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8th International Conference on control Science and systems engineering, ICCSSE 2022

作者： Ren, Jing Gabbar, Hossam A. Huang, Xishi Saberironaghi, Alireza Ontario Tech University Dept. of Electrical and Computer Engineering OshawaON Canada Faculty of Energy Systems and Nuclear Science Engineering and Applied Science Ontario Tech University OshawaON Canada Rs Opto Tech Ltd Jiangsu Suzhou China

ISBN: (纸本)9781665484138

In many industrial applications, the number of defect samples is often insufficient for defect detection using conventional deep learning techniques. Also, the frequent change of PCBA board types on the product line introduces new defect types and adds a layer of challenge to the detection task considered in this paper. We propose a deep learning algorithm that targets learning patterns from various defect types with unbalanced training samples in the PCBA manufacturing product lines. A novel batch sampling method is proposed for the deep learning method for PCBA defect detection. We have validated the proposed algorithm using normal and defective images. The results show that the proposed deep learning method can accurately identify defects in PBCA images and achieve an overall accuracy of 98%. This deep learning technique can also be extended to detect other surface-level defects. © 2022 IEEE.

关键词： Defects

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Mathematical Model of Damping of UAV Oscillations in the Cargo Delivery Problem

Mathematical Model of Damping of UAV Oscillations in the Car...

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Advanced Technology (KhPIWeek), IEEE KhPI Week on

作者： Dmytro Kucherov Tetiana Shmelova Olexii Poshyvailo Valerii Tkachenko Ignat Miroshnichenko Ihor Ogirko dept. Computerized Control Systems Faculty of Computer Science and Technology National Aviation University Kyiv Ukraine dept. Air Navigation Systems Faculty of Air Navigation Electronics and Telecommunications National Aviation University Kyiv Ukraine dept. Mathematic Ukrainian Academy of Printing City Lviv Ukraine

Currently, the use of unmanned vehicles for the delivery of goods is becoming a trend in many areas of human activity. At the same time, it is necessary to solve the problem of the integrity of the cargo because of its possible fluctuations. The paper deals with the problem of delivering cargo attached to a 4-motor UAV on a rigid cable. A control system is needed to achieve the UAV equilibrium position that can compensate for significant mismatches in the XY coordinate plane. A combination of two control algorithms is proposed for solving this problem, one of which provides a given position in the horizontal plane at small mismatch angles and the second at large mismatch angles. The first controller uses the PID controller algorithm with the corresponding optimal setting of its parameters, and the second one uses the bang-bang control scheme. An additional controller is used to coordinate these controllers, which ensures their timely switching. Some simulation is also proposed.

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Fuzzy Logic controller for the Chemotherapy of Brain Tumor

Fuzzy Logic Controller for the Chemotherapy of Brain Tumor

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International Conference on control, Decision and Information Technologies (CoDIT)

作者： Muhammad Zubair Daniela Iacoviello Iqra Shafeeq Mughal Dept. Computer Control and Management Engineering Sapienza University of Rome Rome Italy Dept. di Ingegneria Electrica Electronica e Informatica DIEEI University of Catania Catania Italy

An advanced Fuzzy Logic controller (FLC) that considers all the states of the brain tumor system is designed for the chemotherapy treatment. A Mamdani-type FLC is proposed for dynamically controlling the chemotherapy drug for the tumor system; the chemotherapy treatment of brain tumors requires advanced strategies which mainly depend upon the severity of the tumor. In this work, the advanced FLC designed aims both at determining the amount of chemotherapy to eliminate tumor cells, and at preserving the minimum amount of healthy and immune cells. The controller's performance is verified using MATLAB software based on different control parameters, showing its effectiveness in reducing the tumor cells. It has shown favorable results in terms of steady-state error, rate of convergence, and amount of drug consumed.

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Price Optimisation and Management 3

Price Optimisation and Management

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3rd International Conference on Advancements in Computing, ICAC 2021

作者： Shafkhan, M.T.M Jayasundara, P.R.S.S Kariyapperuma, K.A.D.R.L Lakruwan, H.P.S Rupasinghe, Lakmal Sri Lanka Institute of Information Technology Dept. of Computer and Software Eng Malabe Sri Lanka Sri Lanka Institute of Information Technology Dept. of Computer Systems Engineering Malabe Sri Lanka

ISBN: (纸本)9781665408622

One of the most crucial decisions a company makes is its pricing strategy. When it comes to pricing, a company must consider the present, as well as the future and the past pricing. It enables a company to make sound judgments. In the process of marketing products, price is the only factor that creates income;everything else is a cost. Guessing at product pricing is a little like throwing darts blindfolded;some will hit something, but it probably will not be the dartboard. Large-scale enterprises throughout the world still depend on Excel sheets with numerous manpower or expensive pricing solutions. Expensive pricing systems are difficult to implement for Medium and Large Sized Enterprises in countries like Sri Lanka. Our goal in this research is to propose an affordable, efficient, easy-To-use and secure solution which can be implemented in Medium and Large Sized Enterprises in Sri Lanka. Manufacturing cost, shipping cost, competitor analysis, customer behaviour are taken as the root factors when deciding the price. The proposed solution includes Machine Learning components which is fed with historical data of these four factors to predict the manufacturing cost, shipping cost, competitor price and customer behavioural factors on a given date and as well as an optimisation component which enables the opportunities to minimise the cost and maximise the profit. The four Machine Learning components are implemented using LSTM, ARIMA, Facebook Prophet and a clustering model. The optimisation model is implemented using linear programming optimise these four components. A user-friendly web application is implemented using MEAN stack with micro service architecture to access this. © 2021 IEEE.

关键词： Cost benefit analysis

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Uncertainty-Aware Deep Learning for Segmenting Ultrasound Images of Breast Tumours

Uncertainty-Aware Deep Learning for Segmenting Ultrasound Im...

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IEEE International Conference on systems, Man and Cybernetics

作者： Afsana Ahmed Munia Ibrahim Hossain Seyed Mohammad Jalali Pegah Tabarisaadi Ashikur Rahman Saeid Nahavandi Institute for Intelligent Systems Research and Innovation Deakin University VIC Australia Dept. of Computer Science and Engineering Bangladesh University of Engineering and Technology Dhaka Bangladesh

Precise image segmentation is one of the dominant factors in disease diagnosis. A typical application is the segmentation of breast ultrasound images, allowing radiologists to suggest what to do next. After emerging deep learning technology especially convolutional neural networks (CNNs), the image segmentation model achieved state-of-the-art performance in various medical applications such as cancer detection and classification, lung node segmentation, cell segmentation and so on. However, despite these successes, a big question arises: to what extent is the model certain about the predicted result? Generally, most deep learning models focus on high accuracy but not on uncertainty of predicted results, which is not enough to make a critical real-life decision such as a disease diagnosis, where a wrong decision can be life-threatening. Hence for making a crucial decision, it is essential that the predicted result will provide not only accuracy but also estimate model uncertainty. Our contribution to this research is to build a system that predicts pixel-wise semantic segmentation and provides uncertainty estimation of the predicted results. It is achieved by adding a dropout layer during training and using Monte Carlo dropout in inference. We evaluate our model with the breast ultrasound image dataset (BUSI) and compare the results with a few other state-of-the-art methods where our method outperforms others in terms of IoU.

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A Method Based on Ellipse Fitting for Automatic Morphometric Parameter Measurements of Fish Blood Cells

A Method Based on Ellipse Fitting for Automatic Morphometric...

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IEEE International Workshop on Medical Measurement and Applications (MEMEA)

作者： Imran Ahmed Eulalia Balestrieri Pasquale Daponte Francesco Lamonaca Department of Engineering University of Sannio Benevento Italy Dept. of Computer Science Modelling Electronics and Systems Engineering University of Calabria Arcavacata di Rende Italy

Thanks to their sensitivity to different changes affecting the environment and capability of demonstrating the impacts of various pollutant types, fishes are considered valuable and suitable species to be used as bioindicators for the water body pollution. Measurement of Morphometric parameters of Fish Erythrocytes (MFE) has been considered a valuable approach for analysis of health status of fishes. Conventional MFE measurement methods have several limitations, including poor measurement reproducibility and reliability, since they rely mainly on the human expertise, as well as required intensive highly time-consuming work to take measurements manually. To address these issues, this work presents a solution based on image processing and ellipse fitting technique to automatically measure MFE. The proposed method first applies customized image processing steps to locate cells in the image, segments nucleus and border of cells, and then uses the ellipse fitting algorithm to fit ellipse on detected cell/nucleus. The effectiveness of the proposed method has been validated through the comparison of results carried out by two expert biologists. The experimental results show that the proposed method properly fit the ellipse on both fish blood cell and its nucleus, indicating its potential as a promising tool for biomonitoring applications.

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Proactive Network Traffic Prediction using Generative Adversarial Network

Proactive Network Traffic Prediction using Generative Advers...

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International Conference on Information Networking

作者： Gyurin Byun Van-Vi Vo Syed M. Raza Duc-Tai Le Huigyu Yang Hyunseung Choo Dept. of AI Systems Engineering Sungkyunkwan University Suwon South Korea Convergence Research Institute Sungkyunkwan University Suwon South Korea Dept. of Electrical and Computer Engineering Sungkyunkwan University Suwon South Korea College of Computing and Informatics Sungkyunkwan University Suwon South Korea Dept. of Superintelligence Engineering Sungkyunkwan University Suwon South Korea

ISBN: (数字)9798350330946

ISBN: (纸本)9798350330953

Proactive traffic management in 5G networks is crucial for optimizing network efficiency, ensuring quality of service, adapting to dynamic conditions, and enhancing the user experience. In this paper, we propose a Generative Adversarial Network (GAN) architecture that leverages spatiotemporal features in network traffic data to predict future traffic. Our approach incorporates a Convolutional Long Short-Term Memory (ConvLSTM) model within the generator of the GAN, which collaborates with the discriminator, utilizing a Convolutional Neural Network (CNN) model, to provide essential feedback for training the generator. This integration ensures that our model not only predicts future traffic with improved accuracy but also adapts to dynamic network conditions. Based on experimental results using network traces, our model significantly outperforms the baseline, reducing prediction error by 12% while forecasting network traffic for the next 1 minute. These findings represent a significant advancement in proactive network management, particularly in addressing the challenges posed by real-time streaming and other latency-sensitive applications in 5G networks.

关键词： Training Adaptation models 5G mobile communication Telecommunication traffic Predictive models Generative adversarial networks Generators

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Path-Integral Formula for Computing Koopman Eigenfunctions

arXiv

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arXiv 2023年

作者： Deka, Shankar A. Narayanan, Sriram S.K.S. Vaidya, Umesh The Decision and Control Systems division The Dept. of Electrical Engr. and Computer Science KTH Royal Institute of Technology Sweden The Dept. of Mechanical Engr. Clemson University SC Clemson United States

The paper is about the computation of the principal spectrum of the Koopman operator (i.e., eigenvalues and eigenfunctions). The principal eigenfunctions of the Koopman operator are the ones with the corresponding eigenvalues equal to the eigenvalues of the linearization of the nonlinear system at an equilibrium point. The main contribution of this paper is to provide a novel approach for computing the principal eigenfunctions using a path-integral formula. Furthermore, we provide conditions based on the stability property of the dynamical system and the eigenvalues of the linearization towards computing the principal eigenfunction using the path-integral formula. Further, we provide a Deep Neural Network framework that utilizes our proposed path-integral approach for eigenfunction computation in high-dimension systems. Finally, we present simulation results for the computation of principal eigenfunction and demonstrate their application for determining the stable and unstable manifolds and constructing the Lyapunov function. © 2023, CC BY.

关键词： Eigenvalues and eigenfunctions

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Direct Data-Driven State-Feedback control of Linear Parameter-Varying systems

arXiv

引用

arXiv 2022年

作者： Verhoek, Chris Tóth, Roland Abbas, Hossam S. Control Systems group Dept. of Electrical Engineering Eindhoven University of Technology Eindhoven Netherlands Systems and Control Lab Institute for Computer Science and Control Budapest Hungary Institute for Electrical Engineering in Medicine Universität zu Lübeck Lübeck Germany

The framework of linear parameter-varying (LPV) systems has shown to be a powerful tool for the design of controllers for complex nonlinear systems using linear tools. In this work, we derive novel methods that allow to synthesize LPV state-feedback controllers directly from only a single sequence of data and guarantee stability and performance of the closed-loop system. We show that if the measured open-loop data from the system satisfies a persistency of excitation condition, then the full open-loop and closed-loop input-scheduling-state behavior can be represented using only the data. With this representation we formulate data-driven analysis and synthesis problems, where the latter yields controllers that guarantee stability and performance in terms of infinite horizon quadratic cost, generalized H2-norm and 2-gain of the closed-loop system. The controllers are synthesized by solving a semi-definite program. Additionally, we provide a synthesis method to handle noisy measurement data. Competitive performance of the proposed data-driven synthesis methods is demonstrated w.r.t. model-based synthesis in multiple simulation studies, including a nonlinear unbalanced disc system. © 2022, CC BY-NC-SA.

关键词： State feedback

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Understanding the Quantum Teleportation Protocol

Understanding the Quantum Teleportation Protocol

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computer Science, computer engineering, & Applied Computing (CSCE), Congress in

作者： Kurt T. Spranger Michael R. Grimaila Douglas D. Hodson Dept. of Systems Engineering and Mgmt. Air Force Institute of Technology Wright-Patterson AFB OH Dept. of Electrical & Computer Engineering Air Force Institute of Technology Wright-Patterson AFB OH

Decomposing a complex system into smaller abstract functional blocks and developing mathematical models to represent their behavior is an important activity towards developing comprehensive system understanding. In this paper, we decompose the ideal Quantum Teleportation protocol into a collection of simple quantum circuit blocks, examine the behavior of each block, and show how collections of blocks operate to create more complex circuits. We believe this approach greatly simplifies the understanding of how the Quantum Teleportation protocol works. This paper is introductory in nature and is intended to help those who are new to modeling, simulating, and analyzing ideal quantum circuits.

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