Global localization of in-pipe robot based on ultra-long wave antenna array and global position system

A global localization system of in-pipe robot is introduced in this paper.Global position system(GPS)is applied to monitor the motion of robot along the whole pipeline which is equally divided intomany segments by tracking stations.The definite segment in which robot existing can be detected and thisis long-range localization.Ultra-long wave(ULW)is adopted to solve the problem of metallic shieldingand realize effective communication between inside and outside of pipeline.ULW emitter is carried byrobot.When the plant is broken or defects on pipe-wall are inspected,the robot will stop moving.Anten-na array is presented and disposed upon the definite segment to search the accurate location of robot,andthis is short-range localization.In this paper,five-antenna array is adopted and an effective linear signalfusion algorithm is presented.The localization precision reaches R < 25cm.By tests in Shengli oil field,the whole system is verified with robust solutions.

Feature extension and matching for mobile robot global localization

This paper introduces an indoor global localization method by extending and matching features. In the proposed method, the environment is partitioned into convex subdivisions. Local extended maps of the subdivisions are then built by exten- ding features to constitute the local extended map set. While the robot is moving in the environment, the local extended map of the current local environment is established and then matched with the local extended map set. Therefore, global localization in an indoor environment can be achieved by integrating the position and ori- entation matching rates. Both theoretical analysis and comparison experimental result are provided to verify the effectiveness of the proposed method for global localization.

An object tracking and global localization method using the cylindrical projection of omnidirectional image

We present an omnidirectional vision system we have implemented to provide our mobile robot with a fast tracking and robust localization capability. An algorithm is proposed to do reconstruction of the environment from the omnidirectional image and global localization of the robot in the context of the Middle Size League RoboCup field. This is accomplished by learning a set of visual landmarks such as the goals and the corner posts. Due to the dynamic changing environment and the partially observable landmarks, four localization cases are discussed in order to get robust localization performance. Localization is performed using a method that matches the observed landmarks, i.e. color blobs, which are extracted from the environment. The advantages of the cylindrical projection are discussed giving special consideration to the characteristics of the visual landmark and the meaning of the blob extraction. The analysis is established based on real time experiments with our omnidirectional vision system and the actual mobile robot. The comparative studies are presented and the feasibility of the method is shown.

GMCL： a robust global localization method for mobile robot

A large sample size is required for Monte Carlo localization （MCL） in multi-robot dynamic environ- ment, because of the ＂kidnapped robot＂ phenomenon, which will locate most of the samples in the regions with small value of desired posterior density. For this problem the crossover and mutation operators in evolutionary computation are introduced into MCL to make samples move towards the regions where the desired posterior density is large, so that the sample set can represent the density better. The proposed method is termed genetic Monte Carlo localization （GMCL）. Application in robot soccer system shows that GMCL can considerably reduce the required number of samples, and is more precise and robust in dynamic environment.

Studying the co-evolution of information diffusion,vaccination behavior and disease transmission in multilayer networks with local and global effects

Today,with the rapid development of the internet,a large amount of information often accompanies the rapid transmission of disease outbreaks,and increasing numbers of scholars are studying the relationship between information and the disease transmission process using complex networks.In fact,the disease transmission process is very complex.Besides this information,there will often be individual behavioral measures and other factors to consider.Most of the previous research has aimed to establish a two-layer network model to consider the impact of information on the transmission process of disease,rarely divided into information and behavior,respectively.To carry out a more in-depth analysis of the disease transmission process and the intrinsic influencing mechanism,this paper divides information and behavior into two layers and proposes the establishment of a complex network to study the dynamic co-evolution of information diffusion,vaccination behavior,and disease transmission.This is achieved by considering four influential relationships between adjacent layers in multilayer networks.In the information layer,the diffusion process of negative information is described,and the feedback effects of local and global vaccination are considered.In the behavioral layer,an individual's vaccination behavior is described,and the probability of an individual receiving a vaccination is influenced by two factors:the influence of negative information,and the influence of local and global disease severity.In the disease layer,individual susceptibility is considered to be influenced by vaccination behavior.The state transition equations are derived using the micro Markov chain approach(MMCA),and disease prevalence thresholds are obtained.It is demonstrated through simulation experiments that the negative information diffusion is less influenced by local vaccination behavior,and is mainly influenced by global vaccination behavior;vaccination behavior is mainly influenced by local disease conditions,and is less influenced by global disease conditions;the disease transmission threshold increases with the increasing vaccination rate;and the scale of disease transmission increases with the increasing negative information diffusion rate and decreases with the increasing vaccination rate.Finally,it is found that when individual vaccination behavior considers both the influence of negative information and disease,it can increase the disease transmission threshold and reduce the scale of disease transmission.Therefore,we should resist the diffusion of negative information,increase vaccination proportions,and take appropriate protective measures in time.

SLGC: Identifying influential nodes in complex networks from the perspectives of self-centrality, local centrality, and global centrality

Identifying influential nodes in complex networks and ranking their importance plays an important role in many fields such as public opinion analysis, marketing, epidemic prevention and control. To solve the issue of the existing node centrality measure only considering the specific statistical feature of a single dimension, a SLGC model is proposed that combines a node’s self-influence, its local neighborhood influence, and global influence to identify influential nodes in the network. The exponential function of e is introduced to measure the node’s self-influence;in the local neighborhood,the node’s one-hop neighboring nodes and two-hop neighboring nodes are considered, while the information entropy is introduced to measure the node’s local influence;the topological position of the node in the network and the shortest path between nodes are considered to measure the node’s global influence. To demonstrate the effectiveness of the proposed model, extensive comparison experiments are conducted with eight existing node centrality measures on six real network data sets using node differentiation ability experiments, susceptible–infected–recovered(SIR) model and network efficiency as evaluation criteria. The experimental results show that the method can identify influential nodes in complex networks more accurately.

基于Global/Local法的螺栓连接结构静强度渐进破坏

为了研究螺栓连接结构静强度渐进破坏特点,应用Global/Local有限元分析技术,分两级建立了螺栓连接结构有限元模型,并对其进行了带EWK断裂子程序的材料/几何非线性有限元分析。结果表明:螺栓连接结构的断裂部位位于螺栓孔边缘,当加载到最大载荷的42%时开始出现破坏单元,在加载到最大载荷的48%之前裂纹扩展是一个稳态的过程,之后便迅速扩展直至整体结构失效。Global/Local分析技术提高了整个过程的分析效率。

A Modified Transitional Korteweg-De Vries Equation: Posed in the Quarter Plane

This paper is concerned with a modified transitional Korteweg-de Vries equation ut+f(t)u2ux+uxxx=0, (x,t)∈R+×R+with initial value u(x,0)=g(x)∈H4(R+)and inhomogeneous boundary value u(0,t)=Q(t)∈C2([ 0,∞ )). Under the conditions either 1) f(t)≤0, f′(t)≥0or 2) f(t)≤−αwhere α>0, we prove the existence of a unique global classical solution.

THE GLOBAL AND LOCAL C^(2)-SOLUTIONS FOR THE WAVE EQUATION □u = G(u_t, Du) IN THREE SPACE DIMENSIONS

Kunio Hidano[4] has shown that the global and local C2-solutions for semilinear wave equations with spherical symmetry in three space dimensions. This paper studies the global and local C2-solutions for the semilinear wave equations without spherical symmetry in three space dimensions. A problem put forward by Hiroyuki Takamura[2] is partially answered.

Chinese word segmentation with local and global context representation learning

A local and global context representation learning model for Chinese characters is designed and a Chinese word segmentation method based on character representations is proposed in this paper. First, the proposed Chinese character learning model uses the semanties of loeal context and global context to learn the representation of Chinese characters. Then, Chinese word segmentation model is built by a neural network, while the segmentation model is trained with the eharaeter representations as its input features. Finally, experimental results show that Chinese charaeter representations can effectively learn the semantic information. Characters with similar semantics cluster together in the visualize space. Moreover, the proposed Chinese word segmentation model also achieves a pretty good improvement on precision, recall and f-measure.

Medical image translation using an edge-guided generative adversarial network with global-to-local feature fusion

In this paper,we propose a framework based deep learning for medical image translation using paired and unpaired training data.Initially,a deep neural network with an encoder-decoder structure is proposed for image-to-image translation using paired training data.A multi-scale context aggregation approach is then used to extract various features from different levels of encoding,which are used during the corresponding network decoding stage.At this point,we further propose an edge-guided generative adversarial network for image-to-image translation based on unpaired training data.An edge constraint loss function is used to improve network performance in tissue boundaries.To analyze framework performance,we conducted five different medical image translation tasks.The assessment demonstrates that the proposed deep learning framework brings significant improvement beyond state-of-the-arts.

Thermomechanical analysis of long-term global modal and local deformation measurements of the Kishwaukee Bridge using the bootstrap

In this paper we present a comparative analysis of global frequency and local deformation data for a large concrete bridge. The asymptotic probability distributions of the central statistics are presented, and compared with empirical bootstrap estimates. Bootstrapped distributions are calculated from reference data obtained during 1999–2000 and used to develop change-point alarm criteria for the structure, using reasonable sensitivity measures developed from FEM simulations and structural analysis. The implications of the frequency data are discussed in conjunction with the strain and displacement measurements in order to discern if the load carrying capacity of the bridge has been affected. The critical need for more advanced temperature compensation models for large structures continually in thermal disequilibrium is discussed.

The Local Strategies of Global Brands in Turkey： Cultural Signs and Advertisement Messages

In advertisements directed at consumers within a society or others ocieties, brands employ cultural signs （values, beliefs, rituals, and heroes and symbols） and in accordance, it can be observed that they consciously make use of the terms ＂locality＂ and ＂globality＂. In this study, four global food brands＇ advertisements including cultural codes, locality, and globality have been randomly selected and analyzed. These advertising messages have been analyzed at an intercultural level from visual semiotics perspective. It has been tried to determine the ＂local＂ approaches of global brands by revealing the ＂intercultural＂ dimension transferred through visual and linguistic signs in the advertisements which we reselected with an eclectic method.

The Two Faces of Urbanity： Exploring Global and Local Values---Two Urban Studios in Taksim Square and along the Shores of the Golden Horn in Istanbul

Since the 18th century, the irritating but also fascinating scenes of urbanity--a complex phenomenon with cultural, social, political, economic, temporal, spatial, functional, and formal dimensions--have been described in literary works. Many seemingly opposite facts, such as individuality/society, freedom/loneliness/socialization, anonymity/strangeness/identity/belonging, diversity/chaos/segregation, indifferent city-dweller/initiative citizenship, have been revealed through literary works, travel and utopian writing, urban theories, scientific studies, manifestos, and newspaper articles. On the one hand, there are those who advocate a life outside the city because they consider the problems produced by the city and the phenomenon of density which they perceive merely in quantitative terms, as unsolvable problems. On the other hand, there are those who see the production of loose urban fabric as a solution or those who accept the （seemingly） opposite facts of urbanity as positive values and therefore support city life. All of these ideas are still as actual today as they were in the past. We are often unable to use our citizen rights to the city, to encounter different classes （social/etlmic/religious）, to experience heterogeneity as an aspect inherent in city life and in the route of our daily life--following the orders of the capitalist system mainly organized around work--and we are often drawn into the same districts on the same paths. Our perception of our urban environments may get monotonous and shallow, but the irritating yet fascinating features of the first big cities still exist and may be grasped and brought into consciousness. Throughout their architectural education, especially in urban design studios, students can be encouraged to investigate the rhythm of their daily life, the conditions of their urban environments, and discovering the city as an intellectual and sensual programme, so that the phenomenon of urbanity can be grasped not just on formal, but on various other dimensions as well. This study focuses on the process and outcomes of two urban studios located in Taksim Square and along the shores of the Golden Horn in Istanhul. Taking the multidimensional content of urbanity into account, acquired theoretically through literary works and studies on urban planning and its history, the main aim of these studios has been the phenomenological understanding of the dynamic content of urbanity by the students. Through creative analysis of permanent/temporary spaces engendered by the diversity of user profiles and actions discovered on phenomenological excursions, students examine the qualitative values of density and global and local dynamics. We believe that designing spaces as ＂prototypes＂ helps highlight the multidimensional content of urbanity. The present study aims not only to highlight the multidimensional content of urbanity, but also to encourage its discussion in architectural design education and to emphasize the positive contribution of theoretical readings and phenomenological studies to urban design studios. The present study also aims to emphasize the beneficial correlation of global and local dynamics as the two faces of urbanity; important more than ever for the big cities of the 21 st century if we advocate for a vivid and resilient city life and citizens.

Global parameter estimation of the Cochlodinium polykrikoides model using bioassay data

Cochlodinium polykrikoides is a notoriously harmful algal species that inflicts severe damage on the aquacultures of the coastal seas of Korea and Japan. Information on their expected movement tracks and boundaries of influence is very useful and important for the effective establishment of a reduction plan. In general, the information is supported by a red-tide（a.k.a algal bloom） model. The performance of the model is highly dependent on the accuracy of parameters, which are the coefficients of functions approximating the biological growth and loss patterns of the C. polykrikoides. These parameters have been estimated using the bioassay data composed of growth-limiting factor and net growth rate value pairs. In the case of the C. polykrikoides, the parameters are different from each other in accordance with the used data because the bioassay data are sufficient compared to the other algal species. The parameters estimated by one specific dataset can be viewed as locally-optimized because they are adjusted only by that dataset. In cases where the other one data set is used, the estimation error might be considerable. In this study, the parameters are estimated by all available data sets without the use of only one specific data set and thus can be considered globally optimized. The cost function for the optimization is defined as the integrated mean squared estimation error, i.e., the difference between the values of the experimental and estimated rates. Based on quantitative error analysis, the root-mean squared errors of the global parameters show smaller values, approximately 25%–50%, than the values of the local parameters. In addition, bias is removed completely in the case of the globally estimated parameters. The parameter sets can be used as the reference default values of a red-tide model because they are optimal and representative. However, additional tuning of the parameters using the in-situ monitoring data is highly required.As opposed to the bioassay data, it is necessary because the bioassay data have limitations in terms of the in-situ coastal conditions.

Tire Defect Detection Using Local and Global Features

In this paper, we present a tire defect detection algorithm based on sparse representation. The dictionary learned from reference images can efficiently represent the test image. As the representation coefficients of normal images have a specific distribution, the local feature can be estimate by comparing representation coefficient distribution. Meanwhile, a coding length is used to measure the global features of representation coefficients. The tire defect is located by both these local and global features. Experimental results demonstrate that the proposed method can accurately detect and locate the tire defects.

联合利华：More Local More Global

对于初出国门的企业来说，理解另外一个国家的商业习惯与氛围是一件很难的事情，因为这需要你用脚实践。

Detailed Quantum Mechanical QSAR Analysis of Certain Aminopyrimidoisoquinolinequinones with Anticancer Activity

A detailed quantum mechanical analysis of electronic disposition of five aminopyrimidoisoquinolinequinones (APIQs) was performed after extraction of this subset of compounds from a larger data set of APIQs via a reported clustering methodology (Elfaki, et al. 2020). Both semi empirical PM3 method and DFT quantum mechanical methods were used to calculate global and local quantum mechanical descriptors (QMDs) to define the electronic environment of these molecules in attempt to rationalize their observed anti-cancer response variability. The biological response is the anticancer activity against human gastric adenocarcenoma (AGS) cell line. The correlation matrix between the calculated global electronic descriptors and biological activity demonstrated that the global dipole moment gives the highest correlation. The local electronic environment was analysed by The Mullikan charges (MC) and Fukui functions for N-5, C-6, C-8 in addition to the N atom of phenylamino side group at C-8. MCs furnished no useful information as each of these atoms had almost identical MC values for all the five compounds with exception of C-6 which gave varied values. Regressing MCs of C-6 against the response traces 60% of the latter variability. As C-6 is an extra annular methyl carbon adjacent to N-5 in isoquinoline residue of APIQ, we reasoned that the chemical reactivities of 4 out of the 5 APIQs might be due to a Chichibabin-type tautomerism implying a possible alkylation aspect in their mechanism of action. The corresponding Fukui functions (f-, f+ and f0) showed a considerable consistency with the patterns of chemical reactivity exhibited by this small set of APIQs.

一种多媒体实时磁盘调度的改进方案研究

论述了Hybird Local/Global寻道最优化方法,并在此基础上对Local-merging模式进行了改进。实验证明,改进的算法在磁盘吞吐量上有一定的改善。