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Avionics System Architectures for Software-Defined Spacecraft 1

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11th EAI International Conference on MOBILe Wireless MiddleWARE, Operating Systems and Applications, MOBILWARE 2022

作者： He, Xiongwen Li, Jionghui Bai, Fan Jia, Xiaoyu Huang, Xiaofeng Xu, Mingwei Department of Computer Science and Technology Tsinghua University Beijing100084 China Beijing Institute of Spacecraft System Engineering Beijing100094 China

ISBN: (数字)9783031344978

ISBN: (纸本)9783031344961

Developing upon open system architecture, Software-Defined Spacecraft, as a new generation of spacecraft, can support payload plug-and-play, application software loading as needed, and system function reconfiguration on demand. Therefore, the Software-Defined Spacecraft is able to solve the design and application limitations of traditional specific-designed spacecraft, making it become a significant developing trend of future spacecraft. Regarding to the software defined spacecraft bus, this paper analyzes the requirements for avionics system on the aspects of space field development, technology development and corresponding applications. Then, combining with the development status, the avionics system architecture of software defined spacecraft is proposed, along with the related key technologies. © 2023, ICST Institute for computer sciences, Social Informatics and Telecommunications Engineering.

关键词： Application programs

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Research on High-Frequency Motion Control of Voice Coil Motors Based on Fuzzy PID 16th

Research on High-Frequency Motion Control of Voice Coil Moto...

引用

16th International Conference on Intelligent Robotics and Applications, ICIRA 2023

作者： Huang, Feng Wang, Chenxi Fu, Yang Wang, Lijun Li, Qipeng School of Mechanical and Energy Engineering Zhejiang University of Science and Technology Hangzhou China Zhejiang Lianyi Motor Co. Ltd. Hangzhou China School of Automation and Electrical Engineering Zhejiang University of Science and Technology Hangzhou China

ISBN: (纸本)9789819964918

Voice coil motors are widely used in high-precision manufacturing and processing fields because of their simple mechanical structure, fast dynamic response, and high linearity. The motion control algorithms and control accuracy of voice coil motors have become the focus of industry research. In this paper, the mechanical structure and electrical system of a voice coil motor are modeled, and a cascade fuzzy PID controller is designed for the motor. Then the control simulation is carried out in Simulink to verify the control method. The simulation results show that the performance of the designed fuzzy PID controller is superior to the classical PID controller in terms of adapting load change. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2023.

关键词： Motion control

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Advanced Construction Materials Based on Concrete to Protect the Living Space from Non-Ionizing Radiation 1

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32nd International Conference on Organization and Technology of Maintenance, OTO 2023

作者： Mandrić, Vanja Rupčić, Slavko Vinko, Davor Dominković, Ivica Faculty of Electrical Engineering Computer Science and Information Technology Osijek Osijek Croatia

ISBN: (数字)9783031514944

ISBN: (纸本)9783031514937

This paper presents measurements of the reflection and transmission coefficient of electromagnetic waves through concrete and two concrete-based composites: concrete with steel fibers and concrete with carbon fibers with the aim of enhancing the attenuation of electromagnetic waves passing through concrete and concrete composites. The frequency range for which the measurements were carried out extends from 30 MHz to 18 GHz and includes most of the existing stationary (and mobile) radiation EM sources in the environment in which the general population moves (FM, DVBT2, 2G - 5G mobile radio systems, stationary radar border area control systems). The measurement results show that as the thickness of the concrete increases, the transmission through concrete and concrete composites decreases (parameter S12 decreases). Furthermore, composites with carbon fibers partially reduce, while those with steel fibers significantly reduce, the transmission of EM waves through such composites. The reduction of parameter S12 by composites with steel is up to 52 dB (at a frequency of 2.9 GHz) for a block thickness of 100 mm. It is important to emphasize that in the case of composites with steel fibers, the influence of the fibers on the transmission parameters is more significant than the thickness of the sample. The reason for this is the increase in electrical conductivity of composites with steel fibers due to the increased proportion of conductive components in the concrete. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Steel fibers

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Enriching Semantic Features for Medical Report Generation 12th

Enriching Semantic Features for Medical Report Generation

引用

12th National CCF Conference on Natural Language Processing and Chinese Computing, NLPCC 2023

作者： Luan, Qi Pan, Haiwei Zhang, Kejia Shi, Kun Jia, Xiteng College of Computer Science and Technology Harbin Engineering University Harbin China

ISBN: (纸本)9783031446955

Medical reports play an important role in diagnosing a patient’s illness. However, writing medical reports is time-consuming and labor-intensive, and writing high-quality medical reports often requires extensive clinical experience, which can be a challenge for less experienced doctors. Based on this, the medical report generation tasks emerged. The model architecture used is basically Encoder-Decoder architecture. In this architecture, the extraction quality of visual features is particularly critical. Based on this, previous research has focused on how to better extract visual features, but most researchers have neglected the acquisition of textual features. In this paper, we focus on how to obtain better textual features and how to perform multi-modal feature fusion of visual and textual features more effectively. To this end, we propose two modules, the BM25 Multi-Source Text feature interaction module (BM25-MST) and the Multi-Modal Feature memory fusion module (Mul-MF),respectively. The aim of this BM25-MST module is to generate a multi-source text feature containing rich semantic information, and then use the Mul-MF module to perform full fusion of visual features and text features. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Diagnosis

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Identification of Spam on Social Media by Semi-supervised Learning Approach 1

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2nd EAI International Conference on Pervasive knowledge and collective intelligence on Web and Social Media, PerSOM 2023

作者： Kiran, Sudana Shashi Kiran, Sure Uday Amrutha, Elluru Yasaswi, E. Sai, Annam Kumar Sravya, Kusam Reeja, S.R. School of Computer Science and Engineering VIT-AP University Amaravati India

ISBN: (数字)9783031660443

ISBN: (纸本)9783031660436

This study examines how machine learning methods can be used to identify Twitter spammers. Due to spammers’ increased use of social media platforms, it is crucial to combat their fraudulent operations. This study uses extensive Twitter data, such as user profiles, tweet content, and network connections, to create algorithms that accurately differentiate between genuine users and spammers. By successfully identifying and filtering out spammers utilizing a range of machine learning algorithms, deep learning techniques, feature extraction methodologies, and even categorizing tweets based on their emotional tone, the ultimate goal is to improve platform trust and user experience. In order to efficiently identify spammers and fake users, the article provides a solution that makes use of a unique machine learning algorithm that meticulously analyses user personal information and account history. Because of its popularity, Twitter has drawn spammers and bogus users, which has caused confusion. The study seeks to address "Twitter Spam Drift" by applying a Semi-Supervised Learning Approach (SSLA), which adjusts to changes in spam behavior and has demonstrated promising results on English datasets. To identify spam behaviors on Twitter, the project uses deep-learning classifier algorithms like LSTM, and GRU. Here, as can be seen, we use various methods to achieve accuracy ranging from 87% to 97%. © ICST Institute for computer sciences, Social Informatics and Telecommunications Engineering 2024.

关键词： Tweets

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Pelphix: Surgical Phase Recognition from X-Ray Images in Percutaneous Pelvic Fixation 26th

Pelphix: Surgical Phase Recognition from X-Ray Images in Per...

引用

26th International Conference on Medical Image Computing and computer-Assisted Intervention (MICCAI)

作者： Killeen, Benjamin D. Zhang, Han Mangulabnan, Jan Armand, Mehran Taylor, Russell H. Osgood, Greg Unberath, Mathias Johns Hopkins Univ Baltimore MD 21205 USA

ISBN: (纸本)9783031439957;9783031439964

Surgical phase recognition (SPR) is a crucial element in the digital transformation of the modern operating theater. While SPR based on video sources is well-established, incorporation of interventional X-ray sequences has not yet been explored. This paper presents Pelphix, a first approach to SPR for X-ray-guided percutaneous pelvic fracture fixation, which models the procedure at four levels of granularity - corridor, activity, view, and frame value - simulating the pelvic fracture fixation workflow as a Markov process to provide fully annotated training data. Using added supervision from detection of bony corridors, tools, and anatomy, we learn image representations that are fed into a transformer model to regress surgical phases at the four granularity levels. Our approach demonstrates the feasibility of X-ray-based SPR, achieving an average accuracy of 99.2% on simulated sequences and 71.7% in cadaver across all granularity levels, with up to 84% accuracy for the target corridor in real data. This work constitutes the first step toward SPR for the X-ray domain, establishing an approach to categorizing phases in X-ray-guided surgery, simulating realistic image sequences to enable machine learning model development, and demonstrating that this approach is feasible for the analysis of real procedures. As X-ray-based SPR continues to mature, it will benefit procedures in orthopedic surgery, angiography, and interventional radiology by equipping intelligent surgical systems with situational awareness in the operating room. Code and data available at https://***/benjamindkilleen/pelphix.

关键词： Activity recognition fluoroscopy orthopedic surgery surgical data science

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Unveiling the Future: A Review of Financial Fraud Detection Using Artificial Intelligence Techniques 1

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7th International Conference on Microelectronics and Telecommunication Engineering, ICMETE 2023

作者： Goel, Sankalp Rajpoot, Abha Kiran Department of Computer Science Engineering Sharda University Greater Noida India

ISBN: (数字)9789819995622

ISBN: (纸本)9789819995615

Financial fraud is the illegal use of mobile platforms for transactions when credit card or identity theft is exploited to create fake money. With the spread of smartphones and online transaction services, financial fraud and credit card fraud have become rapidly growing issues. Accurate detection of financial fraud in this context is crucial, as it can result in significant financial losses. Therefore, we conducted a survey of machine learning, deep learning, and data mining methodologies for financial fraud detection. In our study, we evaluated our methodology for detecting fraud and handling vast financial data, contrasting it with artificial neural networks. Our reviewed process encompassed variable selection, sampling, and the utilisation of supervised and unsupervised algorithms. This allowed us to effectively identify financial fraud and process extensive financial datasets. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Neural networks

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A New Paradigm in Blockchain-Based Financial Aid Distribution 1

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World Conference on Information Systems for Business Management, ISBM 2023

作者： Hasan Shahrukh, Md. Raisul Rahman, Md. Tabassinur Mansoor, Nafees Department of Computer Science and Engineering University of Liberal Arts Bangladesh Dhaka1207 Bangladesh

ISBN: (数字)9789819983490

ISBN: (纸本)9789819983483

Blockchain technology has emerged as a game-changer in a variety of industries, providing robust solutions that can supplant conventional procedures. The unique potential of this technology originates from its decentralized ledger systems, which enable enhanced security, transparency, and the validation of transactions without the need for intermediaries. Notably, the financial sector is making substantial progress toward implementing blockchain solutions for a variety of operations, including remittances, lending, and investments. The healthcare industry is simultaneously incorporating this technology into systems for managing medical records, tracing supply chains, and data management. Similarly, the capacity of blockchain to enhance transparency, traceability, and accountability is widely acknowledged in supply chain management, from the procurement of basic materials to the delivery of finished goods. Diverse industries, including real estate, energy, and government, are actively investigating the potential of blockchain to improve efficiency, security, and transparency. Notably, Hyperledger Besu, an open-source blockchain platform, is used to implement smart contracts that automate processes and reduce manual intervention along distribution pathways. This exhaustive review examines the transformative potential of blockchain technology across a variety of industries, discussing the obstacles encountered and providing key insights into future research and development directions. This paper seeks to serve as a pivotal resource for academics, industry stakeholders, and policymakers by synthesizing existing scholarly literature and shedding light on significant findings. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Smart contract

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Learning Well-Separated and Representative Prototypes for Few-Shot Event Detection 12th

Learning Well-Separated and Representative Prototypes for ...

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12th National CCF Conference on Natural Language Processing and Chinese Computing, NLPCC 2023

作者： Zhang, Xintong Li, Shasha Ji, Bin Wang, Ting College of Computer Science and Technology National University of Defense Technology Changsha410073 China National University of Singapore Singapore Singapore

ISBN: (纸本)9783031446955

Event detection can be solved with two subtasks: identification and classification of trigger words. Depending on whether these two subtasks are handled simultaneously, event detection models are divided into the pipeline-based paradigm and the joint-based paradigm. For both paradigms, prototypical networks are an extremely important method to solve a few-shot event detection task. Prototypical networks classify through the distances between instances and prototypes. Therefore, both the distance between prototypes and prototype representations are the key to prototypical networks. Compared with the pipeline-based paradigm, the joint-based paradigm handles two subtasks at the same time to effectively avoid the error cascade. To make better use of prototypical networks in the joint-based paradigm, we propose PN-SR, a Prototypical Network with well-Separated and Representative prototypes. Specifically, we use representation learning methods to generate prototypes. At the same time, we add a loss factor to further enlarge the distances between prototypes of different classes and reduce semantic representation distances of instances with the same class. Experiments show our method outperforms many baselines by at least 26.15% F1 points under the same few-shot settings and achieves SOTA. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Pipelines

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An Association Rules-Based Approach for Anomaly Detection on CAN-bus 23rd

An Association Rules-Based Approach for Anomaly Detection on...

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23rd International Conference on Computational science and Its Applications, ICCSA 2023

作者： D’Angelo, Gianni Ficco, Massimo Robustelli, Antonio Department of Computer Science University of Salerno Salerno Italy

ISBN: (纸本)9783031371073

With the rapid development of the Internet of Things (IoT) and the Internet of Vehicles (IoV) technologies, smart vehicles have replaced conventional ones by providing more advanced driving-related features. IoV systems typically consist of Intra-Vehicle Networks (IVNs) in which many Electronic Control units (ECUs) directly and indirectly communicate among them through the Controller Area Network (CAN) bus. However, the growth of such vehicles has also increased the number of network and physical attacks focused on exploiting security weaknesses affecting the CAN protocol. Such problems can also endanger the life of the driver and passengers of the vehicle, as well as that of pedestrians. Therefore, to face this security issue, we propose a novel anomaly detector capable of considering the vehicle-related state over time. To accomplish this, we combine different most famous algorithms to consider all possible relationships between CAN messages and arrange them as corresponding associative rules. The presented approach, also compared with the state-of-the-art solutions, can effectively detect different kinds of attacks (DoS, Fuzzy, GEAR and RPM) by only considering CAN messages collected during attack-free operating scenarios. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Anomaly detection

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