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International Conference on Mechatronics (ICOM)

作者： Ralph Laurence G. Visaya Ralph Gerard B. Sangalang Department of Electronics Engineering Batangas State University- The Nat'l Eng'g University Batangas City Philippines Dept. of Electronics Engineering Dept. of Computer Engineering Tanauan City College Electronics Systems Research Center Batangas State University- The Nat'l Eng'g University Batangas City Philippines Dept. of Electronics Engineering Batangas State University- The National Engineering University Philippines

ISBN: (数字)9798350349788

ISBN: (纸本)9798350349795

Power supply systems are an essential component of current infrastructure and must operate reliably. Short-circuit defects pose a danger to power supply stability and may potentially result in equipment damage and system outages. This research presents a novel approach for predicting and detecting short circuit faults in power supply systems by combining the Daubechies wavelet transform with convolutional neural networks (CNNs). The researcher will make use of MATLAB Simulink and focuses on the design and simulation with short circuit faults introduced at known points of linear power supplies, boost converters, and buck converters. The voltage and current from the simulations were exported and then fed to Python with the use of PyWavelet for mathematical analysis. The researcher will make use of the db4 transform for the Daubechies wavelet. This decomposes the signals into detail coefficients at various scales, which are then converted into 1D vectors to be flattened and used for training with CNN. Based on the data and results, this shows 94.22% accuracy and 94.67% mAP (mean average precision) at 35 epochs. The researchers concluded that this study was feasible and reliable for implementation in real-world scenarios.

关键词： Wavelet transforms Buck converters Accuracy Power supplies Software packages Voltage Vectors

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Developmental Scaffolding with Large Language Models

arXiv

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arXiv 2023年

作者： Celik, Batuhan Ahmetoglu, Alper Ugur, Emre Oztop, Erhan Computer Engineering Dept. Bogazici University Istanbul Turkey Computer Science Dept. Ozyegin University Istanbul Turkey Symbiotic Intelligent Systems Research Center Institute for Open and Transdisciplinary Research Initiatives Osaka University Japan

Exploration and self-observation are key mechanisms of infant sensorimotor development. These processes are further guided by parental scaffolding to accelerate skill and knowledge acquisition. In developmental robotics, this approach has been adopted often by having a human acting as the source of scaffolding. In this study, we investigate whether Large Language Models (LLMs) can act as a scaffolding agent for a robotic system that aims to learn to predict the effects of its actions. To this end, an object manipulation setup is considered where one object can be picked and placed on top of or in the vicinity of another object. The adopted LLM is asked to guide the action selection process through algorithmically generated state descriptions and action selection alternatives in natural language. The simulation experiments that include cubes in this setup show that LLM-guided (GPT3.5-guided) learning yields significantly faster discovery of novel structures compared to random exploration. However, we observed that GPT3.5 fails to effectively guide the robot in generating structures with different affordances such as cubes and spheres. Overall, we conclude that even without fine-tuning, LLMs may serve as a moderate scaffolding agent for improving robot learning, however, they still lack affordance understanding which limits the applicability of the current LLMs in robotic scaffolding tasks. © 2023, CC BY.

关键词： Scaffolds

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Online Complaint Management System using Image Recognition

Online Complaint Management System using Image Recognition

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International Conference on Communication and Electronics systems (ICCES)

作者： S. Balakrishnan J. Janet Rohith T Sakthivel R Sanjaiy Kumar T N Dept. of Computer Science and Business Systems Sri Krishna College of Engg. and Technology Coimbatore Tamilnadu India Dept. of Computer Science and Engineering Sri Krishna College of Engg. and Technology Coimbatore Tamilnadu India

Clean and safe environments are the responsibility of the government. Currently, people have to lodge their complaints with the Municipal Corporation, and then workers take time to respond to them. In this paper we have made a platform to overcome the communication gap between the user and the municipal corporation. This research study proposes an online complaint management system in a web application, where the citizen can lodge a complaint by taking a picture. After the picture being uploaded, image recognition is used to automatically detect the problem raised by the user and Google map API to detect the location automatically. As soon as the problem has been resolved, the municipal corporation must upload a completed status picture to verify that the work has been completed. The aim of this application is to overcome the communication gap between user and Municipal Corporation, to simplify the process of raising complaints and to maintain a clean and safe environment.

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A Model for Intelligible Interaction Between Agents That Predict and Explain

arXiv

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arXiv 2023年

作者： Baskar, A. Srinivasan, Ashwin Bain, Michael Coiera, Enrico Dept. of Computer Science Information Systems BITS Pilani Goa Campus India Dept. of Computer Science Information Systems and APPCAIR BITS Pilani Goa Campus India School of Computer Science Engineering University of New South Wales Australia Centre for Health Informatics Macquarie University Sydney Australia

Machine Learning (ML) has emerged as a powerful form of data modelling with widespread applicability beyond its roots in the design of autonomous agents. However, relatively little attention has been paid to the interaction between people and ML systems. In this paper we view interaction between humans and ML systems within the broader context of communication between agents capable of prediction and explanation. We formalise the interaction model by taking agents to be automata with some special characteristics and define a protocol for communication between such agents. We define One- and Two-Way Intelligibility as properties that emerge at run-time by execution of the protocol. The formalisation allows us to identify conditions under which run-time sequences are bounded, and identify conditions under which the protocol can correctly implement an axiomatic specification of intelligible interaction between a human and an ML system. We also demonstrate using the formal model to: (a) identify instances of One- and Two-Way Intelligibility in literature reports on humans interacting with ML systems providing logic-based explanations, as is done in Inductive Logic programming (ILP);and (b) map interactions between humans and machines in an elaborate natural-language based dialogue-model to One- or Two-Way Intelligible interactions in the formal model. © 2023, CC BY.

关键词： Inductive logic programming (ILP)

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Comparative Analysis of MLP and CNN-LSTM Models for Solar Power Generation Forecasting 9

Comparative Analysis of MLP and CNN-LSTM Models for Solar Po...

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9th IEEE International Conference on Smart Instrumentation, Measurement and Applications, ICSIMA 2023

作者： Jannah, Nurul Hanifah, Mohd Shahrin Abu Gunawan, Teddy Surya Zabidi, Suriza Ahmad Yusoff, Siti Hajar Sapihie, Siti Nadiah Mohd International Islamic University Malaysia Electrical and Computer Engineering Dept. Kuala Lumpur53100 Malaysia International Islamic University Malaysia Information Systems Department Kuala Lumpur53100 Malaysia National Petroleum Limited Petronas Research Sdn Bhd Bandar Baru Bangi43000 Malaysia

ISBN: (纸本)9798350343380

Solar energy, a cornerstone of renewable energy, for optimal grid integration and management, requires precise forecasting. Photovoltaic (PV) forecasting must be accurate to ensure energy stability and maximize resource utilization. This study compares Multi-Layer Perceptron (MLP) and Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) models for forecasting solar power generation. Both models were trained with 13 features using an open-source dataset from 10 PV sites in Hebei Province, China, spanning 300 days (2018-07-01 to 2019-06-13). The CNN-LSTM was configured with 50 epochs and particular hyperparameters. CNN-LSTM demonstrated superior performance, with Mean Absolute Error (MAE), Mean Squared Error (MSE), and Root Mean Squared Error (RMSE) values of 0.088, 0.051, and 0.227 versus MLP's 0.260, 0.156, and 0.395. The findings demonstrate CNN-LSTM's potential for enhancing solar power forecasting and facilitating the management of renewable energy sources. © 2023 IEEE.

关键词： Long short-term memory

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Slotted ALOHA with Code Combining for IoT Networks

Slotted ALOHA with Code Combining for IoT Networks

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Communications and Networking (MeditCom), IEEE International Mediterranean Conference on

作者： Dimitrios Tyrovolas Athanasios Chrysologou Georgios Chondrogiannis Sotiris Tegos Prodromos-Vasileios Mekikis Panagiotis Diamantoulakis Sotiris Ioannidis Christos Liaskos Nestor Chatzidiamantis George Karagiannidis Dept. of Electrical and Computer Engineering Aristotle University of Thessaloniki Thessaloniki Greece Dept. of Electrical and Computer Engineering Technical University of Chania Chania Greece Computer Science Engineering Department University of Ioannina Ioannina Greece Cyber Security Systems and Applied AI Research Center Lebanese American University (LAU) Lebanon

Internet of Things (IoT) networks are expected to be a key enabler technology for smart cities, due to their ability to offer real-time monitoring. In this work, we propose a novel medium access control (MAC) protocol, inspired by the synergy of slotted ALOHA and hybrid automatic repeat request with code combining (HARQ-CC), termed as code combining slotted ALOHA (CCSA), to improve the performance of IoT networks with multiple randomly deployed sensors. Specifically, we provide analytical closed-form expressions for the network’s outage probability as well as for its average throughput when CCSA is applied. Finally, we provide simulation results that reveal the authenticity of the derived expressions and reveal the capabilities of HARQ-CC to significantly improve the network’s performance when the sensors’ access is based on a random access scheme.

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Open RAN Testbeds with Controlled Air Mobility

arXiv

引用

arXiv 2023年

作者： Mushi, Magreth Liu, Yuchen Sreenivasa, Shreyas Ozdemir, Ozgur Guvenc, Ismail Sichitiu, Mihail Dutta, Rudra Gyurek, Russ The Dept. Computer Science NC State University RaleighNC United States The Dept. Electrical and Computer Engineering NC State University RaleighNC United States Cisco Systems RaleighNC United States

With its promise of increasing softwarization, improving disaggregability, and creating an open-source based ecosystem in the area of Radio Access Networks, the idea of Open RAN has generated rising interest in the community. Even as the community races to provide and verify complete Open RAN systems, the importance of verification of systems based on Open RAN under real-world conditions has become clear, and testbed facilities for general use have been envisioned, in addition to private testing facilities. Aerial robots, including autonomous ones, are among the increasingly important and interesting clients of RAN systems, but also present a challenge for testbeds. Based on our experience in architecting and operating an advanced wireless testbed with aerial robots as a primary citizen, we present considerations relevant to the design of Open RAN testbeds, with particular attention to making such a testbed capable of controlled experimentation with aerial clients. We also present representative results from the NSF AERPAW testbed on Open RAN slicing, programmable vehicles, and programmable radios. © 2023, CC BY-NC-SA.

关键词： Drones

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SPARROW: Smart Precision Agriculture Robot for Ridding of Weeds

SPARROW: Smart Precision Agriculture Robot for Ridding of We...

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Emerging Technology (INCET), International Conference for

作者： Dhanushka Balasingham Sadeesha Samarathunga Gayantha Godakanda Arachchige Anuththara Bandara Sasini Wellalage Dinithi Pandithage Mahaadikara M.D.J.T Hansika Rajitha De Silva Dept. of Computer Systems Engineering Sri Lanka Institute of Information Technology Sri Lanka City of Melbourne Australia Lincoln Agri-Robotics University of Lincoln United Kingdom

ISBN: (数字)9798350361155

ISBN: (纸本)9798350361162

The advancements in precision agriculture are vi-tal to support the increasing demand for global food supply. Precision spot spraying is a major step towards reducing chemicalusage for pest and weed control in agriculture. A novel spot spraying algorithm that autonomously detects weeds and performs trajectory planning for the sprayer nozzle has been proposed. Furthermore, this research introduces a vision-based autonomous navigation system that operates through the detected crop row, effectively synchronizing with an autonomous spraying algorithm. This proposed system is characterized by its cost effectiveness that enable the autonomous spraying of herbicides onto detected weeds.

关键词： Precision agriculture Laser radar Costs Trajectory planning Navigation Spraying Crops

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A Single-Phase Seven-Level Inverter With Triple Boosting Ability

A Single-Phase Seven-Level Inverter With Triple Boosting Abi...

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International Conference on Power Electronics (ICPE)

作者： Dai-Van Vo Minh-Khai Nguyen Truong-Duy Duong Van-Cuong Bui Young-Cheol Lim Joon-Ho Choi Dept. Electrical Engineering Chonnam National University Gwangju Korea Global Electrification & Battery Systems General Motors Warren MI USA Dept. of Electrical and Computer Engineering Wayne State University Detroit USA

This paper proposes a new seven-level inverter for a single-phase system. The proposed topology uses only eight switches, in which the other four switches act as H-bridge, and the others participate in a step-up converter. By applying the switched-capacitor method, three capacitors are connected to the DC source to produce seven-level of voltage, and the output voltage can be stepped up to three times. A comparison study was made to evaluate the proposed seven-level inverter with other seven-level inverters. Finally, experimental results are shown to verify the effectiveness of the proposed seven-level inverter.

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Modelling Weave effect in PCBs using 2D cross-sectional analysis

Modelling Weave effect in PCBs using 2D cross-sectional anal...

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IEEE International Symposium on Electromagnetic Compatibility (EMC)

作者： Dr. Victor Khilkevich Scott Hinaga Dept. of Electrical and Computer Engineering – Electromagnetic Compatibility Laboratory Missouri University of Science and Technology Rolla MO USA Cisco Systems Inc San Jose CA USA

ISBN: (数字)9798350360394

ISBN: (纸本)9798350360400

Printed circuit board dielectric substrates are composite materials produced by embedding fiber glass fabrics into epoxy resin. Because of this the medium in the PCB transmission lines is inhomogeneous which often leads to degradation of the signal integrity performance of the lines, particularly due to the differential skew. The detrimental effect of the fiber weave can be modeled relatively accurately using full-wave analysis, but at a high computational cost. Alternative modelling techniques are less demanding, but often lack accuracy. This article investigates a possibility of using the 2D cross-sectional analysis for the fiber weave effect modeling, which considerably decreases the computational cost of modeling while retaining the accuracy inherent to the field solvers.

关键词： Geometry Analytical models Accuracy Computational modeling Printed circuits Glass Nonhomogeneous media Fabrics Computational efficiency Signal integrity

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