in this paper an application of gustafson-kessel clustering algorithm is presented to create a fault detection map (fdm). five post-stack seismic attributes are extracted from a desired seismic time slice related to 3d seismic data of a gas field located in southwest of iran. to find the optimal cluster numbers, two frequently used clustering validity measures, i.e. sc and xb, are used and then...

BACKGROUND The functional diffusion map (fDM) has been suggested as a tool for early detection of tumor treatment efficacy. We aim to study 3 factors that could act as potential confounders in the fDM: areas of necrosis, tumor grade, and change in tumor size. METHODS Thirty-four pediatric patients with brain tumors were enrolled in a retrospective study, approved by the local ethics committee...

Prostate cancer ranks as the most common lethal malignancy diagnosed and the second leading cause of cancer mortality in American men. Although high response rates are achieved using androgen blockade as first-line therapy, most men progress toward hormone-refractory prostate cancer. Systemic chemotherapies have been shown to improve clinical outcome in hormone refractory prostate cancer patien...

induction motor bearing is one of the key parts of the machine and its analysis and interpretation are important for fault detection. in the present work vibration signal has been taken for the classification i.e. bearing is healthy (h) or defective (d). for this purpose, clustering based classification of bearing vibration data has been carried out using principal component analysis (pca) and ...

BACKGROUND Radiologic response of brain tumors is traditionally assessed according to the Macdonald criteria 10 weeks from the start of therapy. Because glioblastoma (GB) responds in days rather than weeks after boron neutron capture therapy (BNCT) that is a form of tumor-selective particle radiation, it is inconvenient to use the Macdonald criteria to assess the therapeutic efficacy of BNCT by...

This research article presents an enhanced YOLOv8 model with additional feature extraction layer integrated into the traditional architecture to improve fault detection performance in smart additive manufacturing, specifically for FDM 3D printers. Hyperparameter optimization techniques are employed ensure is trained optimal input and batch size configurations. The findings demonstrate that modu...

An active Fault Tolerant Model Predictive Control (FTMPC) using Fuzzy scheduler is developed. Fault tolerant Control (FTC) system stages are broadly classified into two namely Fault Detection and Isolation (FDI) and fault accommodation. Basically, the faults are identified by means of state estimation techniques. Then using the decision based approach it is isolated. This is usually performed u...

The fault detection method (FDM) plays a crucial role in controlling and operating microgrids (MGs), because it allows for systems to rapidly isolate restore faults. Due the fact that MGs use inverter-interfaced distributed production, conventional FDMs are no longer appropriate they dependent on substantial currents. This study presents smart FDM based Hilbert–Huang transform (HHT) deep neural...

This paper investigates the fault detection of a micro parallel plate capacitor subjected to nonlinear electrostatic force. For this end Thau observer, which has good ability in fault detection of nonlinear system has been presented and governing nonlinear dynamic equation of the capacitor has been presented. Upper and lower threshold for fault detection have been obtained. The robustness of th...

the idea of this paper is designing an automatic fault detection system based on fuzzy logic, therefore two signals of pmsm in fault condition are analyzed for inter turn fault detection: current and torque. in this fault type there is some distortion in these signals, but it is not good enough to detecting with fuzzy logic solely, so with combination of wavelet transform and fcm a new method f...