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MUTS-Based Cooperative Target Stalking for A Multi-USV System

IEEE/CAA Journal of Automatica Sinica 2023年第7期10卷 1582-1592页

作者： Chengcheng Wang Yulong Wang Qing-Long Han Yunkai Wu Shanghai Key Laboratory of Power Station Automation Technology and the School of Mechatronic Engineering and AutomationShanghai UniversityShanghai 200444China School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourne VIC 3122Australia College of Automation Jiangsu University of Science and TechnologyZhenjiang 212100China

This paper is concerned with the cooperative target stalking for a multi-unmanned surface vehicle(multi-USV)*** on the multi-agent deep deterministic policy gradient(MADDPG)algorithm,a multi-USV target stalking(MUTS)algorithm is ***,a V-type probabilistic data extraction method is proposed for the first time to overcome shortcomings of the MADDPG *** advantages of the proposed method are twofold:1)it can reduce the amount of data and shorten training time;2)it can filter out more important data in the experience buffer for ***,in order to avoid the collisions of USVs during the stalking process,an action constraint method called Safe DDPG is ***,the MUTS algorithm and some existing algorithms are compared in cooperative target stalking *** order to demonstrate the effectiveness of the proposed MUTS algorithm in stalking tasks,mission operating scenarios and reward functions are well designed in this *** proposed MUTS algorithm can help the multi-USV system avoid internal collisions during the mission ***,compared with some existing algorithms,the newly proposed one can provide a higher convergence speed and a narrower convergence domain.

关键词： Cooperative target stalking improved deep reinforcement learning multi-unmanned surface vehicle(multi-USV)systems V-type probabilistic data extraction

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Experimental Challenges in Maximum Torque Per Ampere Control of Indigenous Interior Permanent Magnet Synchronous Machine and its Solutions 5

Experimental Challenges in Maximum Torque Per Ampere Control...

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5th IEEE India Council International Subsections Conference, INDISCON 2024

作者： Jain, Prakhar Misra, Himanshu Indian Institute of Technology School of Computing and Electrical Engineering Himachal Pradesh Mandi India

ISBN: (纸本)9798350376753

This paper presents the experimental implementation of Maximum Torque per Ampere (MTPA) control for an Interior Permanent Magnet Synchronous Motor (IPMSM) developed indigenously, where knowledge of motor parameters was initially lacking. The paper discusses the resolution of various challenges encountered in IPMSM speed control. These challenges include limitations imposed by high direct axis inductance (Lds) and quadrature axis inductance (Lq) on per phase stator voltage, which restrict the motor's speed and loading capacity below levels specified by the manufacturer. Additionally, the paper addresses issues related to motor starting and the intricate implementation of the MTPA algorithm in a DSP microprocessor. The strategies adopted to overcome these challenges are discussed, and experimental results are provided to illustrate the efficacy of the implemented MTPA control strategy. © 2024 IEEE.

关键词： Permanent magnets

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A Novel Broadband Wide Angle-insensitive Phase Gradient Metasurface for Both Monostatic and Bistatic RCS Reduction

A Novel Broadband Wide Angle-insensitive Phase Gradient Meta...

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2024 International Symposium on Antennas and Propagation, ISAP 2024

作者： Senapati, Himansu Sekhar Anand, Ravi Sarkar, Anirban School of Computing and Electrical Engineering Indian Institute of Technology Himachal Pradesh Mandi India

ISBN: (纸本)9798350364774

In this paper, a novel planar phase gradient metasurface (PGM) with wideband radar cross-section (RCS) lowering capabilities is *** electromagnetic (EM) simulator is used to develop and model a 8x8 sub-array in order to verify its *** simulation's findings show that, at both normal and oblique incidence angles, the reflective metasurface greatly reduces the RCS (below 10 dB) over a broad frequency range of 7GHz to *** both monostatic and bistatic designs, a wide range of incidence angles (-30 degrees to +30 degrees) is used to demonstrate angle-independent RCS *** performance, frequency insensitivity, wide incident angle tolerance, and streamlined design are qualities to point out potential uses in real-world scenarios requiring low-scattering stealth capabilities. © 2024 IEEE.

关键词： Radar cross section

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Hairpin Resonator Based Non-invasive EM Biosensor For Lung Health Monitoring

Hairpin Resonator Based Non-invasive EM Biosensor For Lung H...

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2024 IEEE Microwaves, Antennas, and Propagation Conference, MAPCON 2024

作者： Tiwari, Preeti Anand, Ravi Shah, Prashant Sarkar, Anirban School of Computing and Electrical Engineering Indian Institute of Technology Himachal Pradesh Mandi India

ISBN: (纸本)9798350379693

This work presents the design and evaluation of a novel wearable microwave sensor for real-time monitoring of lung health using a modified hairpin microwave resonator. The proposed sensor operates at a center frequency of 2.2 GHz and is capable of detecting shifts in the resonant frequency due to the changes in permittivity for different lung abnormalities. The proposed sensor provides a significant shift of 515.5 MHz for pulmonary edema and 435 MHz for emphysema, demonstrating its high sensitivity to detect aforementioned respiratory environment. The sensor exhibits a sensitivity of 8.2 % and a figure of merit (FOM) of 18.164, along with a Q-factor of 227, indicating its high-performance capabilities. The simulated results of the hairpin resonator integrated with real characteristics of human tissue mimic, demonstrate its potential as a sensor for real-time monitoring of lung functions, which could aid in the early detection and management of respiratory conditions. © 2024 IEEE.

关键词： Q factor measurement

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Comparison of Various Machine Learning Algorithms in Predicting Air Quality 5

Comparison of Various Machine Learning Algorithms in Predict...

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5th IEEE International Conference on computing, Power, and Communication Technologies, IC2PCT 2024

作者： Madan, Tanisha Sagar, Shraddha Virmani, Deepali Galgotias University School of Computing Science and Engineering Greater Noida India VIPS-TC School of Engineering and Technology Delhi India

ISBN: (纸本)9798350383522

Air pollution is the major environmental issue that need to be controlled immediately as it is causing various life-threatening disease like cancer, pneumonia, asthma, and other breathing problems to human beings. It is also damaging plants and soil and our ecosystem is getting imbalanced. Various human activities like burning of fossil fuels, factories and industries are becoming the major cause of air pollution. But before controlling it is necessary to predict air quality in terms of Air Quality Index. Various statistical methods exist to predict air quality but due to manual calculation it lacks accuracy. Machine learning plays an important role in predicting air quality accurately as it learns from training data. In our approach dataset is collecting from Open weather API. Preprocessing of dataset is done, and normalization of dataset is done using Z-score method. Time series prediction is followed with a delay of one hour. Filtration of dataset and statistical history for a particular date is also calculated. Visualization of dataset is also done in terms of graph. Input parameters taken are PM10. PM25, SO2, NO2, CO and output parameters are Air quality index. Prediction is done using K-Nearest Neighbor, Random Forest, and Naïve Bayes. Random forest is giving better performance as compared to other algorithms in terms of accuracy and Naïve Bayes exhibit least accuracy. Precision and Recall is also calculated for each category. © 2024 IEEE.

关键词： Air Pollution Air Quality Index Decision trees K-Nearest Neighbour Naïve Bayes Random forest

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Ontology Evaluation Tools: Current and Future Research

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Recent Advances in Computer Science and Communications 2023年第6期16卷 2-15页

作者： Debnath, Narayan C. Patel, Archana Department of Software Engineering School of Computing and Information Technology Eastern International University Thu Dau Mot Viet Nam

In recent years, the increasing interest in ontologies resulted in the developing and publishing of many ontologies in the same or different domains. When users try to reuse the existing ontologies in their applications, they may encounter problems determining the most appropriate ontology based on their needs. Ontology evaluation is a process that helps users to examine the quality of the ontology based on different attributes. Many accessible and usable tools for ontology evaluation have been studied in the literature. However, finding an efficient ontology evaluation tool, following ontology specifications and their requirements (advantages/disadvantages), is still missing, limiting the researchers from determining possible future research. This paper aims to help new researchers and practitioners identify appropriate ontology evaluation tools based on their requirements and provide guidelines for future research directions on the same topic. This paper provides a detailed description of the different types of ontologies and classifies the available ontology evaluation tools into two categories, namely domain dependant ontology evaluation tools and domain-independent ontology evaluation tools. © 2023 Bentham Science Publishers.

关键词： Ontology

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Traffic Sign Detection Using YOLOv8 2

Traffic Sign Detection Using YOLOv8

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2nd International Conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2024

作者： Kumar, Rahul Gupta, Aniket Rajeswari, D. School of Computing College of Engineering and Technology Department of Data Science and Business Systems India

ISBN: (纸本)9798350327533

Traffic signals and other signs like parking., stop signs., etc. have become very crucial in autonomous and s elf-driving cars as it helps the smart system to comply with the basic traffic rules along with that it helps navigate routes based on the signs thus enabling a more secure driving experience for the drivers. There have been a lot of new algorithms that have emerged in the past recent years regarding this. In this paper., this research has used the new YOLOv8 object detection system to help us detect traffic signs as it is much fas ter and more precis e than its previous iterations. To improve the algorithm., this paper has used a dataset comprising photos of traffic signs taken at different angles and different light intensities. This system can predict the traffic signs with 93% accuracy. © 2024 IEEE.

关键词： Autonomous vehicle Deep Learning Traffic sign detection yolov8

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Leveraging Explainable AI for Improved Understanding and Prediction of Drug Responses in IGF1R Signaling Pathways

Leveraging Explainable AI for Improved Understanding and Pre...

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2024 International Conference on Advances in Data engineering and Intelligent computing Systems, ADICS 2024

作者： Janiel, J. Rajendran, P. Selvi School Of Computing Hindustan Institute Of Technology And Science Computer Science And Engineering Chennai India

ISBN: (纸本)9798350364828

Pharmacogenomics showcases the aim of precision medicine, which strives to customize treatments for individuals and specific populations. This field delves into exploring how an individuals DNA influences their response to medications. A persons genetic composition can impact the likelihood of experiencing reactions or determining the effectiveness of a medication. By providing insights into the safety and effectiveness of drug therapies pharmacogenomics holds potential for significantly enhancing health outcomes. Through advancements in targeted therapies we can precisely target abnormalities that trigger tumor growth in patients. For instance IGF1R (Insulin like Growth Factor 1 Receptor) which belongs to the tyrosine kinase receptor family plays a crucial role in promoting cell growth, survival and proliferation across different types of cancers. The overexpression of IGF1R has been observed in cancer types indicating its involvement in fueling continuous growth and survival of cancer cells. Targeting IGF1R helps address the dysregulation of this receptor within cancer cells. Artificial Intelligence (AI) comes into play by enabling prediction of suitable drugs based on a patients genomic profile thereby reducing adverse effects and improving treatment effectiveness. Parallel, here has been growing concern regarding model explanation due, to the opaque nature of model predictions. This is particularly important when it comes to modeling drug responses. In our research paper we have employed AI to gain a clear understanding of the prediction model and the factors that affect its results. The findings show that lower valued counts of YAP-pS127-Caution protein tend to negatively impact the output. Similarly lower values of YAP-pS127-Caution protein and higher valued counts of YAP-pS127 -Caution protein, Xanthine, Tyrosine tends to positively impact the output. This helps as an aiding reference in knowing which feature of an unknown cell line should be focused to know

关键词： Proteins

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An Improved Robust Sparse Convex Clustering

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Tsinghua Science and technology 2023年第6期28卷 989-998页

作者： Jinyao Ma Haibin Zhang Shanshan Yang Jiaojiao Jiang Gaidi Li Beijing Institute for Scientific and Engineering Computing Faculty of ScienceBeijing University of TechnologyBeijing 100124China School of Computer Science and Engineering University of New South WalesSydney 2052Australia

Convex clustering,turning clustering into a convex optimization problem,has drawn wide *** overcomes the shortcomings of traditional clustering methods such as K-means,Density-Based Spatial Clustring of Applications with Noise(DBSCAN)and hierarchical clustering that can easily fall into the local optimal ***,convex clustering is vulnerable to the occurrence of outlier features,as it uses the Frobenius norm to measure the distance between data points and their corresponding cluster centers and evaluate *** accurately identify outlier features,this paper decomposes data into a clustering structure component and a normalized component that captures outlier *** from existing convex clustering evaluating features with the exact measurement,the proposed model can overcome the vast difference in the magnitude of different features and the outlier features can be efficiently identified and *** solve the proposed model,we design an efficient algorithm and prove the global convergence of the *** on both synthetic datasets and UCI datasets demonstrate that the proposed method outperforms the compared approaches in convex clustering.

关键词： convex clustering outlier features block coordinate descent Newton’s method

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Hydrodynamic Performance of An Integrated System of Breakwater and A Multi-Chamber OWC Wave Energy Converter

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China Ocean engineering 2024年第4期38卷 543-556页

作者： NING De-zhi ZHANG Xiang-yu WANG Rong-quan ZHAO Ming State Key Laboratory of Coastal and Offshore Engineering Dalian University of TechnologyDalian 116024China Dalian Key Laboratory of Offshore Renewable Energy Dalian University of TechnologyDalian 116024China School of Computing Engineering and MathematicsUniversity of Western SydneyPenrith NSW 2751Australia

A multi-chamber oscillating water column wave energy converter(OWC-WEC)integrated to a breakwater is *** hydrodynamic characteristics of the device are analyzed using an analytical model based on the linear potential flow theory.A pneumatic model is employed to investigate the relationship between the air mass flux in the chamber and the turbine *** effects of chamber width,wall draft and wall thickness on the hydrodynamic performance of a dual-chamber OWC-WEC are *** results demonstrate that the device,with a smaller front wall draft and a wider rear chamber exhibits a broader effective frequency *** device with a chamber-width-ratio of 1:3 performs better in terms of power ***,results from the analysis of a triplechamber OWC-WEC demonstrate that reducing the front chamber width and increasing the rearward chamber width can improve the total performance of the *** the number of chambers from 1 to 2 or 3 can widen the effective frequency bandwidth.

关键词： oscillating water column power extraction efficiency potential flow theory wave energy converter multi-chamber

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