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METHODOLOGY OF MODELING THE DETECTION OF LIMESCALE DEPOSITS IN SANITARY INSTALLATIONS 21

METHODOLOGY OF MODELING THE DETECTION OF LIMESCALE DEPOSITS ...

21st International Multidisciplinary Scientific Geoconference: Water Resources, Forest, Marine and Ocean Ecosystems, SGEM 202

作者： Czajkowski, Adrian Remiorz, Leszek Pawlak, Sebastian Remiorz, Eryk Szygula, Jakub Miscea.pl Engineering Sp. z o.o. Poland Department of Power Engineering and Turbomachinery Faculty of Energy and Environmental Engineering Silesian University of Technology Poland Doctoral School The Silesian University of Technology Poland Faculty of Mechanical Engineering Scientific and Didactic Laboratory of Nanotechnology and Materials Technologies Poland Department of Mining Mechanization and Robotisation Faculty of Mining Safety Engineering and Industrial Automation Silesian University of Technology Poland Department of Distributed Systems and Informatic Devices Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Poland

ISBN: (纸本)9786197603361

The article presents the issue of scale deposits in sanitary installations. Scale contributes to improper operation of sanitary devices and leads to their degradation. Scale build-up in pipes and measuring elements results in higher water consumption due to inaccurate estimation of this resource consumption. The consequence is that devices based on process automation do not work properly due to disturbances in the actual water flow. The formation of deposits also leads to economic and ecological losses, as sanitary installations elements have to be replaced, which affects the increased use of raw materials and the generation of waste. This is not in line with current trends and global objectives related to circular economy. Scale also results in increased energy consumption and reduced energy efficiency. This is due to the resistance of the flows and the increased work of the pumps. Scale has insulating properties, which results in less efficient heat transfer. In this stady, a mathematical model was developed to detect the formation of scale deposits in sanitary installations. On this basis, it is possible to control the quality status of sanitary installation components. In this way, by taking appropriate action at an early stage of the formation of deposits, it can extend the life of the installation. Having information on scale deposits, it will help avoid wasting water and lead to more accurate measurement of water flows. This is important for the proper operation of devices such as heat pumps, where their operation is automated and requires precise measurements of the energy processes taking place. Scale is a significant problem for households, and also for factories or public institutions that are exposed to hard water environments. © 2021 International Multidisciplinary Scientific Geoconference. All rights reserved.

关键词： Deposits

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Statistical Analysis of Intrinsic High-Frequency Characteristic Fluctuation of Emerging Silicon Gate-All-Around Nanosheet (NS) MOSFETs at Sub-3-nm Nodes

Statistical Analysis of Intrinsic High-Frequency Characteris...

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IEEE Electron Devices technology and Manufacturing Conference (EDTM)

作者： Sekhar Reddy Kola Yiming Li Min-Hui Chuang Kazuhiko Endo Seiji Samukawa Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program Institute of Communications Engineering Department of Electronics and Electrical Engineering Institute of Biomedical Engineering Center for mm Wave Smart Radar System and Technologies National Yang Ming Chiao Tung University Hsinchu Taiwan Institute of Fluid Science Tohoku University 2-1-1 Katahira Aoba-ku Sendai Japan National Institute of Advanced Industrial Science and Technology Tsukuba Japan

In recent years, the GAA NS Si MOSFET has been explored as a leading technology. However, the intrinsic parameters of GAA NS Si MOSFETs are affected to varying degrees by various fluctuation sources, Statistically independent and identically distributed $(iid)$ assumptions on the aforementioned random variables overestimate the variability of high-frequency characteristics, compared with considering all fluctuation factors simultaneously. Notably, the random nanosized metal grains dominates the variations of voltage gain, cut-off frequency, and 3dB frequency because the random work functions strongly alter the channel surface potential.

关键词： MOSFET Fluctuations Statistical analysis Gallium arsenide Cutoff frequency Metals Logic gates

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NTIRE 2023 Challenge on Efficient Super-Resolution: Methods and Results

NTIRE 2023 Challenge on Efficient Super-Resolution: Methods ...

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2023 IEEE/CVF Conference on computer Vision and Pattern Recognition Workshops, CVPRW 2023

作者： Li, Yawei Zhang, Yulun Timofte, Radu Van Gool, Luc Yu, Lei Li, Youwei Li, Xinpeng Jiang, Ting Wu, Qi Han, Mingyan Lin, Wenjie Jiang, Chengzhi Luo, Jinting Fan, Haoqiang Liu, Shuaicheng Wang, Yucong Cai, Minjie Li, Mingxi Zhang, Yuhang Fan, Xian-Jun Sheng, Yankai Mao, Yanyu Zhang, Nihao Wang, Qian Zheng, Mingjun Sun, Long Pan, Jinshan Dong, Jiangxin Tang, Jinhui Yang, Zhongbao Wang, Yan Pan, Erlin Cai, Qixuan Dai, Xinan Zhussip, Magauiya Kalyazin, Nikolay Vyal, Dmitry Zou, Xueyi Yan, Youliang Chung, Heaseo Zhang, Jin Yu, Gaocheng Zhang, Feng Wang, Hongbin Liao, Bohao Du, Zhibo Wu, Yu-Liang Shi, Gege Peng, Long Wang, Yang Cao, Yang Zha, Zhengjun Huang, Zhi-Kai Chen, Yi-Chung Chiang, Yuan-Chun Yang, Hao-Hsiang Chen, Wei-Ting Chang, Hua-En Chen, I-Hsiang Hsieh, Chia-Hsuan Kuo, Sy-Yen Liu, Xin Pan, Jiahao Yu, Hongyuan Yu, Weichen Ge, Lin Dong, Jiahua Zou, Yajun Wu, Zhuoyuan Han, Binnan Zhang, Xiaolin Zhang, Heng Yin, Xuanwu Zuo, Kunlong Deng, Weijian Yuan, Hongjie Lu, Zengtong Ouyang, Mingyu Ma, Wenzhuo Liu, Nian Zheng, Hanyou Zhang, Yuantong Zhang, Junxi Chen, Zhenzhong Gendy, Garas Sabor, Nabil Hou, Jingchao He, Guanghui Zhu, Yurui Wang, Xi Fu, Xueyang Zha, Zheng-Jun Yin, Daheng Liu, Mengyang Chen, Baijun Li, Ao Luo, Lei Jin, Kangjun Zhu, Ce Zhang, Xiaoming Xie, Chengxing Li, Linze Meng, Haiteng Zhang, Tianlin Li, Tianrui Zhao, Xiaole Zhang, Zhao Li, Baiang Zheng, Huan Zhao, Suiyi Gao, Yangcheng Ren, Jiahuan Hu, Kang Shi, Jingpeng Wu, Zhijian Huang, Dingjiang Zhu, Jinchen Li, Hui Xv, Qianru Liu, Tianle Weng, Shizhuang Wu, Gang Jiang, Junpeng Liu, Xianming Jiang, Junjun Zhang, Mingjian Hu, Jing Wu, Chengxu Fan, Qinrui Feng, Chengming Luo, Ziwei Hu, Shu Lyu, Siwei Wu, Xi Wang, Xin Computer Vision Lab ETH Zurich Switzerland Computer Vision Lab University of Würzburg Germany Megvii Technology China MicroBT China College of Computer Science and Electronic Engineering Hunan University China Attrsense Xian University of Posts and Telecommunications Xi'an China National Engineering Laboratory for Cyber Event Warning and Control Technologies China Nanjing University of Science and Technology China Nankai University China University of Electronic Science and Technology of China China Tianjin University China Noah's Ark Lab Huawei Technologies McMaster University Canada Espresomedia Korea Republic of AntGroup China University of Science and Technology of China China Department of Electrical Engineering National Taiwan University Taiwan Graduate Institute of Communication Engineering National Taiwan University Taiwan Graduate Institute of Electronics Engineering National Taiwan University Taiwan ServiceNow United States China Mobile Research Institute China Chongqing University of Technology China Multimedia Department Xiaomi Inc. China Institute of Automation Chinese Academy of Sciences China Shenyang Institute of Automation Chinese Academy of Sciences China School of Information and Communication Engineering Communication University of China China Smart Classroom Division Ruijie Networks Co. Ltd. China School of Remote Sensing and Information Engineering Wuhan University China Micro-Nano Electronics Department Shanghai Jiao Tong University Shanghai200240 China Electrical Engineering Department Faculty of Engineering Assiut University Assiut71516 Egypt Southeast University China University of Electronic Science and Technology of China Chengdu China Chongqing University of Posts and Telecommunications Chongqing China Information Technology Co. Ltd Hangzhou China Southwest Jiaotong University China National Space Science Center Chinese Academy of Science China Hefei University of Technology Hefei China Anhui University China Fried Ric

ISBN: (纸本)9798350302493

This paper reviews the NTIRE 2023 challenge on efficient single-image super-resolution with a focus on the proposed solutions and results. The aim of this challenge is to devise a network that reduces one or several aspects such as runtime, parameters, FLOPs, activations, memory footprint, and depth of RFDN while at least maintaining the PSNR of 29.00dB on DIV2K validation datasets. The challenge had 272 registered participants, and 35 teams made valid submissions. They gauge the state-of-the-art for efficient single-image super-resolution. © 2023 IEEE.

关键词： Optical resolving power

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Spectroscopic detection of pigments in tissues: correlation with tissue aging and cancer development

Spectroscopic detection of pigments in tissues: correlation ...

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2022 International Conference Laser Optics, ICLO 2022

作者： Oliveira, L.M. Goncalves, T.M. Botelho, A.R. Martins, I.S. Silva, H.F. Carneiro, I. Carvalho, S. Henrique, R. Tuchin, V.V. Porto Portugal Center of Innovation in Engineering and Industrial Technology Isep Porto Portugal Department of Electrical and Computer Engineering Porto University-School of Engineering Porto Portugal Department of Pathology and Cancer Biology and Epigenetics Group Portuguese Oncology Institute of Porto Porto Portugal Porto Portugal Viana do Castelo Portugal Dept. of Pathol. and Molecular Immunology Porto University-Institute of Biomedical Sciences Abel Salazar Porto Portugal Science Medical Center Saratov State University Saratov Russia Laboratory of Laser Molecular Imaging and Machine Learning National Research Tomsk State University Tomsk Russia Laboratory of Laser Diagnostics of Technical and Living Systems Institute of Precision Mechanics and Control Frc-Saratov Scientific Centre-of the Russian Academy of Sciences Saratov Russia

ISBN: (纸本)9781665466646

The direct calculation of the absorption coefficient spectra of various tissues from spectral measurements allowed to retrieve the contents of melanin and lipofuscin. In the rabbit brain cortex, 1.8 times higher melanin content is explained by the neuron degeneration process. Similar melanin and lipofuscin contents were found in the rabbit pancreas as a result of the tissue aging process. The conversion of 83 % of the melanin in the human normal kidney into lipofuscin in the cancer kidney indicates that lipofuscin can be considered a kidney cancer marker in humans. © 2022 IEEE.

关键词： Tissue

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Learning Greenhouse Climate control Policy from Monitored Data

Learning Greenhouse Climate Control Policy from Monitored Da...

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Chinese automation Congress (CAC)

作者： Xiaoxuan Zhao Haoyu Wang Xiujuan Wang Udom Lewlomphaisarl Dong Li Jing Hua Mengzhen Kang The State Key Laboratory for Management and Control of Complex Systems Chinese Academy of Sciences Institute of Automation Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China Beijing Engineering Research Center of Intelligent Systems and Technologies Beijing China National Electronics and Computer Technology Center Pathum Thani Thailand Institute of Digital Agriculture Zhejiang Academy of Agricultural Sciences Hangzhou China Qingdao AgriTech Co. Ltd. Qingdao China

The knowledge of solar greenhouse growers on environment control plays an important role in greenhouse production and management. We proposed a way to extract the control strategies from the monitored data of greenhouses by building a long short-term memory (LSTM) model. The result is verified according to the real monitored data of a solar greenhouse, which shows that the model can learn the control strategy of a ventilator in the solar greenhouse. Through monitored data and models, the knowledge of greenhouse ventilation control can be learned, and automatic control can be achieved in a greenhouse with a similar configuration.

关键词： Ventilators Green buildings Buildings Production Ventilation Data models Data mining

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QoTa-MPR: QoS-oriented and Traffic-aware Multi-path Routing Protocol for Internet of Remote Things

Research Square

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Research Square 2021年

作者： Ma, Zhongyu Liu, Yanxing Guo, Qun Dang, Xiaochao Hao, Zhanjun Tian, Ran College of Computer Science and Engineering Northwest Normal University China Gansu Internet of Things Engineering Research Center Northwest Normal University China College of Electrical and Information Engineering Lanzhou University of Technology China Key Laboratory of Gansu Advanced Control for Industrial Processes Lanzhou University of Technology China National Demonstration Center for Experimental Electrical and Control Engineering Education Lanzhou University of Technology China

Internet of Remote Things (IoRT) is widely used in both military and civilian applications. However, due to the unique characteristics, which is characterized as long-distance and high-latency, the design of the routing protocol is a great challenge of IoRT. In this paper, a QoS-oriented and traffic-aware multi-path routing protocol (QoTa-MRP) is proposed for IoRT. QoTa-MRP is composed of two parts. The first part is the link traffic-aware based muti-paths source route discovery mechanism, which is used to establish multi-paths with lower link disjoint degree. The second part is path similarity and traffic priority based multi-path selection mechanism, which is used to determine the transmission mode of the traffic flows to enhance the reliability or effectiveness of the transmission. Simultaneously, the protocol is theoretically analyzed in terms of the successful transmission rate of routing transmission data packet. Finally, the dynamic source routing, which is a very representative protocol and is usually used as the baseline comparison protocol, is revisited for the performance verification of the QoTa-MRP in IoRT. It is shown in the simulation results that there are significant superiorities of QoTa-MRP than that of DSR in terms of network throughput, packet loss rate and routing packet header overhead in IoRT. © 2021, CC BY.

关键词： Routing protocols

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A Demand Side Management Solution: Fully Automated Demand Response using OpenADR2.0b Coordinating with BEMS Pilot Project

A Demand Side Management Solution: Fully Automated Demand Re...

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Smart Grids and Energy Systems (SGES), International Conference on

作者： Kotchakorn Maneebang Kanokpol Methapatara Jasada Kudtongngam Metropolitan Electricity Authority of Thailand Bangkok Thailand Energy Forecasting and Control Laboratory National Electronics and Computer Technology Center Pathumthani Thailand

ISBN: (数字)9781728185507

ISBN: (纸本)9781665448505

Per the national Energy Policy, Demand Side Management (DSM) is one of the energy conservations that performs a function to manage electric power of demand-side resources. One of the DSM solutions is a demand response program, which is a part of Thailand Smart Grid Action Plan 2017 - 2021. Demand response program such as peak demand reduction plays a role in both the management of the electricity crisis and enhance energy security. This paper presents a pilot project for a fully automated demand response program at MEA Rat Burana District Office. The system is composed of a Building Energy Management System (BEMS) with Demand Response Client gateway and 5 energy controllers at the air conditioner by using the OpenADR2.0b protocol. Also, this concept leads to automatic or semi-automatic demand response program in the future. The result shows the total energy consumption reduction for air conditioners by 53.5%. The future works to be carried out are to implement into other MEA District Office such as Khlong Toei, Yan Nawa and Bang Khun Thian and to test with a Load Aggregator Management System (LAMS).

关键词： Demand side management Protocols Rats Load management Smart grids Power systems Security

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YOLO-Ant: A Lightweight Detector via Depthwise Separable Convolutional and Large Kernel Design for Antenna Interference Source Detection

arXiv

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arXiv 2024年

作者： Tang, Xiaoyu Chen, Xingming Cheng, Jintao Wu, Jin Fan, Rui Zhang, Chengxi Zhou, Zebo The School of Electronic and Information Engineering Faculty of Engineering South China Normal University Guangdong Foshan528225 China The School of Physics South China Normal University Guangdong Guangzhou510000 China The Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Hong Kong The College of Electronics & Information Engineering Shanghai Research Institute for Intelligent Autonomous Systems The State Key Laboratory of Intelligent Autonomous Systems Frontiers Science Center for Intelligent Autonomous Systems Tongji University Shanghai201804 China The School of Internet of Things Engineering Jiangnan University Wuxi214122 China The School of Aeronautics Astronautics University of Electronic Science and Technology of China and Aircraft swarm intelligent sensing and cooperative control Key Laboratory of Sichuan Province Chengdu610097 China The National Laboratory on Adaptive Optics Chengdu610209 China

In the era of 5G communication, removing interference sources that affect communication is a resource-intensive task. The rapid development of computer vision has enabled unmanned aerial vehicles to perform various high-altitude detection tasks. Because the field of object detection for antenna interference sources has not been fully explored, this industry lacks dedicated learning samples and detection models for this specific task. In this article, an antenna dataset is created to address important antenna interference source detection issues and serves as the basis for subsequent research. We introduce YOLO-Ant, a lightweight CNN and transformer hybrid detector specifically designed for antenna interference source detection. Specifically, we initially formulated a lightweight design for the network depth and width, ensuring that subsequent investigations were conducted within a lightweight framework. Then, we propose a DSLK-Block module based on depthwise separable convolution and large convolution kernels to enhance the network’s feature extraction ability, effectively improving small object detection. To address challenges such as complex backgrounds and large interclass differences in antenna detection, we construct DSLKVit-Block, a powerful feature extraction module that combines DSLK-Block and transformer structures. Considering both its lightweight design and accuracy, our method not only achieves optimal performance on the antenna dataset but also yields competitive results on public datasets. Copyright © 2024, The Authors. All rights reserved.

关键词： Antennas

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Steering post-C-C coupling selectivity enables high efficiency electroreduction of carbon dioxide to multi-carbon alcohols (vol 1, pg 421, 2018)

引用

NATURE CATALYSIS 2022年第6期5卷 578-579页

作者： Zhuang, Tao-Tao Liang, Zhi-Qin Seifitokaldani, Ali Li, Yi De Luna, Phil Burdyny, Thomas Che, Fanglin Meng, Fei Min, Yimeng Quintero-Bermudez, Rafael Dinh, Cao Thang Pang, Yuanjie Zhong, Miao Zhang, Bo Li, Jun Chen, Pei-Ning Zheng, Xue-Li Liang, Hongyan Ge, Wen-Na Ye, Bang-Jiao Sinton, David Yu, Shu-Hong Sargent, Edward H. Department of Electrical and Computer Engineering University of Toronto Toronto Ontario Canada Division of Nanomaterials & Chemistry Hefei National Laboratory for Physical Sciences at Microscale Collaborative Innovation Center of Suzhou Nano Science and Technology CAS Center for Excellence in Nanoscience Department of Chemistry University of Science and Technology of China Hefei Anhui China State Key Laboratory of Molecular Engineering of Polymers Department of Macromolecular Science Fudan University Shanghai China Department of Materials Science and Engineering University of Toronto Toronto Ontario Canada Department of Mechanical and Industrial Engineering University of Toronto Toronto Ontario Canada State Key Laboratory of Particle Detection and Electronics University of Science and Technology of China Hefei Anhui China

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Adaptive Sliding Mode-based Observer and Current controller for Torque Balance control Strategy of Coaxial BLDC Motor

Adaptive Sliding Mode-based Observer and Current Controller ...

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International Conference on control, automation and Information Sciences (ICCAIS)

作者： Lam Cuong Quoc Thai Van Tu Duong Tan Tien Nguyen Thanh Luan Bui Trong Trung Nguyen Huy Hung Nguyen Faculty of Mechanical Engineering National Key Laboratory of Digital Control and System Engineering (DCSELab) Ho Chi Minh City University of Technology (HCMUT) 268 Ly Thuong Ki et Street District 10 Ho Chi Minh City Vietnam Linh Trung Ward Thu Due City Vietnam National University Ho Chi Minh City Ho Chi Minh City Vietnam Industrial Maintenance Training Center Ho Chi Minh City University of Technology (HCMUT) 268 Ly Thuong Kiet Street District 10 Ho Chi Minh City Vietnam Ho Chi Minh City University of Transport Vietnam Faculty of Electronics and Telecommunication Saigon University

In underwater vehicle applications, coaxial brushless direct current (BLDC) motors, serving as thrust actuators, present significant challenges. These challenges encompass external disturbances induced by environmental factors and internal perturbations arising from rapid temperature and electrical parameter fluctuations. To address these issues, this study introduces an Adaptive Sliding Mode control (ASMC) algorithm, employing field-oriented control techniques, and incorporates a Sliding Mode Observer (SMO) to mitigate the aforementioned disturbances. Additionally, a three-level inverter structure, accompanied by a Space Vector Pulse Width Modulation (SVPWM) algorithm tailored for high-power applications to minimize harmonic distortion, has been implemented. Subsequently, a torque balance control strategy is developed, based on the master-slave speed tracking method, incorporating all these control structures and algorithms. The reliability and effectiveness of the proposed controller are substantiated through comprehensive simulation analyses conducted using Matlab/Simulink.

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