3D Road Network Modeling and Road Structure Recognition in Internet of Vehicles

Internet of Vehicles (IoV) is a new system that enables individual vehicles to connect with nearby vehicles,people, transportation infrastructure, and networks, thereby realizing amore intelligent and efficient transportationsystem. The movement of vehicles and the three-dimensional (3D) nature of the road network cause the topologicalstructure of IoV to have the high space and time complexity.Network modeling and structure recognition for 3Droads can benefit the description of topological changes for IoV. This paper proposes a 3Dgeneral roadmodel basedon discrete points of roads obtained from GIS. First, the constraints imposed by 3D roads on moving vehicles areanalyzed. Then the effects of road curvature radius (Ra), longitudinal slope (Slo), and length (Len) on speed andacceleration are studied. Finally, a general 3D road network model based on road section features is established.This paper also presents intersection and road section recognition methods based on the structural features ofthe 3D road network model and the road features. Real GIS data from a specific region of Beijing is adopted tocreate the simulation scenario, and the simulation results validate the general 3D road network model and therecognitionmethod. Therefore, thiswork makes contributions to the field of intelligent transportation by providinga comprehensive approach tomodeling the 3Droad network and its topological changes in achieving efficient trafficflowand improved road safety.

Synthesis, Crystal Structure and Anion Recognition Property of a Flexible Urea-functionalized Receptor

A flexible urea-functionalized receptor bearing two p-nitrobenzene units was designed and synthesized from the reaction of precursors 4-nitrophenyl isocyanate and 1,2-bis（2?-aminophenoxy） benzene. The receptor was characterized by 1 H NMR, MS, FTIR and elemental analysis, and the crystal structure of the receptor was determined by X-ray diffraction analysis. The crystal belongs to the orthorhombic system, space group Pca21 with a = 12.740（2）, b =14.133（3）, c = 15.842（3） ?, V = 2852.4（9） ?3, Z = 4, Mr = 620.57, Dc = 1.445 g/cm3, F（000） = 1288,= 0.0585 and wR = 0.1032 for 3177 observed reflections（Ⅰ > 2σ（Ⅰ））, and R = 0.1304 and wR =for all data. The results show that the receptor displays selective recognition ability for H2PO4– in DMSO with a series of anions using UV-Vis absorption spectra technique. Furthermore, the coordination reaction of the receptor with H2PO4– was investigated via UV-Vis spectra and 1 H NMR.The stoichiometric ratio and the association constant（Ka） of the coordination reaction were obtained as well.

Synthesis, Crystal Structure and Recognition Properties of 2-(5-(4-Chlorophenyl)-1-phenyl-4,5-dihydro-1H-pyrazol-3-yl)pyridine

The title compound 2-（5-（4-chlorophenyl）-1-phenyl-4,5-dihydro-1H-pyrazol-3-yl）- pyridine（C20H16ClN3, Mr = 333.81） has been synthesized and its crystal structure was determined by single-crystal X-ray diffraction. The crystal belongs to monoclinic, space group P21/n with a = 10.9925（12）, b = 11.0378（12）, c = 14.2751（18） , β = 98.074（11）°, V = 1714.9（3）3, Z = 4, Dc = 1.293 g/cm3, μ（MoKα） = 0.228 mm-1, F（000） = 696, the final R = 0.0521 and wR = 0.1349 for 3495 observed reflections with I 〉 2σ（I）. Intermolecular C–H...π interactions and π-π stacking interactions stabilize the crystal structure. The binding study by fluorescence spectroscope titration showed that the title compound can selectively recognize Fe3＋ in THF solution with fluorescence quenching.

4-Tert-butyl-N′-((2-Hydroxynaphthalen-1-yl)methylene)Benzohydrazide:Synthesis,Crystal Structure and Recognition Properties

A new naphthol-based compound 1, C22 H22 N2 O2, has been designed and synthesized. The structure of the title compound 1 was confirmed by IR, 1 H NMR, 13 C NMR, H RMS, and X-ray single-crystal diffraction. The crystal belongs to the monoclinic system, space group P21/c, with a = 12.888（9）, b = 15.543（10）, c = 9.119（6） ？, β = 94.05（3）°, V = 1822（2） ？3, Z = 4, Dc = 1.263 g/cm3, Mr = 346.41, μ = 0.081 mm-1, F（000） = 736.0, the final R = 0.0452 and wR = 0.1142 for 3404 observed reflections with（I 〉 2σ（I））. The crystal structure of 1 is stabilized by O–H···N, N–H···O, C–H···O hydrogen bonds and π-π interactions. The spectroscopic studies of 1 toward various metal ions were also investigated in 25%（V/V） ethanol aqueous solution, and the result showed that it can selectively recognize Zn2＋ with fluorescence enhancement.

Synthesis,Crystal Structure and Recognition Properties of a New Benzothiazole Derivative：C28H24N4O2S

A benzothiazole-based compound 1, C28H24N4O2S, has been synthesized and characterized by single-crystal X-ray diffraction. It crystallizes in monoclinic, space group P21/c with a = 9.6309（14）, b = 15.230（2）, c = 17.197（3）A, β = 105.222（2）°, V = 2433.9（6） A^3, Z = 4, F（000） = 1008, Dc = 1.311 Mg/m^3, Mr = 480.57, μ = 0.166 mm^-1, the final R = 0.0509 and wR = 0.1481 for 6643 observed reflections with I 〉 2σ（I）. The crystal structure of compound 1 is stabilized by C–H…O, N–H…N, N–H…O, O–H…N and C–H…N hydrogen bonds. The spectroscopic studies of the title compound toward various metal ions were also investigated in 25%（V/V） ethanol aqueous solution, and the result showed that it can selectively recognize Cu^2＋ with fluorescence quenching.

A Structure Similarity Analysis Method for On－Line Recognition of Handwritten Chinese Characters

ＡＳｔｒｕｃｔｕｒｅＳｉｍｉｌａｒｉｔｙＡｎａｌｙｓｉｓＭｅｔｈｏｄｆｏｒＯｎ－ＬｉｎｅＲｅｃｏｇｎｉｔｉｏｎｏｆＨａｎｄｗｒｉｔｔｅｎＣｈｉｎｅｓｅＣｈａｒａｃｔｅｒｓＬＩＵＪｉａｆｅｎｇ；ＴＡＮＧＪｉａｎｇｌｏｎｇ；ＳＨＵＷｅｎｈａｏ（刘家锋，唐...

Synthesis, Structure Characterization, and Cu^(2+) Recognition of 3-{[3-(Phenylsulfonamido)benzoyl]methylidene}-3,4-dihydroquinoxaline-2(1H)-one

Aryl diketo acid derivatives are one of the most promising HIV-1 integrase（IN） inhibitors. With a view to substitute the critical diketo acid pharmacophore with the diketo benzimidazole unit, the coupling reaction of compound 4 with o-phenylenediamine was carried out. However, the reaction product, compound 5, was confirmed to be 3-{ [ 3- （phenylsulfonamido） benzoyl] methylidene t -3,4-dihydroquinoxaline-2 （1H） -one rather than the 2-benzimidazole derivative by using X-ray diffraction. Owing to its low solubility in water, the evaluation of the anti-HIV IN activity of the synthesized compound 5 could not be carried out. Consequently, the ion-binding properties of compound 5 in the absence of HIV-1 IN were investigated with UV-Vis spectroscopy in organic solvents. The results show that such a compound can selectively recognize Cu^2＋.

An Auto-Grading Oriented Approach for Off-Line Handwritten Organic Cyclic Compound Structure Formulas Recognition

Auto-grading,as an instruction tool,could reduce teachers’workload,provide students with instant feedback and support highly personalized learning.Therefore,this topic attracts considerable attentions from researchers recently.To realize the automatic grading of handwritten chemistry assignments,the problem of chemical notations recognition should be solved first.The recent handwritten chemical notations recognition solutions belonging to the end-to-end trainable category suffered fromthe problem of lacking the accurate alignment information between the input and output.They serve the aim of reading notations into electrical devices to better prepare relevant edocuments instead of auto-grading handwritten assignments.To tackle this limitation to enable the auto-grading of handwritten chemistry assignments at a fine-grained level.In this work,we propose a component-detectionbased approach for recognizing off-line handwritten Organic Cyclic Compound Structure Formulas(OCCSFs).Specifically,we define different components of OCCSFs as objects(including graphical objects and text objects),and adopt the deep learning detector to detect them.Then,regarding the detected text objects,we introduce an improved attention-based encoder-decoder model for text recognition.Finally,with these detection results and the geometric relationships of detected objects,this article designs a holistic algorithm for interpreting the spatial structure of handwritten OCCSFs.The proposedmethod is evaluated on a self-collected data set consisting of 3000 samples and achieves promising results.

Sensor Network Structure Recognition Based on P-law

A sensor graph network is a sensor network model organized according to graph network structure.Structural unit and signal propagation of core nodes are the basic characteristics of sensor graph networks.In sensor networks,network structure recognition is the basis for accurate identification and effective prediction and control of node states.Aiming at the problems of difficult global structure identification and poor interpretability in complex sensor graph networks,based on the characteristics of sensor networks,a method is proposed to firstly unitize the graph network structure and then expand the unit based on the signal transmission path of the core node.This method which builds on unit patulousness and core node signal propagation(called p-law)can rapidly and effectively achieve the global structure identification of a sensor graph network.Different from the traditional graph network structure recognition algorithms such as modularity maximization and spectral clustering,the proposed method reveals the natural evolution process and law of graph network subgroup generation.Experimental results confirm the effectiveness,accuracy and rationality of the proposed method and suggest that our method can be a new approach for graph network global structure recognition.

Structure Studies on Host-Guest Recognition Sensory Systems

Rhodamine B-ethylenediamine-beta-cyclodextrins (RhB-beta-CDen) and rhodamine B-beta-cyclodextrins (RhB-beta-CD) form inclusion complexes with many guest molecules, which can be used as nucleic acid probe. In this paper we determined the most stable conformations of RhB-beta-CDen and RhB-beta-CD by molecular mechanics and dynamics simulation. The interaction between RhB-beta-CDen and two guest molecules, 1-borneol and cyclohexanol, have been investigated both theoretically and experimentally. The results show that the interaction between borneol and RhB-beta-CDen is stronger than that between cyclohexanol and RhB-beta-CDen.

New Recognition about Faulted Structures in Tarim Basin

ＮｅｗＲｅｃｏｇｎｉｔｉｏｎａｂｏｕｔＦａｕｌｔｅｄＳｔｒｕｃｔｕｒｅｓｉｎＴａｒｉｍＢａｓｉｎＩｎｐａｓｔｔｈｒｅｅｙｅａｒｓ，ｔｈｅｃｏｍｐｒｅｈｅｎｓｉｖｅｐｅｔｒｏｌｅｕｍｇｅｏｌｏｇｉｃａｌｔｅａｍｏｆｔｈｅＭｉｎｉｓｔｒｙｏｆＧｅｏｌｏｇ...

Structural plane recognition from three-dimensional laser scanning points using an improved region-growing algorithm based on the robust randomized Hough transform

The staggered distribution of joints and fissures in space constitutes the weak part of any rock mass.The identification of rock mass structural planes and the extraction of characteristic parameters are the basis of rock-mass integrity evaluation,which is very important for analysis of slope stability.The laser scanning technique can be used to acquire the coordinate information pertaining to each point of the structural plane,but large amount of point cloud data,uneven density distribution,and noise point interference make the identification efficiency and accuracy of different types of structural planes limited by point cloud data analysis technology.A new point cloud identification and segmentation algorithm for rock mass structural surfaces is proposed.Based on the distribution states of the original point cloud in different neighborhoods in space,the point clouds are characterized by multi-dimensional eigenvalues and calculated by the robust randomized Hough transform(RRHT).The normal vector difference and the final eigenvalue are proposed for characteristic distinction,and the identification of rock mass structural surfaces is completed through regional growth,which strengthens the difference expression of point clouds.In addition,nearest Voxel downsampling is also introduced in the RRHT calculation,which further reduces the number of sources of neighborhood noises,thereby improving the accuracy and stability of the calculation.The advantages of the method have been verified by laboratory models.The results showed that the proposed method can better achieve the segmentation and statistics of structural planes with interfaces and sharp boundaries.The method works well in the identification of joints,fissures,and other structural planes on Mangshezhai slope in the Three Gorges Reservoir area,China.It can provide a stable and effective technique for the identification and segmentation of rock mass structural planes,which is beneficial in engineering practice.

Structural recognition of ancient Chinese ideographic characters

Ancient Chinese characters, typically the ideographic characters on bones and bronze before Shang Dynasty(16th—11th century B.C.), are valuable culture legacy of history. However the recognition of Ancient Chinese characters has been the task of paleography experts for long. With the help of modern computer technique, everyone can expect to be able to recognize the characters and understand the ancient inscriptions. This research is aimed to help people recognize and understand those ancient Chinese characters by combining Chinese paleography theory and computer information processing technology. Based on the analysis of ancient character features, a method for structural character recognition is proposed. The important characteristics of strokes and basic components or radicals used in recognition are introduced in detail. A system was implemented based on above method to show the effectiveness of the method.

Recognition of Offline Handwritten Arabic Words Using a Few Structural Features

Handwriting recognition is one of the most significant problems in pattern recognition,many studies have been proposed to improve this recognition of handwritten text for different languages.Yet,Fewer studies have been done for the Arabic language and the processing of its texts remains a particularly distinctive problem due to the variability of writing styles and the nature of Arabic scripts compared to other scripts.The present paper suggests a feature extraction technique for offlineArabic handwriting recognition.A handwriting recognition system for Arabic words using a few important structural features and based on a Radial Basis Function(RBF)neural networks is proposed.The methods of feature extraction are central to achieve high recognition performance.The proposed methodology relies on a feature extraction technique based on many structural characteristics extracted from the word skeleton(subwords,diacritics,loops,ascenders,and descenders).In order to reach our purpose,we built our own word database and the proposed system has been successfully tested on a handwriting database of Algerian city names(wilayas).Finally,a simple classifier based on the radial basis function neural network is presented to recognize certain words to verify the reliability of the proposed feature extraction.The experiments on some images of the benchmark IFN/ENIT database show that the proposed system improves recognition and the results obtained are indicative of the efficiency of our technique.

Assessment of Structural Damage Condition Based on Fuzzy Pattern Recognition

This paper presents a new method of damage condition assessment that allows accommodating other types of uncertainties due to ambiguity, vagueness, and fuzziness that are statistically nondescribable. In this method, healthy observations are used to construct a fury set representing sound performance characteristics. Additionally, the bounds on the similarities among the structural damage states are prescribed by using the state similarity matrix. Thus, an optimal group fuzzy sets representing damage states such as little, moderate, and severe damage can be inferred as an inverse problem from healthy observations only. The optimal group of damage fuzzy sets is used to classify a set of observations at any unknown state of damage using the principles of fitzzy pattern recognition based on an approximate principle . This method can be embedded into the system of Structural Health Monitoring （SHM） to give advice about structural maintenance and life predictio comes from Reference [ 9 ] for damage pattern recognition is presented n. Finally, a case and discussed. The study, which compared result illustrates our method is more effective and general, so it is very practical in engineering.

Synthesis and Crystal Structure of 1,2-Bis-(p-nitrophenylsulfonamido)-4,5-dinitrobenzene

The title compound, 1,2-bis-（p-nitro-phenylsulfonamido）-4,5-dinitrobenzene, was synthesized and characterized by elemental analysis, IR and 1H NMR. A pale yellow prism crystal of C23H26N8O13S2 （Mr = 686.64） was obtained in DMF solution and determined by single-crystal X-ray diffraction method. It crystallizes in triclinic system, space group P1 with a = 10.346（4）, b = 12.210（5）, c = 12.976（5）A , α = 108.220（8）, β = 99.482（4）, γ = 95.490（4）°, V = 1516.7（10） A^3, Z = 2, Dc = 1.504 g/cm^3, F（000） = 712, μ = 0.254, Mr = 686.64, the final R = 0.0561 and wR = 0.1487. One sulfonamido group of the title compound is deprotoned and forms N（3）=C（13）. The crystal involves N,N-dimethylamine from the decomposition of DMF and the proton is transferred to N,N- dimethylamine. It is a strong proof for the characterization of deprotoned recognition compound by X-ray single-crystal structure.

Synthesis and Crystal Structure of 1-(N,N-Di-(p-toluenesulfonyl))-amino-2-(N'-p-toluenesulfonyl)-amino-3,5-dinitrobenzene

The title compound, 1-（N,N-di-（p-toluenesulfonyl））-amino-2-（N＇-p-toluenesulfonyl）- amino-3,5-dinitrobenzene, was synthesized and structurally determined by single-crystal X-ray diffraction method. It crystallizes in orthorhombic, space group Pna21 with a = 13.723（2）, b = 25.354（4）, c = 8.6565（12） A, V= 3011.9（8） A^3, Z = 4, Mr = 660.68, F（000） = 1368, Dc = 1.457 g/cm^3, μ = 0.309, the final R = 0.0609 and wR = 0.1042. The H atom of N2-H group, which is the unique recognition site to anion, is enveloped by two oxygen atoms and one benzene from two and one p-toluenesulfonyl moieties, respectively.

A Novel Algorithm of Error Check and Code Generation for Structured Flowchart

Structured flowchart( SFC) and Automatic code generation based on SFC( CG-SFC) have been widely used in software requirements,design and testing phases. Some CG-SFC tools such as Rhapsody have the ability to build flowchart and generate code,but they do not check whether a given flowchart is correct or structural. For unstructured error ‘goto'statements will be generated randomly. We proposed three algorithms and some error recognition criteria to solve those problems. Structure recognition algorithm can recognize Selection,While/for and do-while structures. Error recognition algorithm incorporating criteria can check all the errors. At last,we develop a CG-SFC system,and compared with existing Rhapsody,it shows that the proposed algorithms are correct and effective.

Laplacian Maximum Margin Criterion for Image Recognition

Previous works have demonstrated that Laplacian embedding can well preserve the local intrinsic structure. However, it ignores the diversity and may impair the local topology of data. In this paper, we build an objective function to learn the local intrinsic structure that characterizes both the local similarity and diversity of data, and then combine it with global structure to build a scatter difference criterion. Experimental results in face recognition show the effectiveness of our proposed approach.

An Assay Study of Molecular Recognition of Amino Acids in Water: Covalent Imprinting of Cysteine

A novel synthetic N-(9-fluorenyl methoxy carbonyl)-L-Cysteine (Fmoc-Cys(SH)-OH) receptor was pre- pared by co-polymerizing (9-fluorenyl methoxy carbonyl)-S-(1-propene-2-thiol)-L-Cysteine (Fmoc-Cys(SCH2CHCH2)-OH) and a non-imprinted polymer prepared from 1-propene-1-thiol photo-chemically 15 h at room temperature and additional 3 h thermally at 80℃. Subsequently, disulfides were reduced with lithium aluminum hydride (LiAlH4) from imprinted polymers. The imprinted polymers selectively recognized Fmoc-Cys(SH)-OH with high binding constants in aqueous and protic solvents by thiol-disulfide exchange reactions. In order to estimate the covalent rebinding, particles were further extracted and disulfides reduced were estimated with the non-covalent recognized and covalently bounded analytes. From rebinding studies that were conducted, we observed that proved polymer particles could be reproducible and contain constant binding strengths and recognition properties. Furthermore, we proved that short incubation periods resulted in fast and efficient thiol-disulfide interchange reactions.