scholarly journals Business management and methods of predictive financial analysis companies

2021 ◽  
Vol 5 (S4) ◽  
Author(s):  
Marián Smorada ◽  
Andrea Lukáčková ◽  
Zuzana Hajduová ◽  
Ľudovít Šrenkel ◽  
Ján Havier
Keyword(s):  
Discriminant Analysis ◽  
Financial Analysis ◽  
Original Research ◽  
One Dimensional ◽  
Analysis Methods ◽  
Economic Practice ◽  
Future Situation ◽  
Discriminant Analyses ◽  
Business Entities ◽  
Research Show

The focus of this presented work is the application of one-dimensional discriminant analysis in specific conditions of economic practice. The research sample of the enterprises has shown, that even these methods can better warn against nearing bankruptcy by predicting whether business will or will not be sustainable. Generally, these discriminant analyses use the financial ratios methods. The future situation of an enterprise can be predicted, among other things, by means of one-dimensional and multidimensional discriminant analysis methods, which are dealt with by several authors. Given the different approaches of authors, one-dimensional discriminant analysis methods that are "older" can be assumed to have a different reliability than multidimensional discriminant analysis methods. The assumptions of our research were verified in a group consisting of prosperous and non-prosperous business entities. The results of the original research show that one-dimensional discriminatory methods had a higher reliability than the multidimensional ones on the sample of enterprises surveyed. At the same time, it has not been established that a 100% reliable method will be found, but it is good to know the assumptions on which these existing methods work and use a combination of multiple methods.

scholarly journals Detecting Bacterial Biofilms Using Fluorescence Hyperspectral Imaging and Various Discriminant Analyses

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2213
Author(s):  
Ahyeong Lee ◽  
Saetbyeol Park ◽  
Jinyoung Yoo ◽  
Jungsook Kang ◽  
Jongguk Lim ◽  
...  
Keyword(s):  
Discriminant Analysis ◽  
Hyperspectral Imaging ◽  
Food Processing ◽  
Nearest Neighbor ◽  
Hyperspectral Image ◽  
Uv Light ◽  
Hyperspectral Images ◽  
K Nearest Neighbor ◽  
E Coli ◽  
Discriminant Analyses

Biofilms formed on the surface of agro-food processing facilities can cause food poisoning by providing an environment in which bacteria can be cultured. Therefore, hygiene management through initial detection is important. This study aimed to assess the feasibility of detecting Escherichia coli (E. coli) and Salmonella typhimurium (S. typhimurium) on the surface of food processing facilities by using fluorescence hyperspectral imaging. E. coli and S. typhimurium were cultured on high-density polyethylene and stainless steel coupons, which are the main materials used in food processing facilities. We obtained fluorescence hyperspectral images for the range of 420–730 nm by emitting UV light from a 365 nm UV light source. The images were used to perform discriminant analyses (linear discriminant analysis, k-nearest neighbor analysis, and partial-least squares discriminant analysis) to identify and classify coupons on which bacteria could be cultured. The discriminant performances of specificity and sensitivity for E. coli (1–4 log CFU·cm−2) and S. typhimurium (1–6 log CFU·cm−2) were over 90% for most machine learning models used, and the highest performances were generally obtained from the k-nearest neighbor (k-NN) model. The application of the learning model to the hyperspectral image confirmed that the biofilm detection was well performed. This result indicates the possibility of rapidly inspecting biofilms using fluorescence hyperspectral images.

scholarly journals Evaluation of crisphead lettuce cultivars in different cover types by manova and discriminant analysis

2013 ◽  
Vol 31 (3) ◽  
pp. 439-444
Author(s):  
Izabela Regina C de Oliveira ◽  
Marcelo T Rezende ◽  
Carlos Tadeu dos S Dias ◽  
Daniela de S Gomes ◽  
Élberis P Botrel ◽  
...  
Keyword(s):  
Discriminant Analysis ◽  
Cover Crops ◽  
Environmental Sustainability ◽  
Cover Crop ◽  
Univariate Analysis ◽  
Polyethylene Film ◽  
Standard Errors ◽  
Multivariate Techniques ◽  
Discriminant Analyses ◽  
Plot Design

In many agricultural experiments the variables are biologically correlated and it is inappropriate to study them only under univariate analysis. Therefore, we evaluated commercial characteristics of crisphead lettuce cultivars and covers under a multivariate approach, using canonical discriminant analysis. We used a split plot design and we tested the cover crop, cultivar and interaction effects by using MANOVA (α= 5%). Means and its standard errors were obtained for average total weight, weight of the head, volume and density of plants. Canonical discriminant analyses were performed using PROC CANDISC procedure in SAS (SAS Institute, 2008) system. Canonical plots were obtained using JMP 9.0 (SAS Institute, 2010) linked to SAS database. With these plots it was possible to note the differences among factors levels. When polyethylene film was used as cover the plants had inferior commercial characteristics than plants in which cover crops were used. Thus, the cover with polyethylene film can be discouraged in the cultivation of crisphead lettuce, promoting environmental sustainability. We suggest these multivariate techniques in horticulture studies.

scholarly journals Cultivar Classification of Single Sweet Corn Seed Using Fourier Transform Near-Infrared Spectroscopy Combined with Discriminant Analysis

2019 ◽  
Vol 9 (8) ◽  
pp. 1530 ◽  
Author(s):  
Guangjun Qiu ◽  
Enli Lü ◽  
Ning Wang ◽  
Huazhong Lu ◽  
Feiren Wang ◽  
...  
Keyword(s):  
Fourier Transform ◽  
Discriminant Analysis ◽  
Near Infrared ◽  
Seed Quality ◽  
Sweet Corn ◽  
Full Range ◽  
Classification Model ◽  
Support Vector ◽  
Corn Seed ◽  
Discriminant Analyses

Seed purity is a key indicator of crop seed quality. The conventional methods for cultivar identification are time-consuming, expensive, and destructive. Fourier transform near-infrared (FT-NIR) spectroscopy combined with discriminant analyses, was studied as a rapid and nondestructive technique to classify the cultivars of sweet corn seeds. Spectra with a range of 1000–2500 nm collected from 760 seeds of two cultivars were used for the discriminant analyses. Thereafter, 126 feature wavelengths were identified from 1557 wavelengths using a genetic algorithm (GA) to build simplified classification models. Four classification algorithms, namely K-nearest neighbor (KNN), soft independent method of class analogy (SIMCA), partial least-squares discriminant analysis (PLS-DA), and support vector machine discriminant analysis (SVM-DA) were tested on full-range wavelengths and feature wavelengths, respectively. With the full-range wavelengths, all four algorithms achieved a high classification accuracy range from 97.56% to 99.59%, and the SVM-DA worked better than other models. From the feature wavelengths, no significant decline in accuracies was observed in most of the models and a high accuracy of 99.19% was still obtained by the PLS-DA model. This study demonstrated that using the FT-NIR technique with discriminant analyses could be a feasible way to classify sweet corn seed cultivars and the proper classification model could be embedded in seed sorting machinery to select high-purity seeds.

Parameterized Discriminant Analysis Methods

2011 ◽  
pp. 78-105
Author(s):  
David Zhang ◽  
Fengxi Song ◽  
Yong Xu ◽  
Zhizhen Liang
Keyword(s):  
Discriminant Analysis ◽  
Linear Discriminant Analysis ◽  
Scatter Matrix ◽  
Linear Discriminant ◽  
Analysis Methods

In this chapter, we mainly present three kinds of weighted LDA methods. In Sections 5.1, 5.2 and 5.3, we respectively present parameterized direct linear discriminant analysis, weighted nullspace linear discriminant analysis and weighted LDA in the range of within-class scatter matrix. We offer a brief summery of the chapter in Section 5.4.

Evaluating PDA using financial analysis for streaming videos: a case study at a US academic library

2019 ◽  
Vol 39 (2) ◽  
pp. 47-52
Author(s):  
Kerry A. Falloon
Keyword(s):  
Financial Analysis ◽  
Academic Library ◽  
Streaming Video ◽  
Original Research ◽  
Content Type ◽  
Financial Valuation ◽  
Valuation Methodology ◽  
Streaming Videos ◽  
Practical Implications

Purpose The purpose of this study is to evaluate the pre and post success of patron-driven acquisition (PDA) streaming video projects using financial analysis, thus comparing PDA as a collection building tool against other legacy purchasing practices. Design/methodology/approach This is primarily a quantitative study based on deductive data derived; however, it does include qualitative findings. Hence, it is a mixed study. Findings The study approaches this topic from the viewpoint that ongoing evaluations of PDA projects, based on savings and benefits derived, can be practically conducted and are useful for CD decision-making by purchasing agents in academic libraries. Research limitations/implications Caution should be used when generalizing this study due to its specificity of its library’s collection development (CD) needs and methodology. The study is not intended to be original research, but it builds upon other case studies in this area. Practical implications In addition to improving CD strategies, libraries could use this study to develop a financial valuation methodology, which can help guide purchasing practices. Social implications This study has implications to all library stakeholders. Originality/value Few studies have compared and analyzed streaming video PDA programs using financial analysis in a practical manner to aid library acquisitions.

Assessing the Validity of the Semantic Differential Portion of the Apperceptive Personality Test

2001 ◽  
Vol 88 (3_suppl) ◽  
pp. 1235-1244 ◽  
Author(s):  
David J. Palmiter ◽  
David E. Silber
Keyword(s):  
Discriminant Analysis ◽  
Social Desirability ◽  
Semantic Differential ◽  
Personality Test ◽  
Ideal Self ◽  
Social Desirability Scale ◽  
Strong Negative Correlation ◽  
Discriminant Analyses ◽  
The Difference ◽  
The Ideal

This study investigated the validity of the semantic differential portion of the Apperceptive Personality Test with 225 undergraduates who completed the Marlowe-Crowne Social Desirability scale, actual-self and ideal-self semantic differential scales (e.g., Actual-self and Ideal-self), and either the Apperceptive Personality Test or a modified version. A projected-self score was calculated using the semantic differential ratings of the hero(ine) character on the test, e.g., Projected-self. A strong negative correlation indicated that, as the difference between the Ideal-self and Actual-self decreased, the difference between the Actual-self and Projected-self increased. Discriminant analyses indicated that highly guarded participants, e.g., high Social Desirability scores, showed more congruency between Ideal-self and Actual-self and less congruency between Actual-self ratings and Projected-self on the APT than did less guarded participants. When the difference scores incorporated only those semantic differential items that loaded on an Evaluative factor, the same result of discriminant analysis was found when participants who completed the modified version were included. These findings support the validity of the test's semantic differential items and suggest that guardedness tends to promote more similarity between Actual-self and Ideal-self and less similarity between Actual-self and Projected-self.

scholarly journals Classification: Astronomical and Mathematical Overview

1994 ◽  
Vol 161 ◽  
pp. 227-233
Author(s):  
F. Murtagh
Keyword(s):  
Feature Selection ◽  
Discriminant Analysis ◽  
Uncertainty Principle ◽  
User Choice ◽  
Short Overview ◽  
Analysis Methods ◽  
Guide Star

A short overview is presented of a number of different discriminant analysis methods. An ‘uncertainty principle’ is presented in regard to the issue of user choice of appropriate method. The discriminant analysis methods described are then used in the important problem of feature selection. A hand-classified set of HST Guide Star plate data is used, with star/galaxy/fault classes.

Sign in / Sign up

Export Citation Format

Share Document