On the early detecting of the COVID-19 outbreak

Introduction: This paper aims to measure the performance of early detection methods, which are usually used for infectious diseases. Methodology: By using real data of confirmed Coronavirus cases from the Kingdom of Saudi Arabia and Italy, the moving epidemic method (MEM) and the moving average cumulative sums (Mov. Avg Cusum) methods are used in our simulation study. Results: Our results suggested that the CUSUM method outperforms the MEM in detecting the start of the Coronavirus outbreak.

Modelling of a Stochastic Spatiotemporal Variable in Transport Domain

In this article, building on our previous work, we engage in spatiotemporal modelling of transport demand in the Montreal metropolitan area over the period of six years. We employ classical machine learning and regression models, which predict bike-sharing demand in the form of daily cumulative sums of bike trips for each considered docking station. Hourly estimates of demand are then determined by considering the statistical distribution of demand across individual hours of an average day. In order to capture seasonal and other regular variation of demand, longer-term distribution characteristics of bike trips, such as their average number falling on each day of the week, month of the year, etc., were also used as input attributes. We initially conjectured that weather would be an important source of irregular variation in bike-sharing demand, and subsequently included several available meteorological variables in our models. We validated our models by Hold-Out and 10-Fold Cross-Validation, with encouraging results.

Laser Doppler Spectrum Analysis Based on Calculation of Cumulative Sums Detects Changes in Skin Capillary Blood Flow in Type 2 Diabetes Mellitus

In this article, we introduce a new method of signal processing and data analysis for the digital laser Doppler flowmetry. Our approach is based on the calculation of cumulative sums over the registered Doppler power spectra. The introduced new parameter represents an integral estimation for the redistribution of moving red blood cells over the range of speed. The prototype of the device implementing the technique is developed and tested in preliminary clinical trials. The methodology was verified with the involvement of two age groups of healthy volunteers and in a group of patients with type 2 diabetes mellitus. The main practical result of the study is the development of a set of binary linear classifiers that allow the method to identify typical patterns of the microcirculation for the healthy volunteers and diabetic patients based on the presented diagnostic algorithm.

On the number of principal ideals in d-tonal partition monoids

For a positive integer d, a non-negative integer n and a non-negative integer $$h\le n$$ h ≤ n , we study the number $$C_{n}^{(d)}$$ C n ( d ) of principal ideals; and the number $$C_{n,h}^{(d)}$$ C n , h ( d ) of principal ideals generated by an element of rank h, in the d-tonal partition monoid on n elements. We compute closed forms for the first family, as partial cumulative sums of known sequences. The second gives an infinite family of new integral sequences. We discuss their connections to certain integral lattices as well as to combinatorics of partitions.

Intelligent signal detectors with random moment of appearance in rail lines monitoring systems

The article discusses the issues of building intelligent receivers of pulsed signals with an unknown arrival time without restrictions on the value of the signal-to-noise ratio under the influence of a complex of interfering factors. Using recurrent methods for detecting disturbances of random processes and an algorithm of cumulative sums, the problem of synthesizing algorithms for detecting Markov signals with random moments of appearance against the background of various combinations of destabilizing factors acting in control systems for the states of rail lines in normal and shunt operating modes is solved. To assess the efficiency of detecting a random signal by the method of cumulative sums, statistical modeling of the specified algorithm was carried out.

Предельные совместные распределения статистик трех критериев пакета NIST

Найдены совместное распределение и предельное совместное распределение статистик следующих критериев пакета NIST: «Monobit Test», «Frequency Test within a Block» и «Cumulative Sums Test» в случае, когда исследуемая последовательность имеет распределение Бернулли. В случае, когда в критерии «Frequency Test within a Block» используются два блока, найдены попарные ковариации данных статистик.

RECENT EVOLUTION OF WATER RESOURCES IN THE SASSANDRA CATCHMENT AREA (COTE DIVOIRE) IN A CONTEXT OF CLIMATE VARIABILITY AND CHANGE

The objective of this study is to assess the impacts of climate change on the surface water resources of the Sassandra catchment area. This study conducted at the scale of the Sassandra sub-catchment areas took into account six (6) sub-catchment areas: Bafing in Badala, Boa in Vialadougou, Davo in Dakpadou, Lobo in Nibehibe, Nzo in Kahin and Sassandra in Semien. The methodological approach is based on the evaluation of the drying up coefficients, the duration of drying up and the volumes of water mobilized by the aquifers. All these parameters were estimated using Maillets law. The analysis of the different dynamics was carried out using the cumulative sums test. The results showed that the breaks in rainfall and the drying up coefficient were between 1982 and 2000, 1985 and 2003 respectively. After these breaks, the drying up coefficients increased (Bafing in Badala, Boa in Vialadougou and Davo in Dakpadou) from 17 to 25.9% and decreased (Lobo in Nibehibe and Nzo in Kahin) from 1.4 to 6.3%. A shortening of 3 to 5 days was observed on the Bafing in Badala, the Boa in Vialadougou and the Davo in Dakpadou. The volumes of water mobilized by the aquifers decreased on the Bafing in Badala, the Davo in Dakpadou and the Sassandra in Semien.While they increased on the Boa in Vialadougou, the Lobo in Nibehibe and the Nzo in Kahin.