Preliminary, alphabetically ordered list of papers accepted for inclusion in the DX’25 proceedings as full papers.
The papers cover a range of topics within the field of diagnosis and prognosis, including:
* **LLM Applications:** Exploring the potential of Large Language Models for diagnostic concepts and fault detection.
* **Fault Diagnosis & Isolation:** Techniques for identifying and locating faults in systems like HVAC, control systems, and radiotherapy equipment, utilizing methods like dynamic slicing, spectrum-based fault localization, and data-driven approaches.
* **Prognosis & Remaining Useful Life:** Predicting future system behavior and estimating remaining useful life, including approaches using particle filters and spectral fault receptive fields.
* **Hybrid Systems & Machine Learning:** Utilizing one-shot learning and deep learning clustering for system identification and predictive maintenance.
* **Competition & Benchmarks:** Details about the DX 2025 competition and its associated benchmarks.
* **Model-Based Diagnosis:** Using qualitative simulation models and fusing temporal logic with probabilistic diagnosis.
The list includes 15 accepted papers with authors and titles provided. The conference will be held from September 22-24, 2025, in Nashville, Tennessee.
The papers cover a range of topics within the field of diagnosis and prognosis, including:
* **LLM Applications:** Exploring the potential of Large Language Models for diagnostic concepts and fault detection.
* **Fault Diagnosis & Isolation:** Techniques for identifying and locating faults in systems like HVAC, control systems, and radiotherapy equipment, utilizing methods like dynamic slicing, spectrum-based fault localization, and data-driven approaches.
* **Prognosis & Remaining Useful Life:** Predicting future system behavior and estimating remaining useful life, including approaches using particle filters and spectral fault receptive fields.
* **Hybrid Systems & Machine Learning:** Utilizing one-shot learning and deep learning clustering for system identification and predictive maintenance.
* **Competition & Benchmarks:** Details about the DX 2025 competition and its associated benchmarks.
* **Model-Based Diagnosis:** Using qualitative simulation models and fusing temporal logic with probabilistic diagnosis.
The list includes 15 accepted papers with authors and titles provided. The conference will be held from September 22-24, 2025, in Nashville, Tennessee.
K8sGPT is a tool for scanning Kubernetes clusters, diagnosing issues in simple English, and enriching data with AI. It helps with workload health analysis, security CVE review, and more.
MIT researchers have developed a method using large language models to detect anomalies in complex systems without the need for training. The approach, called SigLLM, converts time-series data into text-based inputs for the language model to process. Two anomaly detection approaches, Prompter and Detector, were developed and showed promising results in initial tests.
Apply sound data-based anomalous behavior detection, diagnose the root cause via object detection concurrently, and inform the user via SMS.
