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arXiv 2022年

作者： Ruiz-Gironés, Eloi Roca, Xevi Barcelona Supercomputing Center - BSC Barcelona08034 Spain Computer Applications in Science and Engineering Spain

We answer the questions of the high-order technology focus group (HO-TFG) about the mesh generation for the high-lift common research model of the 4th high-lift prediction workshop. The HO-TFG seeks answers about the feasibility of generating meshes for complex geometries, and how to measure the quality of different aspects of the mesh. To answer these questions, we first generate several curved meshes and then, we analyze different aspects of the curved mesh and perform a visual inspection. The main bottleneck of our curving methodology is the preparation of curving-friendly inputs, a process that can take several days for complex geometries. Our distributed parallel implementation executed with 768 processors is able to curve the presented meshes in minutes. © 2022, CC BY-NC-ND.

关键词： Mesh generation

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PID Tuning Using Neural Network Classification of Self-Excited Oscillations

PID Tuning Using Neural Network Classification of Self-Excit...

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International Workshop on Variable Structure Systems, VSS

作者： Ahmed Rehan Igor Boiko Yahya Zweiri Electrical Engineering and Computer Science Department Khalifa University Abu Dhabi UAE Department of Aerospace Engineering and Director of Advanced Research & Innovation Center (ARIC) Khalifa University Abu Dhabi UAE

ISBN: (数字)9798350353686

ISBN: (纸本)9798350353693

This paper proposes a method for tuning PID controllers based on the shape of self-excited oscillations in a system. The approach utilizes a Modified Relay Feedback Test (MRFT) to excite oscillations and a Neural Network (NN) classifier to identify their shapes. The novelty of this work lies in the application of shape-based tuning, categorized into triangular, sinusoidal, wavy, and curved triangular waveforms, each with distinct Tuning Rules (TR)s for integrating and non-integrating systems. A feedforward neural network is developed to classify the MRFT-induced oscillation shapes, enabling the application of appropriate TRs. This classifier shows remarkable accuracy with noise-free signals, and through retraining with noisy data, maintains high performance, outperforming traditional linear discriminant analysis. The study concludes that the NN-based classification significantly enhances the precision of PID tuning by accurately identifying the oscillation shape, thereby ensuring the application of the most effective TR.

关键词： Variable structure systems Training Shape Artificial neural networks Linear discriminant analysis Feedforward neural networks Noise measurement Relays Tuning Oscillators

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Design of Six Element Antenna Array for IoT Application

Design of Six Element Antenna Array for IoT Application

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2nd International Conference on Signal Processing, Communication, Power and Embedded Systems, SCOPES 2024

作者： Satrusallya, Sarmistha Mahapatra, Shaktijeet Mohanty, Mihir Narayan Adarsh Rag, S. Department of Electronics and Communication Engineering Iter Bhubaneswar India Center for Internet of Things Iter Bhubaneswar India Manipal Institute of Technology Department of Data Science and Computer Applications Manipal India

ISBN: (纸本)9798331506452

The concept of Internet-of -Things makes it possible to connect devices in large numbers. The IoT enabled devices with the advantage of sensing, monitoring and tracking are present in different application. For this reason antenna must be compact and multifunctional to be connected to high speed device. In this work, we propose a 6 element linear antenna array with microstrip feed for IoT application. The proposed array operates at 3.8 GHz with a band width of 200Mhz. A peak gain of 9dB makes it suitable for IoT and biomedical application. © 2024 IEEE.

关键词： Antenna arrays

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TSCA: Enhancing Smartphone Security with a Touchpoints-Sensitive and Context-Aware Model for Touchscreen-Based Authentication

TSCA: Enhancing Smartphone Security with a Touchpoints-Sensi...

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International Conference on computer Supported Cooperative Work in Design

作者： Yingjie Wang Ruimin Hu National Engineering Research Center for Multimedia Software School of Computer Science Wuhan University Whuhan China Key Laboratory of Aerospace Information Security and Trusted Computing Ministry of Education School of Cyber Science and Engineering Wuhan University Whuhan China

ISBN: (数字)9798331513054

ISBN: (纸本)9798331513061

With the widespread use of smartphones, more and more private information is stored on them, which requires a more secure authentication method. Continuous authentication methods show potential for privacy protection due to their continuous and transparent nature, as opposed to the entry-point authentication methods like PIN codes and facial recognition. Users' touchscreen behavior, being both common and unique, has been widely studied in the field. However, previous methods based on manual features and deep learning have certain shortcomings when mining patterns from touchscreen behaviors that are beneficial for authentication. First, the operating habits of different users lead to different importance of touch points in a single touchscreen swipe. Second, extracting features from each touchscreen swipe independently ignores useful information from the context. To address this problem, we propose a novel Touchpoints-Sensitive and Context-Aware model called TSCA, which is able to adaptively assign weights to different touch points in a touchscreen swipe while also taking into account information from the context of the touchscreen swipe. We evaluate the TSCA model on two publicly available datasets and show that the TSCA is able to deliver significant performance gains compared to baseline methods while reducing model complexity.

关键词： Deep learning Adaptation models Privacy Computational modeling Authentication Touch sensitive screens Feature extraction Complexity theory Smart phones Context modeling

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A Near-Optimal Category Information Sampling in RFID Systems

arXiv

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arXiv 2024年

作者： Wang, Xiujun Liu, Zhi Zhou, Xiaokang Liao, Yong Hu, Han Zheng, Xiao Li, Jie School of Computer Science Anhui University of Technology Ma'anshan243032 China Anhui Engineering Research Center for Intelligent Applications and Security of Industrial Internet Ma'anshan243032 China

In many RFID-enabled applications, objects are classified into different categories, and the information associated with each object's category (called category information) is written into the attached tag, allowing the reader to access it later. The category information sampling in such RFID systems, which is to randomly choose (sample) a few tags from each category and collect their category information, is fundamental for providing real-time monitoring and analysis in RFID. However, to the best of our knowledge, two technical challenges, i.e., how to guarantee a minimized execution time and reduce collection failure caused by missing tags, remain unsolved for this problem. In this paper, we address these two limitations by considering how to use the shortest possible time to sample a different number of random tags from each category and collect their category information sequentially in small batches. In particular, we first obtain a lower bound on the execution time of any protocol that can solve this problem. Then, we present a near- OPTimal Category information sampling protocol (OPT-C) that solves the problem with an execution time close to the lower bound. Finally, extensive simulation results demonstrate the superiority of OPT-C over existing protocols, while real-world experiments validate the practicality of OPT-C. Copyright © 2024, The Authors. All rights reserved.

关键词： Real time systems

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Developing a Super-lift Luo-converter with Integration of Buck Converters for Electric Vehicle applications

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CSEE Journal of Power and Energy Systems 2021年第4期7卷 811-820页

作者： Behdad Faridpak Meisam Farrokhifar Mojtaba Nasiri Arman Alahyari Nasser Sadoogi Faculty of Electrical and Computer Engineering University of TabrizTabriz ***Iran Center for Energy Science and Technology Skolkovo Institute of Science and TechnologyMoscow 121205Russia Solar Energy Applications Group School of EngineeringTrinity College DublinD02 PN40 DublinIreland Research and Development Department of Jam Hoor Tabriz Company Tabriz ***Iran

In this paper,a DC-DC multi-port converter is introduced by integrating a super-lift and a buck converter(SLBC).The proposed single-input dual-output(SIDO)converter has conventional positive output voltage super-lift advantages while simultaneously generating a step・up voltage by Luo・converter and a step-down voltage by the buck *** this structure,without utilizing electromagnetic components to generate a dual output,the ripple in output voltages is kept ***,the introduced SLBC has a simple structure and an appropriate control method providing a wide range of output ***,to illustrate the advantages of the proposed SIDO converter,a comparison with other similar configurations is carried ***,simulation and experiment results indicate a considerable reduction in conduction losses compared to other SIDO converters in the same *** operation accuracy of SLBC is validated by performing several simulations in PSCAD/EMTDC software and testing a 150W prototype in the laboratory.

关键词： DC-DC converter Luo-converter single-input dual-output(SIDO) super-lift(SL) high voltage gain

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Pursuit-Evasion on a Sphere and When It Can Be Considered Flat 63

Pursuit-Evasion on a Sphere and When It Can Be Considered Fl...

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Milutinovic, Dejan Moll, Alexander Von Manyam, Satyanarayana G. Casbeer, David W. Weintraub, Isaac E. Pachter, Meir Electrical and Computer Engineering Dept. University of California Santa Cruz Santa CruzCA United States Control Science Center Aerospace Systems Directorate Air Force Research Laboratory DaytonOH45435 United States Dcs Corporation DaytonOH United States Air Force Institute of Technology Wright-Patterson Afb Dept. of Electrical Engineering OH United States

ISBN: (纸本)9798350316339

In planar pursuit-evasion differential games considering a faster pursuer and slower evader, the interception points resulting from equilibrium strategies lie on the Apollonius circle. This property is instrumental for leveraging geometric approaches for solving multiple pursuit-evasion scenarios in the plane. Here, we study a pursuit-evasion differential game on a sphere and generalize the planar Apollonius set to the spherical domain. We find that the interception point from the equilibrium strategies can leave the Apollonius set boundary and present a condition to keep the intercept point on the boundary. This condition allows for generalizing planar pursuitevasion strategies to the sphere. © 2024 IEEE.

关键词： Spheres

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TagVibra: push the limit of RFID-based vibration sensing 9

TagVibra: push the limit of RFID-based vibration sensing

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9th International Conference on Big Data Computing and Communications, BigCom 2023

作者： Li, Jian Li, Ping Zhu, Biaokai Dong, Chong Gong, Chao Lv, Zhao Anhui University Anhui Province Key Laboratory of Multimodal Cognitive Computation School of Computer Science and Technology Hefei230601 China Anhui University of Technology Anhui Engineering Research Center for Intelligent Applications and Security of Industrial Internet Ma'anshan243032 China Shanxi Police College Taiyuan030401 China

ISBN: (纸本)9798350331240

RFID-based mechanical vibration detection is considered a promising method for many Internet of Things (IoT) applications. However, existing methods are affected by ambient interference and leakage from the reader signature, which makes it difficult to obtain high-precision detection results. To overcome this limitation, this paper introduces TagVibra, a high-precision non-contact vibration sensing system based on RFID technology. By leveraging the nonlinear effect inside the tag and the modulation mechanism of RFID, TagVibra can achieve sub-millimeter level vibration detection accuracy. We implement TagVibra on our Universal Software Radio Peripheral (USRP) platform and evaluate its performance via experiments. The experimental results show that TagVibra can detect vibration with amplitude as low as 0.3mm, and the average estimation error below 0.7Hz when the vibration frequency is 100Hz. © 2023 IEEE.

关键词： Frequency estimation

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Personalized Multimedia Recommendation Systems Using Higher-Order Tensor Singular-Value-Decomposition

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IEEE Transactions on Broadcasting 2024年第1期70卷 148-160页

作者： Chang, Shih Yu Wu, Hsiao-Chun Yan, Kun Chen, Xinjia Huang, Scott Chih-Hao Wu, Yiyan San Jose State University Department of Applied Data Science San JoseCA95192 United States Louisiana State University School of Electrical Engineering and Computer Science Baton RougeLA70803 United States Yuan Ze University Innovation Center for AI Applications Chungli32003 Taiwan Guilin University of Electronic Technology Guangxi Key Laboratory of Wireless Wideband Communication and Signal Processing Department of Information and Telecommunication Guilin541004 China Northwestern State University Department of Engineering Technology NatchitochesLA71497 United States National Tsing Hua University Department of Electrical Engineering Hsinchu300 Taiwan Communications Research Centre Canada OttawaK2H 8S2 Canada

Because of rapid growth of multimedia data over the Internet, the infobesity has been emerging in recent years. Many recommender systems (RSs) have been proposed using a variety of techniques, including artificial intelligence, machine learning, statistical analysis, and data mining. Nowadays, E-commerce companies such as Amazon, eBay, Netflix, etc. have applied RSs conveniently to provide better customer services than before by enabling customized multimedia-content recommendations. It is well known that classical RSs are almost all based on the user-item attribute matrices. However, this two-fold user-item relationship should be extended to the emerging many-fold relationship among an arbitrary number of attribute groups so that the corresponding new RSs may lead to better performances. Therefore, in this paper, we introduce a novel personalized multimedia recommender system (PMRS) according to our proposed new parallel higher-order tensor singular-value-decomposition (PHOTSVD) algorithm. This PHOTSVD algorithm is capable of accommodating an arbitrary number of entities such as social-media channels, users, queries, webpages, etc. in a robust RS. Furthermore, we also investigate the cold start and data bias problems critical to RSs. Finally, we compare the performances of our proposed new PMRS and three other existing tensor-based RSs over realworld data with respect to the well-adopted metric, namely normalized root-mean-square error (NRMSE). Our proposed new PMRS greatly outperforms the other three existing tensor-based RSs in terms of NRMSE. © 1963-12012 IEEE.

关键词： Singular value decomposition

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Deep Learning-Based Approaches for Accurate Brain Tumor Detection in MRI Images

Deep Learning-Based Approaches for Accurate Brain Tumor Dete...

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Decision Aid sciences and Application (DASA), International Conference on

作者： Mohammed Noori Mohsin Ahmed Amer Ibrahim Ali Saeed Mohammad Khishe Mahmoud Mahfuri Al-ma'moon University College Baghdad Iraq Department of Computer Science and Software Engineering College of Information Technology Computer Center Northern Technical University Ninevah Iraq Innovation Center for Artificial Intelligence Applications Yuan Ze University Taiwan Jadara research center Jadara University Jordan Computer and information Technology Department International University for Science and Technology

ISBN: (数字)9798350369106

ISBN: (纸本)9798350369113

Brain tumor classification is considered one of the major tasks in medical image analysis, where correct and timely diagnosis could be achieved to serve as the key to effective treatment. This research paper proposes a deep learning-based approach for automatic classification of brain tumors from MRI images by fine tuning the ResNet50V2 CNN model. The dataset is made up of four classes, namely: Glioma Tumor, Meningioma Tumor, No Tumor, and Pituitary Tumor, totaling 2,844 images. We have done some strategy data augmentation and class weighting in order to prevent class imbalance, which ensures good performance in all tumor classes. Pre-processing and augmentation of the input images are done via rotation, shifting, zooming, and flipping. It yielded 95.29% on the validation set, with the major highlights of performance metrics for the minority class being class precision equal to 0.97 and class recall equal to 0.92, hence proving the efficiency of performed class balancing. The range of F1-scores, from 0.93 to 0.97, means fantastic predictive capability across all tumor types. Other techniques were also used to make this model optimal, such as early stopping, learning rate reduction, and checkpointing. The high performance of this model shows great promise in helping clinicians toward the right diagnosis of brain tumors in an effective way. Future efforts will involve incorporating larger datasets, exploring advanced augmentation techniques to enhance further model generalizability. Model explainability tools such as Grad-CAM will be used to extract insight into the model's decision-making process. This enhances the clinical interpretability of the results.

关键词： Accuracy Magnetic resonance imaging Decision making Brain tumors Predictive models Brain modeling Data augmentation Data models Optimization Medical diagnostic imaging

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