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26th International Conference on computer and Information Technology, ICCIT 2023

作者： Ahmed, Md. Soyed Ibrahim, Zisan Islam, Mohammad Mazharul Shahadat Islam Sumon, Md. Ehtesanul Islam, A.K.M. Ahsanullah University of Science and Technology Department of Electrical and Electronics Engineering Dhaka Bangladesh University of Windsor Department of Electrical Computer Engineering Canada

ISBN: (纸本)9798350359015

Breast cancer is the primary cause of death among women globally and existing screening techniques are both invasive and costly. In this research work, a rectangular microstrip patch antenna is simulated to identify the existence of a tumor by observing the impacts in the ISM band (2.4 GHz-2.5 GHz) of microwave signals. A simplified model of normal and contaminated breast tissue, antenna substrate Flame Retardant 4 (FR-4), copper ground and patch components are used in our study. To evaluate the effectiveness of the device, a human breast phantom made of layers of glandular and epidermal tissue was developed. A voltage standing wave ratio (VSWR) of 1.112869 and an S-parameter value of -25.44603 dB was obtained. A comparative study of the antenna performance is accomplished with and without the presence of a tumor. The assessed simulated performance implies that it can be an enhanced, precise, and reliable screening technique for breast cancer detection. © 2023 IEEE.

关键词： Breast Cancer ISM Band Microstrip Patch Antenna Return Loss SAR

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Application of Artificial Neural Networks in Electric Arc Furnace Modeling 1

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22nd International Conference on Artificial Intelligence and Soft Computing, ICAISC 2023

作者： Klimas, Maciej Grabowski, Dariusz Department of Electrical Engineering and Computer Science Silesian University of Technology Gliwice Poland

ISBN: (数字)9783031425059

ISBN: (纸本)9783031425042

Electric arc furnaces (EAF) can cause various power quality problems in power systems. Because of that, it is important to investigate the electric arc phenomena and deepen the knowledge related to the modeling of such loads. This paper presents an overview of both shallow and deep neural networks applied for the purpose of EAF modeling. Namely, Multilayer Perceptron (MLP), dual MLP, Modified Nonlinear Autoregressive Exogenous model (NARX), and Long Short-Term Memory (LSTM) networks. Their topologies, advantages, and disadvantages are described and compared. The overall performance of the proposed models is analyzed and compared using some statistical measures. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Long short-term memory

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Automatic Skull Shape Completion of Defective Skulls Using Transformers for Cranial Implant Design 2

Automatic Skull Shape Completion of Defective Skulls Using T...

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2nd International Conference on Machine Learning and Data engineering, ICMLDE 2023

作者： Resmi, S. Singh, Rimjhimpadam Palaniappan, Kannappan Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India Dept. of Electrical Engineering and Computer Science University of Missouri MO United States

Cranioplasty is a surgical method that restores the aesthetic and protecting function of a damaged skull by implanting material into the damaged *** and accurate design of patient specific cranial implants is very much required in the process of *** time consumption for designing and manufacturing of patient specific cranial implant has become an obstruction for cranioplasty procedures. Hence, a fully automatic and fast design of cranial implant becomes very important. The cranial implant design processmainly comprises of two steps. The former step concentrates on the automatic skull shape completion of defective skulls to fill the gaps and the cracks created in the skull. While the second step computes the difference between defective input and the completed skull for generating the implant. Currently computer aided design is used for the skull shape completion task which is a time consuming process. The application of deep learning techniques may result to faster and accurate skull shape completionwhich can be used for the design of patient specific cranial implants. This work proposes a novel approach combining 3D U-Net with Transformers for the automatic skull shape completion *** are using a vision transformer in the encoder section of the 3D U-Net architecture to consider the volumetric skull reconstruction as sequence- to-sequence prediction problem and to efficaciously grasp the global contextual information. The work also compares its performance with the famous variants of 3D U-Net deep network model namely, 3D U-Net and 3D U-Net with attention. From the values resulted for the dice coefficient metric it is clear that the proposed 3D U-Net with transformer approach performs better than the other two models on test images. © 2024 Elsevier B.V.. All rights reserved.

关键词： computer aided design

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Environmentally-Aware Robotic Vehicle Networks Routing Computation for Last-mile Deliveries 32

Environmentally-Aware Robotic Vehicle Networks Routing Compu...

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32nd International Conference on computer Communications and Networks, ICCCN 2023

作者： Qu, Chengyi Singh, Rounak Srinivas, Sharan Calyam, Prasad University of Missouri Department of Electrical Engineering and Computer Science Columbia United States

ISBN: (纸本)9798350336184

For next-generation logistics management, robotic vehicles such as autonomous ground robots and aerial drones can alleviate the strain on last-mile distribution. They can help avoid on-road congestion, navigate hard-to-reach locations, and parallelize delivery operations. However, as the robotic vehicles move in a given delivery area, environmental barriers e.g., trees or buildings, affect air-to-air (A2A), air-to-ground (A2G), ground-to-ground (G2G) network communications on a hybrid truck-drone-robot system. In this paper, we present an environmentally-aware cooperative network routing computation scheme to avoid obstacle blockage in A2A/A2G/G2G network communications for addressing large-scale coordinated operations of the hybrid truck-drone-robot system. Specifically, we propose an offline policy-based routing algorithm and two online extensions (i.e., heuristics and learning-based) to solve the hybrid last-mile delivery vehicles communication problem in order to trade-off between end-to-end communication (i.e., increase network throughput) and delivery efficiencies (i.e., lower parcel delivery time consumption). We evaluate our scheme using state-of-the-art network routing algorithms in a trace-based simulator that integrates both the vehicles and networking sides. Performance evaluation results from our simulations show that: (i) our offline approach is Pareto-optimal among non-learning supported algorithms in a pre-delivery scenario, and (ii) our RL-based online algorithm achieves between 85-96 % of the Oracle strategy performance during delivery procedures. © 2023 IEEE.

关键词： Economic and social effects

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FedSTGNN: A Federated Spatio-Temporal Graph Neural Network 15

FedSTGNN: A Federated Spatio-Temporal Graph Neural Network

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15th International Conference on Information and Communication Technology Convergence, ICTC 2024

作者： Yoon, Heeyong Chon, Kang-Wook Kim, Min-Soo Dgist Department of Electrical Engineering and Computer Science Daegu Korea Republic of School of Computer Science and Engineering Koreatech Cheonan Korea Republic of School of Computing Kaist Daejeon Korea Republic of

ISBN: (纸本)9798350364637

Owing to the explosive growth of the Internet of Things (IoT), there have been vast volumes of sensor-generated time series data in various locations. A lot of network usage occurs through these locations to process the sensor-generated data. To reduce network usage, the point of data processing gradually shifts from the central cloud to servers at the edge of the Internet, called edge servers. To cover the paradigm shift, there has been a challenging issue in training a neural network model, which aggregates the data generated by different locations and causes a massive amount of transmitted data across the network. Federated learning successfully resolves this issue by exchanging model parameters in the edge server through the central cloud. Meanwhile, Spatio-Temporal Graph Neural Networks (STGNNs) have gained much attention for analyzing time series data transmitted from several locations in IoT environments. Despite the increasing number of STGNN models that have been examined, the integration of STGNNs and federated learning remains underexplored. This paper presents FedSTGNN, a framework that seamlessly adapts arbitrary STGNN models to edge computing environments. The proposed method partitions the spatio-temporal graph with a mathematical definition and then trains each partitioned data with an arbitrary STGNN model on edge servers separately. Then, it aggregates all the model parameters in the central cloud with dramatically reduced network usage. Through experiments, we demonstrate that the FedSTGNN framework could train the model with a reduced amount of network communication by utilizing the advantages of edge computing and a slight loss in accuracy. © 2024 IEEE.

关键词： Spatio-temporal data

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Data-Driven Disturbance Compensation for DC Motors 23

Data-Driven Disturbance Compensation for DC Motors

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23rd International Conference on Control, Automation and Systems, ICCAS 2023

作者： Lee, Jaeho Eun, Yongsoon Dgist Department of Electrical Engineering and Computer Science Daegu42988 Korea Republic of

ISBN: (纸本)9788993215274

This paper presents applications of recently developed data-driven disturbance observer [1] for DC motor control. The proposed approach enables effective compensation for external disturbances, allowing for robust control even in the presence of noise or other interfering factors. By utilizing data-driven techniques, the disturbance observer learns the system dynamics from the behavior of the system to accurately estimate and compensate for disturbances. Experimental results demonstrate the effectiveness of the proposed data-driven observer in mitigating the impact of disturbances and improving the overall control performance of the motor system. © 2023 ICROS.

关键词： DC motors

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Enhancing Image Security with Rossler Attractor-Based Encryption 2

Enhancing Image Security with Rossler Attractor-Based Encryp...

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2nd International Conference on Cyber Resilience, ICCR 2024

作者： Al-Najjar, Hazem Al-Rousan, Nadia University Of Petra Faculty Of Information Technology Department Of Computer Science Amman Jordan German Jordanian University Faculty Of Electrical Engineering And Information Systems Department Of Computer Engineering Jordan

ISBN: (纸本)9798350394962

we introduced image encryption algorithms with high sensitivity, such that even a single alteration in a plain-text image would result in a complete transformation of the ciphered image. The first algorithm employed pixel values in a substitution approach, whereas the second algorithm utilized pixel values to generate chaotic function keys. Additionally, we employed a Rossler chaotic function with pixel data to generate chaotic values for the shuffling and substitution processes. After subjecting these algorithms to rigorous testing using standard metrics, our experiments revealed the efficiency of the algorithms in image encryption. Notably, even a minute change in the original image resulted in a vastly different ciphered image. These proposed algorithms underscored the effectiveness of integrating chaotic functions with pixel information, significantly enhancing image security. © 2024 IEEE.

关键词： Cryptography

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Evaluation of CAN Bus Security Vulnerabilities and Potential Solutions 6

Evaluation of CAN Bus Security Vulnerabilities and Potential...

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6th International Conference of Women in Data science at Prince Sultan University, WiDS-PSU 2023

作者： Alfardus, Asma Rawat, Danda B. Department of Electrical Engineering and Computer Science WashingtonDC20059 United States

ISBN: (纸本)9781665477239

The past decade has seen a significant increase in the automobile industry, which has come with some serious challenges and threats. Modem vehicles are now made up of complex mechanical systems, as well as sophisticated electronic devices and connections to the outside world. Various electronic devices utilize standard communication protocols, including the Controller Area Network (CAN), to establish communication with each other. Unfortunately, CAN lacks some fundamental security features, such as encryption and authentication, which makes it vulnerable to security attacks. This can lead to accidents and financial losses for the users of these vehicles. To address this issue, researchers have proposed a number of security measures, such as cryptography and Intrusion Detection Systems (IDS). This paper addresses the security vulnerabilities associated with CAN and proposes potential solutions to overcome its limitations. © 2023 IEEE.

关键词： Cryptography

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Full system in-house developed mission Assembly, Integration and Verification campaign for KvarkenSat, a 2U CubeSat at the Kiruna Space Campus in North Sweden 74

Full system in-house developed mission Assembly, Integration...

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74th International Astronautical Congress, IAC 2023

作者： Juan Gracia, G.-L. Peroy, Cristóbal Nieto Persson, Lars-Olov Laufer, Rene Department of Computer Science Electrical and Space Engineering Luleå University of Technology Sweden

In this paper the Assembly, Integration and Verification campaign for the 2U CubeSat KvarkenSat will be presented. This CubeSat mission is part of the Kvarken Space Center, a joint venture between six universities and institutes from Finland and Sweden, that aim to design, build and operate a CubeSat with the goal of acting as a technological demonstrator, and establish a long-term small satellite competence in the Kvarken region. To achieve this, a simple but complete quality-management approach for satellite AIV has been implemented. The integration and testing capabilities at LTU will allow further collaboration with both industry and academic organizations that will be able to use the Kiruna Space Campus facilities. Ultimately, this effort will support orbital missions from Esrange Space Center (Swedish Space Corporation): small satellites could be assembled and tested on campus and then be transported to the space center for launching. The LTU Kiruna Space Campus has developed the knowledge, resources, and tools to become the leading university in space research and technology. Copyright © 2023 by the International Astronautical Federation (IAF). All rights reserved.

关键词： AIT CubeSat MAIV qualification space-hub V&V

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Automatic Modulation Recognition Based on CNN and GRU

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Tsinghua science and Technology 2022年第2期27卷 422-431页

作者： Fugang Liu Ziwei Zhang Ruolin Zhou the Department of Electronics and Information Engineering Heilongjiang University of Science and TechnologyHarbin 150022China the Department of Electrical and Computer Engineering University of MassachusettsDartmouthMA 02747USA

Based on a comparative analysis of the Long Short-Term Memory(LSTM)and Gated Recurrent Unit(GRU)networks,we optimize the structure of the GRU network and propose a new modulation recognition method based on feature extraction and a deep learning ***-order cumulant,Signal-to-Noise Ratio(SNR),instantaneous feature,and the cyclic spectrum of signals are extracted firstly,and then input into the Convolutional Neural Network(CNN)and the parallel network of GRU for *** modulation modes of communication signals are recognized *** results show that the proposed method can achieve high recognition rate at low SNR.

关键词： modulation recognition deep learning Gated Recurrent Unit(GRU) Convolutional Neural Network(CNN)

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