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Reference Tracking for Constrained Uncertain Linear systems by Stochastic MPC

IFAC-PapersOnLine 2023年第2期56卷 10421-10427页

作者： Jannik Hahn Olaf Stursberg Control and System Theory Dept. of Electrical Engineering and Computer Science University of Kassel 34121 Kassel Germany

This paper addresses model predictive control of a class of linear systems subject to additive stochastic disturbances and constraints. The underlying stochastic optimal control problem combines inverse cumulative distribution functions with ellipsoid-in-polyhedron formulations to reduce the conservatism induced by constraint satisfaction. By use of terminal constraints and time-varying weights within the cost functional, the presented control scheme satisfies criteria for mean-square stability and can be adapted to reference-tracking problems for arbitrary reference signals.

关键词： Probabilistic Constraints Mean-Square Stability Predictive Control Stochastic Control Uncertain systems

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Compact Triple-Band Millimeter Wave Flexible Antenna for Wearable Applications

Compact Triple-Band Millimeter Wave Flexible Antenna for Wea...

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2023 International Telecommunications Conference, ITC-Egypt 2023

作者： Parveez Shariff, B.G. Ali, Tanweer Mane, Pallavi R Kumar, Pradeep Kumar, Praveen Pathan, Sameena Manipal Institute of Technology Manipal Academy of Higher Education Dept. of Electronics and Communication Manipal576104 India University of KwaZulu-Natal Discipline of Electrical Electronic and Computer Engineering Durban4041 South Africa Manipal Institute of Technology Manipal Academy of Higher Education Dept. of Information and Communication Technology Manipal576104 India

ISBN: (纸本)9798350326062

With the wide demand for wearable gadgets, flexible antennas have emerged to fulfill the requirement of uninterrupted connectivity with stringent radiation behavior. A compact triple-band antenna is proposed to operate at mmWave band. A liquid crystal polymer substrate is used as it has good mechanical and resistive properties against bending and is very cost-efficient. The chosen dimension of the substrate is 0.635λ_0x0.635λ 0, where λ0 is the lower operating mmWave wavelength. The proposed antenna operates at 31.76 GHz, 34.46 GHz, and 49.87 GHz with good impedance matching, having reflection coefficients of -23.3dB, -15.81dB, and -27.97dB, respectively. The fractional bandwidth of the designed antenna is 10.97%, 0.99%, and 7.45%. The antenna is validated for bending analysis at angle 6 varying from 8.6^0 to 5.7^0 along the two-dimensional axis. The specific absorption rate (SAR) is 3.3 W/kg and 2.14 W/kg at 15 mm and 20 mm distances. The structure has attained the maximum gain of 6.59, 4.54, and 9.25 dBi, respectively. The radiation pattern is bidirectional with HPBW of 44^0, 42^0, and 36^0 in the E-plane. The radiation pattern is turned to directional over the phantom model with an HPBW of 20^0 and a maximum gain of 10.4 dBi. Finally, the proposed structure is simulated by placing it over a helmet for military hostile surveillance applications. © 2023 IEEE.

关键词： Millimeter waves

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Progressive DCT-based coder and its comparison to atomic function based image lossy compression 16

Progressive DCT-based coder and its comparison to atomic fun...

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16th IEEE International Conference on Advanced Trends in Radioelectronics, Telecommunications and computer engineering, TCSET 2022

作者： Makarichev, Viktor Lukin, Vladimir Brysina, Iryna National Aerospace University Dept. of Computer Systems Networks and Cybersecurity Kharkiv Ukraine National Aerospace University Dept. of Information-Communication Technologies Kharkiv Ukraine National Aerospace University Dept. of Higher Mathematics and System Analysis Kharkiv Ukraine

ISBN: (纸本)9781665468619

In this paper, a progressive DCT-based coder (PDCTC), which implements a lossy image compression algorithm based on discrete cosine transform (DCT) and provides progressive data reconstruction, is introduced. It is compared to JPEG as well as to discrete atomic compression (DAC) that is an algorithm based on discrete atomic transform (DAT). It is shown that the algorithm proposed provides higher compression ratio (CR) than JPEG with the same quality loss measured by PSNR-metric. Also, it is proved that PDCTC and DAC have almost the same efficiency in terms of rate/distortion curve (dependence of PSNR and compression ratio). Besides, the complexity of these algorithms is analyzed. © 2022 IEEE.

关键词： Discrete cosine transforms

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Effective 3D Video Streaming Using 2D Video Encoding system 2

Effective 3D Video Streaming Using 2D Video Encoding System

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2nd Asian Conference on Innovation in Technology, ASIANCON 2022

作者： Patil, Vishwas Manu, T.M. Anami, Basavaraj. S. Billur, Darshankumar K.L.E. Institute of Technology Dept. of Electronics and Communication Hubballi India K.L.E. Institute of Technology Dept. of Computer Science and Engineering Hubballi India K.L.E. College of Engineering & Technology Dept. of Electronics and Communication Hubballi India

ISBN: (数字)9781665468510

ISBN: (纸本)9781665468510

The amount of video traffic on the internet is expanding at an alarming rate, necessitating the use of a high compression technology. There are several 3D video compression techniques available, such as multi-view coding and dept.-image-based rendering. To apply these techniques, an entirely new codec must be introduced to the present system. In this research, a 3D video compression approach is suggested that would provide better compression with decent video quality while leveraging an existing video streaming infrastructure. The proposed method is tested on two test videos using the existing HEVC video encoding technology. Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index (SSIM) are used to evaluate the performance of the proposed 3D video compression technique. These values are then compared to the traditional dept.-image-based rendering technique. There is a decrease of around 50% in video size with a 2% reduction in PSNR, and a penalty of around 7% drop in SSIM. This signifies that we benefit in terms of video size reduction while compromising a small quality level. © 2022 IEEE.

关键词： Image compression

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Fuzzy Based Intelligent Transportation systems for Smart Cities to Mitigate Road Traffic Congestion

Fuzzy Based Intelligent Transportation Systems for Smart Cit...

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International Conference on Innovations in Science, engineering and Technology (ICISET)

作者： Md. Humayun Kabir Md Saiful Islam Md Jiabul Hoque Dept. of Electronics and Telecommunication Engineering Chittagong University of Engineering and Technology Chittagong Bangladesh Dept. of Computer and Communication Engineering International Islamic University Chittagong Chittagong Bangladesh

ISBN: (数字)9798350355499

ISBN: (纸本)9798350355505

Traffic congestion in smart cities is a growing concern. This paper explores the application of Fuzzy Logic in Intelligent Transportation systems (ITS) to address this challenge. Fuzzy logic can handle imprecise and dynamic traffic data and offers advantages over traditional fixed-time signal control. The research proposes a Fuzzy-based ITS framework for dynamically traffic signal control. This framework utilizes real-time sensor traffic data to adjust signal timings, dynamically prioritizing congested areas. The system also incorporates emergency vehicle detection using siren sensors. This ensures priority for emergency vehicles by granting them the right of way. This paper discusses the design of the fuzzy inference system, including the selection of fuzzy variables and membership functions. The effectiveness of the proposed system is evaluated through simulations, demonstrating its potential to reduce traffic congestion and improve traffic flow in smart cities.

关键词： Fuzzy logic Transpiration Technological innovation Uncertainty Smart cities Computational modeling Vehicle detection Transportation Vehicle dynamics Traffic congestion

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Gamification of RF Data Acquisition for Classification of Natural Human Gestures

Gamification of RF Data Acquisition for Classification of Na...

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IEEE National Conference on Radar

作者： Emre Kurtoğlu Kenneth DeHaan Caroline Kobek Pezzarossi Darrin J. Griffin Chris Crawford Sevgi Z. Gurbuz Dept. of Electrical and Computer Engineering The University of Alabama Dept. of American Sign Language Gallaudet University Dept. of Psychology Gallaudet University Dept. of Communication Studies The University of Alabama Dept. of Computer Science The University of Alabama

ISBN: (数字)9798350329209

ISBN: (纸本)9798350329216

In recent years, there have been significant developments in radio frequency (RF) sensor technology used in human-computer interaction (HCI) applications, specifically in areas like gesture recognition and more broadly, human activity recognition. Although extensive research has been conducted on these subjects, most experiments involve controlled settings where participants are instructed on how to perform specific movements. However, when such experiments are conducted on sign language recognition they lack capturing dialectal and background-related diversities. In this work, we explore the differences in RF datasets acquired under controlled experimental settings and in free form environments where users were not constrained by the experimental instructions and limitations. We show that directed (i.e., controlled) data acquisition approaches result in over-optimistic performances which do not perform well on naturally acquired data samples in a real-world use case. We evaluate different approaches on generating synthetic samples from directed dataset, but show that such methods do not offer much benefit over collecting natural data. Therefore, we propose an interactive data acquisition paradigm through gamification. We show that the proposed approach enables the recognition of American Sign Language (ASL) in real-world settings by achieving 69% accuracy on 29 words.

关键词： Radio frequency Human computer interaction Sign language Data acquisition Transforms Radar Predictive models

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Machine Vision Approach Using Multi Features for Detection of Oil Palm Stem Disease 1

Machine Vision Approach Using Multi Features for Detection o...

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1st International Conference on Advanced engineering and Technologies, ICONNIC 2023

作者： Septiarini, Anindita Hamdani, Hamdani Syaifudin, Encik Akhmad Setyaningsih, Emy Nurcahyono, Damar Hadiwijaya, Noor Alam Mulawarman University Dept. of Informatics Samarinda Indonesia Mulawarman University Faculty of Agriculture Samarinda Indonesia Institut Sains Teknologi Akprind Department of Computer System Engineering Yogyakarta Indonesia Politeknik Negeri Samarinda Dept. of Information Technology Samarinda Indonesia

ISBN: (纸本)9798350306484

Indonesia is a significant palm oil producer, widely cultivated due to its status as a prominent vegetable oil-producing plant. Palm oil is a highly sought-after crop in agriculture due to its profitability and the demand for substantial quantities of high-quality oil. Early diagnosis of oil palm diseases is crucial for prompt prevention and eradication measures essential for maintaining high-quality palm oil production. Hence, there is a requirement for a machine vision-based method to classify diseases on plant stems. The proposed method consists of several main processes: pre-processing, feature extraction, and classification. Several machine learning algorithms and feature extraction using color and texture features were performed to develop a machine vision for detecting oil palm stem disease. It applied cross-validation with a K-fold value of 10. Performance evaluation was carried out using three parameters: precision, recall, and accuracy. The Linear Discriminant Analysis (LDA) method achieves the optimum results in testing scenarios combining color features based on HSV color space and textures features, achieving an accuracy value of 90.50%. © 2023 IEEE.

关键词： Palm oil

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Sustainable Agriculture in Food Security Integrating Satellite Data Risk Assessment by Cyberattack Detection: AI Applications

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Remote Sensing in Earth systems Sciences 2025年第2期8卷 435-443页

作者： Kumar, M. Prema Krishnammal, N. Gupta, Manu Begum, Mairaj Unisa Sultana, Sameera Degala, Divya Priya Dept. of ECE Shri Vishnu Engineering College for Women (A) Andhra Pradesh Bhimavaram 534202 India Department of Computer Science and Engineering Dr. N.G.P. Institute of Technology Tamilnadu Coimbatore India Department of Electronics and Communication Engineering Sreenidhi Institute of Science and Technology Telangana Hyderabad India Department of CSE-AIML MALLAREDDY UNIVERSITY Telangana Hyderabad India Department of Computer Science and Engineering MLR Institute of Technology Hyderabad India

Globally, chronic food insecurity persists and is made worse by shocks brought on by climate change, like floods and droughts. In order to guarantee prompt assistance delivery, humanitarian programming prioritizes predicting levels of food insecurity and identifying homes that are at risk. Using complicated and diverse data, machine learning (ML) models have been widely used to promote food security. This research proposes a novel technique in sustainable agriculture-based food security analysis and satellite data cyberattack detection using machine learning models. Here, the input is collected based on satellite data, and its cyber detection has been analyzed using a convolutional spatio adversarial encoder neural network. Then, from this satellite data, the food security analysis data has been collected and processed for noise removal and normalization. Processed data has been classified using the fuzzy Q-Boltzmann ResNet transfer neural network. Experimental analysis is carried out for the food security analysis dataset in terms of data integrity, detection accuracy, average precision, F-1 score, and recall. The proposed approach yielded 97% detection accuracy, data integrity of 98%, 96% average precision, 93% recall, and 94% F-1 score. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025.

关键词： Cyberattack detection Food security analysis Machine learning models Satellite data Sustainable agriculture

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Implementation of parallel AES Processing with CAM-based Massive-parallel SIMD Matrix Core 5

Implementation of parallel AES Processing with CAM-based Mas...

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5th World Symposium on communication engineering, WSCE 2022

作者： Kageyama, Kyosuke Arai, Sota Hamano, Hajime Kong, Xiangbo Koide, Tetsushi Kumaki, Takeshi Electronic and Communication Engineering Kindai Univ. Dept. of Electrical Osaka Japan Ritsumeikan Univ. Dept. of Electronic and Computer Engineering Shiga Japan Hiroshima Univ. Hiroshima Japan

ISBN: (数字)9781665450577

ISBN: (纸本)9781665450577

Recently, several multimedia applications, such as digital image compression, digital video compression, and digital audio processing, are executed on the mobile devices. The processing core in the mobile device requires high performance, versatility, and programmability. Generally, multimedia applications consist of repeated arithmetic operation and table-lookup coding operation. To have high performance, versatility, and programmability by improving the processing speed of the both operations on a processing core, Content Addressable Memory-based massive-parallel SIMD matrix core (CAMX) is proposed. The role of CAMX is an accelerator for mobile CPU core. CAMX has highly parallel processing capability and is configured by two CAM modules which are used in fast table-lookup coding operation. This paper has shown the result of AES encryption. The number of AES encryption total clock cycles are 1,362,699, and also the detail number of clock cycles is confirmed: SubBytes is 1,312,160, ShiftRows and MixColumns is 17,161 in total, AddRoundKey is 2,519. Furthermore, CAMX can process AES encryption in 83.17 clock cycles / bytes, and it is confirmed to be about 50 % performance improvement than existing mobile processor. © 2022 IEEE.

关键词： Table lookup

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Time-Stretched Imaging Flow Cytometry and Photonic Neuromorphic Processing for Particle Classification

Time-Stretched Imaging Flow Cytometry and Photonic Neuromorp...

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2023 Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference, CLEO/Europe-EQEC 2023

作者： Tsilikas, Ioannis Tsirigotis, Aris Deligiannidis, Stavros Tsigaridas, Georgios N. Bogris, Adonis Mesaritakis, Charis National Technical University of Athens Dept. Physics Iroon Polytechniou 9 Zografou Athens15772 Greece University of the Aegean Dept. Information and Communication Systems Engineering Palama 2 str. 83200 Karlovasi Samos Greece University of West Attica Dept. Informatics and Computer Engineering Ag. Spiridonos Egaleo12243 Greece

ISBN: (纸本)9798350345995

In this work, we investigate the compression capabilities of a photonic neuromorphic accelerator relying on an optical spectrum slicing technique [1], following a high-flow 1D imaging cytometry setup, able to image 62000 particles/sec. The utilized image scheme relies on a technique, where spatial information is transfered to the spectrum and subsequently through dispersion to the temporal domain. Therefore, it can replace high speed spectrometers with a single photodetector [2]. On the other hand, the elevated image acquisition rate, trigger the generation of a staggering amount of data, which can cause a processing backlog at the digital backend. In this context, we explore, for the first time, the use of a photonic neuromorphic pre-processing unit, following the cytometer that can reduce the number of trainable parameters at a lightweight digital backend by a factor of 2.5, while at the same time, it can project incoming data to a high dimensional space boosting accuracy. © 2023 IEEE.

关键词： Photonics

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