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Design and comparison of particle swarm optimization tuned Kalman filter based linear quadratic Gaussian controller and linear quadratic regulator for surface to air missile guidance system

Advanced Control for Applications: Engineering and Industria...

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Advanced Control for Applications: engineering and Industrial Systems 2024年第3期6卷

作者： Alitasb, Girma Kassa Beyene, Getasew Mekonnen Salau, Ayodeji Olalekan School of Electrical and Computer Engineering Debre Markos University Debre Markos Ethiopia Department of Electrical and Computer Engineering Debre Berhan University Debre Berhan Ethiopia Department of Electrical/Electronics and Computer Engineering Afe Babalola University Ado-Ekiti Nigeria Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India

The study of missile guidance systems is a well-known nonlinear control engineering area of research. To enhance the control performance of a missle guidance system, several technologies have been proposed in existing works. To resolve the weighting matrix selection issue of a linear quadratic Gaussian (LQG) controller for the surface-to-air missile guidance control system, this study utilizes the particle swarm optimization (PSO) technique. Selecting the best state (Q) and input (R) weighting matrices is a significant difficulty in the design of the LQG controller for real-time applications since it affects the controller's performance and optimality. The weighting matrices are often chosen by a trial-and-error method that not only complicates the design but also does not yield optimal outcomes. Therefore, in this paper, a PSO method is developed and used in the design of the linear quadratic regulator (LQR) and LQG controllers for the surface-to-air missile control system to choose the elements of the Q and R matrices in the best possible way. Finally, a comparative analysis between the designed controllers was presented. The results shows that a good performance was achieved by using the proposed PSO-tuned design process. The LQG and LQR are designed by manually adjusting the weighting matrices and utilizing an intelligent procedure, PSO algorithm which achieved optimal results. Further results indicate that the designed controllers, the PSO tuned LQR and LQG achieved a better performance over the manually adjusted LQR and LQG controllers. © 2024 John Wiley & Sons Ltd.

关键词： Surface to air missiles

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Deep Learning based Smart American Sign Language Detection in Alphabets 6

Deep Learning based Smart American Sign Language Detection i...

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6th International Conference on Contemporary Computing and Informatics, IC3I 2023

作者： RukumaniKhandhan, C. Vijayakumar, P. Sri Sabari, C. Arun, G. Chandrasekaran, N. Rohith Bhat, C. Kongu Engineering College Department of Computer Technology - PG Erode Perundurai India Kongu Engineering College Department of Master of Computer Applications Tamil Nadu Perundurai India Kongu Engineering College Department of Computer Technology - PG Tamil Nadu Perundurai India Erode Sengunthar Engineering College Department of Artificial Intelligence and Data Science Thuduppathi India PSNA College of Engineering and Technology Department of Electrical and Electronics Engineering Dindigul India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350304480

Disabled people are of different kinds like physically challenged people, mentally challenged etc. To help the people who cannot convey their thoughts and who cannot hear others thoughts, sign language is being used to communicate with them. Sign language is something that is used to communicate through body movements mainly through hands and *** Sign Language(ASL) is an authorized sign language that is taught and used widely. ASL is difficult to teach and learn for them because it is completely new and they have no knowledge about it. In this research paper the ASL is recognized and converted into text through data mining techniques. The study uses a dataset of ASL alphabet images and applies various data mining techniques, including feature selection, classification, and clustering. The features extracted from the images include shape, size, color, and texture. The use of neural networks, decision trees, and support vector machines speeds up the data categorization process. Techniques such as k-means clustering and hierarchical grouping are used to facilitate entity grouping. The results show that the best performance is achieved using a combination of feature selection and classification techniques. The decision tree algorithm with the selected features achieves an accuracy of 96.5% on the test dataset. The system can accurately recognize all the ASL alphabets and convert them into text or speech. The system developed can be used to improve communication between deaf and hearing individuals and can be extended to recognize other ASL gestures and phrases. Future research can focus on real-time detection and recognition of ASL gestures using data mining techniques. CNN algorithm is used to recognize the image based on the images collected. The accuracy rate gets low and the detection is inaccurate. Therefore, VGG16 algorithm is used to recognize the images and it is unique in convolutional models. © 2023 IEEE.

关键词： ASL CNN Gestures VGG16

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Marine Predators Algorithm with Deep Learning-Based Leukemia Cancer Classification on Medical Images

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computer Modeling in engineering & Sciences 2024年第10期141卷 893-916页

作者： Sonali Das Saroja Kumar Rout Sujit Kumar Panda Pradyumna Kumar Mohapatra Abdulaziz S.Almazyad Muhammed Basheer Jasser Guojiang Xiong Ali Wagdy Mohamed Department of Computer Science&Engineering Gandhi Institute for TechnologyBPUTBhubaneswar752054India Department of Information Technology Vardhaman College of Engineering(Autonomous)Hyderabad501218TelanganaIndia Department of Electronic&Communication Engineering Vedang Institute of TechnologyBhubaneswar752010India Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia Department of Computing and Information Systems School of Engineering and TechnologySunway UniversityJalan UniversitiBandar SunwaySelangor Darul Ehsan47500Malaysia Research Centre for Human-Machine Collaboration(HUMAC) School of Engineering and TechnologySunway UniversityJalan UniversitiBandar SunwaySelangor Darul Ehsan47500Malaysia Guizhou Key Laboratory of Intelligent Technology in Power System College of Electrical EngineeringGuizhou UniversityGuiyang550025China Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Applied Science Research Center Applied Science Private UniversityAmman11931Jordan

In blood or bone marrow,leukemia is a form of cancer.A person with leukemia has an expansion of white blood cells(WBCs).It primarily affects children and rarely affects *** depends on the type of leukemia and the extent to which cancer has established throughout the *** leukemia in the initial stage is vital to providing timely patient *** image-analysis-related approaches grant safer,quicker,and less costly solutions while ignoring the difficulties of these invasive *** can be simple to generalize computer vision(CV)-based and image-processing techniques and eradicate human *** researchers have implemented computer-aided diagnosticmethods andmachine learning(ML)for laboratory image analysis,hopefully overcoming the limitations of late leukemia detection and determining its *** study establishes a Marine Predators Algorithm with Deep Learning Leukemia Cancer Classification(MPADL-LCC)algorithm onMedical *** projectedMPADL-LCC system uses a bilateral filtering(BF)technique to pre-process medical *** MPADL-LCC system uses Faster SqueezeNet withMarine Predators Algorithm(MPA)as a hyperparameter optimizer for feature ***,the denoising autoencoder(DAE)methodology can be executed to accurately detect and classify leukemia *** hyperparameter tuning process using MPA helps enhance leukemia cancer classification *** results are compared with other recent approaches concerning various measurements and the MPADL-LCC algorithm exhibits the best results over other recent approaches.

关键词： Leukemia cancer medical imaging image classification deep learning marine predators algorithm

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Micron-resolved quantum precision measurement of magnetic field at the Tesla level

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Chinese Physics B 2024年第12期33卷 95-99页

作者： Si-Han An Shi-Yu Ge Wen-Tao Lu Guo-Bin Chen Sheng-Kai Xia Ai-Qing Chen Cheng-Kun Wang Lin-Yan Yu Zhi-Qiang Zhang Yang Wang Gui-Jin Tang Hua-Fu Cheng Guan-Xiang Du College of Telecommunications and Information Engineering Nanjing University of Posts and TelecommunicationsNanjing 210003China Portland Institute Nanjing University of Posts and TelecommunicationsNanjing 210023China The School of Mechanical and Electrical Engineering Suqian CollegeSuqian 223800China School of Computer Science Nanjing University of Posts and TelecommunicationsNanjing 210023China School of Science Nanjing University of Posts and TelecommunicationsNanjing 210023China Yichang Testing Technique R&D Institute Yichang 443003China

We develop a quantum precision measurement method for magnetic field at the Tesla level by utilizing a fiber diamond *** to our system is a micron-sized fiber diamond probe positioned on the surface of a coplanar waveguide made of nonmagnetic *** with a nuclear magnetic resonance magnetometer,this probe demonstrates a broad magnetic field range from 10 mT to 1.5 T with a nonlinear error better than 0.0028%under a standard magnetic field generator and stability better than 0.0012%at a 1.5 T magnetic ***,we demonstrate quantitative mapping of the vector magnetic field on the surface of a permanent magnet using the diamond magnetometer.

关键词： nitrogen-vacancy center fiber diamond magnetometer precision measurement

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Efficient Permutation and Diffusion Model based on TCMT for Image Encryption 2

Efficient Permutation and Diffusion Model based on TCMT for ...

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2nd IEEE International Conference on Intelligent Technologies, CONIT 2022

作者： Sandhu, Mandeep Kaur Singh, Surender Kaur, Manjit Chandigarh University Computer Science and Engineering Punjab Gharuan India Gwangju Institute of Science and Technology School of Electrical Engineering and Computer Science Korea Republic of

ISBN: (数字)9781665484077

ISBN: (纸本)9781665484077

Chaos contains unique properties that are well-suited to the cryptography area. Due to their simplicity and chaotic nature, for security-related challenges, one-dimensional chaotic maps are often used, as opposed to multidimensional chaotic maps, which can be difficult to create and evaluate. Classic one-dimensional chaotic maps, on the other hand, have a limited spectrum of chaotic behavior. We present novel one-dimensional chaotic maps in this study, including a combination Tent-Cubic map (TC). To provide a wide spectrum of chaotic behavior, we proposed a 1-dimensional chaotic map by mixing classical and basic one-dimensional chaotic maps. Afterward, an efficient image encryption scheme named (TCMT) is proposed. It consists of two modules, Tent-Cubic map and Mersenne-permutation Twister's technique are used in each module to perform permutations and diffusion. It has low correlation coefficients, a huge keyspace, and the histogram is uniformly distributed, as well as resistance to different assaults, according to the simulation results. © 2022 IEEE.

关键词： Cryptography

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Dual-Layer Based Microgrid Protection Using Voltage Synchrophasors

Dual-Layer Based Microgrid Protection Using Voltage Synchrop...

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2023 IEEE PES Innovative Smart Grid Technologies Europe, ISGT EUROPE 2023

作者： Menezes, Thiago S. Coury, Denis V. Fernandes, Ricardo A.S. Department of Electrical and Computer Engineering São Carlos School of Engineering University of São Paulo São Carlos Brazil Department of Electrical Engineering Federal University of São Carlos São Carlos Brazil

ISBN: (纸本)9798350396782

Distribution networks have been facing many changes in recent years, mainly considering their integration with microgrids. Their combined use has several operational challenges, such as power quality issues, system instability, and protection problems. Considering the decreased costs of phasor measurement units (PMUs), many protection schemes have been proposed using these devices. Thus, this paper presents a dual-layer protection for microgrids based on the RMS value of voltage measurements. The first layer uses conventional overcurrent relays to detect faults. In case of failure or delayed operation of these relays, a second layer device should operate, which utilizes the voltage from strategically allocated PMUs. In this context, if necessary, the second layer device sends a remote trip signal. The proposed method was evaluated for all fault types, considering different microgrid operation modes and power injection from distributed generators. Overall, the dual-layer protection significantly improved the microgrid protection reliability, regardless of its operation mode. © 2023 IEEE.

关键词： Fault detection microgrid protection synchrophasor undervoltage

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Fundus Image Classification via an Integrated Deep Learning Model and Random Forest for Glaucoma Diagnostics 2nd

Fundus Image Classification via an Integrated Deep Learnin...

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2nd International Conference on Intelligent Manufacturing and Robotics, ICIMR 2024

作者： Zeng, Haotian Cong, Jiheng Hong, Hantong Yu, Zihan Zhang, Fan Li, Guojie School of Advanced Technology Xi’an Jiaotong-Liverpool University Suzhou China School of Robotics Xi’an Jiaotong-Liverpool University Suzhou China Hebei University of Environmental Engineering Qinhuangdao China School of Electrical Engineering Electronics and Computer Science University of Liverpool Liverpool United Kingdom

ISBN: (纸本)9789819639489

Glaucoma is a leading cause of irreversible blindness, often worsened by delayed diagnosis. Traditional diagnostic methods have limitations in early detection and require significant expertise. Recent advancements in machine learning and deep learning have shown promise in enhancing the diagnostic accuracy and efficiency of glaucoma detection using fundus imagery. This study presents a four-stage method for glaucoma classification. Fundus images are processed using VGG16 and ViT for feature extraction, capturing both local and global features. These features are then fused and reduced in dimensionality using Principal Component Analysis. Finally, the reduced features are classified using a Random Forest classifier. The integrated feature fusion model demonstrates significant improvements in diagnostic performance, achieving higher accuracy, specificity, and sensitivity in distinguishing between non-referable and referable glaucoma classes compared to traditional methods. Specifically, our model achieved an accuracy of 94.2%, an F1 score of 94.2%, a sensitivity of 94.44%, and a specificity of 94.0%. The use of both CNNs and ViTs for feature extraction leverages their strengths, resulting in a more effective diagnostic tool. The combination of CNNs, ViTs, and Random Forest classifiers, along with advanced data augmentation techniques, shows substantial potential for early glaucoma detection and ongoing monitoring. This approach addresses the limitations of current machine learning models and enhances diagnostic accuracy and efficiency, making it a promising tool for clinical settings. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Ophthalmology

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ArcText: A Unified Text Approach to Describing Convolutional Neural network Architectures

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2022年第4期3卷 526-540页

作者： Sun, Yanan Yen, Gary G. Xue, Bing Zhang, Mengjie Lv, Jiancheng Sichuan University College of Computer Science Chengdu610065 China Nanjing University State Key Laboratory for Novel Software Technology Nanjing210023 China Oklahoma State University School of Electrical and Computer Engineering StillwaterOK74078 United States Victoria University of Wellington School of Engineering and Computer Science Wellington6140 New Zealand

The superiority of convolutional neural networks (CNNs) largely relies on their architectures that are usually manually crafted with extensive human expertise. Unfortunately, such kind of domain knowledge is not necessarily owned by every interested user. Data mining on existing CNNs can discover useful patterns and fundamental comments from their architectures, providing researchers with strong prior knowledge to design effective CNN architectures when they have no expertise in CNNs. There are various state-of-the-art data mining algorithms at hand, while there is only rare work on mining CNN architectures. One of the main reasons is the gap between CNN architectures and data mining algorithms. Specifically, the current CNN architecture descriptions cannot be exactly vectorized to feed to a data mining algorithm. In this article, we propose a unified approach, named ArcText, to describing CNN architectures based on text. Particularly, four different units and an ordering method have been elaborately designed in ArcText, to uniquely describe the same CNN architecture with sufficient information. Also, the resulted description can be exactly converted back to the corresponding CNN architecture. ArcText bridges the gap between CNN architectures and data mining researchers, and has the potential to be utilized to wider scenarios. © 2020 IEEE.

关键词： Data mining

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Impedance Emulation Control of Wave Energy Converters

Impedance Emulation Control of Wave Energy Converters

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Annual Conference of Industrial Electronics Society

作者： Pranav Chandran InYong Kim Ted Brekken B. Johnson Chandra Family Department of Electrical and Computer Engineering University of Texas at Austin Austin TX School of Electrical Engineering and Computer Science Corvallis OR

ISBN: (数字)9781665464543

ISBN: (纸本)9781665464550

Modeling and control of wave energy conversion (WEC) systems for maximum power extraction is challenging due to complex multiphysics that include fluids, mechanics, and machine drives. To uncover an intuitive model that clearly depicts WEC system operation, we utilize a force-current equivalent circuit framework which then enables us to design an impedance emulation control strategy. To provide context for our framework, we focus on a standard reference model-3 (RM3) point absorber device coupled to a permanent magnet synchronous generator. After the proposed extremum seeking controller is computed, we experimentally validate its performance on a platform that consists of two back-to-back connected inverters that emulate the WEC system.

关键词： Performance evaluation Systems operation Emulation Synchronous generators Permanent magnets Inverters Impedance Wave energy conversion Integrated circuit modeling Standards

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Certain Investigation of Filtered-OFDM in Visible Light Communications system 7

Certain Investigation of Filtered-OFDM in Visible Light Comm...

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7th International Conference on Computing Methodologies and Communication, ICCMC 2023

作者： Rashid Hujijo, Hayder S. Ilyas, Muhammad Qasim, Abdullah Ali Ullah, Ubaid Dept. of Electrical and Computer Engineering Altinbas University Istanbul Turkey Dept. of Computer Engineering Altinbas University Istanbul Turkey Dept. of Tech. Communications Engineering Al-Furat Al-Awsat Technical University Najaf Iraq Network and Communication Engineering Al Ain University Abu Dhabi United Arab Emirates

ISBN: (纸本)9781665464086

Filtered-OFDM scheme recently considers a promising element for Visible Light Communication (VLC) systems. Converting the F-OFDM bipolar signal to a nonnegative signal and being compatible with the Intensity Modulation and Direct Detection (IM/DD) is a crucial issue for researchers. To achieve a unipolar signal, many techniques have been proposed. In this paper, a Direct Current-bias (DC-bias) technique is employed to acquire a signal unipolarity and evaluate the efficiency of the F-OFDM system. The simulation findings offer that when the DC bias increased, the peak-to-average-power ratio (PAPR) increased even when using different modulation orders. In contrast, comparing different modulation orders, F-OFDM shows better bit error rate (BER) performance, especially in low-order modulation schemes. © 2023 IEEE.

关键词： Quadrature amplitude modulation

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