Related papers: Pipeline Leak Detection Techniques
Results obtained with a new very compact detector for imaging with a matrix of Leak Microstructures (LM)are reported. Spatial linearity and spatial resolution obtained by scanning as well as the detection of alpha particles with 100%…
The detection of overlapping communities is a challenging problem which is gaining increasing interest in recent years because of the natural attitude of individuals, observed in real-world networks, to participate in multiple groups at the…
Dependability is an umbrella concept that subsumes many key properties about a system, including reliability, maintainability, safety, availability, confidentiality, and integrity. Various dependability modeling techniques have been…
Fault detection and isolation on hydraulic systems are very important to ensure safety and avoid disasters. In this paper, a fault detection and isolation method, based on the flatness property of nonlinear systems, is experimentally…
This lecture covers the fundamental aspects of the measurement of beam losses including their use for beam diagnostic and safety issues. The detailed functionality and detection principle of various common beam loss monitors are also…
We analyze data leakage in visual datasets. Data leakage refers to images in evaluation benchmarks that have been seen during training, compromising fair model evaluation. Given that large-scale datasets are often sourced from the internet,…
Pipeline integrity is critical to industrial safety and environmental protection, with Magnetic Flux Leakage (MFL) detection being a primary non-destructive testing technology. Despite the promise of deep learning for automating MFL…
With the ongoing emergence of smart and distributed grids, it becomes increasingly important to understand as well as improve legacy infrastructure while operating a much more interconnected and fragile architecture. To support this…
Following the development of digitization, a growing number of large Original Equipment Manufacturers (OEMs) are adapting computer vision or natural language processing in a wide range of applications such as anomaly detection and quality…
While side-channel leakage is traditionally evaluated from a fabricated chip, it is more time-efficient and cost-effective to do so during the design phase of the chip. We present a methodology to rank the gates of a design according to…
Water distribution networks (WDNs) are critical systems for our society and detecting leakages is important for minimizing losses and water waste. This makes optimal sensor placement for leakage detection very relevant. Existing sensor…
Data Loss/Leakage Prevention (DLP) continues to be the main issue for many large organizations. There are multiple numbers of emerging security attach scenarios and a limitless number of overcoming solutions. Today's enterprises' major…
Outlier detection and cleaning are essential steps in data preprocessing to ensure the integrity and validity of data analyses. This paper focuses on outlier points within individual trajectories, i.e., points that deviate significantly…
As systems in smart manufacturing become increasingly complex, producing an abundance of data, the potential for production failures becomes increasingly more likely. There arises the need to minimize or eradicate production failures, one…
Protecting sensitive information from unauthorized disclosure is a major concern of every organization. As an organizations employees need to access such information in order to carry out their daily work, data leakage detection is both an…
When dealing with spreading processes on networks it can be of the utmost importance to test the reliability of data and identify potential unobserved spreading paths. In this paper we address these problems and propose methods for hidden…
Water Distribution Networks (WDNs), critical to public well-being and economic stability, face challenges such as pipe blockages and background leakages, exacerbated by operational constraints such as data non-stationarity and limited…
Early fault detection using instrumented sensor data is one of the promising application areas of machine learning in industrial facilities. However, it is difficult to improve the generalization performance of the trained fault-detection…
Although there exist very accurate hardware systems for measuring traffic on the internet, their widespread use for analysis tasks is limited by their high cost. On the other hand, less expensive, software-based systems exist that are…
We present five methods to the problem of network anomaly detection. These methods cover most of the common techniques in the anomaly detection field, including Statistical Hypothesis Tests (SHT), Support Vector Machines (SVM) and…