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A Self‑Powered Piezoelectric Nanofibrous Membrane as Wearable Tactile Sensor for Human Body Motion Monitoring and Recognition

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Advanced Fiber Materials 2023年第4期5卷 1417-1430页

作者： Jingcheng Li Jing Yin Mei Gui Vanessa Wee Amutha Chinnappan Seeram Ramakrishna Centre for Nanotechnology and Sustainability Department of Mechanical EngineeringNational University of SingaporeSingapore 117081Singapore National Engineering Laboratory for Modern Silk College of Textile and Clothing EngineeringSoochow UniversitySuzhouChina Integrative Sciences and Engineering Program NUS Graduate SchoolNational University of SingaporeSingapore 119077Singapore

Wearable sensors have drawn vast interest for their convenience to be worn on body to monitor and track body movements or exercise activities in real ***,wearable electronics rely on powering systems to ***,a self-powered,porous,flexible,hydrophobic and breathable nanofibrous membrane based on electrospun polyvinylidene fluoride(PVDF)nanofiber has been developed as a tactile sensor with low-cost and simple fabrication for human body motion detection and ***,effects of multi-walled carbon nanotubes(CNT)and barium titanate(BTO)as additives to the fiber morphology as well as mechanical and dielectric properties of the piezoelectric nanofiber membrane were *** fabricated BTO@PVDF piezoelectric nanogenerator(PENG)exhibits the highβ-phase content and best overall electrical performances,thus selected for the flexible sensing device ***,the nanofibrous membrane demonstrated robust tactile sensing performance that the device exhibits durability over 12,000 loading test cycles,holds a fast response time of 82.7 ms,responds to a wide pressure range of 0-5 bar and shows a high relative sensitivity,especially in the small force range of 11.6 V/bar upon pressure applied perpendicular to the ***,when attached on human body,its unique fibrous and flexible structure offers the tactile sensor to present as a health care monitor in a self-powered manner by translating motions of different movements to electrical signals with various patterns or sequences.

关键词： Electrospinning Nanofiber Piezoelectric sensor PENG Wearable Self-powered device

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Deep Neural Networks for ENSO Prediction in the Niño 3.4 and Niño 1+2 Regions

Deep Neural Networks for ENSO Prediction in the Niño 3.4 an...

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World Environmental and Water Resources Congress 2023: Adaptive Planning and Design in an Age of Risk and Uncertainty

作者： Gomez-Tunque, Kennedy Richard Ingol-Blanco, Eusebio Mejia-Marcacuzco, Abel Chávarri-Velarde, Eduardo Pino-Vargas, Edwin Graduate Program in Water Resources Engineering School of Civil Engineering Universidad Nacional de Huancavelica Lima Peru Graduate Program in Water Resources Engineering Universidad Nacional Agraria la Molina Lima Peru Dept. of Civil Engineering Universidad Nacional Jorge Basadre Grohmann Tacna Peru

ISBN: (数字)9780784484852

ISBN: (纸本)9780784484852

Forecasting the El Niño-Southern Oscillation (ENSO) is one of the most challenging tasks because ENSO events show large differences in their amplitude, temporal evolution, and spatial pattern. This research discusses a deep neural network model that integrates convolutional short-term and long-term memory (ConvLSTM) to forecast the patterns of sea surface temperature that represent the evolution of ENSO over different time horizons with simultaneous space-time sequences in the Niño 3.4 and Niño 1+2 regions. Monthly gridded sea surface temperature and anomaly index data were used in El Niño regions for the period 1854-2021. In general, the methodology includes the sea surface temperature (SST) normalization of the tropical Pacific, the creation and selection of the architecture of the deep neural network model, and the training and validation. Furthermore, the forecast and evaluation of the SST and SST anomalies in space-time with the El Niño of 1982/1983 and 1997/1998 and with different time horizons for the test stage were developed. The results show a good model performance with ENSO data for El Niño 1982/1983 (training) and El Niño 1997/1998 (validation) in space and time, and with climatic indices for regions 3.4 and 1+2. The model performance was evaluated using statistical metrics of observed and forecasted data over six months in the equatorial Pacific Ocean (latitude 10°S-10°N and longitude 140°E-80°W). In general, all the metrics used to evaluate the accuracy and forecast of the model show a range from good to excellent for both El Niño regions in the six months of forecast. © World Environmental and Water Resources Congress *** rights reserved

关键词： Surface temperature

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Exploring Bess Services for Transformer Energization on Offshore Oil and Gas Platforms

Exploring Bess Services for Transformer Energization on Offs...

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2024 IEEE Petroleum and Chemical Industry Conference Brasil, PCIC Brasil 2024

作者： Banda, Joseph K. Araujo, Lucas S. Brandao, Danilo I. Marafao, Fernando P. Tedeschi, Elisabetta Department of Electric Power Engineering Trondheim Norway Graduate Program in Electrical Engineering Belo Horizonte Brazil Department of Control and Automation Engineering Sorocaba Brazil University of Trento Department of Industrial Engineering Trento Italy

ISBN: (纸本)9798350368154

The electrification of offshore oil and gas platforms (OOGPs), using offshore wind turbines, is now a reality, aimed at minimizing carbon emissions. In this scenario, the utilization of battery energy storage systems (BESS) improves both efficiency and power quality. As this integration comes with a high CAPEX, industries demand exploring BESS for multiple ancillary services on OOGPs. Thus, this paper proposes an alternative approach to energizing a power transformer (PT) using the BESS power conversion system (PCS) on the platform, aiming to minimize inrush currents. This avoids the necessity for additional bulky devices, converters, or dc voltage sources specifically designated for this purpose. The strategy consists of manipulating residual core flux using BESS PCS followed by a controlled switching, which reduces inrush currents during PT energization. The results show effective reduction of the inrush current from 2.31 pu to 0.16 pu for the presented case study. © 2024 IEEE.

关键词： Power transformers

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APPROACH TO PREDICT CHEMICAL EXERGY AND SYNGAS YIELD IN BRAZILIAN BIOMASS WASTE GASIFICATION USING AN ARTIFICIAL NEURAL NETWORK 37

APPROACH TO PREDICT CHEMICAL EXERGY AND SYNGAS YIELD IN BRAZ...

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37th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems, ECOS 2024

作者： Vargas, Gabriel Gomes de Oliveira Junior, Silvio Polytechnic School of University of São Paulo Mechanical Engineering Graduate Program São Paulo São Paulo Brazil

ISBN: (纸本)9798331307660

In this paper, multi-layer feed forward neural networks are used to predict the chemical exergy, hydrogen mole fraction, carbon monoxide mole fraction, and methane mole fraction during gasification of Brazilian wastes biomasses during gasification in a bubbling fluidized bed reactor. These artificial neural networks (ANNs) with different architectures are trained using the Adam back-propagation algorithm and a cross validation is also performed to ensure that the results generalize to other unseen datasets. A rigorous study is carried out on optimally choosing the number of hidden layers, number of neurons in the hidden layer and activation function in a network. Ten input and four output parameters are used to train and test various neural network architectures in single output prediction paradigms using the available experimental datasets. The model selection procedure is carried out to ascertain the best network architecture in terms of predictive accuracy. The simulation results show that the ANN based methodology is a viable alternative which can be used to predict the performance of a bubbling fluidized bed gasifier. © 2024 37th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems, ECOS 2024. All rights reserved.

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Random Number Generator for Securing Data Exchange in Smart Factory: Recent Trends and Best Practices 3

Random Number Generator for Securing Data Exchange in Smart ...

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3rd International Conference on Computer Technologies, ICCTech 2024

作者： Sama, Andi Meyliana Heryadi, Yaya Sahroni, Taufik Roni Bina Nusantara University Binus Graduate Program - Computer Science Computer Science Department Jakarta11480 Indonesia Bina Nusantara University School of Information System Information System Department Jakarta11480 Indonesia BINUS Graduate Program-Doctor of Computer Science Jakarta Computer Science Department Jakarta11530 Indonesia Bina Nusantara University BINUS Graduate Program - Master of Industrial Engineering Industrial Engineering Department Jakarta11480 Indonesia

ISBN: (纸本)9798350395419

IT/OT convergence in the form of a Cyber-Physical System (CPS) presents an opportunity to apply recent Information Technology (IT) advancements to Operational Technology (OT). The IT/OT convergence introduces cyber security threats for OT. The OT communication protocols, for example, have limited or no security capabilities for securing data exchange beyond basic authentication. The RNG (Random Number Generator) function is crucial in PLC for producing the encryption keys or the initial seed for security algorithms. The software-based PRNG (Pseudo RNG) is the most common approach for RNG in OT, instead of hardware-based RNG. This study provides a systematic literature review of the most recent evidence in digital transformation to secure data exchange in smart factories, within OT, or across OT and IT settings. It does this by looking at the PRNG on PLC and identifying the most recent trends and best practices. The findings include up-to-date data on author countries' distribution, published journals, research trends, industries, and industry types. The findings also address whether data flow is encrypted or shared in plaintext to ensure secure data transfer between IT and legacy OT environments. This paper concludes that while there is known RNG implementation in the actual embedded system in ICS, there is no evidence in the literature for using RNG in ICS networks for PLC implementation to secure data transfer with encryption. © 2024 IEEE.

关键词： Data transfer

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A Multifunctional Hydrogel with Multimodal Self-Powered Sensing Capability and Stable Direct Current Output for Outdoor Plant Monitoring Systems

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Nano-Micro Letters 2025年第4期17卷 1-24页

作者： Xinge Guo Luwei Wang Zhenyang Jin Chengkuo Lee Department of Electrical&Computer Engineering National University of Singapore4 Engineering Drive 3Singapore 117576Singapore Center for Intelligent Sensors and MEMS(CISM) National University of Singapore5 Engineering Drive 1Singapore 117608Singapore NUS Graduate School-Integrative Sciences and Engineering Program(ISEP) National University of SingaporeSingapore 119077Singapore Research Center for Sustainable Urban Farming(SUrF) National University of SingaporeSingapore 117558Singapore

Smart farming with outdoor monitoring systems is critical to address food shortages and sustainability *** systems facilitate informed decisions that enhance efficiency in broader environmental *** outdoor systems equipped with energy harvesters and self-powered sensors often struggle with fluctuating energy sources,low durability under harsh conditions,non-transparent or non-biocompatible materials,and complex ***,a multifunctional hydrogel is developed,which can fulfill all the above requirements and build selfsustainable outdoor monitoring systems solely by *** can serve as a stable energy harvester that continuously generates direct current output with an average power density of 1.9 W m^(-3)for nearly 60 days of operation in normal environments(24℃,60%RH),with an energy density of around 1.36×10^(7)J m^(-3).It also shows good self-recoverability in severe environments(45℃,30%RH)in nearly 40 days of continuous ***,this hydrogel enables noninvasive and self-powered monitoring of leaf relative water content,providing critical data on evaluating plant health,previously obtainable only through invasive or high-power consumption *** potential extends to acting as other self-powered environmental *** multifunctional hydrogel enables self-sustainable outdoor systems with scalable and low-cost production,paving the way for future agriculture.

关键词： Self-powered sensor Hydrogel Energy harvester Outdoor farming Self-sustainable IoT

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Passive design multi-objective optimization for high-performance tropical office buildings: Comparison of four different decision-making algorithms 18

Passive design multi-objective optimization for high-perform...

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18th IBPSA Conference on Building Simulation, BS 2023

作者： Rachman, Arinda Puspita Ichwania, Chalila Atthaillah Mangkuto, Rizki A. Pradipta, Justin Engineering Physics Doctorate Program Institut Teknologi Bandung Bandung Indonesia Engineering Physics Graduate Program Institut Teknologi Bandung Bandung Indonesia Department of Engineering Physics Institut Teknologi Bandung Bandung Indonesia

The implementation of passive design strategies is essential for improving building performance. However, selecting the best passive design solution can be challenging due to the multiple criteria involved. In this study, we compare four different Multi-Criteria Decision-Making (MCDM) methods: WSM, TOPSIS, VIKOR, and COPRAS, for selecting the best passive design solution. The criteria considered include energy use intensity (EUI), percentage of comfort hours (PCH), spatial daylight autonomy (sDA300/50%), and annual sunlight exposure (ASE1000,250). The results show that all MCDM methods provide the same best solution among the design alternatives generated by the optimizer if all criteria are equally important. We also found that WSM and VIKOR suggest similar top 10 alternative solutions, although there are differences in their respective ranking orders. However, if all design alternatives are considered, all evaluated methods suggest a unique ranking of solutions. The findings of this study can help designers and engineers select the most suitable MCDM method for their specific needs and achieve high-performance buildings. © 2023 *** rights reserved.

关键词： Office buildings

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Improving Control Theory Education Through Face-to-Face Implementation of a Mobile Robotics Methodology 16

Improving Control Theory Education Through Face-to-Face Impl...

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16th Brazilian Symposium on Robotics and 15th Workshop on Robotics in Education, SBR-WRE 2024

作者： Pastrana, M.A. Cuéllar Sánchez, William Humberto Mendoza-Peñaloza, Jose Santana, M.S. Muñoz, Daniel M. Department of Mechanical Engineering Mechatronics Graduate Program University of Brasilia DF Brasilia Brazil Faculty of Gama Electronics Engineering Undergraduate Program University of Brasilia DF Brasilia Brazil University of Federal District UDF DF Brasilia Brazil

ISBN: (纸本)9798350391084

Advances in information and communication technologies have significantly transformed engineering education. Virtual laboratories are increasingly adopted to enhance student interaction with control system simulations. The improved visualization and interaction capabilities of modern computers offer a more organic way to teach theoretical foundations. This paper describes the implementation of a methodology for teaching control theory that until now was entirely online in a face-to-face environment at the University of the Federal District in Brasilia, Brazil. This methodology utilizes virtual laboratories with CoppeliaSim, MATLAB, and the EVA mobile robot to teach control theory focused on single-input, single-output (SISO) systems for mobile robot tracking and obstacle avoidance applications. The results of the face-to-face implementation are compared to those of the fully online methodology, revealing that in-person teaching significantly enhances the quality of instruction. ©2024 IEEE.

关键词： MATLAB

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Development of Detection Lung Disease Stand Alone System Based on Convolutional Neural Network (CNN) 7

Development of Detection Lung Disease Stand Alone System Bas...

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7th International Conference of Computer and Informatics engineering, IC2IE 2024

作者： Liewarnata, Edgar Caesar Mariana, Yosica Tan, Sofyan Liawatimena, Suryadiputra Astuti, Winda Bina Nusantara University Binus Aso School of Engineering Automotive and Robotics Program Computer Engineering Department Jakarta11480 Indonesia Bina Nusantara University Binus Aso School of Engineering Product Design Program Industrial Engineering Department Jakarta11480 Indonesia Bina Nusantara University Binus Graduate Program - Master of Computer Science Automotive and Robotics Program Computer Engineering Department Binus Aso School of Engineering Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798331505530

Lung disease, especially Tuberculosis (TBC), placed the highest death rate in Indonesia. Tuberculosis (TB) in Indonesia is ranked second after India. Therefore, it is important to reduce or early detection of the lung disease, to prevent this disease and speed up handling. The system can recognize the disease lung identification, and the system applied as standalone system. In this work, the Convolutional Neural Network (CNN) approach for identifying diseases lung identification is proposed. The Mel Frequency Cepstral Coefficient (MFCC) applied to process the stethoscope sounds which will used as input to the CNN. The performance of the proposed system has been investigated and resulted. The accuracy of 99% and 98%, for training and testing accuracy respectively. Furthermore, the system accurately detects lung diseases identification. © 2024 IEEE.

关键词： Lung cancer

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Applicability of Electrical Resistance Method to Moisture Transfer Measurement in Paste Using Mineral Admixture 2nd

Applicability of Electrical Resistance Method to Moisture Tr...

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2nd International Conference on Sustainable Civil engineering and Architecture, ICSCEA 2021

作者： Aoki, Takahiro Ogawa, Yuko Kawai, Kenji Civil and Environmental Engineering Program Graduate School of Advanced Science and Engineering Hiroshima University 1-4-1 Kagamiyama Higashihiroshima Japan

ISBN: (纸本)9789811933028

Concrete is a porous material which has the ability to hold moisture stably inside. Since moisture is closely related to the deterioration of concrete structures, it is important to understand the moisture transfer in concrete in order to maintain the concrete structure appropriately. The electrical resistance method is one of non-destructive methods to investigate the moisture in concrete and the moisture transfer can be assessed with time by using one specimen. However, the electrical resistance may be affected by mineral admixtures in concrete. Although previous studies on the effects of mineral admixtures on the electrical resistance have been conducted, there are still many unclear points. Therefore, the purpose of this study is to assess the applicability of the electrical resistance method to moisture transfer measurement in paste containing mineral admixtures by focusing on the moisture transfer in the drying process. The moisture transfer in the hardened cement paste using fly ash and blast furnace slag with water-to-binder ratios of 0.35 and 0.55 was investigated by the electrical resistance method. Stainless steel rods of 0.9 mm in diameter were placed at an interval of 4 mm in the specimen. The calibration test was also conducted to obtain the relationship between the electrical resistivity and the internal relative humidity of the specimen. The result showed that the specific resistance of the specimen containing mineral admixtures was higher than that of the specimen without mineral admixtures. It was observed that at the drying period of 70 days, the internal relative humidity at a depth of 4 mm from the exposed surface was almost the same as the surrounding relative humidity. It is possible to know the change in the internal relative humidity distribution in the cement paste using mineral admixtures during the drying process by performing the calibration test appropriately. © 2023, The Author(s), under exclusive license to Springer Nature Singapore P

关键词： Concretes

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