- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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[IEEE 2019 24th Microoptics Conference (MOC) - Toyama, Japan (2019.11.17-2019.11.20)] 2019 24th Microoptics Conference (MOC) - Patterned emission of organic light emitting diodes with laser irradiation
摘要： Self-healing networks aim to detect cells with service degradation, identify the fault cause of their problem, and execute compensation and repair actions. The development of this type of automatic system presents several challenges to be confronted. The first challenge is the scarce number of historically reported faults, which greatly complicates the evaluation of novel self-healing techniques. For this reason, in this paper, a system model to simulate faults in Long-Term Evolution (LTE) networks, along with their most significant key performance indicators, is proposed. Second, the expert knowledge required to build a self-healing system is usually not documented. Therefore, in this paper, a methodology to extract this information from a collection of reported cases is proposed. Finally, following the proposed methodology, an automatic fuzzy-logic-based system for fault identification in LTE networks is designed. Evaluation results show that the fuzzy system provides fault identification with a high success rate.
关键词： Long-Term Evolution (LTE),Diagnosis,fuzzy logic,fault identification,troubleshooting,root cause analysis,self-healing,fault management
更新于2025-09-23 15:21:01
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[IEEE 2019 IEEE 16th India Council International Conference (INDICON) - Rajkot, India (2019.12.13-2019.12.15)] 2019 IEEE 16th India Council International Conference (INDICON) - Performance Comparison Between Bipolar and Unipolar Switching Scheme for a Single-Phase Inverter Based Stand-alone Photovoltaic System
摘要： Self-organizing network (SON) mechanisms reduce operational expenditure in cellular networks while enhancing the offered quality of service. Within a SON, self-healing aims to autonomously solve problems in the radio access network and to minimize their impact on the user. Self-healing comprises automatic fault detection, root cause analysis, fault compensation, and recovery. This paper presents a root cause analysis system based on fuzzy logic. A genetic algorithm is proposed for learning the rule base. The proposed method is adapted to the way of reasoning of troubleshooting experts, which ease knowledge acquisition and system output interpretation. Results show that the obtained results are comparable or even better than those obtained when the troubleshooting experts define the rules, with the clear benefit of not requiring the experts to define the system. In addition, the system is robust, since fine tuning of its parameters is not mandatory.
关键词： genetic algorithms,self-organizing networks (SONs),Fuzzy systems,troubleshooting,root cause analysis,self-healing,supervised learning
更新于2025-09-23 15:21:01
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[IEEE 2019 Far East NDT New Technology & Application Forum (FENDT) - Qingdao, Shandong province, China (2019.6.24-2019.6.27)] 2019 Far East NDT New Technology & Application Forum (FENDT) - Laser line generation for optimized interaction with hidden defects in active thermography
摘要： Self-organizing network (SON) mechanisms reduce operational expenditure in cellular networks while enhancing the offered quality of service. Within a SON, self-healing aims to autonomously solve problems in the radio access network and to minimize their impact on the user. Self-healing comprises automatic fault detection, root cause analysis, fault compensation, and recovery. This paper presents a root cause analysis system based on fuzzy logic. A genetic algorithm is proposed for learning the rule base. The proposed method is adapted to the way of reasoning of troubleshooting experts, which ease knowledge acquisition and system output interpretation. Results show that the obtained results are comparable or even better than those obtained when the troubleshooting experts define the rules, with the clear benefit of not requiring the experts to define the system. In addition, the system is robust, since fine tuning of its parameters is not mandatory.
关键词： troubleshooting,self-healing,genetic algorithms,self-organizing networks (SONs),root cause analysis,Fuzzy systems,supervised learning
更新于2025-09-19 17:13:59
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[IEEE 2019 16th China International Forum on Solid State Lighting & 2019 International Forum on Wide Bandgap Semiconductors China (SSLChina: IFWS) - Shenzhen, China (2019.11.25-2019.11.27)] 2019 16th China International Forum on Solid State Lighting & 2019 International Forum on Wide Bandgap Semiconductors China (SSLChina: IFWS) - Optical and Thermal Designs of LED Matrix Module used in Automotive Headlamps
摘要： User manual designers generally use written procedures, figures, and illustrations to convey procedural information to end users. However, ensuring that the instructions are accurate and unambiguous is difficult. With respect to accuracy, describing the task and under what conditions it should be conducted can be complicated by considerations such as the ordering of actions within a higher level task and the context under which tasks and lower level actions can be initiated, repeated, and completed. With respect to ambiguity, component and task level issues occur such as which portion of a component is relevant and what context constrains activity. To support accuracy and to decrease ambiguity, we propose a model-based approach coupled with model checking and visualization to aid in user manual development. Our approach integrates formal task-analytic and device models with safety specifications into a computational framework. We demonstrate the value of this approach using alarm troubleshooting instructions from the patient user manual of a left ventricular assist device. By encoding a formal task model, we revealed potential problems with task and device descriptions in the troubleshooting instructions. We also applied linear temporal logic and symbolic model checking to identify issues with the order of troubleshooting steps. Our framework provides insights into the use of formal methods for patient user manual evaluation.
关键词： Formal methods,task analysis,user manuals,model checking,troubleshooting
更新于2025-09-19 17:13:59
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Anisotropic Impedance Surface Enabled Low-Profile Broadband Dual-Circularly-Polarized Multi-Beam Reflect-Arrays for Ka-Band Applications
摘要： Self-organizing network (SON) mechanisms reduce operational expenditure in cellular networks while enhancing the offered quality of service. Within a SON, self-healing aims to autonomously solve problems in the radio access network and to minimize their impact on the user. Self-healing comprises automatic fault detection, root cause analysis, fault compensation, and recovery. This paper presents a root cause analysis system based on fuzzy logic. A genetic algorithm is proposed for learning the rule base. The proposed method is adapted to the way of reasoning of troubleshooting experts, which ease knowledge acquisition and system output interpretation. Results show that the obtained results are comparable or even better than those obtained when the troubleshooting experts define the rules, with the clear benefit of not requiring the experts to define the system. In addition, the system is robust, since fine tuning of its parameters is not mandatory.
关键词： genetic algorithms,self-organizing networks (SONs),Fuzzy systems,troubleshooting,root cause analysis,self-healing,supervised learning
更新于2025-09-19 17:13:59
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Single Layer Decoupled Multiple Order Generalized Integral Control for Single-Stage Solar Energy Grid Integrator with Maximum Power Extraction
摘要： User manual designers generally use written procedures, figures, and illustrations to convey procedural information to end users. However, ensuring that the instructions are accurate and unambiguous is difficult. With respect to accuracy, describing the task and under what conditions it should be conducted can be complicated by considerations such as the ordering of actions within a higher level task and the context under which tasks and lower level actions can be initiated, repeated, and completed. With respect to ambiguity, component and task level issues occur such as which portion of a component is relevant and what context constrains activity. To support accuracy and to decrease ambiguity, we propose a model-based approach coupled with model checking and visualization to aid in user manual development. Our approach integrates formal task-analytic and device models with safety specifications into a computational framework. We demonstrate the value of this approach using alarm troubleshooting instructions from the patient user manual of a left ventricular assist device. By encoding a formal task model, we revealed potential problems with task and device descriptions in the troubleshooting instructions. We also applied linear temporal logic and symbolic model checking to identify issues with the order of troubleshooting steps. Our framework provides insights into the use of formal methods for patient user manual evaluation.
关键词： user manuals,Formal methods,model checking,troubleshooting,task analysis
更新于2025-09-19 17:13:59
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[IEEE 2019 Innovations in Power and Advanced Computing Technologies (i-PACT) - Vellore, India (2019.3.22-2019.3.23)] 2019 Innovations in Power and Advanced Computing Technologies (i-PACT) - Ultra-high Negative Dispersion Compensating Index Guiding Single Mode Octagonal Photonic Crystal Fiber: Design and Analysis
摘要： Self-organizing network (SON) mechanisms reduce operational expenditure in cellular networks while enhancing the offered quality of service. Within a SON, self-healing aims to autonomously solve problems in the radio access network and to minimize their impact on the user. Self-healing comprises automatic fault detection, root cause analysis, fault compensation, and recovery. This paper presents a root cause analysis system based on fuzzy logic. A genetic algorithm is proposed for learning the rule base. The proposed method is adapted to the way of reasoning of troubleshooting experts, which ease knowledge acquisition and system output interpretation. Results show that the obtained results are comparable or even better than those obtained when the troubleshooting experts define the rules, with the clear benefit of not requiring the experts to define the system. In addition, the system is robust, since fine tuning of its parameters is not mandatory.
关键词： troubleshooting,self-healing,genetic algorithms,self-organizing networks (SONs),root cause analysis,Fuzzy systems,supervised learning
更新于2025-09-19 17:13:59
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[IEEE 2019 Compound Semiconductor Week (CSW) - Nara, Japan (2019.5.19-2019.5.23)] 2019 Compound Semiconductor Week (CSW) - Electron selective contact for high efficiency core-shell nanowire solar cell
摘要： Self-healing networks aim to detect cells with service degradation, identify the fault cause of their problem, and execute compensation and repair actions. The development of this type of automatic system presents several challenges to be confronted. The first challenge is the scarce number of historically reported faults, which greatly complicates the evaluation of novel self-healing techniques. For this reason, in this paper, a system model to simulate faults in Long-Term Evolution (LTE) networks, along with their most significant key performance indicators, is proposed. Second, the expert knowledge required to build a self-healing system is usually not documented. Therefore, in this paper, a methodology to extract this information from a collection of reported cases is proposed. Finally, following the proposed methodology, an automatic fuzzy-logic-based system for fault identification in LTE networks is designed. Evaluation results show that the fuzzy system provides fault identification with a high success rate.
关键词： Long-Term Evolution (LTE),Diagnosis,fuzzy logic,fault identification,troubleshooting,root cause analysis,self-healing,fault management
更新于2025-09-19 17:13:59
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[IEEE 2019 Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC) - Munich, Germany (2019.6.23-2019.6.27)] 2019 Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC) - High-Fidelity Few-Cycle Laser Pulses Generated Via Nonlinear Ellipse Rotation
摘要： Self-organizing network (SON) mechanisms reduce operational expenditure in cellular networks while enhancing the offered quality of service. Within a SON, self-healing aims to autonomously solve problems in the radio access network and to minimize their impact on the user. Self-healing comprises automatic fault detection, root cause analysis, fault compensation, and recovery. This paper presents a root cause analysis system based on fuzzy logic. A genetic algorithm is proposed for learning the rule base. The proposed method is adapted to the way of reasoning of troubleshooting experts, which ease knowledge acquisition and system output interpretation. Results show that the obtained results are comparable or even better than those obtained when the troubleshooting experts define the rules, with the clear benefit of not requiring the experts to define the system. In addition, the system is robust, since fine tuning of its parameters is not mandatory.
关键词： genetic algorithms,self-organizing networks (SONs),Fuzzy systems,troubleshooting,root cause analysis,self-healing,supervised learning
更新于2025-09-19 17:13:59
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[IEEE 2019 18th International Conference on Optical Communications and Networks (ICOCN) - Huangshan, China (2019.8.5-2019.8.8)] 2019 18th International Conference on Optical Communications and Networks (ICOCN) - Network Nervous System: When Multilayer Telemetry Meets AI-assisted Service Provisioning : (Invited Paper)
摘要： We present a network nervous system (NNS) that leverages hybrid centralized/distributed processing to achieve automatic and effective network control and management (NC&M) for realizing artificial intelligence (AI) assisted service provisioning in IP over elastic optical networks (IPoEONs).
关键词： Artificial intelligence (AI),Multilayer in-band network telemetry (ML-INT),Performance monitoring and troubleshooting,Elastic optical networks (EONs)
更新于2025-09-16 10:30:52