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ELCD-NSC2: a novel early lung cancer detection and non-small cell classification framework

Neural Computing and Applications 2024年第24期36卷 15149-15164页

作者： Helaly, Hadeer A. Badawy, Mahmoud El-Gendy, Eman M. Haikal, Amira Y. Electrical Engineering Department Faculty of Engineering Damietta University Damietta Egypt Computers and Control Systems Engineering Department Faculty of Engineering Mansoura University Mansoura Egypt Department of Computer Science and Informatics Taibah University Medina Saudi Arabia

The survival rate of lung cancer relies significantly on how far the disease has spread when it is detected, how it reacts to the treatment, the patient’s overall health, and other factors. Therefore, the earlier the lung cancer diagnosis, the higher the survival rate. For radiologists, recognizing malignant lung nodules from computed tomography (CT) scans is a challenging and time-consuming process. As a result, computer-aided diagnosis (CAD) systems have been suggested to alleviate these burdens. Deep-learning approaches have demonstrated remarkable results in recent years, surpassing traditional methods in different fields. Researchers are currently experimenting with several deep-learning strategies to increase the effectiveness of CAD systems in lung cancer detection with CT. This work proposes a deep-learning framework for detecting and diagnosing lung cancer. The proposed framework used recent deep-learning techniques in all its layers. The autoencoder technique structure is tuned and used in the preprocessing stage to denoise and reconstruct the medical lung cancer dataset. Besides, it depends on the transfer learning pre-trained models to make multi-classification among different lung cancer cases such as benign, adenocarcinoma, and squamous cell carcinoma. The proposed model provides high performance while recognizing and differentiating between two types of datasets, including biopsy and CT scans. The Cancer Imaging Archive and Kaggle datasets are utilized to train and test the proposed model. The empirical results show that the proposed framework performs well according to various performance metrics. According to accuracy, precision, recall, F1-score, and AUC metrics, it achieves 99.60, 99.61, 99.62, 99.70, and 99.75%, respectively. Also, it depicts 0.0028, 0.0026, and 0.0507 in mean absolute error, mean squared error, and root mean square error metrics. Furthermore, it helps physicians effectively diagnose lung cancer in its early stages and allows spe

关键词： Image classification

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Path Planning for Data Collection Multiagent System with Priority and Moving Nodes in a Sensing Field with Obstacles

Periodica polytechnica Electrical engineering and computer s...

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Periodica polytechnica Electrical engineering and computer science 2024年第3期68卷 309-318页

作者： Szénási, Sára Harmati, István Department of Control Engineering and Information Technology Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Magyar tudósok körútja 2 Budapest1117 Hungary

Nowadays there is a more and more common need for one-off data collection in a specified area. For example, in case of searching for the survivors of disasters or wars, or for skiers who get into trouble. The simplest way of collecting such data is using wireless sensor network (WSN). However, data transmission within the network uses great amount of energy that may significantly reduce the lifetime and operation time of the battery-operated sensors. For this reason, the data transfer between the given sensor nodes is carried out by robots. In order to minimize the latency of data collection, it is possible to use cooperating robots. It frequently occurs that one of the nodes requires more urgent visit than the other ones, for example, the serious injuries require urgent medical attendance. The sensor nodes can also be moved to collect more usable data in a larger field. To solve this, path planning for data collection from priority and moving nodes are also presented here. The algorithm developed here to perform the one-off data collection operates so that the agents start from preliminary determined or random points and then visit all the sensor nodes, download the data from these nodes and after this arrive at a designated point where they upload the collected information. The goal here is the minimization of cost that include not only the walk-through time but also the consequences of the late visit of the higher priority nodes. The optimization is solved using the ant colony optimization. © 2024 Budapest University of Technology and Economics. All rights reserved.

关键词： Motion planning

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Algorithmic Decomposition of Railway Objects for Distributed Interlocking System

Periodica Polytechnica Electrical Engineering and Computer S...

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Periodica Polytechnica Electrical engineering and Computer Science 2024年第4期68卷 319-326页

作者： Arató, Péter Markovits, Tibor Gergely Rácz, György Department of Control Engineering and Information Technology Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Magyar tudósok krt. 2. BudapestH-1117 Hungary

Railway interlocking systems can be implemented as distributed systems, where each part of a station is handled by a separate logical unit. The logical units of such systems form a network and communicate by interchanging messages. Such distributed architectures are well known in large industrial control systems. There are several design practices and also algorithmic task partitioning methods that are applicable in distributed control systems. Some of such methods can also be adapted in designing of railway interlocking systems as well. In the case of such systems, the communication time between components must be kept low. Namely each separate controller in a given route must be able to exchange their internal state within a limited time in order to permit the train movement authorization. This limitation could cause high traffic load, if every logical unit would be interconnected with each other. Therefore, the main goal of the minimization is to reduce the number of connections between logical units. This can achieved by distributing and assigning the topological railway objects to certain logical units. © 2024 Budapest University of Technology and Economics. All rights reserved.

关键词： Distributed parameter control systems

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Robust Trajectory Tracking control of a Differentially Flat Overhead Crane Using Sliding Mode

Periodica polytechnica Electrical engineering and computer s...

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Periodica polytechnica Electrical engineering and computer science 2024年第2期68卷 213-221页

作者： Finta, Barnabás Kiss, Bálint Department of Control Engineering and Information Technology Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics University Műegyetem rkp. 3. BudapestH-1111 Hungary

The control of overhead cranes is a benchmark problem, since it is an underactuated mechanism and its mathematical model is nonlinear. During operation the mass of the load is unknown, representing an uncertainty in the inertial parameters, which requires robustness of the controlled system. Our paper proposes a novel robust control method, that combines the differentially flat property of the dynamics with the robustness of the sliding mode control. The sliding surface is constructed to ensure the tracking of the configuration variables whose accelerations is calculated using the flatness property of the dynamic model. This formulation also allows achieving the matching conditions of the parameter uncertainties. Considering a simplified overhead crane model where the load motion is restricted in a vertical plane, two sliding surfaces are defined for the rope angle and rope length, since the cart position can be calculated from the previous two. The suggested control method is successfully validated in simulations as well as using a reduced-size overhead crane. For the real crane, the rope angle was estimated by utilizing the dynamical model, which uses the estimated cart acceleration. © 2024 Budapest University of Technology and Economics. All rights reserved.

关键词： Acceleration

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Unsupervised Learning-Based Methodology for Detection of Postural Anomalies in Wheelchair Users

Unsupervised Learning-Based Methodology for Detection of Pos...

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2023 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2023

作者： Vermander, Patrick Mancisidor, Aitziber Fortino, Giancarlo Cabanes, Itziar Gravina, Raffaele Department of Automatic Control and System Engineering Bilbao Spain Department of Informatics Modeling Electronics and Systems Engineering Rende Italy

ISBN: (纸本)9798350337020

Postural monitoring in wheelchair users is a topic of growing interest. The detection of changes in the sitting patterns of these patients may serve to detect changes in their functional status and be able to adapt rehabilitation early. For this reason, this paper presents a methodology for the detection of specific postural anomalies that, unlike previous works, adopts unsupervised learning. The proposed methodology involves data dimensionality reduction using Principal Component Analysis, and the application of K-means clustering to group different normal posture states. The anomalies are detected using a threshold approach, where data points that fall outside a certain threshold are considered as anomalies. The results show that the methodology is effective in identifying anomalies with a high degree of accuracy (around 90%). © 2023 IEEE.

关键词： Anomaly detection Kmeans PCA Postural monitoring Wheelchair

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An Evaluation of the Dual Vectors Based Solutions for Robot-World/Hand-Eye Calibration 1

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25th International Symposium on Measurement and control in Robotics, ISMCR 2023

作者： Ganciu, Aura Burlacu, Adrian Department of Automatic Control and Applied Informatics Faculty of Automatic Control and Computer Engineering "Gheorghe Asachi" Technical University of Iași Iași Romania

ISBN: (数字)9783031510854

ISBN: (纸本)9783031510847

The hand-eye calibration problem represents a major challenge in robotics, arising from the widespread usage of robotic systems along with robot-mounted sensors. Briefly, consisting of estimating the position and orientation of a visual sensor (usually a camera attached to the robot’s end-effector) with respect to the robot itself, calibration is critical in tracking rigid bodies—a common task within mixed reality applications. Hand-eye calibration implies solving the problem formulated as AX = XB or AX = YB equations. The solution lies in computing the unknown homogeneous transformation matrices X and Y, given the A and B parameterizations of rigid body motions. We present the dual vectors based approaches for AX = XB and AX = YB calibration problems, making use of the isomorphism between the special Euclidean group and the orthogonal dual tensor group. Comparisons with state-of-the-art algorithms are used to assess our obtained results. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Mixed reality

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Novel Framework of Segmentation 3D MRI of Brain Tumors

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Computers, Materials & Continua 2023年第2期74卷 3489-3502页

作者： Ibrahim Mahmoud El-Henawy Mostafa Elbaz Zainab H.Ali Noha Sakr Department of Computer Science Faculty of Computers and InformaticsZagazig UniversityZagazigEgypt Department of Computer Science Faculty of Computers and InformaticsKafrelsheikh UniversityKafrelsheikhEgypt Department of Embedded Network Sys.and Tec. Faculty of Artificial IntelligenceKafrelsheikh UniversityKafrelsheikhEgypt Computers Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansouraEgypt

Medical image segmentation is a crucial process for computer-aided diagnosis and *** image segmentation refers to portioning the images into small,disjointed parts for simplifying the processes of analysis and *** and speckle noise are different types of noise in magnetic resonance imaging(MRI)that affect the accuracy of the segmentation process ***,image enhancement has a significant role in MRI *** paper proposes a novel framework that uses 3D MRI images from Kaggle and applies different diverse models to remove Rician and speckle noise using the best possible noise-free *** proposed techniques consider the values of Peak Signal to Noise Ratio(PSNR)and the level of noise as inputs to the attention-U-Net model for segmentation of the *** framework has been divided into three stages:removing speckle and Rician noise,the segmentation stage,and the feature extraction *** framework presents solutions for each problem at a different stage of the *** the first stage,the framework uses Vibrational Mode Decomposition(VMD)along with Block-matching and 3D filtering(Bm3D)algorithms to remove the ***,the most significant Rician noise-free images are passed to the three different methods:Deep Residual Network(DeRNet),Dilated Convolution Auto-encoder Denoising Network(Di-Conv-AE-Net),andDenoising Generative Adversarial Network(DGAN-Net)for removing the speckle *** Bm3D have achieved PSNR values for levels of noise(0,0.25,0.5,0.75)for reducing the Rician noise by(35.243,32.135,28.214,24.124)and(36.11,31.212,26.215,24.123)*** framework also achieved PSNR values for removing the speckle noise process for each level as follows:(34.146,30.313,28.125,24.001),(33.112,29.103,27.110,24.194),and(32.113,28.017,26.193,23.121)forDeRNet,Di-Conv-AE-Net,and DGAN-Net,*** experiments that have been conducted have proved the efficiency of the proposed framework a

关键词： MRI Rician noise speckle noise segmentation deep learning

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A Collaborative Graph-based SLAM Framework Using a Computationally Effective Measurement Algebra

Periodica polytechnica Electrical engineering and computer s...

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Periodica polytechnica Electrical engineering and computer science 2023年第4期67卷 403-412页

作者： Péter, Gábor Kiss, Bálint Department of Control Engineering and Information Technology Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Műegyetem rkp. 3. BudapestH-1111 Hungary

Simultaneous localization and mapping (SLAM) is an essential task for autonomous rover navigation in an unknown environment, especially if no absolute location information is available. This paper presents a computationally lightweight framework to enable agents with limited processing power to carry out the SLAM cooperatively and without absolute onboard localization sensors in a 2D environment. The proposed solution is built on a graph-based map representation, where nodes (resp. edges) represent landmarks (resp. odometry-based relative measurements), a measurement algebra with embedded uncertainty, and a compact database format that could be stored on a server in a centralized manner. The operations required by the agents to insert a new landmark in the graph, update landmark positions and combine measurements as a loop is closed in the graph are detailed. The resulting framework was tested in a laboratory environment and on a public dataset with encouraging results;hence our method can be used for cost-effective indoor mobile agents with limited computational resources and onboard sensors to achieve a mapping while keeping track of the agent’s position. The method can also be easily generalized for a 3D scenario. © 2023 Budapest University of Technology and Economics. All rights reserved.

关键词： Mobile agents

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Robust Aerodynamic Parameter Estimation of Unmanned Aircraft Based on Two-step Identification

Periodica polytechnica Electrical engineering and computer s...

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Periodica polytechnica Electrical engineering and computer science 2023年第4期67卷 394-402页

作者： Kimathi, Stephen Lantos, Bela Department of Control Engineering and Information Technology Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Magyar tudósok krt. 2. BudapestH-1117 Hungary

This paper presents the estimation of stability and control derivatives of an unmanned aircraft. The aerodynamics are described using regressors composed of velocity, angular rates, flow angles and control surface deflections. The flight data is generated from numerical simulation of postulated equations of motion describing the aerodynamics model. Least squares based on the equation error method is used to estimate the parameters representing the different force and moment aerodynamic coefficients. Statistical analysis is done on the estimates to determine the accuracy and adequacy of the estimates to describe the aerodynamic model. A dynamic simulation based on the identified aerodynamic model is used to improve the parameter estimates through regression of the errors between the flight data and the model response. The aircraft under consideration is a scaled Yak-54 fixed wing unmanned aerial vehicle. © 2023 Budapest University of Technology and Economics. All rights reserved.

关键词： Fixed wings

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Development of Motion Analysis Tool for Orthopedic Diseases: Inertial Measurements 6th

Development of Motion Analysis Tool for Orthopedic Diseases:...

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6th Computational Methods in Systems and Software, CoMeSySo 2022

作者： Jicinsky, Pavel Mares, Jan Department of Process Control Faculty of Electrical Engineering and Informatics University of Pardubice Pardubice Czech Republic

ISBN: (纸本)9783031214349

Rehabilitation in orthopedics is one of the most important processes that influence the patient’s quality of life. In today’s practice, the orthopedic assessments still depend mainly on subjective view of physician. To further objectify the results, a wearable electronic device was developed based on inertial sensors. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： IMU Motion analysis Orthopedics Signal acquisition and processing

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