Heart failure is one of the severe diseases which menace the human health and affect millions of people. Half of all patients diagnosed with heart failure die within four years. For the purpose of avoiding life-threatening situations and minimizing the costs, it is important to predict mortality rates of heart failure patients. As part of a HEIF-5 project, a data mining study was conducted aimi...

Survival analysis, often called time-to-event analysis, is a set of methods focused on failure time prediction. Such methods are developed in a variety of research domains like medicine, sociology, economics or engineering, and are used to analyze different types of failures. For example, in business applications the failure may denote bankruptcy or loan default. One of the most important chara...

Heart failure is one of the real cardio-vascular ailments influencing the center matured and the matured. It happens because of diminished cardiovascular yield. It can be both right-sided and left-sided failure of heart. This research study proposes a bio-inspired computing paradigm called particle swarm optimization shortly termed as PSO towards the prediction of heart failure. The implementat...

Some considerable damage to steel structures during the Hyogo-ken Nanbu Earthquake occurred. Among them, many exposed-type column bases failed in several consistent patterns, such as brittle base plate fracture, excessive bolt elongation, unexpected early bolt failure, and inferior construction work, etc. The lessons from these phenomena led to the need for improved understanding of column base...

Most error log analysis studies perform a statistical fit to the data assuming a single underlying error process. This paper presents the results of an analysis that demonstrates the log is composed of at least two error processes: transient and intermittent. The mixing of data from multiple processes requires many more events to verify a hypothesis using traditional statistical analysis. Based...

A sudden failure of a critical component in light-emitting diode (LED) manufacturing equipment would result in unscheduled downtime, leading to a possibly significant loss in productivity for the manufacturer. It is therefore important to be able to predict upcoming failures. A major obstacle to failure prediction is the limited amount of equipment lifecycle data available for training, as equi...

Fault detection and failure prediction for nonlinear non-Gaussian systems is an important issue both from the economic and safety point of view. Most of the fault detection techniques assume the system model to be linear and the noise to be Gaussian. These linearization assumptions tend to suffer form poor detection and imprecise prediction. Also, they may lead to false alarms which would incur...

Preventive maintenance (PM) is an effective approach to promoting reliability. Time-based and condition-based maintenance are two major approaches for PM. No matter which approach is adopted for PM, whether a failure can be early detected or even predicted is the key point. This paper presents the experimental results of a failure prediction method for preventive maintenance by state estimation...

Online failure prediction for large-scale software systems is a challenging task. One reason is the complex structure of many—partially inter-dependent—hardware and software components. State-of-the-art approaches use separate prediction models for parameters of interest or a monolithic prediction model which includes different parameters of all components. However, they have problems when deal...