Statistical Analysis of QKD Networks in Real-Life Environment

Author(s):  
K. Lessiak ◽  
J. Pilz
2020 ◽  
Vol 25 (4) ◽  
pp. 174-189 ◽  
Author(s):  
Guillaume  Palacios ◽  
Arnaud Noreña ◽  
Alain Londero

Introduction: Subjective tinnitus (ST) and hyperacusis (HA) are common auditory symptoms that may become incapacitating in a subgroup of patients who thereby seek medical advice. Both conditions can result from many different mechanisms, and as a consequence, patients may report a vast repertoire of associated symptoms and comorbidities that can reduce dramatically the quality of life and even lead to suicide attempts in the most severe cases. The present exploratory study is aimed at investigating patients’ symptoms and complaints using an in-depth statistical analysis of patients’ natural narratives in a real-life environment in which, thanks to the anonymization of contributions and the peer-to-peer interaction, it is supposed that the wording used is totally free of any self-limitation and self-censorship. Methods: We applied a purely statistical, non-supervised machine learning approach to the analysis of patients’ verbatim exchanged on an Internet forum. After automated data extraction, the dataset has been preprocessed in order to make it suitable for statistical analysis. We used a variant of the Latent Dirichlet Allocation (LDA) algorithm to reveal clusters of symptoms and complaints of HA patients (topics). The probability of distribution of words within a topic uniquely characterizes it. The convergence of the log-likelihood of the LDA-model has been reached after 2,000 iterations. Several statistical parameters have been tested for topic modeling and word relevance factor within each topic. Results: Despite a rather small dataset, this exploratory study demonstrates that patients’ free speeches available on the Internet constitute a valuable material for machine learning and statistical analysis aimed at categorizing ST/HA complaints. The LDA model with K = 15 topics seems to be the most relevant in terms of relative weights and correlations with the capability to individualizing subgroups of patients displaying specific characteristics. The study of the relevance factor may be useful to unveil weak but important signals that are present in patients’ narratives. Discussion/Conclusion: We claim that the LDA non-supervised approach would permit to gain knowledge on the patterns of ST- and HA-related complaints and on patients’ centered domains of interest. The merits and limitations of the LDA algorithms are compared with other natural language processing methods and with more conventional methods of qualitative analysis of patients’ output. Future directions and research topics emerging from this innovative algorithmic analysis are proposed.


2020 ◽  
Author(s):  
Kyoshiro Sasaki ◽  
Yuki Yamada

A Registered Reports system is key to preventing questionable research practices. Under this system, manuscripts, including their detailed protocols (i.e., hypothesis, experimental design, sample size, and methods of statistical analysis), are reviewed prior to data collection. If a protocol manuscript is accepted, publication of the full manuscript including the results and discussion is guaranteed in principle regardless of whether the collected data support the registered hypothesis. However, this assurance of publication might be broken under the impact of the COVID-19 pandemic. The present paper reports the first author’s real-life experience related to the collapse of the assurance of publication in the Registered Reports system and discusses the disbenefits of this collapse. Furthermore, we propose the implementation of a journal section specific to protocol manuscripts as a solution to the crisis of the Registered Reports system.


2021 ◽  
Vol 9 (4) ◽  
pp. 789-808
Author(s):  
Amal Helu ◽  
Hani Samawi

In this article, we consider statistical inferences about the unknown parameters of the Lomax distribution basedon the Adaptive Type-II Progressive Hybrid censoring scheme, this scheme can save both the total test time and the cost induced by the failure of the units and increases the efficiency of statistical analysis. The estimation of the parameters is derived using the maximum likelihood (MLE) and the Bayesian procedures. The Bayesian estimators are obtained based on the symmetric and asymmetric loss functions. There are no explicit forms for the Bayesian estimators, therefore, we propose Lindley’s approximation method to compute the Bayesian estimators. A comparison between these estimators is provided by using extensive simulation. A real-life data example is provided to illustrate our proposed estimators.


2021 ◽  
Vol 11 (19) ◽  
pp. 9158
Author(s):  
Lorenzo J. Tardón ◽  
Ignacio Rodríguez-Rodríguez ◽  
Niels T. Haumann ◽  
Elvira Brattico ◽  
Isabel Barbancho

Brain responses are often studied under strictly experimental conditions in which electroencephalograms (EEGs) are recorded to reflect reactions to short and repetitive stimuli. However, in real life, aural stimuli are continuously mixed and cannot be found isolated, such as when listening to music. In this audio context, the acoustic features in music related to brightness, loudness, noise, and spectral flux, among others, change continuously; thus, significant values of these features can occur nearly simultaneously. Such situations are expected to give rise to increased brain reaction with respect to a case in which they would appear in isolation. In order to assert this, EEG signals recorded while listening to a tango piece were considered. The focus was on the amplitude and time of the negative deflation (N100) and positive deflation (P200) after the stimuli, which was defined on the basis of the selected music feature saliences, in order to perform a statistical analysis intended to test the initial hypothesis. Differences in brain reactions can be identified depending on the concurrence (or not) of such significant values of different features, proving that coterminous increments in several qualities of music influence and modulate the strength of brain responses.


Author(s):  
Salem Alawbathani ◽  
Mehreen Batool ◽  
Jan Fleckhaus ◽  
Sarkawt Hamad ◽  
Floyd Hassenrück ◽  
...  

AbstractA poor understanding of statistical analysis has been proposed as a key reason for lack of replicability of many studies in experimental biomedicine. While several authors have demonstrated the fickleness of calculated p values based on simulations, we have experienced that such simulations are difficult to understand for many biomedical scientists and often do not lead to a sound understanding of the role of variability between random samples in statistical analysis. Therefore, we as trainees and trainers in a course of statistics for biomedical scientists have used real data from a large published study to develop a tool that allows scientists to directly experience the fickleness of p values. A tool based on a commonly used software package was developed that allows using random samples from real data. The tool is described and together with the underlying database is made available. The tool has been tested successfully in multiple other groups of biomedical scientists. It can also let trainees experience the impact of randomness, sample sizes and choice of specific statistical test on measured p values. We propose that live exercises based on real data will be more impactful in the training of biomedical scientists on statistical concepts.


Author(s):  
Omid Shojaee ◽  
Majid Asadi ◽  
Maxim Finkelstein

Most of the real-life populations are heterogeneous and homogeneity is often just a simplifying assumption for the relevant statistical analysis. Mixtures of lifetime distributions that correspond to homogeneous subpopulations were intensively studied in the literature. Various distributional and stochastic properties of finite and continuous mixtures were discussed. In this paper, following recent publications, we develop further a mixture concept in the form of the generalized α-mixtures that include all mixture models that are widely explored in the literature. We study some main stochastic properties of the suggested mixture model, that is, aging and appropriate stochastic comparisons. Some relevant examples and counterexamples are given to illustrate our findings.


Author(s):  
Katharina Lessiak ◽  
Christian Kollmitzer ◽  
Stefan Schauer ◽  
Jürgen Pilz ◽  
Stefan Rass

1974 ◽  
Vol 7 (3) ◽  
pp. 192-202 ◽  
Author(s):  
Karl Borch

This paper contains little which can be considered as new. It gives a survey of results which have been presented over the last 10-15 years. At one time these results seemed very promising, but in retrospect it is doubtful if they have fulfilled the expectations they raised. In this situation it may be useful to retrace one's steps and see if problems can be reformulated or if new approaches can be found.Mathematical models have been used in insurance for a long time. One of the first was the Gompertz mortality law; a more recent model, which has been intensively studied is the Compound Poisson Distribution in Lundberg's risk theory.When a model is introduced, one usually proceeds by stages. The first step is to see if the model appears acceptable on a priori reasons. If it does, the second step is to examine the implications of the model, to see if any of these are in obvious contradiction with observations. If the result of this examination is satisfactory, the third step is usually a statistical analysis to find out how well the model approximates the situation in real life, which one wants to analyse. If the model passes this second examination, the next and final step may be to estimate the parameters of the model, and use it in practice, i.e. to make decisions in the real world.The advantage of working with a model is that it gives an overall purpose to the collection and analysis of data. A good model should tell us which data we need, and why.


2009 ◽  
Vol 9 (4) ◽  
pp. 321-343 ◽  
Author(s):  
Zhigang Zhang

In statistical analysis, when the value of a random variable is only known to be between two bounds, we say that this random variable is interval censored. This complicated censoring pattern is a common problem in research fields such as clinical trials or actuarial studies and raises challenges for statistical analysis. In this paper, we focus on regression analysis of case 2 interval-censored data. We first briefly review existing regression methods and an estimation approach under the class of linear transformation models developed by Zhang et al. We then propose a method for survival probability prediction via generalized estimating equations. We also consider a graphical model checking technique and a model selection tool. Some theoretical properties are established and the performance of our procedures is evaluated and illustrated by numerical studies including a real-life data analysis.


2020 ◽  
Vol 172 ◽  
pp. 20009
Author(s):  
Spyridon Efthymiopoulos ◽  
Hector Altamirano ◽  
Valentina Marincioni

The application of insulation to solid walls is one of the measures to help reduce the energy consumption of a building. Where external wall insulation is not feasible (e.g. listed buildings), internal insulation may be the only option to improve the thermal property of external walls. However, such interventions may be followed by unintended consequences [1], such as moisture accumulation and the growth of mould [2]. The study aims to develop a method for the non-disruptive assessment of interstitial mould growth in internally insulated walls. Air sampling through impaction and culture-based analysis was used in the study. Mould species commonly found in buildings were cultivated and used in small-scale experiments, and the effects of several sampling periods and airflow rates assessed. Potential relationships between the sampling variables and the results were determined by means of statistical analysis - a strong correlation between the coverage of mould behind the wall and the sampling periods and airflow rates. The effect of the inertial impaction frequency on the sampling results and the feasibility and applicability of the suggested methodology in real-life scenarios are also discussed.


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