Vision-based long-distance lane perception and front vehicle location for full autonomous vehicles on highway roads

A new vision-based long-distance lane perception and front vehicle location method was developed for decision making of full autonomous vehicles on highway roads,Firstly,a real-time long-distance lane detection approach was presented based on a linear-cubic road model for two-lane highways.By using a novel robust lane marking feature which combines the constraints of intensity,edge and width,the lane markings in far regions were extracted accurately and efficiently.Next,the detected lane lines were selected and tracked by estimating the lateral offset and heading angle of ego vehicle with a Kalman filter,Finally,front vehicles were located on correct lanes using the tracked lane lines,Experiment results show that the proposed lane perception approach can achieve an average correct detection rate of 94.37% with an average false positive detection rate of 0.35%,The proposed approaches for long-distance lane perception and front vehicle location were validated in a 286 km full autonomous drive experiment under real traffic conditions.This successful experiment shows that the approaches are effective and robust enough for full autonomous vehicles on highway roads.

An envelope-based machine learning workflow for locating earthquakes in the southern Sichuan Basin

The development of machine learning technology enables more robust real-time earthquake monitoring through automated implementations. However, the application of machine learning to earthquake location problems faces challenges in regions with limited available training data. To address the issues of sparse event distribution and inaccurate ground truth in historical seismic datasets, we expand the training dataset by using a large number of synthetic envelopes that closely resemble real data and build an earthquake location model named ENVloc. We propose an envelope-based machine learning workflow for simultaneously determining earthquake location and origin time. The method eliminates the need for phase picking and avoids the accumulation of location errors resulting from inaccurate picking results. In practical application, ENVloc is applied to several data intercepted at different starting points. We take the starting point of the time window corresponding to the highest prediction probability value as the origin time and save the predicted result as the earthquake location. We apply ENVloc to observed data acquired in the southern Sichuan Basin, China, between September 2018 and March 2019. The results show that the average difference with the catalog in latitude, longitude, depth, and origin time is 0.02°,0.02°, 2 km, and 1.25 s, respectively. These suggest that our envelope-based method provides an efficient and robust way to locate earthquakes without phase picking, and can be used in earthquake monitoring in near-real time.

A Multi-Objective Optimization for Locating Maintenance Stations and Operator Dispatching of Corrective Maintenance

In this study,we introduce a novel multi-objective optimization model tailored for modern manufacturing,aiming to mitigate the cost impacts of operational disruptions through optimized corrective maintenance.Central to our approach is the strategic placement of maintenance stations and the efficient allocation of personnel,addressing a crucial gap in the integration of maintenance personnel dispatching and station selection.Our model uniquely combines the spatial distribution of machinery with the expertise of operators to achieve a harmonious balance between maintenance efficiency and cost-effectiveness.The core of our methodology is the NSGA Ⅲ+Dispatch,an advanced adaptation of the Non-Dominated Sorting Genetic Algorithm Ⅲ(NSGA-Ⅲ),meticulously designed for the selection of maintenance stations and effective operator dispatching.This method integrates a comprehensive coding process,crossover operator,and mutation operator to efficiently manage multiple objectives.Rigorous empirical testing,including a detailed analysis from a taiwan region electronic equipment manufacturer,validated the effectiveness of our approach across various scenarios of machine failure frequencies and operator configurations.The findings reveal that the proposed model significantly outperforms current practices by reducing response times by up to 23%in low-frequency and 28.23%in high-frequency machine failure scenarios,leading to notable improvements in efficiency and cost reduction.Additionally,it demonstrates significant improvements in oper-ational efficiency,particularly in selective high-frequency failure contexts,while ensuring substantial manpower cost savings without compromising on operational effectiveness.This research significantly advances maintenance strategies in production environments,providing the manufacturing industry with practical,optimized solutions for diverse machine malfunction situations.Furthermore,the methodologies and principles developed in this study have potential applications in various other sectors,including healthcare,transportation,and energy,where maintenance efficiency and resource optimization are equally critical.

An intersection method for locating earthquakes in complex velocity models

The intersection method is one of the basic approaches for locating earthquakes and is not only robust but also efficient. However, its location accuracy is not high, especially for focal depth because the velocity model used for the conventional intersection method is based on homogeneous or laterally homogeneous media, which is too simple. In order to improve the accuracy, we have modified the existing intersection method. In the modified approach, the earthquake loci are not assumed to be circular or hyperbolic and calculation accuracy is improved using a minimum traveltime tree algorithm for tracing rays. The numerical model shows that the modified method can locate earthquakes in complex velocity models.

WORKPIECE LOCATING AND POST PROCESSING SYSTEMS ON 6-DOF CNC MILLING MACHINE

A conventional non-computerized numerical control （CNC） machine is updated by mounting a six degree-of-free （DOF） parallel mechanism on it, thus obtaining a new CNC one. The structure of this CNC milling machine is introduced, and the workpiece locating system and the post processing system of the cutter location （CL） data file are analyzed. The new machine has advantages of low costs, simple structure, good rigidity, and high precision. It is easy to be transformed and used to process the workpiece with a complex surface.

Reviewer Locator模块在科技期刊中的应用实践与发展前景——以《中国肺癌杂志》为例

科技期刊作为科技传播的重要力量,其对重要科研成果的发布速度影响着科学技术的传播效力,而编辑工作效率直接决定稿件发表周期,提高编辑工作效率是科技期刊发展的推进器。为此,从同行评议审稿人储备和遴选方面入手,重点阐述如何准确高效地多维度遴选优质审稿人,归纳并探析Reviewer Locator模块在科技期刊办刊工作中的实际应用经验,助力出版业实现质量更好、效率更高的发展。

无线网络优化LOCATING过程中ERICSSON3算法的应用

介绍在LOCATING过程中处理基本排队时所用到的一种算法——ERICSSON 3算法,探讨通过该算法控制切换的方法(只涉及爱立信设备)。

Research on Passive Locating Method Using Phase Rate of Change with Variant Posture of the Observer

Technology of passive location has broad prospects in applications. In this paper, the method using the phase rate of change for the single observer passive location is introduced based on existing methods. One can obtain the direction of the target with phase information of two orthogonal interferometers on the observer and the radial distance with the corresponding phase rate of change. Then the target can be located with high speed and precision. A locating approach is given when the flying posture of t...

Vision-based Stabilization of Nonholonomic Mobile Robots by Integrating Sliding-mode Control and Adaptive Approach

Vision-based pose stabilization of nonholonomic mobile robots has received extensive attention. At present, most of the solutions of the problem do not take the robot dynamics into account in the controller design, so that these controllers are difficult to realize satisfactory control in practical application. Besides, many of the approaches suffer from the initial speed and torque jump which are not practical in the real world. Considering the kinematics and dynamics, a two-stage visual controller for solving the stabilization problem of a mobile robot is presented, applying the integration of adaptive control, sliding-mode control, and neural dynamics. In the first stage, an adaptive kinematic stabilization controller utilized to generate the command of velocity is developed based on Lyapunov theory. In the second stage, adopting the sliding-mode control approach, a dynamic controller with a variable speed function used to reduce the chattering is designed, which is utilized to generate the command of torque to make the actual velocity of the mobile robot asymptotically reach the desired velocity. Furthermore, to handle the speed and torque jump problems, the neural dynamics model is integrated into the above mentioned controllers. The stability of the proposed control system is analyzed by using Lyapunov theory. Finally, the simulation of the control law is implemented in perturbed case, and the results show that the control scheme can solve the stabilization problem effectively. The proposed control law can solve the speed and torque jump problems, overcome external disturbances, and provide a new solution for the vision-based stabilization of the mobile robot.

Locating method of fire source for spontaneous combustion of sulfide ores

in order to achieve a more efficient way to accurately detect the position of the fire source of spontaneous combustion underground mine, a simple fire source locating method, based on infrared scanning system which can determine the point where the highest temperature on the surface of igniting ores occurs, was proposed. First, the differential equations that describe heat flow in ore body were presented and the relationship between the surface temperature distribution and the depth and intensity of inner fire source was established with a relatively simple heat transfer model. With the solution of equation, the expression of the relationship between the surface temperature distribution and the inner fire source was deduced and the mathematical-physical model of heat transfer process was set up. Then, with the model, visualization of fire source on the basis of MATLAB simulation platform was realized. The results show that： 1） within 10 m, when the detecting depth is less than 2 m, the temperature perturbation on ores surface can change rapidly, and then slowly; after 4 m, in contrast, it changes very little, and is even close to zero at 10 m; 2） When it is close to self-ignition duration and the detective depths are 2, 5 and 10 m, respectively, the maximum temperature differences are correspondingly 0.5, 0.04 and 0.005 ℃ in the scope of 1 m×1 m; under the same condition, the maximum temperature differences are 1.391, 0.136 and 0.018 ℃, respectively, in the scope of 2 m×2 m. Therefore, this system can be used to measure the temperature differences on the surface of ore body and determine the highest temperature point directly. Also, it is possible to determine the depth of fire source and its intensity by locating method of fire source indirectly.

Topological Optimization Method for Aeronautical Thin-Walled Component Fixture Locating Layout

Fixture locating layout has a direct and influential impact on aeronautical thin-walled component(ATWC)manufacturing quality.The purpose is to develop a topological optimization method for ATWC fixture locating layout to minimize the manufacturing deformation.Firstly,a topological optimization model that takes the stiffness of ATWC as the objective function and the volume of the locating structure as the constraint is established.Secondly,ATWC and the locating structure are regarded as an integrated entity,and the variable-density method based topological optimization approach is adopted for the optimization of the locating structure using ABAQUS topology optimization module(ATOM).Thirdly,through a subsequent model reconstruction referring to the obtained topological structure,the optimal fixture locating layout is achieved.Finally,a case study is conducted to verify the proposed method and the comparison results with firefly algorithm(FA)coupled with finite element analysis(FEA)indicate that the number and positions of the locators for ATWC can be optimized simultaneously and successfully by the proposed topological optimization model.

An online fast multi-track locating algorithm for high-resolution single-event effect test platform

To improve the efficiency and accuracy of single-event effect(SEE)research at the Heavy Ion Research Facility at Lanzhou,Hi’Beam-SEE must precisely localize the position at which each heavy ion hitting the integrated circuit(IC)causes SEE.In this study,we propose a fast multi-track location(FML)method based on deep learning to locate the position of each particle track with high speed and accuracy.FML can process a vast amount of data supplied by Hi’Beam-SEE online,revealing sensitive areas in real time.FML is a slot-based object-centric encoder-decoder structure in which each slot can learn the location information of each track in the image.To make the method more accurate for real data,we designed an algorithm to generate a simulated dataset with a distribution similar to that of the real data,which was then used to train the model.Extensive comparison experiments demonstrated that the FML method,which has the best performance on simulated datasets,has high accuracy on real datasets as well.In particular,FML can reach 238 fps and a standard error of 1.6237μm.This study discusses the design and performance of FML.

Neural-Fuzzy-Based Adaptive Sliding Mode Automatic Steering Control of Vision-based Unmanned Electric Vehicles

This paper presents a novel neural-fuzzy-based adaptive sliding mode automatic steering control strategy to improve the driving performance of vision-based unmanned electric vehicles with time-varying and uncertain parameters.Primarily,the kinematic and dynamic models which accurately express the steering behaviors of vehicles are constructed,and in which the relationship between the look-ahead time and vehicle velocity is revealed.Then,in order to overcome the external disturbances,parametric uncertainties and time-varying features of vehicles,a neural-fuzzy-based adaptive sliding mode automatic steering controller is proposed to supervise the lateral dynamic behavior of unmanned electric vehicles,which includes an equivalent control law and an adaptive variable structure control law.In this novel automatic steering control system of vehicles,a neural network system is utilized for approximating the switching control gain of variable structure control law,and a fuzzy inference system is presented to adjust the thickness of boundary layer in real-time.The stability of closed-loop neural-fuzzy-based adaptive sliding mode automatic steering control system is proven using the Lyapunov theory.Finally,the results illustrate that the presented control scheme has the excellent properties in term of error convergence and robustness.

An improved QuikSCAT wind retrieval algorithm and eye locating for typhoon

This paper proposes a rain considered geophysical model function （GMF）, to be noted as GMF plus Rain. GMF plus Rain is based on the basic raidative transfer model with attenuation and scattering effects of rain on radar signal considered. Combined with the NSCAT2 GMF and the rain correction model, the GMF plus Rain model is used to retrieve the ocean wind vectors from the collocated QuikSCAT and SSM/I rain rate data for typhoon Melor. The resulting wind speed estimates of typhoon Melor show improved agreement with the wind fields derived from the best track analysis of Japan Meteorological Agency （JMA）. The results imply that compared with the GMF model, the GMF plus Rain model can improve the precision of wind retrieval under the rain condition. Then, a new general algorithm of locating the eye of typhoon through the normalized radar cross section （NRCS） is proposed. The implementation of this algorithm in the ten QuikSCAT observations of typhoon Melor suggests that this algorithm is effective.

A Study on the Mobile Partial Discharge Locating System

This paper studies on the Partial Discharge (PD) Locating System based on a mobile array of ultra-high frequency (UHF) antennas and a vehicle-mounted PD locating system is established. The system consists of omni-directional antenna array for receiving UHF PD signals, a pre-processing circuit for signal amplification and filtering and the high- speed acquisition and control unit of PD pulse signals. The developed locating system is able to simultaneously record the PD pulse signals received by the antenna array. By assessing the time difference of arrival (TDOA), the two-dimensional hyperbolic locating model quickly locates the PD source. Based on the software developed by LabVIEW, it is also possible to display, store and further analyze the acquired signals. Through the simulation of PD signals and the locating experiments with the system, it is proved that the PD locating system possesses the features of rapidity and precision in determining the bearing of PD source.

Locating microseismic sources based upon L-shaped single-component geophone array:A synthetic study

We have developed a type of L-shaped single-component geophone array as a single station(L-array station)for surface microseismic monitoring.The L-array station consists of two orthogonal sensor arrays,each being a linear array of single-component sensors.L-array stations can be used to accurately estimate the polarization of first arrivals without amplitude picking.In a synthetic example,we first use segmentally iterative ray tracing(SIRT)method and forward model to calculate the travel time and polarization of first arrivals at a set of L-array stations.Then,for each L-array station,the relative delay times of first arrivals along sensor arrays are used to estimate the polarization vector.The small errors in estimated polarization vectors show the reliability and robustness of polarization estimation based on L-array stations.We then use reverse-time ray-tracing(RTRT)method to locate the source position based on estimated polarizations at a set of L-array stations.Very small errors in inverted source location and origin time indicate the great potential of L-array stations for source localization applications in surface microseismic monitoring.

Locating the Small 1999 Frenchman Flat, Nevada Earthquake with InSAR Stacking

Due to high interferometric coherence in the Nevada region,Interferometric Synthetic Aperture Radar(InSAR)phase stacking is capable of mapping coseismic signals from the 27 January 1999,M w 4.8 Frenchman Flat earthquake.This is one of the smallest earthquakes yet studied using InSAR with line-of-sight displacements as small as~1.5 cm.Modelling the event as dislocation in an elastic half space suggests that the fault centroid was located at(115.96°W,36.81°N)with a precision of 0.2~0.3 km(1σ)at a depth of 3.4±0.2 km.Despite the dense local seismic network in southern Nevada,differences as large as 2~5 km were observed between our InSAR earthquake location and those estimated from seismic data.The InSAR-derived magnitude appeared to be greater than that from seismic data,which is consistent with other studies,and believed to be due to the relatively long time interval of InSAR data.

A Two-Station Passive Locating Solution Independent of the Baseline Length

The two-station positioning system based on time difference and azimuth measurement has measurement redundancy. Therefore, not only can a positioning solution which is completely independent of the baseline length between two stations be derived, but also the baseline length can be solved as an unknown quantity. These findings not only enhance the performance of the two-station positioning system, but also provide a design basis for the construction of a self-organizing dynamic intelligent positioning system.

RFID Complex Event Processing: Applications in Real-Time Locating System

Complex event processing (CEP) can extract meaningful events for real-time locating system (RTLS) applications. To identify complex event accurately in RTLS, we propose a new RFID complex event processing method GEEP, which is based on the timed automata (TA) theory. By devising RFID locating application into complex events, we model the timing diagram of RFID data streams based on the TA. We optimize the constraint of the event streams and propose a novel method to derive the constraint between objects, as well as the constraint between object and location. Experiments prove the proposed method reduces the cost of RFID complex event processing, and improves the efficiency of the RTLS.

The clinical research of esophagus radiographic locating method of atrial septal puncture-including the clinical analyses of 486 cases

Objective To devise the safety and validity of clinical application of esophagus radiographic locating method of transseptal puncture. Methods Four hundreds and eighty-six patients who were undergone transseptal puncture were randomized into two groups. Esophagus radiographic locating method of tansseptal puncture was applied in the study group(n=243) and modified-Ross locating method was used in the control group(n=243). After successful location, transseptal puncture was made. Then observe the success rate and complication incidences of the 2 groups. Results Left atria impression in the study group was clearly seen. 120 cases in control group could not shown clearly the left atria silhouette. The success rate of locating transseptal puncture in the study group and control group were 100% and 50.6 % respectively(P【0.001). The success rate of transeptal puncture in the study group and control group was 99.6% and 45.7% respectively (P【0.001). There were no puncture complication in study group and pericardial tamponade occurred in 1 case in control group. Conclusion The esophagus radiographic locating method of transeptal puncture is accurate, safe and simple to perform. According to the radiographic result, to perform thetranseptal puncture can achieve high success rate with few complications.