Evaluation of physiologic complexity in time series using generalized sample entropy and surrogate data analysis

Complexity in time series is an intriguing feature of living dynamical systems, with potential use for identification of system state. Although various methods have been proposed for measuring physiologic complexity, uncorrelated time series are often assigned high values of complexity, errouneously classifying them as a complex physiological signals. Here, we propose and discuss a method for complex system analysis based on generalized statistical formalism and surrogate time series. Sample entropy (SampEn) was rewritten inspired in Tsallis generalized entropy, as function of q parameter (qSampEn). qSDiff curves were calculated, which consist of differences between original and surrogate series qSampEn. We evaluated qSDiff for 125 real heart rate variability (HRV) dynamics, divided into groups of 70 healthy, 44 congestive heart failure (CHF), and 11 atrial fibrillation (AF) subjects, and for simulated series of stochastic and chaotic process. The evaluations showed that, for nonperiodic signals, qSDiff curves have a maximum point (qSDiff(max)) for q not equal 1. Values of q where the maximum point occurs and where qSDiff is zero were also evaluated. Only qSDiff(max) values were capable of distinguish HRV groups (p-values 5.10 x 10(-3); 1.11 x 10(-7), and 5.50 x 10(-7) for healthy vs. CHF, healthy vs. AF, and CHF vs. AF, respectively), consistently with the concept of physiologic complexity, and suggests a potential use for chaotic system analysis. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.4758815]

CID: an efficient complexity-invariant distance for time series

The ubiquity of time series data across almost all human endeavors has produced a great interest in time series data mining in the last decade. While dozens of classification algorithms have been applied to time series, recent empirical evidence strongly suggests that simple nearest neighbor classification is exceptionally difficult to beat. The choice of distance measure used by the nearest neighbor algorithm is important, and depends on the invariances required by the domain. For example, motion capture data typically requires invariance to warping, and cardiology data requires invariance to the baseline (the mean value). Similarly, recent work suggests that for time series clustering, the choice of clustering algorithm is much less important than the choice of distance measure used.In this work we make a somewhat surprising claim. There is an invariance that the community seems to have missed, complexity invariance. Intuitively, the problem is that in many domains the different classes may have different complexities, and pairs of complex objects, even those which subjectively may seem very similar to the human eye, tend to be further apart under current distance measures than pairs of simple objects. This fact introduces errors in nearest neighbor classification, where some complex objects may be incorrectly assigned to a simpler class. Similarly, for clustering this effect can introduce errors by “suggesting” to the clustering algorithm that subjectively similar, but complex objects belong in a sparser and larger diameter cluster than is truly warranted.We introduce the first complexity-invariant distance measure for time series, and show that it generally produces significant improvements in classification and clustering accuracy. We further show that this improvement does not compromise efficiency, since we can lower bound the measure and use a modification of triangular inequality, thus making use of most existing indexing and data mining algorithms. We evaluate our ideas with the largest and most comprehensive set of time series mining experiments ever attempted in a single work, and show that complexity-invariant distance measures can produce improvements in classification and clustering in the vast majority of cases.

Effects of task modality, length and complexity on time for activities in lucid dreams

Introduction: Nocturnal dreams can be considered as a kind of simulation of the real world on a higher cognitive level (Erlacher & Schredl, 2008). Within lucid dreams, the dreamer is aware of the dream state and thus able to control the ongoing dream content. Previous studies could demonstrate that it is possible to practice motor tasks during lucid dreams and doing so improved performance while awake (Erlacher & Schredl, 2010). Even though lucid dream practice might be a promising kind of cognitive rehearsal in sports, little is known about the characteristics of actions in lucid dreams. The purpose of the present study was to explore the relationship between time in dreams and wakefulness because in an earlier study (Erlacher & Schredl, 2004) we found that performing squads took lucid dreamers 44.5 % more time than in the waking state while for counting the same participants showed no differences between dreaming and wakefulness. To find out if the task modality, the task length or the task complexity require longer times in lucid dreams than in wakefulness three experiments were conducted. Methods: In the first experiment five proficient lucid dreamers spent two to three non-consecutive nights in the sleep laboratory with polysomnographic recording to control for REM sleep and determine eye signals. Participants counted from 1-10, 1-20 and 1-30 in wakefulness and in their lucid dreams. While dreaming they marked onset of lucidity as well as beginning and end of the counting task with a Left-Right-Left-Right eye movement and reported their dreams after being awakened. The same procedure was used for the second experiment with seven lucid dreamers except that they had to walk 10, 20 or 30 steps. In the third experiment nine participants performed an exercise involving gymnastics elements such as various jumps and a roll. To control for length of the task the gymnastic exercise in the waking state lasted about the same time as walking 10 steps. Results: As a general result we found – as in the study before – that performing a task in the lucid dream requires more time than in wakefulness. This tendency was found for all three tasks. However, there was no difference for the task modality (counting vs. motor task). Also the relative time for the different lengths of the tasks showed no difference. And finally, the more complex motor task (gymnastic routine) did not require more time in lucid dreams than the simple motor task. Discussion/Conclusion: The results showed that there is a robust effect of time in lucid dreams compared to wakefulness. The three experiments could not explain that those differences are caused by task modality, task length or task complexity. Therefore further possible candidates needs to be investigated e.g. experience in lucid dreaming or psychological variables. References: Erlacher, D. & Schredl, M. (2010). Practicing a motor task in a lucid dream enhances subsequent performance: A pilot study. The Sport Psychologist, 24(2), 157-167. Erlacher, D. & Schredl, M. (2008). Do REM (lucid) dreamed and executed actions share the same neural substrate? International Journal of Dream Research, 1(1), 7-13. Erlacher, D. & Schredl, M. (2004). Time required for motor activity in lucid dreams. Perceptual and Motor Skills, 99, 1239-1242.

Time for actions in lucid dreams: effects of task modality, length, and complexity

The relationship between time in dreams and real time has intrigued scientists for centuries. The question if actions in dreams take the same time as in wakefulness can be tested by using lucid dreams where the dreamer is able to mark time intervals with prearranged eye movements that can be objectively identified in EOG recordings. Previous research showed an equivalence of time for counting in lucid dreams and in wakefulness (LaBerge, 1985; Erlacher and Schredl, 2004), but Erlacher and Schredl (2004) found that performing squats required about 40% more time in lucid dreams than in the waking state. To find out if the task modality, the task length, or the task complexity results in prolonged times in lucid dreams, an experiment with three different conditions was conducted. In the first condition, five proficient lucid dreamers spent one to three non-consecutive nights in the sleep laboratory. Participants counted to 10, 20, and 30 in wakefulness and in their lucid dreams. Lucidity and task intervals were time stamped with left-right-left-right eye movements. The same procedure was used for these condition where eight lucid dreamers had to walk 10, 20, or 30 steps. In the third condition, eight lucid dreamers performed a gymnastics routine, which in the waking state lasted the same time as walking 10 steps. Again, we found that performing a motor task in a lucid dream requires more time than in wakefulness. Longer durations in the dream state were present for all three tasks, but significant differences were found only for the tasks with motor activity (walking and gymnastics). However, no difference was found for relative times (no disproportional time effects) and a more complex motor task did not result in more prolonged times. Longer durations in lucid dreams might be related to the lack of muscular feedback or slower neural processing during REM sleep. Future studies should explore factors that might be associated with prolonged durations.

Inference of gene regulatory networks from time series by Tsallis entropy

Background: The inference of gene regulatory networks (GRNs) from large-scale expression profiles is one of the most challenging problems of Systems Biology nowadays. Many techniques and models have been proposed for this task. However, it is not generally possible to recover the original topology with great accuracy, mainly due to the short time series data in face of the high complexity of the networks and the intrinsic noise of the expression measurements. In order to improve the accuracy of GRNs inference methods based on entropy (mutual information), a new criterion function is here proposed. Results: In this paper we introduce the use of generalized entropy proposed by Tsallis, for the inference of GRNs from time series expression profiles. The inference process is based on a feature selection approach and the conditional entropy is applied as criterion function. In order to assess the proposed methodology, the algorithm is applied to recover the network topology from temporal expressions generated by an artificial gene network (AGN) model as well as from the DREAM challenge. The adopted AGN is based on theoretical models of complex networks and its gene transference function is obtained from random drawing on the set of possible Boolean functions, thus creating its dynamics. On the other hand, DREAM time series data presents variation of network size and its topologies are based on real networks. The dynamics are generated by continuous differential equations with noise and perturbation. By adopting both data sources, it is possible to estimate the average quality of the inference with respect to different network topologies, transfer functions and network sizes. Conclusions: A remarkable improvement of accuracy was observed in the experimental results by reducing the number of false connections in the inferred topology by the non-Shannon entropy. The obtained best free parameter of the Tsallis entropy was on average in the range 2.5 <= q <= 3.5 (hence, subextensive entropy), which opens new perspectives for GRNs inference methods based on information theory and for investigation of the nonextensivity of such networks. The inference algorithm and criterion function proposed here were implemented and included in the DimReduction software, which is freely available at http://sourceforge.net/projects/dimreduction and http://code.google.com/p/dimreduction/.

Complexity of human postural control in young and older adults during prolonged standing

Aging is known to have a degrading influence on many structures and functions of the human sensorimotor system. The present work assessed aging-related changes in postural sway using fractal and complexity measures of the center of pressure (COP) dynamics with the hypothesis that complexity and fractality decreases in the older individuals. Older subjects (68 +/- 4 years) and young adult subjects (28 +/- 7 years) performed a quiet stance task (60 s) and a prolonged standing task (30 min) where subjects were allowed to move freely. Long-range correlations (fractality) of the data were estimated by the detrended fluctuation analysis (DFA); changes in entropy were estimated by the multi-scale entropy (MSE) measure. The DFA results showed that the fractal dimension was lower for the older subjects in comparison to the young adults but the fractal dimensions of both groups were not different from a 1/f noise, for time intervals between 10 and 600 s. The MSE analysis performed with the typically applied adjustment to the criterion distance showed a higher degree of complexity in the older subjects, which is inconsistent with the hypothesis that complexity in the human physiological system decreases with aging. The same MSE analysis performed without adjustment showed no differences between the groups. Taken all results together, the decrease in total postural sway and long-range correlations in older individuals are signs of an adaptation process reflecting the diminishing ability to generate adequate responses on a longer time scale.

A matching pursuit-based signal complexity measure for the analysis of newborn EEG

This paper presents a new relative measure of signal complexity, referred to here as relative structural complexity, which is based on the matching pursuit (MP) decomposition. By relative, we refer to the fact that this new measure is highly dependent on the decomposition dictionary used by MP. The structural part of the definition points to the fact that this new measure is related to the structure, or composition, of the signal under analysis. After a formal definition, the proposed relative structural complexity measure is used in the analysis of newborn EEG. To do this, firstly, a time-frequency (TF) decomposition dictionary is specifically designed to compactly represent the newborn EEG seizure state using MP. We then show, through the analysis of synthetic and real newborn EEG data, that the relative structural complexity measure can indicate changes in EEG structure as it transitions between the two EEG states; namely seizure and background (non-seizure).

Task Complexity and Variation in L2 Learner’s Oral Discourse

There are many factors which affect the L2 learner’s performance at the levels of phonology, morphology and syntax. Consequently when L2 learners attempt to communicate in the target language, their language production will show systematic variability across the above mentioned linguistic domains. This variation can be attributed to some factors such as interlocutors, topic familiarity, prior knowledge, task condition, planning time and tasks types. This paper reports the results of an on going research investigating the issue of variability attributed to the task type. It is hypothesized that the particular type of task learners are required to perform will result in variation in their performance. Results of the statistical analyses of this study investigating the issue of variation in the performance of twenty L2 learners at the English department of Tabriz University provided evidence in support of the hypothesis that performance of L2 learners show systematic variability attributed to task.

Time flies with music whatever its emotional valence

The present study used a temporal bisection task to investigate whether music affects time estimation differently from a matched auditory neutral stimulus, and whether the emotional valence of the musical stimuli (i.e., sad vs. happy music) modulates this effect. The results showed that, compared to sine wave control music, music presented in a major (happy) or a minor (sad) key shifted the bisection function toward the right, thus increasing the bisection point value (point of subjective equality). This indicates that the duration of a melody is judged shorter than that of a non-melodic control stimulus, thus confirming that ""time flies"" when we listen to music. Nevertheless, sensitivity to time was similar for all the auditory stimuli. Furthermore, the temporal bisection functions did not differ as a function of musical mode. (C) 2010 Elsevier B.V. All rights reserved.

Tonal Modulation and Subjective Time

This work investigated listeners` sense of the temporal expression of tonal modulation. One experiment described the effects on retrospective reproductions of sudden and gradual modulations to close and distant keys. The results showed that modulations elicit time underestimations as an inverse function of interkey distances, with a major impact for sudden modulations. A proposed vectorial model - ""Expected Development Fraction"" (EDF) - describes the development of expectations when an interkey distance is traversed during a certain time interval. This expected development is longer than the perceived duration, leading to underestimation of the time.

Influence of third-generation oral contraceptives on the complexity analysis and symbolic dynamics of heart rate variability

Objective To evaluate the influence of oral contraceptives (OCs) containing 20 mu mu g ethinylestradiol (EE) and 150 mu mu g gestodene (GEST) on the autonomic modulation of heart rate (HR) in women. Methods One-hundred and fifty-five women aged 24 +/-+/- 2 years were divided into four groups according to their physical activity and the use or not of an OC: active-OC, active-non-OC (NOC), sedentary-OC, and sedentary-NOC. The heart rate was registered in real time based on the electrocardiogram signal for 15 minutes, in the supine-position. The heart rate variability (HRV) was analysed using Shannon`s entropy (SE), conditional entropy (complexity index [CInd] and normalised CInd [NCI]), and symbolic analysis (0V%, 1V%, 2LV%, and 2ULV%). For statistical analysis the Kruskal-Wallis test with Dunn post hoc and the Wilcoxon test (p < 0.05 was considered significant) were applied. Results Treatment with this COC caused no significant changes in SE, CInd, NCI, or symbolic analysis in either active or sedentary groups. Active groups presented higher values for SE and 2ULV%, and lower values for 0V% when compared to sedentary groups (p < 0.05). Conclusion HRV patterns differed depending on life style; the non-linear method applied was highly reliable for identifying these changes. The use of OCs containing 20 mu mu g EE and 150 mu mu g GEST does not influence HR autonomic modulation.

Materialized view selection under the maintenance time constraint

A data warehouse is a data repository which collects and maintains a large amount of data from multiple distributed, autonomous and possibly heterogeneous data sources. Often the data is stored in the form of materialized views in order to provide fast access to the integrated data. One of the most important decisions in designing a data warehouse is the selection of views for materialization. The objective is to select an appropriate set of views that minimizes the total query response time with the constraint that the total maintenance time for these materialized views is within a given bound. This view selection problem is totally different from the view selection problem under the disk space constraint. In this paper the view selection problem under the maintenance time constraint is investigated. Two efficient, heuristic algorithms for the problem are proposed. The key to devising the proposed algorithms is to define good heuristic functions and to reduce the problem to some well-solved optimization problems. As a result, an approximate solution of the known optimization problem will give a feasible solution of the original problem. (C) 2001 Elsevier Science B.V. All rights reserved.

Concepção e implementação do time-driven activity based costing numa PME industrial: evidência de um estudo empírico

Dissertação para obtenção do Grau de Mestre em Contabilidade e Finanças Orientador: Mestre Paulino Manuel Leite da Silva

Determination of pharmocotherapeutical complexity in institutionalized elderly

The phenomenon of aging is nowadays society as acquired the status of a social problem, with growing attention and concern, leading to an increase number of studies dedicated to the elderly. The lack of domestic, familiar or social support often lead elderly to nursing homes. Institutionalization is in many cases the only opportunity to have access to health care and life quality. Aging is also associated with a higher prevalence of chronic diseases that require long term medication sometimes for life. Frequently the onset of multiple pathologies at the same time require different therapies and the phenomenon of polypharmacy (five ou more drugs daily) can occur. Even more, the slow down of physiological and cognitives mechanisms associated with these chronic diseases can interphere, in one hand, with the pharmacocinetic of many medications and, on the other hand, with the facility to accomplish the therapeutical regimen. All of these realities contribute to an increase of pharmacotherapeutical complexity, decreasing the adherence and effectiveness of treatment. The pharmacotherapeutical complexity of an individual is characterized by the conciliator element of different characteristics of their drug therapy, such as: the number of medications used; dosage forms; dosing frequency and additional indications. It can be measured by the Medication Regimen Complexity Index (MRCI), originally validated in English.

A survey of techniques and technologies for web-based real-time interactive rendering

When exploring a virtual environment, realism depends mainly on two factors: realistic images and real-time feedback (motions, behaviour etc.). In this context, photo realism and physical validity of computer generated images required by emerging applications, such as advanced e-commerce, still impose major challenges in the area of rendering research whereas the complexity of lighting phenomena further requires powerful and predictable computing if time constraints must be attained. In this technical report we address the state-of-the-art on rendering, trying to put the focus on approaches, techniques and technologies that might enable real-time interactive web-based clientserver rendering systems. The focus is on the end-systems and not the networking technologies used to interconnect client(s) and server(s).