IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews)

The five papers in this special issue focus on pattern recognition technologies for anti-terrorism applications. View full abstract»

Tracking-based approaches for abandoned object detection often become unreliable in complex surveillance videos due to occlusions, lighting changes, and other factors. We present a new framework to robustly and efficiently detect abandoned and removed objects based on background subtraction (BGS) and foreground analysis with complement of tracking to reduce false positives. In our system, the back... View full abstract»

Face recognition and identification is a very active research area nowadays due to its importance in both human computer and social interaction. Psychological studies suggest that face recognition by human beings can be featural, configurational, and holistic. In this paper, by incorporating spatially structured features into a histogram-based face-recognition framework, we intend to pursue consis... View full abstract»

In this paper, we propose a novel background subtraction approach in order to accurately detect moving objects. Our method involves three important proposed modules: a block alarm module, a background modeling module, and an object extraction module. The block alarm module efficiently checks each block for the presence of either a moving object or background information. This is accomplished by us... View full abstract»

The effectiveness with which individual identity can be predicted in, for example, an antiterrorist scenario can benefit from seeking a broad base of identity evidence. The issue of improving performance can be addressed in a number of ways, but system configurations based on integrating different information sources (often involving more than one biometric modality) are a widely adopted means of ... View full abstract»

We propose a mechanism to assess threats that are based on observables. Observables are properties of persons, i.e., their behavior and interaction with other persons and objects. We consider observables that can be extracted from sensor signals and intelligence. In this paper, we discuss situation assessment that is based on observables for threat assessment. In the experiments, the assessment is... View full abstract»

This paper presents the most up-to-date methods for the task of designing a system to accurately classify abnormal events, or faults, in a complex tribological mechanism, using elemental analysis of lubrication oil as an indicator of engine condition. The discussion combines perspectives from numerous fault diagnosis applications, both online and offline, to focus upon the task of offline event de... View full abstract»

The emerging interdisciplinary area of biologically inspired network systems research is reviewed. Examples of such systems found in the literature are grouped into two classes: in silico and in vitro/vivo network systems. For each class, background knowledge is provided concerning the biological systems, mechanisms, or materials used, and the manner in which they are applied to the design of the ... View full abstract»

Multidimensional scaling (MDS) is a technique used to extract a set of independent variables from a proximity matrix or matrices. Applications of MDS are found in a wide range of areas, including visualization, pattern analysis, data preprocessing, scale development, cybernetics, and localization. The overall rationale behind the paper is to help share innovations across disciplines. We survey and... View full abstract»

The main purpose of this paper is the classification of documents in terms of their content. Two systems are presented here that share a two-level architecture that include 1) a word map created via unsupervised learning that functions as a document-representation module and 2) a supervised multilayer-perceptron-based classifier. Two approaches to create word maps are presented and compared; these... View full abstract»

The goal of this paper is to provide an introduction to the application of wave probabilistic functions in the area of dynamic system models. This paper presents dynamic features of wave probabilistic models that are basic principles of quantum cybernetics. These features are mathematically described, and the illustrative examples demonstrate possible applications of the theory. View full abstract»

The present article deals with an application of multiobjective optimization (MOO) technique for fuzzy clustering. The problem of automatic clustering can be posed as one of the searching for a suitable set of cluster centers such that some measure of cluster validity is optimized. However, no single validity measure works equally well for different kinds of data sets. Moreover, it is extremely di... View full abstract»

Both research and practice have shown that preexistence of long-term associations/clusters of active and competitive organizations, the so-called virtual organizations breeding environments (VBEs), can greatly enhance dynamic creation of virtual organizations (VOs). During the past decade, a number of VBEs are formed worldwide, mostly among organizations located in a common region that, in princip... View full abstract»

We present a new machine learning framework for indoor location estimation. In many cases, locations could be easily estimated using various traditional positioning methods and conventional machine learning approaches based on signalling devices, e.g., access points (APs). When there exist environmental changes, however, such traditional methods cannot be employed due to data distribution change. ... View full abstract»

Video forgery, also referred as video falsifying, is a technique for generating fake videos by altering, combining, or creating new video contents. For instance, the outcome of a 100 m race in the olympic game is forged as an example in this paper. We track objects and segment motions using a modified mean shift mechanism. The resulting video layers can be played in different speeds and from diffe... View full abstract»

Supply chain visibility is one of the main levers for achieving operational efficiency. Modern supply chain tracking systems can deliver serial-level information about the location of items progressing through the chain. However, these systems still fail to meet the managers' visibility requirements in full, since they provide discrete information about product location at specific time instances ... View full abstract»

This paper investigates a new approach for the personal recognition using rank-level combination of multiple biometrics representations. There has been very little effort to study rank-level fusion approaches for multibiometrics combination and none using multiple palmprint representations. In this paper, we propose a new nonlinear rank-level fusion approach and present a comparative study of rank... View full abstract»

Security assessment and classification are the major concerns in real-time operation of electric power systems. This paper proposes a multiclass support vector machine (SVM) classifier for static and transient security assessment and classification. A straightforward and quick procedure called the sequential forward selection method is used for a feature selection process. The security status of a... View full abstract»

Social networking has become one of the most important trends on the Web, leading to the development of several social applications such as blogs. Blogs are locations on the Web where individuals are provided with the ability to express their opinion, experience, and knowledge about a product, an event, or any other subject. The tremendous popularity of these services has rendered the problem of i... View full abstract»