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arXiv 2023年

作者： Reed, Robert Laurenti, Luca Lahijanian, Morteza The Dept. of Aerospace Engineering Sciences University of Colorado Boulder United States The Delft Center for Systems and Control TU Delft Netherlands

Deep Kernel Learning (DKL) combines the representational power of neural networks with the uncertainty quantification of Gaussian Processes. Hence, it is potentially a promising tool to learn and control complex dynamical systems. In this work, we develop a scalable abstraction-based framework that enables the use of DKL for control synthesis of stochastic dynamical systems against complex specifications. Specifically, we consider temporal logic specifications and create an end-to-end framework that uses DKL to learn an unknown system from data and formally abstracts the DKL model into an interval Markov decision process to perform control synthesis with correctness guarantees. Furthermore, we identify a deep architecture that enables accurate learning and efficient abstraction computation. The effectiveness of our approach is illustrated on various benchmarks, including a 5-D nonlinear stochastic system, showing how control synthesis with DKL can substantially outperform state-of-the-art competitive methods. © 2023, CC BY.

关键词： Markov processes

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Delayed dynamic-feedback controller design for multi-frequency vibration suppression

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IFAC-PapersOnLine 2024年第27期58卷 196-201页

作者： Adrian Saldanha Adam Peichl Wim Michiels Tomas Vyhlidal Department of Computer Science KU Leuven Celestijnenlaan 200A 3001 Leuven Belgium Dept. Instrumentation and Control Engineering Faculty of Mechanical Engineering and Czech Institute of Informatics Robotics and Cybernetics Czech Technical University in Prague Prague 6 Czechia

We present a methodology for designing a dynamic controller with delayed output feedback for achieving non-collocated vibration suppression with a focus on the multi-frequency case. To synthesize the delay-based controller, we first remodel the system of equations as a delay-differential algebraic equation (DDAE) in such a way that existing tools for design of a static output feedback controller can be easily adapted. The problem of achieving non-collocated vibration suppression with sufficient damping is formulated as a constrained optimization problem of minimizing the spectral abscissa in the presence of zero-location constraints, with the constraints exhibiting polynomial dependence on its parameters. We transform the problem into an unconstrained one using elimination, following which we solve the resulting non-convex, non-smooth optimization problem.

关键词： vibration suppression time-delay DDAE

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An Artificial Neural Network Model to Forecast Grain Crops in North-Kazakstan Agricultural Experimental Station

An Artificial Neural Network Model to Forecast Grain Crops i...

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2023 IEEE International Conference on Communications, Information, Electronic and Energy systems, CIEES 2023

作者： Mimenbayeva, Aigul Omirtay, Maylen Niyazova, Rozamgul Bekmagambetova, Gulmira Suleimenova, Raya Tursumbayeva, Ainur Astana It University Dept. of Computational and Data Sciences Astana Kazakhstan Astana It University Specialty Smart Technologies Astana Kazakhstan L. Gumilyov Eurasian National University Dept. of Artificial Intelligence Technologies Astana Kazakhstan S. Seifullin Kazakh Agrotechnical Research University Dept. of Computer Science Astana Kazakhstan Eurasian Technological University School of Engineering and Information Technology Almaty Kazakhstan S. Seifullin Kazakh Agrotechnical Research University Dept. of Information Systems Astana Kazakhstan

ISBN: (纸本)9798350336917

The paper analyzes and predicts the yield of grain crops of LLP 'North-Kazakhstan Agricultural Experimental Station' for the last 30 years. The class of artificial neural networks-multilayer perceptron (MLP) was used as a research tool. The process of training of a model of a neural network consisting of 30 networks was performed on the basis of 70% training and 30% control samples. Based on the analysis of residuals histogram and scatter plot of the target and output function, the best neural network models MLP-1-7-1 (p=0.92), MLP-1-8-1 (p=0.97), MLP-1-5-1 (p=0.82) were selected. Next, using the best MLP 1-8-1 network, the model was tested the given data. Using time series projection, a graph was illustrated and a table of predicted grain yield values for the coming years was tabulated. The absolute error showed the high accuracy of the obtained best MLP 1-8-1 network for forecasting the amount of grain crop yield. The obtained model of artificial network can be applied in research and monitoring of agricultural production development. © 2023 IEEE.

关键词： Multilayer neural networks

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Optimizing Mobility IoT Device Networks with Dynamic RIS in mMIMO-Cooperative NOMA 6G systems

Optimizing Mobility IoT Device Networks with Dynamic RIS in ...

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Emerging Technologies for Dependable Internet of Things (ICETI), International Conference on

作者： Khalil Hassan Mohamed Hassan Khalid Hamid Elmuntaser Hassan Rania A. Mokhtar Mamoon M. Saeed Dept. of Comm. Systems Uni. of Science & Technology Omdurman Sudan Dept. of Electrical Eng Omdurman Islamic Uni. Omdurman Sudan Dept. of Computer Science Al-Neelain University Khartoum Sudan Department of Computer Engineering Taif University Taif KSA Department of Communications and Electronics Engineering Faculty of Engineering University of Modern Sciences (UMS) Yemen

ISBN: (数字)9798331533557

ISBN: (纸本)9798331533564

Advanced technologies like reconfigurable intelligent surfaces (RISs), massive multiple-input multiple-output (mMIMO), and non-orthogonal multiple access (NOMA) are crucial for the upcoming 6G communications landscape, particularly for IoT applications. This study uniquely explores the effects of RIS dynamics on the performance of mMIMO downlink (DL) cooperative NOMA systems in dense IoT environments. It introduces a novel methodology for modeling dynamic traffic distribution and integrating RIS, focusing on key performance metrics such as network capacity, spectral efficiency (SE), latency, and energy efficiency (EE). Various scenarios are evaluated, considering different distributions of IoT devices and signal-to-noise ratios (SNRs). Using simulation software, the research analyzes performance under unstable channel conditions with varying device distances, speeds, and power locations, employing 256-QAM modulation and successive interference cancellation (SIC). The results demonstrate that dynamic RIS significantly enhances capacity, spectrum efficiency, latency, and EE, paving the way for optimized IoT network architecture in future wireless systems.

关键词： 6G mobile communication Wireless communication NOMA Interference cancellation System performance Reconfigurable intelligent surfaces Network architecture Dynamic scheduling Internet of Things Resource management

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Comparative analysis of OFDM in AWGN & Local Acoustic Channel

Comparative analysis of OFDM in AWGN & Local Acoustic Channe...

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Humanitarian Technology Conference (KHI-HTC), IEEE Karachi Section

作者： Areeb Ahmed Aish Siddqui Rehan Khan Ghulam Nabi Murtaza Ali Dept. Electrical and Computer Systems Engineering Mohammad Ali Jinnah University Karachi Pakistan Centers of Excellence in Science and Applied Technologies (CESAT) Islamabad Pakistan

In this research study, a comparative analysis is presented that analyze the Orthogonal Frequency Division Multiplexing (OFDM) in two distinct communication systems Additive White Gaussian Noise (AWGN) and a Local Acoustic Channel. This study incorporates insights from the BELLHOP model to enhance understanding of sound propagation in dept. of water and guide the adaptation of OFDM for optimized communication. From simulated experiments, evaluate the performance of OFDM is assessed in the presence of local acoustic channel and AWGN, the important parameters like signal-to-noise ratio (SNR) and bit error rate (BER). The system of BELLHOP provides valuable context in the comparative analysis, highlighting the result of environmental factors on the performance of OFDM. The study not only contributes to the ongoing efforts in advancing underwater communication technique but also emphasizes the significance of tailored approach’s in different underwater scenarios, ultimately having the way for more robust and efficient communication systems beneath the waves. Through a comparative analysis between AWGN and a local acoustic channel, results show that the system achieves a BER of 10 −3 at SNR of 10 in local acoustic channel, while in the AWGN, a similar BER is achieved at SNR of 16.

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Multivariate Optimal Hybrid Deep Learning Model for Forecasting of Day-Ahead Solar Irradiance with Meteorological Constraints

Multivariate Optimal Hybrid Deep Learning Model for Forecast...

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Annual North-American Power Symposium

作者： Sohag Kumar Saha Satish M. Mahajan Dept. of Electrical & Computer Engineering (ECE) Tennessee Technological University Center for Energy Systems Research (CESR) Tennessee Technological University Cookeville TN USA

ISBN: (数字)9798331521035

ISBN: (纸本)9798331521042

With the growing integration of solar power gener-ation into smart grids, accurate solar irradiance forecasting is of paramount importance for efficient grid operation and renew-able energy management. In this paper, a data decomposition approach with two different methods of deep learning and grid search optimization was combined to develop a better hybrid model to forecast solar irradiance. The proposed model combines spatial and temporal information to improve forecasting accuracy by considering the impact of meteorological constraints such as global horizontal irradiance, temperature, relative humid-ity, wind speed, cloud type, direct normal irradiance, diffuse horizontal irradiance, and solar zenith angle. In addition to the model architecture, this work incorporates hyper-parameter optimization to fine-tune the parameters of the model for optimal performance. The design of the model ensures that the system adapts to the specific characteristics of the solar irradiance data and meteorological conditions under consideration. The proposed hybrid model was evaluated using real-world data to outperform traditional forecasting methods in terms of accuracy. The results of the proposed hybrid model indicate better prediction ability as measured by four parameters (lower RMSE and MAE, fewer epochs, and a higher R2 co-efficient).

关键词： Solar irradiance Deep learning Adaptation models Accuracy Predictive models Data models Smart grids Forecasting Optimization Load modeling

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Angle of Arrival Estimation Using SRS in 5G NR Uplink Scenarios

arXiv

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arXiv 2024年

作者： Spanos, Thodoris Fabra, Fran López-Salcedo, José A. Seco-Granados, Gonzalo Kanistras, Nikos Lapin, Ivan Paliouras, Vassilis Dept. of Electrical and Computer Engineering University of Patras Greece Loctio Greece Spain Radio Navigation Systems and Techniques Section European Space Agency Netherlands

This paper presents a comprehensive exploration of Angle of Arrival (AoA) estimation techniques in 5G environments, using the Sounding Reference Signal (SRS) in Uplink scenarios both in simulations and with actual measurements. Leveraging 5G capabilities, we investigate AoA algorithms for single-base station positioning. The study includes simulations and practical tests on a developed dedicated testbed featuring a base station equipped with a three-element Uniform Linear Array (ULA), considering Line of Sight conditions in an open environment. The testbed, employing Ettus E312 as the transmitter and Ettus N310 as the receiver, details waveform structures and reception processes. Additionally, our study examines the performance of Angle of Arrival (AoA) estimation algorithms, such as Multiple Signal Classification (MUSIC), Estimation of Signal Parameters via Rotational Invariant Techniques (ESPRIT), and Joint Angle and Delay Estimation (JADE) ESPRIT. A MATLAB ray tracing propagation model of the environment where the measurements are conducted, has been constructed. Simulation results using this model are presented, along with the actual measurements. The obtained results affirm the effectiveness of our implementation. © 2024, CC BY-NC-ND.

关键词： Testbeds

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A generation of dataset towards an Anomaly-Based Intrusion Detection System to detect Denial of Sleep Attacks in Internet of Things (IoT)

A generation of dataset towards an Anomaly-Based Intrusion D...

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International Conference on Advances in ICT for Emerging Regions

作者： Ishara Dissanayake Hesiri Dhammika Weerasinghe Anuradhi Welhenge Dept. of Computer Engineering University of Sri Jayewardenepura Ratmalana Sri Lanka Dept. of Computer Systems Engineering University of Kelaniya Kelaniya Sri Lanka

In this digital era, Wireless Sensor networks (WSN), or else, Internet of Things (IoT) when these sensor networks are accessible via the internet, is a common and widely used technology. These tiny sensor nodes in these networks help to enhance and automate processes in various fields such as, smart homes and cities, healthcare, smart vehicular networks, Smart Grids and so on. Although this technology is widely used in many fields, these tiny devices are equipped with limited amounts of resources. Limited capacity of battery power is one of the major concerns with IoT when it comes to some specific applications. In addition to this, this limited battery capacity is vulnerable for power depletion attacks which can reduce the lifetime of these devices significantly. So, there is an urgent need of solid solution to preserve this battery power as much as possible. One proper solution for this is, a machine learning based intelligent intrusion detection system that can detect power depletion attacks against these IoT applications. However, the lack of a proper dataset to train and evaluate these machine learning models appears as a major obstacle for an intelligent intrusion detection system. So, in this paper, we are going to discuss how we can use COOJA simulator to generate a proper dataset that can be used to develop and evaluate machine learning models to detect Denial of Sleep attacks against Wireless Sensor Networks. Here, we are going to discuss 3 strategies (UDP flood attack, wormhole attack and externally generated legitimate request attack) to simulate Denial of Sleep attacks for WSNs, so that, any person can generate their own dataset according to their requirements. At the end of the paper, we have evaluated each strategy to deplete the power of the sensor nodes. Then, our conclusions are given.

关键词： Wireless sensor networks Data security Urban areas Intrusion detection Machine learning Solids Batteries

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A Novel Architecture of CXL Protocol Data Link Layer for Low Latency Memory Access

A Novel Architecture of CXL Protocol Data Link Layer for Low...

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International Conference on Microelectronics, ICM

作者： Basma H. Mohamed Esmail Hany Mahmoud El-Tahawy Mohamed Abdel-Salam M. Watheq El-Kharashi Mona Safar Computer and Systems Engineering Dept. Ain Shams University Cairo Egypt Siemens EDA Cairo Egypt Cairo Egypt

With the increase in memory-intensive applications, there is a need to provide low latency paths for memory access and coherent caching between host processors and storage devices. This paper proposes a novel architecture for the Data Link Layer of Compute Express Link (CXL) protocol, as defined in CXL Specification Revision 2.0. The architecture presented here contains the transmission and reception chains, which ensures the reliable conveyance of the packets between two CXL components using the CXL protocol. This paper explains how the proposed architecture ensures reliable data conveyance, responses and requests, through the addition of a 16-bit Cyclic Redundancy Check (CRC) to each 512-bit FLow control unIT (FLIT) in the transmitter side, and how the packets are processed in receiver side. The architecture is intended to have simple implementation in addition to having minimum datapath delays. The whole architecture is designed using HDL then verified using test-benches for different protocol scenarios to make sure that the functionality of the system is achieved. In addition, the whole design is synthesized using United Microelectronics Corporation (UMC) 130 nm [1] and Taiwan Semicomductors Manufactor Company (TSMC) 28 nm [2] technologies to get the maximum achieved frequency and calculate the corresponding power and area. The proposed hardware implementation manages to work up to 1 GHz using TSMC 28 nm technology and 438.59 MHz using UMC 130 nm technology. Its estimated dynamic and leakage power consumption by UMC 130 nm technology at 1 GHz are 95.3698 mW and 171.17 mW, respectively. In addition, its area cost extracted after synthesis is 242124.8 $\mu \mathrm{m}^{2}$.

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Movement-Based Interaction: An Approach to Visual and Auditory Stimulus and Memory*

Movement-Based Interaction: An Approach to Visual and Audito...

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Experiment@ International Conference (exp.at)

作者： Maria Rita Nogueira Paulo Menezes Institute of Systems and Robotics University of Coimbra Coimbra Portugal Dept. of Electrical and Computer Engineering University of Coimbra Coimbra Portugal

ISBN: (数字)9798350314403

ISBN: (纸本)9798350314410

Movement-based interaction design is an innovative field that leverages the body's natural movements to create intuitive and engaging interfaces. This approach takes a sensorial approach to visual and auditory memory, seeking to enhance user engagement and create more meaningful experiences. The use of movement-based interfaces has significant implications for senior citizens, who may have mobility limitations or cognitive impairments. Using movement-based interfaces, seniors can engage in physical activity and maintain cognitive function, essential aspects for healthy aging. Movement-based interfaces can also help children develop physical coordination, cognitive skills, and social interaction. Furthermore, movement-based interaction design can benefit everyone's physical well-being by promoting physical activity and reducing sedentary behavior. Studies have demonstrated that movement-based interfaces can enhance posture, physical activity levels, and general health. By combining movement with sensory experiences, movement-based interaction design can create a more engaging and enjoyable experience for users, which can motivate them to maintain physical and cognitive health. In this article, we present two case studies that research the effectiveness of movement-based interaction design in enhancing visual and auditory memory. Overall, the results of these case studies suggest that movement-based interaction design is an effective approach to enhancing visual and auditory memory. The introduction of movement-based interfaces can give participants a more enjoyable and memorable experience, improving user engagement and information retention.

关键词： Visualization Pediatrics Aging Older adults

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