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This showcase presents a visual approach based on clustering and superimposing to construct a high-level overview of sequential event data while balancing the amount of information and the cardinality in it. We also implement an interactive prototype, ...

This paper presented a combinatorial application of quality by design (QbD) and quality risk management (QRM) tools with the goal of managing process risk and achieving high level of quality control during the development of the high shear wet ...

Visual exploration and analysis of multidimensional data becomes increasingly difficult with increasing dimensionality. We want to understand the relationships between dimensions of data, but lack flexible techniques for exploration beyond low-order ...

Nonnegative Matrix Factorization (NMF), a relatively novel paradigm for dimensionality reduction, has been in the ascendant since its inception. It incorporates the nonnegativity constraint and thus obtains the parts-based representation as well as ...

Magnetic and inductive sensors are widely used in research and industry for a variety of applications, e.g. for geophysical prospecting, nondestructive testing (NDT) of materials, in the food industries, for distance and proximity sensing, security ...

Network anomaly detection is an important issue in network security. Detecting network anomaly is a challenging because of the multivariate property of the collected data, the diversity of the causes and the complexity of the existing algorithms. ...

Nonnegative matrix factorization (NMF) is a widely-used method for multivariate analysis of nonnegative data to obtain a reduced representation of data matrix only using a basis matrix and a encoding variable matrix having non-negative elements. A NMF ...

Multivariate visualization techniques are often used as assistant tools for classification tasks up to now. However, few classification systems fully utilize the capability of multivariate visualization and integrate them with multivariate analysis ...

The acquisition of multiple brain imaging types for a given study is a very common practice. There have been a number of approaches proposed for combining or fusing multitask or multimodal information. These can be roughly divided into those that ...

The fuzzy associative conjuncted maps (FASCOM) is a fuzzy neural network that associates data of nonlinearly related inputs and outputs. In the network, each input or output dimension is represented by a feature map that is partitioned into fuzzy or ...

Self-organizing neural networks are usually focused on prototype learning, while the topology is held fixed during the learning process. Here we propose a method to adapt the topology of the network so that it reflects the internal structure of the ...

Process analytical technology guidance by the US Food & Drug Administration lately became the major driver of pharmaceutical process optimization. The majority of these processes are complex and consequently multivariate. Although new insights have ...

This paper proposes a new algorithm that improves the efficiency of the anomaly detection stage of a vector-based intrusion detection scheme. In general, intrusion detection schemes are based on the hypothesis that normal system/user behaviors are ...

This paper introduces an interactive classification technique for volume data, called ISpace, which uses Independent Component Analysis (ICA) and a multidimensional histogram of the volume data in a transformed space. Essentially, classification in the ...

Observation-based testing calls for analyzing profiles of executions induced by potential test cases, in order to select a subset of executions to be checked for conformance to requirements. A family of techniques for selecting such a subset is ...

We introduce the concept of local moments for a distribution in Rp, p 1, at a point z Rp. Local moments are defined as normalized limits of the ordinary moments of a truncated version of the distribution, ignoring the probability mass falling outside a ...

We explore the use of multivariate visualization techniques to support a new approach to test data selection, called observation-based testing. Applications of multivariate visualization are described, including: evaluating and improving synthetic tests;...

Performance prediction can play an important role in improving the efficiency of multicomputers in executing scalable parallel applications. An accurate model of program execution time must include detailed algorithmic and architectural ...