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Himawari-8 Satellite Based Dynamic Monitoring of Grassland Fire in China-Mongolia Border Regions

SENSORS 2018年第1期18卷 276页

作者： Na, Li Zhang, Jiquan Bao, Yulong Bao, Yongbin Na, Risu Tong, Siqin Si, Alu Northeast Normal Univ Sch Environm Changchun 130024 Peoples R China Minist Educ Key Lab Vegetat Ecol Changchun 130024 Peoples R China Inner Mongolia Normal Univ Collage Geog Hohhot 010022 Peoples R China Northeast Normal Univ Sch Geog Sci Changchun 130024 Peoples R China

In this study, we used bands 7, 4, and 3 of the Advance Himawari Imager (AHI) data, combined with a threshold algorithm and a visual interpretation method to monitor the entire process of grassland fires that occurred on the China-Mongolia border regions, between 05:40 (UTC) on April 19th to 13:50 (UTC) on April 21st 2016. The results of the AHI data monitoring are evaluated by the fire point product data, the wind field data, and the environmental information data of the area in which the fire took place. The monitoring result shows that, the grassland fire burned for two days and eight hours with a total burned area of about 2708.29 km(2). It mainly spread from the northwest to the southeast, with a maximum burning speed of 20.9 m/s, a minimum speed of 2.52 m/s, and an average speed of about 12.07 m/s. Thus, using AHI data can not only quickly and accurately track the dynamic development of a grassland fire, but also estimate the spread speed and direction. The evaluation of fire monitoring results reveals that AHI data with high precision and timeliness can be highly consistent with the actual situation.

关键词： threshold algorithm visual interpretation Himawari-8 satellite grassland fire China-Mongolia border regions

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Imposing Minimax and Quantile Constraints on Optimal Matching in Observational Studies

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JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS 2017年第1期26卷 66-78页

作者： Rosenbaum, Paul R. Univ Penn Wharton Sch Dept Stat Philadelphia PA 19104 USA

Modern methods construct amatched sample byminimizing the total cost of a flow in a network, finding a pairing of treated and control individuals that minimizes the sum of within-pair covariate distances subject to constraints that ensure distributions of covariates are balanced. In aggregate, these methods work well;however, they can exhibit a lack of interest in a small number of pairs with large covariate distances. Here, a newmethod is proposed for imposing a minimax constraint on aminimum total distancematching. Such a match minimizes the total within-pair distance subject to various constraints including the constraint that the maximum pair difference is as small as possible. In an example with 1391 matched pairs, this constraint eliminates dozens of pairs with moderately large differences in age, but otherwise exhibits the same excellent covariate balance found without this additional constraint. A minimax constraint eliminates edges in the network, and can improve the worst-case time bound for the performance of the minimum cost flow algorithm, that is, a better match from a practical perspective may take less time to construct. The techni-ue adapts ideas for a different problem, the bottleneck assignment problem, whose sole objective is to minimize the maximum within-pair difference;however, here, that objective becomes a constraint on the minimum cost flow problem. The method generalizes. Rather than constrain the maximum distance, it can constrain an order statistic. Alternatively, the method can minimize the maximum difference in propensity scores, and subject to doing that, minimize the maximum robust Mahalanobis distance. An example from labor economics is used to illustrate. Supplementary materials for this article are available online.

关键词： Bottleneck assignment Fine balance threshold algorithm

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A NeuroFuzzy Approach for Fall Detection 23

A NeuroFuzzy Approach for Fall Detection

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23rd International Conference on Engineering, Technology and Innovation (ICE/ITMC)

作者： Ando, B. Baglio, S. Marletta, V. Crispino, R. Univ Catania Dept Elect Elect & Informat Engn DIEEI Catania Italy

ISBN: (纸本)9781538607749

Falls represent a serious issue which can have catastrophic consequences and the need for ICT based solutions aimed to improve the life quality and autonomy of frail people, is hence emerging, with particular regards to falls' detection and classification. Although two main computing approaches for fall detection are threshold based algorithms and machine learning methods, it can be affirmed that up today a well-accepted solution has not been yet identified. In this paper, the experience in developing reliable fall detector of the research group working in the field of assistive technologies at the DIEEI of the University of Catania-Italy is reported, with specific regards to the investigation of a NeuroFuzzy based approach.

关键词： Assistive Technology ADL Fall Detection Smartphone Inertial Sensors threshold algorithm NeuroFuzzy paradigm

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A Multisensor Data-Fusion Approach for ADL and Fall classification

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IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 2016年第9期65卷 1960-1967页

作者： Ando, Bruno Baglio, Salvatore Lombardo, Cristian Orazio Marletta, Vincenzo Univ Catania Dept Elect Elect & Informat Engn I-95126 Catania Italy

This paper deals with an advanced approach for the monitoring of elders and people with neurological pathologies (e.g., Alzheimer). The system that adopts a multisensor approach is able to recognize critical events, such as falls or prolonged inactivity, to monitor the user posture, and to notify the alerts to caregivers. In particular, this paper focuses on smart algorithms developed for the activities of daily living (ADL) classification, which use the information provided by inertial sensors embedded in the user device. In particular, a novel multisensor data-fusion approach, combining data from an accelerometer and a gyroscope, is presented. Apart from alert management, the information provided by this system is useful to track the evolution of the user pathology, also during rehabilitation tasks. Results obtained during tests with users demonstrate suitable performances of the adopted paradigm, in terms of sensitivity and specificity, in performing falls and ADL classification tasks. The average value of the sensitivity index for the classes of falls and ADL considered through this paper is 0.81, while the average value of the specificity index is 0.98.

关键词： Ambient Assisted Living (AAL) activities of daily living (ADL) fall detection inertial sensors smartphone threshold algorithm user posture user safety monitoring

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Representation of the non-dominated set in biobjective discrete optimization

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COMPUTERS & OPERATIONS RESEARCH 2015年第Nov.期63卷 172-186页

作者： Vaz, Daniel Paquete, Luis Fonseca, Carlos M. Klamroth, Kathrin Stiglmayr, Michael Max Planck Inst Informat D-66123 Saarbrucken Germany Univ Coimbra Dept Informat Engn CISUC P-3000 Coimbra Portugal Univ Wuppertal Dept Math & Nat Sci Wuppertal Germany

This paper introduces several algorithms for finding a representative subset of the non-dominated point set of a biobjective discrete optimization problem with respect to uniformity, coverage and the epsilon-indicator. We consider the representation problem itself as multiobjective, trying to find a good compromise between these quality measures. These representation problems are formulated as particular facility location problems with a special location structure, which allows for polynomial-time algorithms in the biobjective case based on the principles of dynamic programming and threshold approaches. In addition, we show that several multiobjective variants of these representation problems are also solvable in polynomial time. Computational results obtained by these approaches on a wide range of randomly generated point sets are presented and discussed. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Multiobjective discrete optimization Representation Dynamic programming threshold algorithm

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Efficient processing of optimal meeting point queries in Euclidean space and road networks

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KNOWLEDGE AND INFORMATION SYSTEMS 2015年第2期42卷 319-351页

作者： Yan, Da Zhao, Zhou Ng, Wilfred Hong Kong Univ Sci & Technol Dept Comp Sci & Engn Kowloon Hong Kong Peoples R China

Finding an optimal meeting point (OMP) for a group of people (or a set of objects) at different locations is an important problem in spatial query processing. There are many real-life applications related to this problem, such as determining the location of a conference venue, deciding the pick-up location of a tourist bus, and planing tactics of artificial intelligence in real-time strategy games. Formally, given a set of query points in a spatial setting , an OMP query fetches the point that minimizes a cost function defined over the distances from to all points in . Since there are infinitely many locations in a given space setting, it is infeasible to examine all of them to find the OMP, and thus, the problem is challenging. In this paper, we study OMP queries in the following two spatial settings which are common in real-life applications: Euclidean space and road networks. In the setting of Euclidean space, we propose a general framework for answering all OMP query variants and also identify the best algorithms for particular types of OMP queries in the literature. In the setting of road networks, we study how to access only part of the road network and examine part of the candidates. Specifically, we explore two pruning techniques, namely Euclidean distance bound and threshold algorithm, which help improve the efficiency of OMP query processing. Extensive experiments are conducted to demonstrate the efficiency of our proposed approaches on both real and synthetic datasets.

关键词： Optimal meeting point Spatial query processing Road network threshold algorithm

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Detecting Slipping-Like Perturbations by Using Adaptive Oscillators

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ANNALS OF BIOMEDICAL ENGINEERING 2015年第2期43卷 416-426页

作者： Tropea, Peppino Vitiello, Nicola Martelli, Dario Aprigliano, Federica Micera, Silvestro Monaco, Vito Scuola Super Sant Anna BioRobot Inst I-56025 Pisa Italy Don Carlo Gnocchi Fdn I-50143 Florence Italy Ecole Polytech Fed Lausanne Translat Neural Engn Lab Ctr Neuroprosthet CH-1015 Lausanne Switzerland Ecole Polytech Fed Lausanne Sch Engn Inst Bioengn CH-1015 Lausanne Switzerland

This study introduces a novel algorithm to detect unexpected slipping-like perturbations based on the comparison between actual leg joint angles and those predicted by a pool of adaptive oscillators. The approach grounds on the hypothesis that during postural transitions, the difference between these datasets diverges and can early signal that the dynamic balance is challenged. To test this hypothesis, leg joint angles of twelve healthy young participants were recorded while undergoing four different perturbations delivered during steady locomotion. Joint angles were estimated after spanning the whole domain of the adaptive oscillator dynamics. Results confirmed that the implemented strategy allows to early detect a postural transition induced by a slipping-like perturbation: the best performance is represented by a mean detection time ranging between 150 and 250 ms and a low rate (lower than 10%) of false alarms. On the whole, the proposed approach is efficient even if it is based on a quite simple threshold-based algorithm. Moreover, it does not need any falling-based training before being implemented, is not computationally heavy, and is not subject dependent. Finally, since it is based on leg joint angles, it appears well suited to be implemented in lower-limb orthoses/prostheses already equipped with joint position sensors.

关键词： Pre-fall detection Adaptive oscillators Perturbation Walking Joint angles threshold algorithm

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Top-k queries on RDF graphs

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INFORMATION SCIENCES 2015年 316卷 201-217页

作者： Wang, Dong Zou, Lei Zhao, Dongyan Peking Univ Beijing 100871 Peoples R China

Recent years have witnessed unprecedented volumes of structured data published in RDF format. Taking full advantage of such data has attracted a growing amount of research interest from both academia and industry. However, efficient processing of top-k queries in RDF data is still a new topic. Most existing approaches ignore top-k queries, or only provide a limited number of ranking functions. In this paper, we provide an effective and efficient processing algorithm for top-k queries that consists of a novel tree-style index MS-tree and MS-tree-based filtering and pattern-matching functions. Firstly, candidate entities in RDF data were efficiently ranked and filtered through an MS-tree-based topdown method. Then, query structure patterns are matched in RDF data through graphic exploration. In order to handle more complex scoring functions, a dynamic variable selecting optimization is employed to accelerate the threshold decrease. We evaluate our solutions with both synthetic and real-world datasets. The experimental results show that our model significantly outperforms state-of-the-art approaches. (C) 2015 Elsevier Inc. All rights reserved.

关键词： Top-k SPARQL query Graph exploration Entity encoding threshold algorithm

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Efficient location-based search of trajectories with location importance

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KNOWLEDGE AND INFORMATION SYSTEMS 2015年第1期45卷 215-245页

作者： Yan, Da Cheng, James Zhao, Zhou Ng, Wilfred Chinese Univ Hong Kong Dept Comp Sci & Engn Shatin Hong Kong Peoples R China Hong Kong Univ Sci & Technol Dept Comp Sci & Engn Hong Kong Hong Kong Peoples R China

Given a database of trajectories and a set of query locations, location-based trajectory search finds trajectories in the database that are close to all the query locations. Location-based trajectory search has many applications such as providing reference routes for travelers who are planning a trip to multiple places of interest. However, previous studies only consider the spatial aspect of trajectories, which is inadequate for real applications. For example, one may obtain the reference route of a tourist who just passed by a place of interest without paying a visit. We propose the Important Connected Trajectories (k-ICT) query by associating trajectories with location importance. For any query location, the result trajectories should contain an important point close to it. We describe an effective method to infer the importance of trajectory points from the temporal information. We also propose efficient R-tree-based and grid-based algorithms to answer -ICT queries, and verify the efficiency of our algorithms through extensive experiments on both real and synthetic datasets.

关键词： Trajectory Location importance threshold algorithm Voronoi diagram

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fNIRS-Based Wavelet thresholds for Motor Area Determination 5

fNIRS-Based Wavelet Thresholds for Motor Area Determination

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5th International Conference on the Development of Biomedical Engineering in Vietnam

作者： Ha, Dao V. Nguyen, Hai T. Ngo, Cuong Q. Tran, Mai T. Toi Van Vo HCMC Univ Tech Educ Fac Elect Elect Engn Hanoi Vietnam HCMC Univ Technol Fac Elect Elect Engn Hanoi Vietnam Int Univ Dept Biomed Engn VNU HCMC Hanoi Vietnam

ISBN: (纸本)9783319117768;9783319117751

The brain is the most important part in human body. In order to determine and evaluate the activities of the body, brain signals measured using non-invasive technique functional Near Infrared Spectroscopy (fNIRS) will be investigated. In this paper, Oxy- Hb signals in the cerebral cortex that was collected from 24 channels put into preprocessing to smooth using a Savitzky - Golay filter. Data removed noise will be transformed discrete wavelets into different frequency components. threshold algorithms are applied to identify the channels (the mobile areas) that have Oxy - Hb changes while biting spacer and lifting object. This research is conducted experiments on five subjects with changes of biting or lifting for collection of the Oxy - Hb changes on the mobile areas. This method will help researchers save a lot of effort and archive the proper assessment of human activities through brain signals.

关键词： fNIRS data threshold algorithm discrete wavelet transform

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