Change in the embedding dimension as an indicator of an approaching transition

Predicting a transition point in behavioral data should take into account the complexity of the signal being influenced by contextual factors. In this paper, we propose to analyze changes in the embedding dimension as contextual information indicating a proceeding transitive point, called OPtimal Embedding tRANsition Detection (OPERAND). Three texts were processed and translated to time-series of emotional polarity. It was found that changes in the embedding dimension proceeded transition points in the data. These preliminary results encourage further research into changes in the embedding dimension as generic markers of an approaching transition point

Recurrence networks - A novel paradigm for nonlinear time series analysis

This paper presents a new approach for analysing structural properties of time series from complex systems. Starting from the concept of recurrences in phase space, the recurrence matrix of a time series is interpreted as the adjacency matrix of an associated complex network which links different points in time if the evolution of the considered states is very similar. A critical comparison of these recurrence networks with similar existing techniques is presented, revealing strong conceptual benefits of the new approach which can be considered as a unifying framework for transforming time series into complex networks that also includes other methods as special cases. It is demonstrated that there are fundamental relationships between the topological properties of recurrence networks and the statistical properties of the phase space density of the underlying dynamical system. Hence, the network description yields new quantitative characteristics of the dynamical complexity of a time series, which substantially complement existing measures of recurrence quantification analysis

Power-laws in recurrence networks from dynamical systems

Recurrence networks are a novel tool of nonlinear time series analysis allowing the characterisation of higher-order geometric properties of complex dynamical systems based on recurrences in phase space, which are a fundamental concept in classical mechanics. In this Letter, we demonstrate that recurrence networks obtained from various deterministic model systems as well as experimental data naturally display power-law degree distributions with scaling exponents $\gamma$ that can be derived exclusively from the systems' invariant densities. For one-dimensional maps, we show analytically that $\gamma$ is not related to the fractal dimension. For continuous systems, we find two distinct types of behaviour: power-laws with an exponent $\gamma$ depending on a suitable notion of local dimension, and such with fixed $\gamma=1$.Comment: 6 pages, 7 figure

A BLUEPRINT FOR RESEARCH-LED TEACHING ENGINEERING AT SCHOOLS: A CASE STUDY FOR TAYLOR’S UNIVERSITY

Although it is expected that research conducted at universities and institutions of higher learning will have some positive impact on the teaching quality, the literature seem to point in another direction. Available literature reports zero correlation between teaching and research. However, this need not be the case and a number of recommendations to create a positive correlation between teaching and research are proposed. This paper outlines a framework that utilises the Grand Challenges for Engineering and CDIO to create a clear link between teaching and research in Taylor’s School of Engineering. Aligning the academic staff research objectives to the Grand Challenges, creates a sense of purpose that extends beyond the academic staff to their students. Ensuring that students’ projects and other CDIO activities are derived from the academic staff research interests help creates a learning environment in which research and teaching are integrated. This integration is highly desirable as it benefits both the students and the academic staff

Produksi dan Kualitas Benih Kedelai dalam Sistem Produksi Bersih

Production of high quality seed is one of the key factors for soybean self-sufficiency. The study was aimed to produce high quality soybean seed from zero waste system. The trial was carried out at Sebapo Experimental Station, Jambi, Center for Agricultural Post Harvest Research and Development, and Center for Agricultural Land Resources Research and Development, The Ministry of Agriculture, Bogor, from January until October 2017. The experiment used a complete randomized design with a treatments combination both organic nutrient of composted soybean litter (5 tons ha-1) and inorganic nutrient (25 kg Nitrogen ha-1, 50 kg P2O5 ha-1, and 50 kg K2O ha-1). The treatments were designed as follow : K0 (control), K1 (100% organic), K2 (75% organic + 25% inorganic), K3 (50% organic + 50% inorganic), K4 (25% organic + 75% inorganic), and K5 (100% inorganic). The results showed that the treatment K3 produced the highest seed production (1.72 tons ha-1) and the highest 1,000 seed weight (147.71 g). After 3 months storage at room temperature, the seed with treatment K3 could maintain its quality with indicator 1,000 seed weight (140.98 g), 10.82% water content, 34.98% protein content, 57.42 μScm-1g-1 electrical conductivity, 80.98% germination percentage and 27.48% etmal-1 rate of germination speed

Long-term changes in the north-south asymmetry of solar activity: A nonlinear dynamics characterization using visibility graphs

Solar activity is characterized by complex dynamics superimposed onto an almost periodic, approximately 11-year cycle. One of its main features is the presence of a marked, time-varying hemispheric asymmetry, the deeper reasons for which have not yet been completely uncovered. Traditionally, this asymmetry has been studied by considering amplitude and phase differences. Here, we use visibility graphs, a novel tool of nonlinear time series analysis, to obtain complementary information on hemispheric asymmetries in dynamical properties. Our analysis provides deep insights into the potential and limitations of this method, revealing a complex interplay between factors relating to statistical and dynamical properties, i.e., effects due to the probability distribution and the regularity of observed fluctuations. We demonstrate that temporal changes in the hemispheric predominance of the graph properties lag those directly associated with the total hemispheric sunspot areas. Our findings open a new dynamical perspective on studying the north-south sunspot asymmetry, which is to be further explored in future work

Long-term changes in the north–south asymmetry of solar activity : a nonlinear dynamics characterization using visibility graphs

Peer reviewedPublisher PD

The backbone of the climate network

We propose a method to reconstruct and analyze a complex network from data generated by a spatio-temporal dynamical system, relying on the nonlinear mutual information of time series analysis and betweenness centrality of complex network theory. We show, that this approach reveals a rich internal structure in complex climate networks constructed from reanalysis and model surface air temperature data. Our novel method uncovers peculiar wave-like structures of high energy flow, that we relate to global surface ocean currents. This points to a major role of the oceanic surface circulation in coupling and stabilizing the global temperature field in the long term mean (140 years for the model run and 60 years for reanalysis data). We find that these results cannot be obtained using classical linear methods of multivariate data analysis, and have ensured their robustness by intensive significance testing.Comment: 6 pages, 5 figure

Dynamic patterns of expertise: The case of orthopedic medical diagnosis

The aim of this study was to analyze dynamic patterns for scanning femoroacetabular impingement (FAI) radiographs in orthopedics, in order to better understand the nature of expertise in radiography. Seven orthopedics residents with at least two years of expertise and seven board-certified orthopedists participated in the study. The participants were asked to diagnose 15 anteroposterior (AP) pelvis radiographs of 15 surgical patients, diagnosed with FAI syndrome. Eye tracking data were recorded using the SMI desk-mounted tracker and were analyzed using advanced measures and methodologies, mainly recurrence quantification analysis. The expert orthopedists presented a less predictable pattern of scanning the radiographs although there was no difference between experts and non-experts in the deterministic nature of their scan path. In addition, the experts presented a higher percentage of correct areas of focus and more quickly made their first comparison between symmetric regions of the pelvis. We contribute to the understanding of experts' process of diagnosis by showing that experts are qualitatively different from residents in their scanning patterns. The dynamic pattern of scanning that characterizes the experts was found to have a more complex and less predictable signature, meaning that experts' scanning is simultaneously both structured (i.e. deterministic) and unpredictable