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American Control Conference (ACC)

作者： Shoma Matsui Kai Cai Karen Rudie Department of Electrical and Computer Engineering Ingenuity Labs Research Institute Queen's University Kingston Canada Department of Core Informatics Osaka Metropolitan University Osaka Japan

ISBN: (数字)9798350382655

ISBN: (纸本)9798350382662

In this paper, we study a security problem of protecting secrets in distributed systems. Specifically, we employ discrete-event systems to describe the structure and behaviour of distributed systems, in which global secret information is separated into pieces and stored in local component agents. The goal is to prevent such secrets from being exposed to intruders by imposing appropriate protection measures. This problem is formulated as to ensure that at least one piece of every distributed global secret is secured by a required number of protections, while the overall cost to apply protections is minimum. We first characterize the solvability of this security problem by providing a necessary and sufficient condition, and then develop an algorithm to compute a solution based on the supervisory control theory of discrete-event systems. Finally, we illustrate the effectiveness of our solution with an example system comprising distributed databases.

关键词： Sufficient conditions Costs Distributed databases Supervisory control Discrete-event systems Security Protection

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Exponentially Fast Collaborative Broadcasting in 3D Space

Exponentially Fast Collaborative Broadcasting in 3D Space

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Information and Network Technologies (ICINT), International Conference on

作者： Yotam Ashkenazi Shlomi Dolev Sergey Frenkel Manish Kumar Sweta Kumari Ram Prasadh Narayanan Archit Somani Department of Computer Science Ben-Gurion University of the Negev Beersheba Israel The Institute of Informatics Problems Russian Academy of Science Russia Department of Computer Science New Jersey Institute of Technology New Jersey United States Department of Computer Science and Engineering Shiv Nadar University Delhi India Institute for Information and Communication Systems Science Walton Institute Ireland

ISBN: (数字)9798331536756

ISBN: (纸本)9798331536763

Broadcasting stands as a vital function within wireless sensor networks (WSNs), where nodes disseminate messages throughout the entire network, radiating in all possible directions. Our focus lies on the issue of three-dimensional broadcasting, involving n sensors/robots positioned uniformly across a three-dimensional space. We propose an exponentially fast hybrid collaborative broadcasting algorithm in three-dimensional space "growing ball" through successive propagation steps. We study the effect of various parameters such as the density of the growing ball (ρ), distance (d), the energy emitted by node (E emit ), and ϵ used by the collaborative broadcast. Our approach is based on the idea of dividing the 3D space into two halves that reduce mathematical intricacy. The number of nodes N k in the k th step of the growing ball is the factor of (1+ϵ) k implies the exponential fast broadcast.

关键词： Wireless sensor networks Three-dimensional displays Collaboration Broadcasting

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Development and Evaluation of an Interactive Web Interface for BPMN Elements Identification from Natural Language Text

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Procedia computer Science 2025年 256卷 431-438页

作者： Vitor Camargo de Moura Guilherme Rego Rockembach Marcelo Soares Pimenta Isabela Gasparini Encarna Sosa-Sánchez Lucineia Heloisa Thom Institute of Informatics – Federal University of Rio Grande do Sul (UFRGS) Porto Alegre 91501-970 Brazil Departament of Computer Science University of Santa Catarina State Joinville 89219-710 Brazil Department of Computer Systems and Telematics Engineering – University of Extremadura Cáceres 10003 Spain

Process discovery represents a high percentage of the time demanded along the business process management lifecycle. Texts in natural language, or process descriptions, can be explored as a critical information source. Extracting information automatically from these documents is challenging due to their ambiguity and complexity. While various (semi-)automated solutions are proposed in the literature, functional code access is rare, and tool deployment is almost nonexistent. This research introduces an accessible web interface that allows users to upload process descriptions and interact with the text, automatically identifying the main process elements from the Business Process Model and Notation. Interactions include highlighting elements associated with specific participants. An evaluation experiment with ten potential real-world users was conducted to assess the tool’s benefits. The experiment compared performance in answering questions related to process descriptions across three scenarios: using plain text, using the proposed tool, and using ChatGPT. Results indicated an advantage in using the tool, particularly regarding time consumption. Data collected on ChatGPT usage also provided insights into how users leverage this technology for problem-solving.

关键词： BPMN process description natural language Web interface development evaluation

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Blockchain For Mobile Health Applications: Acceleration With GPU Computing

arXiv

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arXiv 2023年

作者： Drakopoulos, Georgios Marountas, Michail Liapakis, Xenophon Tzimas, Giannis Mylonas, Phivos Sioutas, Spyros Department of Informatics Ionian University Greece Interamerican Sa Greece Technological and Educational Institute of Western Greece Antirrio Campus Greece Computer Engineering and Informatics Department University of Patras Greece

Blockchain is a linearly linked, distributed, and very robust data structure. Originally proposed as part of the Bitcoin distributed stack, it found a number of applications in a number of fields, most notably in smart contracts, social media, secure IoT, and cryptocurrency mining. It ensures data integrity by distributing strongly encrypted data in widely redundant segments. Each new insertion requires verification and approval by the majority of the users of the blockchain. Both encryption and verification are computationally intensive tasks which cannot be solved with ordinary off-the-shelf CPUs. This has resulted in a renewed scientific interest in secure distributed communication and coordination protocols. Mobile health applications are growing progressively popular and have the enormous advantage of timely diagnosis of certain conditions. However, privacy concerns have been raised as mobile health application by default have access to highly sensitive personal data. This chapter presents concisely how blockchain can be applied to mobile health applications in order to enhance *** Codes 65Y05, 68Q05, 68Q10, 68W10 © 2023, CC BY.

关键词： Blockchain

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An Architectural Extension for Digital Twin Platforms to Leverage Behavioral ModelsBehaviors

An Architectural Extension for Digital Twin Platforms to Lev...

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IEEE International Conference on Automation Science and engineering (CASE)

作者： Daniel Lehner Santiago Gil Peter H. Mikkelsen Peter G. Larsen Manuel Wimmer CDL-MINT Institute of Business Informatics - Software Engineering Johannes Kepler University Linz Austria Department of Electrical and Computer Engineering Aarhus University Aarhus Denmark

To reduce the work effort for developing and managing Digital Twin (DT)-based services, so-called DT platforms have emerged recently. These DT platforms make it easier to collect, store, and manage data from physical devices, but often they do not provide means for running behavioral models or synchronizing these with runtime data from the physical devices. These aspects are however crucial for developing many DT-based services. As a result, the implementation of a DT that uses behavioral models still requires a lot of implementation effort, which hinders the adoption of DTs for many applications, in particular for small and medium-sized enterprises that often do not have the resources to implement such complex systems. In this paper, we propose an extension to existing DT platforms that simplifies the incorporation of behavioral models. We base this extended platform on requirements derived from two particular use case examples that require behavioral modeling to run their DT services. We discuss the interfaces offered by the extended DT platform, demonstrate its applicability and evaluate the implementation and adaptation effort of our proposed solution in comparison to a baseline implementation. Based on the case studies, the evaluation shows that the extended DT platform reduces the implementation effort by 56% and the effort for adapting DT services across DTs by 39%, compared to existing DT platforms.

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Human-Spa: An Online Platform Based on Spatial Transcriptome Data for Diseases of Human Systems

Human-Spa: An Online Platform Based on Spatial Transcriptome...

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2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Su, Yunyun Cui, Feifei Yan, Shiyu Zou, Quan Cao, Chen Zhang, Zilong Hainan University School of Computer Science and Technology Haikou China Hainan University School of Life Sciences Haikou China University of Electronic Science and Technology of China Institute of Fundamental and Frontier Sciences Chengdu China Nanjing Medical University School of Biomedical Engineering and Informatics Nanjing China

ISBN: (纸本)9798350337488

Spatial transcriptomics has become a major method for high-throughput analysis of gene expression at the current level of cells, which can directly study gene expression changes in disease cells, reveal the occurrence and development mechanism of diseases, identify potential therapeutic targets related to diseases, and provide new clues for disease diagnosis and treatment. Although there have been major breakthroughs in the analysis and acquisition of transcriptome data, there are still many challenges in how to effectively manage, share and utilize these valuable data resources in the study of human systemic diseases. To solve this problem, we are committed to building a spatial transcriptome database website related to human systemic diseases, aiming to provide reliable datasets related to multiple diseases, and provide certain data information and analysis results to accelerate the progress of human systemic diseases research. This paper will introduce the construction process of the database website in detail, and discuss its application prospects in disease research, with the aim of promoting further development and innovation in the field of human health. Here, Human-spa mainly includes 12 Human systems, 38 disease types, 55 datasets, and Human-Spa provides a very friendly web interface for visualization and dataset parsing. In conclusion, the construction of Human-Spa will provide a powerful tool and resource platform for Human disease research. Human-Spa is available for free at http://***/ © 2023 IEEE.

关键词： data analysis database website diseases of human system spatial transcriptome

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Enhancing the Performance of Semi-supervised Electricity Theft Detection in Smart Grids with Feature engineering and Ensemble Learning

Enhancing the Performance of Semi-supervised Electricity The...

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IEEE Kansas Power and Energy Conference

作者： Ruobin Qi Wynter Japp Stephen Pan Jun Zheng Sihua Shao Department of Computer Science and Engineering New Mexico Institute of Mining and Technology Socorro NM School of Computing and Informatics University of Louisiana Lafayett Lafayette LA Department of Computer Science University of Arizona Tucson AZ Department of Electrical Engineering New Mexico Institute of Mining and Technology Socorro NM

ISBN: (数字)9798350372403

ISBN: (纸本)9798350372410

Electricity theft is a type of cyberattack posing significant risks to the security of smart grids. Semi-supervised outlier detection (SSOD) algorithms utilize normal power usage data to build detection models, enabling them to detect unknown electricity theft attacks. In this paper, we applied feature engineering and ensemble learning to improve the detection performance of SSOD algorithms. Specifically, we extracted 22 time-series and wavelet features from load profiles, which served as inputs for the seven popular SSOD algorithms investigated in this study. Experimental results demonstrate that the proposed feature engineering greatly enhances the performance of SSOD algorithms to detect various false data injection (FDI) attacks. Furthermore, we constructed bagged ensemble models using the best-performing SSOD algorithm as the base model, with results indicating further improvements in detection performance compared to the base model alone.

关键词： Wavelet domain Electricity Feature extraction Data models Smart meters Smart grids Ensemble learning

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Enhanced Speech Emotion and Gender Recognition Using Hybrid CNN-LSTM Models

Enhanced Speech Emotion and Gender Recognition Using Hybrid ...

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Sentiment Analysis and Deep Learning (ICSADL), International Conference on

作者： S Priyadharshini G. Naveen Sundar D. Narmadha Senthil Kumar Thangavel Adeyemi Abel Ajibesin Selvanayaki Kolandapalayam Shanmugam Department of Computer Science and Engineering Karunya Institute of Technology and Sciences Coimbatore India Department of Computer Science and Engineering Amrita School of Computing Coimbatore India Department of Information Technology Faculty of Informatics and Design Cape Peninsula University of Technology South Africa Department of Mathematics and Computer Science Ashland University USA

ISBN: (数字)9798331523923

ISBN: (纸本)9798331523930

The current paper proposes a new approach for peripheral speech emotion analysis and gender estimation incorporating the best machine learning architectures such as CNNs and LSTMs. Its correct depiction of emotions and the variation of the gendered speech to indicate manifold signal-to-noise ratio make the approach accommodate the difficulty inherent in recognizing emotions from the recording of voices as well as predicting the gender of a speaker. It is then able to ally with preprocessing and collection of a vast range of different speech samples, feature extraction of pitch, tone and spectral data. These features serve as input to the CNNs and LSTMs: LSTMs work well at temporal regular features and the CNNs work well in feature extraction by location (spatio feature). The approach is tested on the RAVDESS and IEMOCAP datasets and establishes a near perfect match to prior approaches with reference to recognition accuracy of emotion analysis and gender prediction. Thus, applying the identified dual method approach, which could be described by such characteristics as highly accurate data pre-preprocessing, clear indication of the features of interest, a different CNN-LSTM model joint training, it offers a reasonably good platform to gain certain insights into such characteristics of the speech as our experiment demonstrates. This work offers satisfactory configurations on concerns such as human computer relation, customer relation and mental health surveillance to suggest that other applications could be achieved in future.

关键词： Training Emotion recognition Accuracy Computational modeling Speech recognition Speech enhancement Predictive models Feature extraction Data models Convolutional neural networks

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Joint Packet Scheduling and UAV Trajectory Design in Air-Ground Integrated Network

Joint Packet Scheduling and UAV Trajectory Design in Air-Gro...

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2023 IEEE Globecom Workshops, GC Wkshps 2023

作者： Li, Shichao Yu, Zhiqiang Chen, Hongbin Zhang, Ning Dong, Mianxiong School of Information and Communication Guilin University of Electronic Technology Guilin541004 China University of Windsor Department of Electrical and Computer Engineering WindsorONN9B3P4 Canada Muroran Institute of Technology Department of Sciences and Informatics Muroran050-8585 Japan

ISBN: (纸本)9798350370218

Compared with the terrestrial network, the air-ground integrated network consisting of unmanned aerial ve-hicles (UAV s) and high altitude platforms (HAPs) offers the advantages of large coverage, high capacity, and seamless connection, which can provide effective communication services for the Internet of remote things (IoRT). In this paper, we investigate the joint packet scheduling and UAV trajectory design problem, with the objective of minimizing the average packet queue delay of IoRT in the air-ground integrated network. Since the problem is a non-convex in nature, we reformulate it into a Markov decision process (MDP) firstly. Then, based on the multi-agent deep deterministic policy gradient (MADDPG) method, we propose a joint packet scheduling and UAV trajectory design (JPSTD) algorithm. Simulation results show that the proposed JPSTD algorithm outperforms the benchmark algorithms in terms of reducing the average packet queue delay. © 2023 IEEE.

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Discrepancy and Thematic Bibliometric Analyses of the Remaining Limitations in Artificial Intelligence

Discrepancy and Thematic Bibliometric Analyses of the Remain...

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2024 IEEE International Conference on Computing, ICOCO 2024

作者： Mansor, Mahayaudin M. Ibrahim, Nurain Radi, Noor Fadhilah Ahmad Rahim, Nadirah Abdul Yahaya, Syarul Heiry Bakar, Mohd Aftar Abu Zakaria, Roslinazairimah School of Mathematical Sciences College of Computing Informatics and Mathematics Universiti Teknologi MARA Malaysia Institute of Big Data Analytics and Artificial Intelligence Universiti Teknologi MARA Malaysia Department of Electrical and Computer Engineering Kuliyyah of Engineering International Islamic University Malaysia Department of Science Computer and Mathematics Universiti Teknologi MARA Penang Campus Malaysia Department of Mathematical Sciences Faculty of Science & Technology Universiti Kebangsaan Malaysia Centre for Mathematical Sciences Universiti Malaysia Pahang Al-Sultan Abdullah Malaysia

ISBN: (纸本)9798331530303

As artificial intelligence (AI) advances, it is essential to continuously comprehend its limitations to optimise the integration of AI into autonomous systems that empower humans. The first objective of this study is to highlight the key capabilities of both humans and AI, focusing on the differences and identifying limitations of AI from the literature. Through discrepancy analysis, this study uses a Venn diagram to visualise the remaining limitations of AI into five key domains: (i) emotional intelligence, (ii) consciousness and awareness, (iii) creative imagination, (iv) communication, and (v) ethical decision-making. Furthermore, this study employs thematic bibliometric analysis to provide a more detailed examination of each AI limitation as the second objective. This study has identified underdeveloped and emerging research themes with potential for future development, such as emotion recognition, human-computer interaction, digital health, and situational awareness, which may require further research. Additionally, this study commends the ongoing efforts to harness AI’s computational power and algorithmic innovations to enhance AI’s overall performance and applicability. ©2024 IEEE.

关键词： Emotion Recognition

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