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Smart Agent-Based Direct Load Control of Air Conditioner Populations in Demand Side Management

Smart Agent-Based Direct Load Control of Air Conditioner Pop...

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International Conference on Control, Automation and Diagnosis (ICCAD)

作者： Pegah Yazdkhastil Chris P. Diduch Dept. of of Electrical & Computer Engineering Smart Grid Research Center University of New Brunswick Fredericton NB

The rapid fluctuations of renewable resources, such as wind and solar, pose challenges to the reliability of the grid and make it difficult to integrate them into existing power systems. To address this uncertainty and variability in generation, direct load control is a promising method for managing the demand side. Thermostatically controlled appliances, such as air conditioners, can play a significant role in this process. However, to implement direct load control, the system operator needs a reliable estimate of the load's magnitude and the degree to which it can be shifted. This paper introduces a smart-agent architecture that utilizes a mathematical model of the aggregated power consumption of the load to forecast its behavior, even in the presence of changes imposed by the controller. To evaluate the system's performance, a numerical simulator was developed. It was observed that the system can adapt to changes in the system, retrain itself, and develop a new mathematical model to improve its prediction of the aggregated power consumption.

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Study the Effect of Dielectric Permittivity and Changing Substrates Material on Microstrip Patch Antenna 4

Study the Effect of Dielectric Permittivity and Changing Sub...

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4th International Congress on Human-computer Interaction, Optimization and Robotic Applications, HORA 2022

作者： Hassoun, Zainab Abdullah Wali, Musa H. Hussein, Hussein Ali Haroon, Noor Hanoon Alkhayyat, Ahmed Islamic University Dept. of Computer Technical Engineering Najaf Iraq Al-Qadisiyah University Dept. of Electronics and Communication Engineering Al Diwaniyah Iraq Al-Mustansiriyah University Dept. of Electrical Engineering Baghdad Iraq Information and Communication Technology Research Group Scientific Research Center Al-Ayen University Thi-Qar Iraq

ISBN: (纸本)9781665468350

In this paper, three different cases of analysis were investigated. The first case is study the effect of varying the dielectric permittivity on the Microstrip Patch Antenna (MPA). While the second case is to inspect the impact of modifying the thickness of the substrate with the insertion of an air gap between the patch and the substrate. Investigating the effect of changing the type of the conductive material in the third case (copper, aluminum, gold, platinum, and graphene were used). It is found that the bandwidth depends on the substrate type. The use of graphene patch give a relative gain of 15dB. It is also found that the increase in dielectric constant (varepsilon mathrmr) causes the bandwidth downsizing as well as decreasing the gain. Using a wooden substrate increases the antenna bandwidth. Utilizing the air gap, between the patch and the substrate, to enhance electrical insulation. It is found that reducing the air gap caused a noticeable bandwidth reduction. © 2022 IEEE.

关键词： Natural frequencies

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Wideband Circularly Polarized FOWLP Antenna in Package for Satellite Communications

Wideband Circularly Polarized FOWLP Antenna in Package for S...

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Electronic Components and Technology Conference (ECTC)

作者： Kai Bo Zheng Mei Sun Yong Xin Guo IME attached student from Dept. of Electrical and Computer Engineering National University of Singapore (NUS) Singapore A*STAR (Agency for Science Technology and Research) Institute of Microelectronics (IME) Singapore Electrical and Computer Engineering Dept. National University of Singapore Singapore

This paper presents a wideband circularly-polarized Antenna-in-Package (AiP) element implemented in Fan-Out Wafer-Level-Packaging (FOWLP) technology for satellite communication. The AiP element features a meta-surface radiator with a single-ended aperture coupled feeding structure to achieve a wideband and circular polarization performance. By stacking a top mold of 500μm, a middle mold of 90μm and a 42μm RDL layer at the bottom, with a size of 10 mm×10 mm×0.652 mm, the AiP element achieves a Return Loss > 17.95 dB, an Axial Ratio < 2.67 dB, and a Gain of 7.19-7.88 dBi over 27–31 GHz. The antenna design concept is further confirmed using printed circuit board (PCB) technology for fast prototyping and evaluation.

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Deep Reinforcement Learning based Routing in an Air-to-Air Ad-hoc Network 41

Deep Reinforcement Learning based Routing in an Air-to-Air A...

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41st IEEE/AIAA Digital Avionics Systems Conference, DASC 2022

作者： Wang, Zhe Han, Ruixuan Li, Hongxiang Knoblock, Eric J. Apaza, Rafael D. Gasper, Michael R. University of Louisville Dept. of Electrical and Computer Engineering LouisvilleKY United States Nasa Glenn Research Center Communications and Intelligent Systems Division ClevelandOH United States

ISBN: (数字)9781665486071

ISBN: (纸本)9781665486071

This paper studies the Multiple Sources and Multiple Destinations (MSMD) routing problem in a dynamic Air-to-Air Ad-hoc Network (AAAN). We consider a spectrum-limited scenario where multiple links have to share the same frequency channel so that co-channel interference becomes inevitable. As a result, routing decisions and spectrum access are coupled and must be jointly considered. This paper proposes a deep Q-learning-based algorithm to find an optimal routing and channel selection strategy that minimizes the end-to-end communication delay. Specifically, under the assumption that only local information is available to every node, the Deep Q-Network (DQN) is trained offline to learn the optimal routing and channel selection strategy. After the trained DQN is implemented in every node, multiple relay nodes can simultaneously determine their next-hop relay and channel selections in real-time. Simulation results demonstrate the efficacy of our proposed algorithm. © 2022 IEEE.

关键词： Reinforcement learning

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Performance Evaluation of Coherent MIMO Radar Assisted with Space-Time Coding 9

Performance Evaluation of Coherent MIMO Radar Assisted with ...

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9th International Conference on computer and Communication engineering, ICCCE 2023

作者： Barakat, Mohammed Elmogtaba Saeed, Rashid A. Barakat, Mohammed Edam, Salaheldin Khalifa, Othman O. Sudan University of Science and Technology School of Electronics Engineering Khartoum Sudan Taif University College of Computers and Information Technology Department of Computer Engineering P.O. Box 11099 Taif21944 Saudi Arabia International Islamic University Malaysia Dept. of Electrical and Computer Engineering Malaysia Libyan Center for Engineering Research and Information Technology Bani Waleed Libya

ISBN: (纸本)9798350325218

Using multiple-input multiple-output (MIMO) technology has revolutionized the radar field by providing higher resolution, improved target detection, and reduced interference. However, interrupting signals can significantly degrade the Performance of MIMO radar systems to transmit and receive signals simultaneously;MIMO radar systems employ multiple antennas at the transmitter and receiver. This allows for improved spatial resolution and increased target detection capabilities. However, MIMO radar systems are susceptible to fading and interference, degrading performance. STC is a technique to mitigate these effects by transmitting multiple signals simultaneously from different antennas. This article evaluates the performance of space-time coding (STC) with coherent multiple-input multiple-output (MIMO) radar. The paper investigates the impact of STC on the radar system's detection and estimation capabilities in various scenarios, including target detection in cluttered environments and target tracking in the presence of interference. The simulation results demonstrate that STC can significantly improve the radar system's performance by reducing interference effects and increasing the signal-to-noise ratio. Furthermore, the study shows that different STC schemes have varying degrees of effectiveness depending on the specific scenario. Overall, this research provides valuable insights into the potential benefits of using STC with coherent MIMO radar for various applications. © 2023 IEEE.

关键词： Target tracking

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Increasing the Approach towards Healthcare Informatics and Data Analytics in Medical Science 1

Increasing the Approach towards Healthcare Informatics and D...

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1st International Conference on Healthcare Innovations, Software and engineering Technologies, HISET 2024

作者： Kadam, Shrikant Rangrao Chavan, Parinita Rani, D Shobha Vats, Mrinalini Thapliyal, Renu Chaudhari, Ravindra D. Jaywant College of Engineering and Polytechnic Department of Computer Engineering Karad India Jaywant College of Management Karad India Institute of Aeronautical Engineering Department of Electrical and Electronics Engineerin Hyderabad India Department of Surgery Karad India R2E Technologies Private Limited Uttarakhand India Shri Shiv Chhatrapati College Dept. of Zoology & Research Center Pune India

ISBN: (纸本)9798350360707

In the past, the majority of the data produced at the point of care was unstructured and included paper prescriptions, handwritten notes from nurses and doctors, hospital admission and discharge records, and pictures from MRIs and CT scans. Thus, it is necessary to study importance of developing healthcare informatics and data analytics. Due to patient treatment, compliance with legal and regulatory obligations, and record keeping, the healthcare industry has historically produced enormous amounts of data. In the field of healthcare, health informatics combines computer science and information science. Health informatics encompasses a variety of study fields, including bioinformatics, clinical informatics, public health informatics, image informatics (e.g., neuro-informatics), and translational bio informatics (TBI). Different studies are made for analyzing the importance of healthcare and the data security for the medical data for each individual. Thus, it can be easily said that there are still many changes required in the field of medical healthcare but still in the coming time healthcare data storing will become crucial with time as the number of individuals will increase so that data analysis of health is analyzed and stored. © 2024 IEEE.

关键词： Electronic health record

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Heart Failure: Machine Learning Prediction Within a 5-Year Framework 24

Heart Failure: Machine Learning Prediction Within a 5-Year F...

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24th IEEE International Conference on Bioinformatics and Bioengineering, BIBE 2024

作者： Tsarapatsani, Konstantina-Helen Tsakanikas, Vasilios D. Sakellarios, Antonis Trampisch, Hans J. Karapintzou, Efterpi Rudolf, Henrik Matsopoulos, George K. Fotiadis, Dimitrios I. Biomedical Research Institute Foundation for Research and Technology-Hellas Ioannina Greece Ruhr University Bochum Department of Medical Informatics Biometry and Epidemiology Bochum Germany University of Ioannina Unit of Medical Technology and Intelligent Information Systems Dept. of Materials Science and Engineering Greece Institute for Biostatistics and Informatics in Medicine and Ageing Research University Medical Center Rostock Germany School of Electrical and Computer Engineering National Technical University of Athens Athens Greece University of Ioannina and Biomedical Research Institute-FORTH Unit of Medical Technology and Intelligent Information Systems Dept. of Materials Science and Engineering Ioannina Greece

ISBN: (纸本)9798331518622

Heart failure (HF) is a complex syndrome that is affected by many factors and causes. It is crucial to early recognize the disease subtypes and the unidentified clinical pathways that give rise to it. Machine learning (ML) is the tool that assist to deal with these challenges and improve the prediction of HF. In this work, the HF risk prediction was implemented by employed ML classifiers, such as Random Forest (RF), Extreme Grading Boosting (XGBoost) and Light Gradient-Boosting Machine (LGBM). We utilized the data from the German epidemiological trial on ankle brachial index - getABI cohort, which includes 6,454 patients. The performance of classifiers was estimated by Accuracy (ACC), Sensitivity, Specificity and the area under the receiver operating characteristic curve (AUC) in mean values for each ML classifier. The results were also interpreted using the Explainable artificial intelligence (XAI) approach, the Shapley Additive exPlanations (SHAP) values. Our work reveals that LGBM classifier predict the HF risk within 5 years follow-up in general population with 68 % accuracy. Moreover, the N-terminal pro-B-type natriuretic peptide (NT-proBNP) was identified as the most important feature for HF risk prediction. © 2024 IEEE.

关键词： Risk perception

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Deep Learning-Based Aerosol and Ocean Data Retrieval from Satellite Polarimeter Measurements

Deep Learning-Based Aerosol and Ocean Data Retrieval from Sa...

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IEEE Southeastcon

作者： Lingxiao Wang Snorre Stamnes Sunzid Hassan Alexander Isiani Cheston Sturdivant Hoang My Le Khan Raqib Mahmud Dept. of Electrical Engineering Louisiana Tech University Ruston Louisiana USA NASA Langley Research Center Hampton Virginia USA Dept. of Computer Science Louisiana Tech University Ruston Louisiana USA

ISBN: (数字)9798331504847

ISBN: (纸本)9798331504854

This paper presents a deep learning (DL)-based approach for retrieving aerosol and ocean optical parameters from polarimeter measurements. The traditional data retrieval method, i.e., Microphysical Aerosol Properties from Polarimetry (MAPP) algorithm, involves vector radiative transfer (VRT) calculations, which are a time-consuming and computationally intensive process. To address this limitation, we propose replacing the VRT calculations in MAPP with DL models to accelerate the data retrieval process. The core idea is to train DL models to replicate VRT calculations used in MAPP. To achieve this, we collected 2 million input-output pairs from the VRT calculations in MAPP to construct a comprehensive training dataset. Three types of DL models, including feedforward neural networks (FNNs), convolutional neural networks (CNNs), and recurrent neural networks (RNNs), were developed to learn the underlying VRT calculation pattern through supervised learning. The performance of these models was evaluated using a test dataset, with the RNN model achieving the highest prediction accuracy. Experimental results indicate that the proposed DL-based approach can improve the data retrieval efficiency of MAPP algorithm while maintaining high accuracy in the data retrieval process.

关键词： Deep learning Recurrent neural networks Oceans Computational modeling Sea measurements Data retrieval Aerosols Predictive models Optical variables measurement Polarimetry

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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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Raising Compute Density of Molecular Dynamics Simulation Through Approximate Memoization

Raising Compute Density of Molecular Dynamics Simulation Thr...

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International Conference on Application Specific Systems (ASAP), Architectures and Processors

作者： Salim Khemira Xinyuan Wang Anh Nguyen Yutaka Tamiya Makoto Taiji Takahide Yoshikawa Jason H. Anderson Dept. of Electrical and Computer Engineering University of Toronto Toronto Canada Fujitsu Laboratories Kawasaki Japan RIKEN Center for Biosystems Dynamics Research Kobe Japan

ISBN: (数字)9798350349634

ISBN: (纸本)9798350349641

Molecular dynamics (MD) simulation involves simulating the interactions of particles. MD has many applications in basic biological sciences, drug discovery, materials science, and other fields. Simulating $1\mu \mathrm{s}$ of a 100K-atom system can take hours or days 1 1 https://***/en/research/labs/***, where the compute-heavy aspect of MD is calculating the long-range forces between pairs of particles. In this paper, we explore the application of approximate computing in MD as a means to improve compute density. Specifically, we employ approximate memoization, where previously computed forces (and more) are stored in a table, and are retrieved in subsequent force calculations, provided the inputs to the force calculation are the same or similar. If the prior-computed table values can be used, significant computational work is avoided. In an experimental study, we apply software simulation to understand the degree to which approximation is feasible. We then propose a hardware implementation of memoization to be used within an ASIC MD simulator, MDGRAPE-4A [18]. We show that compute density, measured as $\text{pair-interactions}/(s\cdot\mu m^{2})$ is improved substantially, between 40 % and 70 % for the studied cases. This is contingent on the particular system being simulated, the table size, and permitted level of approximation.

关键词： Materials science and technology Program processors Density measurement Force Dynamics Systems architecture Software

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