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11th International Conference on System Modeling and Advancement in Research Trends, SMART 2022

作者： Rajawat, Anand Singh Goyal, S.B. Bedi, Pradeep Constantin, Neagu Bogdan Raboaca, Maria Simona Verma, Chaman School of Computer Sciences and Engineering Sandip University Nashik India City University Faculty of Information Technology Petaling Jaya Malaysia Galgotais University Greater Noida India Gheorghe Asachi Technical University of Iasi Department of Power Engineering Iasi700050 Romania National Research and Development Institute for Cryogenics and Isotopic Technologies Icsi Energy Department Ramnicu Valcea240050 Romania University of Eotvos Lorand Faculty of Informatics Budapest1053 Hungary

ISBN: (纸本)9781665487320

Automation industries are using Industry 4.0 solutions for several reasons. Still, the most important is to make it easier for their employees to get secure information and to work better with people in other departments. The goal of this effort is to improve productivity and efficiency by making it easier to make good decisions at the right time. This will make it possible to make these kinds of improvements. Constraint-based security solutions are becoming increasingly popular as the digital and physical worlds become more connected. Based on the processing speed, the amount of memory that can be used, and the amount of backup power that can be used. The algorithms and security frameworks used in earlier research need many resources. Several researchers have given an overview of the many security problems with the CPS and their studies and recommendations. But constraint-based applications need light security systems that can work with hardware with limited capabilities. We proposed a safety mechanism that can be used with the already-made constraint-based CPS program. To propose Cyber-Physical System for Industrial Automation Using Quantum Deep Learning, We proposed Cyber-Physical System for Industrial Automation that uses Quantum Learning to find attacking patterns. © 2022 IEEE.

关键词： Cyber Physical System

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MRIGAT: Many-to-many Recommendation using Interaction based Knowledge Graph Attention 22

MRIGAT: Many-to-many Recommendation using Interaction based ...

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3rd International Symposium on Artificial Intelligence for Medical Sciences, ISAIMS 2022

作者： Gao, Feng Yuan, Kai Gu, Jinguang Liu, Yun Department of Computer Science and Technology Wuhan University of Science and Technology China The Key Laboratory of Rich-Media Knowledge Organization Service of Digital Publishing Content Institute of Scientific and Technical Information of China China Guangxi Eco-engineering Vocational & Technical College China 1st Affiliated Hospital Dept. of Medical Informatics School of Biomedical Engineering & Informatic Nanjing Medical University China

ISBN: (纸本)9781450398442

Recommendation systems combining Graph Neural Networks and Knowledge Graphs have been successfully applied in various domains. However, most existing approaches only consider one-to-one or one-to-many user-item interactions and cannot cater to many-to-many recommendation scenarios, such as providing prescriptions based on clinical diagnosis and medical history. Providing such a recommendation requires considering the implicit interaction within input user features as well as output candidates. In this paper, we propose a two-stage knowledge graph attention aggregation mechanism that helps recommend drug combinations for a patient based on his conditions. First, a disease-drug interaction graph is constructed and integrated with the medical domain knowledge, forming a collaborative knowledge graph. Secondly, an intra-feature attention aggregation is performed to obtain the representations of diseases and drugs based on drug-drug and disease-disease interactions, respectively. Thirdly, an inter-feature attention aggregation is performed using the disease-drug interaction to better represent a user's condition. Finally, the user's condition representation is concatenated with other user features to generate the final user representation for the prescription recommendation. Experiments with realistic datasets show that our approach can outperform existing recommendation systems by 4.3% and 6.1% in precision and recall, respectively. © 2022 ACM.

关键词： Knowledge graph

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Full-Duplex Wireless for 6G: Progress Brings New Opportunities and Challenges

arXiv

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arXiv 2023年

作者： Smida, Besma Sabharwal, Ashutosh Fodor, Gabor Alexandropoulos, George C. Suraweera, Himal A. Chae, Chan-Byoung The Department of Electrical and Computer Engineering University of Illinois Chicago ChicagoIL77005 United States The Department of Electrical and Computer Engineering Rice University HoustonTX77005 United States Ericsson Research KTH Royal Institute of Technology Stockholm Sweden The Department of Informatics and Telecommunications National and Kapodistrian University of Athens Athens15784 Greece The Department of Electrical and Electronic Engineering University of Peradeniya Peradeniya20400 Sri Lanka The School of Integrated Technology Yonsei University Seoul03722 Korea Republic of

The use of in-band full-duplex (FD) enables nodes to simultaneously transmit and receive on the same frequency band, which challenges the traditional assumption in wireless network design. The full-duplex capability enhances spectral efficiency and decreases latency, which are two key drivers pushing the performance expectations of next-generation mobile networks. In less than ten years, in-band FD has advanced from being demonstrated in research labs to being implemented in standards, presenting new opportunities to utilize its foundational concepts. Some of the most significant opportunities include using FD to enable wireless networks to sense the physical environment, integrate sensing and communication applications, develop integrated access and backhaul solutions, and work with smart signal propagation environments powered by reconfigurable intelligent surfaces. However, these new opportunities also come with new challenges for large-scale commercial deployment of FD technology, such as managing self-interference, combating cross-link interference in multi-cell networks, and coexistence of dynamic time division duplex, subband FD and FD networks. © 2023, CC BY-NC-ND.

关键词： Wireless networks

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Detecting Anomalous Insiders Using Network Analysis 1

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9th International Conference on Communications, Signal Processing, and Systems, CSPS 2020

作者： Dai, Lei Zhang, Liwei Li, Limin Chen, You Beijing Institute of Technology Beijing China China Academy of Electronics and Information Technology Beijing China Department of Biomedical Informatics Vanderbilt University Medical Center NashvilleTN United States Department of Electrical Engineering & Computer Science School of Engineering Vanderbilt University NashvilleTN United States

ISBN: (数字)9789811584114

ISBN: (纸本)9789811584107

Collaborative information systems (CISs) can improve efficiency and quality of services, because they enable users to coordinate and collaborate on common works with a large scale. In recent decades, increasing number of hospitals start to adopt CIS to improve efficiency and quality of health care treatment, and CIS is becoming an important platform for hospital employees to treat patients. CIS is rich in resources of relations among users, however, people seldom study networks of users existing in the CIS, especially in health information systems. In this paper, we construct collaborative weighted networks of users from two typical CIS: one from health care respect, Vanderbilt University STARPANEL system;and the other from a more general respect, Wikipedia talk system. We learn characteristics of those two networks, and find both networks follow degree-strength relations, which could be used for detecting anomalous behaviors of users in the CIS, for instance, anomalous behaviors of hospital employees and wiki editors. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Hospitals

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The Ins and Outs of Socially Assistive Robots: Sensors and Behaviors of a Therapeutic Robot for Depression Management

The Ins and Outs of Socially Assistive Robots: Sensors and B...

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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Sawyer Collins Zachary Henkel Kenna Baugus Henkel Casey C. Bennett Čedomir Stanojević Jennifer A. Piatt Cindy L. Bethel Selma Šabanović Luddy School of Informatics Computing and Engineering Indiana University Bloomington IN USA Computer Science Department Mississippi State University Starkville MS USA Department of Computing DePaul University Chicago IL USA Department of Behavioral Social And Health Sciences Clemson University Clemson SC USA School of Public Health Indiana University Bloomington Bloomington IN USA

ISBN: (数字)9798350375022

ISBN: (纸本)9798350375039

Using socially assistive robots (SARs) as specialized companions for those living with depression to manage symptoms provides a unique opportunity for exploration of robotic systems as comfort objects. Moreover, the robotic components allow for specialized behavioral responses to particular stimuli, as preferred by the user. We have conducted semi-structured interviews with 10 participants about the zoomorphic robot’s Therabot™ desired behaviors and focus groups with five additional participants regarding the preferred sensors within the Therabot™ system. In this paper, using the data from interviews and focus groups, we explore SAR input and output for depression management. While participants overall expected the robot to respond in much similar ways as a well-trained service animal, they expressed interest in the robot understanding unique information about the environment and the user, such as when the user might need interaction.

关键词： Animals Prototypes Medical treatment Robot sensing systems Depression Assistive robots Sensor systems Reflection Sensors Interviews

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Hybrid Models for Recognizing Indonesian Textual Entailment

Hybrid Models for Recognizing Indonesian Textual Entailment

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International Conference on informatics and Computational Sciences (ICICoS)

作者： Hendri Ahmadian Taufik Fuadi Abidin Hammam Riza Kahlil Muchtar Graduate School of Mathematics and Applied Sciences Universitas Syiah Kuala Banda Aceh Indonesia Department of Informatics Faculty of Mathematics and Natural Sciences Universitas Syiah Kuala Banda Aceh Indonesia Research Center for Artificial Intelligence and Cyber Security National Research and Innovation Agency Jakarta Indonesia Department of Electrical and Computer Engineering Faculty of Engineering Universitas Syiah Kuala Banda Aceh Indonesia

ISBN: (数字)9798350375886

ISBN: (纸本)9798350375893

A paragraph raises pertinent issues about linguistic disparities in understanding the semantic relationships between sentences within the natural language processing domain (NLP) Addressing this challenge necessitates the development of robust NLP models, with a specific emphasis on text entailment. This research endeavors to enhance the performance of Indonesian NLP benchmarks in text entailment by harnessing a variant of the Bidirectional Encoder Representations from Transformer (BERT) model tailored explicitly for the Indonesian language, known as IndoBERT. The approach in this study adopts a hybrid methodology, amalgamating the IndoBERT layer modification model by summing the last four hidden layers with neural networks. The performance evaluation of the hybrid models, combining the IndoBERT layer modification model with the Bidirectional Gated Recurrent Unit (BiGRU) model and the IndoBERT layer modification model with the Bidirectional Long Short-Term Memory (BiLSTM) model, yields the F1-scores of 0.87 and 0.84, respectively.

关键词： Recurrent neural networks Accuracy Computational modeling Bidirectional control Benchmark testing Transformers Natural language processing

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Age-of-Information and Energy Optimization in Digital Twin Edge Networks

Age-of-Information and Energy Optimization in Digital Twin E...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Yongna Guo Yaru Fu Yan Zhang Tony Q. S. Quek School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden School of Science and Technology Hong Kong Metropolitan University China Department of Informatics University of Oslo Oslo Norway Information Systems Technology and Design Singapore University of Technology and Design Singapore

ISBN: (数字)9798350351255

ISBN: (纸本)9798350351262

In this paper, we study the intricate realm of digital twin synchronization and deployment in multi-access edge computing (MEC) networks, with the aim of optimizing and balancing the two performance metrics Age of Information (AoI) and energy efficiency. We jointly consider the problems of edge association, power allocation, and digital twin deployment. However, the inherent randomness of the problem presents a significant challenge in identifying an optimal solution. To address this, we first analyze the feasibility conditions of the optimization problem. We then examine a specific scenario involving a static channel and propose a cyclic scheduling scheme. This enables us to derive the sum AoI in closed form. As a result, the joint optimization problem of edge association and power control is solved optimally by finding a minimum weight perfect matching. Moreover, we examine the one-shot optimization problem in the contexts of both frequent digital twin migrations and fixed digital twin deployments, and propose an efficient online algorithm to address the general optimization problem. This algorithm effectively reduces system costs by balancing frequent migrations and fixed deployments. Numerical results demonstrate the effectiveness of our proposed scheme in terms of low cost and high efficiency.

关键词： Measurement Multi-access edge computing Costs Numerical analysis Power control Information age Digital twins Synchronization Resource management Optimization

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Automatic Determination of Seeded Region Growing Parameters in Watershed Regions to Segmentation of Tuna

Automatic Determination of Seeded Region Growing Parameters ...

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International Conference on informatics and Computing (ICIC)

作者： Wanvy Arifha Saputra Agus Zainal Arifin Nuruddin Wiranda Edi Yohanes Zainal Abidin Bambang Suriansyah Department of Electrical Engineering Politeknik Negeri Banjarmasin Banjarmasin Indonesia Department of Informatics Institut Teknologi Sepuluh Nopember Surabaya Surabaya Indonesia Department of Computer Education Lambung Mangkurat University Banjarmasin Indonesia

ISBN: (纸本)9798350345728

Seeded region growing has two main parameters, namely seed initialization and threshold determination. Parameter values can be done manually or automatically. Automatic parameter assessment is suitable to be applied on a real time basis, but the parameter assessment must be precise. This is due to the greater risk of segmentation errors than manual. This research aims to propose automatic determination of seeded region growing in the watershed region for image segmentation of tuna. The tuna image was processed into the hue, saturation, and intensity (HSI) color space. The hue color space was then taken up in the formation of the watershed region. After that, the density of a region was calculated, then the density was sorted and the highest density was taken. The region that had the highest density was taken based on the highest gray level intensity, then the threshold was obtained from the difference between the average number of regions used and the average intensity of the region left. The results of tuna image segmentation were successfully carried out by proving the average values of relative foreground area error (RAE), missclassification error (ME), and modified Hausdroff distance (MHD) respectively for category 1 data of 6.77%, 1.78% and 0.18%, while for category 2 data of 3.44%, 1.30% and 0.66%.

关键词： Image segmentation Histograms Magnetohydrodynamics Automation Image color analysis Manuals Real-time systems

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Development of a Calibration-Free Brain-computer Interface Utilizing Common Spatial Patterns and Artificial Neural Networks for EEG Signal Analysis

Development of a Calibration-Free Brain-Computer Interface U...

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Human-computer Interaction, Optimization and Robotic Applications (HORA), International Congress on

作者： Korhan Cengiz Shreyas J Udayaprasad P K Gururaj H L Dilip Kumar S M College of Information Technology University of Fujairah UAE Faculty of Organization and Informatics University of Zagreb Croatia Department of Information Technology Manipal Institute of Technology Bengaluru Manipal Academy of Higher Education Manipal Karnataka India Department of Artificial Intelligence & Machine Learning Global Academy of Technology Bengaluru India Dept. of Computer Science and Engineering University Visvesvaraya College of Engineering Bangalore India

ISBN: (数字)9798350394634

ISBN: (纸本)9798350394641

A brain computer interface (BCI) system uses a technique known calibration, that takes 20 to 30 minutes to accomplish. For the objective of creating a reliable decoder, the calibration process is challenging and expensive. In order to address the drawbacks of the current system, a spectral-spatial technique has been suggested. The motor imagery (MI) data set, comprising 15 electroencephalography (EEG) signals and fourteen test subjects, is taken into consideration. The two modules are designed to extract characteristics and process data. An artificial neural network (ANN) is used to independently train and test the suggested spectral-spatial algorithm. Based on it, a variety of machine learning techniques, including random forest (RF), neural networks (NN), and XGboost, are used to classify the data, that is then sent to the hidden layer (Lth layer). The obtained results indicates 2% of improvement in comparison with existing methodology.

关键词： Training Machine learning algorithms Artificial neural networks Electroencephalography Brain-computer interfaces Calibration Reliability

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Physical Layer Security in AmBC-NOMA Networks with Random Eavesdroppers

arXiv

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arXiv 2024年

作者： Pei, Xinyue Wang, Xingwei Huang, Min Chen, Yingyang Li, Xiaofan Tsiftsis, Theodoros A. School of Computer Science and Engineering Northeastern University Shenyang110819 China The College of Information Science and Engineering Northeastern University Shenyang110819 China The College of Information Science and Technology Jinan University Guangzhou510632 China The School of Intelligent Systems Science and Engineering Jinan University Zhuhai519070 China Department of Informatics Telecommunications University of Thessaly Lamia35100 Greece The Department of Electrical and Electronic Engineering University of Nottingham Ningbo China Ningbo315100 China

In this work, we investigate the physical layer security (PLS) of ambient backscatter communication non-orthogonal multiple access (AmBC-NOMA) networks where non-colluding eavesdroppers (Eves) are randomly distributed. In the proposed system, a base station (BS) transmits a superimposed signal to a typical NOMA user pair, while a backscatter device (BD) simultaneously transmits its unique signal by reflecting and modulating the BS's signal. Meanwhile, Eves passively attempt to wiretap the ongoing transmissions. Notably, the number and locations of Eves are unknown, posing a substantial security threat to the system. To address this challenge, the BS injects artificial noise (AN) to mislead the Eves, and a protected zone is employed to create an Eve-exclusion area around the BS. Theoretical expressions for outage probability (OP) and intercept probability (IP) are provided to evaluate the system's reliability-security trade-off. Asymptotic behavior at high signal-to-noise ratio (SNR) is further explored, including the derivation of diversity orders for the OP. Numerical results validate the analytical findings through extensive simulations, demonstrating that both the AN injection and protected zone can effectively enhance PLS. Furthermore, analysis and insights of different key parameters, including transmit SNR, reflection efficiency at the BD, power allocation coefficient, power fraction allocated to desired signal, Eve-exclusion area radius, Eve distribution density, and backscattered AN cancellation efficiency, on OP and IP are also provided. Copyright © 2024, The Authors. All rights reserved.

关键词： Signal to noise ratio

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