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Research on students' mental crisis monitoring and intervention mechanism based on online social network

Research on students' mental crisis monitoring and intervent...

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2012 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2012

作者： Li, Suna Shao, Xia Zhao, Feifei Tianjin Polytechnic University Tianjin China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Dongguan Research Institute of CASIA Cloud Computing Center Chinese Academy of Sciences Songshan Lake Dongguan China

ISBN: (纸本)9781467324007

Internet as the fertile ground of free speech, everyone can express their emotions, cognition and views of things via the internet, especially in the era of Web2.0, the occurrence of blog which provides a wider space for personal speech. Internet provides a broad platform for contemporary college students to express thought and emotion, at the same time it provides a channel for education workers to understand students' thought and mental. Through real-time monitoring information on school area network, we can get real-time status, mood and some dynamic data which can portray characteristics of emotion of the concerned entity;also we can abstract the characterization of psychological crisis information, and use this feature to do data mining on these data. In this way we can find group of students which have tendency of psychological crisis, and use corresponding psychological crisis intervention online and offline methods to ease students' psychological crisis and to prevent tragic events in timely. © 2012 IEEE.

关键词： Students

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Human behavior model and its application on performance management in a chemical plant workshop

Human behavior model and its application on performance mana...

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2012 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2012

作者： Han, Feng Liu, Xiwei Shang, Xiuqin Cheng, Changjian Li, Bo Fan, Dong Olefine Plant SINOPEC Qilu Petrochemical Co. Ltd. Zibo China School of Chemical Engineering Beijing University of Chemical Technology Beijing China State Key Laboratory of Management and Control for Complex Systems Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Beijing China Dongguan Research Institute of CASIA Cloud Computing Center Chinese Academy of Sciences Songshan Lake Dongguan China

ISBN: (纸本)9781467324007

To investigate the influences of performance management rules on human behavior in a chemical plant workshop, we construct an artificial workshop. It mainly contains human behavior model, workshop environment model including the definition of work position performance management rules and production events, and their interaction rules. The human behavior model is built based on DISC (Dominance, Influence, Steadiness, Compliance) behavior model and the Agent technology. A platform for workshop human behavior computing is finally created for computational experiments on performance management and decision-making. The platform can be used as a support for refined management in the chemical plant. © 2012 IEEE.

关键词： Chemical plants

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Chinese Coreference Resolution via Ordered Filtering 12

Chinese Coreference Resolution via Ordered Filtering

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Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning

作者： Xiaotian Zhang Chunyang Wu Hai Zhao Center for Brain-Like Computing and Machine Intelligence Department of Computer Science and Engineering Shanghai Jiao Tong UniversityMOE-Microsoft Key Laboratory for Intelligent Computing and Intelligent Systems Shanghai Jiao Tong University

ISBN: (纸本)9781627484046

We in this paper present the model for our participation (BCMI) in the CoNLL-2012 Shared Task. This paper describes a pure rule-based method, which assembles different filters in a proper order. Different filters handle different situations and the filtering strategies are designed manually. These filters are assigned to different ordered tiers from general to special cases. We participated in the Chinese and English closed tracks, scored 51.83 and 59.24 respectively.

关键词： Coreference Resolution Filtration Filters Ordered Chinese philosophy Chinese Chinese art proper order paper

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Hybrid Rule-based Algorithm for Coreference Resolution 12

Hybrid Rule-based Algorithm for Coreference Resolution

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Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning

作者： Heming Shou Hai Zhao Center for Brain-Like Computing and Machine Intelligence Department of Computer Science and Engineering Shanghai Jiao Tong UniversityMOE-Microsoft Key Laboratory for Intelligent Computing and Intelligent Systems Shanghai Jiao Tong University

ISBN: (纸本)9781627484046

This paper describes our coreference resolution system for the CoNLL-2012 shared task. Our system is based on the Stanford's dcore-f deterministic system which applies multiple sieves with the order from high precision to low precision to generate coreference chains. We introduce the newly added constraints and sieves and discuss the improvement on the o-riginal system. We evaluate the system using OntoNotes data set and report our results of average F-score 58.25 in the closed track.

关键词： Coreference Resolution Sieves sieving

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A novel parking control algorithm for a car-like mobile robot

A novel parking control algorithm for a car-like mobile robo...

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IEEE International Conference on Networking, Sensing and Control

作者： Yaru Zhang Shuming Tang Zhilin Zhang State Key Laboratory of Management and Control for Complex Systems Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China

This paper proposes a novel algorithm for parking motion of a Car-like mobile robot. The algorithm presented here addresses calculating equations for planning a parking path in real time. Moreover, by incorporating the constraints of the mechanical and kinematical characteristics of the car and the geometry of the parking lot in the path planning, we can turn a parking problem into solving algebraic equations. By tracking a planned path, the Car-like mobile robot can drive into the parking area without hitting any boundaries. The efficiency of the proposed algorithm is demonstrated by simulation.

关键词： Vehicles Mobile robots Algorithm design and analysis Mathematical model Turning Equations Signal processing algorithms

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A weighted pattern recognition algorithm for short-term traffic flow forecasting

A weighted pattern recognition algorithm for short-term traf...

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IEEE International Conference on Networking, Sensing and Control

作者： Shuangshuang Li Zhen Shen Fei-Yue Wang State Key Laboratory of Management and Control for Complex Systems Beijing Engineering Research Center for Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China

The k-nearest neighbor (k-NN) nonparametric regression is a classic model for single point short-term traffic flow forecasting. The traffic flows of the same clock time of the days are viewed as neighbors to each other, and the neighbors with the most similar values are regarded as nearest neighbors and are used for the prediction. In this method, only the information of the neighbors is considered. However, it is observed that the “trends” in the traffic flows are useful for the prediction. Taking a sequence of consecutive time periods and viewing the a sequence of “increasing”, “equal” or “decreasing” of the traffic flows of two consecutive periods as a pattern, it is observed that the patterns can be used for prediction, despite the patterns are not from the same clock time period of the days. Based on this observation, a pattern recognition algorithm is proposed. Moreover, empirically, we find that the patterns from different clock time of the days can have different contributions to the prediction. For example, if both to predict the traffic flow in the morning, the pattern from the morning can lead to better prediction than same patterns from afternoon or evening. In one sentence, we argue that both the pattern and the clock time of the pattern contain useful information for the prediction and we propose the weighted pattern recognition algorithm (WPRA). We give different weights to the same patterns of different clock time for the prediction. In this way, we take both virtues of the k-NN method and the PRA method. We use the root mean square error (RMSE) between the actual traffic flows and the predicted traffic flows as the measurement. By applying the results to actual data and the simulated data, about 20% improvement compare with the PRA is obtained.

关键词： Clocks Data models Pattern recognition Prediction algorithms Mathematical model Meteorology Vectors

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A review on vision-based pedestrian detection in intelligent transportation systems

A review on vision-based pedestrian detection in intelligent...

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IEEE International Conference on Networking, Sensing and Control

作者： Bo Li Qingming Yao Kunfeng Wang State Key Laboratory of Management and Control for Complex Systems Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China

Pedestrians are key participants in transportation systems, so pedestrian detection in video surveillance systems is of great significance to the research and application of intelligent Transportation systems (ITS). We review some methods and models for vision-based pedestrian detection in recent years. In this paper, the pedestrian detection techniques are divided into macroscopic and microscopic according to different application in transportation systems. Macroscopic pedestrian detection aims to estimate crowd density without distinguishing each pedestrian, and microscopic pedestrian detection focuses on detection and recognition of individual pedestrians. The latter detection style is deeply studied, so it is presented in detail in this paper, especially for the feature-classifier-based detection method. Finally, the pedestrian detection algorithms are discussed and concluded from the viewpoint of video surveillance and ITS. Existing problems and future trends are presented in that section.

关键词： Feature extraction Shape Training Transportation Traffic control Video surveillance

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A vehicle license plate recognition system based on analysis of maximally stable extremal regions

A vehicle license plate recognition system based on analysis...

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IEEE International Conference on Networking, Sensing and Control

作者： Bo Li Bin Tian Qingming Yao Kunfeng Wang State Key Laboratory of Management and Control for Complex Systems Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China

Vehicle License Plate Recognition (VLPR) system is a core module in intelligent Transportation systems (ITS). In this paper, a VLPR system is proposed. Considering that license plate localization is the most important and difficult part in VLPR system, we present an effective license plate localization method based on analysis of Maximally Stable Extremal Region (MSER) features. Firstly, MSER detector is utilized to extract candidate character regions. Secondly, the exact locations of license plates are inferred according to the arrangement of characters in standard license plates. The advantage of this license plate localization method is that less assumption of environmental illumination, weather and other conditions is made. After license plate localization, we continue to recognize the license plate characters and color to complete the whole VLPR system. Finally, the proposed VLPR system is tested on our own collected dataset. The experimental results show the availability and effectiveness of our VLPR system in locating and recognizing all the explicit license plates in an image.

关键词： Licenses Image color analysis Character recognition Lighting Histograms Feature extraction Image segmentation

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Rear lamp based vehicle detection and tracking for complex traffic conditions

Rear lamp based vehicle detection and tracking for complex t...

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IEEE International Conference on Networking, Sensing and Control

作者： Ye Li Qingming Yao State Key Laboratory of Management and Control for Complex Systems Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China

In video surveillance system, detection and tracking of vehicles are two foundational and significant tasks. In this paper, a vehicle detection and tracking method based on rear lamp pairs is proposed. The proposed method combines color with motion information to perform vehicle detection. In order to adapt to different weather conditions like night, the rear lamps are divided into two categories: unlit lamps and lighted lamps. First, threshold segmentation are used to extract both the unlit and lighted lamp candidates in hue-saturation-value (HSV) color space and the thresholds are selected automatically by maximally stable extremal region (MSER) method. Then, all lamp candidates are tracked by using Kalman filter and lamp candidates with short-lived trajectories are removed to avoid disturbances. Next, two adjacent lamp candidates with similar speed are bound together as a region of interest (ROI), which represents a potential pair of lamps. Image cross-correlation symmetry analysis based on Gabor filter is utilized to find the ROIs with symmetrical texture and these symmetric ROIs can be regarded as pairs of lamps. The experimental results show that the proposed method can effectively deal with various illumination conditions and improve the accuracy and robustness of vehicle detection. In addition, this method can perform vehicle detection and tracking under complex traffic conditions and the Gabor filter based symmetry analysis can successfully suppress subtle difference between the left and right parts of a vehicle as well as environment noises.

关键词： Vehicles Image color analysis Vehicle detection Gabor filters Correlation Tracking Kalman filters

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Adaptive exponential time-varying sliding mode control for hypersonic cruise vehicles

Adaptive exponential time-varying sliding mode control for h...

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Chinese Control Conference (CCC)

作者： Liang Wang Xiangdong Liu Binglong Cong Zhen Chen Key laboratory for Intelligent Control & Decision of Complex Systems Beijing Institute of Technology Beijing China Beijing Institute of Technology Beijing Beijing CN

ISBN: (纸本)9781467325813

This paper describes the design of an adaptive exponential time-varying sliding mode control (AETVSMC) with strong robustness for hypersonic cruise vehicles subject to parametric uncertainties on the inertial and aerodynamic coefficients. An adaptation scheme is adopted to deal with unknown but bounded system uncertainties. Thus, the selection of switching gains can be obtained on-line and the upper bounds of the model uncertainties are not required to be known in advance. Stability analysis of the closed-loop system is derived based on the Lyapunov theory. Finally, simulation results demonstrate the effectiveness and robustness of the proposed approach.

关键词： Uncertainty Vehicles Adaptation models Switches Robustness Aerodynamics

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