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Authors:MARCOS E. GAUDIANO, CARLOS M. LUCCA, JORGE A. REVELLI Abstract: Advances in Complex Systems, Volume 24, Issue 06, September 2021. In this work, we study the hierarchical properties observed in temporal patterns of public transport strike records of Córdoba city, Argentina. We show how a previously developed entropy-based methodology can be applied here to unveil different strike regimes, to which particular political uncontrollability degrees can be naturally associated. From data analysis, a successive increment in the uncontrollability of the public transport system can be quantitatively inferred. The proposed analysis turns out to be easily generalizable to other contexts, providing a theoretical framework for contrasting the intensity of the strikes, independently of its nature, city and/or historical time. Citation: Advances in Complex Systems PubDate: 2022-03-03T08:00:00Z DOI: 10.1142/S0219525922500023 Issue No:Vol. 24, No. 06 (2022)
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Authors:JUN SU, PENG ZHOU Abstract: Advances in Complex Systems, Volume 24, Issue 06, September 2021. Music listening is one of the most enigmatic of human mental phenomena; it not only triggers emotions but also changes our behavior. During the music session many people are observed to exhibit varying emotional response, which can be influenced by diverse factors such as music genre and instrument as well as the personal attributes of audiences. In this study, we assume that there is an intrinsic, complex and implicit relationship between the basic sound features of music and human emotional response to the music. The response levels of 12 individuals to a representative repertoire of 36 classical/popular Chinese traditional music (CTM) are systematically analyzed using the chills as a quantitative indicator, totally resulting in 432 ([math]) CTM–individual pairs that define a systematic individual-to-music response profile (SPTMRP). Gaussian process (GP) is then employed to model the multivariate correlation of SPTMRP profile with 15 sound features (including 5 Timbres, 4 Rhythms and 6 Pitchs) and 5 individual features in a supervised manner, which is also improved by genetic algorithm (GA) feature selection and compared with other machine learning methods. It is shown that the built GP regression model possesses a strong internal fitting ability ([math]) and a good external predictive power ([math]), which performed much better than linear PLS and nonlinear SVM and RF, confirming that the human emotional response to music can be quantitatively explained by GP methodology. Statistical examination of the GP model reveals that the sound features contribute more significantly to emotional response than individual features; their importance increases in the order: [math], in which the spectral centroid (SC), relative amplitude of salient peaks (RASP), ratio of peak amplitudes (RPA), sum of all rhythm histograms (SARH) and period of unfolded maximum peak (PUMP) as well as gender are primarily responsible for the response. Citation: Advances in Complex Systems PubDate: 2022-02-25T08:00:00Z DOI: 10.1142/S0219525922500011 Issue No:Vol. 24, No. 06 (2022)
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Authors:GUANG ZENG, JUN ZHANG, RUI YE, ANDREAS SCHADSCHNEIDER, SHUCHAO CAO, QIAO WANG, WEIGUO SONG Abstract: Advances in Complex Systems, Volume 24, Issue 06, September 2021. Large crowds are challenging the comfort and safety level of big cities, while music may be a potential method to improve pedestrian flow. This paper focuses on the influence of different tempos and types of background music on pedestrian dynamics. Three tempos (90[math]beats/min (BPM), 120[math]BPM and 150[math]BPM) and two types (pure music and metronome stimuli) of music are considered. It is found that more frequent stop-and-go behaviors emerge with rhythms. Compared with that under a low tempo (90[math]BPM) of rhythm condition, stopping is more frequent with a high tempo one (120[math]BPM or 150[math]BPM). The number of stopping pedestrians per unit time increases 68.57%, 376.00%, 298.29%, 224.00%, 438.29% and 393.71% with 90 BPM, 120[math]BPM and 150[math]BPM music, 90[math]BPM, 120[math]BPM and 150[math]BPM metronome, compared with that without any rhythm, respectively. The velocity and flow are lower, and higher local densities appear with background music. The step frequency at high density with rhythms ([math], [math] and [math][math]Hz for 90[math]BPM, 120[math]BPM and 150[math]BPM music; [math], [math] and [math][math]Hz for 90[math]BPM, 120[math]BPM and 150[math]BPM metronome) is lower than that without any rhythm ([math][math]Hz). Pedestrians need more time to avoid collisions and to step under background music conditions, because they are influenced by the music and not fully focusing on walking. As a result, step frequency decreases and stopping behavior is more frequent. This in turn leads to the decrease of the velocity and flow and the emergence of higher local densities. Our study will be helpful for understanding the effect of background music on pedestrian dynamics. Citation: Advances in Complex Systems PubDate: 2022-02-24T08:00:00Z DOI: 10.1142/S0219525921500119 Issue No:Vol. 24, No. 06 (2022)
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