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Optimal Location of PMUs to Enhance State Estimation of Power systems

Optimal Location of PMUs to Enhance State Estimation of Powe...

引用

2023 IEEE Jordan international Joint conference on Electrical Engineering and Information Technology, JEEIT 2023

作者： Al Qaralleh, Atallah Ahmad Alawasa, Khaled Al-Odienat, Abdullah I. Mutah University Faculty of Engineering Karak Jordan Sultan Qaboos University Department of Eletrical and Computer Engineering Muscat Oman Amman Arab University Department of Renewable Energy Engineering Amman11953 Jordan

ISBN: (纸本)9798350324051

The Wide Area Monitoring systems (WAMs) has brought several advantages for the power system monitoring, operation, control. Recently, the introduction of Phasor measurement Units (PMUs) to power grids played a significant role in transforming them into smart grids. However, PMUs are costly and installing PMU at each bus is feasible. Therefore, the formulation of optimal placement of PMUs (OPP) in power systems is very important to minimize the total number, while preserving the observability of the system. Newton Raphson load flow method is applied to obtain load flow results of the system. Weighted least squares WLS with PMUs approaches for the state estimation of IEEE 14 bus test case is presented. The results show more accurate state estimation process. © 2023 IEEE.

关键词： Phasor measurement units

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Rollick Games: A Formal Language Based Platform for Location-Based Pervasive Games 1

引用

15th international conference on Interactive Mobile Communication, Technologies, and Learning, IMCL 2023

作者： Anestis, George Gioldasis, Nektarios Karasavvidis, Stefanos Palioudakis, Tzanis Moumoutzis, Nektarios Christodoulakis, Stavros Laboratory of Distributed Multimedia Information Systems and Applications School of Electrical and Computer Engineering Technical University of Crete Chania Greece School of Electrical and Computer Engineering Technical University of Crete Chania Greece

ISBN: (数字)9783031560750

ISBN: (纸本)9783031560743

In this paper, we present the Rollick Games platform and its Pervasive Game modeling Language that enables the description of location-based pervasive games using a GUI provided by the Game Studio web app. The runtime environment (Pervasive Game Execution Environment) is responsible for generating the Pervasive Game Execution Language from a game model and loading it to an instance of the game's Execution Engine. The Execution Environment includes a set of agents responsible for monitoring the players’ context and interaction with other game elements and among each other. The Engine follows an event-driven paradigm and uses an event loop waiting for events to be dispatched from the agents to carry out its computations based on its current state, context, and event data. The proposed approach allows for both sharing and reusing game models, significantly reducing time to market and development costs. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： modeling languages

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Dynamic Simulation Evaluation of Digital Intelligent Technology in computer Automatic Control System

Dynamic Simulation Evaluation of Digital Intelligent Technol...

引用

2023 international conference on Evolutionary Algorithms and Soft Computing Techniques, EASCT 2023

作者： Qu, Jia Wang, Lei Shandong Transport Vocational College Department of Navigation Weifang China Shandong Transport Vocational College Department of Management and Information Weifang China

ISBN: (纸本)9798350313413

The proliferation of digital intelligent technology is a direct consequence of the meteoric advancements in information technology coupled with consistent innovations in computer technology. As computer performance and computational capabilities have soared, there has been a marked shift towards integrating digital technology across diverse sectors, encompassing industrial production, management, transportation, medical care, and more. Particularly in computer automatic control systems, the infusion of digital intelligent technology is gaining *** harnessing the power of mathematical modeling and creating sophisticated simulation environments, digital intelligence technology can execute exhaustive dynamic simulation analyses of systems. This allows for a holistic evaluation of system performance, accurate predictions of system behaviors, refined system designs, and a substantial reduction in system development expenditures. A glance at experimental data reveals a transformative impact: the average operation time of digital intelligent technology in computer automatic control systems for dynamic simulation analysis has plummeted from over 94 seconds to a mere 58 seconds, in stark contrast to traditional control systems. Similarly, data analysis duration has been slashed from over 47 seconds to just below 26 seconds. Most impressively, the accuracy has surged from a modest 63% to an impressive 90%. In the backdrop of the Industry 4.0 revolution, digital intelligent technology is increasingly recognized as a pivotal catalyst propelling industrial metamorphosis and elevation, bestowing enterprises with a formidable competitive edge. This underscores the monumental significance of integrating digital intelligent technology into computer automatic control systems. The benefits are manifold: there ' s a marked enhancement in system performance and robustness, and it paves the way for monumental gains in industrial production and managerial efficiency, unlocking vas

关键词： automatic control computer technology intelligent technology interface design system design

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Integrating Object Detection and Wide Area Network Infrastructure for Sustainable Ferry Operation

Integrating Object Detection and Wide Area Network Infrastru...

引用

2023 IEEE international conference on Imaging systems and Techniques, IST 2023

作者： Musaddiq, Arslan Mozart, David Maleki, Neda Olsson, Tobias Ahlgren, Fredrik Linnaeus University Applied IoT Lab Department of Computer Science and Media Technology Sweden

ISBN: (纸本)9798350330830

Low-Power Wide-Area Network (LPWAN) technologies offer new opportunities for data collection, transmission, and decision-making optimization. Similarly, a wide range of use cases of computer vision and object detection algorithms can be found across different industries. This paper presents a case study focusing on the utilization of LPWAN infrastructure, specifically the Helium network, coupled with computer vision and object detection algorithms, to optimize passenger ferry operation. The passenger ferry called M/S Dessi operates between Kalmar and Färjestaden in Sweden during the summer season. By implementing an Edge-computing solution, real-Time data collection and communication are achieved, enabling accurate measurement of passenger flow. This approach is superior to traditional methods of collecting passenger data, such as manual counting or CCTV surveillance. Real-Time passenger data is invaluable for traffic planning, crowd prediction, revenue enhancement, and speed and fuel optimization. The utilization of the Helium network ensures reliable and long-distance data transmission, extending the system's applicability to multiple ferries and distant locations. The proposed approach can be utilized to integrate passenger ferries that operate in close proximity to urban areas into society's digital transformation efforts. This study highlights the potential of LPWAN, computer vision, and object detection in enhancing passenger ferry operations, contributing to enhanced efficiency and sustainability. © 2023 IEEE.

关键词： Object detection

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Intelligent computer Simulators for Training of Control Personnel of Electrotechnological Productions 5

Intelligent Computer Simulators for Training of Control Pers...

引用

5th international conference on Control systems, Mathematical modeling, Automation and Energy Efficiency, SUMMA 2023

作者： Ershova, Olga CAD&C Saint-Petersburg State Institute of Technology Saint-Petersburg Russia

ISBN: (纸本)9798350309126

Intelligent reconfigurable computer simulators are presented as part of the CAD staffing subsystem for training personnel in the control of electrochemical and electrothermal industrial technologies, designed to improve control efficiency by improving staff qualifications. The simulators are made in an industrial SCADA interface using an expert subsystem and include information, mathematical, algorithmic and software. Information support includes databases of administrative and production personnel, raw materials, equipment, products, process variables, a knowledge base developed on the basis of expert knowledge and data on the operation of the facility and intended for control in emergency situations, which are described using a knowledge representation model. Mathematical support includes problem-oriented mathematical models, reconfigurable for various equipment, raw materials, products and productivity by adjusting the coefficients of the model and allowing to calculate the main criteria for the effectiveness of the management object and evaluate the effectiveness of control training. Algorithmic support includes a control algorithm, algorithms for solving models, and training scenarios. The software includes instructor and trainees interfaces, dynamic mnemonic circuits with controls in the SCADA HMI environment. An assessment of the adequacy of models based on experimental and literary data was carried out, confirming their adequacy. Testing of methods and technologies for creating simulators, conducted on the example of electrotechnological productions, showed their effectiveness by reducing the development time and convenience of software implementation. The working capacity of the simulators is confirmed by the acts on the introduction of Russian universities and industrial enterprises into the educational process. © 2023 IEEE.

关键词： computer aided design

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COMPOSITE Electromagnetic Scattering and SAR Imaging of the Topographical Environment

COMPOSITE Electromagnetic Scattering and SAR Imaging of the ...

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2023 international conference on Remote Sensing, Mapping, and Geographic systems, RSMG 2023

作者： Wang, Qingkuan Wang, Qingfen Wang, Zhaolong Song, Tao Wang, Tong Peng, Peng Air Force Engineering University No.1 Changle East Road Baqiao District Xi’an710038 China School of Computer Science and Engineering Northeastern University Shenyang110169 China

ISBN: (纸本)9781510668898

In this paper, a method of environmental geometric modeling utilizing a digital elevation model is proposed to solve the problem that the environmental modeling based on spectral function cannot describe the actual terrain. At the same time, by combining the shooting and bouncing ray (SBR) method with the facet-based scattering model (FBSM), the SBR-FBSM algorithm is proposed. Finally, the simulation analysis is carried out for the actual environment, the target-environment composite scene, and the complex scene respectively to verify the rationality, and effectiveness of the proposed electromagnetic scattering algorithm and its applicability in the SAR imaging field. © 2023 SPIE.

关键词： Digital instruments

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A Novel Classification Model Based on DWT and CNN-LSTM Motor EEG Imagination Signals 7

A Novel Classification Model Based on DWT and CNN-LSTM Motor...

引用

7th international conference on Pattern Recognition and Artificial Intelligence, PRAI 2024

作者： Yang, Yuyao Chen, Zuowen Li, Weisu Ma, Yahong Xijing University School of Electronic Information Xi'an Key Laboratory of High Pricision Industrial Intelligent Vision Measurement Technology Xi'an China

ISBN: (纸本)9798350350890

Feature extraction and pattern classification play important roles in brain-computer interface (BCI) systems, which are widely used in rehabilitation medicine, artificial intelligence and other fields. Although advanced EEG acquisition technology can generate a large amount of EEG data for different brain regions, it inevitably has disadvantages such as high cost, long time consuming and inherent high false positives. Considering the contradiction between data volume and accuracy, this paper proposes a MI EEG feature extraction and classification method based on discrete wavelet transform (DWT) and Convolutional Neural Network-Long Short Term Memory (CNN-LSTM). Based on the project BCI motor imagination EEG(MI-EGG) data set, all evaluation indexes of the proposed CNN-LSTM model are superior to other models. The prediction accuracy, precision, recall rate, F1-score and MCC of C3 and C4 channels reaches 96.43%, 96.57%, 96.57%, 96.57% and 93.02%, respectively. The reliability of the proposed model is also proved by tenfold cross-validation. The average accuracy is 99.64%, which is far higher than the other models. It can be concluded that it is a reliable method to predict MI-EEG signals by using CNN-LSTM to train the modeling ability of images. © 2024 IEEE.

关键词： Electroencephalography

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Data- and Activity-Centric Business Process modeling: An Approach Based on Business Units 25th

Data- and Activity-Centric Business Process Modeling: An Ap...

引用

25th international conference on Web Information systems Engineering, WISE 2024

作者： Maamar, Zakaria Benna, Amel Burégio, Vanilson Lopes, Wictor Hafsi, Amal Ben Njima, Cheima Guegan, Chirine Ghedira University of Doha for Science and Technology Doha Qatar Research Center for Scientific and Technical Information Algiers Algeria Federal Rural University of Pernambuco Recife Brazil Higher Institute of Computer Science and Communication Technologies Sousse Tunisia IAE - Lyon 3 University Lyon France

ISBN: (纸本)9789819605781

This paper presents the concept of business unit to model business processes. A business unit’s main strength is that it represents resources like personnel and time that business processes consume at run-time. Due to concerns of resource scarcity and unavailability, their consumption is controlled using policies expressed in Open Digital Rights Language (ODRL) in this paper. In addition to policies, ODRL integrates permission, prohibition, and obligation rules that define how, when, where, and by whom resources are consumed. Parsing resources’ ODRL policies results in extracting the necessary business units that are the future building blocks of business processes. The technical doability of business unit-based modeling of business processes is also demonstrated in the paper using a Large-Language-Model (LLM). © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Business process Business unit LLM ODRL Resource

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Integration of Scpi over Vxi-11 Protocols in an Automated Gas Sensing measurement System 6th

Integration of Scpi over Vxi-11 Protocols in an Automated Ga...

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6th international conference on Nanotechnologies and Biomedical Engineering, ICNBME 2023

作者： Sereacov, Alexandr Technical University of Moldova Chisinau Moldova

ISBN: (纸本)9783031427817

Gas sensing plays a crucial role in numerous applications, such as environmental monitoring, industrial safety, and healthcare. Semiconductor oxide nanostructured sensors have emerged as promising candidates due to their high sensitivity and low cost. However, the accurate and efficient characterization of their gas sensing properties remains a challenge. In this article, we present an automated measurement system that combines a source meter device for executing measurements and a software platform for user interface, signal visualization, and data storage. The system enables both transient measurements in time and volt-ampere characteristics measurements of the sensors. The software platform provides a user-friendly interface for configuring measurement parameters, initiating measurements, and visualizing real-time sensor responses. The acquired data is processed, analyzed, and stored in the network file storage for further examination. A comparison with existing systems based on LabVIEW or MATLAB highlights the advantages of the proposed measurement system, such as improved flexibility, scalability, and ease of integration with different source meter devices. The system’s modular architecture opens the way for advanced data analysis and modeling. Our approach enhances the speed, reliability, and repeatability of gas sensing characterization. The described measurement system offers researchers an effective and customizable tool for gas sensing analysis, facilitating scientific advancements in this field. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： MATLAB

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Robust subspace learning via binary weights for face recognition

Robust subspace learning via binary weights for face recogni...

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2024 international conference on measurement, Communication, and Virtual Reality, MCVR 2024

作者： Wang, Nan An, Jiayi Feng, Weijia College of Computer and Information Engineering Tianjin Normal University Tianjin300387 China

ISBN: (纸本)9781510691773

In extreme noise environments, existing subspace learning algorithms applied to face recognition tasks exhibit limitations in feature extraction capabilities, robustness, and anomaly detection. To address these issues, this paper proposes a robust two-dimensional principal component analysis (2DPCA) method based on binary weights, aimed at effectively identifying and eliminating outliers, thereby enhancing the robustness and efficacy of face recognition systems in practical applications. By incorporating a binary weight strategy and optimal means, our model maintains a high capability for low-dimensional representation across varying noise levels. We conducted extensive experiments by artificially adding 40% and 60% occlusion noise into four publicly available facial datasets: Aberdeen, YALE, CaltechFaces, and GT. The experimental results demonstrate that the proposed algorithm achieves satisfactory outcomes even when handling severely corrupted data, particularly under conditions of 60% noise, where its reconstruction performance significantly surpasses that of the comparison algorithms, underscoring its superior robustness and adaptability. © 2025 SPIE.

关键词： Principal component analysis

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