The method of classification of user and system data based on the attributes

2016 ◽  
Author(s):  
Igor Zikratov ◽  
Igor Pantiukhin ◽  
Anna Sizykh
Keyword(s):  
System Data

Curb Detection and Accessibility Evaluation from Low-Density Mobile Mapping Point Cloud Data

2018 ◽  
Vol 12 (3) ◽  
pp. 376-385
Author(s):  
Kiichiro Ishikawa ◽  
Daisuke Kubo ◽  
Yoshiharu Amano ◽  
◽  
Keyword(s):  
Point Clouds ◽  
Noise Removal ◽  
Low Density ◽  
Mobile Mapping ◽  
Cloud Data ◽  
Mapping System ◽  
Mobile Mapping System ◽  
System Data ◽  
Scan Data

Our goal is to automatically classify objects from Mobile Mapping System data to enable the automatic construction of dynamic maps. We aimed at the extraction of curbstones and classification of curb types. Although there is much research about curbstones being recognized from laser-scanned point clouds, there are few methods to classify curb types. In this paper, we propose a method to extract curbstones from low-density-type laser scan data. We also propose a method to distinguish whether curbstones allow access to off-road facilities. Evaluation tests give anF-measure of ≥94.4% and an accessibility classification accuracy of ≥99.6%. Moreover, the results of applying multiple filters to noise removal are compared.

scholarly journals UKHTI VS UGHTEA: ARABIC KINSHIP ADDRESS TERM AS SLANG AND IDENTITY IN INDONESIAN TWITTER

2020 ◽  
Author(s):  
Salma Qonitah ◽  
Wiwin Triwinarti
Keyword(s):  
Research Problem ◽  
Internet Usage ◽  
Data Sources ◽  
Possessive Pronoun ◽  
Appraisal System ◽  
Corpus Linguistic ◽  
System Data ◽  
Twitter Users ◽  
Linguistic Approach

Microblogging has taken a quotidian position in the scope of internet usage. This research explores the pragmatic of ughtea, a slang form of ukhti, as a term of address slang and identity in Twitter’s prominent behaviour on virtual sphere: tweeting. Semantically, ukhti refers to “sister” of a possessive pronoun of the first person i.e. the speaker, both in biological and ideological contexts. For the last two years (2018—2019), the usage of the term ukhti has undergone the extension of its meaning through its use among Indonesian Twitter users by changing its form into ughtea as a slang with degenerative meaning, in order to insinuate the exclusivity of the use of the term ukhti among Indonesian conservative Muslims and the misbehavior of ukhti. As a result, the meaning of the term ukhti experiences pejoration. These certain Indonesian Twitter users, according to McCulloch’s classification of Internet People (2019) are classified as Post Internet People. This research problem focuses on the analysis of the speakers, terms, and how both terms used in the context of pejoration. This study aims to analyze both terms in terms of shifting meaning in terms of speakers, speech, and usage by implementing corpus linguistic approach and Martin and White (2005)’s appraisal system. Data sources were obtained from Twitter users' tweets during a certain period (October 2019).

scholarly journals Application of Text Mining Method for Classification of Work Order in Power Grid Production

2021 ◽  
Author(s):  
Yadi Zhao ◽  
Zhifeng Wei ◽  
Bingqiang Gao ◽  
Shuo Zhang
Keyword(s):  
Production Management ◽  
Power Grid ◽  
Production Equipment ◽  
Classification Model ◽  
Document Frequency ◽  
Equipment Failures ◽  
System Data ◽  
Equipment State ◽  
Analysis System

With the completion of the State Grid Corporation’s maintenance system, the number of substations has increased dramatically, the grid structure has become increasingly complex, and there have been internal and external reasons such as the contingency of emergencies, and equipment failures have occurred from time to time. This paper aims to explore the potential value of massive data, show the laws of business data, and further give full play to the comprehensive support of data for enterprise operation and production management, and promote the realization of intelligent and lean power grid core business. This paper uses power system data to provide reliable data support for equipment defect full cycle management and equipment state analysis through ANOVA and neural network statistical analysis. At the same time, we use Term Frequency-Inverse Document Frequency(TF-IDF)Algorithm to calculate the importance of keywords and construct the power keyword library. By constructing Bayesian text classification model, we can classify the defect parts, defect categories and defect causes automatically. This method can be applied to the construction of power grid production work order text analysis system, improve the data quality and system automation level, help the business department to improve work efficiency and provide the basis for power grid business analysis. This method is applied to the data cleaning of the primary production equipment of power grid enterprises, and the accuracy of data error correction for equipment defects with voltages above 110kV is between 93% and 95%, and good results have been achieved.

Note on the spectral classification of carbon stars in the photographic infrared region

1966 ◽  
Vol 24 ◽  
pp. 21-23
Author(s):  
Y. Fujita
Keyword(s):  
Infrared Region ◽  
Spectral Classification ◽  
Carbon Stars

We have investigated the spectrograms (dispersion: 8Å/mm) in the photographic infrared region fromλ7500 toλ9000 of some carbon stars obtained by the coudé spectrograph of the 74-inch reflector attached to the Okayama Astrophysical Observatory. The names of the stars investigated are listed in Table 1.

Diagnostic Value of Electron Microscopy in Soft Tissue Tumors

1970 ◽  
Vol 28 ◽  
pp. 220-221
Author(s):  
Gerald Fine ◽  
Azorides R. Morales
Keyword(s):  
Cardiac Myxoma ◽  
Osteogenic Sarcoma ◽  
Diagnostic Value ◽  
Soft Tissue Tumors ◽  
Amelanotic Melanoma ◽  
Growth Patterns ◽  
Light Microscopic Level ◽  
Mesenchymal Tumors ◽  
Good Agreement

For years the separation of carcinoma and sarcoma and the subclassification of sarcomas has been based on the appearance of the tumor cells and their microscopic growth pattern and information derived from certain histochemical and special stains. Although this method of study has produced good agreement among pathologists in the separation of carcinoma from sarcoma, it has given less uniform results in the subclassification of sarcomas. There remain examples of neoplasms of different histogenesis, the classification of which is questionable because of similar cytologic and growth patterns at the light microscopic level; i.e. amelanotic melanoma versus carcinoma and occasionally sarcoma, sarcomas with an epithelial pattern of growth simulating carcinoma, histologically similar mesenchymal tumors of different histogenesis (histiocytoma versus rhabdomyosarcoma, lytic osteogenic sarcoma versus rhabdomyosarcoma), and myxomatous mesenchymal tumors of diverse histogenesis (myxoid rhabdo and liposarcomas, cardiac myxoma, myxoid neurofibroma, etc.)

Ultrastructure of mesotheliomas

1984 ◽  
Vol 42 ◽  
pp. 98-101
Author(s):  
Irving Dardick
Keyword(s):  
Electron Microscopy ◽  
Latent Period ◽  
Spindle Cell ◽  
Spindle Cell Sarcoma ◽  
Metastatic Adenocarcinoma ◽  
Cell Sarcoma ◽  
Cytological Features ◽  
Industrial Use ◽  
Degree Of Differentiation

With the extensive industrial use of asbestos in this century and the long latent period (20-50 years) between exposure and tumor presentation, the incidence of malignant mesothelioma is now increasing. Thus, surgical pathologists are more frequently faced with the dilemma of differentiating mesothelioma from metastatic adenocarcinoma and spindle-cell sarcoma involving serosal surfaces. Electron microscopy is amodality useful in clarifying this problem.In utilizing ultrastructural features in the diagnosis of mesothelioma, it is essential to appreciate that the classification of this tumor reflects a variety of morphologic forms of differing biologic behavior (Table 1). Furthermore, with the variable histology and degree of differentiation in mesotheliomas it might be expected that the ultrastructure of such tumors also reflects a range of cytological features. Such is the case.

Interpreting HVEM of muscle-cell impulse networks

1992 ◽  
Vol 50 (1) ◽  
pp. 126-127
Author(s):  
Paul DeCosta ◽  
Kyugon Cho ◽  
Stephen Shemlon ◽  
Heesung Jun ◽  
Stanley M. Dunn
Keyword(s):  
Structural Analysis ◽  
Muscle Cell ◽  
Electron Micrographs ◽  
Relative Size ◽  
Automatic Classification ◽  
Nerve Fibers ◽  
Analysis Algorithm ◽  
Structural Networks

Introduction: The analysis and interpretation of electron micrographs of cells and tissues, often requires the accurate extraction of structural networks, which either provide immediate 2D or 3D information, or from which the desired information can be inferred. The images of these structures contain lines and/or curves whose orientation, lengths, and intersections characterize the overall network.Some examples exist of studies that have been done in the analysis of networks of natural structures. In, Sebok and Roemer determine the complexity of nerve structures in an EM formed slide. Here the number of nodes that exist in the image describes how dense nerve fibers are in a particular region of the skin. Hildith proposes a network structural analysis algorithm for the automatic classification of chromosome spreads (type, relative size and orientation).

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