scholarly journals A Classification Method of the Incident By Extraction From Text

2019 ◽  
Vol 8 (12S2) ◽  
pp. 1-5 ◽  
Keyword(s):  
Early Warning ◽  
Classification Method ◽  
Accident Risk ◽  
Incident Case ◽  
Matching Rule ◽  
Attribute Matching ◽  
Feature Expression

In this research, in order to use for prediction of the accident risk which prevents serious accident and disaster, the method of detecting and classifying an incident from a text is proposed. A multi-attribute matching machine is used for detection and a classification. The feature expression is extracted from the incident case sentence currently released, and detection of an incident and the classification of an accident kind are carried out by the matching rule created from extraction data. Although classification precision was mostly as good as 0.783 as a result of the evaluation experiment, the room for an improvement for extraction precision was seen. The incident which was able to be managed with flawlessness or a slight injury although it was likely to get injured can warn of a big accident, and can urge evasion of it. Therefore, this research which leads to an early warning by detecting and classifying mechanically is meaningful. A future subject is an improvement of extraction precision.

scholarly journals A Classification Method of the Incident By Extraction From Text

2019 ◽  
Vol 8 (12S2) ◽  
pp. 1-5
Keyword(s):  
Early Warning ◽  
Classification Method ◽  
Accident Risk ◽  
Incident Case ◽  
Matching Rule ◽  
Attribute Matching ◽  
Feature Expression

In this research, in order to use for prediction of the accident risk which prevents serious accident and disaster, the method of detecting and classifying an incident from a text is proposed. A multi-attribute matching machine is used for detection and a classification. The feature expression is extracted from the incident case sentence currently released, and detection of an incident and the classification of an accident kind are carried out by the matching rule created from extraction data. Although classification precision was mostly as good as 0.783 as a result of the evaluation experiment, the room for an improvement for extraction precision was seen. The incident which was able to be managed with flawlessness or a slight injury although it was likely to get injured can warn of a big accident, and can urge evasion of it. Therefore, this research which leads to an early warning by detecting and classifying mechanically is meaningful. A future subject is an improvement of extraction precision.

scholarly journals The Use of UV Spectroscopy and SIMCA for the Authentication of Indonesian Honeys According to Botanical, Entomological and Geographical Origins

Molecules ◽  
2021 ◽  
Vol 26 (4) ◽  
pp. 915
Author(s):  
Diding Suhandy ◽  
Meinilwita Yulia
Keyword(s):  
Spectral Data ◽  
Uv Spectroscopy ◽  
Moving Average ◽  
Food Product ◽  
Classification Method ◽  
Economic Losses ◽  
Food Fraud ◽  
Authentication System ◽  
Uv Visible

As a functional food, honey is a food product that is exposed to the risk of food fraud. To mitigate this, the establishment of an authentication system for honey is very important in order to protect both producers and consumers from possible economic losses. This research presents a simple analytical method for the authentication and classification of Indonesian honeys according to their botanical, entomological, and geographical origins using ultraviolet (UV) spectroscopy and SIMCA (soft independent modeling of class analogy). The spectral data of a total of 1040 samples, representing six types of Indonesian honey of different botanical, entomological, and geographical origins, were acquired using a benchtop UV-visible spectrometer (190–400 nm). Three different pre-processing algorithms were simultaneously evaluated; namely an 11-point moving average smoothing, mean normalization, and Savitzky–Golay first derivative with 11 points and second-order polynomial fitting (ordo 2), in order to improve the original spectral data. Chemometrics methods, including exploratory analysis of PCA and SIMCA classification method, was used to classify the honey samples. A clear separation of the six different Indonesian honeys, based on botanical, entomological, and geographical origins, was obtained using PCA calculated from pre-processed spectra from 250–400 nm. The SIMCA classification method provided satisfactory results in classifying honey samples according to their botanical, entomological, and geographical origins and achieved 100% accuracy, sensitivity, and specificity. Several wavelengths were identified (266, 270, 280, 290, 300, 335, and 360 nm) as the most sensitive for discriminating between the different Indonesian honey samples.

Study on Effect of Spheroidization on Hazardous Classification of ADN

2021 ◽  
Vol 881 ◽  
pp. 71-76
Author(s):  
Jian Yang ◽  
Hong Bin Li ◽  
Song Tao Ren ◽  
Peng Gang Jin ◽  
Zan Gao
Keyword(s):  
Temperature Stability ◽  
Impact Sensitivity ◽  
Classification Method ◽  
Ammonium Dinitramide ◽  
Classification Procedure ◽  
Research Results ◽  
Before And After ◽  
Hazard Classification ◽  
Friction Sensitivity

In order to determine the influence of spheroidization process of Ammonium dinitramide’s hazard grade, the hazardous division of Ammonium dinitramide before and after spheroidization is studied by using hazard classification procedure for combustible and explosive substances and articles standard (WJ20405) and hazard classification method and criterion for combusitible and explosive substances and articles standard (WJ20404). The research results show that spheroidization process can significantly improve the temperature stability of Ammonium dinitramide and significantly reduce friction sensitivity and impact sensitivity of Ammonium dinitramide. So spheroidization process can reduce the hazardous of Ammonium dinitramide and improve the safe character of Ammonium dinitramide.

scholarly journals Segmentation and Multi-Scale Convolutional Neural Network-Based Classification of Airborne Laser Scanner Data

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3347 ◽  
Author(s):  
Zhishuang Yang ◽  
Bo Tan ◽  
Huikun Pei ◽  
Wanshou Jiang
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Laser Scanning ◽  
Laser Scanner ◽  
Region Growing ◽  
Point Clouds ◽  
Classification Method ◽  
Multi Scale ◽  
Airborne Laser

The classification of point clouds is a basic task in airborne laser scanning (ALS) point cloud processing. It is quite a challenge when facing complex observed scenes and irregular point distributions. In order to reduce the computational burden of the point-based classification method and improve the classification accuracy, we present a segmentation and multi-scale convolutional neural network-based classification method. Firstly, a three-step region-growing segmentation method was proposed to reduce both under-segmentation and over-segmentation. Then, a feature image generation method was used to transform the 3D neighborhood features of a point into a 2D image. Finally, feature images were treated as the input of a multi-scale convolutional neural network for training and testing tasks. In order to obtain performance comparisons with existing approaches, we evaluated our framework using the International Society for Photogrammetry and Remote Sensing Working Groups II/4 (ISPRS WG II/4) 3D labeling benchmark tests. The experiment result, which achieved 84.9% overall accuracy and 69.2% of average F1 scores, has a satisfactory performance over all participating approaches analyzed.

scholarly journals Quantifying the effectiveness of early warning systems for natural hazards

2016 ◽  
Vol 16 (1) ◽  
pp. 149-166 ◽  
Author(s):  
M. Sättele ◽  
M. Bründl ◽  
D. Straub
Keyword(s):  
Natural Hazards ◽  
Early Warning ◽  
Risk Mitigation ◽  
Early Warning Systems ◽  
Mitigation Measures ◽  
Management Approach ◽  
Warning Systems ◽  
Integrated Risk ◽  
Framework Approach

Abstract. Early warning systems (EWSs) are increasingly applied as preventive measures within an integrated risk management approach for natural hazards. At present, common standards and detailed guidelines for the evaluation of their effectiveness are lacking. To support decision-makers in the identification of optimal risk mitigation measures, a three-step framework approach for the evaluation of EWSs is presented. The effectiveness is calculated in function of the technical and the inherent reliability of the EWS. The framework is applicable to automated and non-automated EWSs and combinations thereof. To address the specifics and needs of a wide variety of EWS designs, a classification of EWSs is provided, which focuses on the degree of automations encountered in varying EWSs. The framework and its implementation are illustrated through a series of example applications of EWS in an alpine environment.

scholarly journals Quantifying the effectiveness of early warning systems for natural hazards

2015 ◽  
Vol 3 (7) ◽  
pp. 4479-4526 ◽  
Author(s):  
M. Sättele ◽  
M. Bründl ◽  
D. Straub
Keyword(s):  
Natural Hazards ◽  
Early Warning ◽  
Risk Mitigation ◽  
Early Warning Systems ◽  
Mitigation Measures ◽  
Management Approach ◽  
Warning Systems ◽  
Integrated Risk ◽  
Framework Approach

Abstract. Early warning systems (EWS) are increasingly applied as preventive measures within an integrated risk management approach for natural hazards. At present, common standards and detailed guidelines for the evaluation of their effectiveness are lacking. To support decision-makers in the identification of optimal risk mitigation measures, a three-step framework approach for the evaluation of EWS is presented. The effectiveness is calculated in function of the technical and the inherent reliability of the EWS. The framework is applicable to automated and non-automated EWS and combinations thereof. To address the specifics and needs of a wide variety of EWS designs, a classification of EWS is provided, which focuses on the degree of automations encountered in varying EWS. The framework and its implementation are illustrated through a series of example applications of EWS in an alpine environment.

scholarly journals Automatic Morphological Classification of Galaxies

1994 ◽  
Vol 161 ◽  
pp. 243-247
Author(s):  
S. Okamura ◽  
M. Doi ◽  
M. Fukugita ◽  
N. Kashikawa ◽  
M. Sekiguchi ◽  
...  
Keyword(s):  
Surface Brightness ◽  
Classification Method ◽  
Morphological Classification

We study the performance and limitations of the morphological classification method based on luminosity concentration and mean surface brightness. In particular, the effects of the different colour bands and of a finite seeing are investigated.

scholarly journals Classification of Early Type Stars on the Dominion Astrophysical Observatory Photometric System

1973 ◽  
Vol 50 ◽  
pp. 152-161
Author(s):  
S. C. Morris ◽  
G. Hill ◽  
G. A. H. Walker ◽  
H. I. B. Thompson
Keyword(s):  
Classification Method ◽  
Photometric System ◽  
Early Type ◽  
Balmer Series ◽  
Early Type Stars ◽  
Independent Parameters

A classification method has been developed for early–type stars observed on the Dominion Astrophysical Observatory photometric system. Two reddening-independent parameters, Q(35) and Q(38), are used. Q(35) is a measure of the Balmer discontinuity, while Q(38) is a measure of the strength of the upper members of the Balmer series. A preliminary calibration of Q(35) and Q(38) in terms of spectral types and luminosity classes is given, and applications to several groups of stars are shown.

Sign in / Sign up

Export Citation Format

Share Document