scholarly journals Naive Principal Component Analysis in Software Reliability Studies

2019 ◽  
Vol 06 (01) ◽  
pp. 28-32
Author(s):  
A Loganathan ◽  
Muthuraj R Jeromia
Keyword(s):  
Principal Component Analysis ◽  
Software Reliability ◽  
Principal Component ◽  
Component Analysis

scholarly journals Towards a software defect proneness model: feature selection

2021 ◽  
Vol 4 (4) ◽  
pp. 354-365
Author(s):  
Vitaliy S. Yakovyna ◽  
◽  
Ivan I. Symets
Keyword(s):  
Principal Component Analysis ◽  
Feature Selection ◽  
Random Forest ◽  
Software Reliability ◽  
Principal Component ◽  
Component Analysis ◽  
Support Vector ◽  
Tree Classifier ◽  
Code Metrics ◽  
Software Code

This article is focused on improving static models of software reliability based on using machine learning methods to select the software code metrics that most strongly affect its reliability. The study used a merged dataset from the PROMISE Software Engineering repository, which contained data on testing software modules of five programs and twenty-one code metrics. For the prepared sampling, the most important features that affect the quality of software code have been selected using the following methods of feature selection: Boruta, Stepwise selection, Exhaustive Feature Selection, Random Forest Importance, LightGBM Importance, Genetic Algorithms, Principal Component Analysis, Xverse python. Basing on the voting on the results of the work of the methods of feature selection, a static (deterministic) model of software reliability has been built, which establishes the relationship between the probability of a defect in the software module and the metrics of its code. It has been shown that this model includes such code metrics as branch count of a program, McCabe’s lines of code and cyclomatic complexity, Halstead’s total number of operators and operands, intelligence, volume, and effort value. A comparison of the effectiveness of different methods of feature selection has been put into practice, in particular, a study of the effect of the method of feature selection on the accuracy of classification using the following classifiers: Random Forest, Support Vector Machine, k-Nearest Neighbors, Decision Tree classifier, AdaBoost classifier, Gradient Boosting for classification. It has been shown that the use of any method of feature selection increases the accuracy of classification by at least ten percent compared to the original dataset, which confirms the importance of this procedure for predicting software defects based on metric datasets that contain a significant number of highly correlated software code metrics. It has been found that the best accuracy of the forecast for most classifiers was reached using a set of features obtained from the proposed static model of software reliability. In addition, it has been shown that it is also possible to use separate methods, such as Autoencoder, Exhaustive Feature Selection and Principal Component Analysis with an insignificant loss of classification and prediction accuracy

A German version of the Intermittent Claudication Questionnaire (ICQ): cultural adaptation and validation

VASA ◽  
2012 ◽  
Vol 41 (5) ◽  
pp. 333-342 ◽  
Author(s):  
Kirchberger ◽  
Finger ◽  
Müller-Bühl
Keyword(s):  
Principal Component Analysis ◽  
Intermittent Claudication ◽  
Completion Time ◽  
Short Form ◽  
Principal Component ◽  
Component Analysis ◽  
German Version ◽  
Average Completion Time ◽  
Sf 36 ◽  
Related Quality

Background: The Intermittent Claudication Questionnaire (ICQ) is a short questionnaire for the assessment of health-related quality of life (HRQOL) in patients with intermittent claudication (IC). The objective of this study was to translate the ICQ into German and to investigate the psychometric properties of the German ICQ version in patients with IC. Patients and methods: The original English version was translated using a forward-backward method. The resulting German version was reviewed by the author of the original version and an experienced clinician. Finally, it was tested for clarity with 5 German patients with IC. A sample of 81 patients were administered the German ICQ. The sample consisted of 58.0 % male patients with a median age of 71 years and a median IC duration of 36 months. Test of feasibility included completeness of questionnaires, completion time, and ratings of clarity, length and relevance. Reliability was assessed through a retest in 13 patients at 14 days, and analysis of Cronbach’s alpha for internal consistency. Construct validity was investigated using principal component analysis. Concurrent validity was assessed by correlating the ICQ scores with the Short Form 36 Health Survey (SF-36) as well as clinical measures. Results: The ICQ was completely filled in by 73 subjects (90.1 %) with an average completion time of 6.3 minutes. Cronbach’s alpha coefficient reached 0.75. Intra-class correlation for test-retest reliability was r = 0.88. Principal component analysis resulted in a 3 factor solution. The first factor explained 51.5 of the total variation and all items had loadings of at least 0.65 on it. The ICQ was significantly associated with the SF-36 and treadmill-walking distances whereas no association was found for resting ABPI. Conclusions: The German version of the ICQ demonstrated good feasibility, satisfactory reliability and good validity. Responsiveness should be investigated in further validation studies.

Multifactorial analysis of clinical laboratory signs, the levels of IL-17A, IL-23, IL-33, IL-35, and specific antibodies in the serum of patients with Lyme borreliosis without erythema migrans

2020 ◽  
Vol 4 (11) ◽  
pp. 676-681
Author(s):  
V.V. Sapozhnikova ◽  
◽  
A.L. Bondarenko ◽  
Keyword(s):  
Principal Component Analysis ◽  
Lyme Borreliosis ◽  
Clinical Laboratory ◽  
Acute Infection ◽  
Erythema Migrans ◽  
Principal Component ◽  
Component Analysis ◽  
Control Group ◽  
Multifactorial Analysis ◽  
Specific Antibodies

Aim: to determine the association between clinical laboratory parameters, the production of cytokines (IL-17A, -23, -33, -35), and specific IgM and IgG in the serum of patients with Lyme borreliosis without erythema migrans. Patients and Methods: complete blood count, the concentrations of IL-17A, -23, -33, -35, and the levels of specific IgM and IgG were measured during acute infection and convalescence (n=30). The control group included age- and sex-matched healthy individuals (n=30). Statistical analysis was performed using the StatSoft Statistica v 10.0 software (parametric and non-parametric methods and multifactorial analysis, i.e., principal component analysis). Results: most (80%) patients with Lyme borreliosis without erythema migrans are the people of working age. In most patients, the combination of the specific antibodies against Borrelia afzelii and Borrelia garinii (76.7%) and severe intoxication and inflammatory process (100%) were detected. Moderate and severe disease associated with meningism was diagnosed in 90% and 10%, respectively. The mean duration of hectic period was 8.3±1.27 days. Abnormal ECG was reported in 40% of patients, i.e., conduction abnormalities in 20%, sinus bradycardia in 16.7%,and sinus tachycardia in 3.3%. The clinical laboratory signs of hepatitis without jaundice were identified in 26.7%. During treatment, the significant reduction in band and segmented neutrophil counts as well as the significant increase in platelet count were revealed compared to these parameters at admission. Abnormal cytokine levels (i.e., the increase in IL-17A, -23, -33 and the deficiency of IL-35) were detected. Conclusions: multifactorial analysis has demonstrated that the severity of immunological abnormalities in patients with Lyme borreliosis without erythema migrans is associated with fever, cardiac and liver disorders, the high levels of IL-23 and IL-33, and the lack of IL-35 and specific IgM and IgG. KEYWORDS: tick-borne borreliosis, Lyme disease without erythema migrans, clinical laboratory signs, cytokines, specific antibodies, multifactorial analysis, principal component analysis. FOR CITATION: Sapozhnikova V.V., Bondarenko A.L. Multifactorial analysis of clinical laboratory signs, the levels of IL-17A, IL-23, IL-33, IL-35, and specific antibodies in the serum of patients with Lyme borreliosis without erythema migrans. Russian Medical Inquiry. 2020;4(11):676–681. DOI: 10.32364/2587-6821-2020-4-11-676-681.

Oxypropylation of Brazilian Pine-Fruit Shell Evaluated by Principal Component Analysis

2018 ◽  
Vol 6 (7) ◽  
pp. 715-723 ◽  
Author(s):  
Stephany C. de Rezende ◽  
Jo鉶 A. Pinto ◽  
Isabel P. Fernandes ◽  
Fernanda V. Leimann and Maria-Filomena Barreiro
Keyword(s):  
Principal Component Analysis ◽  
Principal Component ◽  
Component Analysis
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