Fatty Acids Evaluation by Principal Component Analysis for the Traceability of Sicilian and Calabrian Olive Oils

Caridi, F.; Mottese, Antonio Francesco; Messina, Maurizio; D’Agostino, Maurizio

doi:10.2174/1573401317666210127105215

Cited by 4 publications

(2 citation statements)

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“…At present, principal component analysis (PCA), as a multivariable analysis method, has been widely applied in practice. This method can transform correlated highdimensional index variables into low-dimensional unrelated index variables, and the transformed index variables are called principal components [32,33]. When there are multiple variables that are connected with one another, principal component analysis (PCA) is used to both identify the most relevant characteristics or components from a dataset and to represent the data in a lower-dimensional space.…”

Section: Matrix Size Adjustmentmentioning

confidence: 99%

RETRACTED ARTICLE: Support attack detection algorithm for recommendation system based on deep learning

Wang

2023

J Wireless Com Network

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In order to enhance the performance of recommendation systems that support attack detection algorithms, we have designed a novel approach based on deep learning. Specifically, our algorithm focuses on improving convergence, user scoring accuracy, algorithm efficiency, and detection accuracy. To achieve this, we first construct a preliminary user rating matrix, which is optimised by incorporating the user preference word matrix and the weight of the preference word. Additionally, we adjust the size of the matrix using principal component analysis. Next, we construct a deep, bidirectional RNN model based on the deep learning network. This model is then combined with the user scoring matrix to identify the type of user. In the case of abnormal or false users, our algorithm is able to identify the recommendation system’s support attack through the detection results. The experimental results demonstrate the effectiveness of our algorithm. Specifically, our approach achieves fast convergence speeds, with the loss value remaining low throughout the process. Moreover, we achieve high average accuracy in user scoring, with a score of 97.14%. The detection time of the recommendation system support attack is also consistently lower than 0.7 s. Furthermore, our approach achieves an average accuracy of 98.09% in the detection of recommendation system support attacks. Overall, our algorithm shows promising results for practical applications in the field of recommendation systems.

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Section: Matrix Size Adjustmentmentioning

confidence: 99%

RETRACTED ARTICLE: Support attack detection algorithm for recommendation system based on deep learning

Wang

2023

J Wireless Com Network

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“…Unsupervised PCA is a powerful technique to describe significant trends in data. The principal components are created from a data matrix of samples and variables, representing the majority of the original variables' information [22]. Therefore, only a few principal components could effectively describe a significant variability percentage.…”

Section: Statistical Analysis 241 Principal Component Analysis (Pca)mentioning

confidence: 99%

Geographical Indication Characteristics of Aroma and Phenolic Acids of the Changping Strawberry

Wu,

Wang,

Hao

et al. 2023

Foods

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Strawberry is the most consumed berry fruit worldwide due to its unique aroma and high nutritive value. This fruit is also an important source of phenolic compounds. Changping strawberries are recognized as a national agricultural product of geographical indication (GI) due to their unique flavor. Widely accepted standards for identifying GI strawberries from non-GI strawberries are currently unavailable. This study compared the aroma and phenolic acid composition of GI and non-GI strawberries. Furthermore, the characteristic aroma and phenolic acid markers of GI strawberries were determined. A classification model based on the markers was established using Fisher discriminant analysis (FDA). In this study, six groups of strawberries with variety name of “Hongyan”, including GI strawberries from Changping and non-GI strawberries from Changping, Miyun, Pinggu, Shunyi, and Tongzhou, were collected. A total of 147 volatile substances were discovered using gas chromatography–tandem mass spectrometry. The contents of a few compounds principally responsible for the distinctive aroma in GI strawberries were in the top three of the six groups, providing GI strawberries with a generally pleasant fragrance. OPLS–DA identified isoamyl butyrate and trans-2-octen-1-ol as characteristic markers. Enrichment analysis indicated that beta-oxidation of very long-chain fatty acids, mitochondrial beta-oxidation of very long-chain fatty acids, fatty acid biosynthesis, and butyrate metabolism played critical roles in volatile compound biosynthesis. The total phenolic content was 24.41–36.46 mg/kg of fresh weight. OPLS–DA results revealed that cinnamic acid could be used as a characteristic phenolic acid marker of GI strawberries. Based on the three characteristic markers, FDA was performed on the different groups, which were then divided. The separation of strawberry samples from different origins using the three characteristic markers was found to be feasible. These findings help effectively understand the aroma and phenolic acid composition of strawberries and contribute to the development of strawberries with a pleasant fragrance and health benefits.

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An introductory review on the application of principal component analysis in the data exploration of the chemical analysis of food samples

Souza,

Bezerra,

Cerqueira

et al. 2024

Food Sci Biotechnol

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Fatty Acids Evaluation by Principal Component Analysis for the Traceability of Sicilian and Calabrian Olive Oils

Cited by 4 publications

References 0 publications

RETRACTED ARTICLE: Support attack detection algorithm for recommendation system based on deep learning

RETRACTED ARTICLE: Support attack detection algorithm for recommendation system based on deep learning

Geographical Indication Characteristics of Aroma and Phenolic Acids of the Changping Strawberry

An introductory review on the application of principal component analysis in the data exploration of the chemical analysis of food samples

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