochastic search is related to its ability to navigate the search space of neural networks and discover those of high quality. In this paper we investigate the search space associated with designing the above recurrent neural networks in order to differentiate which network should be easier to automatically design via a stochastic search. Our investigation utilizes two popular dynamic systems problems; (1) the Henon map and (2) the inverted pendulum as a benchmark.

关键词： Neural networks Recurrent neural networks Stochastic processes Chaotic communication Neurons Biological system modeling Evolutionary computation Navigation Helium Visualization

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Modular robotics: design and examples

Modular robotics: design and examples

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International Conference on Emerging Technologies and Factory automation (ETFA)

作者： A.C. Sanderson Center for Advanced Technology in Robotics and Automation and Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute RPI Troy NY USA Intellignet robotics Laboratory Institute for Information Science and Electronics University of Tsukuba Tsukuba Japan

An object-oriented modular approach to the engineering of complex robotic systems emphasizes reliability, reusability, ease of development, and user and network interfaces. This modular approach integrates many architectural principles and computational techniques which support adaptive and learning capability at the local, modular level. The TETROBOT is a modular and reconfigurable robotic system which was developed to demonstrate the reliable performance in a wide variety of task domains through reconfiguration of the same fundamental hardware and software components. Such a modular approach emphasizes the synthesis and integration of engineering modules and takes advantage of object-oriented engineering principles to design for a family of tasks. This paper provides an overview of the TETROBOT modular system and describes three modular systems in other applications domains.

关键词： Robots Hardware Robustness Humans Indium phosphide Utility programs

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Analysis of a Partially Decentralized Framework for Operating Future Power systems

Analysis of a Partially Decentralized Framework for Operatin...

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IEEE Power and Energy Society General Meeting

作者： Mingyang Li Peter B. Luh Eugene Litvinov Peng Zhang Center for Intelligent and Networked Systems (CFINS) Department of Automation Tsinghua National Laboratory for Information Science & Technology (TNLIST) Tsinghua University Dept. of Electrical & Computer Engineering University of Connecticut ISO New England Inc.

ISBN: (纸本)9781457710001

In future power systems, the Smart Grid technologies will bring in a large number of new entities, which are different from those in the current systems in two major aspects: first, the entities are geographically distributed throughout the system with their detailed information not available to the system operator, and second, the entities tend to autonomously optimize their own benefits. In view of both aspects, it is difficult to use the current centralized framework to operate future systems. In this paper, we present and analyze a new partially decentralized framework and the corresponding mechanisms as one step from the current framework toward the future ones, and the focus is on the real time electricity markets with a dispatch cycle of five minutes. In each dispatch cycle, the system operator posts electricity price forecasts, and individual entities actively respond to the prices to dispatch themselves. The system-wide power imbalance is used as a correction term in the next dispatch cycle to iteratively update the price forecasts, so that system balance is maintained in the long term. The new framework can accommodate the large number of entities without knowing their detailed information, and enable the entities to achieve better economic benefits. Small examples are used to analyze our framework and to compare it with the current one.

关键词： System operation Autonomous entities Renewable generation Decentralized Real time market Electricity price Decentralized Operating systems Dispatching Electricity pricing Frameworks power systems correct entry Smart grids Prices

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Improving pedestrian attribute recognition with weakly-supervised multi-scale attribute-specific localization

arXiv

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arXiv 2019年

作者： Tang, Chufeng Sheng, Lu Zhang, Zhaoxiang Hu, Xiaolin State Key Laboratory of Intelligent Technology and Systems Institute for Artificial Intelligence Department of Computer Science and Technology Beijing National Research Center for Information Science and Technology Tsinghua University College of Software Beihang University Institute of Automation Chinese Academy of Sciences

Pedestrian attribute recognition has been an emerging research topic in the area of video surveillance. To predict the existence of a particular attribute, it is demanded to localize the regions related to the attribute. However, in this task, the region annotations are not available. How to carve out these attribute-related regions remains challenging. Existing methods applied attribute-agnostic visual attention or heuristic body-part localization mechanisms to enhance the local feature representations, while neglecting to employ attributes to define local feature areas. We propose a flexible Attribute Localization Module (ALM) to adaptively discover the most discriminative regions and learns the regional features for each attribute at multiple levels. Moreover, a feature pyramid architecture is also introduced to enhance the attribute-specific localization at low-levels with high-level semantic guidance. The proposed framework does not require additional region annotations and can be trained end-to-end with multi-level deep supervision. Extensive experiments show that the proposed method achieves state-of-the-art results on three pedestrian attribute datasets, including PETA, RAP, and PA-100K. Copyright © 2019, The Authors. All rights reserved.

关键词： Heuristic methods

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An empirical analysis of social interaction on tobacco-oriented social networks

An empirical analysis of social interaction on tobacco-orien...

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2013 International Conference for Smart Health, ICSH 2013

作者： Liang, Yunji Zheng, Xiaolong Zeng, Daniel Dajun Zhou, Xingshe Leischow, Scott School of Computer Science Northwestern Polytechnical University Xi'an China Department of Management Information System University of Arizona Tucson AZ United States State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Dongguan Research Institute of CASIA Cloud Computing Center Chinese Academy of Sciences Songshan Lake Dongguan China Mayo Clinic in Arizona Phoenix AZ United States

ISBN: (纸本)9783642398438

Social media is widely utilized in the tobacco control campaigns. It is a great challenge to evaluate the efficiency of tobacco control policies on social network sites and find gaps among tobacco-oriented social networks. In this paper, we construct three tobacco-oriented social networks according to user interaction on Facebook tobacco-related fan pages. We further investigate the interaction patterns including temporal distribution and interaction patterns to reveal the differences of tobacco-oriented social networks. Our empirical analysis demonstrates that: 1) the user interaction on the pro-tobacco fan pages is more active. Fan pages for tobacco promotion are more successful in obtaining more user attention. 2) The gap between tobacco promotion and tobacco control is widening. These empirical results can provide us significant insights into understanding the evolutionary patterns of social interaction in tobacco-oriented social networks and further help the government departments of tobacco control to make reasonable decisions. © 2013 Springer-Verlag.

关键词： Tobacco

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Spear or Shield: Leveraging Generative AI to Tackle Security Threats of Intelligent Network Services

arXiv

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arXiv 2023年

作者： Du, Hongyang Niyato, Dusit Kang, Jiawen Xiong, Zehui Lam, Kwok-Yan Fang, Yuguang Li, Yonghui School of Computer Science and Engineering Nanyang Technological University Singapore School of Automation Guangdong University of Technology China Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore National Centre for Research in Digital Trust School of Computer Science and Engineering Nanyang Technological University Singapore Department of Computer Science City University of Hong Kong Hong Kong School of Electrical and Information Engineering University of Sydney SydneyNSW2006 Australia

Generative AI (GAI) models have been rapidly advancing, with a wide range of applications including intelligent networks and mobile AI-generated content (AIGC) services. Despite their numerous applications and potential, such models create opportunities for novel security challenges. In this paper, we examine the challenges and opportunities of GAI in the realm of the security of intelligent network AIGC services such as suggesting security policies, acting as both a "spear" for potential attacks and a "shield" as an integral part of various defense mechanisms. First, we present a comprehensive overview of the GAI landscape, highlighting its applications and the techniques underpinning these advancements, especially large language and diffusion models. Then, we investigate the dynamic interplay between GAI’s spear and shield roles, highlighting two primary categories of potential GAI-related attacks and their respective defense strategies within wireless networks. A case study illustrates the impact of GAI defense strategies on energy consumption in an image request scenario under data poisoning attack. Our results show that by employing an AI-optimized diffusion defense mechanism, energy can be reduced by 8.7%, and retransmission count can be decreased from 32 images, without defense, to just 6 images, showcasing the effectiveness of GAI in enhancing network security. © 2023, CC BY.

关键词： Network security

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CNN Wave Computing: Theory, Architectures, Implementations and Applicaions

CNN Wave Computing: Theory, Architectures, Implementations a...

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IEEE International Workshop on Cellular Nanoscale Networks and their Applications, (CNNA)

作者： Marco Gilli Csaba Rekeczky Bertram Shi Department of Electronics Politecnico di Turino Torino Italy Analogic and Neural Computing Systems Laboratory of the Computer and Automation Information Technology Department Institute of the Hungarian Academy of Sciences Budapest Hungary Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Kowloon Hong Kong China

A cellular neural/nonlinear network (CNN) is any spatial arrangement of mainly locally coupled cells, where each cell is a dynamical system which has an input, an output and a state that evolves according to some prescribed dynamical laws. Since the CNN was first introduced in 1988, research in this field has developed rapidly. The goal of this tutorial is to provide participants with a snapshot of the current state of the art and research trends. It covers the broad multi-disciplinary areas of CNN research, from theoretical aspects to applications. The presenters have experience ranging from theoretical analysis of CNN dynamics, VLSI implementation and system level applications

关键词： Cellular neural networks computer architecture computer networks Very large scale integration Analog computers computer interfaces computer vision Biological system modeling Nonlinear dynamical systems computer industry

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Diffusion-Driven Semantic Communication for Generative Models with Bandwidth Constraints

arXiv

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arXiv 2024年

作者： Guo, Lei Chen, Wei Sun, Yuxuan Ai, Bo Pappas, Nikolaos Quek, Tony State Key Laboratory of Advanced Rail Autonomous Operation Beijing Jiaotong University China School of Electronic and Information Engineering Beijing Jiaotong University Beijing China Department of Computer and Information Science Linköping University Linköping Sweden Information Systems Technology and Design Singapore University of Technology and Design Singapore Singapore

Diffusion models have been extensively utilized in AI-generated content (AIGC) in recent years, thanks to the superior generation capabilities. Combining with semantic communications, diffusion models are used for tasks such as denoising, data reconstruction, and content generation. However, existing diffusion-based generative models do not consider the stringent bandwidth limitation, which limits its application in wireless communication. This paper introduces a diffusion-driven semantic communication framework with advanced VAE-based compression for bandwidth-constrained generative model. Our designed architecture utilizes the diffusion model, where the signal transmission process through the wireless channel acts as the forward process in diffusion. To reduce bandwidth requirements, we incorporate a downsampling module and a paired upsampling module based on a variational auto-encoder with reparameterization at the receiver to ensure that the recovered features conform to the Gaussian distribution. Furthermore, we derive the loss function for our proposed system and evaluate its performance through comprehensive experiments. Our experimental results demonstrate significant improvements in pixel-level metrics such as peak signal to noise ratio (PSNR) and semantic metrics like learned perceptual image patch similarity (LPIPS). These enhancements are more profound regarding the compression rates and SNR compared to deep joint source-channel coding (DJSCC). Copyright © 2024, The Authors. All rights reserved.

关键词： Bandwidth

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