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Time-series unmanned aerial vehicle photogrammetry monitoring method without ground control points to measure mining subsidence

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JOURNAL OF APPLIED REMOTE SENSING 2021年第2期15卷

作者： Lian, Xugang Liu, Xiaoyu Ge, Linlin Hu, Haifeng Du, Zheyuan Wu, Yanru Taiyuan Univ Technol Sch Min Engn Taiyuan Peoples R China Univ New South Wales Sch Civil & Environm Engn Sydney NSW Australia

Surface subsidence and its secondary effects caused by underground coal mining continually threaten the safety and property of residents in mining areas. The commonly used total station and leveling approach is time-consuming and laborious, and the spatial range is limited. In this study, an FEIMA D2000 quadrotor unmanned aerial vehicle (UAV) was used to conduct 4-cm/pixel photogrammetry in four trial periods over a surface influence area (3.75 km(2)) of a working mine face. The performance comparison experiments from five point-cloud filtering algorithms in two sub-regions of the study area show that the ATIN algorithm provides the best filtering for this study area. Coal mining subsidence monitoring in mountainous area based on time-series UAV photogrammetry technology is proposed. Using this approach, the ATIN algorithm was used to filter the overall point cloud data in the study area to obtain the digital elevation model (DEM). The surface dynamic subsidence basin was determined with two phases of DEM subtraction. The results show that, compared with the measured leveling data in the field in the same period, the average root mean square error is 165 mm, and the maximum subsidence monitoring accuracy reaches 98%. (C) 2021 Society of Photo-Optical Instrumentation Engineers (SPIE)

关键词： unmanned aerial vehicle photogrammetry subsidence monitoring filtering algorithm surface subsidence basin

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Constrained clustering by constraint programming

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ARTIFICIAL INTELLIGENCE 2017年 244卷 70-94页

作者： Thi-Bich-Hanh Dao Khanh-Chuong Duong Vrain, Christel Univ Orleans INSA Ctr Val Loire LIFO EA 4022 F-45067 Orleans France

Constrained Clustering allows to make the clustering task more accurate by integrating user constraints, which can be instance-level or cluster-level constraints. Few works consider the integration of different kinds of constraints, they are usually based on declarative frameworks and they are often exact methods, which either enumerate all the solutions satisfying the user constraints, or find a global optimum when an optimization criterion is specified. In a previous work, we have proposed a model for Constrained Clustering based on a Constraint Programming framework. It is declarative, allowing a user to integrate user constraints and to choose an optimization criterion among several ones. In this article we present a new and substantially improved model for Constrained Clustering, still based on a Constraint Programming framework. It differs from our earlier model in the way partitions are represented by means of variables and constraints. It is also more flexible since the number of clusters does not need to be set beforehand;only a lower and an upper bound on the number of clusters have to be provided. In order to make the model-based approach more efficient, we propose new global optimization constraints with dedicated filtering algorithms. We show that such a framework can easily be embedded in a more general process and we illustrate this on the problem of finding the optimal Pareto front of a bi-criterion constrained clustering task. We compare our approach with existing exact approaches, based either on a branch-and-bound approach or on graph coloring on twelve datasets. Experiments show that the model outperforms exact approaches in most cases. (C) 2015 Elsevier B.V. All rights reserved.

关键词： Constrained clustering Bi-criterion clustering Constraint programming Modeling Global optimization constraint filtering algorithm

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Solving subgraph isomorphism problems with constraint programming

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CONSTRAINTS 2010年第3期15卷 327-353页

作者： Zampelli, Stephane Deville, Yves Solnon, Christine Univ Lyon 1 LIRIS CNRS UMR5205 F-69622 Villeurbanne France Univ Louvain Dept Comp Sci & Engn B-1348 Louvain Belgium Ecole Mines F-44307 Nantes 3 France

The subgraph isomorphism problem consists in deciding if there exists a copy of a pattern graph in a target graph. We introduce in this paper a global constraint and an associated filtering algorithm to solve this problem within the context of constraint programming. The main idea of the filtering algorithm is to label every node with respect to its relationships with other nodes of the graph, and to define a partial order on these labels in order to express compatibility of labels for subgraph isomorphism. This partial order over labels is used to filter domains. Labelings can also be strengthened by adding information from the labels of neighbors. Such a strengthening can be applied iteratively until a fixpoint is reached. Practical experiments illustrate that our new filtering approach is more effective on difficult instances of scale free graphs than state-of-the-art algorithms and other constraint programming approaches.

关键词： Subgraph isomorphism Global constraint filtering algorithm

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Wireless Distance Estimation Based on Error Correction of Bluetooth RSSI

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IEICE TRANSACTIONS ON COMMUNICATIONS 2015年第6期E98B卷 1018-1031页

作者： Jung, Joon-young Kang, Dong-oh Choi, Jang-ho Bae, Changseok Kim, Dae-young ETRI 218 Gajeongno Daejeon 305700 South Korea Chungnam Natl Univ Daejeon 305700 South Korea

In this paper, we propose an error-correction low-pass filter (EC-LPF) algorithm for estimating the wireless distance between devices. To measure this distance, the received signal strength indication (RSSI) is a popularly used method because the RSSI of a wireless signal, such as Wi-Fi and Bluetooth, can be measured easily without the need for additional hardware. However, estimating the wireless distance using an RSSI is known to be difficult owing to the occurrence of inaccuracies. To examine the inaccuracy characteristics of Bluetooth RSSI, we conduct a preliminary test to discover the relationship between the actual distance and Bluetooth RSSI under several different environments. The test results verify that the main reason for inaccuracy is the existence of measurement errors in the raw Bluetooth RSSI data. In this paper, the EC-LPF algorithm is proposed to reduce measurement errors by alleviating fluctuations in a Bluetooth signal with responsiveness for real-time applications. To evaluate the effectiveness of the EC-LPF algorithm, distance accuracies of different filtering algorithms are compared, namely, a low-pass filer (LPF), a Kalman filter, a particle filter, and the EC-LPF algorithm under two different environments: an electromagnetic compatibility (EMC) chamber and an indoor hall. The EC-LPF algorithm achieves the best performance in both environments in terms of the coefficient of determination, standard deviation, measurement range, and response time. In addition, we also implemented a meeting room application to verify the feasibility of the EC-LPF algorithm. The results prove that the EC-LPF algorithm distinguishes the inside and outside areas of a meeting room without error.

关键词： distance estimation error correction filtering algorithm RSSI Bluetooth

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Optimal state estimation for singular system with stochastic uncertain parameter

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OPTIMAL CONTROL APPLICATIONS & METHODS 2020年第4期41卷 1001-1015页

作者： Yu, Xingkai Li, Jianxun Shanghai Jiao Tong Univ Sch Elect Informat & Elect Engn 800 Dongchuan Rd Shanghai 200240 Peoples R China Tsinghua Univ Dept Precis Instrument Beijing 100084 Peoples R China

This article studies singular systems with uncertain parameters by using a direct method which is called the first restricted equivalent transformation (FRET). The stochastic uncertain parameters we studied in the article, which are more general and challenging, are different from the two existing types: time-invariant parameters and time-varying parameters. We propose an optimal filtering algorithm to filter out artifacts, such as noise, from the uncertain parameter by using the projection theorem and the FRET. The proposed algorithm guarantees optimum in the sense of linear minimum mean-square error. Simulation results verify the proposed algorithm.

关键词： equivalent transformation filtering algorithm projection theorem singular system stochastic uncertain parameter

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Enhancing the MCL-SLAM algorithm to overcome the issue of illumination variation, non-static environment and kidnapping to present the NIK-SLAM

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INTERNATIONAL JOURNAL OF INTELLIGENT ROBOTICS AND APPLICATIONS 2024年 1-22页

作者： Agunbiade, Olusanya Yinka Univ Western Cape Dept Informat Syst Cape Town South Africa

Simultaneous Localization and Mapping (SLAM) is a major challenge that has been comprehensively investigated by scholars. SLAM's ability to support autonomous navigation helps the robot to move from one place to another without being controlled by humans. This achievement has attracted the attention of scholars towards focusing on this area. Over the decades, countless procedures have been developed with extraordinary accomplishments. However, some problems can degrade the efficiency of SLAM (Simultaneous Localization and Mapping) technique, and examples of such problems include environmental noises (light intensity and shadow), non-static environment, and kidnap robots. These problems create inconsistency in measurement that can lead to erroneous navigation for an unmanned vehicle. In minimizing the effect of these problems, a novel SLAM technique based on several re-modifications of MCL is presented in this paper. This innovative technique is known as NIK-SLAM. The NIK-SLAM is equipped with filters alongside some modifications of the original Monte-Carlo algorithm (MCL) to maximize its performance. The filters were employed to overcome the effect of shadow and light intensity while the re-modification of MCL is used to overcome the limitation of kidnapping and non-static objects. A publicly available dataset (TUM-RGBD) and a private dataset were used for evaluation. Matlab was used for simulation while assessments were based on quantitative and qualitative validation. The results demonstrated a better performance of the NIK-SLAM, attaining a lower trajectory error for most experiments when compared to the original MCL and other SLAM algorithms found in the literature, but at the expense of delayed processing time. Furthermore, this accomplishment supports pathway planning, and exploration into unstable environments while it decreases accident rates/human fatalities, and in the future study, the issue of delayed processing time will be addressed.

关键词： Autonomous robot Trajectory Navigation filtering algorithm Kidnap problem Non-static environment Simultaneous localization and mapping

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Design of 4PUS-PPPS redundant parallel mechanism oriented to the visual system of flight simulator

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INTERNATIONAL JOURNAL OF INTELLIGENT ROBOTICS AND APPLICATIONS 2021年第4期5卷 534-542页

作者： Ren, Bin Zhang, Zhiqiang Shanghai Univ Sch Mechatron Engn & Automat Shanghai Key Lab Intelligent Mfg & Robot Shanghai 200444 Peoples R China

The Design of the flight simulator mechanism is an essential link in the development of aviation technology. The six-degree-of-freedom Stewart parallel mechanism is used as the mechanical body of most traditional flight simulators. They can simulate the six-degree-of-freedom motion of the aircraft. However, the reachable attitude of the moving platform of the Stewart parallel mechanism is relatively small, and its range of motion is +/- 35 degrees, which can only achieve a small range of yaw, roll and pitch. It can only satisfy the simulation of the attitude change of a civil aviation aircraft. A 4PUS-PPPS redundant parallel mechanism equipped with visual function is proposed to simulate the high motion performance of fighter aircraft, which can realize the movement of angles (- 90 degrees,178 degrees) around the horizontal axis of the aircraft. The flight attitude data of the aircraft were acquired and processed by filtering algorithms in the software of Unity 3D environment. Then, the three steering gears that simulate the action of the moving platform are controlled by the processed data, which realizes the simulation control of the combination of virtual and honest and provides a new idea for the research of redundant parallel mechanisms.

关键词： Flight simulator Redundant parallel mechanism Visual function filtering algorithm

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Beam position measurement system at HIRFL-CSRm

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NUCLEAR ENGINEERING AND TECHNOLOGY 2023年第4期55卷 1332-1341页

作者： Li, Min Xiao, Guoqing Mao, Ruishi Zhao, Tiecheng Yuan, Youjin Li, Weilong Zhou, Kai Kang, Xincai Li, Peng Li, Juan Chinese Acad Sci Inst Modern Phys Lanzhou 73000 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China Lanzhou Univ Technol Lanzhou 730050 Peoples R China Lanzhou Kejin Taiji Corp Ltd Lanzhou 73000 Peoples R China

Beam position measurement system can not only provide the beam position monitoring, but also be used for global orbit correction to reduce beam loss risk and maximize acceptance. The Beam Position Monitors (BPM) are installed along the synchrotron to acquire beam position with the front-end elec-tronics and data acquisition system (DAQ). To realize high precision orbit measurement in the main heavy ion synchrotron and cooling storage ring of heavy-ion research facility in Lanzhou (HIRFL-CSRm), a series of alignment and calibration work has been implemented on the BPM and its DAQ system. This paper analyzed the tests performed in the laboratory as well as with beam based on the developed al-gorithms and hardware. Several filtering algorithms were designed and implemented on the acquired BPM raw data, then the beam position and resolution were calculated and analyzed. The results show that the position precision was significantly improved from more than 100 mm to about 50 mm by implementing the new designed filtering algorithm. According to the analyzation of the measurement results and upcoming physical requirements, further upgrade scheme for the BPM DAQ system of CSRm based on field programmable gate array (FPGA) technology was proposed and discussed.(c) 2023 Korean Nuclear Society, Published by Elsevier Korea LLC. This is an open access article under the CC BY-NC-ND license (http://***/licenses/by-nc-nd/4.0/).

关键词： BPM Closed orbit measurement filtering algorithm Heavy ion synchrotron DAQ FPGA

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Semiparametric inference in mixture models with predictive recursion marginal likelihood

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BIOMETRIKA 2011年第3期98卷 567-582页

作者： Martin, Ryan Tokdar, Surya T. Indiana Univ Purdue Univ Dept Math Sci Indianapolis IN 46202 USA Duke Univ Dept Stat Sci Durham NC 27708 USA

Predictive recursion is an accurate and computationally efficient algorithm for nonparametric estimation of mixing densities in mixture models. In semiparametric mixture models, however, the algorithm fails to account for any uncertainty in the additional unknown structural parameter. As an alternative to existing profile likelihood methods, we treat predictive recursion as a filter approximation by fitting a fully Bayes model, whereby an approximate marginal likelihood of the structural parameter emerges and can be used for inference. We call this the predictive recursion marginal likelihood. Convergence properties of predictive recursion under model misspecification also lead to an attractive construction of this new procedure. We show pointwise convergence of a normalized version of this marginal likelihood function. Simulations compare the performance of this new approach with that of existing profile likelihood methods and with Dirichlet process mixtures in density estimation. Mixed-effects models and an empirical Bayes multiple testing application in time series analysis are also considered.

关键词： Density estimation Dirichlet process mixture Empirical Bayes filtering algorithm Marginal likelihood Martingale Mixed effects model Multiple testing Profile likelihood

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A Novel Teaching Approach for Mobile Internet-Based Collaborative Knowledge Construction in "Teaching Management"

INTERNATIONAL JOURNAL OF EMERGING TECHNOLOGIES IN LEARNING

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INTERNATIONAL JOURNAL OF EMERGING TECHNOLOGIES IN LEARNING 2021年第12期16卷 51-64页

作者： Zhang, Sheng Bangkok Thonburi Univ Educ Bangkok Thailand

With the development of education, teaching, as the basic and central work at school, is conducted most frequently with the largest workload. In simple words, teaching management for the purpose of the management of teaching work is an essential content of school management, as well as a basic activity of school leaders. Therefore, more than just the basis and guarantee for the normal operation of school teaching, teaching management course plays a critical role in teacher growth and education reform, has great significance for schools. However, problems in current teaching management courses, such as lack of teacher-student interaction, single teaching content, and simple teaching methods have hindered students to develop interest in learning, and impede teachers to give full play to their educational personality. In this paper, a new collaborative knowledge construction teaching approach was applied in mobile Internet technology environment, and a blended teaching model of students' online autonomous collaborative learning before class, knowledge internalization in class, and leak filling after class was proposed. At the same time, the personalized recommendation technology based on collaborative filtering algorithm was applied. Firstly, mobile terminal core information was collected from the mobile Internet learning platform for preprocessing, and then the processed data were identified by the collaborative filtering algorithm to recognize the intrusion data, thereby realizing the quick screening and accurate pushing of learning resources. It was found from the teaching practice that this model can effectively enhance students' interest in learning, improve learning effects and independent innovation capabilities.

关键词： Mobile internet teaching management collaborative knowledge filtering algorithm

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