Selection of optimized features for fusion of palm print and finger knuckle‐based person authentication

The impact of digital technology in biometrics is much more efficient at interpreting data than humans, which results in completely replacement of manual identification procedures in forensic science. Because the single modality‐based biometric frameworks limit performance in terms of accuracy and anti‐spoofing capabilities due to the presence of low quality data, therefore, information fusion of more than one biometric characteristic in pursuit of high recognition results can be beneficial. In this article, we present a multimodal biometric system based on information fusion of palm print and finger knuckle traits, which are least associated to any criminal investigation as evidence yet. The proposed multimodal biometric system might be useful to identify the suspects in case of physical beating or kidnapping and establish supportive scientific evidences, when no fingerprint or face information is present in photographs. The first step in our work is data preprocessing, in which region of interest of palm and finger knuckle images have been extracted. To minimize nonuniform illumination effects, we first normalize the detected circular palm or finger knuckle and then apply line ordinal pattern (LOP)‐based encoding scheme for texture enrichment. The nondecimated quaternion wavelet provides denser feature representation at multiple scales and orientations when extracted over proposed LOP encoding and increases the discrimination power of line and ridge features. To best of our knowledge, this first attempt is a combination of backtracking search algorithm and 2D²LDA has been employed to select the dominant palm and knuckle features for classification. The classifiers output for two modalities are combined at unsupervised rank level fusion rule through Borda count method, which shows an increase in performance in terms of recognition and verification, that is, 100% (correct recognition rate), 0.26% (equal error rate), 3.52 (discriminative index), and 1,262 m (speed).     

III–V super-lattice SPST/SPMT pin switches for THz communication: theoretical reliability and experimental feasibility studies

Microsystem Technologies - A physics-based Quantum-Modified CLassical Drift–Diffusion (QMCLDD) non-linear mathematical model has been developed for design and characterisation of GaN/AlGaN...     

Favorable influence of ssDNA-functionalized SWCNT on the navigation pattern of C. elegans

Microsystem Technologies - Single-Walled Carbon Nanotubes (SWCNTs) are widely used as potential carriers in drug delivery systems. The objective of this work was to observe the effects of pristine,...     

Retraction of “Developing an integrated display of health data for aging in place”

The following article from Human Factors and Ergonomics in Manufacturing & Service Industries, “Developing an Integrated Display of Health Data for Aging in Place,” by Yang Gong and Arpita Chandra, published online on October 20, 2011 in Wiley Online Library ( www.onlinelibrary.wiley.com ), has been retracted by agreement between the authors, the journal Editors‐in‐Chief, Waldemar Karwowski and Gavriel Salvendy, and Publisher Wiley Periodicals, Inc. The retraction has been agreed as these articles were mistakenly published after being rejected.     

I-convergence in probabilistic n-normed space

In this article we introduce the notion of I-Cauchy sequence and I-convergent sequence in probabilistic n-normed space. The concept of I*-Cauchy sequence and I*-convergence in probabilistic n-normed space are also introduced and some of their properties related to these notions have been established.     

Coarse head pose estimation of construction equipment operators to formulate dynamic blind spots

Several hundred workers die in construction in the United States every year because equipment operators are unable to see their fellow workers during operation of their vehicle. In this paper we propose a step towards improving this situation by providing an automated method based on range imaging for estimating the coarse head orientation of a construction equipment operator. This research utilizes commercially-available low resolution range cameras to measure the continuously changing field-of-view (FOV) of an equipment operator in outdoor construction. This paper presents a methodology to measure so-called dynamic blind spot maps. The dynamic blind spot map is then projected on a known static equipment blind spot map that already exists to each construction vehicle. A robust computational coarse head pose estimation algorithm and results to three different pieces of construction equipment and multiple operators are presented. The developed method has the potential in automatically determining the spaces around vehicles that are currently not in the field-of-view of the vehicle operator thus providing eventually additional means and technology for improving safety in construction.     

BFO optimized RLS algorithm for power system harmonics estimation

In this paper a new estimation approach combining both Recursive Least Square (RLS) and Bacterial Foraging Optimization (BFO) is developed for accurate estimation of harmonics in distorted power system signals. The proposed RLS–BFO hybrid technique has been employed for estimating the fundamental as well as harmonic components present in power system voltage/current waveforms. The basic foraging strategy is made adaptive by using RLS that sequentially updates the unknown parameters of the signal. Simulation and experimental studies are included justifying the improvement in performance of this new estimation algorithm.