Template Matching using Statistical Model and Parametric Template for Multi-Template

This paper represents a template matching using statistical model and parametric template for multi-template. This algorithm consists of two phases: training and matching phases. In the training phase, the statistical model created by principal component analysis method (PCA) can be used to synthesize multi-template. The advantage of PCA is to reduce the variances of multi-template. In the matching phase, the normalized cross correlation (NCC) is employed to find the candidates in inspection images. The relationship between image block and multi-template is built to use parametric template method. Results show that the proposed method is more efficient than the conventional template matching and parametric template. Furthermore, the proposed method is more robust than conventional template method.

Coordinated Multi-User Spectrum Sharing in Distributed Antenna-Based Cognitive Radio Systems

Spectrum sharing for efficient reuse of licensed spectrum is an important concept for cognitive radio technologies.In a spectrum-sharing system(SSS),deploying the antennas in a distributed manner can offer a new spatial dimension for the efficient reuse of licensed frequency bands.To improve the whole performance of multiple secondary users(SUs),this paper addresses the problem of coordinated multi-SU spectrum sharing in a distributed antenna-based SSS.By adopting the Hungarian method,the primal decomposition method and pricing policy,we propose a coordinated multi-user transmission scheme,so as to maximize the sum-rate of SUs.Simulation results show that the proposed method can significantly enhance the system performance,and the computational complexity is low.

Resource selection of moose(Alces alces cameloides) and their response to human disturbances in the northwestern slope of Lesser Khingan Mountains, northeastern China

Moose （Alces alces cameloides） is typically representative of the fauna of the frigid temperate zone and has been put on the Chinese second priority list of protected animals. The moose of northeast China is on the southern most edge of its distribution in Asia. To study resource selection characteristics of moose and their response to human distur- bances and forest resource variables, the field work was conducted in Heilongiiang Provincial Shengshan Forestry Farm, which is located in the northwestern slope of Lesser Khingan Mountains, northeastern China, from January to March in both 2006 and 2007. A total of 428 plots were examined within the study area. Signs of moose use were found in 19 plots. Based on the analysis of resource selection function, we found that moose selected areas with higher densities of mixed deciduous broadleaf patch and mixed coniferous and broad leaf patch, and a higher NDVI value. Moose avoided settlement 6 km away and remained low probability of occurrence within 3 km from roads,

HIHO Decoding Algorithms of Turbo Product Codes for High Rate Optical Communications

This paper presents a new Hard-Input Hard-Output (HIHO) iterative decoding algorithm for Turbo Product Codes (TPC), and especially describes the BCH-TPC codes aiming to alleviate error propagation and lower error floor. This algorithm mainly emp hasizes a decision mechanism for bit-flips, which thoroughly evaluates four different aspects of the decoding process, properly weighs and combines their respective reliability measures, and then employs the combined measure to make a judgment with regard to whether any particular bit should be flipped or not. Simulations result in a very steep Bit Error Rate (BER) curve indicating that a high-level net coding gain can be expected with a reasonable complexity. The simplicity and effectiveness of this HIHO decoding algorithm makes it a p romising candidate for the application in future high-speed fiber optical communications.

Industrial Fusion Cascade Detection of Solder Joint

With the remarkable advancements in machine vision research and its ever-expanding applications,scholars have increasingly focused on harnessing various vision methodologies within the industrial realm.Specifically,detecting vehicle floor welding points poses unique challenges,including high operational costs and limited portability in practical settings.To address these challenges,this paper innovatively integrates template matching and the Faster RCNN algorithm,presenting an industrial fusion cascaded solder joint detection algorithm that seamlessly blends template matching with deep learning techniques.This algorithm meticulously weights and fuses the optimized features of both methodologies,enhancing the overall detection capabilities.Furthermore,it introduces an optimized multi-scale and multi-template matching approach,leveraging a diverse array of templates and image pyramid algorithms to bolster the accuracy and resilience of object detection.By integrating deep learning algorithms with this multi-scale and multi-template matching strategy,the cascaded target matching algorithm effectively accurately identifies solder joint types and positions.A comprehensive welding point dataset,labeled by experts specifically for vehicle detection,was constructed based on images from authentic industrial environments to validate the algorithm’s performance.Experiments demonstrate the algorithm’s compelling performance in industrial scenarios,outperforming the single-template matching algorithm by 21.3%,the multi-scale and multitemplate matching algorithm by 3.4%,the Faster RCNN algorithm by 19.7%,and the YOLOv9 algorithm by 17.3%in terms of solder joint detection accuracy.This optimized algorithm exhibits remarkable robustness and portability,ideally suited for detecting solder joints across diverse vehicle workpieces.Notably,this study’s dataset and feature fusion approach can be a valuable resource for other algorithms seeking to enhance their solder joint detection capabilities.This work thus not only presents a novel and effective solution for industrial solder joint detection but lays the groundwork for future advancements in this critical area.

Preparation and investigation of Pd doped Cu catalysts for selective hydrogenation of acetylene

A series of PdCu bimetallic catalysts with low Cu and Pd loadings and different Cu:Pd atomic ratios were prepared by conventionally sequential impregnation(CSD)and modified sequential impregnation(MSI)of Cu and Pd for selective hydrogenation of acetylene.Characterization indicates that the supported copper(I)nitrate in the PdCu bimetallic catalysts prepared by MSI can be directly reduced to Cu metal particles due to the hydrogen spillover from Pd to Cu(NO3)2 crystals.In addition,for the catalysts prepared by MSI,Pd atoms can form PdCu alloy on the surface of metal particles,however,for the catalysts prepared by CSI,Pd tends to migrate and exist below the surface layer of Cu.Reaction results indicate that compared with CSI,the MSI method enables samples to possess preferable stability as well as comparable reaction activity.This should be due to the MSI method in favor of the formation of PdCu alloy on the surface of metal particles.Moreover,even Pd loading is super low,<0.045 wt-%in this study,by through adjusting Cu loading to an appropriate value,attractive reactivity and selectivity still can be achieved.

Carbon coated Au/TiO_2 mesoporous microspheres: a novel selective photocatalyst

Photocatalysts with desirable selectivity to transformation and purification of targeted pollutants are of great importance in water purification. Here, we demonstrate that selective photocatalysis can be realized by the assistance of gold-enhanced selective adsorption onto carbon-coated Au/TiO2 mesoporous microspheres （Au/TiO2@C-MM）, which were prepared via a surfactant-assisted two-step method that involved the assembly of oleic acid-stabilized titania and gold nanoparticles into colloidal spheres in an emulsion using sodium dodecyl sulfate as a surfactant and the conversion of the surfactants into carbon under annealing in Ar. Due to the negatively charged amorphous carbon, the mesoporous structure, and the surface plasmon resonance absorption of the Au components, the Au/TiO2@C-MM shows enhanced charge- and size-selective adsorption prop- erties, which enables the materials to have high selectivity in the photocatalytic process.

On essential topics of BYY harmony learning： Current status, challenging issues, and gene analysis applications

As a supplementary of [Xu L. Front. Electr. Electron. Eng. China, 2010, 5（3）： 281-328], this paper outlines current status of efforts made on Bayesian Ying- Yang （BYY） harmony learning, plus gene analysis appli- cations. At the beginning, a bird＇s-eye view is provided via Gaussian mixture in comparison with typical learn- ing algorithms and model selection criteria. Particularly, semi-supervised learning is covered simply via choosing a scalar parameter. Then, essential topics and demand- ing issues about BYY system design and BYY harmony learning are systematically outlined, with a modern per- spective on Yin-Yang viewpoint discussed, another Yang factorization addressed, and coordinations across and within Ying-Yang summarized. The BYY system acts as a unified framework to accommodate unsupervised, su- pervised, and semi-supervised learning all in one formu- lation, while the best harmony learning provides novelty and strength to automatic model selection. Also, mathe- matical formulation of harmony functional has been ad- dressed as a unified scheme for measuring the proximity to be considered in a BYY system, and used as the best choice among others. Moreover, efforts are made on a number of learning tasks, including a mode-switching factor analysis proposed as a semi-blind learning frame- work for several types of independent factor analysis, a hidden Markov model （HMM） gated temporal fac- tor analysis suggested for modeling piecewise stationary temporal dependence, and a two-level hierarchical Gaus- sian mixture extended to cover semi-supervised learning, as well as a manifold learning modified to facilitate au- tomatic model selection. Finally, studies are applied to the problems of gene analysis, such as genome-wide asso- ciation, exome sequencing analysis, and gene transcrip- tional regulation.

Efficient and selective electro-reduction of nitrobenzene by the nano-structured Cu catalyst prepared by an electrodeposited method via tuning applied voltage

Pollution caused by toxic nitrobenzene has been a widespread environmental concern. Selective reduction of nitrobenzene to aniline is beneficial to further efficient and cost-effective biologic treatment. Electro- chemical reduction is a promising method and Cu-based catalysts have been found to be an efficient cathode material for this purpose. In this work, Cu catalysts with different morphologies were fabricated on Ti plate using a facile electrodepositon method via tuning the applied voltage. The dendritic nano-structured Cu catalysts obtained at high applied voltages exhibited an excellent efficiency and selectivity toward the reduction of nitro- benzene to aniline. Effects of the working potential and initial nitrobenzene concentration on the selective reduction of nitrobenzene to aniline using the Cu/Ti electrode were investigated. A high rate constant of 0.0251 mini and 97.1% aniline selectivity were achieved. The fabri- cated nano-structured Cu catalysts also exhibited good stability. This work provides a facile way to prepare highly efficient, cost-effective, and stable nano-sWuctured electro- catalysts for pollutant reduction.

A transposon-introduced G-quadruplex motif is selectively retained and constrained to downregulate CYP321A1

Insects utilize xenobiotic compounds to up-and downregulate cytochrome P450 monooxygenases(P450s)involved in detoxification of toxic xenobiotics including phytochemicals and pesticides.G-quadruplexes(G4)-forming DNA motifs are enriched in the promoter regions of transcription factors and function as cis-acting elements to regulate these genes.Whether and how P450s gain and keep G4 DNA motifs to regulate their expression still remain unexplored.Here,we show that CYP321A1,a xenobiotic-metabolizing P450 from Helicoverpa zea,a polyphagous insect of economic importance,has acquired and preserved a G4 DNA motif by selectively retaining a transposon known as HzIS1-3 that carries this G4 DNA motif in its promoter region.The HzIS1-3 G4 DNA motif acts as a silencer to suppress the constitutive and induced expression of CYP321A1 by plant allelochemicals flavone and xanthotoxin through folding into an intramolecular parallel or hybrid-1 conformation in the absence or presence of K^(+).The G4 ligand N-methylmesoporphyrin IX(NMM)strengthens the silencing effect of HzIS1-3 G4 DNA motif by switching its structure from hybrid-1 to hybrid-2.The enrichment of transposons in P450s and other environment-adaptation genes implies that selective retention of G4 DNA motif-carrying transposons may be the main evolutionary route for these genes to obtain G4 DNA motifs.

Selective Insertion in Copolymerization of Ethylene and Styrene Catalyzed by Half-Titanocene System Bearing Ketimide Ligand： A Theoretical Study

The copolymerization of ethylene and styrene can be efficiently carried out by using Cp＊TiCl2（N=CtBu2）/ MAO （Cp＊=η5-C5Me5） system, yielding the poly（ethylene-co-styrene）s with isolated styrene units. In order to in- vestigate the reasons for formation of the structure, the mechanism of copolymerization, especially the selective in- sertion of ethylene and styrene, is studied in detail by density functional theory （DFT） method. At the initiation stage, insertion of ethylene is kinetically more favorable than insertion of styrene, and insertion of styrene kinet- ically and thermodynamically prefers 2,1-insertion. That is different from the conventional half-titanocene system, in which the 1,2-insertion is favorable. At chain propagation stage, the computational results suggest that the con- tinuous insertion of styrene is hard to occur at room temperature due to the high free energy barriers （28.90 and 35.04 kcal/mol for 1,2-insertion, and 29.15 and 34.00 kcal/mol for 2,1-insertion） and thermodynamically unfavora- ble factors in two different conditions. That is mainly attributed to the steric hindrance between the coming styrene and chain-end styrene or ketimide ligand. The computational results are in good agreement with the experimental data.