scholarly journals Pitfalls in stock discrimination by shape analysis of otolith contours

2015 ◽  
Vol 72 (7) ◽  
pp. 2090-2097 ◽  
Author(s):  
Alf Harbitz ◽  
Ole Thomas Albert
Keyword(s):  
Shape Analysis ◽  
Fourier Transforms ◽  
Influential Factor ◽  
Correct Classification ◽  
Success Rates ◽  
Greenland Halibut ◽  
Classification Rate ◽  
Stock Discrimination ◽  
The Impact

Abstract This paper focuses on artefacts that may corrupt stock discrimination by shape analysis of otolith contours, how one can examine if such artefacts are important, and how they can be avoided. The scope focuses on Fourier transforms of contour points, the linear Fisher discrimination technique, and success rates based on cross validation by the “leave one out at a time” technique. The “zero-score” technique is introduced as a tool to examine the importance of a possible artefact, based on the theoretical result that the probability of correct classification of any otolith from either of two identical groups is zero. If one of the identical groups is exposed to a possible influential factor, e.g. a different smoothing, a high classification rate will reveal that this factor is an important artefact. The concept of a “lasso contour” is introduced that drastically reduces the impact of smoothing and provides a non-concave shape that enables a one-dimensional representation of the contour without ambiguities. Results are illustrated by comparison between Greenland halibut (Reinhardtius hippoglossoides) otolith contours from southern Greenland and Northeast Arctic waters. The conclusion is that the probability of correct classification of locality based on the original contours is too optimistic (77–79%), while the scores based on lasso contours are insensitive to smoothing and still optimistically high (68–70%).

Alzheimer's Disease Classification Based on Multi-feature Fusion

2019 ◽  
Vol 15 (2) ◽  
pp. 161-169 ◽  
Author(s):  
Nuwan Madusanka ◽  
Heung-Kook Choi ◽  
Jae-Hong So ◽  
Boo-Kyeong Choi
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Feature Fusion ◽  
Biological Data ◽  
Correct Classification ◽  
Mr Images ◽  
Correct Classification Rate ◽  
Classification Rate ◽  
Morphometric Features

Background: In this study, we investigated the fusion of texture and morphometric features as a possible diagnostic biomarker for Alzheimer’s Disease (AD). Methods: In particular, we classified subjects with Alzheimer’s disease, Mild Cognitive Impairment (MCI) and Normal Control (NC) based on texture and morphometric features. Currently, neuropsychiatric categorization provides the ground truth for AD and MCI diagnosis. This can then be supported by biological data such as the results of imaging studies. Cerebral atrophy has been shown to correlate strongly with cognitive symptoms. Hence, Magnetic Resonance (MR) images of the brain are important resources for AD diagnosis. In the proposed method, we used three different types of features identified from structural MR images: Gabor, hippocampus morphometric, and Two Dimensional (2D) and Three Dimensional (3D) Gray Level Co-occurrence Matrix (GLCM). The experimental results, obtained using a 5-fold cross-validated Support Vector Machine (SVM) with 2DGLCM and 3DGLCM multi-feature fusion approaches, indicate that we achieved 81.05% ±1.34, 86.61% ±1.25 correct classification rate with 95% Confidence Interval (CI) falls between (80.75-81.35) and (86.33-86.89) respectively, 83.33%±2.15, 84.21%±1.42 sensitivity and 80.95%±1.52, 85.00%±1.24 specificity in our classification of AD against NC subjects, thus outperforming recent works found in the literature. For the classification of MCI against AD, the SVM achieved a 76.31% ± 2.18, 78.95% ±2.26 correct classification rate, 75.00% ±1.34, 76.19%±1.84 sensitivity and 77.78% ±1.14, 82.35% ±1.34 specificity. Results and Conclusion: The results of the third experiment, with MCI against NC, also showed that the multiclass SVM provided highly accurate classification results. These findings suggest that this approach is efficient and may be a promising strategy for obtaining better AD, MCI and NC classification performance.

scholarly journals Impact of Feature Selection on Clustering Images ofVertebral Compression Fractures

2020 ◽  
Author(s):  
Raquel Candido ◽  
Rafael Lama ◽  
Natália Chiari ◽  
Marcello Nogueira-Barbosa ◽  
Paulo Azevedo Marques ◽  
...  
Keyword(s):  
Feature Selection ◽  
Metastatic Cancer ◽  
Vertebral Compression Fractures ◽  
Features Selection ◽  
Correct Classification ◽  
Compression Fractures ◽  
Vertebral Bodies ◽  
The Impact ◽  
Aided Diagnosis

Non-traumatic Vertebral Compression Fractures (VCFs) are generally caused by osteoporosis (benign VCFs) or metastatic cancer (malignant VCFs) and the success of the medical treatment strongly depends on a fast and correct classification of VCFs. Recently, methods for computer-aided diagnosis (CAD) based on machine learning have been proposed for classifying VCFs. In this work, we investigate the problem of clustering images of VCFs and the impact of feature selection by genetic algorithms, comparing the clustering i)with all features and ii)with feature selection through the purity results. The analysis of the clusters helps to understand the results of classifiers and difficulties of differentiating images of different classes by an expert. The results indicate that features selection improved the separability of clusters and purity. Feature selection also helps to understand which attributes are most important for analysing the images of vertebral bodies.

scholarly journals Bags-of-Features for fish school cluster characterization in pelagic ecosystems: application to the discrimination of juvenile and adult anchovy (Engraulis ringens) clusters off Peru

2012 ◽  
Vol 69 (8) ◽  
pp. 1329-1339 ◽  
Author(s):  
Ronan Fablet ◽  
Paul Gay ◽  
Salvador Peraltilla ◽  
Cecilia Peña ◽  
Ramiro Castillo ◽  
...  
Keyword(s):  
Data Sets ◽  
Correct Classification ◽  
Classification Rate ◽  
Fish Schools ◽  
Fish School ◽  
Acoustic Data ◽  
School Based ◽  
Engraulis Ringens ◽  
Fisheries Acoustics

Whereas fisheries acoustics data processing mainly focused on the detection, characterization, and recognition of individual fish schools, here we addressed the characterization and discrimination of fish school clusters. The proposed scheme relied on the application of the Bags-of-Features (BoF) approach to acoustic echograms. This approach is widely exploited for pattern recognition issues and naturally applies here, considering fish schools as the relevant elementary objects. It relies on the extraction and categorization of fish schools in fisheries acoustic data. Echogram descriptors were computed per unit echogram length as the numbers of schools in different school categories. We applied this approach to the discrimination of juvenile and adult anchovy ( Engraulis ringens ) off Peru. Whereas the discrimination of individual schools is low (below 70%), the proposed BoF scheme achieved between 89% and 92% of correct classification of juvenile and adult echograms for different survey data sets and significantly outperformed classical school-based echogram characteristics (about 10% of improvement of the correct classification rate). We further illustrate the potential of the proposed scheme for the estimation of the spatial distribution of juvenile and adult anchovy populations.

scholarly journals Application of a Novel S3 Nanowire Gas Sensor Device in Parallel with GC-MS for the Identification of Rind Percentage of Grated Parmigiano Reggiano

2018 ◽  
Author(s):  
Marco Abbatangelo ◽  
Estefanía Núñez-Carmona ◽  
Veronica Sberveglieri ◽  
Dario Zappa ◽  
Elisabetta Comini ◽  
...  
Keyword(s):  
Multivariate Analysis ◽  
Correct Classification ◽  
Working Process ◽  
Classification Rate ◽  
Sensor Device ◽  
Novel Method ◽  
Two Stages ◽  
Parmigiano Reggiano ◽  
Made In

Parmigiano Reggiano cheese is one of the most appreciated and consumed food worldwide, especially in Italy, for its high content of nutrients and for its taste. However, these characteristics make this product subject to counterfeiting in different forms. In this study, a novel method based on an electronic nose has been developed in order to investigate the potentiality of this tool to distinguish rind percentage in grated Parmigiano Reggiano packages that should be lower than 18%. Different samples in terms of percentage, seasoning and rind working process were considered to tackle the problem at 360°. In parallel, GC-MS technique was used to give a name to the compounds that characterize Parmigiano and to relate them with sensors responses. Data analysis consisted of two stages: multivariate analysis (PLS) and classification made in a hierarchical way with PLS-DA ad ANNs. Results are promising in terms of correct classification of the samples. The classification rate is higher for ANNs than PLS-DA, reaching also 100% values.

scholarly journals Ubicación de revistas científicas en cuartiles según SJR

2021 ◽  
Vol 24 (1) ◽  
Author(s):  
Tomás Marín Velásquez ◽  
Dany Day Josefina Arriojas Tocuyo
Keyword(s):  
Discriminant Analysis ◽  
Descriptive Statistics ◽  
Influential Factor ◽  
Scientific Journals ◽  
Multivariate Statistical ◽  
Impact Indicators ◽  
El Sistema ◽  
Using Data ◽  
The Impact

Se analiza el sistema de cuartiles para la clasificación de revistas científicas, mediante clasificación estadística multivariante, utilizando datos de la página oficial de Scopus en 2019. Se tomó una muestra de 5740 registros y se extrajeron cuatro indicadores (CiteScore, Porcentaje de citaciones, SJR y Percentil) además del cuartil de ubicación (Q). El comportamiento de los indicadores se analizó mediante estadística descriptiva por cuartil, además de la clasificación mediante Análisis Discriminante y Redes Neuronales Artificiales. El cuartil con mayor dispersión de indicadores fue Q1 y el cuartil con indicadores más homogéneos fue el Q4. El Análisis Discriminante arrojó 97,82% de cuartiles correctamente clasificados y 97,23% con RNA. Existen revistas que no se ajustan al cuartil donde se encuentra, de acuerdo a la estadística multivariante. Se observó que el factor más influyente en la clasificación es el Percentil y no los indicadores de impacto. The quartile system for the classification of scientific journals is analyzed, through multivariate statistical classification, using data from the official Scopus website in 2019. A sample of 5740 records was taken and four indicators were extracted (CiteScore, Citation Percentage, SJR and Percentile) in addition to the location quartile (Q). The behavior of the indicators was analyzed through descriptive statistics by quartile, in addition to classification through Discriminant Analysis and Artificial Neural Networks. The quartile with the highest indicator dispersion was Q1 and the quartile with the most homogeneous indicators was Q4. Discriminant Analysis showed 97.82% of correctly classified quartiles and 97.23% with RNA. There are magazines that do not adjust to the quartile where it is, according to multivariate statistics. It was observed that the most influential factor in the classification is the Percentile and not the impact indicators. O sistema quartil para a classificação de periódicos científicos é analisado, através da classificação estatística multivariada, usando dados do site oficial Scopus em 2019. Uma amostra de 5740 registros foi retirada e quatro indicadores foram extraídos (CiteScore, Citation Percentage, SJR e Percentile), além do quartil de localização (Q). O comportamento dos indicadores foi analisado utilizando estatísticas descritivas por quartil, além da classificação por Análise Discriminatória e Redes Neurais Artificiais. O quartil com maior dispersão de indicadores foi o Q1 e o quartil com os indicadores mais homogêneos foi o Q4. A Análise Discriminatória mostrou 97,82% dos quartis corretamente classificados e 97,23% com ANN. Há periódicos que não se ajustam ao quartil onde é encontrado, de acordo com as estatísticas multivariadas. Foi observado que o fator mais influente na classificação é o Percentil e não os indicadores de impacto.

scholarly journals Aspects of the Early History of Romani

1970 ◽  
Vol 71 ◽  
pp. 70
Author(s):  
Claus Peter Zoller
Keyword(s):  
South Asia ◽  
Present Article ◽  
Early History ◽  
Correct Classification ◽  
North West ◽  
The North ◽  
History Of ◽  
The Impact ◽  
North Western

We owe to Ralph Lilley Turner the correct classification of Romani as originating from a central or inner form of Indo-Aryan. Turner also clarified that the “Dardic” elements in Romani have been borrowed into early Romani after its speakers had left their original home and reached the north-west of South Asia where they stayed for several hundred years before finally leaving the subcontinent. Until now, the extent of the “Dardic” influence on early Romani was poorly understood. In the present article much data has been put together which shows that this impact indeed is considerable. But it is intelligible only if we accept Turner’s hypothesis of a long stopover in north-western South Asia. The data presented below will also show that the notion of “Dardic” is too narrow in this context: the impact on early Romani, in fact, comprises linguistic elements and features found in Nuristani, Dardic and West Pahāṛī.

ON THE CLASSIFICATION OF DIGITAL TECHNOLOGIES IN CIVIL PROCESS

2019 ◽  
pp. 27-35
Author(s):  
Alexandr Neznamov
Keyword(s):  
Information Processing ◽  
Scientific Community ◽  
Digital Technologies ◽  
Significant Feature ◽  
Legal Proceedings ◽  
Civil Process ◽  
Civil Proceedings ◽  
Processing Information ◽  
The Impact

Digital technologies are no longer the future but are the present of civil proceedings. That is why any research in this direction seems to be relevant. At the same time, some of the fundamental problems remain unattended by the scientific community. One of these problems is the problem of classification of digital technologies in civil proceedings. On the basis of instrumental and genetic approaches to the understanding of digital technologies, it is concluded that their most significant feature is the ability to mediate the interaction of participants in legal proceedings with information; their differentiating feature is the function performed by a particular technology in the interaction with information. On this basis, it is proposed to distinguish the following groups of digital technologies in civil proceedings: a) technologies of recording, storing and displaying (reproducing) information, b) technologies of transferring information, c) technologies of processing information. A brief description is given to each of the groups. Presented classification could serve as a basis for a more systematic discussion of the impact of digital technologies on the essence of civil proceedings. Particularly, it is pointed out that issues of recording, storing, reproducing and transferring information are traditionally more «technological» for civil process, while issues of information processing are more conceptual.

Influence of internal and external risks on sustainability of financial system of Аltai krai

2018 ◽  
Vol 35 (4) ◽  
pp. 133-136
Author(s):  
R. N. Ibragimov
Keyword(s):  
Sustainable Development ◽  
Financial Stability ◽  
Management Strategy ◽  
Financial System ◽  
Risk Management Strategy ◽  
The Sustainable Development ◽  
The Stability ◽  
The Impact

The article examines the impact of internal and external risks on the stability of the financial system of the Altai Territory. Classification of internal and external risks of decline, affecting the sustainable development of the financial system, is presented. A risk management strategy is proposed that will allow monitoring of risks, thereby these measures will help reduce the loss of financial stability and ensure the long-term development of the economy of the region.

Fish diversity

2017 ◽  
Author(s):  
Derek Burton ◽  
Margaret Burton
Keyword(s):  
Life Style ◽  
Fish Diversity ◽  
Additional Species ◽  
The Impact ◽  
Current Species

Fish diversity is considered in terms of variety of their morphological, taxonomic, habitat and population attributes. Fish, with over 30, 000 current species, represent the largest group of vertebrates. The complexity of classification of a group of this size and antiquity, together with recognition of additional species, demands continuous ongoing revision. The impact of the recent fundamental changes in fish classification in 2016 is discussed. Life in water involves adaptations to widely different habitats which can result in physiological morphological and life-style variations which are reviewed.

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