Transform techniques and non-stationarity with an emphasis on network applications

The recent years brought a phenomenal development of Internet. It is, therefore, important to find some ways to improve the performances. The first step in this direction is the characterization and modeling of the network traffic. It has been tested that the network traffic behaves like a self-similar process, while packets interarrivals time possess the long-range dependence property. In particular, we model them by using fractional Brownian motion and fractional Gaussian noise, respectively. Note that, the former is just the cumulative sum of the latter. By using these concepts, the traffic characterization reduces to the estimation of one value: the Hurst parameter. Numerous methods exist to evaluate this parameter. Nevertheless, a few studies take account of the inherent non-stationarity present in real data. For short samples, the stationarity hypothesis might hold. But for larger samples, this is hardly the case. As an example, for network traffic, the day cycle shows non-stationarity. By not considering the non-stationarity, an inaccurate or even inappropriate estimation may result. Our objective in this thesis is to test the robustness of several techniques such as aggregated variance method, rescaled range method, and wavelets method, in presence of a set of non-stationarity trends. We study the estimators on a known signal generated using Hosking, Davies and Harte method, or wavelets-based synthesis. We add various deterministic non-stationarity trends to the original signal. We considered polynomial, power-law, sinusoidal, and level-shift trends. Results help analyze the behavior of the estimators. All the simulations are carried out using Matlab. We show that, depending on the trend, the estimators react differently. We have also used real data to verify the effectiveness of estimators. Results confirm the observations that we have made with lab data. In particular, we show that the wavelets method provides several flaws. Especially, its results must be carefully analyzed when the data is non-stationary

A Domain-Knowledge Modeling of Hospital-Acquired Infection Risk in Healthcare Personnel From Retrospective Observational Data: A Case Study for Covid-19

Healthcare personnel (HCP) is facing a consistent risk of viral infections. We proposed a domain-knowledge-driven infection risk model to quantify the individual HCP and the population-level risks. For individual-level risk estimation, a time-variant model was proposed to capture the disease transmission dynamics. At the population-level, the infection risk was estimated using a Bayesian network model constructed from three feature sets. For model validation, we investigated the case study of the Coronavirus disease. The variance-based sensitivity analysis indicated that the uncertainty in the estimated risk was attributed to two variables: the number of close contacts and the viral transmission probability. We further validated the individual risk model by considering six occupations in the U.S. O*Net database. For the population-level risk model validation, the infection risk in Texas and California was estimated. The accurate estimation of infection risk will significantly enhance the PPE allocation, safety plans for HCP, and hospital staffing strategies

A Clinical Study of the Rate of Episiotomy and Perineal Outcomes after Delivery

Episiotomy is widely performed as a ‘routine’ procedure during childbirth. The potential benefits for the use of the episiotomy include the prevention of severe perineal lacerations and pelvic floor relaxation. Evidently, episiotomy procedure may increase the likelihood of severe perineal pain, healing outcomes, and third or fourth degree tears.  In spite of all these factors this procedure still remains a clinical practice and as part of normal delivery. The aim of this study was to investigate the rate of episiotomy and perineal outcomes after normal delivery. This cross-sectional study was conducted using a self-administered survey and chart review in two government hospitals located in Bangkok, Thailand. Anonymous patient’s data of 400 women was analyzed using descriptive statistics. The results revealed 80% of women received episiotomy. 2.2% of women who had episiotomy experienced a severe perineal laceration, compared to those who delivered without episiotomy. Perineal pain appears to be highest (90.94%) in women who had episiotomy than those who had spontaneous delivery without episiotomy (70%). Therefore, restrictive use of this procedure should be recommended to reduce complications and increase comfort for women after delivery

Managing Employee Resistance to Process Innovation Case: The Textile and Garment industry in Vietnam

This research deepens and expands the study of different antecedents leading to the re-sistance to process innovation within the firms. It concentrates on analysing the correlations between four independent variables: employee’s commitments, strength toward the existing habits, self-esteem, knowledge management and three dimensions of resistance of employ-ees in response to the proposed innovations: cognition, emotion and behaviour. The empiri-cal study was conducted in the context of the Textile and Garment industry in Vietnam by utilizing a sample of 96 employees working in the enterprises undergoing the changes in manufacturing process. The outcomes of the study confirmed the influence of loyalty to the organization (a construct of employee’s commitment), strength toward the existing habits and self-esteem on three dimensions of resistance to innovation. In terms of knowledge management, only the organizational memory construct affects to the opposed thought, emo-tion and behaviour of employees while the knowledge acquisition element only impacts on the behavioural perspective of the resistance to innovation. Likewise, essential practical implications are offered for the company’s board of management when they deploy changes in business processes

Solvable Polynomials over the Gaussian Field Q(i)

In this paper, we describe a congruence property of solvable polynomials with coefficients in the Gaussian field Q(i).Comment: 11 pages (new version corrects some typos). arXiv admin note: text overlap with arXiv:2107.0127

Anisotropic Quadratic Forms and Inversive Geometry

We develop an inversive geometry for anisotropic quadradic spaces, in analogy with the classical inversive geometry of a Euclidean plane.Comment: 24 pages. Revised December 2019 for clarit