Path Planner for Intelligent Laser Surface Modification

An optimal algorithm of manufacturing path planner for intelligent laser surface modification is presented. Elements included in the optimal objective have been analyzed. A 6-D manufacture trace that satisfies the requirements of special craft and 5-axis laser processing robot system has been generated from the path planner by method of parallel section in which combinations of modification spots size with curvature of processing surfaces and modification craft parameters are considered. Related experiments have been successfully carried out with the computer integrated multifunctional laser manufacturing system.

Adaptive evolution of MRGX2, a human sensory neuron specific gene involved in nociception

MRGX2, a G-protein-coupled receptor, is specifically expressed in the sensory neurons of the human peripheral nervous system and involved in nociception. Here, we studied DNA polymorphism patterns and evolution of the MRGX2 gene in world-wide human populations and the representative nonhuman primate species. Our results demonstrated that MRGX2 had undergone adaptive changes in the path of human evolution, which were likely caused by Darwinian positive selection. The patterns of DNA sequence polymorphisms in human populations showed an excess of derived substitutions, which against the expectation of neutral evolution, implying that the adaptive evolution of MRGX2 in humans was a relatively recent event. The reconstructed secondary structure of the human MRGX2 revealed that three of the four human-specific amino acid substitutions were located in the extra-cellular domains. Such critical substitutions may alter the interactions between MRGX2 protein and its ligand, thus, potentially led to adaptive changes of the pain-perception-related nervous system during human evolution. (c) 2005 Elsevier B.V. All rights reserved.

Research of Face Location System Based on Human Vision Simulations

In this paper we present a robust face location system based on human vision simulations to automatically locate faces in color static images. Our method is divided into four stages. In the first stage we use a gauss low-pass filter to remove the fine information of images, which is useless in the initial stage of human vision. During the second and the third stages, our technique approximately detects the image regions, which may contain faces. During the fourth stage, the existence of faces in the selected regions is verified. Having combined the advantages of Bottom-Up Feature Based Methods and Appearance-Based Methods, our algorithm performs well in various images, including those with highly complex backgrounds.

SOC dynamic power management using artificial neural network

Dynamic Power Management (DPM) is a technique to reduce power consumption of electronic system by selectively shutting down idle components. In this article we try to introduce back propagation network and radial basis network into the research of the system-level power management policies. We proposed two PM policies-Back propagation Power Management (BPPM) and Radial Basis Function Power Management (RBFPM) which are based on Artificial Neural Networks (ANN). Our experiments show that the two power management policies greatly lowered the system-level power consumption and have higher performance than traditional Power Management(PM) techniques-BPPM is 1.09-competitive and RBFPM is 1.08-competitive vs. 1.79 . 1.45 . 1.18-competitive separately for traditional timeout PM . adaptive predictive PM and stochastic PM.

An adaptive frequency synthesizer architecture reducing reference sidebands

An adaptive phase-locked loop (PLL) frequency synthesizer architecture for reducing reference sidebands at the output of the frequency synthesizer is described. The architecture combines two tuning loops: one is the main loop for locking the PLL frequency synthesizer and operating all the time, the other one is auxiliary loop for reducing reference sidebands and operating only when the main loop is closely locked. A 1.8V 1GHz fully integrated CMOS dual-loop frequency synthesizer is designed in a 0.18um CMOS process. The suppression of the reference sidebands of the proposed frequency synthesizer is 13.8dB more than that of the general frequency synthesizer.

Pipeline Architecture and Parallel Computation-Based Real-Time Stereovision Tracking System for Surgical Navigation

This paper studies the development of a real-time stereovision system to track multiple infrared markers attached to a surgical instrument. Multiple stages of pipeline in field-programmable gate array (FPGA) are developed to recognize the targets in both left and right image planes and to give each target a unique label. The pipeline architecture includes a smoothing filter, an adaptive threshold module, a connected component labeling operation, and a centroid extraction process. A parallel distortion correction method is proposed and implemented in a dual-core DSP. A suitable kinematic model is established for the moving targets, and a novel set of parallel and interactive computation mechanisms is proposed to position and track the targets, which are carried out by a cross-computation method in a dual-core DSP. The proposed tracking system can track the 3-D coordinate, velocity, and acceleration of four infrared markers with a delay of 9.18 ms. Furthermore, it is capable of tracking a maximum of 110 infrared markers without frame dropping at a frame rate of 60 f/s. The accuracy of the proposed system can reach the scale of 0.37 mm RMS along the x- and y-directions and 0.45 mm RMS along the depth direction (the depth is from 0.8 to 0.45 m). The performance of the proposed system can meet the requirements of applications such as surgical navigation, which needs high real time and accuracy capability.

Pipeline Architecture and Parallel Computation-Based Real-Time Stereovision Tracking System for Surgical Navigation

This paper studies the development of a real-time stereovision system to track multiple infrared markers attached to a surgical instrument. Multiple stages of pipeline in field-programmable gate array (FPGA) are developed to recognize the targets in both left and right image planes and to give each target a unique label. The pipeline architecture includes a smoothing filter, an adaptive threshold module, a connected component labeling operation, and a centroid extraction process. A parallel distortion correction method is proposed and implemented in a dual-core DSP. A suitable kinematic model is established for the moving targets, and a novel set of parallel and interactive computation mechanisms is proposed to position and track the targets, which are carried out by a cross-computation method in a dual-core DSP. The proposed tracking system can track the 3-D coordinate, velocity, and acceleration of four infrared markers with a delay of 9.18 ms. Furthermore, it is capable of tracking a maximum of 110 infrared markers without frame dropping at a frame rate of 60 f/s. The accuracy of the proposed system can reach the scale of 0.37 mm RMS along the x- and y-directions and 0.45 mm RMS along the depth direction (the depth is from 0.8 to 0.45 m). The performance of the proposed system can meet the requirements of applications such as surgical navigation, which needs high real time and accuracy capability.

Adaptive fading Kalman filter with an application

A new adaptive state estimation algorithm, namely adaptive fading Kalman filter (AFKF), is proposed to solve the divergence problem of Kalman filter. A criterion function is constructed to measure the optimality of Kalman filter. The forgetting factor in AFKF is adaptively adjusted by minimizing the defined criterion function using measured outputs. The algorithm remains convergent and tends to be optimal in the presence of model errors. It has been successfully applied to the headbox of a paper-making machine for state estimation.

Intelligent control of avalanched photodiode to get optimal state

To improve the sensitivity of our laser radar system, we provided a set of control method for APDs (Avalanched Photodiodes) based on single-chip computer together with the circuits dealing with noise and temperature. It adjusts the voltages intelligently and maintains the APD's optimal working status.

Automated voltammetric system for shipboard determination of metal speciation in sea water

An automated and semi-intelligent voltammetric system is described for trace metal analysis. The system consists of a voltammeter interfaced with a personal computer, a sample changer, 2 peristaltic pumps, a motor burette and a hanging mercury drop electrode. The system carries out fully automatically approximately 5 metal determinations per hour (including at least 3 repetitive scans and calibration by standard addition) at trace levels encountered in clean sea water. The computer program decides what level of standard addition to use and evaluates the data prior to switching to the next sample. Alternatively, the system can be used to carry out complexing ligand titration with copper whilst recording the labile copper concentration; in this mode up to 8 full titrations are carried out per day. Depth profiles for chromium speciation in the Mediterranean Sea and a profile for copper complexing ligand concentrations in the North Atlantic Ocean measured on board-ship with the system are presented. The chromium speciation was determined using a new method to differentiate between Cr(III) and Cr(VI) utilizing adsorption of Cr(III) on silica particles.

Deformation Monitoring and Forecasting Model Study Based on Grey System Theory

The grey system theory studies the uncertainty of small sample size problems. This paper using grey system theory in the deformation monitoring field, based on analysis of present grey forecast models, developed the spatial multi-point model. By using residual modification, the spatial multi-point residual model eras developed in further study. Then, combined with the sedimentation data of Xiaolangdi Multipurpose Dam, the results are compared and analyzed, the conclusion has been made and the advantages of the residual spatial multi-point model has been proved.

An integrated aurora image retrieval system: AuroraEye

With the digital all-sky imager (ASI) emergence in aurora research, millions of images are captured annually. However, only a fraction of which can be actually used. To address the problem incurred by low efficient manual processing, an integrated image analysis and retrieval system is developed. For precisely representing aurora image, macroscopic and microscopic features are combined to describe aurora texture. To reduce the feature dimensionality of the huge dataset, a modified local binary pattern (LBP) called ALBP is proposed to depict the microscopic texture, and scale-invariant Gabor and orientation-invariant Gabor are employed to extract the macroscopic texture. A physical property of aurora is inducted as region features to bridge the gap between the low-level visual features and high-level semantic description. The experiments results demonstrate that the ALBP method achieves high classification rate and low computational complexity. The retrieval simulation results show that the developed retrieval system is efficient for huge dataset. (c) 2010 Elsevier Inc. All rights reserved.

Genome-wide analysis of restriction-modification system in unicellular and filamentous cyanobacteria

Cyanobacteria are an ancient group of gram-negative bacteria with strong genome size variation ranging from 1.6 to 9.1 Mb. Here, we first retrieved all the putative restriction-modification (RM) genes in the draft genome of Spirulina and then performed a range of comparative and bioinformatic analyses on RM genes from unicellular and filamentous cyanobacterial genomes. We have identified 6 gene clusters containing putative Type I RMs and 11 putative Type II RMs or the solitary methyltransferases (MTases). RT-PCR analysis reveals that 6 of 18 MTases are not expressed in Spirulina, whereas one hsdM gene, with a mutated cognate hsdS, was detected to be expressed. Our results indicate that the number of RM genes in filamentous cyanobacteria is significantly higher than in unicellular species, and this expansion of RM systems in filamentous cyanobacteria may be related to their wide range of ecological tolerance. Furthermore, a coevolutionary pattern is found between hsdM and hsdR, with a large number of site pairs positively or negatively correlated, indicating the functional importance of these pairing interactions between their tertiary structures. No evidence for positive selection is found for the majority of RMs, e. g., hsdM, hsdS, hsdR, and Type II restriction endonuclease gene families, while a group of MTases exhibit a remarkable signature of adaptive evolution. Sites and genes identified here to have been under positive selection would provide targets for further research on their structural and functional evaluations.

Genome-wide analysis of restriction-modification system in unicellular and filamentous cyanobacteria

Cyanobacteria are an ancient group of gram-negative bacteria with strong genome size variation ranging from 1.6 to 9.1 Mb. Here, we first retrieved all the putative restriction-modification (RM) genes in the draft genome of Spirulina and then performed a range of comparative and bioinformatic analyses on RM genes from unicellular and filamentous cyanobacterial genomes. We have identified 6 gene clusters containing putative Type I RMs and 11 putative Type II RMs or the solitary methyltransferases (MTases). RT-PCR analysis reveals that 6 of 18 MTases are not expressed in Spirulina, whereas one hsdM gene, with a mutated cognate hsdS, was detected to be expressed. Our results indicate that the number of RM genes in filamentous cyanobacteria is significantly higher than in unicellular species, and this expansion of RM systems in filamentous cyanobacteria may be related to their wide range of ecological tolerance. Furthermore, a coevolutionary pattern is found between hsdM and hsdR, with a large number of site pairs positively or negatively correlated, indicating the functional importance of these pairing interactions between their tertiary structures. No evidence for positive selection is found for the majority of RMs, e. g., hsdM, hsdS, hsdR, and Type II restriction endonuclease gene families, while a group of MTases exhibit a remarkable signature of adaptive evolution. Sites and genes identified here to have been under positive selection would provide targets for further research on their structural and functional evaluations.

Evaluation of a combined wavelet and a combined principal component analysis classification system for BCG diagnostic problem

Heart disease is one of the main factor causing death in the developed countries. Over several decades, variety of electronic and computer technology have been developed to assist clinical practices for cardiac performance monitoring and heart disease diagnosis. Among these methods, Ballistocardiography (BCG) has an interesting feature that no electrodes are needed to be attached to the body during the measurement. Thus, it is provides a potential application to asses the patients heart condition in the home. In this paper, a comparison is made for two neural networks based BCG signal classification models. One system uses a principal component analysis (PCA) method, and the other a discrete wavelet transform, to reduce the input dimensionality. It is indicated that the combined wavelet transform and neural network has a more reliable performance than the combined PCA and neural network system. Moreover, the wavelet transform requires no prior knowledge of the statistical distribution of data samples and the computation complexity and training time are reduced.