Evaluation of Short-term Yarn Unevenness by Distance-discriminant Analysis

1995 ◽  
Vol 86 (1) ◽  
pp. 176-180
Author(s):  
G. H. Rong ◽  
K. Slater ◽  
R. C. Fei
2021 ◽  
Author(s):  
Guowan Shao ◽  
Chunjiang Peng ◽  
Wenchu Ou ◽  
Kai Duan

Linear discriminant analysis (LDA) is sensitive to noise and its performance may decline greatly. Recursive discriminative subspace learning method with an L1-norm distance constraint (RDSL) formulates LDA with the maximum margin criterion and becomes robust to noise by applying L1-norm and slack variables. However, the method only considers inter-class separation and intra-class compactness and ignores the intra-class manifold structure and the global structure of data. In this paper, we present L1-norm distance discriminant analysis with multiple adaptive graphs and sample reconstruction (L1-DDA) to deal with the problem. We use multiple adaptive graphs to preserve intra-class manifold structure and simultaneously apply the sample reconstruction technique to preserve the global structure of data. Moreover, we use an alternating iterative technique to obtain projection vectors. Experimental results on three real databases demonstrate that our method obtains better classification performance than RDSL.


2008 ◽  
Vol 5 (1) ◽  
Author(s):  
Tri Ratnawati

Discriminant analysis use for evidence to difference Short Term, Medium Term, Long Term Financing Decision, before crisis and at that moment of the crisis. Amount of the sample is 424 analysis unit of each, this result cause someone to repant Net Working Capital (NWC) and Leverage Short Term (LST) domination for Short Term Financing Decision, Profitability Medium Term (PMT) and Leverage Medium Term (LMT) domination for Medium Term Financing Decision and Dividend Payout Ratio (DPR) domination for Long Term Financing decision before and ant that moment of the crisis. Key Word:    Financing Dicision, discriminant analysis, before crisis, at that moment of the crisis


2011 ◽  
Vol 55-57 ◽  
pp. 472-477 ◽  
Author(s):  
Tong Liang Fan ◽  
Min Jun Deng ◽  
Hong Cheng Huang

An enhanced discrete Fourier transform DFT-based channel estimation for OFDM systems is proposed. Conventional DFT-based channel estimations improve the performance by suppressing time domain noise. However, they potentially require information on channel impulse responses and may also result in mean-square error (MSE) floor due to incorrect channel information such as channel delay spread. In order to overcome the disadvantage, our proposed channel estimation can improve the performance by deciding significant channel taps adaptively. Significant channel taps are detected on the basis of Mahalanobis distance discriminant analysis. Simulation results demonstrate that the proposed algorithm outperforms the conventional DFT-based estimation in terms of BER and MSE performance.


2011 ◽  
Vol 2256 (1) ◽  
pp. 112-119 ◽  
Author(s):  
Ioannis Tsapakis ◽  
William H. Schneider ◽  
Adel Bolbol ◽  
Artemis Skarlatidou

2011 ◽  
Vol 255-260 ◽  
pp. 3740-3743
Author(s):  
Xiao Ming Yan ◽  
Xiang Yun Chen ◽  
Feng Qiang Gong

The instability identification of goaf risky is an important work in the mine engineering. Based on distance discriminant analysis, a method to identify the instability of goaf risky in mines was presented in this paper. Nine factors influencing the stability of goaf risky, including uniaxial compressive strength of rock, elastic modulus of rock, rock quality designation (RQD), area ration of pillar, ratio of width to height of pillar, depth of ore body, volume of goaf, dip of ore body and area of goaf, were selected as discriminant indexes in the stability analysis of goaf. The actual data of 40 goafs were used as training samples to establish a discriminant analysis model to identify the stability of goaf. The results show that this discriminant analysis model has high precision and misdiscriminant ratio is 0.025 in re-substitution process. The instability identification of a metal mine was discriminanted by using this model and the identification result is identical with that of practical situation.


2021 ◽  
Author(s):  
Guowan Shao ◽  
Chunjiang Peng ◽  
Wenchu Ou ◽  
Kai Duan

Dimensionality reduction plays an important role in the fields of pattern recognition and computer vision. Recursive discriminative subspace learning with an L1-norm distance constraint (RDSL) is proposed to robustly extract features from contaminated data and L1-norm and slack variables are utilized for accomplishing the goal. However, its performance may decline when too many outliers are available. Moreover, the method ignores the global structure of the data. In this paper, we propose cutting L1-norm distance discriminant analysis with sample reconstruction (C-L1-DDA) to solve the two problems. We apply cutting L1-norm to measure within-class and between-class distances and thus outliers may be strongly suppressed. Moreover, we use cutting squared L2-norm to measure reconstruction errors. In this way, outliers may be constrained and the global structure of data may be approximately preserved. Finally, we give an alternating iterative algorithm to extract feature vectors. Experimental results on two publicly available real databases verify the feasibility and effectiveness of the proposed method.


2020 ◽  
pp. 37-42
Author(s):  
V. V. Koss ◽  
◽  
M. V. Elizarov ◽  
D.Yu. Leonov ◽  
◽  
...  

Integrating neurological services into primary health care should be an important policy goal in both developing and developed countries. Providing neurological care through primary health care requires significant investment in training primary health care professionals to identify and treat neurological disorders. Such training should meet the specific practical needs of different groups of primary health care professionals, such as doctors, nurses, and community health workers. Preferably, continuous training is necessary to provide follow-up support to strengthen new skills. In many countries, this is not possible, and therefore suboptimal assistance is provided. Purpose: to analyze the organization of orthopedic and neurological services in the practice of a gerontologist. Methods: General clinical, neurological examination using diagnostic criteria of the DISEASE, PKP syndrome, 3-stage scale of global Deterioration (Global Determination Scale – GDS) and Clinical Dementia Rating scale (clinical Dementia Rating – CDR); neuroimaging methods – MRI/CT of the brain; quantitative EEG; experimental psychological examination: MMSE test, coding subtest, special experimental psychological study using Schulte tables, tests for memorizing 10 words and 8 numbers, Wechsler Memory Scale – Revised – WMS-R, spielberger-Hanin anxiety scale, geriatric Depression Scale; discriminant analysis was used to predict the development of dementia. Results: As a result of repeated studies, it was found that after three years in the group of patients with ART. II with PKP syndrome in 35.3%, dementia syndrome was diagnosed. Depending on the subtype of the PKP syndrome, dementia syndrome was detected in 55% of patients with the amnesic subtype, in 34.8% – with multi – domain, in 15.8% – with non-amnesic. The most vulnerable to the development of dementia were patients with the amnesic subtype of PKP syndrome. Conclusion: Using discriminant analysis of testing data of patients WITH stage II diabetes with advanced age PKP syndrome, informative and independent predictors of dementia development were established, which were included in the prognostic formula, namely, indicators of maximum reproduction of 10 words, coding subtest, complex verbal paired associations (short-term memory), visual reproduction (short-term memory), light verbal paired associations (long-term memory). There was a significant increase in pronounced correlations between various cognitive indicators in the group of patients with art. II WITH PKP syndrome in comparison with the groups of patients with ART. II without PKP syndrome, practically healthy elderly and young people, which indicates the formation of a stable pathological state in the cognitive sphere in patients with PKP syndrome. As we can see, the activity of a gerontologist is often closely related to neurology, so we consider it necessary to point out in conclusion the high efficiency of the neurology service based on a gerontologist


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