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18th International Conference on AC and dC Power Transmission, ACdC 2022

作者： Huang, Zhida Wu, Wencong Cai, Haiqing Huang, Libin State Key Laboratory of HVDC Electric Power Research Institute CSG Guangzhou510663 China National Energy Power Grid Technology R&D Centre Guangzhou510663 China Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangzhou510663 China CSG Key Laboratory for Power System Simulation Guangzhou510663 China

ISBN: (数字)9781839537615

ISBN: (纸本)9781839537615

At present, the power grid is carrying out the practical work of smart substation On-line monitoring and control function module of relay protection. Compared with traditional substations, the new-generation assurance system has been greatly improved in 7 functional modules, including fault archiving, special maintenance information patrol, fixed value checking, configuration checking, substation testing, intelligent alarm, and master station modeling. It can fully adapt to the functional requirements of smart substations and traditional substations. This paper analyzes the monitoring and analysis requirements of the assurance system based on the equipment configuration of the station control layer of the new generation of intelligent substations, and proposes a complete design scheme of seven functional modules from three aspects: functional requirements, implementation logic, and performance design. The practical application results in the power grid simulation laboratory show that the On-line monitoring and control function module of relay protection based on the guarantee system can be compatible with the traditional 103 substations and 61850 substations and achieve the expected goals and performance requirements. It has the value of promotion and application. © ACdC 2022. All rights reserved.

关键词： relay protection

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Automatic Liver Tumor Segmentation in CT Modalities Using MAT-ACM

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computer systems Science & Engineering 2022年第12期43卷 1057-1068页

作者： S.Priyadarsini Carlos Andrés Tavera romero Abolfazl Mehbodniya P.Vidya Sagar Sudhakar Sengan Department of Computer Science and Engineering P.S.R.Engineering CollegeSivakasiTamil Nadu626123India COMBA R&D Laboratory Faculty of EngineeringUniversidad Santiago de CaliCali76001Colombia Department of Electronics and Communications Engineering Kuwait College of Science and TechnologyKuwait Department of Computer Science and Engineering Koneru Lakshmaiah Education FoundationVaddeswaramAndhra Pradesh522502India Department of Computer Science and Engineering PSN College of Engineering and TechnologyTirunelveliTamil Nadu627152India

In the recent days, the segmentation of Liver Tumor (LT) has beendemanding and challenging. The process of segmenting the liver and accuratelyspotting the tumor is demanding due to the diversity of shape, texture, and intensity of the liver image. The intensity similarities of the neighboring organs of theliver create difficulties during liver segmentation. The manual segmentation doesnot provide an accurate segmentation because the results provided by differentmedical experts can vary. Also, this manual technique requires a large numberof image slices and time for segmentation. To solve these issues, the Fully Automatic Segmentation (FAS) technique is proposed. In this proposed Multi-AngleTexture Active Contour Model (MAT-ACM) method, the input Computed Tomography (CT) image is preprocessed by Contrast Enhancement (CE) with Non-Linear Mapping Technique (NLMT), in which the liver is differentiated from itsneighbouring soft tissues with related strength. Then, the filtered images are givenas the input to Adaptive Edge Modeling (AEM) with Canny Edge detection(CEd) technique, which segments the Liver region (Lr) from the given CTimages. An AEM with a CEd model is implemented, which increases the convergence speed of the iterative process for decreasing the Volumetric Overlap Error(VOE) is 6.92% rates when compared with the traditional Segmentation Techniques (ST). Finally, the Liver Tumor Segmentation (LTS) is developed by applyingthe MAT-ACM, which accurately segments the Lr from the segmented Lrs. Theevaluation of the proposed method is compared with the existing LTS methodsusing various performance measures to prove the superiority of the proposedMAT-ACM method.

关键词： Computed tomography contrast enhancement adaptive edge modeling multi-angle texture active contour liver tumor segmentation

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Mixed Electric Vehicles and UAVs for Last-Mile delivery Under Ecological Objective

Mixed Electric Vehicles and UAVs for Last-Mile Delivery Unde...

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International Conference on Intelligent Computing in data Sciences (ICdS)

作者： Bouhia Hanaa Jamal Benhra R&D engineer intern ECC Computer science engineer ESITH Casablanca Morocco LARILE Laboratory OSIL ENSEM Hassan II University of Casablanca Casablanca Morocco

ISBN: (数字)9798350351200

ISBN: (纸本)9798350351217

The article introduces the Electric Vehicle routing Problem with drones (EVrPd), an innovative approach to optimizing last-mile delivery by integrating Electric Vehicles (EVs) with drones. The main goal is to minimize energy consumption and CO2 emissions while ensuring efficient delivery operations. This solution utilizes a mixed fleet of EVs as mother ships and drones for the final parcel delivery. EVs and drones are both capable of delivering parcels, with drones deployed for smaller and more urgent deliveries. The system focuses on optimizing the payload distribution to maximize energy efficiency and drone autonomy. drones are replenished on the rooftops of EVs using IoT technology. To solve the routing problem, this solution employs bio-inspired algorithms such as Ant Colony Optimization (ACO) for EVs and Particle Swarm Optimization (PSO) for drones. This approach maximizes energy efficiency and drone autonomy while ensuring efficient parcel distribution. By integrating these innovative techniques, EVrPd offers promising prospects for a more sustainable and efficient urban logistics system.

关键词： Energy consumption Electric vehicles routing Energy efficiency Particle swarm optimization Marine vehicles Optimization drones Logistics Payloads

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A Networked Method Applied to Sensitivity Analysis of a VSG controlled BESS system 5

A Networked Method Applied to Sensitivity Analysis of a VSG ...

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5th International Conference on Power Engineering, ICPE 2024

作者： Sun, Zhiyuan Luo, Chao Zheng, Kun Zhu, Yihua Yu, Jiawei Guangxi Power Grid Electric Power Research Institute China S. Power Grid Guangxi Key Laboratory of Intelligent Control and Maintenance of Power Equipment Nanning China Electric Power Research Institute China Southern Power Grid State Key Laboratory of Hvdc Guang zhou China National Energy Power Grid Technology R&d Centre Guang zhou China Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guang zhou China

ISBN: (纸本)9798331531140

The grid-forming battery energy storage system (BESS) plays important role in constructing new energy system. This paper presents a frequency domain modal-based stability analysis of virtual synchronous generator (VSG) controlled BESS. Both ac and dc side interactive dynamics of the grid-tied inverter system are considered, by establishing a hybrid ac/dc impedance network. Then, the frequency domain modal analysis (FMA) method for networked converter systems is applied to the BESS system, covering the eigen-sensitivity from the node level to parameter level. Using this method, key parameters that influence the BESS system's weakly/negative damping modes most can be better analyzed and identified. The analysis results are validated via the time-domain simulations. © 2024 IEEE.

关键词： Frequency domain analysis

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Adaptive Identification of Power system Operational States Based on Spatio-Temporal dynamic Graph Neural Networks 4

Adaptive Identification of Power System Operational States B...

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4th IEEE International Conference on Electronic Technology, Communication and Information, ICETCI 2024

作者： Zhang, Qingqing Ma, Qinfeng Liu, Mingshun Zhang, Jie Zhu, Yihua Liang, Zhuohang An, Su Pu, Qingxin dai, Jiang Power Dispatching and Control Center of Guizhou Power Grid Co. Ltd. Guizhou China China Southern Power Grid State Key Laboratory of HVDC Electric Power Research Institute Guangzhou510663 China National Energy Power Grid Technology R&D Centre Guangzhou510663 China Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangzhou510663 China

ISBN: (纸本)9798350361643

The state identification of the operational status of power systems plays a crucial role in ensuring the safety, efficiency, and reliable operation of power systems, forming the foundation for the management and control of power system operations. In the practical operation of power systems, the duration of fault states is short, while the system remains in a safe and stable state for a significantly longer period, leading to an imbalance in the training samples available. This imbalance can cause traditional machine learning classification algorithms to favor the majority categories of power system operational states, resulting in inaccurate evaluation metrics and reduced model generalization capability. To address this issue, this paper introduces a spatiotemporal dynamic graph neural network model for the identification of power system operational states. By incorporating class cost coefficients, focal loss, and cross-entropy in a joint loss function, the model adaptively focuses on the less represented operational state categories during training, improving classification accuracy on imbalanced and challenging samples. Moreover, the integration of temporal information and spatial topology information within the graph neural network enhances the model's robustness and generalization ability in state identification. Experimental results on the standard IEEE 68-bus system demonstrate that, compared to traditional machine learning methods, the proposed joint loss with the spatiotemporal dynamic graph neural network model achieves higher accuracy in the identification of power system operational states, significantly improving classification performance on imbalanced samples with a 4.8% increase in F1-score, reaching a peak F1-score of 98.6%. © 2024 IEEE.

关键词： Graph neural networks

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Contrastive Graph representations for Logical Formulas Embedding (Extended Abstract)

Contrastive Graph Representations for Logical Formulas Embed...

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International Conference on data Engineering

作者： Qika Lin Jun Liu Lingling Zhang Yudai Pan Xin Hu Fangzhi Xu Hongwei Zeng School of Computer Science and Technology Xi'an Jiaotong University Shaanxi Province Key Laboratory of Satellite and Terrestrial Network Tech. R&D Xi'an Jiaotong University

ISBN: (数字)9798350317152

ISBN: (纸本)9798350317169

Embedding symbolic logical formulas into a low-dimensional continuous space provides an effective way for the Neural-Symbolic system. However, current studies are all constrained by the syntactic structure modeling and fail to preserve intrinsic semantics. To this end, we propose a novel model of Contrastive Graph representations (ConGr) for logical formulas embedding. Firstly, it introduces a densely connected graph convolutional network (GCN) with an attention mechanism to process syntax parsing graphs of formulas. Secondly, the contrastive instances for each anchor formula are generated by the transformation under the guidance of logical properties. Two types of contrast, global-local and global-global, are carried out to refine formula embeddings with semantic information. Extensive experiments demonstrate that ConGr obtains superior performance against state-of-the-art baselines.

关键词： Attention mechanisms Graph convolutional networks Semantics Syntactics data engineering

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Synergy recovery of Aluminum-Phosphorus from Incineration Sewage Sludge Ash by Acid and Alkaline Treatment

SSRN

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SSrN 2024年

作者： Shi, Chen Zhao, Bohan Guo, Xiaoyuan Wang, Xiangyang Hao, Xiaodi Sino-Dutch R&D Centre for Future Wastewater Treatment Technologies Key Laboratory of Urban Stormwater System and Water Environment Beijing University of Civil Engineering and Architecture Beijing100044 China

This study first focused on the wet chemical acidic leaching method from the laboratory scale, explored the potential of recovering phosphorus and aluminum from incineration ash, and studied the kinetic characteristics of phosphate and aluminum phosphate extracted by different acids, so as to select the appropriate acidic leaching extraction process. It was found that the extraction efficiency of phosphorus by oxalic acid was generally higher than that by inorganic acid. At the same time, when the concentration of leaching agent increased from 0.25 M to 1 M, the concentration of phosphorus leaching from sludge ash increased to 3.84%;when nitric acid is used as leaching agent, the leaching rate of aluminum is the highest. Then, based on the aluminum-rich ash, the above four leaching agents were used and the pH (NaOH) was adjusted to explore the kinetics of recovering Al-P. It was found that the recovery rates of phosphorus in ash were 99.84%, 87.99%, and 94.78%, respectively, and the recovery rate of Al can reach 100%. All these results show the recovery potential of aluminum-rich ash and expands the application route of ash phosphorus recovery to a certain extent. © 2024, The Authors. All rights reserved.

关键词： Extraction

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Autonomous vehicle navigation using high-definition maps through CArLA-rOS simulator bridge

Autonomous vehicle navigation using high-definition maps thr...

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2022 International Symposium on Intelligent Unmanned systems and Artificial Intelligence, SIUSAI 2022

作者： Fatima, H. Sundus Abbas, Ammar N. Bawany, Faraz Zia, Huma Yusuf, Syed Adnan Khurram, Muhammad Computer and Information System Smart City Lab NCAI NED University Pakistan Abu Dhabi University Dubai United Arab Emirates R&D Department Intelexica Pvt Ltd SouthamptonSO152RZ United Kingdom

Autonomous vehicles (AV) have garnered significant interest in recent years due to its potential for controlling thousands of accidents that happen yearly due to human error. However, AV bring with it very complex and sophisticated requirements and challenges related to extensive testing of the algorithms and hardware in the physical world. The evolution of automotive simulation tools provides an opportunity to fully test and validate AV architectures without the risk of creating hazardous situations in real world. This research demonstrates the application of Hd (High definition) maps in autonomous vehicle navigation using rOS interface integrated with the CArLA (CAr Learning to Act) simulator. The sensor data includes Light detection and ranging (LidAr), rGB-depth (rGB-d), and vehicle odometry. Hd maps play an important role in robustness of the autonomous systems where due to sensor obstruction or weather conditions the vehicle is unable to perceive the information ahead. It also aids the vehicle to sense its environment even outside from the sensor's field of view. The research is divided into the three fundamental concepts of Simultaneous Localization and Mapping (SLAM) approach that is, (i) mapping, (ii) localization, and (iii) navigation. Two rOS tools are used for mapping, (a) OctoMap mapping, and (ii) real-Time Appearance-Based Mapping (rTAB-Map). We demonstrate the effectiveness of localization using rTAB-Map and compare actual path, position and orientation to their estimated equivalents. Our results show acceptable error in XY axes and exemplifies the error accumulated in Z axis. © Published under licence by IOP Publishing Ltd.

关键词： Mapping

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Coating Seeds with Alginate-Like Exopolysaccharides Extracted from Conventional Activated Sludge Affects the Growth Physiology of Wheat Under Gradient Salt Stress

SSRN

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SSrN 2024年

作者： Shi, Chen Zhang, Lin Wang, Xiang-Yang Zhao, Bo-Han Cheng, Ming Yuan, Shi-Chao Hao, Li-Ting Hao, Xiao-di Sino-Dutch R&D Centre for Future Wastewater Treatment Technologies Key Laboratory of Urban Stormwater System and Water Environment Beijing University of Civil Engineering and Architecture Beijing100044 China

With the continuous innovations in wastewater treatment technology, the resource use of excess sludge has become the focus of research. Alginate-like exopolysaccharides (ALE) obtained from aerobic granular sludge and conventional activated sludge (CAS) have many practical applications, including waterproofing, adsorption, flame retardancy, slow-release properties, and seed coating. In this study, ALE extracted from the CAS was used as a new seed coating, which was uniformly sprayed onto the surface of wheat seeds. ALE was most effective in resisting salt stress in wheat seedlings at a NaCl concentration of 125 mmol/L. Germination percentage, plant height, K+/Na+ ratio, soluble sugar and soluble protein content of ALE-coated seeds increased by 13.33%, 46.32%, 37.25%, 8.89%, and 36.22%, respectively, compared with those of wheat seeds without ALE coating. Inhibition of O2·- product activity and malondialdehyde content were reduced by 38.62% and 48.00%, respectively. Therefore, the ALE coating had a mitigating effect on wheat seed germination and seedling growth in salt-stressed environments, and this application would be beneficial to the use of saline soil resources and the improvement of ecosystems in coastal areas. © 2024, The Authors. All rights reserved.

关键词： Seed

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Modified Kelvin-Voigt fractional derivative model for viscoelasticity measurement in optical coherence elastography

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Chinese Optics Letters 2025年第1期23卷 93-101页

作者： Chenming Yang Zhongliang Li Nan Nan Teng Liu Yaoli Luo Xiangzhao Wang Advanced Light Source and System R&D Center Department of Advanced Optical and Microelectronic EquipmentShanghai Institute of Optics and Fine MechanicsChinese Academy of SciencesShanghai 201800China Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of SciencesBeijing 100049China School of Optical-Electrical and Computer Engineering University of Shanghai for Science and TechnologyShanghai 200093China State Key Laboratory of Extreme Photonics and Instrumentation College of Optical Science and EngineeringZhejiang UniversityHangzhou 310027China

Optical coherence elastography(OCE)can quantitatively obtain the viscoelasticity of tissues using rheological models and is widely applied to the clinical diagnosis of ***,commonly used rheological models in OCE do not account for the distinctive dependence of high-frequency storage and loss moduli on frequency in tissues,which results in the rheological models failing to accurately measure the viscoelastic properties of *** this paper,a modified Kelvin-Voigt fractional derivative model is presented based on the power-law behavior of soft tissues and the dependence of high-frequency complex shear modulus on frequency in living *** the rheometer and OCE tests,the modified model can provide the prediction of the power-law relationship between the low-frequency shear viscosity and frequency;compared with the Kelvin-Voigt and Kelvin-Voigt fractional derivative models,the modified model has a higher goodness-of-fit(accuracy>96%)for the high-frequency storage moduli of gelatin ***,the proposed model can reduce the root mean square error of fit by approximately 83%for the high-frequency(1–128 kHz)storage modulus of the polydimethylsiloxane phantoms obtained from publicly available ***,the modified model accurately predicts the mechanical properties of biomimetic materials over a wide frequency range,with the potential to more accurately reflect pathological changes in tissues.

关键词： optical coherence tomography optical coherence elastography viscoelasticity rheological model

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