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algorithm for Reaction Classification

JOURNAL OF CHEMICAL INFORMATION AND MODELING 2013年第11期53卷 2884-2895页

作者： Kraut, Hans Eiblmaier, Josef Grethe, Guenter Loew, Peter Matuszczyk, Heinz Saller, Heinz InfoChem GmbH D-81241 Munich Bavaria Germany

Reaction classification has important applications, and many approaches to classification have been applied. Our own algorithm tests all maximum common substructures (MCS) between all reactant and product molecules in order to find an atom mapping containing the minimum chemical distance (MCD). Recent publications have concluded that new MCS algorithms need to be compared with existing methods in a reproducible environment, preferably on a generalized test set, yet the number of test sets available is small, and they are not truly representative of the range of reactions that occur in real reaction databases. We have designed a challenging test set of reactions and are making it publicly available and usable with InfoChem's software or other classification algorithms. We supply a representative set of example reactions, grouped into different levels of difficulty, from a large number of reaction databases that chemists actually encounter in practice, in order to demonstrate the basic requirements for a mapping algorithm to detect the reaction centers in a consistent way. We invite the scientific community to contribute to the future extension and improvement of this data set, to achieve the goal of a common standard.

关键词： algorithm reaction classification Reaction centers sorting algorithm Taxonomy REACTION MCS gene algorithms TEST SETS scientific community

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TRAFFIC PATTERN DETECTION IN A PARTIALLY DEPLOYED VEHICULAR AD HOC NETWORK OF VEHICLES

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IEEE WIRELESS COMMUNICATIONS 2009年第6期16卷 40-46页

作者： Vaqar, Sayyid A. Basir, Otman Univ Waterloo Dept Elect & Comp Engn Waterloo ON N2L 3G1 Canada

Knowledge about traffic conditions on the road play an important role in route planning and avoiding traffic jams. With recent developments in technology, it is possible for vehicles to be equipped with communication and GPS systems. Equipped vehicles on the road can act as nodes to form a vehicular ad hoc network. These nodes can collect information regarding traffic conditions such as position, speed, and direction from other participating nodes. Depending on the number of participating nodes in the ad hoc network, this collected information can provide useful information on driving conditions to the node collecting this information. With proper analysis this information can be used in detecting and/or predicting traffic jam conditions on freeways. In this article the traffic information gathered by a node in an ad hoc network is viewed as a snapshot in time of the current traffic conditions on the road segment. This snapshot is considered as a pattern in time of the current traffic conditions. The pattern. is analyzed using pattern recognition techniques. A weight-of-evidence-based classification algorithm is presented to identify different road traffic conditions. The algorithm is tested using data generated by microscopic modeling of traffic flow for simulation of vehicle or node mobility in ad hoc networks. Test results are presented depicting different percentage levels of vehicles equipped with communication capability.

关键词： vehicle Line of nodes Ad hoc networks sorting algorithm traffic patterns Snapshots Freeway Technology Development route planning Road Traffic Driving Conditions Ganglia traffic congestion Traffic information

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Software Engineering and Scale-Free Networks

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IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS 2009年第4期39卷 845-854页

作者： Wen, Lian Dromey, R. Geoff Kirk, Diana Griffith Univ Software Qual Inst Brisbane Qld 4111 Australia Auckland Univ Technol Auckland 1142 New Zealand

Complex-network theory is a new approach in studying different types of large systems in both the physical and the abstract worlds. In this paper, we have studied two kinds of network from software engineering: the component dependence network and the sorting comparison network (SCN). It is found that they both show the same scale-free property under certain conditions as complex networks in other fields. These results suggest that complex-network theory can be a useful approach to the study of software systems. The special properties of SCNs provide a more repeatable and deterministic way to study the evolution and optimization of complex networks. They also suggest that the closer a sorting algorithm is to the theoretical optimal limit, the more its SCN is like a scale-free network. This may also indicate that, to store and retrieve information efficiently, a concept network might need to be scale-free.

关键词： Concept network (CN) scale-free network software engineering sorting algorithm

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Reducing Computational Complexity of Gating Procedures Using sorting algorithms

Reducing Computational Complexity of Gating Procedures Using...

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International Conference on Information Fusion

作者： Viet Duc Nguyen Tim Claussen Digital Signal Processing and System Theory Christian-Albrechts-Universitat zu Kiel

ISBN: (纸本)9781479902842

Gating is an important part in many data association algorithms, specifically tracking algorithms. Its purpose is the preselection of suitable measurements or observations respectively in order to avoid unlikely measurement-to-track associations. As such, it can be essential for a low computational load. A very common gating method is individual ellipsoidal gating incorporating the Mahalanobis distance. On the one hand it is a reliable gating method used in many different tracking techniques, e.g., the global nearest neighbor method or the Multi-Hypothesis Tracking approach, but on the other hand it can be also very time consuming due to the inversions of covariance matrices related to all the measurement-to-track pairs. In this paper a Gating-by-sorting approach is proposed to accelerate the gating procedure significantly. It uses sorting algorithms to carry out coarse gating followed by a second ellipsoidal gating step. The gating approach is incorporated into a multi-hypothesis tracker and applied to a real radar dataset. Results are obtained by measuring the computational load within tracking processes. They show that the proposed gating algorithm outperforms classical ellipsoidal gating by orders of magnitude.

关键词： sorting algorithm complexity classes nearest neighbor algorithm Primary election data association Inversion tracking

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Variation in target volume and centroid position due to breath holding during four-dimensional computed tomography scanning: A phantom study

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JOURNAL OF APPLIED CLINICAL MEDICAL PHYSICS 2020年第1期21卷 11-17页

作者： Miyamae, Yuta Akimoto, Mami Sasaki, Makoto Fujimoto, Takahiro Yano, Shinsuke Nakamura, Mitsuhiro Kyoto Univ Hosp Div Clin Radiol Serv Kyoto Japan Natl Canc Ctr Dept Radiol Technol Radiol Diag Tokyo Japan Kurashiki Cent Hosp Dept Radiat Oncol Okayama Japan Kyoto Univ Grad Sch Med Div Med Phys Dept Informat Technol & Med EngnHuman Hlth Sci Kyoto Japan

This study investigated the effects of respiratory motion, including unwanted breath holding, on the target volume and centroid position on four-dimensional computed tomography (4DCT) imaging. Cine 4DCT images were reconstructed based on a time-based sorting algorithm, and helical 4DCT images were reconstructed based on both the time-based sorting algorithm and an amplitude-based sorting algorithm. A spherical object 20 mm in diameter was moved according to several simulated respiratory motions, with a motion period of 4.0 s and maximum amplitude of 5 mm. The object was extracted automatically, and the target volume and centroid position in the craniocaudal direction were measured using a treatment planning system. When the respiratory motion included unwanted breath-holding times shorter than the breathing cycle, the root mean square errors (RSME) between the reference and imaged target volumes were 18.8%, 14.0%, and 5.5% in time-based images in cine mode, time-based images in helical mode, and amplitude-based images in helical mode, respectively. In helical mode, the RSME between the reference and imaged centroid position was reduced from 1.42 to 0.50 mm by changing the reconstruction method from time- to amplitude-based sorting. When the respiratory motion included unwanted breath-holding times equal to the breathing cycle, the RSME between the reference and imaged target volumes were 19.1%, 24.3%, and 15.6% in time-based images in cine mode, time-based images in helical mode, and amplitude-based images in helical mode, respectively. In helical mode, the RSME between the reference and imaged centroid position was reduced from 1.61 to 0.83 mm by changing the reconstruction method from time- to amplitude-based sorting. With respiratory motion including breath holding of shorter duration than the breathing cycle, the accuracies of the target volume and centroid position were improved by amplitude-based sorting, particularly in helical 4DCT.

关键词： 4DCT breath-holding time scan mode sorting algorithm

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Integrating LiDAR and high-resolution imagery for object-based mapping of forest habitats in a heterogeneous temperate forest landscape

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INTERNATIONAL JOURNAL OF REMOTE SENSING 2018年第23期39卷 8859-8884页

作者： Gonzalez, Ramiro Silveyra Latifi, Hooman Weinacker, Holger Dees, Matthias Koch, Barbara Heurich, Marco Univ Freiburg Dept Biometry & Environm Syst Anal Tennenbacherstr 4 D-79106 Freiburg Germany KN Toosi Univ Technol Fac Geodesy & Geomat Engn Tehran Iran Univ Wurzburg Dept Remote Sensing Wurzburg Germany Univ Freiburg Chair Remote Sensing & Landscape Informat Syst Freiburg Germany Univ Freiburg Chair Wildlife Ecol & Management Freiburg Germany

Land-cover mapping (LCM) at a fine scale would be useful for forest management across heterogeneous natural landscapes. However, the heterogeneity of land covers at such scales results in complex spectral and textural properties that hinder the applicability of LCM. Besides, the method suffers from, e.g. inconsistent representation of different land-cover types, lack of sufficient and balanced training samples, and instability of classifiers trained by a high number of predictor variables. Even well-known object-based classification approaches are challenged with an objective evaluation of segmentation outputs. Here we classified partially ambiguous land-cover types across heterogeneous forest landscapes in the Bavarian Forest National Park (Germany) by combining metrics from airborne light detection and ranging (LiDAR) and colour infrared (CIR) imagery data and a random forest classifier implemented in an object-based paradigm. We evaluated the segmentation results by creating a global quality score based on inter- and intra-measurements of variance and the number of segments. Selected segmentation outputs were combined with balanced training samples to run the classification algorithm based on representative blocks within the national park. The entire processing chain was implemented in an open-source domain. The final segmentation consisted of LiDAR-based height, image-based Normalized Difference Vegetation Index (NDVI) and red band, with 20 cluster seeds and a minimum segment size of 40 pixels. In the classification, the most important variables included the height of the top layer, NDVI, Enhanced Vegetation Index (EVI) and Green-Red Vegetation Index (GRVI). The average values of 500 random forest runs indicated an overall accuracy of 86.6% and an estimated Cohen's kappa coefficient of 85.2%, with different probabilities of correct classification for land-cover classes. Mature deciduous, standing deadwood, fallen deadwood, meadow, and bare soil classes were clas

关键词： Classifiers object orientation temperate forest sorting algorithm normalized difference vegetation index Taxonomy Bavarian Forest forest habitats Lidar Heterogeneous Disease Predictive Factor Lowest common multiple High resolution imaging

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USING APPLIANCE SIGNATURES FOR MONITORING RESIDENTIAL LOADS AT METER PANEL LEVEL

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IEEE TRANSACTIONS ON POWER DELIVERY 1991年第4期6卷 1380-1385页

作者： SULTANEM, F Direction des Etudes et Recherches Electricitd de France Clamart France

As an initial approach, in order to identify electrical household appliances strictly by analyzing variations in current-voltage signals at meter panel level may seem to be utopian or, to say the least, an ambitious undertaking. However, on observation of the currents consumed by these appliances it is surprising to see that each one of them is recognizable and perfectly identifiable by a certain number of parameters. Nevertheless, difficulties flow from the fact that an appliance is generally switched on while other appliances are already in use. The main issue is then to isolate the characteristic parameters of the appliance from the aggregate signal. One is also aware that the success of the identification does not only depend on the efficiency of the monitoring device, but also on a set of circumstances relating to the composition of the range of appliances installed on the measurement site, and the random sequencing of their operation. This paper presents a study whose aim is to show the feasibility of this device. In particular, it presents the test findings secured on site using a test prototype.

关键词： site measurements sorting algorithm Sufficient Writers measuring instruments Reactive power Device Panel device test LOAD

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DETECTION OF TECHNOGENIC RADIONUCLIDES AT LOW CONCENTRATIONS WHEN MONITORING NUCLEAR POWER PLANT EMISSIONS USING AN ARMS SPECTROMETRIC CHANNEL

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ATOMIC ENERGY 2010年第1期108卷 70-78页

作者： Korolev, S. A. Lavrukhin, Yu. E. Rumyantsev, O. V. Russian Acad Sci GEOKhI RAN Vernadskii Inst Geochem & Analyt Chem Moscow Russia

The application of statistical algorithms in the problem of early detection of technogenic, nuclear power plant emissions in the atmosphere near the ground by means of the spectrometric channel of ARMS ( Automatic Radiation Monitoring System) is examined. It is noted that the changes in the radon progeny content which are associated with the diurnal behavior of the intensity of turbulent mixing influence the variance of the readings in the (131)I and (137)Cs detection ranges. As a result, when a stationary Poisson model is used in the algorithm the number of false alarms increases and the algorithm becomes ineffective. Regional corrections lowering the probability of false alarms to <= 10(-3) with correct detection probability >= 0.7 were introduced into the detection and classification algorithm on the basis of the results of monitoring performed over the course of a year for intervals with stationary gamma background.

关键词： atmosphere reading Early Diagnosis diurnal animal sorting algorithm Variance Nuclear powerplants False alarms Arms algorithms ground turbulent mixing RADON PROGENY

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EVALUATION OF TEXTURAL AND MULTIPOLARIZATION RADAR FEATURES FOR CROP CLASSIFICATION

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IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 1995年第5期33卷 1170-1181页

作者： ANYS, H HE, DC Universite de Sherbrooke Sherbrooke Que Can

The aim of this research is to evaluate crop discrimination using airborne radar data based on multipolarization and textural information. Multipolarization data (C-HH, C-VV, and C-HV) were used for discriminating 5 crop types i.e., corn, wheat, soya, pasture, and alfalfa. For the multipolarization evaluation, an unsupervised classification algorithm and a supervised method based on maximum likelihood were used on the data. For the textural evaluation, textural measures of different degrees were calculated on three different order histograms and were evaluated from the crop discrimination point of view. Results show that multipolarization correct classification rates of 86.31% and 74.47% were obtained for supervised and unsupervised methods respectively. Hence, multipolarization radar data offer an adequate tool for crop identification especially with supervised classification. The evaluation of textural measures shows that for a first order histogram the mean measure gives the best rate of discrimination. In the case of second and third order histograms, the best measures are contrast and large number emphasis respectively. These textural measures were integrated with the three multipolarization channels in order to determine their specific contributions. Results show that crop class separability is thereby improved and that the rate of correct classification increased hy 9.79% for the crops.

关键词： histograms sorting algorithm Discrimination Medicago sativa order maximum likelihood CROP IDENTIFICATION radar data airborne radar

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Classification of multisource remote sensing imagery using a Genetic algorithm and Markov random fields

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IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 1999年第3期37卷 1255-1260页

作者： Tso, BCK Mather, PM Univ Nottingham Sch Geog Nottingham NG7 2RD England

The use of contextual information for modeling the prior probability mass function has found applications in the classification of remotely sensed data, With the increasing availability of multisource remotely sensed data sets, random field models, especially Markov random fields (MRF), have been found to pro,ide a theoretically robust yet mathematical tractable way of coding multisource information and of modeling contextual behavior. It is well known that the performance of a model is dependent both on its functional form (in this case, the classification algorithm) and on the accuracy of the estimates of model parameters, In dealing with multisource data, the determination of source weighting and MRF model parameters is a difficult issue. We extend the methodology proposed in [1] by demonstrating that the use of an effective search procedure, the Genetic algorithm, leads to improved parameter estimation and hence higher classification accuracies.

关键词： model parameters remote-sensing data sorting algorithm remote sensing mass function Parameter estimation Markov random fields Genetic algorithm (GA)

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