Mathematical Problems in Engineering (CFP)

There has been a significant progress in biometrics with the development of the small-size sensors in the last few years, and some traits such as fingerprint and iris now start to be applied to mobile devices for payment as well as security. However, most of them are vulnerable to spoofing attacks, for example, printed photos, mimic mask, and screenshot of a valid user for the face-based log-in system, driven by detailed strategies with various materials. To cope with these limitations, efficient
optimization skills are strongly required for applications on the embedded systems. Specifically, the possibilities of advanced mathematical modeling, for example, lowrank analysis, tensor decomposition, frequency filtering, and normalization, can be extended to further biometric-inspired applications for smart home and robot-based security and service. To this end, many researchers have devoted considerable efforts to constructing simple yet powerful optimization algorithms for biometric-based recognition framework.

We kindly invite investigators to contribute reviews as well as original papers describing recent findings and breakthrough developments which are expected to revolutionize the field of biometrics and its antispoofing methods with a special attention on optimization.

Potential topics include but are not limited to the following:

• Biometric image (e.g., fingerprint, iris, and vein) enhancement with various optimization schemes (e.g., kernel estimation, subspace analysis) including denoising, reconstruction, and edge-aware filtering
• Sparse representation and low rank-based framework for biometric recognition
• Tensor-based feature point detection and matching for recognition
• Covariance updating-based incremental learning technique for biometrics
• Optimization techniques and their conceptual study for segmentation and recognition in biometric images
• Frequency filtering and normalization based feature modeling for biometrics and antispoofing
• Variational framework for biometrics and antispoofing
• Deep neural networks for biometric recognition and liveness detection (i.e., antispoofing technique) with new mathematical interpretation
• Variants of stochastic gradient descent methods for improving the conventional convolutional neural network for biometrics

Authors can submit their manuscripts through the Manuscript Tracking System at https://mts.hindawi.com/submit/journals/mpe/iaba/.

Manuscript Due: Friday, 11 August 2017
First Round of Reviews: Friday, 3 November 2017
Publication Date: Friday, 29 December 2017

Lead Guest Editor
Wonjun Kim, Konkuk University, Seoul, Republic of Korea

Guest Editors
Simone Bianco, University of Milano-Bicocca, Milan, Italy
Chanho Jung, Hanbat National University, Daejeon, Republic of Korea

About this Journal

Mathematical Problems in Engineering is a peer-reviewed, Open Access journal that publishes results of rigorous engineering research carried out using mathematical tools. Contributions containing formulations or results related to applications are also encouraged. The primary aim of Mathematical Problems in Engineering is rapid publication and dissemination of important mathematical work which has relevance to engineering. All areas of engineering are within the scope of the journal. In particular, aerospace engineering, bioengineering, chemical engineering, computer engineering, electrical engineering, industrial engineering and manufacturing systems, and mechanical engineering are of interest. Mathematical work of interest includes, but is not limited to, ordinary and partial differential equations, stochastic processes, calculus of variations, and nonlinear analysis.

The most recent Impact Factor for Mathematical Problems in Engineering is 0.644 according to the 2015 Journal Citation Reports released by Thomson Reuters in 2016.

Mathematical Problems in Engineering currently has an acceptance rate of 22%. The average time between submission and final decision is 62 days and the average time between acceptance and publication is 41 days.

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