Phase-object detection by use of double-exposure fringe-modulated speckle patterns

We study the properties of a double-exposure image specklegram of a diffuse object obtained by use of a double-aperture pupil. A phase object is placed in front of one aperture during the first or the second exposure. Also, it is assumed that a uniform displacement of the diffuser between exposures is produced. The recorded specklegram is coherently illuminated and analyzed by Fourier transform operations. The average intensity distribution and the interference fringe visibility in the Fourier plane are investigated. On this basis, an alternative interference technique to detect phase objects is proposed.     

Multiplierless and fully pipelined JPEG compression soft IP targeting FPGAs

This paper presents the design of a soft IP for JPEG compression targeted for high performance in a FPGA device. The JPEG compressor architecture achieves high throughput with a deep and optimized pipeline and with a multiplierless datapath architecture. The JPEG compressor architecture was designed in a hierarchical and modular fashion and the details of the global architecture and of its modules are presented in this paper. A modular and strictly structural VHDL design is followed to develop the JPEG compressor soft IP. The VHDL codes were synthesized to Altera and Xilinx FPGAs. Synthesis results and relevant performance comparisons with related works are presented. Our high throughput compressor is able to compress 39.8 millions of pixels per second when mapped onto an Altera FLEX 10KE FPGA. Our JPEG soft IP mapped to FLEX 10KE low cost FPGA is able to compress 115 images per second in SDTV resolution (720 × 480 pixels). Considering this SDTV resolution our design is worthy as a core of an M-JPEG video compressor, reaching a real time processing rate of 30 fps, once mapped to the FLEX 10KE FPGA device.     

Thermal–hydraulic passive system reliability-based design approach

In order to enhance the safety of new advanced reactors, optimization of the design of the implemented passive systems is required. Therefore, a reliability-based approach to the design of a thermal–hydraulic passive system is being considered, and a limit state function (LSF)-based approach elicited from mechanical reliability is developed. The concept of functional failure, i.e., the possibility that the load will exceed the capacity in a reliability physics framework, in terms of performance parameter is introduced here for the reliability evaluation of a natural circulation passive system, designed for decay heat removal of innovative light water reactors. Water flow rate circulating through the system is selected as passive system performance characteristic parameter and the related limit state or performance function is defined. The probability of failure of the system is assessed in terms of safety margin, corresponding to the LSF. Results help the designer to determine the allowable limits or set the safety margin for the system operation parameters, to meet the safety and reliability requirements.     

Fast detection of exact clones in business process model repositories

As organizations reach higher levels of business process management maturity, they often find themselves maintaining very large process model repositories, representing valuable knowledge about their operations. A common practice within these repositories is to create new process models, or extend existing ones, by copying and merging fragments from other models. We contend that if these duplicate fragments, a.k.a. exact clones, can be identified and factored out as shared subprocesses, the repository's maintainability can be greatly improved. With this purpose in mind, we propose an indexing structure to support fast detection of clones in process model repositories. Moreover, we show how this index can be used to efficiently query a process model repository for fragments. This index, called RPSDAG, is based on a novel combination of a method for process model decomposition (namely the Refined Process Structure Tree), with established graph canonization and string matching techniques. We evaluated the RPSDAG with large process model repositories from industrial practice. The experiments show that a significant number of non-trivial clones can be efficiently found in such repositories, and that fragment queries can be handled efficiently.     

The roles of textural images in improving land-cover classification in the Brazilian Amazon

Texture has long been recognized as valuable in improving land-cover classification, but how data from different sensors with varying spatial resolutions affect the selection of textural images is poorly understood. This research examines textural images from the Landsat Thematic Mapper (TM), ALOS (Advanced Land Observing Satellite) PALSAR (Phased Array type L-band Synthetic Aperture Radar), the SPOT (Satellite Pour l’Observation de la Terre) high-resolution geometric (HRG) instrument, and the QuickBird satellite, which have pixel sizes of 30, 12.5, 10/5, and 0.6 m, respectively, for land-cover classification in the Brazilian Amazon. GLCM (grey-level co-occurrence matrix)-based texture measures with various sizes of moving windows are used to extract textural images from the aforementioned sensor data. An index based on standard deviations and correlation coefficients is used to identify the best texture combination following separability analysis of land-cover types based on training sample plots. A maximum likelihood classifier is used to conduct the land-cover classification, and the results are evaluated using field survey data. This research shows the importance of textural images in improving land-cover classification, and the importance becomes more significant as the pixel size improved. It is also shown that texture is especially important in the case of the ALOS PALSAR and QuickBird data. Overall, textural images have less capability in distinguishing land-cover types than spectral signatures, especially for Landsat TM imagery, but incorporation of textures into radiometric data is valuable for improving land-cover classification. The classification accuracy can be improved by 5.2–13.4% as the pixel size changes from 30 to 0.6 m.     

Fabrication of microstructures on different materials by diode-pumped solid state laser writing for microfluidics applications

Laser writing attached many attentions for fabrication micro-channels in microfluidics devices and lab-on-chip devices for biomedical applications. In this study, micro-channels were fabricated on different materials as masters using nanosecond diode-pumped solid state (DPSS) laser writing for imprinting on glass and polymer microfluidics devices. Good quality microstructures were fabricated on silicon, nickel alloy, cooper/brass and alumina, respectively by laser writing which proved that the nanosecond DPSS laser is suitable for rapid prototyping and rapid manufacturing of surface microstructures on different substrates as mask-less exposure system of imprinting.     

3D Face Recognition Using Simulated Annealing and the Surface Interpenetration Measure

This paper presents a novel automatic framework to perform 3D face recognition. The proposed method uses a Simulated Annealing-based approach (SA) for range image registration with the Surface Interpenetration Measure (SIM), as similarity measure, in order to match two face images. The authentication score is obtained by combining the SIM values corresponding to the matching of four different face regions: circular and elliptical areas around the nose, forehead, and the entire face region. Then, a modified SA approach is proposed taking advantage of invariant face regions to better handle facial expressions. Comprehensive experiments were performed on the FRGC v2 database, the largest available database of 3D face images composed of 4,007 images with different facial expressions. The experiments simulated both verification and identification systems and the results compared to those reported by state-of-the-art works. By using all of the images in the database, a verification rate of 96.5 percent was achieved at a False Acceptance Rate (FAR) of 0.1 percent. In the identification scenario, a rank-one accuracy of 98.4 percent was achieved. To the best of our knowledge, this is the highest rank-one score ever achieved for the FRGC v2 database when compared to results published in the literature.     

A fast time-domain algorithm for the simulation of switching powerconverters

An efficient algorithm for the simulation of switched-mode power converters is developed. A Chebyshev series expansion is used to effectively solve the differential equations describing the system in each topology. The power of the new simulation technique lies both in the simple, but accurate, polynomial approximation for the state transition matrices and in the ability to explicitly obtain the instants at which the switching of the circuit topology takes place. The simulation technique is illustrated with reference to a simple Buck converter operating at a constant frequency. The derivation of the new algorithm is presented and its performance is analyzed. The case of a rapidly varying input forcing function is analyzed. Examples illustrating the generality and the computational efficiency of the algorithm are presented