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9th International Conference on ICT for Smart Society, ICISS 2022

作者： Ekanayake, Dhanushka De Alwis, Pubudu Harshana, Pasindu Munasinghe, Dilusha Jayakody, Anuradha Gamage, Ms. Narmada Sri Lanka Institute of Information Technology Dep. of Computer Systems Engineering Malabe Sri Lanka

ISBN: (数字)9781665471350

ISBN: (纸本)9781665471350

Sri Lanka's agricultural sector confronts serious challenges from fertilizer shortages and agriculture-related chemical scarcity. Innovations comparable to aquaponic systems may be offered to Sri Lankan farmers to overcome these difficulties using IoT and ML technology. This research scope is to implement a smart and secure aquaponic environment monitoring system to forecast plant and fish growth factors, provide Sri Lankan farmers with insights into the environment's behaviors, and take measures according to the predictions utilizing control mechanisms. In this research, more exact predictions have been generated by the Random Forest algorithm model rather than the LSTM model, and most of the investigated parameters given good accuracy according to the absolute mean error (Media TDS-1.95, Media pH-0.06, Media Temperature-0.49, Env. Temperature- 0.94, Env. Humidity-2.70) except the environment light intensity (64.11). The ML solution studied in this research paper would increase the quality of traditional agriculture in Sri Lanka for greater productivity and economic benefit. © 2022 IEEE.

关键词： Internet of things

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Assessment of Combined Cooling, Heating, and Power (CCHP) systems for Energy Efficiency in Administrative Buildings in Hot and Dry Climate

Assessment of Combined Cooling, Heating, and Power (CCHP) Sy...

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Conference on Electrical Power Distribution Networks (EPDC)

作者： Shahrzad Zeynali Mohammad Nazififard Hamed Hashemi-Dezaki Dep. of Energy Systems Engineering University of Kashan Kashan Iran Dep. of Electrical and Computer Engineering University of Kashan Kashan Iran

ISBN: (数字)9798350385502

ISBN: (纸本)9798350385519

Combined cooling, heating, and power (CCHP) systems have garnered significant attention as a cost-effective solution for reducing energy consumption in buildings due to their ability to provide higher thermal efficiency compared to single power generation systems. This study focuses on modeling and evaluating the energy consumption of an administrative building within the University of Kashan, alongside the output values of a nearby CCHP power plant. The consumption values of the university’s central administrative building have been obtained using available measuring devices. Also, the validity of the modeling results has been assessed using Design-Builder software. Additionally, the study investigates the role of the CCHP system in the building in terms of energy production and consumption by comparing the building’s consumption with the production of CCHP electricity and heat. The simulation results indicate that the total annual energy consumption of the office building is 182.67 kWh/m$^systems$, while the values recorded by the engine room measuring devices show 199.75 kWh/m$^systems$. This suggests a potential discrepancy between the simulated and measured values, with the simulated value being approximately ten percent lower than the measured value. Possible factors contributing to this variance include discrepancies in people’s activity models used in the simulation software and the actual consumption behavior patterns. Furthermore, the study highlights that the 1 MW CCHP system can meet the thermal and electrical needs of a 3-story administrative building, such as the central administrative building of the University of Kashan, while also being able to supply excess electrical energy to the grid. This underscores the potential of CCHP systems in effectively addressing energy demands in buildings.

关键词： Energy consumption Electric potential Simulation Buildings Energy measurement Production Software

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An Intelligent Energy Management for an On-Grid Hybrid Energy System Cost Reduction

SSRN

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SSRN 2024年

作者： Miranda, Israel Riverón Gomez-Gonzalez, Jose Francisco Mendez-Perez, Juan Albino Dep. Computer Science and Systems Engineering University of La Laguna Spain Dep. Industrial Engineering University of La Laguna Spain

This paper introduces an innovative Energy Management System (EMS) designed to reduce the cost of energy flows in a Hybrid Renewable Energy System (HRES) connected to a grid with an Energy Storage System (ESS) based on lithium-ion electric batteries. This study considers power purchase and sale tariffs, as well as costs associated with the battery wear contingent upon its State of Charge (SoC). The proposed EMS combines three Fuzzy Logic Controllers (FLCs) arranged in a cascade to regulate battery intensity with a Hysteresis-Based Calculation algorithm (HBC) in a supervisory control hierarchy to establish charge and discharge setpoints. Its goal is to minimise the energy flow costs at the current instant while maintaining the power supply to the loads. Two generation and consumption scenarios were simulated, one of which was a test case for examining all possible power-balanced situations. The results were compared with the optimal costs obtained by the Bellman-Ford algorithm (BFA). This research concludes that the intelligent EMS proposed is reliable in reducing the operating costs of the HRES, and it posits itself as a more reliable and computationally cost-effective alternative to the optimisation techniques. © 2024, The Authors. All rights reserved.

关键词： Energy management systems

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Planing It by Ear: Convolutional Neural Networks for Acoustic Anomaly Detection in Industrial Wood Planers

Planing It by Ear: Convolutional Neural Networks for Acousti...

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2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Deschênes, Anthony Georges, Rémi Subakan, Cem Ugulino, Bruna Henry, Antoine Morin, Michael Dep. of Wood and Forest Sciences Université Laval QC Canada Dep. of Computer Science and Software Engineering Université Laval QC Canada Dep. of Operations and Decision Systems Université Laval QC Canada FORAC Research Consortium Université Laval QC Canada Mila-Quebec AI Institute QC Canada FPInnovations QC Canada Concordia University QC Canada

ISBN: (纸本)9798350368741

In recent years, the wood product industry has been facing a skilled labor shortage. The result is more frequent sudden failures, resulting in additional costs for these companies already operating in a very competitive market. Moreover, sawmills are challenging environments for machinery and sensors. Given that experienced machine operators may be able to diagnose defects or malfunctions, one possible way of assisting novice operators is through acoustic monitoring. As a step towards the automation of wood-processing equipment and decision support systems for machine operators, in this paper, we explore using a deep convolutional autoencoder for acoustic anomaly detection of wood planers on a new real-life dataset. Specifically, our convolutional autoencoder with skip connections (Skip-CAE) and our Skip-CAE transformer outperform the DCASE autoencoder baseline, one-class SVM, isolation forest and a published convolutional autoencoder architecture, respectively obtaining an area under the ROC curve of 0.846 and 0.875 on a dataset of real-factory planer sounds. Moreover, we show that adding skip connections and attention mechanism under the form of a transformer encoder-decoder helps to further improve the anomaly detection capabilities. © 2025 IEEE.

关键词： Acoustic Anomaly detection Convolutional neural networks Transformer Wood planer

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Two-Rated-Power, Dual-Winding, Three-Phase Induction Motor

Two-Rated-Power, Dual-Winding, Three-Phase Induction Motor

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International Conference on Electrical Machines, ICEM

作者： Fernando J. T. E. Ferreira Dep. of Electrical and Computer Engineering Institute of Systems and Robotics University of Coimbra Coimbra Portugal

ISBN: (数字)9798350370607

ISBN: (纸本)9798350370614

This paper proposes using star-delta and star-series connection modes in three-phase dual-winding squirrelcage induction motors to have available 100% and 55% of the original rated power for a given supply line-to-line voltage. The connection mode can be changed on a nine-terminal block. The experimental results obtained with a commercial 4-kW, 400-V, 50-Hz, 4-pole induction motor whose stator windings were redesigned to provide 4-kW and 2.2-kW output powers are presented and validate the proposed solution. Two-rated-power motors with the proposed output power ratio could be used as spare motors to replace faulty/damaged motors with the same frame size. The proposed solution allows fine-tuning the motor power to the actual maximum power required by the driven application/load and can be considered cost-effective as it may lead to significant gains in the motor efficiency and power factor when the low-power mode is adopted. In many cases, it may avoid the underloaded operation of induction motors, while keeping their original rated power available.

关键词： Reactive power Stator cores Costs Induction motors Torque Windings Stator windings Voltage Transformers Power generation

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CNN-based Human Activity Recognition on Edge Computing Devices

CNN-based Human Activity Recognition on Edge Computing Devic...

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Omni-layer Intelligent systems (COINS), International Conference on

作者： Amandeep Singh Tiziana Margaria Florenc Demrozi Dep. of Computer Science and Information Systems University of Limerick Ireland Dep. of Electrical Engineering and Computer Science University of Stavanger Norway

Human Activity Recognition (HAR) is a research area that involves wearable devices integrating inertial and/or physiological sensors to classify human actions and status across various application domains, such as healthcare, sports, industry, and entertainment. However, executing HAR algorithms on remote devices or the cloud can lead to issues such as latency, bandwidth requirements, and energy consumption. Transitioning towards Edge HAR can be a more effective and versatile solution, overcoming the challenges of traditional HAR techniques. We present a novel HAR model for computation on edge devices: we design a Convolutional Neural Network (CNN) Deep Learning approach and compare its performance with cloud-computing HAR models. The paper is accompanied by a self-collected dataset. The experiments on this dataset demonstrate that the proposed edge computing model achieves promising results ( $\geq$ 92 %) in terms of Precision, Recall, and Fl-score. Furthermore, the model exhibits significantly reduced latency, with only 117 ms, and utilizes minimal memory, with a peak of 18.8 Kb RAM and 956 Kb Flash memory.

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Intelligent Recognition of Immune Cells: Analysis and Research 19

Intelligent Recognition of Immune Cells: Analysis and Resear...

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19th IEEE International Conference on e-Business engineering, ICEBE 2023

作者： Li, Chih-En Liu, Wei-Lun Lai, Kun-Yi Chiang, Yu-Hsiang Yan, Xiaowei Chen, Hao-Xiang Li, Hsu-Ching Cheng, Wan-Shu National Kaohsiung University of Science and Technology Department of Electrical Engineering Kaohsiung Taiwan Institute for Systems Biology Seattle Washington United States Providence University Dep. of Computer Science and Information Management Taichung Taiwan

ISBN: (纸本)9798350325553

Immunotherapy utilizes the potential of the patient's immune system to fight disease. T-lymphocytes have become the central focus of the immune system in the fight against cancer. One of the fundamental studies in immunotherapy is how to accurately identify various types of immune cells. Therefore, the study of immune-related cells will be an important reference for the treatment of COVID19 or other related diseases. In this paper, a series of experiments were conducted with COVID-19 patients as the starting point to design a strategy to identify the important subtypes of CD$4^{+}$T cells. In this paper, an intelligent machine learning algorithm is proposed according to the results of different experiments of linear and nonlinear dimension reduction algorithms, integrating the important characteristics of these two algorithms and improving the performance. Our experimental results show that the algorithm designed based on the front-end experiments can effectively distinguish the important lymphocytes. The proposed algorithm not only improves the performance, but also the dimension reduction procedure keeps the important features of both global and regional data. The experimental results of this paper will be beneficial for the subsequent analysis of the clustering in identifying important subtypes of CD$4^{+}$T cells. Most importantly, this wm significantly improve the procedure of manually integrating and labeling the recorded data after several tedious and monotonous analyses with external software. © 2023 IEEE.

关键词： COVID-19

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Deception in Nash Equilibrium Seeking

arXiv

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arXiv 2024年

作者： Tang, Michael Javed, Umar Chen, Xudong Krstić, Miroslav Poveda, Jorge I. The Dep. of Electrical and Computer Engineering University of California La Jolla San DiegoCA United States The Dep. of Electrical Computer and Energy Engineering The University of Colorado BoulderCO United States The Dep. of Mechanical and Aerospace Engineering University of California La Jolla San DiegoCA United States The Dep. of Electrical and Systems Engineering Washington University Saint LouisMO United States

In socio-technical multi-agent systems, deception exploits privileged information to induce false beliefs in "victims," keeping them oblivious and leading to outcomes detrimental to them or advantageous to the deceiver. We consider model-free Nash-equilibrium-seeking for non-cooperative games with asymmetric information and introduce model-free deceptive algorithms with stability guarantees. In the simplest algorithm, the deceiver includes in his action policy the victim’s exploration signal, with an amplitude tuned by an integrator of the regulation error between the deceiver’s actual and desired payoff. The integral feedback drives the deceiver’s payoff to the payoff’s reference value, while the victim is led to adopt a suboptimal action, at which the pseudogradient of the deceiver’s payoff is zero. The deceiver’s and victim’s actions turn out to constitute a "deceptive" Nash equilibrium of a different game, whose structure is managed — in real time — by the deceiver. We examine quadratic, aggregative, and more general games and provide conditions for a successful deception, mutual and benevolent deception, and immunity to deception (for a "non-generic" set of payoff functions). Stability results are established using techniques based on averaging and singular perturbations. Among the examples in the paper is a microeconomic duopoly in which the deceiver induces in the victim a belief that the buyers disfavor the deceiver more than they actually do, leading the victim to increase the price above the Nash price, and resulting in an increased profit for the deceiver and a decreased profit for the victim. A study of the deceiver’s integral feedback for the desired profit reveals that, in duopolies with equal marginal costs, a deceiver that is greedy for very high profit can attain any such profit, and pursue this with arbitrarily high integral gain (impatiently), irrespective of the market preference for the victim. Copyright © 2024, The Authors. All rights reserved.

关键词： Profitability

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Enhancements to the 5G-NR 2-Step RACH: an Unsourced Multiple Access Perspective

Enhancements to the 5G-NR 2-Step RACH: an Unsourced Multiple...

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2024 IEEE Conference on Standards for Communications and Networking, CSCN 2024

作者： Agostini, Patrick Chamberland, Jean-Francois Clazzer, Federico Dommel, Johannes Liva, Gianluigi Munari, Andrea Narayanan, Krishna Polyanskiy, Yury Stanczak, Slawomir Utkovski, Zoran Fraunhofer Heinrich-Hertz-Institut Berlin Germany Texas A&M University College Station Dep. of Electrical and Computer Engineering TX United States Wessling Germany Massachusetts Institute of Technology Laboratory for Information and Decision Systems CambridgeMA United States

ISBN: (纸本)9798331507428

The ever increasing demand for massive connectivity, combined with the specific characteristics of machinegenerated wireless traffic, is pushing the existing solutions for device registration and data transfer beyond their operational limits. In this paper, we target specifically the 3GPP 5G New Radio random access channel, proposing some enhancements inspired by recent research results in the field of unsourced multiple access (UMAC). Aiming to enable massive grant-free connectivity for large machine-type and Internet of things terminals, we focus on modifications of the two-step random access procedures originally introduced in 3GPP Release 16. By means of simulations, we show that remarkable gains in both energy and spectral efficiency can be attained while retaining a strong resemblance to the legacy protocol. © 2024 IEEE.

关键词： 5G mobile communication systems

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IoT based on Membrane Computing Models 11

IoT based on Membrane Computing Models

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11th International Conference on Electromechanical and Energy systems, SIELMEN 2021

作者： Victor, Ababii Viorica, Sudacevschi Silvia, Munteanu Olesea, Borozan Ana, Nistiriuc Victor, Lasco Technical University of Moldova Computer Sciences and Systems Engineering Dep. Chisinau Moldova

ISBN: (纸本)9781665400787

In the given paper it is approached a method of the application of the Membrane Computing models in the design of IoT systems with Collective Intelligence properties. The topology of the IoT system is presented as a Mesh network that ensures a total interconnection of its devices. The Collective Intelligence definition model presents a Hopfield Neural Network based on the set of knowledge consisting of data and their processing models. The following were elaborated: cell structure, cell interaction diagram and the manner of formation of hierarchical structures and of Collective Intelligence. The synthesis process of an IoT system on the basis of Membrane Computing models with Collective Intelligence properties is presented by the sequence of operations that begins with the definition of the mathematical model and ends with the development of the structure of the IoT system on the basis of the programmable devices ESP8266. © 2021 IEEE.

关键词： Hopfield neural networks

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