AN APPROACH TO NATURAL STROKE EXTRACTION FOR OFF-LINE LOOSELY-CONSTRAINED HANDWRITTEN CHINESE CHARACTERS

2003 ◽  
Vol 17 (08) ◽  
pp. 1483-1513
Author(s):  
DANIEL S. YEUNG ◽  
H. S. FONG ◽  
ERIC C. C. TSANG ◽  
WENHAO SHU ◽  
XIAOLONG WANG
Keyword(s):  
Performance Tuning ◽  
Model Parameters ◽  
Chinese Characters ◽  
Personal Writing ◽  
New Approach ◽  
Stroke Extraction ◽  
Fuzzy Partitioning ◽  
Stroke Models ◽  
Matching Strategy ◽  
Ranked List

This paper proposes a new approach to extracting natural strokes from the skeletons of loosely-constrained, off-line handwritten Chinese characters. It admits the output substrokes from a previously proposed fuzzy substroke extractor as its inputs. By identifying a number of expected ambiguities which include mutual similarities, unstable touches and joint/cross distortions, fuzzy stroke models are constructed and a "hit-all" fuzzy stroke matching strategy is pursued. Fuzzy partitioning technique is used to generate a ranked list of consistent stroke sets from the set of fuzzy strokes being identified. With this approach, a maximum of 20 distinct natural stroke classes can be extracted from each input character, together with an estimate on the actual count of strokes which compose the character. Our system offers a number of performance tuning capabilities such as the computation of the fuzzy scores of each extracted stroke, the adjustment on the fuzzy stroke model parameters, and the potential of incorporating one's personal writing styles into our methodology.

scholarly journals A New Approach to Group Multi-Objective Optimization under Imperfect Information and Its Application to Project Portfolio Optimization

2021 ◽  
Vol 11 (10) ◽  
pp. 4575
Author(s):  
Eduardo Fernández ◽  
Nelson Rangel-Valdez ◽  
Laura Cruz-Reyes ◽  
Claudia Gomez-Santillan
Keyword(s):  
Portfolio Optimization ◽  
Imperfect Information ◽  
Model Parameters ◽  
Final Decision ◽  
Project Portfolio ◽  
Objective Functions ◽  
Multi Objective Optimization ◽  
New Approach ◽  
Multi Objective ◽  
Group Member

This paper addresses group multi-objective optimization under a new perspective. For each point in the feasible decision set, satisfaction or dissatisfaction from each group member is determined by a multi-criteria ordinal classification approach, based on comparing solutions with a limiting boundary between classes “unsatisfactory” and “satisfactory”. The whole group satisfaction can be maximized, finding solutions as close as possible to the ideal consensus. The group moderator is in charge of making the final decision, finding the best compromise between the collective satisfaction and dissatisfaction. Imperfect information on values of objective functions, required and available resources, and decision model parameters are handled by using interval numbers. Two different kinds of multi-criteria decision models are considered: (i) an interval outranking approach and (ii) an interval weighted-sum value function. The proposal is more general than other approaches to group multi-objective optimization since (a) some (even all) objective values may be not the same for different DMs; (b) each group member may consider their own set of objective functions and constraints; (c) objective values may be imprecise or uncertain; (d) imperfect information on resources availability and requirements may be handled; (e) each group member may have their own perception about the availability of resources and the requirement of resources per activity. An important application of the new approach is collective multi-objective project portfolio optimization. This is illustrated by solving a real size group many-objective project portfolio optimization problem using evolutionary computation tools.

scholarly journals A New Extended-F Family: Properties and Applications to Lifetime Data

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Saima K. Khosa ◽  
Ahmed Z. Afify ◽  
Zubair Ahmad ◽  
Mi Zichuan ◽  
Saddam Hussain ◽  
...  
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Estimators ◽  
Real Data ◽  
Model Parameters ◽  
Additional Parameter ◽  
Alpha Power ◽  
New Approach ◽  
New Class ◽  
Mathematical Properties ◽  
Extended Weibull Distribution

In this article, a new approach is used to introduce an additional parameter to a continuous class of distributions. The new class is referred to as a new extended-F family of distributions. The new extended-Weibull distribution, as a special submodel of this family, is discussed. General expressions for some mathematical properties of the proposed family are derived, and maximum likelihood estimators of the model parameters are obtained. Furthermore, a simulation study is provided to evaluate the validity of the maximum likelihood estimators. Finally, the flexibility of the proposed method is illustrated via two applications to real data, and the comparison is made with the Weibull and some of its well-known extensions such as Marshall–Olkin Weibull, alpha power-transformed Weibull, and Kumaraswamy Weibull distributions.

STROKE RELATION CODING—A NEW APPROACH TO THE RECOGNITION OF MULTI-FONT PRINTED CHINESE CHARACTERS

1988 ◽  
Vol 02 (01) ◽  
pp. 149-160 ◽  
Author(s):  
PO-NING CHEN ◽  
YUNG-SHENG CHEN ◽  
WEN-HSING HSU
Keyword(s):  
Data Base ◽  
Relative Position ◽  
Processing Time ◽  
Mapping Method ◽  
Chinese Characters ◽  
New Approach ◽  
Relative Direction ◽  
The Stability ◽  
Merging Method

This paper describes a new approach to the recognition of multi-font printed Chinese characters. The basic idea is to encode a character in terms of two pre-defined stroke relations, namely, relative position relation and relative direction relation. The code-mapping method chosen in our system possesses two main advantages: the first is that the tree-like data base can be easily extended, and the second is that the processing time is independent of the amount of data base. Since the stability of the extracted strokes greatly affects the coding results, a new stroke merging method, which has been experimentally proven to extract strokes more steadily, is also proposed.

A New Approach to Determine Dynamic Strength Model Parameters under Taylor Impact Test

2012 ◽  
Vol 525-526 ◽  
pp. 377-380
Author(s):  
F. Xu ◽  
Wei Guo Guo ◽  
Q.J. Wang ◽  
Zhi Yin Zeng
Keyword(s):  
Impact Test ◽  
Dynamic Strength ◽  
Hopkinson Bar ◽  
Optimization Techniques ◽  
Model Parameters ◽  
Strength Model ◽  
New Approach ◽  
Taylor Impact ◽  
Bar Test ◽  
Taylor Impact Test

In this paper, to determine the dynamic strength model for steels, a new approach which does not rely on the Hopkinson bar test has been proposed. As the DH36 steel for example, using the results of Taylor impact test and the quasi-static compression test, the initial parameters of Johnson-Cook plastic strength model have been fitted out, then the initial strength parameters have been optimized using the optimization techniques of the sparse Taylor impact cylinder. It has been shown that the optimized results in numerical simulation are consistent with results of Taylor impact test, and the optimized Johnson-Cook model can also well describe flow stress curve fitted from the Hopkinson bar test.

Robust Centralized Fusion Steady-State Kalman Filter with Uncertain Parameters and Measurement Noise Variances

2014 ◽  
Vol 701-702 ◽  
pp. 532-537 ◽  
Author(s):  
Xue Mei Wang ◽  
Wen Qiang Liu ◽  
Zi Li Deng
Keyword(s):  
Kalman Filter ◽  
Steady State ◽  
Lyapunov Equation ◽  
Small Region ◽  
Measurement Noise ◽  
Model Parameters ◽  
Parameter Uncertainties ◽  
New Approach ◽  
Uncertain Model ◽  
Robust Kalman Filter

For the linear discrete time multisensor system with uncertain model parameters and measurement noise variances, the centralized fusion robust steady-state Kalman filter is presented by a new approach of compensating the parameter uncertainties by a fictitious noise. Based on the Lyapunov equation, it is proved that for given fictitious noise variance, the variances of the actual filtering errors have a less-conservative upper bound when the uncertainty of parameters is limited in a sufficiently small region which is called as robust region of the parameter uncertainties. Further, a simulation example demonstrates how to search the robust region. It is also proved that the robust accuracy of the centralized fusion robust steady-state Kalman filter is higher than that of each local robust Kalman filter. A simulation example shows its effectiveness.

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