3D fingerprint reconstruction system using feature correspondences and prior estimated finger model

The paper studies a 3D fingerprint reconstruction technique based on multi-view touchless fingerprint images. This technique offers a solution for 3D fingerprint image generation and application when only multi-view 2D images are available. However, the difficulties and stresses of 3D fingerprint reconstruction are the establishment of feature correspondences based on 2D touchless fingerprint images and the estimation of the finger shape model. In this paper, several popular used features, such as scale invariant feature transformation (SIFT) feature, ridge feature and minutiae, are employed for correspondences establishment. To extract these fingerprint features accurately, an improved fingerprint enhancement method has been proposed by polishing orientation and ridge frequency maps according to the characteristics of 2D touchless fingerprint images. Therefore, correspondences can be established by adopting hierarchical fingerprint matching approaches. Through an analysis of 440 3D point cloud finger data (220 fingers, 2 pictures each) collected by a 3D scanning technique, i.e., the structured light illumination (SLI) method, the finger shape model is estimated. It is found that the binary quadratic function is more suitable for the finger shape model than the other mixed model tested in this paper. In our experiments, the reconstruction accuracy is illustrated by constructing a cylinder. Furthermore, results obtained from different fingerprint feature correspondences are analyzed and compared to show which features are more suitable for 3D fingerprint images generation.     

Gravity optimised particle filter for hand tracking

This paper presents a gravity optimised particle filter (GOPF) where the magnitude of the gravitational force for every particle is proportional to its weight. GOPF attracts nearby particles and replicates new particles as if moving the particles towards the peak of the likelihood distribution, improving the sampling efficiency. GOPF is incorporated into a technique for hand features tracking. A fast approach to hand features detection and labelling using convexity defects is also presented. Experimental results show that GOPF outperforms the standard particle filter and its variants, as well as state-of-the-art CamShift guided particle filter using a significantly reduced number of particles.     

A GPU-based parallel method for evolutionary tree construction

Evolutionary trees are widely applied in various applications to show the inferred evolutionary relationships among species or entities. Neighbor-Joining is one solution for data-intensive and time-consuming evolutionary tree construction, with polynomial time complexity. However, its performance becomes poorer with the growth of massive datasets. Graphics Processing Units (GPUs) have brought about new opportunities for these time-consuming applications. Based on its high efficiency, a GPU-based parallel Neighbor-Joining method is proposed, and two efficient parallel mechanisms, data segmentation with asynchronous processing and the minimal chain model with bitonic sort, are put forward to speed up the processing. The experimental results show that an average speedup of 25.1 is achieved and even approximately 30 can be obtained with a sequence dataset ranging from 16,000 to 25,000. Moreover, the proposed parallel mechanisms can be effectively exploited in some other high performance applications.     

Robust passive autofocus system for mobile phone camera applications

A robust autofocus system is a ubiquitous function in today’s mobile phone camera applications. However, due to the power consumption and size requirements, it is difficult for the autofocus function to be implemented into the design of mobile phone cameras. This paper presents a passive autofocus system with low computational complexity. This system uses a novel contrast measurement to determine degree of image sharpness, which can better reflect the information about image discontinuities. In order to gauge the performance of this measurement, a modified peak search strategy is used in the experiments. The experimental results from several typical image sequences validate the effectiveness of the proposed method.     

A Non-Line-of-Sight mitigation localization algorithm for sensor networks using clustering analysis

Non-Line-of-Sight propagation of wireless signal has an impact on measured distances in range-based localization and will bias the final localization results. A new localization algorithm is proposed in this paper to mitigate Non-Line-of-Sight errors when there are more than enough anchor nodes deployed around the node to be located. This algorithm utilizes multi-round clustering analysis to filter the pre-located estimators which derive from all possible subsets of measured distances. In each round, the method density-based spatial clustering of applications with noise is adopted. Simulations show that the proposed algorithm can effectively improve localization accuracy not only when the measured distances with Non-Line-of-Sight error are minor but also under the condition that all of them suffer random Non-Line-of-Sight error.     

Runtime home mapping for effective memory resource usage

In tiled Chip Multiprocessors (CMPs) last-level cache (LLC) banks are usually shared but distributed among the tiles. A static mapping of cache blocks to the LLC banks leads to poor efficiency since a block may be mapped away from the tiles actually accessing it. Dynamic policies either rely on the static mapping of blocks to a set of banks (D-NUCA) or rely on the OS to dynamically load pages to statically mapped addresses (first-touch).     

Telerobot-enabled HUB-CI model for collaborative lifecycle management of design and prototyping

The HUB-CI model is investigated in a telerobotic system in a client/server network to manage the lifecycle of engineering design and prototyping. The purpose of this platform is to support collaborative engineering design and proof of concept to enhance distributed team collaboration and resource utilization. The suggested platform is exemplified in two collaboration support tools and a physical prototyping platform. Structured Co-Insight Management is developed to support innovative idea exchanges and the consensus decision-making during the design process. Conflict/error detection management helps preventing conflicts and errors during the lifecycle of design and development. Physical collaboration over the network occurs when a team controls the telerobot operation during prototyping and testing in design cycles. A pilot system is implemented with a group project for the design of an electronic circuit (including both hardware and software designs). The functional assessment method is used to compare this platform to other collaborative design tools. The system presented offers unique qualitative advantages as an integrated collaboration support system.     

Quick Activation of Optimized Zeolites with Microwave Heating and Utilization of Zeolites for Reusable Desiccant

Effectiveness of microwave heating in an activation treatment of zeolites was studied and utilization of zeolites for reusable desiccant was examined. X zeolite was chosen as a target material for its large adsorption capacity. Na-X zeolite easily caused a thermal runaway by microwave radiation of 500 W but Ca contained X zeolite merely reached ca. 573 K under the same conditions. Mixtures of Na-X and Ca-X with suitably mixed ratios did not cause the thermal runaway and their heating temperatures were controlled (>573 K) at will. Under the most suitable conditions, the mixture reached a dehydration degree of 92%. A degradation degree of adsorptive capacity of the mixture for water was examined after three treatments. The average degradation degree was 1.5% per treatment. The heating method is promising as a quick and easy technique to activate zeolite. By applying the method, the zeolites with suitable mixing ratios are usable as a reusable desiccant for home use.     

High oleic acid oil suppresses lung tumorigenesis in mice through the modulation of extracellular signal-regulated kinase cascade

This study was undertaken to estimate the effect of dietary high oleic acid oil (OA) on 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK)-induced lung tumorigenesis in mice. Diet containing 10% oil was fed to mice through experimental periods. On day 30 after NNK injection (100 mg/kg body weight, i.p.), the treatment increased the level of prostaglandin E₂ (PGE₂) as well as proliferating cell nuclear antigen, a marker of cell proliferation in a high linoleic acid oil (LA)-fed group but not in an OA-fed group. The NNK treatment also induced the activation of an extracellular signal-regulated kinase (Erk) cascade (Erk, Mek and Raf-1) in an LA-fed group. On the other hand, OA feeding abolished the NNK-induced activation of the Erk cascade. In conjugation with these events, OA feeding reduced lung tumor incidence and tumor multiplicity (percentage of mice with tumors) in mice compared with LA feeding at the 20th experimental week. These results suggest that OA suppresses lung tumorigenesis and that this suppression is correlated with the inhibition of PGE₂ production and inactivation of the Erk cascade.