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Energy Storage Power control Strategy Based on Adaptive Parameter Virtual Synchronous Generator 7th

Energy Storage Power Control Strategy Based on Adaptive Para...

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7th international conference on Life System Modeling and Simulation, LSMS 2021, and 7th international conference on Intelligent computing for Sustainable Energy and Environment, ICSEE 2021

作者： Gao, Wengen Wu, Minghui Wei, Lisheng Lu, Huacai Tang, Ye College of Electrical Engineering Anhui Polytechnic University Wuhu241000 China Key Laboratory of Advanced Perception and Intelligent Control of High-End Equipment Chinese Ministry of Education Wuhu241000 China AnHui Key Laboratory of Detection Technology and Energy Saving Devices Wuhu241000 China

ISBN: (纸本)9789811672095

According to the electrical model and mechanical model of synchronous generator, the control model of virtual synchronous generator is deduced, and the relationship between control parameters and virtual synchronous generator is analyzed. Based on the power electronics technology, the energy storage power control strategy is given, including the virtual synchronous generator power control loop and the voltage and current double loop control strategy. Combined with the actual operating conditions of energy storage power conversion system, an adaptive adjustment method of virtual synchronous generator parameters is proposed, and the simulation model is built, and the effectiveness of the adaptive parameter control strategy of virtual synchronous generator is verified by simulation analysis. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Synchronous generators

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Skin cancer detection using machine learning techniques with ABCD features

Skin cancer detection using machine learning techniques with...

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electrical Power engineering, Communication and computing Technology(ODICON), Odisha international conference on

作者： Jaya Bijaya Arjun Das Debahuti Mishra Abhishek Das Mihir Narayan Mohanty Archana Sarangi Department of Computer Science and Engineering ITER Siksha ‘O’ Anusandhan (Deemed to be University) Bhubaneswar Odisha India School of Information Technology SRM University Sikkim Gangtok Sikkim India Department of Electronics and Communication Engineering ITER Siksha ‘O’ Anusandhan (Deemed to be University) Bhubaneswar Odisha India

ISBN: (纸本)9781665478403

Due to their identical look and lack of distinguishable color variation, detecting skin cancer from dermoscopic images is a difficult process. A better combination of pre-processing and detection methods can make this task comparatively easier and more accurate. For automatic and accurate detection of skin cancer, we have proposed a set of few pre-processing steps like segmentation of skin lesions from background images followed by the ABCD feature extraction for better training of machine learning models like Support Vector Machine (SVM), K-Nearest Neighbor (KNN), and Random Forest (RF). For this purpose, we have used ISIC 2020 dataset for verification. From this experiment, it is observed that SVM with RBF kernel provided a better detection score of 93.51, whereas 91 %, and 90.67% scores were observed using KNN and RF respectively.

关键词： Support vector machines Radio frequency Training Image segmentation Computational modeling Feature extraction Skin

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Impact of Parameters for the In-situ Measurement of the Electric Field Strength of the SSB Signal in a 5G NR System Using the Frequency-Selective Method in Zero-Span Mode

Impact of Parameters for the In-situ Measurement of the Elec...

引用

international conference on Smart Systems and Technologies (SST)

作者： Vanja Mandrić Slavko Rupčić Bogdan Pavković Josip Ilakovac Department of Communication Faculty of Electrical Engineering Computer Science and Information Technology Osijek Osijek Croatia Department of Computing and Control Engineering Faculty of Technical Sciences University of Novi Sad Novi Sad Serbia Faculty of Electrical Engineering Computer Science and Information Technology Osijek Osijek Croatia

ISBN: (数字)9798350386394

ISBN: (纸本)9798350386400

Measuring 5G systems is a major challenge for measurement engineers, who need to be aware of all the limitations of the new generation The parameters of the frequency-selective measurement system (spectrum analyzer - ROHDE & SCHWARZ FSH8) were investigated in the measurement of 5G NR SSB signals (3.4 – 3.8 GHz). The focus was on the setting parameters which, according to the literature, have an influence on the measurement: RBW, VBW, SWEEP TIME and the duration of the measurement. All measurements were carried out in zero-span mode. In the second part of the measurement, these SSB synchronization signal measurement results were compared with the 5G signal measurement results at the same location using the NARDA SRM-3006 device equipped with a decoder for the 5G NR system (FR1) to determine the optimal method for measuring these signals with a spectrum analyzer (SA).The measurement results show that the resolution bandwidth (RBW) has the largest variation in the measured electric field (EF) strength values of the SSB 5G NR signal of 17.20 dB (MH/RMS) and 17.70 (RMS/AGV10). It is therefore necessary to pay particular attention to the setting of this measurement parameter. In addition, the video resolution (VBW) shows a significantly lower field strength variation of 2.50 dB, but also the same deviation from the reference value of 2.50 dB (RMS/AGV10). Other analyzed parameters have a negligible influence on the measurement of the EF *** post-processing was performed in the work to determine the final (maximum) value of the EF strength at the points of assumed highest exposure, which is used to assess the impact and compliance with the permissible values according to the relevant standards.

关键词： Time-frequency analysis 5G mobile communication Measurement uncertainty Electric variables measurement Amplitude modulation Time measurement Frequency measurement Decoding Electric fields Signal resolution

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Active Vibration control for Building Structures based on 8Synthesis Problem 17

Active Vibration Control for Building Structures based on 8S...

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17th international conference on electrical engineering, computing science and automatic control, CCE 2020

作者： Rodriguez-Torres, Andres Morales-Valdez, Jesus Yu, Wen CINVESTAV-IPN Dep. of Automatic Control Mexico city Mexico Catedras CONACYT-CINVESTAV Ipn Dep. of Automatic Control Mexico city Mexico

ISBN: (纸本)9781728189871

This paper presents the development of an 8 controller synthesis designed based on the infinity norm and the frequency spectrum of the disturbance to achieve the reduction of vibrations in buildings structures subjected to seismic excitation. A feature of the proposed controller is that it can be designed around an experimental test. Through verifying Doyle's assumptions in control 8 theory ensure the stability of the closed-loop system. The mathematical model is introduced by means of mechanical elements and generalized through modal analysis. The effectiveness of the proposed controller is illustrated employing simulation results of a reduced scale two-stories building structure and the proposed algorithm is tested against the 1985's Mexico city earthquake data. © 2020 IEEE.

关键词： controllers

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Neuroplasticity Changes to Configure Human Talent

Neuroplasticity Changes to Configure Human Talent

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international conference on Circuit, Power and computing Technologies (ICCPCT)

作者： Rohan Parija Nongmeikapam Thoiba Singh Department of Computer Science Engineering Chandigarh University Punjab India

Neuroplasticity is the capability of the brain to adapt its structure and function to new environments. It is essential for learning, memory, and brain repair after brain damage. Neuroplasticity can also be utilized to assess human ability or potential for excellence in a particular discipline. One method is to assess the brain activity of people who excel at a given topic, such as chess, math, or music composition. Researchers can uncover the neural markers of experience and talent by comparing their brain patterns with those of average performers or beginners. Previously, researchers discovered that London taxi drivers have larger hippocampi, a part of the brain associated with spatial memory and movement, than control subjects. This was attributed to their extensive training and experience in navigating the complex city streets. Neuroplasticity can also be used to enhance human talent by providing optimal conditions for learning and performance. This may include electrical or magnetic pulse stimulation of the brain, the use of neurofeedback or biofeedback techniques, or the application of cognitive strategies such as purposeful practice, spaced repetition, and interleaving. These techniques try to change the brain's activity and connectivity in ways that aid in skill learning and retention. Transcranial direct current stimulation (tDCS), a non-invasive brain stimulation method that administers mild electrical currents to the scalp, has been shown in prior research to improve mathematical abilities in healthy people. Finally, neuroplasticity can be utilized to discover human talent by measuring brain activity in experts and learners, as well as to improve human talent by providing optimal learning and performance settings. Neuroplasticity provides a viable path for understanding and increasing human potential across a wide range of fields.

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HeteroSys: Heterogeneous and Collaborative Sensing in the Wild

HeteroSys: Heterogeneous and Collaborative Sensing in the Wi...

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international conference on Smart computing (SMARTCOMP)

作者： Indrajeet Ghosh Adam Goldstein Avijoy Chakma Jade Freeman Timothy Gregory Niranjan Suri Sreenivasan Ramasamy Ramamurthy Nirmalya Roy Department of Information Systems University of Maryland Baltimore County United States Department of Electrical Engineering and Computer Science UC Berkeley United States DEVCOM Army Research Lab Department of Computer Science Bowie State University United States

Advances in Internet-of-Things, artificial intelligence, and ubiquitous computing technologies have contributed to building the next generation of context-aware heterogeneous systems with robust interoperability to control and monitor the environmental variables of smart environments. Motivated by this, we propose HeteroSys, an end-to-end multi-functional smart IoT-based system prototype for heterogeneous and collaborative sensing in a smart IoT-based environment. A unique characteristic of HeteroSys is that it relies on Home Assistant (HA) to collate heterogeneous sensors (e.g., passive infrared sensors (PIR), reed (door) switches, object tags, wearable wrist-mounted, water leak sensors, and internet protocol cameras), and uses a variety of networking protocols such as Zigbee open standard for mesh networking, WiFi, and Bluetooth Low Energy (BLE) for communication. The reliance on HA (and its broad community support) makes HeteroSys ideal for various applications such as object detection, human activity recognition and behavior patterns. We articulated the development phase, integration, testing challenges and evaluation of the HeteroSys. We conducted an extensive 24-hour longitudinal data collection from 5 participants performing 6 activities by deploying in an indoor home environment. Our assessment of the acquired dataset reveals that the representations learned using deep learning architecture aid in improving the detection of activities to 83.1% accuracy.

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Research on Virtual Power Plants Participating in Ancillary Service Market

Research on Virtual Power Plants Participating in Ancillary ...

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electrical engineering and control science (IC2ECS), international conference on

作者： Guohui Lan Zitao Zhang Minxing Guo Li Lan Ran Lyu Su Wang Institute of Economics and Technology State Grid Shanghai Electric Power Company Shanghai China School of Electrical Engineering Southeast University Nanjing China

Under the “Double Carbon” strategy, the speed of new energy installation and grid connection has been continuously improved. In order to better absorb new energy power generation and ensure the safe and stable operation of the power system, it is urgent to provide ancillary service resources such as frequency regulation and peak shaving. The virtual power plant aggregates the distributed energy scattered in the power grid through advanced communication, computing, dispatching, market and other means, making it a “power generation system” that can be uniformly dispatched, and then follow the dispatching instructions and participate in the ancillary service market. Firstly, the relevant structure and development of virtual power plant is introduced. Secondly, the relevant types of virtual power plants participating in the ancillary service market are analyzed. Thirdly, the actual situation of virtual power plants participating in ancillary service markets for frequency regulation and peak shaving is compared and analyzed with reference to the market access conditions, compensation mechanism and allocation mechanism, which lays a theoretical foundation for different provinces to further improve the mechanism of virtual power plants participating in ancillary service markets. At last, according to China’s national conditions, suggestions on the construction of market mechanism for virtual power plants to participate in ancillary services are proposed.

关键词： Frequency modulation Urban areas Virtual power plants Dispatching Regulation Power grids Telecommunication computing

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Do We Run Large-scale Multi-Robot Systems on the Edge? More Evidence for Two-Phase Performance in System Size Scaling

Do We Run Large-scale Multi-Robot Systems on the Edge? More ...

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IEEE international conference on Robotics and Automation (ICRA)

作者： Jonas Kuckling Robin Luckey Viktor Avrutin Andrew Vardy Andreagiovanni Reina Heiko Hamann Department of Computer and Information Science University of Konstanz Konstanz Germany Centre for the Advanced Study of Collective Behaviour University of Konstanz Germany Institute of Computer Engineering University of Lübeck Lübeck Germany Institute for Systems Theory and Automatic Control University of Stuttgart Stuttgart Germany Department of Computer Science and the Department of Electrical and Computer Engineering Memorial University of Newfoundland St. John’s Canada IRIDIA Université Libre de Bruxelles Brussels Belgium

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

With increasing numbers of mobile robots arriving in real-world applications, more robots coexist in the same space, interact, and possibly collaborate. Methods to provide such systems with system size scalability are known, for example, from swarm robotics. Example strategies are self-organizing behavior, a strict decentralized approach, and limiting the robot-robot communication. Despite applying such strategies, any multi-robot system breaks above a certain critical system size (i.e., number of robots) as too many robots share a resource (e.g., space, communication channel). We provide additional evidence based on simulations, that at these critical system sizes, the system performance separates into two phases: nearly optimal and minimal performance. We speculate that in real-world applications that are configured for optimal system size, the supposedly high-performing system may actually live on borrowed time as it is on a transient to breakdown. We provide two modeling options (based on queueing theory and a population model) that may help to support this reasoning.

关键词： Limiting System performance Space communications Scalability Sociology Swarm robotics Mobile robots

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Holistic Recommendation System Framework for Health Care Programs 1

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3rd international conference on Sustainable Advanced computing, ICSAC 2021

作者： Navin, K. Krishnan, M. B. Mukesh SRM Insitute of Science Technology Chennai Kattankulathur India

ISBN: (数字)9789811690129

ISBN: (纸本)9789811690112

Government health care programs for disease surveillance, control, and prevention adopt a strategized technique in collecting information from various sources, monitor the trend of disease outbreak, initiate actions, and detect the response for further course of action. The main components for implementing such programs are integration and decentralization of surveillance activities at the zonal, and subzonal levels, developing and deploying human resources involving field workers to experts, strengthening public health lab facilities, and most importantly embracing digital information communications technology (ICT), the key component in binding all other components in bringing the effective implementation of the program. The proposed work explains the adoption of ICT through a holistic framework depicting the strategy and techniques in implementing the program. It discusses the digitalized strategy in data collection as well as data compilation, data analysis through integrated decision support modules, and proper presentation and dissemination of information data. The key element of the framework involves adopting various recommendation systems techniques in the analysis of data for information filtering, decision support, and data dissemination at various stages of handling the data. It suggests the selection of different recommendation techniques to address various needs such as predicting the disease dynamics and provide decision support in predicting likely hood of the next outbreak of the disease, rate of speeding, demographic details of spread, etc. The framework proposes a strategy to use smartphone-based mobile intervention to support the program and also proposes an API-based data exchange architectural style for data gathering and dissemination connected to various sources and endpoints. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： mHealth

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Autonomous robotic re-alignment for face-to-face underwater human-robot interaction*

Autonomous robotic re-alignment for face-to-face underwater ...

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IEEE international conference on Robotics and Automation (ICRA)

作者： Demetrious T. Kutzke Ashwin Wariar Junaed Sattar Department of Computer Science & Engineering Minnesota Robotics Institute University of Minnesota–Twin Cities Minneapolis MN USA

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

The use of autonomous underwater vehicles (AUVs) to accomplish traditionally challenging and dangerous tasks has proliferated thanks to advances in sensing, navigation, manipulation, and on-board computing technologies. Utilizing AUVs in underwater human-robot interaction (UHRI) has witnessed comparatively smaller levels of growth due to limitations in bi-directional communication and significant technical hurdles to bridge the gap between analogies with terrestrial interaction strategies and those that are possible in the underwater domain. A necessary component to support UHRI is establishing a system for safe robotic-diver approach to establish face-to-face communication that considers nonstandard human body pose. In this work, we introduce a stereo vision system for enhancing UHRI that utilizes threedimensional reconstruction from stereo image pairs and machine learning for localizing human joint estimates. We then establish a convention for a coordinate system that encodes the direction the human is facing with respect to the camera coordinate frame. This allows automatic setpoint computation that preserves human body scale and can be used as input to an image-based visual servo control scheme. We show that our setpoint computations tend to agree both quantitatively and qualitatively with experimental setpoint baselines. The methodology introduced shows promise for enhancing UHRI by improving robotic perception of human orientation underwater.

关键词： Visualization Navigation Robot kinematics Human-robot interaction Machine learning Robot sensing systems Stereo vision

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