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***-Processor-Towards Development of AI-enhanced End-To-End BCIs

Current Directions in Biomedical engineering 2023年第1期9卷 471-474页

作者： Buron, Leo Erbslöh, Andreas Seidl, Karsten Schiele, Gregor Seidl, Karsten Ur-Rehman, Zia Klaes, Christian University of Duisburg-Essen Faculty of Engineering Duisburg Germany Fraunhofer Institute of Microelectronic Circuit and Systems Business Unit Health Duisburg Germany Ruhruniversity Bochum Faculty of Medicine Bochum Germany

This paper presents a software-based Python framework for developing future AI-enhanced end-To-end Brain-Computer-Interfaces (BCI). This framework contains modules from the emulated analogue front-end and from neural signal pre-processing for invasive neural applications. These modules can be assembled into several pipeline versions for evaluation and benchmarking. The aim of this framework is to accelerate the development of BCIs due to system-wide optimizations in order to set the requirements for hardware development without prior knowledge on the basis of accuracy (recall and precision) and latency. In the next step, the pipeline can be optimised for on-chip and embedded execution. © 2023 the author(s), published by Walter de Gruyter Berlin/Boston.

关键词： Pipelines

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CircRNA-disease inference using deep ensemble model based on triple association

CircRNA-disease inference using deep ensemble model based on...

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2022 Chinese Automation Congress, CAC 2022

作者： Fu, Laiyi Du, Hongkai Wang, Ying Peng, Qinke Xi'an Jiaotong University School of Automation Science and Engineering Systems Engineering Institute Xi'an China Xi'an Jiaotong University School of Software Engineering Systems Engineering Institute Xi'an China

ISBN: (纸本)9781665465335

Accumulating evidence indicates more and more circular RNAs (i.e. circRNAs) have played a vital role in regulating gene expression and are related to diseases through different biological procedures. Predicting circRNA-disease associations helps to conjecture possible disease related circRNA and facilitate human disease diagnosis and downstream treatment. Nevertheless, little effort was made to uncover the interaction between various diseases and circRNAs. In our work, human circRNA-disease association network is first generated using known miRNA-circRNA interactions and disease related miRNA (microRNA) information. Then we further integrated this information to compute similarity scores between human diseases and circRNAs. Here, we proposed one deep ensemble model called DeepInteract, which first used two stacked auto-encoders to explore hidden features utilizing similarity information, and adopted a 3-layer neuron network to predict the final association. Our method is capable of capturing more complex non-linear features comparing to other approaches. Our results indicate the proposed method is superior to other previous competitors. Many prediction results have been validated by some biological experiments using our model. © 2022 IEEE.

关键词： Association reactions

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Application of mT5 and Semantic Role Labeling for Aspect-Based Sentiment Analysis in Political Opinion 5

Application of mT5 and Semantic Role Labeling for Aspect-Bas...

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5th International Conference on Sensing, Measurement and Data Analytics in the Era of Artificial Intelligence, ICSMD 2024

作者： Yu, Jinpeng Li, Zijun Liu, Na Kong, Weixuan Huang, Zijun Li, Xuefeng College of Electronic and Information Engineering Tongji University Shanghai China Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Shanghai China College Of Software Engineering Tongji University Shanghai China

ISBN: (纸本)9798331529192

As aspect-based sentiment analysis (ABSA) extends its application across various domains, effectively utilizing this technology in political opinion analysis poses significant challenges, particularly due to limited training data in sensitive areas. To address this, we constructed two datasets: a 7,334-sample three-class sentiment analysis dataset from political news via web scraping, and a high-quality dataset of 100 manually annotated news sentences designed for testing aspect-level sentiment computation. 'This paper proposes a sentiment classification method based on the mT5 model, combined with Named Entity Recognition (NER) and Semantic Role Labeling (SRL). Experimental results show that our method performs comparably to existing approaches on the SemEval-2014 (Rest14) dataset, while achieving 84% accuracy in aspect entity recognition and 69% overall recognition accuracy on our custom dataset. These findings suggest that the proposed method can significantly enhance model performance in scenarios with limited and sensitive training data. © 2024 IEEE.

关键词： mT5 Model News Sentiment Analysis Political Opinion Analysis Semantic Role Labeling (SRL)

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Adaptive event-triggered state estimation for large-scale systems subject to deception attacks

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Science China(Information Sciences) 2022年第2期65卷 139-154页

作者： Hanchen XIAO Derui DING Hongli DONG Guoliang WEI College of Science University of Shanghai for Science and Technology Department of Control Science and Engineering University of Shanghai for Science and Technology School of Software and Electrical Engineering Swinburne University of Technology Institute of Complex Systems and Advanced Control Northeast Petroleum University

This paper addresses state estimation issues of large-scale systems with measurements subject to deception attacks, where the communication topology among sub-estimators is the same as the physical coupling structure of the subsystems. In consideration of the limited channel bandwidth, a novel adaptive event-triggered scheme is proposed for governing the data transmission among sub-estimators. With the help of Lyapunov analysis approaches, sufficient conditions are derived to ensure the input-to-state stability of the dynamics of estimation errors. Meanwhile, the bound of the estimation errors is obtained in the mean-square sense. The desired estimator parameters are presented in an analytical form dependent on the solution of a set of matrix inequalities. The developed scheme is related to the local information of the subsystems and thus satisfies the requirement of scalability. Finally, a simulation example of power systems is given to reveal the usefulness and effectiveness of the developed design scheme.

关键词： large-scale discrete-time systems adaptive event-triggering communication Adaptive event-triggering communication deception attacks input-to-state stability power systems

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FT-AED: Benchmark Dataset for Early Freeway Traffic Anomalous Event Detection 38

FT-AED: Benchmark Dataset for Early Freeway Traffic Anomalou...

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38th Conference on Neural Information Processing systems, NeurIPS 2024

作者： Coursey, Austin Ji, Junyi Quinones-Grueiro, Marcos Barbour, William Zhang, Yuhang Derr, Tyler Biswas, Gautam Work, Daniel B. Department of Civil and Environmental Engineering Vanderbilt University United States Institute for Software Integrated Systems United States Department of Computer Science United States

Early and accurate detection of anomalous events on the freeway, such as accidents, can improve emergency response and clearance. However, existing delays and mistakes from manual crash reporting records make it a difficult problem to solve. Current large-scale freeway traffic datasets are not designed for anomaly detection and ignore these challenges. In this paper, we introduce the first large-scale lane-level freeway traffic dataset for anomaly detection. Our dataset consists of a month of weekday radar detection sensor data collected in 4 lanes along an 18-mile stretch of Interstate 24 heading toward Nashville, TN, comprising over 3.7 million sensor measurements. We also collect official crash reports from the Tennessee Department of Transportation Traffic Management Center and manually label all other potential anomalies in the dataset. To show the potential for our dataset to be used in future machine learning and traffic research, we benchmark numerous deep learning anomaly detection models on our dataset. We find that unsupervised graph neural network autoencoders are a promising solution for this problem and that ignoring spatial relationships leads to decreased performance. We demonstrate that our methods can reduce reporting delays by over 10 minutes on average while detecting 75% of crashes. Our dataset and all preprocessing code needed to get started are publicly released at https://***/ft-aed/to facilitate future research. © 2024 Neural information processing systems foundation. All rights reserved.

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Temporal Sensitivity Analysis of Internal Temperature Informed Charging Algorithms and Rapid Thermal Management System for E-mobility

Temporal Sensitivity Analysis of Internal Temperature Inform...

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2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Samanta, Akash Chetri, Chandan Karnehm, Dominic Neve, Antje Williamson, Sheldon Ontario Tech University Department of Electrical Computer and Software Engineering Oshawa Canada Bundeswehr University Munich Institute of Intelligent Distributed Systems Neubiberg Germany

ISBN: (纸本)9798350376067

The experimental studies presented in this paper reveal that existing thermal management systems (TMS) and temperature-informed charging algorithms exhibit a response time lag of at least 5.3 minutes due to their reliance on surface temperature measurements. The results indicate that changes in the internal thermal state of lithium-ion batteries (LIBs), induced by variations in charging currents, take an average of 2 minutes to manifest on the battery surface, particularly evident in cylindrical cells. Current thermal management systems for automotive battery packs solely rely on surface temperature measurements, neglecting the approximately 5.8°C temperature difference between the core and surface in TMS control. Consequently, changes in the battery's thermal state due to internal heat losses are not promptly detected by surface-mounted temperature sensors. This delayed response time accelerates battery degradation and increases the risk of thermal runaway events. In this study, temperature-informed fast charging algorithms, tested under various ambient conditions for LIBs, along with a comparative analysis, demonstrate that response time can be reduced by at least 2 minutes by considering internal temperature rather than relying solely on surface temperature measurements. Moreover, accounting for the temperature difference between the core and surface facilitates rapid TMS control and health-conscious fast charging, thereby mitigating the risk of thermal runaway events. © 2024 IEEE.

关键词： Surface measurement

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Dramatizing software Patterns: Focus Group Report 28

Dramatizing Software Patterns: Focus Group Report

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28th European Conference on Pattern Languages of Programs, EuroPLoP 2023

作者： Vranic, Valentino Vranic, Aleksandra Vranic, Branislava Institute of Informatics Information Systems and Software Engineering Faculty of Informatics and Information Technologies Slovak University of Technology Bratislava Slovakia

ISBN: (纸本)9798400700408

The focus group on drama patterns we organized at EuroPLoP 2023 attracted 16 participants (apart from the organizers), who together built a short drama play (created by Aleksandra Vranic) based on the motifs from the stories of Alice in Wonderland. We discussed how particular drama patterns metaphorically correspond to some software patterns and elaborated on two examples of such correspondence: the Thoughts Reflecting Environment drama pattern and its correspondence to the Observer design pattern and the Loosely Coupled Situations drama pattern and its correspondence to the Visitor design pattern. Both drama patterns were first played by the participants and then related to the corresponding design pattern. We also played Observer in a technical, nonmetaphoric way. We also made a performance at the banquet, which was accepted with delight. We achieved this with no rehearsals and with the actor for the main role appointed just before the performance, which confirmed once more how powerful patterns are. © 2023 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： design patterns drama patterns organizational patterns pattern composition

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Discussion Manipulation, Language and Domain Dependent Models: An Overview

Discussion Manipulation, Language and Domain Dependent Model...

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2023 IEEE Zooming Innovation in Consumer Technologies Conference, ZINC 2023

作者： Chalas, Filip Stupavsky, Igor Vranic, Valentino Slovak University of Technology in Bratislava Faculty of Informatics and Information Technologies Institute of Informatics Information Systems and Software Engineering Slovakia

ISBN: (纸本)9798350347722

The amount of antisocial online behavior (AOB) in the political field has been on the rise in recent years. In the research, we are dealing with the reason for confusing AOB with other forms of antisocial behavior. We specifically dealt with NLP in the political field in the Slovak language, with a specific number of prefixes and suffixes. In this paper, we focus on the area of detection of manipulation of political discussions. The data source consisted of previously collected data in the period from April 2018 with an update until November 19, 2022 realized within this research from the site ***, which we supplemented with new claims. We trained several classification models on preprocessed data and evaluated them. For multi-class classification, the best results were achieved using logistic regression and a support vector machine trained on the resampled dataset-both achieving an accuracy of 0.56 and a macro F1 score of 0.39. In the case of binary classification, the best results were achieved by logistic regression-accuracy 0.7 and macro F1 score 0.56. These models could help detect manipulation in online political discussions. © 2023 IEEE.

关键词： Logistic regression

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Patterns for Improving User Contribution 28

Patterns for Improving User Contribution

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28th European Conference on Pattern Languages of Programs, EuroPLoP 2023

作者： Haiderzai, Mohammad Daud Vranic, Valentino Institute of Informatics Information Systems and Software Engineering Faculty of Informatics and Information Technologies Slovak University of Technology Bratislava Slovakia

ISBN: (纸本)9798400700408

User contributions is an important part in software development, the pursuit of identifying effective means of user contributions in software development is a crucial area of interest for software companies and their development teams. Determining the most opportune moments, locations, and methods for such contributions presents a significant challenge for organizations, which necessitates the exploration of generic and proven solutions. Applying patterns, established and observed solutions may provide the answers to such challenges and similar ones. This paper offers insights into the practical implementation of seven newly discovered organizational patterns in a real-life environment. The patterns are comprehensively described, accompanied by illustrative examples, and subsequently applied in actual practices. © 2023 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： software design

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Evaluation of 5G Edge and Cloud Computing for Data Processing in Visual Referencing of Mobile Robot Manipulators 56

Evaluation of 5G Edge and Cloud Computing for Data Processin...

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56th CIRP International Conference on Manufacturing systems, CIRP CMS 2023

作者： Boshoff, Marius Schuster, David Christ, Lukas Hesenius, Marc Gruhn, Volker Kuhlenkötter, Bernd Production Systems Ruhr University Bochum Bochum Germany Institute for Software Engineering University of Duisburg-Essen Essen Germany

To fit the requirements of growing flexibility in production processes, intralogistics is increasingly automated, for example, by Mobile Robot Manipulators, which can transport material and perform assembly tasks. However, these transport systems have limited battery capacity and recharging involves occasional downtime. New approaches, such as Edge Computing, offer transport systems to offload intensive computational processes, e.g., for path planning or AI-based image analysis, and thus saving precious energy resources. However, since offloading such processes onto a server is tied to high security and transmission requirements, using 5G for communication might be an attractive solution. Therefore, an exemplary referencing use case of a Mobile Robot Manipulator is presented and the 5G based communication with two cloud servers and one edge server is examined. Our experimental results show that with a mean transmission time of 540 milliseconds Edge Computing facilitates both faster and more stable data transmission compared to Cloud Computing with a mean transmission time of 1,973 milliseconds. This has a significant impact on industrial processes whose efficiency and productivity depend on the quality of data transfer. © 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of the 56th CIRP International Conference on Manufacturing systems 2023.

关键词： 5G Cloud Communication Edge Mobile Robotics

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