Neural Dependency Parser for Tibetan Sentences

2021 ◽  
Vol 20 (2) ◽  
pp. 1-16
Author(s):  
Bo An ◽  
Congjun Long
Keyword(s):  
Expert Knowledge ◽  
Dependency Analysis ◽  
Feature Vectors ◽  
Analysis Task ◽  
Dependency Parser

The research of Tibetan dependency analysis is mainly limited to two challenges: lack of a dataset and reliance on expert knowledge. To resolve the preceding challenges, we first introduce a new Tibetan dependency analysis dataset, and then propose a neural-based framework that resolves the reliance on the expert knowledge issue by automatically extracting feature vectors of words and predicts their head words and type of dependency arcs. Specifically, we convert the words in the sentence into distributional vectors and employ a sequence to vector network to extract feature words. Furthermore, we introduce a head classifier and type classifier to predict the head word and type of dependency arc, respectively. Experiments demonstrate that our model achieves promising performance on the Tibetan dependency analysis task.

Using Expert Knowledge to Identify Visual Cues for Landmine Detection

2008 ◽  
Author(s):  
James J. Staszewski ◽  
Alan D. Davison ◽  
David J. Dippel ◽  
Julia A. Tischuk
Keyword(s):  
Visual Cues ◽  
Expert Knowledge ◽  
Landmine Detection

Influential individuals: Approach to modeling

2018 ◽  
pp. 114-131
Author(s):  
O. Yu. Bondarenko
Keyword(s):  
Social Interactions ◽  
Social Status ◽  
Experimental Approach ◽  
Expert Knowledge ◽  
Formal Models ◽  
Leader Influence ◽  
Learning Game ◽  
Game Theoretic ◽  
Asymmetric Interactions ◽  
Influential Individuals

his article explores theoretical and experimental approach to modeling social interactions. Communication and exchange of information with other people affect individual’s behavior in numerous areas. Generally, such influence is exerted by leaders, outstanding individuals who have a higher social status or expert knowledge. Social interactions are analyzed in the models of social learning, game theoretic models, conformity models, etc. However, there is a lack of formal models of asymmetric interactions. Such models could help elicit certain qualities characterizing higher social status and perception of status by other individuals, find the presence of leader influence and analyze its mechanism.

Implementation of Fuzzy Logic Control on Battery Charging System

2019 ◽  
Vol 3 (1) ◽  
pp. 118-126 ◽  
Author(s):  
Prihangkasa Yudhiyantoro
Keyword(s):  
Complex System ◽  
Fuzzy Logic ◽  
Fuzzy Logic Control ◽  
Expert Knowledge ◽  
Experimental Result ◽  
Rule Base ◽  
Battery Charging ◽  
Charging System ◽  
Logic Control ◽  
Charging Control

This paper presents the implementation fuzzy logic control on the battery charging system. To control the charging process is a complex system due to the exponential relationship between the charging voltage, charging current and the charging time. The effective of charging process controller is needed to maintain the charging process. Because if the charging process cannot under control, it can reduce the cycle life of the battery and it can damage the battery as well. In order to get charging control effectively, the Fuzzy Logic Control (FLC) for a Valve Regulated Lead-Acid Battery (VRLA) Charger is being embedded in the charging system unit. One of the advantages of using FLC beside the PID controller is the fact that, we don’t need a mathematical model and several parameters of coefficient charge and discharge to software implementation in this complex system. The research is started by the hardware development where the charging method and the combination of the battery charging system itself to prepare, then the study of the fuzzy logic controller in the relation of the charging control, and the determination of the parameter for the charging unit will be carefully investigated. Through the experimental result and from the expert knowledge, that is very helpful for tuning of the  embership function and the rule base of the fuzzy controller.

New Feature Vectors using GFCC for Speaker Identification

2018 ◽  
Vol 6 (8) ◽  
pp. 243
Author(s):  
A. Nagesh
Keyword(s):  
Speaker Recognition ◽  
Speaker Identification ◽  
Signal To Noise Ratio ◽  
Main Idea ◽  
Extraction Methods ◽  
Identification System ◽  
Identification Performance ◽  
Feature Vectors ◽  
Overall Performance ◽  
New Feature

The feature vectors of speaker identification system plays a crucial role in the overall performance of the system. There are many new feature vectors extraction methods based on MFCC, but ultimately we want to maximize the performance of SID system.  The objective of this paper to derive Gammatone Frequency Cepstral Coefficients (GFCC) based a new set of feature vectors using Gaussian Mixer model (GMM) for speaker identification. The MFCC are the default feature vectors for speaker recognition, but they are not very robust at the presence of additive noise. The GFCC features in recent studies have shown very good robustness against noise and acoustic change. The main idea is  GFCC features based on GMM feature extraction is to improve the overall speaker identification performance in low signal to noise ratio (SNR) conditions.

Support for Study: Online Educational Environments and the Rights to Education

2008 ◽  
Vol 12 (1) ◽  
Author(s):  
Lin Lin ◽  
Karen Swan
Keyword(s):  
Online Learning ◽  
Conceptual Framework ◽  
Collaborative Inquiry ◽  
Expert Knowledge ◽  
The Self ◽  
Open Educational Resource ◽  
Educational Resource ◽  
Online Learners ◽  
Educational Environments ◽  
Independent Inquiry

This paper uses an online learning conceptual framework to examine the “rights to education” that the current online educational environments could provide. The conceptual framework is composed of three inquiries or three spaces for inquiries, namely, independent inquiry, collaborative inquiry, and formative inquiry towards expert knowledge [42] that online learners pursue and undertake in the process of their learning. Our examinations reveal that most online open educational resource environments (OERs) can incorporate more Web2.0 or Web3.0 technologies so as to provide the self-directed learners, who are the main audience of OERs, with more opportunities to participate, collaborate, and co-create knowledge, and accordingly, to achieve their full rights to education.

Improving the Computational Cost for Copied Region Detection in Forensic Images

2016 ◽  
Vol 2 (1) ◽  
pp. 55
Author(s):  
Tu Huynh-Kha ◽  
Thuong Le-Tien ◽  
Synh Ha ◽  
Khoa Huynh-Van
Keyword(s):  
Wavelet Transform ◽  
Euclidean Distance ◽  
Research Work ◽  
Computational Cost ◽  
Correlation Coefficients ◽  
Zernike Moments ◽  
Computational Time ◽  
Discrete Wavelet ◽  
Feature Vectors ◽  
Region Detection

This research work develops a new method to detect the forgery in image by combining the Wavelet transform and modified Zernike Moments (MZMs) in which the features are defined from more pixels than in traditional Zernike Moments. The tested image is firstly converted to grayscale and applied one level Discrete Wavelet Transform (DWT) to reduce the size of image by a half in both sides. The approximation sub-band (LL), which is used for processing, is then divided into overlapping blocks and modified Zernike moments are calculated in each block as feature vectors. More pixels are considered, more sufficient features are extracted. Lexicographical sorting and correlation coefficients computation on feature vectors are next steps to find the similar blocks. The purpose of applying DWT to reduce the dimension of the image before using Zernike moments with updated coefficients is to improve the computational time and increase exactness in detection. Copied or duplicated parts will be detected as traces of copy-move forgery manipulation based on a threshold of correlation coefficients and confirmed exactly from the constraint of Euclidean distance. Comparisons results between proposed method and related ones prove the feasibility and efficiency of the proposed algorithm.

The Limitations of Wintering Away From Customary Pastures in Relation to Dzud in Mongolia's Gobi Region

2020 ◽  
Vol 24 (1) ◽  
pp. 86-110
Author(s):  
Annika Ericksen
Keyword(s):  
Expert Knowledge ◽  
Ethnographic Research ◽  
Heavy Snowfall ◽  
Variable Environment ◽  
Migration Decisions ◽  
Complicating Factors ◽  
High Uncertainty

This article, based on ethnographic research in a Gobi district in Mongolia, focuses on herders 'wintering away' from customary winter campsites to access better pasture elsewhere. Because of the drawbacks associated with wintering at non-customary as opposed to 'home' pastures, many herders consider 'wintering away' to be a last resort. In the 2009–10 dzud (winter disaster), in Bayanlig soum, most households that wintered away were hit by unusually heavy snowfall and suffered higher livestock losses than those households that stayed at their customary campsites. While herders' migration decisions are guided by expert knowledge of the environment, complicating factors and high uncertainty can contribute to livestock losses despite their best efforts. Mobility is essential to herders' success in a variable environment, but not all forms and instances of migration are equally beneficial. This article draws on herders' accounts to explore a migration dilemma in the Gobi that may become more common.

Sign in / Sign up

Export Citation Format

Share Document