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The North Sea Bicycle Race ECG project : time-domain analysis

Długosz D., Eftestøl T., Królak A., Wiktorski T., Ørn S.

Journal of Automation Mobile Robotics and Intelligent Systems

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2018

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Vol. 12, No. 1

23--32

EN

Analysis of electrocardiogram and heart rate provides useful information about health condition of a patient. The North Sea Bicycle Race is an annual cycling competition in Norway. Examination of ECG recordings collected from participants of this race may allow defining and evaluating the relationship between physical endurance exercises and heart electrophysiology. Parameters reflecting potentially alarming deviations are to be identified in this study. This paper presents results of a time-domain analysis of ECG data collected in 2014, implementing K-Means clustering. A double stage analysis strategy, aimed at producing hierarchical clusters, is proposed. The first phase allows rough separation of data. Second stage is applied to reveal internal structure of the majority clusters. In both steps, discrepancies driving the separation could stem from three sources. Firstly, they could be signs of abnormalities in electrical activity of the heart. Secondly, they may allow discriminating between natural groups of participants – according to sex, age, physical fitness. Finally, some deviations could result from faults in data extraction, therefore serving in evaluation of the parameters. The clusters were defined predominantly by combinations of features: heartbeat signals correlation, P-wave shape, and RR intervals; none of the features alone was discriminative for all the clusters.

2

Challenges in causal inference from Personal Monitoring Devices

Wiktorski T.

Annals of Computer Science and Information Systems

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2018

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Vol. 16

99--102

EN

Personal Monitoring Devices (PMDs) collect im- mense amount of data about health and wellness of hundreds of millions of people. One of the obstacles of the prevailing data analytics approaches to PMDs' data is limited value of correlation-based conclusions in a health context. Causal inference seems a natural solution, but general causal inference methodologies are difficult to apply to PMDs data due to size and complexity of observational data. Some methods, such as randomized trials, are largely infeasible in PMDs' context due to lack of control over the investigated population. In this paper, we overview existing approaches to causal inference including recent works that attempt to take advantage of time series data to automatically derive causality using extended difference- in-deference or Granger methods. We then outline challenges and opportunities for causal inference in the health context. Finally, we propose a following challenge: can we establish a new standard of evidence and a study design process that: (1) allows for drawing causal conclusions from large observational datasets and (2) can suggest interventions to enforce causal links discovered in the data.

3

Wpływ substancji mineralnej na proces pirolizy węgla koksującego

Świetlik U., Wiktorski T.

Karbo

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2006

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Nr 1

13-18

PL

Zbadano wpływ substancji mineralnej zawartej w węglu koksującym (Ad 17 %) na proces karbonizacji i właściwości otrzymanego koksu, stosując odmineralizowanie węgla kwasami mineralnymi w następującej kolejności: 5 % HCl, 40 % HF, 35 % HCl. Pod wpływem kwasów z węgla zostaje usunięta większość substancji mineralnej – do zawartości popiołu w węglu Ad 0,4 % po końcowym etapie demineralizacji. Największy stopień demineralizacji węgla uzyskano stosując 40 % HF, który rozkłada prawie wszystkie związki Al, Si, K, stanowiące znaczną część substancji mineralnej. Działanie kwasów powoduje również zmiany w substancji organicznej węgla zmieniając jego właściwości, takie jak: zawartość części lotnych, skład elementarny, ciepło spalania, właściwości koksownicze. W istotny sposób wpływa więc na przebieg procesu karbonizacji poprzez obniżenie właściwości plastycznych węgla i inny przebieg reakcji zachodzących w stanie plastycznym, co prowadzi do otrzymania koksu o gorszych parametrach użytkowych.

EN

The influence of coking coal mineral matter content ( Ad – 17 % ) on carbonization process and properties of the resultant coke after coal demineralization by mineral acids: 5 % HCl, 40 % HF, 35 % HCl was investigated. The activity of acids has removed the most of mineral matter from coal – up to the ash content Ad - 0,4 % after the final demineralization. The highest degree of mineral matter removing occured when 40 % HF was used. This acid can dissolve the most of compounds Al, Si, K which present majority of the mineral matter of coal. The acids influence on the organic matter of coal too, changing the properties of coal such as: volatile matter content, elemental composition, calorific value, coking properties. Therefore, the acids have an impact an the behaviour of coal during carbonization process; a decrease of coal plasticity is observed, resulting in coke showing worse properties.