scholarly journals Quadratic Programming Data Descriptors for Abnormal Beat Detection in ECG Recordings

2017 ◽  
Author(s):  
Fayyaz ul Amir Afsar Minhas
Keyword(s):  
Individual Differences ◽  
Quadratic Programming ◽  
Individual Variability ◽  
Training Data ◽  
Wavelet Domain ◽  
Equal Error Rate ◽  
Dissimilarity Representation ◽  
Classification Technique ◽  
Different Types ◽  
Beat Detection

AbstractThis paper analyzes the efficacy of applying one class classifiers (OCCs) to the problem of abnormal beat detection in ECG. It also proposes a novel OCC called Quadratic Programming Dissimilarity representation based Data Descriptor (QPDDD). A comparison of the proposed classification technique with existing classifiers over the MIT-BIH arrhythmia database is presented. Results show that OCCs coupled with wavelet domain features present a practical, robust and scalable solution for handling inter-individual variability in ECG patterns of different types of cardiac beats. An equal error rate of 90-95% was obtained for the MIT-BIH arrhythmia database depending upon the amount of training data used. A major advantage of the proposed scheme is that it requires only normal beats during its training. Another advantage is that it is able to handle inter-individual differences in ECG morphologies as the training takes place separately for each individual.

Inter-individual variation shapes the human microbiome

2019 ◽  
Vol 42 ◽  
Author(s):  
Emily F. Wissel ◽  
Leigh K. Smith
Keyword(s):  
Individual Differences ◽  
Individual Variation ◽  
Human Microbiome ◽  
Individual Variability ◽  
Microbiota Composition ◽  
Target Article ◽  
Microbiome Research

Abstract The target article suggests inter-individual variability is a weakness of microbiota-gut-brain (MGB) research, but we discuss why it is actually a strength. We comment on how accounting for individual differences can help researchers systematically understand the observed variance in microbiota composition, interpret null findings, and potentially improve the efficacy of therapeutic treatments in future clinical microbiome research.

Comparative Analysis of Machine Learning Techniques Using Predictive Modeling

2020 ◽  
Vol 13 ◽  
Author(s):  
Ritu Khandelwal ◽  
Hemlata Goyal ◽  
Rajveer Singh Shekhawat
Keyword(s):  
Machine Learning ◽  
Comparative Analysis ◽  
Data Science ◽  
Training Data ◽  
Machine Learning Techniques ◽  
Future Trends ◽  
Data Set ◽  
Learning Stage ◽  
Learning Techniques ◽  
Different Types

Introduction: Machine learning is an intelligent technology that works as a bridge between businesses and data science. With the involvement of data science, the business goal focuses on findings to get valuable insights on available data. The large part of Indian Cinema is Bollywood which is a multi-million dollar industry. This paper attempts to predict whether the upcoming Bollywood Movie would be Blockbuster, Superhit, Hit, Average or Flop. For this Machine Learning techniques (classification and prediction) will be applied. To make classifier or prediction model first step is the learning stage in which we need to give the training data set to train the model by applying some technique or algorithm and after that different rules are generated which helps to make a model and predict future trends in different types of organizations. Methods: All the techniques related to classification and Prediction such as Support Vector Machine(SVM), Random Forest, Decision Tree, Naïve Bayes, Logistic Regression, Adaboost, and KNN will be applied and try to find out efficient and effective results. All these functionalities can be applied with GUI Based workflows available with various categories such as data, Visualize, Model, and Evaluate. Result: To make classifier or prediction model first step is learning stage in which we need to give the training data set to train the model by applying some technique or algorithm and after that different rules are generated which helps to make a model and predict future trends in different types of organizations Conclusion: This paper focuses on Comparative Analysis that would be performed based on different parameters such as Accuracy, Confusion Matrix to identify the best possible model for predicting the movie Success. By using Advertisement Propaganda, they can plan for the best time to release the movie according to the predicted success rate to gain higher benefits. Discussion: Data Mining is the process of discovering different patterns from large data sets and from that various relationships are also discovered to solve various problems that come in business and helps to predict the forthcoming trends. This Prediction can help Production Houses for Advertisement Propaganda and also they can plan their costs and by assuring these factors they can make the movie more profitable.

scholarly journals Letter transpositions and morphemic boundaries in the second language processing of derived words: An exploratory study of individual differences

2021 ◽  
Vol 42 (2) ◽  
pp. 417-446
Author(s):  
Hasibe Kahraman ◽  
Bilal Kırkıcı
Keyword(s):  
Individual Differences ◽  
Language Processing ◽  
Exploratory Study ◽  
Reading Proficiency ◽  
Individual Variability ◽  
Morphological Processing ◽  
Group Level ◽  
Priming Effects ◽  
Second Language Processing ◽  
Morphological Priming

AbstractResearch into nonnative (L2) morphological processing has produced largely conflicting findings. To contribute to the discussions surrounding the contradictory findings in the literature, we examined L2 morphological priming effects along with a transposed-letter (TL) methodology. Critically, we also explored the potential effects of individual differences in the reading networks of L2 speakers using a test battery of reading proficiency. A masked primed lexical decision experiment was carried out in which the same target (e.g., ALLOW) was preceded by a morphological prime (allowable), a TL-within prime (allwoable), an substituted letter (SL)-within prime (allveable), a TL-across prime (alloawble), an SL-across prime (alloimble), or an unrelated prime (believable). The average data yielded morphological priming but no significant TL priming. However, the results of an exploratory analysis of the potential effects of individual differences suggested that individual variability mediated the group-level priming patterns in L2 speakers. TL-within and TL-across priming effects were obtained only when the performance of participants on nonword reading was considered, while the magnitude of the morphological priming effects diminished as the knowledge of vocabulary expanded. The results highlight the importance of considering individual differences while testing L2 populations.

Semi-Supervised Classification and its Application to Filtering IDS False Positives

2013 ◽  
Vol 427-429 ◽  
pp. 2309-2312
Author(s):  
Hai Bin Mei ◽  
Ming Hua Zhang
Keyword(s):  
Supervised Learning ◽  
Supervised Classification ◽  
Classification Performance ◽  
False Positives ◽  
Training Data ◽  
Classification Model ◽  
Classification Technique

Alert classifiers built with the supervised classification technique require large amounts of labeled training alerts. Preparing for such training data is very difficult and expensive. Thus accuracy and feasibility of current classifiers are greatly restricted. This paper employs semi-supervised learning to build alert classification model to reduce the number of needed labeled training alerts. Alert context properties are also introduced to improve the classification performance. Experiments have demonstrated the accuracy and feasibility of our approach.

scholarly journals Right Ventrolateral Prefrontal Cortex Mediates Individual Differences in Conflict-driven Cognitive Control

2011 ◽  
Vol 23 (12) ◽  
pp. 3903-3913 ◽  
Author(s):  
Tobias Egner
Keyword(s):  
Conflict Resolution ◽  
Individual Differences ◽  
Cognitive Control ◽  
Inferior Frontal Gyrus ◽  
Group Analysis ◽  
Individual Variability ◽  
Primary Role ◽  
Conflict Adaptation ◽  
Traditional Group ◽  
Behavioral Expression

Conflict adaptation—a conflict-triggered improvement in the resolution of conflicting stimulus or response representations—has become a widely used probe of cognitive control processes in both healthy and clinical populations. Previous fMRI studies have localized activation foci associated with conflict resolution to dorsolateral PFC (dlPFC). The traditional group analysis approach employed in these studies highlights regions that are, on average, activated during conflict resolution, but does not necessarily reveal areas mediating individual differences in conflict resolution, because between-subject variance is treated as noise. Here, we employed a complementary approach to elucidate the neural bases of variability in the proficiency of conflict-driven cognitive control. We analyzed two independent fMRI data sets of face–word Stroop tasks by using individual variability in the behavioral expression of conflict adaptation as the metric against which brain activation was regressed while controlling for individual differences in mean RT and Stroop interference. Across the two experiments, a replicable neural substrate of individual variation in conflict adaptation was found in ventrolateral PFC (vlPFC), specifically, in the right inferior frontal gyrus, pars orbitalis (BA 47). Unbiased regression estimates showed that variability in activity in this region accounted for ∼40% of the variance in behavioral expression of conflict adaptation across subjects, thus documenting a heretofore unsuspected key role for vlPFC in mediating conflict-driven adjustments in cognitive control. We speculate that vlPFC plays a primary role in conflict control that is supplemented by dlPFC recruitment under conditions of suboptimal performance.

Rhythmic Activity and Individual Variability in Recognition Memory: Theta Oscillations Correlate with Performance whereas Alpha Oscillations Correlate with ERPs

2017 ◽  
Vol 29 (1) ◽  
pp. 183-202 ◽  
Author(s):  
Yvonne Y. Chen ◽  
Jeremy B. Caplan
Keyword(s):  
Individual Differences ◽  
Recognition Memory ◽  
Memory Task ◽  
Rhythmic Activity ◽  
Individual Variability ◽  
Theta Oscillations ◽  
Alpha Oscillations ◽  
Alpha Oscillation ◽  
Familiarity And Recollection ◽  
Visual Inattention

During study trials of a recognition memory task, alpha (∼10 Hz) oscillations decrease, and concurrently, theta (4–8 Hz) oscillations increase when later memory is successful versus unsuccessful (subsequent memory effect). Likewise, at test, reduced alpha and increased theta activity are associated with successful memory (retrieval success effect). Here we take an individual-differences approach to test three hypotheses about theta and alpha oscillations in verbal, old/new recognition, measuring the difference in oscillations between hit trials and miss trials. First, we test the hypothesis that theta and alpha oscillations have a moderately mutually exclusive relationship; but no support for this hypothesis was found. Second, we test the hypothesis that theta oscillations explain not only memory effects within participants, but also individual differences. Supporting this prediction, durations of theta (but not alpha) oscillations at study and at test correlated significantly with d′ across participants. Third, we test the hypothesis that theta and alpha oscillations reflect familiarity and recollection processes by comparing oscillation measures to ERPs that are implicated in familiarity and recollection. The alpha-oscillation effects correlated with some ERP measures, but inversely, suggesting that the actions of alpha oscillations on memory processes are distinct from the roles of familiarity- and recollection-linked ERP signals. The theta-oscillation measures, despite differentiating hits from misses, did not correlate with any ERP measure; thus, theta oscillations may reflect elaborative processes not tapped by recollection-related ERPs. Our findings are consistent with alpha oscillations reflecting visual inattention, which can modulate memory, and with theta oscillations supporting recognition memory in ways that complement the most commonly studied ERPs.

Depression as a Consequence of Inadequate Neurochemical Adaptation in Response to Stressors

1992 ◽  
Vol 160 (S15) ◽  
pp. 36-43 ◽  
Author(s):  
Hymie Anisman ◽  
Robert M. Zacharko
Keyword(s):  
Individual Differences ◽  
Pharmacological Treatment ◽  
Individual Variability ◽  
Symptoms Of Depression ◽  
Symptom Profile ◽  
Behavioural Effects ◽  
Neurochemical Changes ◽  
Strain Variability

Stressors induce behavioural disturbances and neurochemical changes in animals, some of which are reminiscent of the symptoms and presumed neurochemical concomitants of depression in humans. Just as in humans, where considerable inter-individual variability is evident in the symptom profile of depression, there is marked inter-individual and inter-strain variability in the behavioural effects of stressors in animals. It is proposed that stressors induce adaptive neurochemical changes, failure of which may engender behavioural disturbances. Variability in the symptoms of depression and in the efficacy of its pharmacological treatment may reflect the biochemical heterogeneity of the illness. Inter-individual differences in vulnerability to stressor-provoked neurochemical changes may contribute to the behavioural profiles observed.

Distinct profiles of stimulus specific cortical activity for ignoring distraction during working memory encoding and maintenance, and associations with performance

2020 ◽  
Author(s):  
Charlotte Ashton ◽  
André Gouws ◽  
Marcus Glennon ◽  
THEODORE ZANTO ◽  
Steve Tipper ◽  
...  
Keyword(s):  
Working Memory ◽  
Individual Differences ◽  
Relevant Information ◽  
Cortical Activity ◽  
Irrelevant Information ◽  
Neural Mechanisms ◽  
Memory Encoding ◽  
Different Types ◽  
Short Time

Abstract Our ability to hold information in mind for a short time (working memory) is separately predicted by our ability to ignore two types of distraction: distraction that occurs while we put information into working memory (encoding) and distraction that occurs while we maintain already encoded information within working memory. This suggests that ignoring these different types of distraction involves distinct mechanisms which separately limit performance. Here we used fMRI to measure category-sensitive cortical activity and probe these mechanisms. The results reveal specific neural mechanisms by which relevant information is remembered and irrelevant information is ignored, which contribute to intra-individual differences in WM performance.

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