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Design of intelligent Robot Platform based on Multi-sensor Fusion

Design of Intelligent Robot Platform based on Multi-sensor F...

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2020 International Conference on 5G Mobile Communication and Information Science, MCIS-5G 2020

作者： Dajin, Ya Xiaochun, Lei Yue, Li Junyan, Chen Rongcun, Huang Lin, Lan School of Computer and Information Security Guilin University of Electronic Technology Guilin541004 China Guangxi Colleges and Universities Key Lab. of Intelligent Processing of Computer Images and Graphics Guilin541004 China Guangxi Cooperative Innovation Center of Cloud Computing and Big Data Guilin University of Electronic Technology Guilin541004 China

The mobile robot adapts to the more complicated indoor and outdoor environments, and can expand its scope of application. In order to reduce the influence of the cumulative error caused by navigation in complex environments, the indoor mobile robot that combines Inertial Measurement Unit (IMU) and encoder fusion is designed and implemented. In view of the limitations of the traditional single lidar scheme, a Multi-sensor Fusion scheme is proposed to achieve indoor map construction, path planning, multi-point navigation and other functions, and a MSIF KartoSLAM (Multi-sensor Information Fusion) algorithm is proposed, which combines the KartoSLAM algorithm and Multi-sensor information to achieve map construction in complex environments. Through comprehensive testing in the indoor environment, the results show that the Multi-sensor Fusion scheme is superior to the traditional single lidar scheme, and can achieve higher accuracy in mapping and navigation. At the same time, the robot platform can also be combined with the Internet of Things technology and integrated into intelligent housing system. © 2020 Published under licence by IOP Publishing Ltd.

关键词： Navigation

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A novel measurement of uncertain information based on interval type-2 cross-entropy and its application

A novel measurement of uncertain information based on interv...

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Youth Academic Annual Conference of Chinese Association of Automation (YAC)

作者： Qiang Ma Kongchun Mei Junjun Mao School of Mathematical Science. Anhui University Hefei PR China Key Lab of Intelligent Computing & Signal Processing of Ministry of Education Anhui University Hefei PR China

ISBN: (纸本)9781538629024

The aim of this paper is to put forward a novel measurement of uncertain information to dispose of multiple attribute group decision making (MAGDM) based on interval type-2 cross-entropy. Firstly, some basic concepts and a ranking value formula to calculate the ranking value of interval type-2 fuzzy sets (IT2FSs) is briefly introduced. Meanwhile, a novel measurement based on interval type-2 cross-entropy to measure the uncertainty of the IT2FSs is investigated, the advantage of measurment can be interpreted as it not only considers the uncertainty of the element itself, but also considers the uncertainty caused by other elements. By using the measurement which has proposed, a method was presented to determine attribute weights based on the principle of minimization. Moreover, a decision making procedure based on measurement value is given to select the best alternative(s). Lastly, we apply the proposed decision making procedure based on measurement value to a simple practical example, which can illustrate the practicality and effectiveness.

关键词： C# languages

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Research on network Chinese pornography characteristic and corresponding filtering system's model

Research on network Chinese pornography characteristic and c...

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International Conference on Internet Technology and Applications, ITAP 2010

作者： Peng, Yu-Zhong School of Computer and Information Engineering Key Lab. of Scientific Computing and Intelligent Information Processing in Universities of Guangxi Guangxi Teacher Education University Nanning 53001 China

ISBN: (纸本)9781424451432

At present,the internet pornographic text is in varied forms and changeful, although it is prohibited ever. It severely harms people's mental and physical health development and social stability. There are IP-based,keyword-based and intelligent content analysis filtering systems against it today. But they are difficult to deal with manifestations of diversity, changeful, and increasingly concealed porn. In this paper, a in-depth research has done for the appeared characteristics of such undesirable information on our statistical analysis. And based on this characteristics, a new text pre-processing algorithm PA-PTCI is proposed, and a effective model combined with content filtering technology to the current text information filtering pornography problem is designed. The experimental result shows the PA-PTCI algorithm and the proposed model are quite effective. ©2010 IEEE.

关键词： Information filtering

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Social sensing enhanced time estimation for bus service

Social sensing enhanced time estimation for bus service

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作者： Liu, Jin Li, Juan Cui, Xiaohui Niu, Xiaoguang Sun, Xiaoping Zhou, Jing State Key Lab. of Software Engineering Computer School Wuhan University Wuhan China Guangxi Key Laboratory of Trusted Software Guilin University of Electronic Technology Guilin China International School of Software Wuhan University Wuhan China Computer School Wuhan University Wuhan China Key Lab of Intelligent Information Processing Institute of Computing Technology CAS Beijing China School of Computer Science Communication University of China China

The precise prediction of bus routes or the arrival time of buses for a traveler can enhance the quality of bus service. However, many social factors influence people's preferences for taking buses. These social factors may include heavy traffic cost, traffic congestion, poor air quality and so forth. Existing prediction techniques rarely consider social sensing when predicting the bus arrival time. Accordingly, this paper proposes a social sensing enhanced service for predicting bus routes, which integrates sensing ability and social networks to understand and measure the influence between social events and vehicle velocity. We focus on the analysis of two different attributions: PT service quality attributions PEAs and road condition attributions PRCAs. Both of them synthesize the social sensing in their evaluation of bus routes. PEA represents individual preferences and PRCA represents physical factors that significantly influence vehicle velocity. Bus relevant social events were further categorized into PEA events or PRCA events. PEAs of buses were scored according to the tendency of bus conditions reflected in social events. Furthermore, an artificial neural network prediction model is established to estimate the bus travel time. © 2015 John Wiley & Sons, Ltd.

关键词： Buses

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An Improved ACO with First-job Restriction and P-ANT for Batch Scheduling Problem

An Improved ACO with First-job Restriction and P-ANT for Bat...

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Symposia and Workshops on Ubiquitous, Autonomic and Trusted computing, UIC-ATC

作者： Yang Yang Zhaohong Jia Yiwen Zhang Kai Li Key Lab of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei China School of Management Hefei University of Technology Hefei China

ISBN: (数字)9781728140346

ISBN: (纸本)9781728140353

This research applies ant colony optimization (ACO) algorithm to minimizing the makespan and the maximum tardiness for scheduling the jobs with non-identical sizes and release time on parallel batch process machines. To improve search efficiency, a new first job selection strategy and a dynamic heuristic are provided. Additionally, a new role, called P-ANT, is designed to improve the search ability of the ant colony. To solve the studied problem, a novel multi-objective ACO algorithm with P-ANT (MACOP) is proposed. The MACOP is compared with several other state-of-the-art algorithms through extensive experiments. The results demonstrate the effectiveness of the proposed MACOP algorithm.

关键词： Heuristic algorithms Job shop scheduling Genetic algorithms signal processing algorithms Optimization Batch production systems Ant colony optimization

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SES: Bridging the Gap Between Explainability and Prediction of Graph Neural Networks

SES: Bridging the Gap Between Explainability and Prediction ...

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International Conference on Data Engineering

作者： Zhenhua Huang Kunhao Li Shaojie Wang Zhaohong Jia Wentao Zhu Sharad Mehrotra Anhui University Hefei China Key Lab of Intelligent Computing and Signal Processing of Ministry of Education Hefei China Amazon Research Seattle USA University of California Irvine Irvine USA

ISBN: (数字)9798350317152

ISBN: (纸本)9798350317169

Despite the Graph Neural Networks' (GNNs) pro-ficiency in analyzing graph data, achieving high-accuracy and interpretable predictions remains challenging. Existing GNN interpreters typically provide post-hoc explanations disjointed from GNNs' predictions, resulting in misrepresentations. Self-explainable GNNs offer built-in explanations during the training process. However, they cannot exploit the explanatory outcomes to augment prediction performance, and they fail to provide high-quality explanations of node features and require additional processes to generate explainable subgraphs, which is costly. To address the aforementioned limitations, we propose a self-explained and self-supervised graph neural network (SES) to bridge the gap between explainability and prediction. SES comprises two processes: explainable training and enhanced predictive learning. During explainable training, SES employs a global mask generator co-trained with a graph encoder and directly produces crucial structure and feature masks, reducing time consumption and providing node feature and subgraph explanations. In the enhanced predictive learning phase, mask-based positive-negative pairs are constructed utilizing the ex-planations to compute a triplet loss and enhance the node representations by contrastive learning. Extensive experiments demonstrate the superiority of SES on multiple datasets and tasks. SES outperforms baselines on real-world node classification datasets by notable margins of up to 2.59% and achieves state-of-the-art (SOTA) performance in explanation tasks on synthetic datasets with improvements of up to 3.0%. Moreover, SES delivers more coherent explanations on real-world datasets, has a fourfold increase in Fidelity+ score for explanation quality, and demonstrates faster training and expla-nation generating times. To our knowledge, SES is a pioneering GNN to achieve SOTA performance on both explanation and prediction tasks.

关键词： Training Bridges Accuracy Reliability engineering Data engineering Graph neural networks Generators

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Understanding the Robustness of 3D Object Detection with Bird'View Representations in Autonomous Driving

Understanding the Robustness of 3D Object Detection with Bir...

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2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2023

作者： Zhu, Zijian Zhang, Yichi Chen, Hai Dong, Yinpeng Zhao, Shu Ding, Wenbo Zhong, Jiachen Zheng, Shibao Institute of Image Communication and Network Engineering Shanghai Jiao Tong University China Institute for Ai Tsinghua University BNRist Center Thbi Lab Dept. of Comp. Sci. and Tech. China School of Computer Science and Technology Anhui University Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Information Materials and Intelligent Sensing Laboratory of Anhui Province China Saic Motor Ai Lab Zhongguancun Laboratory China

ISBN: (纸本)9798350301298

3D object detection is an essential perception task in autonomous driving to understand the environments. The Bird's-Eye-View (BEV) representations have significantly improved the performance of 3D detectors with camera inputs on popular benchmarks. However, there still lacks a systematic understanding of the robustness of these vision-dependent BEV models, which is closely related to the safety of autonomous driving systems. In this paper, we evaluate the natural and adversarial robustness of various representative models under extensive settings, to fully understand their behaviors influenced by explicit BEV features compared with those without BEV. In addition to the classic settings, we propose a 3D consistent patch attack by applying adversarial patches in the 3D space to guarantee the spatiotemporal consistency, which is more realistic for the scenario of autonomous driving. With substantial experiments, we draw several findings: 1) BEV models tend to be more stable than previous methods under different natural conditions and common corruptions due to the expressive spatial representations;2) BEV models are more vulnerable to adversarial noises, mainly caused by the redundant BEV features;3) Camera-LiDARfusion models have superior performance under different settings with multi-modal inputs, but BEV fusion model is still vulnerable to adversarial noises of both point cloud and image. These findings alert the safety issue in the applications of BEV detectors and could facilitate the development of more robust models. © 2023 IEEE.

关键词： Autonomous driving

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Automatic adaptation of annotation standards: Chinese word segmentation and POS tagging: a case study 09

Automatic adaptation of annotation standards: Chinese word s...

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Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language processing of the AFNLP: Volume 1 - Volume 1

作者： Wenbin Jiang Liang Huang Qun Liu Key Lab. of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China Google Research Charleston Rd. Mountain View CA

ISBN: (纸本)9781932432459

Manually annotated corpora are valuable but scarce resources, yet for many annotation tasks such as treebanking and sequence lab.ling there exist multiple corpora with different and incompatible annotation guidelines or standards. This seems to be a great waste of human efforts, and it would be nice to automatically adapt one annotation standard to another. We present a simple yet effective strategy that transfers knowledge from a differently annotated corpus to the corpus with desired annotation. We test the efficacy of this method in the context of Chinese word segmentation and part-of-speech tagging, where no segmentation and POS tagging standards are widely accepted due to the lack of morphology in Chinese. Experiments show that adaptation from the much larger People's Daily corpus to the smaller but more popular Penn Chinese Treebank results in significant improvements in both segmentation and tagging accuracies (with error reductions of 30.2% and 14%, respectively), which in turn helps improve Chinese parsing accuracy.

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A Real-time LoRa-based IoT System for intelligent Meteorological Monitoring

A Real-time LoRa-based IoT System for Intelligent Meteorolog...

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International Conference on Computer and Communications (ICCC)

作者： Donghe Wang Hai Hu Haojun Yang Kan Zheng Ministry of Education Intelligent Computing and Communications (IC2) Lab Wireless Signal Processing and Networks (WSPN) Lab Key Laboratory of Universal Wireless Communications Beijing University of Posts and Telecommunications Beijing China

ISBN: (数字)9781728186351

ISBN: (纸本)9781728186368

Real-time monitoring of meteorological conditions has been arousing increasing attention in current production and life. However, considering the challenges of deployment costs and demand for low power consumption, existing monitoring system needs to be improved to meet the requirements of new Internet-of-Things (IoT) applications. Therefore, a wireless sensor network system dedicated for meteorological monitoring is studied based on Long Range (LoRa) in this paper. Firstly, our meteorological monitoring system is designed for real-time services such as agricultural production demand. Then, the implementation of the proposed system is presented in detail as well as the prototype system is deployed on the campus. Finally, various experiments are conducted to provide the results for demonstrating the reliability and effectiveness of the proposed system.

关键词： Wireless communication Wireless sensor networks Humidity measurement Production Real-time systems Internet of Things Monitoring

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Risk analysis of system security based on evidence theory

Risk analysis of system security based on evidence theory

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2010 International Conference on Computer Design and Applications, ICCDA 2010

作者： Xu, Peida Xu, Jianling Deng, Yong Su, Xiaoyan Key Laboratory of Digital Agricultural Early-warning Technology Ministry of Agriculture of China Beijing China Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University China School of Electronics and Information Technology Shanghai Jiao Tong University Shanghai China Grain Economics Institute Nanjing University of Finance and Economics Nanjing China Hangzhou Key Lab. of E-Business and Information Security Hangzhou Normal University Hanzhou Zhejiang China Hangzhou Key Lab. of E-Business and Information Security Hangzhou Normal University Shanghai China

ISBN: (纸本)9781424471638

Risk evaluation is very important to the design and improvement of physical protection systems. In this paper, an evaluation method of multi-source information fusion is proposed based on the D-S evidence theory. In the proposed method, each individual component of the protection system in the simulated plane is modeled. Then, the threat report of each component according to the specific tactics is determined based on its real environment. Finally, the comprehensive threat distribution is obtained based on through the D-S evidence theory to combine multi-sources information. The proposed method can easily applied to the evaluation of the effectiveness of the protection system. We make the total threat of the protection system lowest through changes of the protection resources allocation. A numerical example is used to illustrate the efficiency of the proposed method. © 2010 IEEE.

关键词： Information fusion

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