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2023 Advances in Science and engineering Technology International Conferences, ASET 2023

作者： Baz Khan, Kashif Rast Al-Othman, Amani Al-Nashash, Hasan Al-Sayah, Mohammad American University of Sharjah Biomedical Engineering Graduate Program Sharjah United Arab Emirates American University of Sharjah Department of Chemical and Biological Engineering Sharjah United Arab Emirates American University of Sharjah Department of Electrical Engineering Sharjah United Arab Emirates American University of Sharjah Chemistry and Environmental Sciences Sharjah United Arab Emirates

ISBN: (纸本)9781665454742

Research applications of neural sensing and muscle stimulation have been advanced by the development of bioelectrodes that are biocompatible, flexible and long lasting. The existing metallic made bioelectrodes exhibit extremely high electrochemical resistances that would interfere with the neural-electrode bridge and suffer from mechanical and immunological mismatch. Novel, flexible, implantable bioelectrodes based on MXenes (Ti3C2) and Polydimethylsiloxane (PDMS) composite are proposed. Mxenes possess the advantage of having metallic ultra-conductive transition metals consisting of large groups of carbides, nitrides, or carbonitrides, while PDMS has inherent biostability, flexibility and biocompatibility. In the current research, PDMS has been used as the supporting matrix for conductive fillers such as PMMA, PEDOT, and Mxenes. A series of characterization techniques were performed such as Electrochemical Impedance Spectroscopy (EIS), Cyclic Voltammetry (CV) and mechanical testing. The average results of triplicate samples exhibited samples' bulk impedance of 0.913 kΩ, an impedance of 1.612 MΩ, at 1 kHz frequency and a conductivity of 1.41x10-4S/cm, charge storage capacity of 0.056 mC/cm2 and Young's modulus of 3.81 MPa. © 2023 IEEE.

关键词： Elastic moduli

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Impact of In flux on self-assembled InGaN/GaN superlattice grown on GaN template by plasma-assisted molecular beam epitaxy

Impact of In flux on self-assembled InGaN/GaN superlattice g...

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2022 Compound Semiconductor Week, CSW 2022

作者： Khan, Kamruzzaman Sun, Kai Wurm, Christian Ahmadi, Elaheh University of Michigan Department of Materials Science and Engineering Ann ArborMI United States University of California Department of Electrical and Computer Engineering Santa BarbaraCA United States University of Michigan Department of Electrical Engineering and Computer Science Ann ArborMI United States University of Michigan Applied Physics Program Ann ArborMI United States

ISBN: (数字)9781665453400

ISBN: (纸本)9781665453400

We have previously reported spontanous formation of InGaN/GaN superlattice structure on nominal InGaN films grown by plasma-assisted molecular beam epitaxy (PAMBE). In this work, we report on the impact of In flux on the formation and periodicity of self-assembled InxGa1-xN/InyGa1-yN superlattice structure (SASL). We show that the thickness and In composition in the InGaN layer varies by changing the In flux. These films were stucturally characterized by X-ray diffraction and simulated by globalfit software to get the thickness and In composition. The superlattice structures were confimred by scanning transmission electron microscopy and the thickness of InGaN layer and In composition were determined by energy dispersive X-ray spectroscopy. This work can provide a method for using the SASL with better control for their optoelectronics application. © 2022 IEEE.

关键词： III-V semiconductors

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Optimizing Trading Strategies in Quantitative Markets Using Multi-Agent Reinforcement Learning

Optimizing Trading Strategies in Quantitative Markets Using ...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Hengxi Zhang Zhendong Shi Yuanquan Hu Wenbo Ding Ercan E. Kuruoğlu Xiao-Ping Zhang Shenzhen International Graduate School Tsinghua University Shenzhen China Department of Electrical Computer and Biomedical Engineering Ryerson University Toronto Canada

Quantitative markets are characterized by swift dynamics and abundant uncertainties, making the pursuit of profit-driven stock trading actions inherently challenging. Within this context, Reinforcement Learning (RL) — which operates on a reward-centric mechanism for optimal control — has surfaced as a potentially effective solution to the intricate financial decision-making conundrums presented. This paper delves into the fusion of two established financial trading strategies, namely the constant proportion portfolio insurance (CPPI) and the time-invariant portfolio protection (TIPP), with the multi-agent deep deterministic policy gradient (MADDPG) framework. As a result, we introduce two novel multi-agent RL (MARL) methods: CPPI-MADDPG and TIPP-MADDPG, tailored for probing strategic trading within quantitative markets. To validate these innovations, we implemented them on a diverse selection of 100 real-market shares. Our empirical findings reveal that the CPPI-MADDPG and TIPP-MADDPG strategies consistently outpace their traditional counterparts, affirming their efficacy in the realm of quantitative trading.

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Research Article Interaction of Transformer Oil Parameters on Each Other and on Transformer Health Index Using Curve Estimation Regression Method

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International Transactions on electrical Energy Systems 2022年 2022卷

作者： Saeid, Morteza Zeinoddini-Meymand, Hamed Kamel, Salah Khan, Baseem Department of Electrical and Computer Engineering Graduate University of Advanced Technology Kerman Iran Department of Electrical Engineering Faculty of Engineering Aswan University Aswan81542 Egypt Department of Electrical and Computer Engineering Hawassa University Hawassa Ethiopia

Power transformers are one of the most significant and expensive equipment in power systems that are exposed to electrical, thermal, and chemical tensions. The transformer health index is a measure that uses test data and field inspections to assess the condition and determine the remaining life of the transformer. The purpose of this article as a new idea is to determine the relationships between electrical, physical, and chemical parameters of transformer oil, dissolved gases, and the transformer health index. One of the advantages of using the regression method in analyzing transformer data compared to the other methods to evaluate the transformer health index is determining the influence of the parameters that have the most impact on each other. Some achievements of this article are as follows: (1) introducing moisture content as the parameter that plays an effective role in reducing dielectric oil breakdown voltage and improving the transformer health index;(2) determining the inverse relationship between acidity and furfural components;(3) determining furfural as a parameter with the greatest role in reducing the Interfacial tension (IFT) of oil (molecular interconnection);(4) determining CO gas as the parameter with the most role in the production of furfural component;(5) determining C2H2 gas as the parameter with the most role in producing the acid component. For example, with a 1 ppm increase in the moisture component, the oil breakdown voltage decreases by 0.583 kV in the compound, growth, exponential, and logistic regressions, or with a 1 ppm increase in the furfural component, the oil interfacial tension decreases by 0.644 mN/m in power regression. In this article, the curve estimation regression method is used and the results are plotted by SPSS statistical software to analyze the interaction between different transformer parameters. To perform the simulations, test data related to 120 transformers have been considered. Copyright © 2022 Morteza Saeid e

关键词： Furfural

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AV Navigation in 3D Urban Environments with Curriculum-based Deep Reinforcement Learning

AV Navigation in 3D Urban Environments with Curriculum-based...

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International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Kevin Braathen de Carvalho Iure Rosa L. de Oliveira Alexandre S. Brandão Department of Electrical Engineering Graduate Program in Computer Science Nucleus of Specialization in Robotics Universidade Federal de Viçosa Viçosa MG Brazil Department of Electrical Engineering Federal University of Viçosa Viçosa MG Brazil

Unmanned Aerial Vehicles (UAVs) are widely used in various applications, from inspection and surveillance to transportation and delivery. Navigating UAVs in complex 3D environments is a challenging task that requires robust and efficient decision-making algorithms. This paper presents a novel approach to UAV navigation in 3D environments using a Curriculum-based Deep Reinforcement Learning (DRL) approach. The proposed method utilizes a deep neural network to model the UAV’s decision-making process and to learn a mapping from the state space to the action space. The learning process is guided by a reinforcement signal that reflects the performance of the UAV in terms of reaching its target while avoiding obstacles and with energy efficiency. Simulation results show that the proposed method has a positive trade off when compared to the baseline algorithm. The proposed method was able to perform well in environments with a state space size of 22 millions, allowing the usage in big environments or in maps with high resolution. The results demonstrate the potential of DRL for enabling UAVs to operate effectively in complex environments.

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Mixed Deep Reinforcement Learning Considering Discrete-continuous Hybrid Action Space for Smart Home Energy Management

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Journal of Modern Power Systems and Clean Energy 2022年第3期10卷 743-754页

作者： Chao Huang Hongcai Zhang Long Wang Xiong Luo Yonghua Song IEEE State Key Laboratory of Internet of Things for Smart City University of MacaoMacao S.A.R.China School of Computer and Communication Engineering University of Science and Technology BeijingBeijing 100083China Shunde Graduate School University of Science and Technology BeijingFoshan 528399China State Key Laboratory of Internet of Things for Smart City and Department of Electrical and Computer Engineering University of MacaoMacao S.A.R.China

This paper develops deep reinforcement learning(DRL)algorithms for optimizing the operation of home energy system which consists of photovoltaic(PV)panels,battery energy storage system,and household ***-free DRL algorithms can efficiently handle the difficulty of energy system modeling and uncertainty of PV ***,discretecontinuous hybrid action space of the considered home energy system challenges existing DRL algorithms for either discrete actions or continuous ***,a mixed deep reinforcement learning(MDRL)algorithm is proposed,which integrates deep Q-learning(DQL)algorithm and deep deterministic policy gradient(DDPG)*** DQL algorithm deals with discrete actions,while the DDPG algorithm handles continuous *** MDRL algorithm learns optimal strategy by trialand-error interactions with the ***,unsafe actions,which violate system constraints,can give rise to great *** handle such problem,a safe-MDRL algorithm is further *** studies demonstrate that the proposed MDRL algorithm can efficiently handle the challenge from discrete-continuous hybrid action space for home energy *** proposed MDRL algorithm reduces the operation cost while maintaining the human thermal comfort by comparing with benchmark algorithms on the test ***,the safe-MDRL algorithm greatly reduces the loss of thermal comfort in the learning stage by the proposed MDRL algorithm.

关键词： Demand response deep reinforcement learning discrete-continuous action space home energy management safe reinforcement learning

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Generation of Synthetic Series for Hydroelectric Plants in Brazilian Interconnected System by Metaheuristic

Generation of Synthetic Series for Hydroelectric Plants in B...

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International Universities Power engineering Conference (UPEC)

作者： Renato Andrade Mosqueira Furtado André Luís Marques Marcato Ivo Chaves da Silva Junior Electrical Engineering Graduate Program Federal University of Juiz de Fora Juiz de Fora Brazil Department of Electrical Engineering Federal University of Juiz de Fora Juiz de Fora Brazil

ISBN: (数字)9798350379730

ISBN: (纸本)9798350379747

This article aims to explain the use of the intelligent technique known as Arithmetic Optimization Algorithm for generating synthetic series for hydroelectric plants which belong to the Brazilian interconnected system. Thus, the metaheuristic is responsible for determining the best coefficients as well as the optimal order for each month which may represent historical data based on an optimization problem whose objective function is to minimize the standard deviation of errors between the real and estimated water inflow values. Finally, with the optimal coefficients and order, the next step is to generate synthetic flow series considering a period of five years ahead, guaranteeing forecasts of inflow energy which are coherent with the historical data. The simulations were carried out considering Itaipu, Belo Monte, Tucuruí and Comp PAF-MOX hydroelectric plants whose results show the applicability of the Arithmetic Optimization Algorithm for generating flow scenarios allowing a convincing energy planning.

关键词： Power engineering Metaheuristics Interconnected systems Linear programming Planning Standards Arithmetic

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Black-hole-inspired thermal trapping with graded heat-conduction metadevices

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National Science Review 2023年第2期10卷 131-138页

作者： Liujun Xu Jinrong Liu Peng Jin Guoqiang Xu Jiaxin Li Xiaoping Ouyang Ying Li Cheng-Wei Qiu Jiping Huang Department of Physics State Key Laboratory of Surface Physics and Key Laboratory of Micro and Nano Photonic Structures (MOE) Fudan University Department of Electrical and Computer Engineering National University of Singapore Graduate School of China Academy of Engineering Physics School of Materials Science and Engineering Xiangtan University Interdisciplinary Center for Quantum Information State Key Laboratory of Modern Optical InstrumentationZJU-Hangzhou Global Scientific and Technological Innovation CenterZhejiang University International Joint Innovation Center Key Laboratory of Advanced Micro/Nano Electronic Devices and Smart Systems of Zhejiang The Electromagnetics Academy of Zhejiang University Zhejiang University

The curved space-time produced by black holes leads to the intriguing trapping *** far,metadevices have enabled analogous black holes to trap light or sound in laboratory ***,trapping heat in a conductive environment is still challenging because diffusive behaviors are *** by black holes,we construct graded heat-conduction metadevices to achieve thermal trapping,resorting to the imitated advection produced by graded thermal conductivities rather than the trivial solution of using insulation materials to confine thermal *** experimentally demonstrate thermal trapping for guiding hot spots to diffuse towards the *** heat-conduction metadevices have advantages in energy-efficient thermal regulation because the imitated advection has a similar temperature field effect to the realistic advection that is usually driven by external energy *** results also provide an insight into correlating transformation thermotics with other disciplines,such as cosmology,for emerging heat control schemes.

关键词： thermal trapping graded metadevices imitated advection

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MathReader : Text-to-Speech for Mathematical Documents

MathReader : Text-to-Speech for Mathematical Documents

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Sieun Hyeon Kyudan Jung Nam-Joon Kim Hyun Gon Ryu Jaeyoung Do Department of Electrical and Computer Engineering Seoul National University Department of Mathematics Chung-Ang University NVIDIA Interdisciplinary Program in Artificial Intelligence Seoul National University

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

TTS (Text-to-Speech) document reader from Microsoft, Adobe, Apple, and OpenAI have been serviced worldwide. They provide relatively good TTS results for general plain text, but sometimes skip contents or provide unsatisfactory results for mathematical expressions. This is because most modern academic papers are written in LaTeX, and when LaTeX formulas are compiled, they are rendered as distinctive text forms within the document. However, traditional TTS document readers output only the text as it is recognized, without considering the mathematical meaning of the formulas. To address this issue, we propose MathReader, which effectively integrates OCR, a fine-tuned T5 model, and TTS. MathReader demonstrated a lower Word Error Rate (WER) than existing TTS document readers, such as Microsoft Edge and Adobe Acrobat, when processing documents containing mathematical formulas. MathReader reduced the WER from 0.510 to 0.281 compared to Microsoft Edge, and from 0.617 to 0.281 compared to Adobe Acrobat. This will significantly contribute to alleviating the inconvenience faced by users who want to listen to documents, especially those who are visually impaired. The code is available at https://***/hyeonsieun/MathReader.

关键词： Text recognition Error analysis Pipelines Optical character recognition Graphics processing units Signal processing Real-time systems Mathematical models Text to speech Speech processing

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PyBlocks: A Modular Open-Source Simulator for Visible Light Communication Systems

PyBlocks: A Modular Open-Source Simulator for Visible Light ...

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International Symposium on Instrumentation Systems, Circuits and Transducers (INSCIT)

作者： Luiz Santana Árabe P. B Pedro Oliveira Luciana P. Salles Graduate Program in Electrical Engineering Universidade Federal de Minas Gerais Belo Horizonte MG Brazil Department of Electrical Engineering Universidade Federal de Minas Gerais Belo Horizonte MG Brazil

ISBN: (数字)9798350350869

ISBN: (纸本)9798350350876

The PyBlocks Simulator is an open-source tool designed for Visible Light Communication (VLC) systems using a block diagram paradigm. It promotes modularity and reusability by representing system components as blocks implemented in Python. PyBlocks can simultaneously simulate multiple domains, making it suitable for complex systems that require analyzing combined effects across electrical and optical layers. This study validates PyBlocks by comparing its simulated results with experimental data from a real VLC system. The open-source nature of PyBlocks fosters collaboration and continuous improvement, providing a valuable resource for researchers and professionals in the field.

关键词： Transducers Instruments Cutoff frequency Optical receivers Software Encoding Systems simulation Optical transmitters Visible light communication Python

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